{"gname":"Academia Sinica","grp_id":"38","rels":[{"rel_title":"Learning the electronic health record at the minute-scale","rel_doi":"10.64898\/2026.10.04.26364562","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364562","rel_abs":"Electronic health record foundation models are traditionally trained on the scale of years, days, or hours. These timescales, however, lack the minute-scale resolution required to directly guide clinical decisions at the bedside. We introduced minute-scale learning, a new paradigm for training and evaluating models, and developed MINT, a minute-scale foundation model for pediatric emergencies. MINT was pretrained and validated on 766,733 pediatric emergency department visits at five health systems, comprising 16 years of data from 10 hospitals. On minute-scale forecasting tasks, MINT outperformed and generalized to external health systems better than task-specific models (superior in 21 of 25 comparisons). MINT outperformed physicians in forecasting escalations of respiratory support. MINT demonstrated uniquely minute-scale capabilities including department-scale monitoring, dynamic risk explanations, individualized physiologic response forecasts, and hypothesis generation. Learning at the minute-scale improves performance, strengthens generalizability, and provides insights, actionability, and scientific capabilities that are not accessible at other timescales.","rel_num_authors":12,"rel_authors":[{"author_name":"Kush Narang","author_inst":"Stanford University"},{"author_name":"Newton Addo","author_inst":"University of California, San Francisco"},{"author_name":"Jaskaran Bains","author_inst":"University of California, San Francisco"},{"author_name":"Maytal Firnberg","author_inst":"University of California, San Francisco"},{"author_name":"Sonny Tat","author_inst":"University of California, San Francisco"},{"author_name":"Anneka Hooft","author_inst":"University of California, San Francisco"},{"author_name":"Daniela Chanci Arrubla","author_inst":"Duke University"},{"author_name":"Baraa Abed","author_inst":"Duke University"},{"author_name":"Chandan Singh","author_inst":"Microsoft Research"},{"author_name":"Rishikesan Kamaleswaran","author_inst":"Duke University"},{"author_name":"Jean Feng","author_inst":"University of California, San Francisco"},{"author_name":"Aaron E Kornblith","author_inst":"University of California San Francisco"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Memory and executive functioning show differential associations with scam susceptibility in middle to older adulthood","rel_doi":"10.64898\/2026.10.04.26364617","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364617","rel_abs":"Objectives: The rising prevalence of financial exploitation among older adults has prompted research on the cognitive mechanisms underlying financial decision making in later life. Prior work has demonstrated a link between cognitive impairment and financial vulnerability. The present study examined the unique contributions of composite measures of memory and executive functioning to scam susceptibility in middle-aged to older adults without dementia. Methods: One hundred and fifty-one participants (age= 68.2 {+\/-} 8.0 years, 72.2% female, years of education= 16.4 {+\/-} 2.2) completed standard neuropsychological measures from the Uniform Data Set (UDS), Version 3, and the California Verbal Learning Test, Second Edition, and a self-report scam susceptibility measure. Psychometrically robust composite scores, the UDS-M+ and UDS3-EF, were computed to represent memory and executive functioning domains. Linear regression models examined independent associations between UDS-M+ and UDS3-EF performance and scam susceptibility. Nested model comparisons evaluated unique contributions of the UDS-M+ and UDS3-EF when included in a joint model. Results: Lower UDS-M+ (b= -0.25, 95% CI [-0.45, -0.04], p= .018) and lower UDS3-EF (b= -0.33, 95% CI [-0.54, -0.12], p= .002) scores were independently associated with greater scam susceptibility after adjusting for age, sex, years of education, and income. However, only UDS3-EF remained significant in a joint model. Post hoc analyses revealed that only memory was associated with scam susceptibility in middle-aged adults whereas only executive functioning was significant in older adults. Conclusions: These findings highlight the importance of monitoring memory and executive functioning across middle to older adulthood when considering susceptibility to scams.","rel_num_authors":12,"rel_authors":[{"author_name":"Cassidy P. Molinare","author_inst":"University of Southern California"},{"author_name":"Belinda Y. Zhang","author_inst":"University of Southern California"},{"author_name":"Mark Sanderson-Cimino","author_inst":"UC San Francisco Memory and Aging Center"},{"author_name":"Melanie Leguizamon","author_inst":"University of Southern California"},{"author_name":"Emma Oyen","author_inst":"University of Southern California"},{"author_name":"Daisy T. Noriega-Makarskyy","author_inst":"University of Southern California"},{"author_name":"Jenna Axelrod","author_inst":"University of Southern California"},{"author_name":"Aaron C Lim","author_inst":"University of Southern California"},{"author_name":"Camdyn Wu","author_inst":"University of Southern California"},{"author_name":"Maanya Agarwal","author_inst":"University of Southern California"},{"author_name":"Laura Mosqueda","author_inst":"University of Southern California"},{"author_name":"S. Duke Han","author_inst":"University of Southern California"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Dietary sodium intake and kidney tubular protein abundance in urinary extracellular vesicles","rel_doi":"10.64898\/2026.10.04.26364680","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364680","rel_abs":"Background: Dietary sodium intake is a modifiable determinant of blood pressure, and impaired renal sodium handling is implicated in the pathogenesis of hypertension. Whether dietary sodium intake modulates renal tubular sodium transporter abundance among normotensive adults at risk for hypertension is unknown. Methods: Forty-six normotensive adults with normal kidney function at risk of developing hypertension were prospectively enrolled to complete a very low sodium (LS) diet followed by a high sodium (HS) diet. Urinary extracellular vesicle (uEV) proteins were quantified from a 24-hour urine collection at the end of each diet. We compared normalized uEV protein concentrations between diets and tested whether diet modified uEV protein associations with serum aldosterone, urinary aldosterone, and serum cortisol-cortisone ratio under either diet using Wilcoxon rank sums and linear mixed effects models, respectively. Results: Participants achieved median [IQR] urine sodium 13.2 [7.7-19.9] mEq\/24h on the LS diet and 244.0 [197.1-297.0] mEq\/24h on the HS diet. LS intake induced greater renin activity, greater plasma and urinary aldosterone, and lower urinary cortisol, when compared to HS intake. In parallel, NCC, ENaC, SGLT2, OXSR1, and Pendrin uEV concentrations were significantly higher during LS intake than HS intake (p<0.05 for all), whereas TRPV5 and AQP2 uEV concentrations were lower during LS intake than HS intake (p<0.001 for both). Conclusions: Controlled dietary sodium modulation induced nephron-segment specific changes in uEV protein abundance. These findings demonstrate the ability of uEVs to serve as a non-invasive tool to probe in vivo renal sodium, water, and electrolyte handling.","rel_num_authors":13,"rel_authors":[{"author_name":"Sophie E Claudel","author_inst":"Boston Medical Center"},{"author_name":"Sanan Mahrokhian","author_inst":"Brigham and Women's Hospital, Harvard Medical School"},{"author_name":"Isabelle Hanna","author_inst":"Brigham and Women's Hospital, Harvard Medical School"},{"author_name":"Andrew J Newman","author_inst":"Brigham and Women's Hospital, Harvard Medical School"},{"author_name":"Jenifer Brown","author_inst":"Brigham and Women's Hospital"},{"author_name":"Ashish Verma","author_inst":"Boston University School of Medicine, Boston, MA"},{"author_name":"Sushrut Waikar","author_inst":"Boston Medical Center"},{"author_name":"Richard J. Auchus","author_inst":"University of Michigan"},{"author_name":"Hayes McDonald","author_inst":"Vanderbilt University"},{"author_name":"Kevin Schey","author_inst":"Vanderbilt University"},{"author_name":"Dungeng Peng","author_inst":"Vanderbilt University"},{"author_name":"James M Luther","author_inst":"Vanderbilt University"},{"author_name":"Anand Vaidya","author_inst":"Brigham and Women's Hospital, Harvard Medical School"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"A Modular Architecture for Dynamic Evaluation of Best-Practice Care","rel_doi":"10.64898\/2026.10.03.26364324","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.03.26364324","rel_abs":"Objective: Retrospective evaluation of clinical pathway adherence using electronic medical record (eMR) data is limited by heterogeneous data structures and statistical measures that do not account for patient-specific context, care sequence, or timing. We designed a modular event-based architecture to dynamically evaluate the New South Wales Adult Sepsis Pathway over time. Method: Data from eMRs were collected from adult emergency department encounters across four hospitals between July 2022 and June 2024 and processed through three sequential layers: event-stream transformation, pathway-relevance filtering, and state-based pathway evaluation. Heterogeneous records were standardized and organized into a chronological timeline for each encounter. The framework then updated the pathway state as new clinical information became available and assessed whether recommended care was delivered within the relevant timeframe and sequence. Result: The architecture processed 451,124 encounters. This included 57,631,084 clinical events extracted and transformed into encounter-level event streams. After filtering for pathway relevance, 43,951,146 events remained (76.3%). A total of 129,907 (34.6%) encounters entered the sepsis pathway, 50,118 (38.6%) entered YELLOW state, indicating progression to suspected sepsis, and 3,349 (2.6%) encounters progressed to RED state from GREEN, indicating the initial shock. Of 50,118 encounters entering YELLOW state, 2,426 (4.8%) progressed to shock, 8,700 (17.4%) encounters were recognized with sepsis through a blood culture order, and 4,287 (8.6%) encounters were recognized with sepsis through an antibiotic order. This demonstrates the ability of the architecture to prioritize higher-acuity states during evaluation rather than going through an intermediate state. Conclusion: The architecture developed shows the feasibility of transforming fragmented routine eMR data into a reusable longitudinal representation that supports context-dependent pathway evaluation. Separating data preparation from pathway rules improves transparency, maintainability, and adaptability and provides a foundation for future interoperable, near-real-time pathway monitoring","rel_num_authors":6,"rel_authors":[{"author_name":"Minh Trang Hoang","author_inst":"Faculty of Medicine and Health, The Univeristy of Sydney"},{"author_name":"Tim Shaw","author_inst":"Faculty of Medicine and Health, The Univeristy of Sydney"},{"author_name":"Christina Igasto","author_inst":"Digital Canberra"},{"author_name":"Candice Donnelly","author_inst":"Faculty of Medicine and Health, The Univeristy of Sydney"},{"author_name":"Amith Shetty","author_inst":"NSW Ministry of Heatlh"},{"author_name":"Malcolm Pradhan","author_inst":"Faculty of Medicine and Health, The Univeristy of Sydney"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Identifying Message \"Recipes\" for High Perceived Effectiveness: Cognitive, Social, and Emotional Profiles of Vaping Public Education Messages Among Young Adults Who Vape","rel_doi":"10.64898\/2026.10.04.26364669","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364669","rel_abs":"Introduction: Vaping public education campaigns are a central prevention strategy for young adults (YAs), but message effectiveness varies widely and formative testing typically evaluates one message attribute at a time. This study examined how four perceptual dimensions, including cognitive engagement, social relevance, emotional arousal, and emotional valence, relate to perceived message effectiveness (PME), and whether multiple combinations of these dimensions correspond to similarly high PME. Methods: In a cross-sectional online message-testing study conducted from March to April 2025, 540 U.S. YAs who vape each evaluated 15 messages randomly sampled from a corpus of 229 text-image vaping public education messages, yielding 8,100 message evaluations. Cross-classified multilevel models estimated associations between each perceptual dimension and PME. An Explainable Boosting Machine probed nonlinear associations, and k-means clustering of high-predicted-PME perceptual configurations identified distinct profiles. Analyses were conducted in 2026. Results: Cognitive engagement (b = 0.20, 95% CI [0.18, 0.22]) and social relevance (b = 0.15, 95% CI [0.13, 0.17]) showed the strongest associations with PME, followed by emotional arousal (b = 0.06, 95% CI [0.04, 0.08]); emotional valence showed no linear association (b = 0.00, 95% CI [-0.02, 0.02]). The Explainable Boosting Machine revealed a U-shaped valence pattern, with higher predicted PME at both the negative and positive ends of the scale. Clustering yielded five distinct perceptual profiles with similarly high predicted PME (4.10-4.25). Conclusions: Multiple perceptual configurations correspond to similarly high PME, supporting a configurational approach to formative message testing rather than a single optimal message formula.","rel_num_authors":9,"rel_authors":[{"author_name":"Jiaying Liu","author_inst":"University of California, Santa Barbara"},{"author_name":"Qiyao Peng","author_inst":"University of California, Santa Barbara"},{"author_name":"Musa Malik","author_inst":"University of Oklahoma"},{"author_name":"Yidi Wang","author_inst":"University of California, San Diego"},{"author_name":"Emily Norton","author_inst":"University of Georgia"},{"author_name":"Tianlai Ye","author_inst":"University of California, Santa Barbara"},{"author_name":"Colleen Markey","author_inst":"University of Georgia"},{"author_name":"Allison Worsdale","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Lawrence H. Sweet","author_inst":"University of Georgia"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Rural-urban differences in gut microbiome among Vietnamese women","rel_doi":"10.64898\/2026.10.04.26364707","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364707","rel_abs":"Gut microbiome plays an important role in human health. Urbanization has been suggested to alter the gut microbiome. We comprehensively evaluated differences in gut microbiome profiles of 76 urban and 81 rural female residents of Vietnam using shotgun metagenomic data. We evaluated rural-urban differences in gut microbial diversity, individual microbial taxa, and metabolic pathways. Rural residents had higher alpha and beta diversities in age-adjusted models (p<0.05). Additionally, significant rural-urban differences were observed for 35 microbial taxa in age-adjusted models (FDR<0.1). Rural residents had higher relative abundance of classes, orders, and families of FGB2982 and FGB38642 and strain SGB15332 of the species Faecalibacterium prausnitzii, whereas urban residents had higher relative abundances of species Bacteroides thetaiotaomicron, Coprobacter fastidiosus, Bilophila wadsworthia, Enterobacter cloacae, Enterobacter hormaechei, Klebsiella aerogenes, Dielma fastidiosa, and Holdemania massiliensis. Notably, these associations were attenuated after further adjustment for socioeconomic characteristics, lifestyle, dietary factors, and comorbidity (FDR>0.1). In the fully adjusted model, significant rural-urban differences were observed in the abundance of 17 microbial taxa, including Ruminococcus sp AF13 28 and Prevotella pectinovora, as well as in three metabolic pathways (FDR<0.1). This study suggests that urbanization-related factors may contribute to differences in the gut microbiome between urban and rural Vietnamese women.","rel_num_authors":6,"rel_authors":[{"author_name":"Justin Y Guo","author_inst":"Montgomery Bell Academy"},{"author_name":"Huong T.T. Tran","author_inst":"Vietnam National Cancer Institute, National Cancer Hospital, Hanoi, Vietnam"},{"author_name":"Qiuyin Y Cai","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Minh  Van Hoang","author_inst":"Hanoi University of Public Health"},{"author_name":"Xiao-ou Shu","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Sang Minh Nguyen","author_inst":"Vanderbilt University Medical Center"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Post-Initiation Care Patterns and Weight Loss With Semaglutide and Tirzepatide for Obesity in Clinical Practice","rel_doi":"10.64898\/2026.10.04.26364715","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364715","rel_abs":"Abstract Background: Randomized trials show substantial weight loss with semaglutide and tirzepatide under structured care, but little is known about whether patients in routine practice continue therapy, reach a maintenance dose, and have their weight measured. Objectives: To describe the first year after initiation of semaglutide or tirzepatide for obesity, including care patterns, maintenance-dose attainment, weight documentation, and total body weight loss (TBWL). Methods: This retrospective cohort study used Epic Cosmos, an electronic health record network of >350 US health systems, to identify adults with obesity and without diabetes who initiated injectable semaglutide or tirzepatide in 2024. Outcomes over 12 months included prescribing persistence, discontinuation, switching, add-on therapy, and reinitiation; attainment of Food and Drug Administration (FDA)-labeled maintenance doses; availability of follow-up weight; and TBWL across progressively restricted populations. Results: Among 743,153 adults (60.1% semaglutide; mean age, 48.5 years; 72.5% female), 12-month prescribing persistence was 29.9% for semaglutide and 35.9% for tirzepatide. FDA-labeled maintenance-dose attainment was 28.3% and 55.0%, respectively, and only 8.8% and 16.4% remained prescribing persistent at a maintenance dose with a recorded weight at 12 months. About half of initiators lacked a 12-month weight. Among all initiators, [&ge;]5% TBWL was documented in 25.6% (semaglutide) and 30.4% (tirzepatide), rising to 51.9% and 61.9% among those with recorded weight, 66.1% and 79.5% among those also prescribing persistent, and 82.9% and 87.3% among those further at a maintenance dose. Conclusions: In routine practice, most patients initiating semaglutide or tirzepatide did not remain on therapy, reach a maintenance dose, and have weight documented through the first year. Documented weight loss was greatest among those completing each step of care, suggesting continuation, dose escalation, and monitoring as targets for improvement.","rel_num_authors":14,"rel_authors":[{"author_name":"Huanhuan Yang","author_inst":"Yale University"},{"author_name":"Chungsoo Kim","author_inst":"Yale School of Medicine"},{"author_name":"Joseph S. Ross","author_inst":"Yale University"},{"author_name":"Chenxi Huang","author_inst":"Yale University"},{"author_name":"Kyungseon Choi","author_inst":"Yale University"},{"author_name":"Bo Kang","author_inst":"Yale University"},{"author_name":"Adith Arun","author_inst":"Yale School of Medicine"},{"author_name":"Huilin Tang","author_inst":"The University of Pennsylvania"},{"author_name":"Yong Chen","author_inst":"The University of Pennsylvania"},{"author_name":"Hua Xu","author_inst":"Yale University"},{"author_name":"Mona Sharifi","author_inst":"Yale School of Medicine"},{"author_name":"Zhihui Li","author_inst":"Tsinghua University"},{"author_name":"Harlan Krumholz","author_inst":"Yale University"},{"author_name":"Yuan Lu","author_inst":"Yale University"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Emergency Department Utilization After 60-Day Peripheral Nerve Stimulation Versus Usual Care for Refractory Occipital Neuralgia: A Prospective Propensity-Matched Cohort, Difference-in-Differences Analysis","rel_doi":"10.64898\/2026.10.02.26364550","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364550","rel_abs":"Background: Temporary 60-day percutaneous peripheral nerve stimulation (PNS) can relieve pain in refractory occipital neuralgia (ON), but whether it alters acute healthcare utilization relative to the natural trajectory of the disease is unknown, because prior studies have lacked a concurrent comparator. Methods: We performed a secondary analysis of prospectively collected data from a tertiary interventional pain center. Adults with medically refractory ON (primary diagnosis occipital neuralgia, ICD-10-CM M54.81) who underwent 60-day occipital PNS (n = 42) were compared with concurrent patients who were clinically eligible for PNS but were denied insurance authorization and continued optimized non-PNS management (usual care; n = 63). Headache-related emergency department (ED) encounters - index (occipital neuralgia) and non-index (other headache\/facial-pain diagnoses) - were ascertained over the 12 months before and after the treatment window via the electronic record and the statewide health information exchange. Patients were 1:1 propensity-matched on a priori confounders (age, sex, baseline total headache-related ED utilization, HIT-6, and baseline headache-medication use). The primary analysis was a difference-in-differences (DiD) comparison of the change in headache-related ED utilization, reported as the additive difference (Hodges-Lehmann estimate, distribution-free 95% CI) and, alongside, as a multiplicative rate ratio (RR). Results: Thirty-six matched pairs were well balanced. Baseline headache-related ED utilization was nearly identical between matched groups (6.3 vs. 6.2 visits\/year). Over the following year, PNS patients' utilization fell to 2.5 while usual-care patients' rose to 6.9. The DiD was 5.0 fewer headache-related ED visits per patient (95% CI 3.0-6.0; p < 0.001), corresponding to a rate ratio of 0.36 (95% CI 0.27-0.48; p < 0.001). Results were consistent in the full sample, in covariate-adjusted models, and after excluding controls denied for incomplete conservative-therapy trials. The effect was driven by non-index headache visits. Conclusions: Relative to a concurrent, matched usual-care cohort whose headache related ED utilization rose over time, 60-day occipital PNS was associated with a substantial reduction in acute-care use, strengthening the case for a role of PNS on healthcare utilization in refractory ON.","rel_num_authors":6,"rel_authors":[{"author_name":"Cameron William Harris","author_inst":"Valley Health System GME"},{"author_name":"Eric T Nguyen","author_inst":"Department of Physical Medicine and Rehabilitation, Charles R. Drew University of Medicine and Science"},{"author_name":"Sergio Mosquera Limas","author_inst":"Department of Orthopaedics and Rehabilitation, Division of Physiatry, Yale New Haven Hospital"},{"author_name":"Samir J Sheth","author_inst":"Division of Pain Management, Sutter Health System"},{"author_name":"Robert William Chow","author_inst":"Department of Anesthesiology, Yale School of Medicine"},{"author_name":"Charles A. Odonkor","author_inst":"Division of Physiatry, Interventional Pain Medicine, Department of Orthopaedics and Rehabilitation, Yale School of Medicine"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Power Calculation for Noninferiority Stepped-Wedge Cluster Randomized Trials","rel_doi":"10.64898\/2026.10.04.26364705","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26364705","rel_abs":"Background: Stepped-wedge cluster randomized trials (SW-CRTs) are increasingly used when interventions need to be implemented sequentially across clusters. Despite extensive developments in the design and analysis of superiority SW-CRTs, methods for planning noninferiority SW-CRTs remain limited. Methods: We propose swNIsim, a simulation-based framework for power calculation in noninferiority SW-CRTs using generalized linear mixed-effects models (GLMMs). The proposed approach accommodates both continuous and binary outcomes and supports practical design features, including unequal numbers of clusters across sequences, varying cluster-period sizes, delayed intervention effects, and analyses with or without adjustment for secular time effects. Noninferiority margins can be specified using several commonly applied strategies. Results: Through extensive simulation studies, we examined the impact of key design parameters on statistical power, including the number of periods, the number of clusters per sequence, the number of individuals per cluster-period, and the degree of between-cluster variability. For a fixed total sample size, designs with more time periods consistently achieved higher power. Increasing the number of clusters per sequence produced modest gains in power, whereas greater between-cluster variability reduced power. Type I error rates were well controlled across the scenarios examined. Balanced allocation of clusters across sequences was more efficient than unbalanced allocation schemes. Two real-world SW-CRT examples were used to illustrate application of the method. Conclusions: The proposed swNIsim provides a flexible and practical approach for power calculation in noninferiority SW-CRTs. By accommodating a wide range of design configurations and outcome types, and through implementation as a freely available R package, swNIsim may facilitate the planning and design of noninferiority stepped-wedge trials.","rel_num_authors":3,"rel_authors":[{"author_name":"Justin Guo","author_inst":"Montgomery Bell Academy"},{"author_name":"Chih-Yuan Hsu","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Yu Shyr","author_inst":"Vanderbilt University Medical Center"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Acquisition Speed versus Spatial Resolution in Ultra-High-Resolution Photon-Counting CT: Phantom Study to Guide Protocol Development","rel_doi":"10.64898\/2026.10.04.26363713","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.04.26363713","rel_abs":"Faster ultrahigh-resolution (UHR) photon-counting CT acquisitions facilitate breath-hold imaging, but identical reconstruction settings may conceal differences in spatial resolution. To assess spatial resolution and depiction of small airways and venous stents across helical UHR acquisition configurations. Stationary wire, airway, and venous-stent phantoms underwent one acquisition per configuration using five configurations on a dual-source scanner at 120 kVp. Reconstructions used 0.2- and 0.4-mm thicknesses, the same sharp kernel, and iterative reconstruction strength 1. We measured the full-width at half-maximum of the slice sensitivity profile (SSP) and spatial frequency at 20% of the modulation transfer function (MTF20). Rank-based F tests with Holm adjustment assessed configuration differences in resolution and variability across slices. Airway detection used a profile contrast-to-noise criterion; stent assessment was qualitative. Calculated acquisition time for 400-mm coverage decreased from 9.80 to 1.30 seconds between the slowest and fastest configurations. At 0.2-mm reconstruction thickness, median SSP increased from 0.316 to 0.496 mm, and median MTF20 decreased from 2.870 to 2.059 lp\/mm (both P<.001). Interquartile ranges increased from 0.047 to 0.197 mm for SSP and from 0.256 to 0.654 lp\/mm for MTF20 (both variability P<.001). Increasing reconstruction thickness to 0.4 mm increased SSP by a median 0.221 mm across 2459 matched slice-wire measurements (P<.001). At 0.2-mm reconstruction thickness, 0.4- and 0.6-mm lumens with 0.2-mm walls were detected only in the slowest configuration. Faster configurations showed less distinct stent struts and greater adjacent-wall distortion. Faster helical UHR photon-counting CT configurations had poorer spatial resolution despite identical nominal slice thickness. Consistent acquisition and reconstruction settings are important for longitudinal comparisons.","rel_num_authors":3,"rel_authors":[{"author_name":"Navid Azimi","author_inst":"Emory University"},{"author_name":"Joao A.C. Lima","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Amir Pourmorteza","author_inst":"Emory University"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Overdose-related communication in Connecticut: reported receipt, perceived utility, and responses among overdose prevention and response professionals","rel_doi":"10.64898\/2026.10.01.26363949","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26363949","rel_abs":"Background Timely overdose response depends not only on surveillance systems that detect overdose clusters, but also on communication pathways that deliver actionable information to the professionals positioned to respond. Understanding which overdose-related communications are received, perceived as useful, and translated into action is essential for improving overdose prevention and response infrastructure. Objective We assessed which overdose-related communication channels professionals reported receiving, which they perceived as most helpful, how organizations reported responding to overdoses or overdose clusters, and whether these patterns differed by professional role, county, and funding source. Methods We conducted an exploratory descriptive survey in 2024 using a convenience sample of professionals across Connecticut whose jobs involved overdose prevention or response (N=149). Using this survey data, we summarized reported receipt and perceived utility of overdose-related communication channels, organizational response actions, and internal receipt of Connecticut Department of Public Health overdose alerts. Results were stratified descriptively by professional role, county, and funding source. We interpreted findings using a public health communication-to-action cascade focused on signal detection, communication receipt, internal dissemination, perceived utility, and response action. Results Reported communication receipt and perceived utility differed most clearly by professional role. Peer information sharing was the most commonly reported communication source and was frequently perceived as helpful, but respondents who reported receiving formal channels such as state alerts, local alerts, or platform-based information often identified those channels as most helpful. Internal receipt of Connecticut Department of Public Health overdose alerts also varied by role. SSPs\/substance use treatment programs and first responders more often reported outreach to people who use drugs, whereas government and health district respondents reported a more even mix of public communication and outreach activities. Conclusions Overdose-related communication in Connecticut appears role-dependent and unevenly distributed. Informal peer networks are widely used and perceived as helpful, while formal alert systems may require improvements to reach and actionability. Practical improvements include opt-in communication pathways tailored to professional roles, clearer access points for state and local alerts, internal dissemination protocols that specify who should receive which alerts, and alert-to-action playbooks that connect specific alert types to recommended response steps.","rel_num_authors":2,"rel_authors":[{"author_name":"A Ram","author_inst":"Yale University"},{"author_name":"Frederick  L Altice","author_inst":"Yale University School of Medicine"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Diabetes Polygenic Scores Predict Glycemic Indices and Insulin Use in Individuals with Atypical Diabetes","rel_doi":"10.64898\/2026.10.01.26364299","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364299","rel_abs":"Aims\/Hypothesis: Atypical forms of diabetes often provide diagnostic challenges and are suboptimally treated. We sought to determine whether type 1 and 2 diabetes polygenic scores (PS) would help improve classification of islet autoantibody-negative (IAb-) atypical diabetes cases. Methods: We implemented type 1 diabetes PS (T1D PS) and type 2 diabetes PS (T2D PS) in 309 IAb- individuals' genome sequencing from the Rare and Atypical Diabetes Network (RADIANT), the largest and most comprehensively phenotyped collection of unsolved and atypical diabetes cases. We performed regression analyses to assess associations between PS, clinical characteristics, and glycemic measures. Results: Both T1D and T2D PS were significantly higher in RADIANT than in ancestry-matched controls from UK Biobank. Both PS were associated with C-peptide measures throughout participant oral glucose tolerance tests (OGTT), although in opposite directions; T1D PS was associated with lower C-peptide measures, while T2D PS was associated with higher measures. Participants with T1D PS above a previously established optimal PS value for differentiating cases and controls (T1D PS GRS2>12.88) had 13-fold higher odds of both insulin deficiency on OGTT and use of both basal and bolus insulin therapy. Conclusions\/Interpretation: Individuals in RADIANT with ambiguous diabetes subtypes displayed genetic enrichment for both type 1 and type 2 diabetes, despite ascertainment to remove standard type 1 and type 2 diabetes. T1D PS identified individuals with an unrecognized \"type 1 diabetes-like\" phenotype with insulin deficiency and need for intensive insulin in the absence of islet autoantibodies. PS may help identify individuals with atypical diabetes who will ultimately benefit from insulin therapy.","rel_num_authors":21,"rel_authors":[{"author_name":"Steven D. Gage","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Raymond J. Kreienkamp","author_inst":"Boston Children's Hospital"},{"author_name":"Aaron J. Deutsch","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Eric J. Richards","author_inst":"Diabetes Genetics Initiative and Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Boyce T"},{"author_name":"Liana K. Billings","author_inst":"Division of Endocrinology, Endeavor Health, Skokie, Illinois; Department of Medicine, University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA"},{"author_name":"Sara J. Cromer","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Siri Atma W. Greeley","author_inst":"Department of Medicine and Pediatrics, Section of Endocrinology, Diabetes, and Metabolism, the Kovler Diabetes Center, University of Chicago, Chicago, IL, USA"},{"author_name":"Irl B. Hirsch","author_inst":"Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA"},{"author_name":"Alicia Huerta-Chagoya","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Steven E. Kahn","author_inst":"Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and University of Washington, Seattle, WA, USA"},{"author_name":"Klara R. Klein","author_inst":"Division of Endocrinology and Metabolism, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA"},{"author_name":"Josep M. Mercader","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Neda Rasouli","author_inst":"Division of Endocrinology, Metabolism and Diabetes, University of Colorado, School of Medicine and VA Eastern Colorado Heath Care System, Aurora, CO, USA"},{"author_name":"Marjan Rezaei","author_inst":"Division of Endocrinology, Metabolism and Diabetes, University of Colorado, School of Medicine, Aurora, CO, USA"},{"author_name":"Maria J. Redondo","author_inst":"Department of Pediatrics, Diabetes and Endocrinology, Baylor College of Medicine, Houston, TX, USA"},{"author_name":"Ashok Balasubramanyam","author_inst":"Division of Diabetes, Endocrinology and Metabolism, Baylor College of Medicine, Houston, TX, USA"},{"author_name":"Jose C. Florez","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"Louis H. Philipson","author_inst":"Department of Medicine and Pediatrics, Section of Endocrinology, Diabetes, and Metabolism, the Kovler Diabetes Center, University of Chicago, Chicago, IL, USA"},{"author_name":"Jason Flannick","author_inst":"Diabetes Genetics Initiative and Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Divisio"},{"author_name":"Miriam S. Udler","author_inst":"Center for Genomic Medicine and Diabetes Unit, Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Mass General Brigham, Boston, MA, USA"},{"author_name":"- RADIANT Study Group","author_inst":""}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"When Is Amyloid Really Cleared? Substantial Discordance Between Centiloid Quantification and Visual Reads of Amyloid PET after Amyloid-Targeting Therapy","rel_doi":"10.64898\/2026.10.03.26364642","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.03.26364642","rel_abs":"Amyloid-targeting therapies (ATTs) substantially reduce amyloid PET signal and slow clinical decline in early symptomatic Alzheimer disease. As ATTs enter clinical practice, PET may assess target engagement and guide treatment management, but there is no consensus on how to measure treatment-related amyloid clearance (TRAC). We compared Centiloid quantification across pipelines and visual reads for interpreting pre- and post-ATT amyloid PET. Methods: We analyzed 18F-florbetapir or 18F-florbetaben PET from 101 patients treated with lecanemab or donanemab: 88 pre-ATT and 54 post-ATT scans, including 41 paired scans. Centiloids were derived using FDA-cleared MIMneuro and two research pipelines (rPOP, CapAIBL) and compared using intraclass correlation coefficients (ICC). Clearance rates were estimated using linear mixed-effects models. Full TRAC was defined on post-ATT scans quantitatively (<11 Centiloids) or based on visual interpretation by three expert readers. Results: Treated patients were 74+\/-7 years old; 57% were female, 59% were apolipoprotein E4 carriers, and 78% had mild cognitive impairment (22% mild dementia). Centiloid agreement between pipelines was equally high pre- and post-ATT (both ICCs=0.90). Among paired scans (mean treatment duration, 16.7 +\/- 4.6 months), clearance estimates were similar across pipelines and greater with donanemab (n=15 patients; between -62 and -60 Centiloids\/year depending on the pipeline) than lecanemab (n=26; -38 to -36 Centiloids\/year; all Ps<0.005). Among 54 post-ATT scans, between 44% and 57% were <11 Centiloids depending on pipeline, with 20 (37%) meeting this criterion across all three pipelines. In contrast, only 11% to 19% were visually negative across readers, with 4 (7%) unanimously read as negative. Of the 20 post-ATT scans <11 Centiloids across all pipelines, 13 (65%) were considered positive by all readers, commonly with residual occipital binding. Conclusion: Centiloid quantification was robust across pipelines before and after ATT initiation, yielding clearance rates consistent with clinical trials. However, quantitative and visual assessments were markedly discordant after ATT, with an unusually high proportion of scans <11 Centiloids remaining visually positive, warranting cautious interpretation of post-ATT Centiloid values. Larger studies should assess the clinical relevance of these findings and further develop robust approaches to establish full TRAC.","rel_num_authors":19,"rel_authors":[{"author_name":"Renaud La Joie","author_inst":"UCSF"},{"author_name":"Marlene Lin","author_inst":"UCSF"},{"author_name":"Yingbing Wang","author_inst":"UCSF"},{"author_name":"David N Soleimani-Meigooni","author_inst":"UCSF"},{"author_name":"Ganna Blazhenets","author_inst":"UCSF"},{"author_name":"Corrina S Fonseca","author_inst":"UCSF"},{"author_name":"Tara Ellingson","author_inst":"UCSF"},{"author_name":"Hong Nguyen","author_inst":"UCSF"},{"author_name":"Kambiz Nael","author_inst":"UCSF"},{"author_name":"Salil Soman","author_inst":"UCSF"},{"author_name":"Pierrick Bourgeat","author_inst":"CSIRO"},{"author_name":"Jake P Levy","author_inst":"UCSF"},{"author_name":"Gina Rhee","author_inst":"UCSF"},{"author_name":"Julio C Rojas","author_inst":"UCSF"},{"author_name":"Melanie Stephens","author_inst":"UCSF"},{"author_name":"Nhat Bui","author_inst":"UCSF"},{"author_name":"Peter A Ljubenkov","author_inst":"UCSF"},{"author_name":"Lawren VandeVrede","author_inst":"UCSF"},{"author_name":"Gil D Rabinovici","author_inst":"UCSF"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"An adaptive technical and behavioral approach for biomarker acquisition in autism with intellectual disability","rel_doi":"10.64898\/2026.10.01.26364439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364439","rel_abs":"Autistic individuals with intellectual disability (ASD+ID) and profound autism are rarely studied in neuroscience research due to barriers including communication challenges, sensory sensitivities, anxiety, and elevated behavioral support needs. Consequently, biomarker development in autism fails to include the portion of the autistic population with highest support needs and greatest potential to benefit from treatments derived from imminent advances in personalized medicine. Here we present a multimodal, participant-centered protocol for simultaneous electroencephalography (EEG) and eye-tracking (ET) acquisition to advance clinical trial readiness research in this underserved population. The protocol combines individualized behavioral supports and an adaptive EEG-ET acquisition platform. Pre-visit caregiver interviews informed participant-specific research plans, including customized visual supports, reinforcement strategies, and EEG net desensitization procedures. A gaze-contingent stimulus presentation system used participant-preferred videos to support attention to experimental stimuli and behavior consistent with data acquisition (e.g., refraining from movement) while dynamically adapting stimulus delivery based on visual engagement with the assay and real-time assessment of data quality. By quantifying attended trials in real time and prioritizing unattended stimulus classes, the paradigm maximizes acquisition efficiency to minimize participant burden. This approach was utilized to deploy candidate biomarkers with demonstrated replicability in the Autism Biomarkers Consortium for Clinical Trials (ABC-CT): the N170 event-related potential to faces, resting-state EEG, and visual attention to human faces (measured with ET). Feasibility was evaluated in 76 children with ASD+ID (M age = 8.76 years; IQ = 32.4) and a small comparison sample of 8 children with intellectual disability without autism (M age = 8.91 years; IQ = 45.9). Usable EEG data (>7 minutes) were acquired in 61% (ASD+ID) and 88% (ID) of participants, respectively. Sufficient ET data were obtained from 67% (ASD+ID) and 63% (ID) of participants, respectively. Findings demonstrate the feasibility of inclusive biomarker acquisition and provide a framework for expanding participation of individuals with ASD+ID and profound autism in neuroscience research. Ongoing research seeks to evaluate this approach in larger samples and to demonstrate feasibility in multisite research studies.","rel_num_authors":8,"rel_authors":[{"author_name":"Cassandra J Stevens","author_inst":"Schiefelbusch Institute for Life Span Studies, University of Kansas"},{"author_name":"Sara Eberle","author_inst":"Yale Child Study Center"},{"author_name":"Casey Carrow","author_inst":"Yale Child Study Center"},{"author_name":"Sherab Tsheringla","author_inst":"Yale Child Study Center"},{"author_name":"Christine Cukar-Capizzi","author_inst":"Yale Child Study Center"},{"author_name":"Julie  M. Wolf","author_inst":"Yale Child Study Center"},{"author_name":"Adam Naples","author_inst":"Yale Child Study Center"},{"author_name":"James McPartland","author_inst":"Yale Child Study Center"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"An adaptive technical and behavioral approach for biomarker acquisition in autism with intellectual disability","rel_doi":"10.64898\/2026.10.01.26364439","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364439","rel_abs":"Autistic individuals with intellectual disability (ASD+ID) and profound autism are rarely studied in neuroscience research due to barriers including communication challenges, sensory sensitivities, anxiety, and elevated behavioral support needs. Consequently, biomarker development in autism fails to include the portion of the autistic population with highest support needs and greatest potential to benefit from treatments derived from imminent advances in personalized medicine. Here we present a multimodal, participant-centered protocol for simultaneous electroencephalography (EEG) and eye-tracking (ET) acquisition to advance clinical trial readiness research in this underserved population. The protocol combines individualized behavioral supports and an adaptive EEG-ET acquisition platform. Pre-visit caregiver interviews informed participant-specific research plans, including customized visual supports, reinforcement strategies, and EEG net desensitization procedures. A gaze-contingent stimulus presentation system used participant-preferred videos to support attention to experimental stimuli and behavior consistent with data acquisition (e.g., refraining from movement) while dynamically adapting stimulus delivery based on visual engagement with the assay and real-time assessment of data quality. By quantifying attended trials in real time and prioritizing unattended stimulus classes, the paradigm maximizes acquisition efficiency to minimize participant burden. This approach was utilized to deploy candidate biomarkers with demonstrated replicability in the Autism Biomarkers Consortium for Clinical Trials (ABC-CT): the N170 event-related potential to faces, resting-state EEG, and visual attention to human faces (measured with ET). Feasibility was evaluated in 76 children with ASD+ID (M age = 8.76 years; IQ = 32.4) and a small comparison sample of 8 children with intellectual disability without autism (M age = 8.91 years; IQ = 45.9). Usable EEG data (>7 minutes) were acquired in 61% (ASD+ID) and 88% (ID) of participants, respectively. Sufficient ET data were obtained from 67% (ASD+ID) and 63% (ID) of participants, respectively. Findings demonstrate the feasibility of inclusive biomarker acquisition and provide a framework for expanding participation of individuals with ASD+ID and profound autism in neuroscience research. Ongoing research seeks to evaluate this approach in larger samples and to demonstrate feasibility in multisite research studies.","rel_num_authors":8,"rel_authors":[{"author_name":"Cassandra J Stevens","author_inst":"Schiefelbusch Institute for Life Span Studies, University of Kansas"},{"author_name":"Sara Eberle","author_inst":"Yale Child Study Center"},{"author_name":"Casey Carrow","author_inst":"Yale Child Study Center"},{"author_name":"Sherab Tsheringla","author_inst":"Yale Child Study Center"},{"author_name":"Christine Cukar-Capizzi","author_inst":"Yale Child Study Center"},{"author_name":"Julie  M. Wolf","author_inst":"Yale Child Study Center"},{"author_name":"Adam Naples","author_inst":"Yale Child Study Center"},{"author_name":"James McPartland","author_inst":"Yale Child Study Center"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Social and behavioral risk factors are associated with age-related differences in sustained attention: A cross-sectional GradCPT analysis of the All of Us dataset","rel_doi":"10.64898\/2026.10.01.26364102","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364102","rel_abs":"Background Attentional control declines with normal aging, yet the role of modifiable lifestyle factors in accelerating this decline remains incompletely characterised in large, diverse populations. We examined associations between four modifiable risk factors (smoking intensity, alcohol binge drinking, social satisfaction and blood pressure) and sustained attention performance in 13,866 adults drawn from the All of Us Research Program. Methods Cognitive performance was assessed using the Gradual-Onset Continuous Performance Task (GradCPT). A composite cognitive efficiency score was derived via principal component analysis of four GradCPT metrics: d' (perceptual sensitivity), response criterion, median reaction time and reaction time variability. Associations between cognitive efficiency and each risk factor were examined using multiple linear regression adjusted for age, sex and race\/ethnicity. Effect sizes were expressed as age-equivalent years of cognitive aging (age-equivalent years = regression coefficient for the risk factor divided by the regression coefficient for age) to aid clinical interpretation. Results GradCPT performance declined progressively with age (p < 0.001). Social satisfaction emerged as the strongest lifestyle predictor: low social satisfaction was associated with approximately 5.8 additional age-equivalent years of cognitive aging relative to high social satisfaction. Smoking showed a dose-response pattern, with heavy smokers (> 20 cigarettes\/day) exhibiting an approximately 5-year age-equivalent deficit versus never-smokers. Stage 2 hypertension showed a modest, non-significant negative association. Binge drinking showed limited significant associations, likely complicated by survivor and abstainer biases. Bootstrapped analyses of combined exposures showed that combinations of risk factors, particularly those involving low social satisfaction, produced larger cognitive deficits than expected under an additive model. Conclusions These findings support an interactive rather than a purely additive model of lifestyle-related cognitive vulnerability and highlight the GradCPT as a subclinical measure of attention-based cognitive risk in non-clinical populations. Keywords Cognitive aging, Sustained attention, GradCPT, Modifiable risk factors, Social isolation, Smoking, Hypertension, All of Us Research Program","rel_num_authors":4,"rel_authors":[{"author_name":"Natan M Coresh-Chiappori","author_inst":"Morgan State University"},{"author_name":"Theresa Boyer","author_inst":"Johns Hopkins University"},{"author_name":"A Richey Sharrett","author_inst":"Johns Hopkins University"},{"author_name":"Ingrid K Tulloch","author_inst":"Morgan State University"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Sex differences in genetic liability to modifiable Alzheimer's disease risk factors","rel_doi":"10.64898\/2026.10.01.26364536","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364536","rel_abs":"NTRODUCTION: Alzheimer's disease (AD) shows sex differences in risk, clinical progression, and biomarker profiles, but whether inherited genetic liability to modifiable risk factors contributes differently to AD susceptibility in females and males remains unclear. We evaluated whether genetic relationships between several modifiable dementia risk factors and AD differ between females and males. METHODS: We integrated polygenic risk scores (PRSs) for modifiable risk factors, genome-wide genetic correlation, and two-sample Mendelian randomization (MR) analyses. PRS associations with AD diagnosis were evaluated in the Alzheimer's Disease Genetics Consortium (n=27,751) and with AD plasma biomarkers in the Health and Aging Brain Study-Health Disparities (n=2,307-2,737, depending on the biomarker). Primary analyses evaluated female- and male-specific associations and compared sex-specific estimates. RESULTS: Educational attainment and physical activity PRSs were associated with AD in both sexes. PRS sex differences were nominal for educational attainment, total cholesterol, and LDL cholesterol, but none remained significant after FDR correction. Genetic correlation showed FDR-significant sex differences for social isolation, physical activity, LDL cholesterol, and pulse pressure. MR identified FDR-significant associations within sex strata; higher HDL cholesterol was associated with lower AD risk in females, whereas higher total cholesterol and type 2 diabetes were associated with lower and higher AD risk, respectively, in males. Sensitivity analyses provided inconsistent support, and no sex difference in MR estimates remained significant after FDR correction. In HABS-HD, type 2 diabetes PRS was associated with higher NfL, BMI PRS with higher pTau181, and the composite PRS with higher NfL among males after FDR correction. DISCUSSION: Evidence that modifiable dementia risk factors relate differently to AD by sex was limited and depended on the genetic measure examined. Sex differences in genome-wide genetic overlap were not consistently reflected in PRS or MR, indicating that shared genetic architecture does not necessarily translate into sex-specific inherited liability or causal effects","rel_num_authors":10,"rel_authors":[{"author_name":"Rakshya U Sharma","author_inst":"University of California, San Francisco"},{"author_name":"Paulina Tolosa-Tort","author_inst":"University of California, San Francisco"},{"author_name":"Meri Okorie","author_inst":"University of California, San Francisco"},{"author_name":"Aadrita Chatterjee","author_inst":"University of California, San Francisco"},{"author_name":"Caroline Jonson","author_inst":"DataTecnica LLC"},{"author_name":"Kristine Yaffe","author_inst":"University of California San Francisco"},{"author_name":"Michael E Belloy","author_inst":"Washington University in St. Louis"},{"author_name":"Shea J Andrews","author_inst":"University of California San Francisco"},{"author_name":"- ADGC","author_inst":""},{"author_name":"- HABS-HD Study team","author_inst":""}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Sex differences in genetic liability to modifiable Alzheimer's disease risk factors","rel_doi":"10.64898\/2026.10.01.26364536","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364536","rel_abs":"NTRODUCTION: Alzheimer's disease (AD) shows sex differences in risk, clinical progression, and biomarker profiles, but whether inherited genetic liability to modifiable risk factors contributes differently to AD susceptibility in females and males remains unclear. We evaluated whether genetic relationships between several modifiable dementia risk factors and AD differ between females and males. METHODS: We integrated polygenic risk scores (PRSs) for modifiable risk factors, genome-wide genetic correlation, and two-sample Mendelian randomization (MR) analyses. PRS associations with AD diagnosis were evaluated in the Alzheimer's Disease Genetics Consortium (n=27,751) and with AD plasma biomarkers in the Health and Aging Brain Study-Health Disparities (n=2,307-2,737, depending on the biomarker). Primary analyses evaluated female- and male-specific associations and compared sex-specific estimates. RESULTS: Educational attainment and physical activity PRSs were associated with AD in both sexes. PRS sex differences were nominal for educational attainment, total cholesterol, and LDL cholesterol, but none remained significant after FDR correction. Genetic correlation showed FDR-significant sex differences for social isolation, physical activity, LDL cholesterol, and pulse pressure. MR identified FDR-significant associations within sex strata; higher HDL cholesterol was associated with lower AD risk in females, whereas higher total cholesterol and type 2 diabetes were associated with lower and higher AD risk, respectively, in males. Sensitivity analyses provided inconsistent support, and no sex difference in MR estimates remained significant after FDR correction. In HABS-HD, type 2 diabetes PRS was associated with higher NfL, BMI PRS with higher pTau181, and the composite PRS with higher NfL among males after FDR correction. DISCUSSION: Evidence that modifiable dementia risk factors relate differently to AD by sex was limited and depended on the genetic measure examined. Sex differences in genome-wide genetic overlap were not consistently reflected in PRS or MR, indicating that shared genetic architecture does not necessarily translate into sex-specific inherited liability or causal effects","rel_num_authors":10,"rel_authors":[{"author_name":"Rakshya U Sharma","author_inst":"University of California, San Francisco"},{"author_name":"Paulina Tolosa-Tort","author_inst":"University of California, San Francisco"},{"author_name":"Meri Okorie","author_inst":"University of California, San Francisco"},{"author_name":"Aadrita Chatterjee","author_inst":"University of California, San Francisco"},{"author_name":"Caroline Jonson","author_inst":"DataTecnica LLC"},{"author_name":"Kristine Yaffe","author_inst":"University of California San Francisco"},{"author_name":"Michael E Belloy","author_inst":"Washington University in St. Louis"},{"author_name":"Shea J Andrews","author_inst":"University of California San Francisco"},{"author_name":"- ADGC","author_inst":""},{"author_name":"- HABS-HD Study team","author_inst":""}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"A Modality-Invariant Measure of Neural Health","rel_doi":"10.64898\/2026.10.02.26364203","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364203","rel_abs":"Quantifying neural health with a single measure remains a major unmet challenge. Here, we report a physiological marker based on the spatial distribution of signal-derived energy correlates in the resting brain. We hypothesize that energy organization in the healthy brain approaches an entropy-maximizing, homeostatically regulated state characterized by five properties: lognormal energy distributions, balanced spatial allocation, statistical independence between regions, low energy variance, and temporal stability. Together, these properties define an energetic profile that the Neural Health Index (NHI) summarizes as a single score, computable from (scalp\/intracranial) electroencephalography, magnetoencephalography, or functional magnetic resonance imaging. Across 808 participants spanning neurological, psychiatric, neurodevelopmental, and neurodegenerative disorders, NHI distinguished healthy from clinical populations with sensitivity and specificity exceeding 95% in internal and external validation, scaled with disease severity, tracked pharmacological treatment exposure, and generalized to unseen diagnoses. These findings support NHI as a disease-agnostic, modality-invariant candidate biomarker for disease stratification and treatment monitoring.","rel_num_authors":5,"rel_authors":[{"author_name":"Luis A Sanchez Colon","author_inst":"Johns Hopkins University"},{"author_name":"Ernst Niebur","author_inst":"Johns Hopkins University"},{"author_name":"Joon Kang","author_inst":"Johns Hopkins University"},{"author_name":"Chiadi Onyike","author_inst":"Johns Hopkins University"},{"author_name":"Sridevi Sarma","author_inst":"Johns Hopkins University"}],"rel_date":"2026-10-06","rel_site":"medrxiv"},{"rel_title":"Learning fly pose from vision-language annotations","rel_doi":"10.64898\/2026.09.30.755712","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755712","rel_abs":"Animal pose estimation typically requires manual annotation of body parts to train neural networks for each new recording system or environmental condition. Here we use a general-purpose vision-language model (VLM) to generate annotations in multi-animal recordings of fruit flies (Drosophila melanogaster). Initial annotations follow written anatomical descriptions and are reviewed by an independent VLM session using neighboring video frames. On 120 held-out fly images, AI annotations had a median distance of 2.28 pixels from human labels, with 84.0% agreement within eight pixels, averaged across landmark types. The comparison included 10 landmarks, with head and eyes analyzed separately because of systematic differences in placement. Review improved agreement primarily at the feet, with the largest remaining discrepancies at positions with limited visual evidence. Visual inspection revealed cases in which the AI annotations were more anatomically accurate than those of an experienced human annotator, particularly at the feet. A convolutional network trained using SLEAP on 300 AI-annotated fly images showed similar agreement with human labels and closely reproduced the AI annotations on held-out images, with a median distance of 1.56 pixels. We also applied the procedure to recordings from another laboratory, using new AI annotations to train a separate pose network. Although VLM annotation required minutes per fly, the trained networks enabled pose estimation throughout more than 700,000 frames. These results demonstrate that VLM annotations can support fast animal pose estimation without manually labeled training images.","rel_num_authors":4,"rel_authors":[{"author_name":"Joshua W. Shaevitz","author_inst":"Joseph Henry Laboratories of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Matthew G. Sierra","author_inst":"Joseph Henry Laboratories of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Sarah Kuo Kim","author_inst":"Joseph Henry Laboratories of Physics and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Scott D. Pletcher","author_inst":"Department of Molecular and Integrative Physiology and Institute of Gerontology, University of Michigan, Ann Arbor, MI 48109, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Chromosome-scale genome assembly of the North American invasive Asteraceae, Tanacetum vulgare (common tansy)","rel_doi":"10.64898\/2026.09.30.755630","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755630","rel_abs":"Common tansy (Tanacetum vulgare), a significant agricultural invasive species, threatens forage productivity, livestock carrying capacity, and plant biodiversity across North American agroecosystems. Despite being a close relative to the ornamental Asteraceae Chrysanthemum, T. vulgare genomic studies are severely lacking, but remain critical to the development of novel weed management tools and the investigation of plant invasion evolution. In this study, we performed the assembly and annotation of the diploid genome (2n=2x=18) of an invasive North American T. vulgare genotype using long-read PacBio HiFi and Iso-Seq sequencing technology. The assembled haplotype genome comprised 9 pseudomolecules with a total size of ~4.8 Gb and a scaffold N50 of 546 Mb. In addition, both the plastid and mitochondrial genome sequences were assembled. BUSCO analysis revealed a high overall genome completeness with 69,343 predicted protein-coding genes (AED<0.6: 98%). A high-quality North American invasive reference T. vulgare genome, complementing a recent one assembled for a native European accession, is critical for the investigation of plant invasion biology, genome evolution, and the future development of novel genetic biocontrol weed management technologies.","rel_num_authors":8,"rel_authors":[{"author_name":"Dimiru Tadesse","author_inst":"USDA, Agricultural Research Service"},{"author_name":"Adrian Platts","author_inst":"Michigan State University"},{"author_name":"Lori Croghan","author_inst":"University of Minnesota"},{"author_name":"Alan Smith","author_inst":"University of Minnesota"},{"author_name":"Neil O Anderson","author_inst":"University of Minnesota"},{"author_name":"Roger Becker","author_inst":"University of Minnesota"},{"author_name":"Patrick P. Edger","author_inst":"Michigan State University"},{"author_name":"Matthew Tancos","author_inst":"USDA, Agricultural Research Service"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Generating a Collection of Single-Gene Deletions in the eps Operon in Bacillus subtilis Strain NCIB 3610","rel_doi":"10.64898\/2026.10.05.756831","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756831","rel_abs":"In the environment, bacteria mainly exist in multicellular, surface-adhered communities called biofilms. One key feature of the biofilms is a self-produced extracellular matrix that embeds cells within a structured community and contributes to their adhesion, organization, and retention. The matrix of most characterized biofilms contains three primary components: polysaccharides, protein, and extracellular DNA (eDNA). Upon biofilm induction, Bacillus subtilis produces and secretes a polysaccharide known as exopolysaccharide (EPS). The 15 genes of the epsA-O operon encode proteins that coordinate the assembly, export, and polymerization of EPS oligosaccharide (glycan) subunits. While much progress has been made to elucidate the chemical structure of EPS, further work is needed to determine the contributions of some eps genes to EPS biosynthesis experimentally. Here, we generated a collection of marker-less, in-frame deletions targeting each eps gene in the epsA-O operon in B. subtilis strain NCIB 3610 using the Cre system. Biofilm phenotypes of resulting mutants were used to assess each gene's importance to biofilm development. Impact The epsA-O single-gene deletion collection was designed to enable systematic assessment of the contribution of each eps gene to EPS production and biofilm-associated phenotypes. When combined with current knowledge of EPS structure, this collection will help clarify the roles of individual genes in EPS biosynthesis. This approach can also be easily adapted for the systematic analyses of other large, complex operons in diverse bacterial species.","rel_num_authors":10,"rel_authors":[{"author_name":"Nicole T Cavanaugh","author_inst":"Northeastern University"},{"author_name":"Bryanna P Upton","author_inst":"Northeastern University"},{"author_name":"Eva V Franco","author_inst":"Northeastern University"},{"author_name":"Leticia Lima Angelini","author_inst":"Northeastern University"},{"author_name":"Cameron W Habib","author_inst":"Northeastern University"},{"author_name":"Juliana Xu","author_inst":"Northeastern University"},{"author_name":"Claire Chai","author_inst":"Brookline High School"},{"author_name":"Emily Wu","author_inst":"Northeastern University"},{"author_name":"Maor Bar-Peled","author_inst":"University of Georgia"},{"author_name":"Yunrong Chai","author_inst":"Northeastern University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Dissecting functional dynamics of fecal-derived in vitro stable microbial communities with metaproteomics","rel_doi":"10.64898\/2026.10.05.754657","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.754657","rel_abs":"Fecal-derived in vitro microbial communities represent promising models for investigating gut microbiome function and facilitating translational applications. However, the factors governing community establishment and the underlying mechanisms remain incompletely understood. We employed large-scale quantitative metaproteomics to investigate the functional and community dynamics of human fecal microbiomes cultured in three media over 25 serial passages. Our results demonstrated that both culture medium and donor-specific microbiome characteristics significantly influence community establishment. Taxon-specific functional analyses revealed nutrient availability in the medium and the microbial stress responses as key determinants of in vitro community establishment. Notably, the metabolism of mucin glycans in RapidAIM medium contributed to the maintenance of Bacteroidaceae species that were poorly supported in other media, resulting in an in vitro community that most closely resembled the uncultured fecal inoculum. Overall, these findings provide mechanistic insights into in vitro gut microbial community establishment, supporting further optimization and application of fecal-derived in vitro microbiome models.","rel_num_authors":11,"rel_authors":[{"author_name":"Angela Wang Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Emily Fekete Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Marybeth Creskey Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Zhibin Ning Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Janice Mayne Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Kai Cheng Dr.","author_inst":"Quadram Institute Bioscience, Norwich Research Park, University of East Anglia, Norwich, Norfolk, United Kingdom"},{"author_name":"Qing Wu Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Vanessa D'Costa Prof.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Xuguang Li Dr.","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Daniel Figeys Prof.","author_inst":"Quadram Institute Bioscience, Norwich Research Park, University of East Anglia, Norwich, Norfolk, United Kingdom"},{"author_name":"Xu Zhang Dr.","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Dissecting functional dynamics of fecal-derived in vitro stable microbial communities with metaproteomics","rel_doi":"10.64898\/2026.10.05.754657","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.754657","rel_abs":"Fecal-derived in vitro microbial communities represent promising models for investigating gut microbiome function and facilitating translational applications. However, the factors governing community establishment and the underlying mechanisms remain incompletely understood. We employed large-scale quantitative metaproteomics to investigate the functional and community dynamics of human fecal microbiomes cultured in three media over 25 serial passages. Our results demonstrated that both culture medium and donor-specific microbiome characteristics significantly influence community establishment. Taxon-specific functional analyses revealed nutrient availability in the medium and the microbial stress responses as key determinants of in vitro community establishment. Notably, the metabolism of mucin glycans in RapidAIM medium contributed to the maintenance of Bacteroidaceae species that were poorly supported in other media, resulting in an in vitro community that most closely resembled the uncultured fecal inoculum. Overall, these findings provide mechanistic insights into in vitro gut microbial community establishment, supporting further optimization and application of fecal-derived in vitro microbiome models.","rel_num_authors":11,"rel_authors":[{"author_name":"Angela Wang Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Emily Fekete Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Marybeth Creskey Miss","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Zhibin Ning Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Janice Mayne Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Kai Cheng Dr.","author_inst":"Quadram Institute Bioscience, Norwich Research Park, University of East Anglia, Norwich, Norfolk, United Kingdom"},{"author_name":"Qing Wu Dr.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Vanessa D'Costa Prof.","author_inst":"Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, Canada"},{"author_name":"Xuguang Li Dr.","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "},{"author_name":"Daniel Figeys Prof.","author_inst":"Quadram Institute Bioscience, Norwich Research Park, University of East Anglia, Norwich, Norfolk, United Kingdom"},{"author_name":"Xu Zhang Dr.","author_inst":"Regulatory Research Division, Centre for Oncology, Biostatistics, Research and Radiopharmaceuticals, Biologic and Radiopharmaceutical Drugs Directorate, Health "}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Bio-inspired chromatophore network model generates dynamic skin patterns akin to those observed in cephalopods","rel_doi":"10.64898\/2026.09.30.755305","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755305","rel_abs":"Cephalopod skin exhibits a wide range of dynamic visual displays, including traveling waves, light\/dark flashes, and flickering, all generated by muscle-regulated expansion and retraction of pigment-filled elastic sacs known as chromatophores. While central neural control is essential for high-level body-wide pattern coordination, experimental evidence from excised and denervated skin reveals that intricate spatiotemporal patterns can also emerge spontaneously in the skin. This raises questions about the respective roles of central versus peripheral control. To determine the simplest control necessary to generate such patterns, we developed ChromatoNet, a biophysical model of chromatophore arrays that includes mechanical interactions on 1- and 2-dimensional lattices with the excitability properties of radial muscles. With minimal external input, our modified Morris--Lecar model reproduces a rich repertoire of skin dynamics, including spontaneous flickering as well as traveling and spiral waves. Both spontaneous and stimulus-evoked waves emerge at an intrinsic resonant frequency, determined by model parameters. Propagation speeds remain stable across conditions and are consistent with the range observed in denervated skin preparations. The model generates diverse output states in response to local couplings and the time-dependence and shape of the input stimulation, with little top-down direction. The results provide a proof-of-principle that chromatophore\/muscle dynamics with minimal central neural driving can produce rich dynamic patterns.","rel_num_authors":9,"rel_authors":[{"author_name":"Yasemin Ersoy","author_inst":"University of Chicago"},{"author_name":"Robin Peter","author_inst":"University of California San Francisco"},{"author_name":"Gabriel Barello","author_inst":"PitchBook"},{"author_name":"Emily Meyer","author_inst":"University of Colorado Anschutz"},{"author_name":"Emily Mackevicius","author_inst":"Basis Research Institute"},{"author_name":"Stephen Senft","author_inst":"Marine Biological Laboratory"},{"author_name":"Roger T Hanlon","author_inst":"Marine Biological Laboratory"},{"author_name":"Bard Ermentrout","author_inst":"University of Pittsburgh"},{"author_name":"Stephanie Palmer","author_inst":"University of Chicago"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Bio-inspired chromatophore network model generates dynamic skin patterns akin to those observed in cephalopods","rel_doi":"10.64898\/2026.09.30.755305","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755305","rel_abs":"Cephalopod skin exhibits a wide range of dynamic visual displays, including traveling waves, light\/dark flashes, and flickering, all generated by muscle-regulated expansion and retraction of pigment-filled elastic sacs known as chromatophores. While central neural control is essential for high-level body-wide pattern coordination, experimental evidence from excised and denervated skin reveals that intricate spatiotemporal patterns can also emerge spontaneously in the skin. This raises questions about the respective roles of central versus peripheral control. To determine the simplest control necessary to generate such patterns, we developed ChromatoNet, a biophysical model of chromatophore arrays that includes mechanical interactions on 1- and 2-dimensional lattices with the excitability properties of radial muscles. With minimal external input, our modified Morris--Lecar model reproduces a rich repertoire of skin dynamics, including spontaneous flickering as well as traveling and spiral waves. Both spontaneous and stimulus-evoked waves emerge at an intrinsic resonant frequency, determined by model parameters. Propagation speeds remain stable across conditions and are consistent with the range observed in denervated skin preparations. The model generates diverse output states in response to local couplings and the time-dependence and shape of the input stimulation, with little top-down direction. The results provide a proof-of-principle that chromatophore\/muscle dynamics with minimal central neural driving can produce rich dynamic patterns.","rel_num_authors":9,"rel_authors":[{"author_name":"Yasemin Ersoy","author_inst":"University of Chicago"},{"author_name":"Robin Peter","author_inst":"University of California San Francisco"},{"author_name":"Gabriel Barello","author_inst":"PitchBook"},{"author_name":"Emily Meyer","author_inst":"University of Colorado Anschutz"},{"author_name":"Emily Mackevicius","author_inst":"Basis Research Institute"},{"author_name":"Stephen Senft","author_inst":"Marine Biological Laboratory"},{"author_name":"Roger T Hanlon","author_inst":"Marine Biological Laboratory"},{"author_name":"Bard Ermentrout","author_inst":"University of Pittsburgh"},{"author_name":"Stephanie Palmer","author_inst":"University of Chicago"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Electrical stimulation of the human pulvinar generates visual percepts","rel_doi":"10.64898\/2026.09.28.754866","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.28.754866","rel_abs":"Visual prostheses have targeted early structures in the visual pathway, including the retina, optic nerve, lateral geniculate nucleus, and visual cortex, to generate visual percepts. Stimulation of higher-order visual regions, which may better encode complex visual features, remains relatively unexplored. We tested whether electrical stimulation of the medial and inferior pulvinar elicits visual percepts in a patient with medically refractory epilepsy undergoing invasive seizure monitoring with intracranial electroencephalography. Bipolar stimulation (30 biphasic pulses, 0.5 ms per phase, 3 mA, 1 Hz) was delivered between adjacent pulvinar contacts while eye movements were tracked. Stimulation of different electrode pairs elicited visual percepts at distinct retinotopic locations (p = 0.010). Stimulation also altered cortical activity, producing an early power increase followed by gamma desynchronization in occipital and parietal regions (p < 0.001) and beta desynchronization in the lateral temporal region (p < 0.01). These findings suggest that pulvinar stimulation can generate visual percepts and modulate distributed cortical networks, supporting further investigation of the pulvinar as a target for vision restoration.","rel_num_authors":5,"rel_authors":[{"author_name":"William S. Kemball-Cook","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Edward R. Bader","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Alexis D. Boro","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Emad N. Eskandar","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Nathaniel J. Killian","author_inst":"Albert Einstein College of Medicine"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Forensic likelihood ratios for shotgun sequencing data from DNA mixtures","rel_doi":"10.64898\/2026.09.28.755155","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.28.755155","rel_abs":"Shotgun sequencing of DNA mixtures has the potential to become an important tool in forensic genetics, particularly for degraded samples or complex mixtures. However, the analysis of shotgun-sequenced mixtures is challenged by several confounding factors, including sequencing errors, population structure, the potential presence of relatives, linkage, and linkage disequilibrium. Additionally, the statistical methods currently available for such data are limited. Here, we develop likelihood ratios that summarize the evidence for the presence of a suspects DNA in a mixture, assuming genotypes of the suspect and the victim are available, while accounting for DNA from unknown contributors modeled either as general population contamination or as a single contaminating individual. We show that these likelihood ratios are not robust to model assumptions and can falsely support the presence of the suspects DNA when the true contributor is even a distant relative. We therefore propose a combined evidence score, {Lambda}: the likelihood ratio minimized over contamination models, reported only when the evidence favors the suspect over a hypothesized sibling by at least a factor of C (default C = 10) under at least one contamination model, and otherwise set to 1 (log {Lambda} = 0). In simulations based on 1000 Genomes data, {Lambda} retains nearly all power to detect true contributors at mixture proportions as low as 5% while eliminating the false positives produced by model mis-specification, population structure, and by untested relatives. The methods are implemented in the open-source program DNAMIXTURE, providing the forensic and population genetics community a resource for robustly identifying small individual contributions to a DNA mixture.","rel_num_authors":5,"rel_authors":[{"author_name":"Rasmus Nielsen","author_inst":"University of California, Berkeley"},{"author_name":"Eske Willerslev","author_inst":"University of Copenhagen"},{"author_name":"Thorfinn Sand Korneliussen","author_inst":": Kobenhavns Universitet Globe Institute"},{"author_name":"Abigail Ramsoe","author_inst":"University of Copenhagen"},{"author_name":"Martin Sikora","author_inst":"University of Copenhagen"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Nutrient-sensitive histone propionylation regulates T cell fate and function","rel_doi":"10.64898\/2026.10.01.756002","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756002","rel_abs":"Tissue microenvironments differ widely in nutrient composition; yet how local nutrient conditions shape epigenetic programs that direct immune cell fate is poorly understood. We identify histone lysine propionylation (Kpr) as a chromatin mechanism linking nutrient availability to T cell fate decisions. Proteomic analysis reveals that Kpr is broadly reduced in exhausted T cells. H3K18pr is enriched at stemness-associated loci in effector T cells and depleted upon exhaustion. Isoleucine and propionate supply propionyl-CoA in T cells, and restricted nutrient availability within the tumor microenvironment limits histone Kpr, promoting T cell exhaustion. Disrupting isoleucine catabolism in T cells further suppresses Kpr, without altering histone acetylation, and impairs T cell function and antitumor immunity in a manner rescued by propionate. Dietary supplementation of isoleucine and propionate increases Kpr in tumor infiltrating lymphocytes, limits exhaustion, and improves tumor control. These findings establish a microenvironment-chromatin axis crucial for antitumor immunity and amenable to nutritional intervention.","rel_num_authors":24,"rel_authors":[{"author_name":"Alison Jaccard","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Kelly Rome","author_inst":"Pathology and Laboratory Medicine, Childrens Hospital of Philadelphia, Philadelphia, PA, USA"},{"author_name":"Qihua Yang","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Shuo Zhang","author_inst":"Penn Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"},{"author_name":"Noah Ford","author_inst":"Center for Cellular Immunotherapies, 3400 Civic Center Boulevard, Building 421, SPE 8-105, Philadelphia, PA 19104"},{"author_name":"Adam Chatoff","author_inst":"Aging + Cardiovascular Discovery Center, Lewis Katz School of Medicine, Temple University, Philadelphia, PA 19140, USA"},{"author_name":"Tran Ngoc Van Le","author_inst":"Pathology and Laboratory Medicine, Childrens Hospital of Philadelphia, Philadelphia, PA, USA"},{"author_name":"Michael Noji","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Andrea Andress Huacachino","author_inst":"Aging + Cardiovascular Discovery Center, Lewis Katz School of Medicine, Temple University, Philadelphia, PA 19140, USA"},{"author_name":"Stephanie Stransky Lauar","author_inst":"Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, New York 10461, United States"},{"author_name":"Carlos Pondevida","author_inst":"Penn Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"},{"author_name":"Krittin Trihemasava","author_inst":"Pathology and Laboratory Medicine, Childrens Hospital of Philadelphia, Philadelphia, PA, USA"},{"author_name":"Laura V. Pinheiro","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Sanat Bhadsalve","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Eun Kyung Ko","author_inst":"Penn Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"},{"author_name":"Charles Salinas","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"},{"author_name":"Mariola M. Marcinkiewicz","author_inst":"Aging + Cardiovascular Discovery Center, Lewis Katz School of Medicine, Temple University, Philadelphia, PA 19140, USA"},{"author_name":"Brian C. Capell","author_inst":"Penn Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"},{"author_name":"Golnaz Vahedi","author_inst":"Penn Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA"},{"author_name":"Simone Sidoli","author_inst":"Department of Biochemistry, Albert Einstein College of Medicine, Bronx, New York, New York 10461, United States"},{"author_name":"Roddy S. OConnor","author_inst":"Center for Cellular Immunotherapies, 3400 Civic Center Boulevard, Building 421, Philadelphia, PA 19104"},{"author_name":"Will Bailis","author_inst":"Pathology and Laboratory Medicine, Childrens Hospital of Philadelphia, Philadelphia, PA, USA"},{"author_name":"Nathaniel W Snyder","author_inst":"Temple University Lewis Katz School of Medicine"},{"author_name":"Kathryn E. Wellen","author_inst":"Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Sex hormones gate the neuronal control of dendritic cell migration and immunity","rel_doi":"10.64898\/2026.10.01.754550","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.754550","rel_abs":"How endocrine states modulate local immune responses is a fundamental question in immunology. Sexual dimorphism is a striking example: females generally mount stronger immune responses than males, yet how sex hormones intersect with local signals is poorly understood. Here, we identify an endocrine-neuro-immune circuit in which sex hormones determine whether immune cells respond to nociceptor signals. In female skin, nociceptor-derived CGRP promotes dendritic cell (DC) migration and T cell priming indirectly through inflammatory monocytes. CGRP induces monocyte production of Activin A, which upregulates CXCR4 on DCs and promotes migration to draining lymph nodes. In males, androgen receptor signaling suppresses monocyte Activin A and silences this circuit. Disrupting the relay abolishes enhanced female immunity, whereas deleting androgen receptor in male monocytes restores neuronal control. Thus, sex hormones regulate immunity by determining how immune cells interpret neuronal signals, revealing how endocrine state can gate local neuroimmune communication to generate sex-specific immune responses.","rel_num_authors":5,"rel_authors":[{"author_name":"Konrad Knopper","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Tamar L Ben-Shaanan","author_inst":"Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot 7610001, Israel"},{"author_name":"Jinping An","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Ying Xu","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Jason G Cyster","author_inst":"1Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Sex hormones gate the neuronal control of dendritic cell migration and immunity","rel_doi":"10.64898\/2026.10.01.754550","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.754550","rel_abs":"How endocrine states modulate local immune responses is a fundamental question in immunology. Sexual dimorphism is a striking example: females generally mount stronger immune responses than males, yet how sex hormones intersect with local signals is poorly understood. Here, we identify an endocrine-neuro-immune circuit in which sex hormones determine whether immune cells respond to nociceptor signals. In female skin, nociceptor-derived CGRP promotes dendritic cell (DC) migration and T cell priming indirectly through inflammatory monocytes. CGRP induces monocyte production of Activin A, which upregulates CXCR4 on DCs and promotes migration to draining lymph nodes. In males, androgen receptor signaling suppresses monocyte Activin A and silences this circuit. Disrupting the relay abolishes enhanced female immunity, whereas deleting androgen receptor in male monocytes restores neuronal control. Thus, sex hormones regulate immunity by determining how immune cells interpret neuronal signals, revealing how endocrine state can gate local neuroimmune communication to generate sex-specific immune responses.","rel_num_authors":5,"rel_authors":[{"author_name":"Konrad Knopper","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Tamar L Ben-Shaanan","author_inst":"Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot 7610001, Israel"},{"author_name":"Jinping An","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Ying Xu","author_inst":"Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"},{"author_name":"Jason G Cyster","author_inst":"1Howard Hughes Medical Institute and Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Cholera toxin remodels intestinal immunity and suppresses systemic metabolism","rel_doi":"10.64898\/2026.09.29.755509","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755509","rel_abs":"Cholera toxin (CTx) is a potent enterotoxin and widely used mucosal adjuvant, yet the acute host response to CTx itself, in the absence of a co-administered antigen, remains vague. In this study, we integrated physiological and metabolic phenotyping with intestinal transcriptomics, epithelial imaging, immune profiling, hepatic gene-expression analysis, and paired microbiome profiling to characterize the response to a single oral CTx exposure in mice. Within 24 h, CTx remodeled immune-cell composition in both epithelial and lamina propria compartments, with responses shaped by sex and genetic background. Recurrent changes included increased epithelial group 3 innate lymphoid cells, reduced lamina propria ROR{gamma}t+ regulatory T cells, and decreased epithelial ILC1\/NK cells in males of both strains. CTx also increased villus DCLK1+ tuft cells and reduced MUC2 immunoreactivity. Jejunal transcriptomics revealed induction of inflammatory defense, glycolytic, autophagy, and lipid-utilization programs together with suppression of proliferative and mitochondrial programs, consistent with coordinated stress adaptation. These local changes were accompanied by rapid restructuring of the fecal microbial community and by systemic hypometabolism, despite markedly different hypothermic responses across strains. CTx also elicited a selective hepatic stress and metabolic program, including conserved suppression of Cyp7a1 across sexes and strains. Together, these findings show that CTx alone rapidly reorganizes the intestinal immune, epithelial, metabolic, and microbial environment while suppressing whole-body metabolism. This work provides an integrated framework for understanding the acute host response to CTx and for interpreting its widespread use as a mucosal adjuvant.","rel_num_authors":13,"rel_authors":[{"author_name":"Ana Cristina Roginski","author_inst":"Arizona State University, Biodesign Center for Health Through Microbiomes"},{"author_name":"Mahdieh Godazgar","author_inst":"Yale University School of Medicine, Department of Comparative Medicine"},{"author_name":"Caio Loureiro Salgado","author_inst":"Mayo Clinic, Department of Immunology"},{"author_name":"Gourab Lahiri","author_inst":"Arizona State University, School of Life Sciences"},{"author_name":"Cheyanne Woodrow","author_inst":"Arizona State University, School of Life Sciences"},{"author_name":"Thomas Hartley McDermott","author_inst":"Arizona State University, School of Life Sciences"},{"author_name":"Bruna Genisa Costa Lima","author_inst":"Arizona State University, School of Life Sciences"},{"author_name":"Gina Paola Rodriguez-Castano","author_inst":"Arizona State University, Biodesign Center for Health Through Microbiomes"},{"author_name":"Lee Voth-Gaeddert","author_inst":"Arizona State University, Biodesign Center for Health Through Microbiomes"},{"author_name":"Henrique Borges da Silva","author_inst":"Mayo Clinic, Department of Immunology"},{"author_name":"Marcelo O. Dietrich","author_inst":"Yale School of Medicine, Department of Comparative Medicine"},{"author_name":"Miyeko D Mana","author_inst":"Arizona State University, School of Life Sciences"},{"author_name":"Esther Borges Florsheim","author_inst":"Arizona State University, School of Life Sciences"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Facial color properties affect perceived age.","rel_doi":"10.64898\/2026.09.29.743707","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.743707","rel_abs":"Age is a fundamental social attribute that affects rights, responsibilities and even social status. Color information of the face can affect perceived age, but the nature of its contribution, independent of luminance information, remains underexplored. To better characterize the role of color in age perception, we conducted two experiments. In our first experiment, we tested whether natural age-related changes in facial color alone can drive changes in perceived age. In our second experiment, we manipulated red-green contrast across faces aged 18-91 and tested the effect of this manipulation of perceived youthfulness. Our findings demonstrate that natural age-related color changes do provide cues for age perception, dissociable from luminance information. We also found that the optimal red-green contrast level to make faces look the youngest was significantly higher than the originals, meaning that faces tended to appear younger when their redness was accentuated, even though average face redness increases with age. Our analysis revealed that younger faces required greater increases in redness level compared to their older counterparts to achieve the youngest appearance. These results suggest that the spatial distribution of redness contributes to apparent youthfulness, especially in younger faces.","rel_num_authors":3,"rel_authors":[{"author_name":"Jean Hsieh","author_inst":"UNSW, Sydney"},{"author_name":"Colin W.G. Clifford","author_inst":"UNSW, Sydney"},{"author_name":"Erin Goddard","author_inst":"UNSW, Sydney"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"The G\u03b1i\/o GPCR LPAR2 Acts as a Non-Classical Factor for Aldosterone Induced Injury in a Cardiomyocyte Model","rel_doi":"10.64898\/2026.09.29.755539","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755539","rel_abs":"Aldosterone is a key regulator of systemic sodium, potassium, and fluid homeostasis. Chronic elevation of aldosterone, as observed in primary aldosteronism, chronic heart and kidney diseases, promotes cardiac hypertrophy, inflammation, fibrosis, and heart failure, which are further enhanced in aging. Although these pathological effects are primarily attributed to the mineralocorticoid receptor (MR), emerging evidence suggests roles for nonclassical G protein-coupled receptor (GPCR) signaling. We identified lysophosphatidic acid receptor 2 (LPAR2) as a novel GPCR candidate that mediates aldosterone signaling in cardiomyocytes. Using AC16 human cardiomyocyte cells and reporter gene assays, we demonstrate that aldosterone activates a Gi\/o-dependent GPCR pathway. Pharmacological inhibition of LPAR2 internalization confirms its specific reaction to aldosterone. Functional studies revealed that aldosterone-induced cardiomyocyte injury requires both MR and LPAR2, where specific antagonists to both receptors reduced the ability of aldosterone to induce collagen expression and cell death markers. These findings uncover a previously unrecognized non-classical mechanism of aldosterone action in the heart and highlight LPAR2 as a promising therapeutic target for aldosterone-driven cardiovascular disease.","rel_num_authors":3,"rel_authors":[{"author_name":"Saswat Kumar Mohanty","author_inst":"Brown University Division of Biology and Medicine"},{"author_name":"Rujun Gong","author_inst":"University of Toledo College of Medicine"},{"author_name":"Marc Tatar","author_inst":"Brown University Division of Biology and Medicine"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Molecular anatomy of the glomerular filtration barrier reveals topology-encoded albumin sieving","rel_doi":"10.64898\/2026.09.30.755551","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755551","rel_abs":"The kidney filters plasma rapidly while retaining albumin, yet where and how this selectivity is encoded within the glomerular filtration barrier remain unresolved. Here we combine cryo-electron tomography (cryo-ET) of vitrified mouse glomeruli with structure-resolved transport modelling to predict albumin passage from the native three-dimensional architecture of the barrier. Among the three barrier layers, endothelial fenestrae and the flexible Nephrin-Neph1 slit-diaphragm lattice are substantially permeable to albumin. The glomerular basement membrane (GBM) instead provides the dominant restriction through steric exclusion governed by void-network topology. In local GBM reconstructions, water traverses broadly connected void space, whereas narrow throats exclude albumin, leaving few accessible paths. To scale this mechanism to the tissue level, we combine structural statistics from local cryo-ET volumes with mesoscale measurements of GBM heterogeneity to generate representative ensembles. Integrating these ensembles with other layers predicts whole-barrier albumin sieving in close agreement with an independent measurement. The topology-driven mechanism also explains early filtration failure in Alport syndrome mice, in which collagen-IV disruption remodels the GBM network and opens albumin-accessible paths while cellular interfaces remain preserved. These findings identify the structural origin of glomerular albumin selectivity and establish a quantitative route from locally resolved architecture to tissue-scale physiology.","rel_num_authors":11,"rel_authors":[{"author_name":"Xing Wang","author_inst":"Peking University"},{"author_name":"Weiyan Zheng","author_inst":"Peking University"},{"author_name":"Wenjing Du","author_inst":"Peking University"},{"author_name":"Dongxuan Chi","author_inst":"Peking University First Hospital"},{"author_name":"Wenjia Fan","author_inst":"Peking University"},{"author_name":"Ruoheng Mo","author_inst":"Peking University"},{"author_name":"Jie Ding","author_inst":"Peking University First Hospital"},{"author_name":"Li Yang","author_inst":"Peking University First Hospital"},{"author_name":"Jing Nie","author_inst":"Peking University First Hospital"},{"author_name":"Ming Han","author_inst":"Peking University"},{"author_name":"Qiang Guo","author_inst":"Peking University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"A map of RBP-miRNA regulatory connections for deciphering the mechanisms of transcriptome remodeling in cancer","rel_doi":"10.64898\/2026.09.29.755492","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755492","rel_abs":"Micro-RNAs (miRNAs) are key post-transcriptional regulators of gene expression that influence cancer progression and outcome. Whereas transcriptional dysregulation of miRNA abundance underlies abnormal functionality of some miRNAs in cancer, emerging data points to RNA-binding proteins (RBPs) as prominent post-transcriptional regulators of miRNA activity. Here, by modelling the regulon activities of well-characterized miRNA families in RNA-seq data of a comprehensive collection of RBP inhibition experiments, human cell lines and tissues, we report a map of regulatory connections between 34 RBPs and 28 miRNAs. Furthermore, through a global analysis of the abundance as well as the activity of miRNAs in thousands of tumor and control samples from 17 human cancers, we show that RBP-driven regulation of miRNA activity is common in tumors and contributes to the heterogeneity in miRNA activity profiles. We uncover a set of RBPs that regulate the activity of tumor-suppressor and oncogenic miRNAs, including miR-29-3p, miR-17-5p and miR-19-3p. Of particular interest, we describe a pan-cancer negative regulatory role for DDX55 on the activity of the miR-29-3p family, a critical miRNA family with tumor suppressor functions that is involved in most human cancers. Our functional studies confirm that DDX55 inhibition restores the gene-silencing activity of miR-29-3p and reduces cancer cell viability. Overall, our study provides the first pan-cancer investigation of functional regulatory connections between RBPs and miRNAs, and highlights RBPs whose interventional modulation may serve as a new approach to reprogram abnormal miRNA activities in cancer.","rel_num_authors":15,"rel_authors":[{"author_name":"Gabrielle Perron","author_inst":"McGill University"},{"author_name":"Mohan Amaravadi","author_inst":"McGill University"},{"author_name":"Hsin-Wei Tseng","author_inst":"McGill University"},{"author_name":"Pouria Jandaghi","author_inst":"McGill University"},{"author_name":"Elham Moslemi","author_inst":"McGill University"},{"author_name":"Tamiko Nishimura","author_inst":"McGill University"},{"author_name":"Maryam Rajaee","author_inst":"McGill University"},{"author_name":"Rached Alkallas","author_inst":"McGill University"},{"author_name":"Bruce Culbertson","author_inst":"University of California, San Francisco"},{"author_name":"Kristle Garcia","author_inst":"University of California, San Francisco"},{"author_name":"Ian R Watson","author_inst":"McGill University"},{"author_name":"Hani Goodarzi","author_inst":"University of California, San Francisco"},{"author_name":"Thomas Duchaine","author_inst":"McGill University"},{"author_name":"Yasser Riazalhosseini","author_inst":"McGill University"},{"author_name":"Hamed S Najafabadi","author_inst":"McGill University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Integrating single-cell and bulk transcriptomes identifies neuronal heat-stress-associated candidate genes in a reef-building coral","rel_doi":"10.64898\/2026.10.05.756843","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756843","rel_abs":"Cell-type-specific molecular responses are obscured in bulk RNA sequencing, whereas generating matched single-cell datasets across environmental conditions remains costly and technically challenging, particularly in non-model organisms. Here, we present a workflow that integrates existing bulk and single-cell RNA-seq resources to prioritize cell-type-associated environmental-response genes. We demonstrate the workflow by examining heat-stress-associated neuronal genes in the reef-building coral Stylophora pistillata. Neuronal genes were first identified based on cell type-specific expression in single-cell transcriptomic data and then intersected with differentially expressed genes from bulk RNA-seq datasets under heat-stress. In parallel, we applied a deconvolution approach to infer cell type-specific expression changes directly from bulk data, independently capturing neuronal transcriptional responses. This integrated pipeline reduced thousands of heat-responsive genes previously identified in bulk RNA-seq studies to nine heat-associated, neuron-enriched candidates. Eight of the nine candidates showed their highest mean expression in the same neuronal subcluster. Targeted sequence-based characterization supported the identification of a TRPA-family ion channel, two calmodulin\/centrin-family Ca2+-binding proteins, and a Class A\/rhodopsin-like GPCR of unresolved ligand specificity. Two additional candidates were predicted secreted proteins belonging to conserved coral protein families, while the molecular functions of the remaining candidates remained unresolved. Their coordinated regulation suggests heat-associated remodeling of neuronal sensory and intracellular signaling processes. Our workflow provides a scalable framework for extracting cell type-associated molecular responses from existing transcriptomic resources and prioritizing candidates for further investigation. More broadly, it offers a generalizable strategy for investigating cell type-specific gene expression responses across organisms, cell types, and environmental conditions without requiring new single-cell datasets.","rel_num_authors":3,"rel_authors":[{"author_name":"Ruiqi Li","author_inst":"University of Souther California"},{"author_name":"Martin Tresguerres","author_inst":"UC San Diego"},{"author_name":"Carly D Kenkel","author_inst":"University of Southern California"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Hormonal factors are poor indicators of endometriosis pain","rel_doi":"10.64898\/2026.09.29.755136","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755136","rel_abs":"Endometriosis is a common yet understudied condition in which sex hormones play a key role in the etiology and pathophysiology of the disease. Sex hormones are dysregulated in endometriosis and are pharmacologically targeted to reduce symptoms including pain, but the relationships between endometriosis-related pain with sex hormone levels and their receptors are not clear. In 60 women previously diagnosed or undergoing laparoscopic surgery for the diagnosis of endometriosis, we collected patient-reported endometriosis\/pelvic pain intensity in the last 30 days, pain interference scale, and the Endometriosis Health Profile 30 (EHP30) pain subscale. In a sub-sample of 38 participants, biopsies from control non-lesion pelvic peritoneum and endometrial lesion tissues were collected during surgery to analyze the tissue abundance of the primary receptors for estrogen, as well as androgen, progesterone, and prolactin receptors. Serum was collected to analyze systemic sex hormone levels including estradiol, prolactin, progesterone, and testosterone. Between tissues, we found elevated transcript levels for estrogen receptor alpha (ESR1) in lesions, but no difference in estrogen receptor beta (ESR2) transcript levels between tissue samples were found. Relating tissue receptor transcript levels to clinical pain revealed that only ESR1 and PGR in lesions were negatively associated with endometriosis\/pelvic pain intensity, however, following false discovery rate correction the association with ESR1 was no longer statistically significant. No other tissue or systemic factors were associated with clinical pain outcomes. Together, these data demonstrate unique alterations in receptor abundance in lesions yet select transcript levels only weakly relate to pain in endometriosis.","rel_num_authors":11,"rel_authors":[{"author_name":"Adam J Dourson","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Rachel L Cundiff-O'Sullivan","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Juliet M Mwirigi","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Holly R Hoefgen","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Maggie Dwiggins","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Elise Bardawil","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Thomas J Baranski","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Benjamin P Kay","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Robert Gereau IV","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Whitney T Ross","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"},{"author_name":"Hadas Nahman-Averbuch","author_inst":"Washington University School of Medicine; St. Louis, MO, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Contraction type dependence of serial sarcomere addition following resistance training","rel_doi":"10.64898\/2026.09.29.755478","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755478","rel_abs":"Longitudinal muscle growth occurs through the addition of sarcomeres in series, a process termed serial sarcomerogenesis. To investigate contraction mode dependence of sarcomerogenesis in Sprague-Dawley rats (n=36, 14 to18 weeks, ~468g), we compared the effects of isometric, eccentric, and concentric training (4 to 6 weeks; 3 times\/week) on morphological and mechanical adaptations of the plantar flexors. Isometric training was performed at a joint angle corresponding to the plateau nearing the descending limb of the force length relationship, eccentric contractions began at a shorter muscle length and lengthened to this same joint position, and concentric contractions started at this lengthened position but then actively shortened. Owing to the rapid regulation of serial sarcomere number the 4-and 6-week timepoints were collapsed. While force output increased across all training modes (+16%; p<0.05), longitudinal muscle growth was regulated by contraction type. Both isometric and eccentric training were highly effective at increasing serial sarcomere number when optimal loading conditions (high forces at longer lengths) are provided (+7-9%; p<0.05). Concentric training, even when initiated at long lengths with high forces was not an effective stimulus for longitudinal remodelling (+2%; p>0.05). Therefore, these findings identify the mechanical loading environment associated with isometric and eccentric training as a key driver of serial sarcomerogenesis.","rel_num_authors":7,"rel_authors":[{"author_name":"Amelia Rilling","author_inst":"University of Guelph"},{"author_name":"Alexander M Zero","author_inst":"University of Guelph"},{"author_name":"Alexandra Kirkup","author_inst":"University of Guelph"},{"author_name":"Maxum Stratford","author_inst":"University of Guelph"},{"author_name":"Kathryn Chapman","author_inst":"University of Guelph"},{"author_name":"Avery Hinks","author_inst":"University of Guelph"},{"author_name":"Geoffrey A Power","author_inst":"University of Guelph"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Recent effective population size of the snowy owl (Bubo scandiacus) tracks historical climate variation","rel_doi":"10.64898\/2026.09.30.752484","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.752484","rel_abs":"Arctic ecosystems are undergoing rapid climate warming, providing an opportunity to examine molecular evolution under environmental stress. Here, we used whole-genome resequencing to assess population structure, genetic diversity, and recent demographic history in the snowy owl (Bubo scandiacus), a highly mobile Arctic apex predator classified as Vulnerable by the IUCN. We analysed genome-wide data from individuals sampled across the species' circumpolar range using a chromosome-level reference genome. Population genomic analyses revealed an absence of detectable population structure, indicating extensive gene flow and near-panmixia across continents. Genome-wide nucleotide diversity was low ({pi}= 2.47 x 10^(-4)), while runs of homozygosity were dominated by short tracts, indicating limited standing genetic variation despite little evidence for recent close inbreeding. Our demographic inference revealed a sustained decline in effective population size over the past ~1,600 years, a pronounced reduction coinciding with the Medieval Warm Period followed by a partial recovery during the subsequent cooler interval. This direct, measurable effect of past climate warming on effective population size raises concerns for the long-term survival of the snowy owl. Our results demonstrate that high connectivity and low levels of recent inbreeding have not necessarily buffered this species against climate-driven demographic erosion of genetic diversity. This study highlights the value of using whole-genome population genomics to inform genomic monitoring and conservation decision-making in rapidly changing environments.","rel_num_authors":14,"rel_authors":[{"author_name":"Emily Louise Gilbert Enevoldsen","author_inst":"Department of Biosciences, University of Oslo, Oslo, Norway"},{"author_name":"Diana Aguilar-G\u00f3mez","author_inst":"Department of Ecology and Evolutionary Biology, University of California Los Angeles, CA, USA"},{"author_name":"Karl-Otto Jacobsen","author_inst":"Norwegian Institute for Nature Research, Fram Centre, Troms\u00f8, Norway"},{"author_name":"Roar Solheim","author_inst":"Natural History Museum, University of Agder, Kristiansand, Norway"},{"author_name":"Ingar Jostein \u00d8ien","author_inst":"BirdLife Norway, Trondheim, Norway"},{"author_name":"Tomas Aarvak","author_inst":"BirdLife Norway, Trondheim, Norway"},{"author_name":"Siv Nam Khang Hoff","author_inst":"Department of Biosciences, University of Oslo, Oslo, Norway"},{"author_name":"Oliver Sven Kersten","author_inst":"Department of Biosciences, University of Oslo, Oslo, Norway"},{"author_name":"Karen L Wiebe","author_inst":"Department of Biology, University of Saskatchewan, Saskatoon, Canada"},{"author_name":"Jean-Fran\u00e7ois Therrien","author_inst":"Acopian Center for Conservation Learning, Hawk Mountain Sanctuary, Orwigsburg, PA, United States"},{"author_name":"Irina Menyushina","author_inst":"Dept of Integrative Biology, University of California Berkeley, California, USA"},{"author_name":"Rasmus Nielsen","author_inst":"Dept of Integrative Biology, University of California Berkeley, California, USA"},{"author_name":"Sanne Boessenkool","author_inst":"Department of Biosciences, University of Oslo, Oslo, Norway"},{"author_name":"Helle Tessand Baalsrud","author_inst":"Department of Biosciences, University of Oslo, Oslo, Norway; Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, \u00c5s, Norway"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"How spiders use dragline silk to control abseiling and jumping","rel_doi":"10.64898\/2026.09.29.755426","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755426","rel_abs":"Spiders arrest their fall by abseiling on dragline silk, varying silk release rate to avoid excessive strains that could break the thread. To understand how this is achieved, we develop a minimal dynamical model of abseiling and formulate a time-optimal control problem subject to physical limits on silk strain and dragline spinning rate. We find that the optimal trajectory includes an interval over which the strain is constant, resulting in uniform deceleration consistent with published experiments. To test the generality of this strategy, we then turn to a distinct extreme motor behavior seen in jumping spiders: using a dragline anchored at the takeoff site to correct their orientation while jumping at speeds exceeding 100 body lengths per second. We show that the same constant-strain strategy suffices to counteract the initial body rotation and ensure an upright landing without significant loss of range. Together, our theoretical framework suggests how strain regulation may serve as a strategy for controlling extreme movements such as abseiling seen in many spiders and may be specialized to tasks such as aerial braking and reorientation in jumping spiders.","rel_num_authors":3,"rel_authors":[{"author_name":"Petur Bryde","author_inst":"M I T"},{"author_name":"Paul Shamble","author_inst":"Yale University"},{"author_name":"L Mahadevan","author_inst":"Harvard University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"The single-PDZ domain protein TXBP-3 regulates contractility in the C. elegans spermatheca","rel_doi":"10.64898\/2026.10.05.756805","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756805","rel_abs":"In the C. elegans reproductive system, oocyte transit through the spermatheca relies on parallel calcium and Rho-dependent signaling pathways to regulate actomyosin contractility. Here, we identify the conserved single-PDZ domain protein TXBP-3\/TAX1BP3 as a dosage-dependent regulator of spermathecal contractility. TXBP-3 is expressed in contractile tissues, including the spermatheca and spermathecal-uterine (sp-ut) valve. Animals lacking txbp-3 do not display overt phenotypes or defects in ovulation. However, in nematodes expressing the genetically encoded calcium sensor GCaMP, deletion of txbp-3 results in more rapid transit of embryos through the spermatheca. Conversely, tissue-specific overexpression of TXBP-3 results in slower transit times due to hypercontraction of the spermathecal neck and sp-ut valve, causing oocyte severing and failures of embryos to exit the spermatheca. We find TXBP-3 promotes the active phosphorylated state of the calcium\/calmodulin-dependent protein kinase II (CaMKII) UNC-43. When TXBP-3 is overexpressed or unc-43 is depleted, ovulations in which the embryo fails to exit show disrupted calcium signaling. Additionally, TXBP-3 functions independently of the RhoGEF RHGF-1 and in parallel with the RhoGAP SPV-1 to maintain the alignment of actin fiber bundles and protect embryo structural integrity. Together, our results establish TXBP-3 as a regulator of contractility, kinase activation, and cytoskeletal architecture in contractile tissues.","rel_num_authors":2,"rel_authors":[{"author_name":"Maria Khalid","author_inst":"Northeastern University"},{"author_name":"Erin J Cram","author_inst":"Northeastern University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"TMEM209\/NPP-28 partitions PLK-1 between the nuclear envelope and nuclear interior during mitosis","rel_doi":"10.64898\/2026.10.05.752757","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.752757","rel_abs":"The onset of mitosis in animal cells is marked by nuclear envelope breakdown (NEBD), which requires coordinated disassembly of nuclear pore complexes (NPCs) and the nuclear lamina. Polo-like kinase 1 (Plk1\/PLK-1) initiates NEBD through phosphorylation of NPC components, but mechanisms that spatially regulate PLK-1 between NPCs and the nuclear interior are unclear. Here, we identify the Caenorhabditis elegans TMEM209 homolog NPP-28 as a transmembrane nucleoporin that concentrates PLK-1 at the nuclear envelope while limiting its nuclear accumulation to promote NEBD. We identify docking sites within NPP-28 that mediate PLK-1 nuclear envelope-association. NPP-28 is phosphorylated by PLK-1 in vitro, and mutational analysis suggests that NPP-28-mediated docking facilitates NEBD, whereas phosphorylation prevents premature NEBD. Simultaneous loss of npp-28 and the transmembrane nucleoporin npp-12\/gp210 exacerbates mitotic NEBD defects in early embryos and causes severe defects in germline development. Together, our findings identify NPP-28 as a spatial regulator of PLK-1 during mitosis with functional relationships with other conserved transmembrane nucleoporins depending on context.","rel_num_authors":11,"rel_authors":[{"author_name":"Victoria Puccini de Castro","author_inst":"Yale University"},{"author_name":"Sarah R. Barger","author_inst":"Yale University"},{"author_name":"Razvan Azamfirei","author_inst":"Yale University"},{"author_name":"Tiffany Y. Su","author_inst":"Ludwig Institute for Cancer Research"},{"author_name":"Rebecca A. Green","author_inst":"University of California San Diego, Ludwig Institute for Cancer Research"},{"author_name":"Ronald J. Biggs","author_inst":"Ludwig Institute for Cancer Research"},{"author_name":"Frances E. Q. Moore","author_inst":"Yale University"},{"author_name":"Shoken Lee","author_inst":"Yale University"},{"author_name":"Karen Oegema","author_inst":"University of California San Diego, Ludwig Institute for Cancer Research"},{"author_name":"Pablo Lara-Gonzalez","author_inst":"University of California Irvine"},{"author_name":"Shirin Bahmanyar","author_inst":"Yale University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"HIV-1 Ribonucleoprotein Complex Organization Facilitates Assembly of the Mature HIV-1 Capsid","rel_doi":"10.64898\/2026.10.05.756791","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756791","rel_abs":"The encapsulation of the viral RNA condensate inside the capsid is a crucial step in the late stages of the HIV-1 replication cycle. While it is agreed that RNA encapsulation depends on RNA-bound integrase (IN), that capsid-bound IN-RNA filaments are present within the capsid, and that the ribonucleoprotein (RNP) complex takes up only a fraction of the capsid volume, the timing of filament formation and ribonucleoprotein (RNP) encapsulation are unclear. Here, we ran virion-scale, coarse grained molecular dynamics simulations to identify how the organization of the RNP and IN in particular affects mature capsid assembly and genome encapsulation. These virion-scale simulations allow for direct comparison between experimental capsid morphologies and those self-assembled in the simulations. It was found, when relatively few tetramers are on the RNP surface, that IN tetramers could facilitate RNA encapsulation without filling a significant fraction of the capsid volume, but do not form a capsid-templated filament. When octameric IN-RNA filaments are modeled, it was found that WT-like capsid morphologies form only when the IN is organized as a single long filament, in agreement with recent experimental suggestions. These capsids are more conical and elongated than the capsids assembled around the RNP with tetrameric IN. Thus, we suggest the IN-RNA filament assembles ahead of the capsid and directs it to its final conical morphology, consistent with the experimental observation of less elongated capsids when IN oligomerization is disrupted.","rel_num_authors":5,"rel_authors":[{"author_name":"Curt Waltmann","author_inst":"University of Chicago"},{"author_name":"Manish Gupta","author_inst":"University of Chicago"},{"author_name":"Alan N. Engelman","author_inst":"Dana-Farber Cancer Institute"},{"author_name":"Dmitry Lyumkis","author_inst":"The Salk Institute for Biological Studies"},{"author_name":"Gregory A Voth","author_inst":"University of Chicago"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"SARS-CoV-2 Nucleocapsid Protein forms biomolecular condensates and interacts with ALS-associated RNA binding proteins in vitro","rel_doi":"10.64898\/2026.09.29.755449","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755449","rel_abs":"As we have entered the endemic phase of COVID-19, there is a need to assess the long-term effects of SARS-CoV-2 infection on the trajectory of neurodegenerative disorders. Herein, we investigate whether the SARS-CoV-2 RNA-binding nucleocapsid protein (NCP; N-protein) may influence molecular processes relevant to motor neuron degeneration in amyotrophic lateral sclerosis (ALS). We detected N-protein immunoreactivity in ALS spinal cord motor neurons, including cytoplasmic N-protein-positive puncta that colocalized with cytoplasmic TAR DNA-binding protein 43 (TDP-43). In vitro, optogenetically induced N-protein biomolecular condensates (BMCs) showed reversible, liquid-like behavior and recovered after photobleaching. Using this model, we found that these condensates colocalized with TDP-43 and the RNA-binding proteins G3BP1\/2, PABPC1 and TIA1. Condensate formation was associated with TDP-43 cytoplasmic mislocalization, altered TARDBP expression, and altered exon 3 splicing of POLDIP3. The N-terminal portion of N-protein influenced BMC formation, whereas truncated C-terminal proteoforms did not form detectable BMCs or show detectable TDP-43 colocalization in this assay. Extending these observations to a human cell model, we show that optogenetically induced N-protein BMCs colocalize with TDP-43 in human iPSC-derived motor neurons. Collectively, these findings support further investigation into potential molecular links between SARS-CoV-2 exposure and the trajectory of neurodegenerative disease.","rel_num_authors":7,"rel_authors":[{"author_name":"Joseph-Patrick W. E. Clarke","author_inst":"Western University"},{"author_name":"Alexandra Keating","author_inst":"Western University"},{"author_name":"Veronica Noches","author_inst":"Western University"},{"author_name":"Crystal McLellan","author_inst":"Western University"},{"author_name":"Davide Dulcis","author_inst":"University of California San Diego School of Medicine"},{"author_name":"John Ravits","author_inst":"University of California San Diego School of Medicine"},{"author_name":"Michael Joseph Strong","author_inst":"Western University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"p38\u03b1 MAPK integrates opposing oncogenic APC\/\u03b2-catenin\/TCF and GUCY2C tumor-suppressor axes in colorectal cancer","rel_doi":"10.64898\/2026.10.05.756833","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756833","rel_abs":"Introduction: Sporadic colorectal cancers (CRCs) form following initiating APC mutations, inducing constitutive {beta}-catenin\/TCF signaling. Similarly, the guanylyl cyclase C (GUCY2C) tumor suppressor axis is universally silenced in CRC. While the GUCY2C receptor is retained, loss of its paracrine hormones guanylin (GUCA2A) and uroguanylin (GUCA2B) is among the earliest events in transformation. Mutant APC\/{beta}-catenin\/TCF signaling driving CRC transcriptionally silences GUCY2C hormone expression while suppressing that oncogenic pathway reconstitutes hormone production opposing tumorigenesis. p38 opposes tumor initiation, and its loss promotes transformation in chemical and genetic mouse models of CRC. In healthy intestine, p38 supports a gradient of epithelial differentiation along the crypt-surface axis. Here, we reveal that p38 links regulation of oncogenic APC\/{beta}-catenin\/TCF signaling and GUCY2C hormone expression. Methods: Regulation of p38 by APC\/{beta}-catenin\/TCF signaling was defined in four genetically engineered human CRC cell lines with conditional oncogenic APC\/{beta}-catenin\/TCF signaling and healthy human colon organoids. Expression of p38 was eliminated from conditional human CRC cell lines by pharmacological inhibition, RNA knockdown, and CRISPR\/Cas9 gene editing. Transcriptomic analysis of these cells by RNA sequencing defined the set of genes regulated by APC\/{beta}-catenin\/TCF signaling controlled through p38. Results: In CRC cell lines, APC\/{beta}-catenin\/TCF signaling suppressed p38 phosphorylation and activity, whereas inhibition of APC\/{beta}-catenin\/TCF restored p38 signaling. In the absence of APC\/{beta}-catenin\/TCF signaling, inhibiting p38 repressed GUCY2C hormone expression. Inhibiting APC\/{beta}-catenin\/TCF signaling enriched phosphorylated p38 at the GUCA2A promoter. In that context, analysis of the CPTAC proteomic database revealed that phosphorylation of p38 and its upstream kinases MKK3 and MKK4 was reduced in human CRC. Finally, transcriptomic analysis revealed that p38 is a critical signaling node controlling the expression of a substantial subset of APC\/{beta}-catenin\/TCF-regulated genes in human CRC cells and patient tumors. Conclusions: APC\/{beta}-catenin\/TCF signaling inhibits p38 phosphorylation and transcriptional activity, suppressing GUCA2A and GUCA2B expression and functionally silencing the retained GUCY2C receptor. These findings identify p38 as a signaling intermediary integrating oncogenic APC\/{beta}-catenin\/TCF activity to extinction of the GUCY2C tumor-suppressor axis and reveal a broader p38-dependent component of the APC\/{beta}-catenin\/TCF-regulated transcriptome.","rel_num_authors":10,"rel_authors":[{"author_name":"Ariana A Entezari","author_inst":"Thomas Jefferson University"},{"author_name":"Adi Caspi","author_inst":"Thomas Jefferson University"},{"author_name":"Jasmine R Alvarez","author_inst":"Thomas Jefferson University"},{"author_name":"Andrew E Evans","author_inst":"Thomas Jefferson University"},{"author_name":"Jeffrey A Rappaport","author_inst":"Johns Hopkins University"},{"author_name":"Thomas J M Kuret","author_inst":"Thomas Jefferson University"},{"author_name":"Allison S Doermann","author_inst":"Thomas Jefferson University"},{"author_name":"Ramkrishna Mitra","author_inst":"Thomas Jefferson University"},{"author_name":"Adam E Snook","author_inst":"Thomas Jefferson University"},{"author_name":"Scott A Waldman","author_inst":"Thomas Jefferson University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Extracellular vesicle cross-linking coupled with solid-phase purification facilitates discovery of ribonucleoprotein complexes assembled on EV RNAs.","rel_doi":"10.64898\/2026.10.03.756357","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.03.756357","rel_abs":"Extracellular vesicles (EVs) are fundamental mediators of intercellular communication that transfer macromolecular cargo, including proteins and RNAs, to functionally reprogram recipient cells. However, the molecular processes by which transferred ribonucleoprotein (RNP) complexes engage recipient host machinery to influence cellular behavior are poorly understood, primarily due to a dearth of methods capable of tracking these post-transfer interactions. To address this gap, we developed two complementary chemical biology platforms: EV-CLASP and EV(r)-CLASP. While EV-CLASP maps the native, intra-vesicular RNP landscape packaged within the EV, EV(r)-CLASP captures post-transfer dynamics by identifying the host proteins that directly associate with EV-derived RNAs following cellular uptake. Both approaches leverage metabolic labeling and photo-crosslinking for high-specificity recovery. Donor cells are cultured with 4-thiouridine (4SU) to biosynthetically label newly synthesized RNAs during EV biogenesis. Purified EVs can be crosslinked using 365 nm UV light to capture intra-vesicular RNP composition. Alternatively, 4SU-labeled EVs can be delivered to recipient cells and subsequently crosslinked to identify the primary physical interactions formed within the recipient-cell environment. Crosslinked RNP complexes are isolated under stringent conditions using solid-phase reversible beads to minimize background, followed by quantitative mass spectrometry for protein identification. Together, EV-CLASP and EV(r)-CLASP provide a robust, versatile framework for defining the dynamic RNP assemblies that facilitate extracellular RNA communication, offering a powerful toolkit to uncover novel RNA-associated regulatory networks, therapeutic targets, and biomarkers across diverse biological and disease contexts.","rel_num_authors":9,"rel_authors":[{"author_name":"Rajat Dhyani","author_inst":"Department of Biochemistry, Vanderbilt University, Nashville, TN, USA"},{"author_name":"Stephen Clarke","author_inst":"Department of Biochemistry, Vanderbilt University, Nashville, TN, USA"},{"author_name":"Masashi Kuroda","author_inst":"Division of Diabetes and Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA"},{"author_name":"Yohei Sanada","author_inst":"Division of Diabetes and Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA"},{"author_name":"Marc Gorum II","author_inst":"Department of Biomedical Sciences, Meharry Medical College, Nashville, TN, USA."},{"author_name":"Bahnisikha Barman","author_inst":"Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA"},{"author_name":"Alissa Weaver","author_inst":"Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA."},{"author_name":"Takahisa Nakamura","author_inst":"Division of Diabetes and Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA."},{"author_name":"Manuel Ascano","author_inst":"Department of Biochemistry, Vanderbilt University, Nashville, TN, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats","rel_doi":"10.64898\/2026.10.01.756043","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756043","rel_abs":"Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.","rel_num_authors":55,"rel_authors":[{"author_name":"Apurva S. Chitre","author_inst":"University of California San Diego"},{"author_name":"Thiago Missfeldt Sanches","author_inst":"University of California San Diego"},{"author_name":"Gavrila Ang","author_inst":"University of California San Diego"},{"author_name":"Nana K. Amissah","author_inst":"University at Buffalo"},{"author_name":"Rodolfo Avila","author_inst":"University of California San Diego"},{"author_name":"Hannah Bimschleger","author_inst":"University of California San Diego"},{"author_name":"Paola Campo","author_inst":"University of California San Diego"},{"author_name":"Nazzareno Cannella","author_inst":"University of Camerino"},{"author_name":"Denghui Chen","author_inst":"University of California San Diego"},{"author_name":"Riyan Cheng","author_inst":"University of California San Diego"},{"author_name":"Katarina A. Cohen","author_inst":"University of California San Diego"},{"author_name":"Ayteria D. Crow","author_inst":"Medical University of South Carolina"},{"author_name":"Eric Dereschewitz","author_inst":"Medical University of South Carolina"},{"author_name":"Michelle R. Doyle","author_inst":"University of California San Diego"},{"author_name":"Maya Eid","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Anthony M. George","author_inst":"University at Buffalo"},{"author_name":"Aidan P. Horvath","author_inst":"University of Michigan"},{"author_name":"Keita Ishiwari","author_inst":"University at Buffalo"},{"author_name":"Benjamin B. Johnson","author_inst":"University of California San Diego"},{"author_name":"Elaine Keung","author_inst":"University of California San Diego"},{"author_name":"Christopher King","author_inst":"University at Buffalo"},{"author_name":"Connor D. Martin","author_inst":"University at Buffalo"},{"author_name":"Angel Garcia Martinez","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Daniel Munro","author_inst":"University of California San Diego"},{"author_name":"Alesa H. Netzley","author_inst":"University of Michigan"},{"author_name":"Khai-Minh Nguyen","author_inst":"University of California San Diego"},{"author_name":"Beverly Peng","author_inst":"University of California San Diego"},{"author_name":"Dominika Pullmann","author_inst":"New York Medical College"},{"author_name":"Sara R. M. U. Rahman","author_inst":"University of California San Diego"},{"author_name":"Analyse T. Roberts","author_inst":"Medical University of South Carolina"},{"author_name":"Mohammad Sadegi","author_inst":"University of California San Diego"},{"author_name":"Deborah Sevigny-Resetco","author_inst":"Oregon Health & Science University"},{"author_name":"Laura Soverchia","author_inst":"University of Camerino"},{"author_name":"Celine L. St. Pierre","author_inst":"University of California San Diego"},{"author_name":"Nina Suzuki","author_inst":"University of California San Diego"},{"author_name":"Brady M. Thompson","author_inst":"University at Buffalo"},{"author_name":"Shambhavi Tyagi","author_inst":"University of California San Diego"},{"author_name":"Massimo Ubaldi","author_inst":"University of Camerino"},{"author_name":"Robert M. Vogel","author_inst":"University of California San Diego"},{"author_name":"Tengfei Wang","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Yizhi Wang","author_inst":"University of California San Diego"},{"author_name":"Hao Chen","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Roberto Ciccocioppo","author_inst":"University of Camerino"},{"author_name":"Giordano de Guglielmo","author_inst":"University of California San Diego"},{"author_name":"David Dietz","author_inst":"University at Buffalo"},{"author_name":"Shelly B. Flagel","author_inst":"University of Michigan"},{"author_name":"Thomas Jhou","author_inst":"University of Maryland School of Medicine"},{"author_name":"Jicai Jiang","author_inst":"North Carolina State University"},{"author_name":"Peter W. Kalivas","author_inst":"Medical University of South Carolina"},{"author_name":"Brittany N. Kuhn","author_inst":"Medical University of South Carolina"},{"author_name":"Paul J. Meyer","author_inst":"University at Buffalo"},{"author_name":"Suzanne H. Mitchell","author_inst":"Oregon Health & Science University"},{"author_name":"Terry E. Robinson","author_inst":"University of Michigan"},{"author_name":"Oksana Polesskaya","author_inst":"University of California San Diego"},{"author_name":"Abraham A. Palmer","author_inst":"University of California San Diego"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats","rel_doi":"10.64898\/2026.10.01.756043","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756043","rel_abs":"Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.","rel_num_authors":55,"rel_authors":[{"author_name":"Apurva S. Chitre","author_inst":"University of California San Diego"},{"author_name":"Thiago Missfeldt Sanches","author_inst":"University of California San Diego"},{"author_name":"Gavrila Ang","author_inst":"University of California San Diego"},{"author_name":"Nana K. Amissah","author_inst":"University at Buffalo"},{"author_name":"Rodolfo Avila","author_inst":"University of California San Diego"},{"author_name":"Hannah Bimschleger","author_inst":"University of California San Diego"},{"author_name":"Paola Campo","author_inst":"University of California San Diego"},{"author_name":"Nazzareno Cannella","author_inst":"University of Camerino"},{"author_name":"Denghui Chen","author_inst":"University of California San Diego"},{"author_name":"Riyan Cheng","author_inst":"University of California San Diego"},{"author_name":"Katarina A. Cohen","author_inst":"University of California San Diego"},{"author_name":"Ayteria D. Crow","author_inst":"Medical University of South Carolina"},{"author_name":"Eric Dereschewitz","author_inst":"Medical University of South Carolina"},{"author_name":"Michelle R. Doyle","author_inst":"University of California San Diego"},{"author_name":"Maya Eid","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Anthony M. George","author_inst":"University at Buffalo"},{"author_name":"Aidan P. Horvath","author_inst":"University of Michigan"},{"author_name":"Keita Ishiwari","author_inst":"University at Buffalo"},{"author_name":"Benjamin B. Johnson","author_inst":"University of California San Diego"},{"author_name":"Elaine Keung","author_inst":"University of California San Diego"},{"author_name":"Christopher King","author_inst":"University at Buffalo"},{"author_name":"Connor D. Martin","author_inst":"University at Buffalo"},{"author_name":"Angel Garcia Martinez","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Daniel Munro","author_inst":"University of California San Diego"},{"author_name":"Alesa H. Netzley","author_inst":"University of Michigan"},{"author_name":"Khai-Minh Nguyen","author_inst":"University of California San Diego"},{"author_name":"Beverly Peng","author_inst":"University of California San Diego"},{"author_name":"Dominika Pullmann","author_inst":"New York Medical College"},{"author_name":"Sara R. M. U. Rahman","author_inst":"University of California San Diego"},{"author_name":"Analyse T. Roberts","author_inst":"Medical University of South Carolina"},{"author_name":"Mohammad Sadegi","author_inst":"University of California San Diego"},{"author_name":"Deborah Sevigny-Resetco","author_inst":"Oregon Health & Science University"},{"author_name":"Laura Soverchia","author_inst":"University of Camerino"},{"author_name":"Celine L. St. Pierre","author_inst":"University of California San Diego"},{"author_name":"Nina Suzuki","author_inst":"University of California San Diego"},{"author_name":"Brady M. Thompson","author_inst":"University at Buffalo"},{"author_name":"Shambhavi Tyagi","author_inst":"University of California San Diego"},{"author_name":"Massimo Ubaldi","author_inst":"University of Camerino"},{"author_name":"Robert M. Vogel","author_inst":"University of California San Diego"},{"author_name":"Tengfei Wang","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Yizhi Wang","author_inst":"University of California San Diego"},{"author_name":"Hao Chen","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Roberto Ciccocioppo","author_inst":"University of Camerino"},{"author_name":"Giordano de Guglielmo","author_inst":"University of California San Diego"},{"author_name":"David Dietz","author_inst":"University at Buffalo"},{"author_name":"Shelly B. Flagel","author_inst":"University of Michigan"},{"author_name":"Thomas Jhou","author_inst":"University of Maryland School of Medicine"},{"author_name":"Jicai Jiang","author_inst":"North Carolina State University"},{"author_name":"Peter W. Kalivas","author_inst":"Medical University of South Carolina"},{"author_name":"Brittany N. Kuhn","author_inst":"Medical University of South Carolina"},{"author_name":"Paul J. Meyer","author_inst":"University at Buffalo"},{"author_name":"Suzanne H. Mitchell","author_inst":"Oregon Health & Science University"},{"author_name":"Terry E. Robinson","author_inst":"University of Michigan"},{"author_name":"Oksana Polesskaya","author_inst":"University of California San Diego"},{"author_name":"Abraham A. Palmer","author_inst":"University of California San Diego"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats","rel_doi":"10.64898\/2026.10.01.756043","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756043","rel_abs":"Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.","rel_num_authors":55,"rel_authors":[{"author_name":"Apurva S. Chitre","author_inst":"University of California San Diego"},{"author_name":"Thiago Missfeldt Sanches","author_inst":"University of California San Diego"},{"author_name":"Gavrila Ang","author_inst":"University of California San Diego"},{"author_name":"Nana K. Amissah","author_inst":"University at Buffalo"},{"author_name":"Rodolfo Avila","author_inst":"University of California San Diego"},{"author_name":"Hannah Bimschleger","author_inst":"University of California San Diego"},{"author_name":"Paola Campo","author_inst":"University of California San Diego"},{"author_name":"Nazzareno Cannella","author_inst":"University of Camerino"},{"author_name":"Denghui Chen","author_inst":"University of California San Diego"},{"author_name":"Riyan Cheng","author_inst":"University of California San Diego"},{"author_name":"Katarina A. Cohen","author_inst":"University of California San Diego"},{"author_name":"Ayteria D. Crow","author_inst":"Medical University of South Carolina"},{"author_name":"Eric Dereschewitz","author_inst":"Medical University of South Carolina"},{"author_name":"Michelle R. Doyle","author_inst":"University of California San Diego"},{"author_name":"Maya Eid","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Anthony M. George","author_inst":"University at Buffalo"},{"author_name":"Aidan P. Horvath","author_inst":"University of Michigan"},{"author_name":"Keita Ishiwari","author_inst":"University at Buffalo"},{"author_name":"Benjamin B. Johnson","author_inst":"University of California San Diego"},{"author_name":"Elaine Keung","author_inst":"University of California San Diego"},{"author_name":"Christopher King","author_inst":"University at Buffalo"},{"author_name":"Connor D. Martin","author_inst":"University at Buffalo"},{"author_name":"Angel Garcia Martinez","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Daniel Munro","author_inst":"University of California San Diego"},{"author_name":"Alesa H. Netzley","author_inst":"University of Michigan"},{"author_name":"Khai-Minh Nguyen","author_inst":"University of California San Diego"},{"author_name":"Beverly Peng","author_inst":"University of California San Diego"},{"author_name":"Dominika Pullmann","author_inst":"New York Medical College"},{"author_name":"Sara R. M. U. Rahman","author_inst":"University of California San Diego"},{"author_name":"Analyse T. Roberts","author_inst":"Medical University of South Carolina"},{"author_name":"Mohammad Sadegi","author_inst":"University of California San Diego"},{"author_name":"Deborah Sevigny-Resetco","author_inst":"Oregon Health & Science University"},{"author_name":"Laura Soverchia","author_inst":"University of Camerino"},{"author_name":"Celine L. St. Pierre","author_inst":"University of California San Diego"},{"author_name":"Nina Suzuki","author_inst":"University of California San Diego"},{"author_name":"Brady M. Thompson","author_inst":"University at Buffalo"},{"author_name":"Shambhavi Tyagi","author_inst":"University of California San Diego"},{"author_name":"Massimo Ubaldi","author_inst":"University of Camerino"},{"author_name":"Robert M. Vogel","author_inst":"University of California San Diego"},{"author_name":"Tengfei Wang","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Yizhi Wang","author_inst":"University of California San Diego"},{"author_name":"Hao Chen","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Roberto Ciccocioppo","author_inst":"University of Camerino"},{"author_name":"Giordano de Guglielmo","author_inst":"University of California San Diego"},{"author_name":"David Dietz","author_inst":"University at Buffalo"},{"author_name":"Shelly B. Flagel","author_inst":"University of Michigan"},{"author_name":"Thomas Jhou","author_inst":"University of Maryland School of Medicine"},{"author_name":"Jicai Jiang","author_inst":"North Carolina State University"},{"author_name":"Peter W. Kalivas","author_inst":"Medical University of South Carolina"},{"author_name":"Brittany N. Kuhn","author_inst":"Medical University of South Carolina"},{"author_name":"Paul J. Meyer","author_inst":"University at Buffalo"},{"author_name":"Suzanne H. Mitchell","author_inst":"Oregon Health & Science University"},{"author_name":"Terry E. Robinson","author_inst":"University of Michigan"},{"author_name":"Oksana Polesskaya","author_inst":"University of California San Diego"},{"author_name":"Abraham A. Palmer","author_inst":"University of California San Diego"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats","rel_doi":"10.64898\/2026.10.01.756043","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756043","rel_abs":"Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.","rel_num_authors":55,"rel_authors":[{"author_name":"Apurva S. Chitre","author_inst":"University of California San Diego"},{"author_name":"Thiago Missfeldt Sanches","author_inst":"University of California San Diego"},{"author_name":"Gavrila Ang","author_inst":"University of California San Diego"},{"author_name":"Nana K. Amissah","author_inst":"University at Buffalo"},{"author_name":"Rodolfo Avila","author_inst":"University of California San Diego"},{"author_name":"Hannah Bimschleger","author_inst":"University of California San Diego"},{"author_name":"Paola Campo","author_inst":"University of California San Diego"},{"author_name":"Nazzareno Cannella","author_inst":"University of Camerino"},{"author_name":"Denghui Chen","author_inst":"University of California San Diego"},{"author_name":"Riyan Cheng","author_inst":"University of California San Diego"},{"author_name":"Katarina A. Cohen","author_inst":"University of California San Diego"},{"author_name":"Ayteria D. Crow","author_inst":"Medical University of South Carolina"},{"author_name":"Eric Dereschewitz","author_inst":"Medical University of South Carolina"},{"author_name":"Michelle R. Doyle","author_inst":"University of California San Diego"},{"author_name":"Maya Eid","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Anthony M. George","author_inst":"University at Buffalo"},{"author_name":"Aidan P. Horvath","author_inst":"University of Michigan"},{"author_name":"Keita Ishiwari","author_inst":"University at Buffalo"},{"author_name":"Benjamin B. Johnson","author_inst":"University of California San Diego"},{"author_name":"Elaine Keung","author_inst":"University of California San Diego"},{"author_name":"Christopher King","author_inst":"University at Buffalo"},{"author_name":"Connor D. Martin","author_inst":"University at Buffalo"},{"author_name":"Angel Garcia Martinez","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Daniel Munro","author_inst":"University of California San Diego"},{"author_name":"Alesa H. Netzley","author_inst":"University of Michigan"},{"author_name":"Khai-Minh Nguyen","author_inst":"University of California San Diego"},{"author_name":"Beverly Peng","author_inst":"University of California San Diego"},{"author_name":"Dominika Pullmann","author_inst":"New York Medical College"},{"author_name":"Sara R. M. U. Rahman","author_inst":"University of California San Diego"},{"author_name":"Analyse T. Roberts","author_inst":"Medical University of South Carolina"},{"author_name":"Mohammad Sadegi","author_inst":"University of California San Diego"},{"author_name":"Deborah Sevigny-Resetco","author_inst":"Oregon Health & Science University"},{"author_name":"Laura Soverchia","author_inst":"University of Camerino"},{"author_name":"Celine L. St. Pierre","author_inst":"University of California San Diego"},{"author_name":"Nina Suzuki","author_inst":"University of California San Diego"},{"author_name":"Brady M. Thompson","author_inst":"University at Buffalo"},{"author_name":"Shambhavi Tyagi","author_inst":"University of California San Diego"},{"author_name":"Massimo Ubaldi","author_inst":"University of Camerino"},{"author_name":"Robert M. Vogel","author_inst":"University of California San Diego"},{"author_name":"Tengfei Wang","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Yizhi Wang","author_inst":"University of California San Diego"},{"author_name":"Hao Chen","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Roberto Ciccocioppo","author_inst":"University of Camerino"},{"author_name":"Giordano de Guglielmo","author_inst":"University of California San Diego"},{"author_name":"David Dietz","author_inst":"University at Buffalo"},{"author_name":"Shelly B. Flagel","author_inst":"University of Michigan"},{"author_name":"Thomas Jhou","author_inst":"University of Maryland School of Medicine"},{"author_name":"Jicai Jiang","author_inst":"North Carolina State University"},{"author_name":"Peter W. Kalivas","author_inst":"Medical University of South Carolina"},{"author_name":"Brittany N. Kuhn","author_inst":"Medical University of South Carolina"},{"author_name":"Paul J. Meyer","author_inst":"University at Buffalo"},{"author_name":"Suzanne H. Mitchell","author_inst":"Oregon Health & Science University"},{"author_name":"Terry E. Robinson","author_inst":"University of Michigan"},{"author_name":"Oksana Polesskaya","author_inst":"University of California San Diego"},{"author_name":"Abraham A. Palmer","author_inst":"University of California San Diego"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Genomic SEM reveals shared genetic architecture and expands locus discovery for locomotor activity in heterogeneous stock rats","rel_doi":"10.64898\/2026.10.01.756043","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.01.756043","rel_abs":"Locomotor response to a novel environment is a heritable, addiction-relevant behavioral phenotype in rodents. We characterized its genetic basis in 9,341 male and female heterogeneous stock (HS) rats from eight studies. Locomotor activity was heritable across studies, while pairwise genetic correlations were positive but variable, indicating shared yet nonidentical genetic influences. Given nonuniform genetic architecture, we compared three complementary approaches to locus discovery that analyzed SNP effects 1) on a pooled locomotor phenotype (MEGA), 2) across studies under a fixed-effect model (METAL), or 3) on a shared genetic factor (Genomic SEM). To ensure comparability, all three locus-discovery approaches were applied to a common subset of seven studies. Together, these approaches identified 38 loci, with both convergence and method-specific discovery across analyses. Genomic SEM identified 31 loci, compared to 8 for MEGA and 13 for METAL. To interpret the loci, we integrated brain molecular QTLs, predicted coding and splice consequences, and open-field locomotor phenotypes from knockouts of orthologous mouse genes. Our results highlighted established neurobehavioral candidates spanning locomotor and reward-related biology (Negr1 and Lmo4), serotonergic signaling (Htr1b), and GABAergic signaling (Gabrg2), as well as relatively novel genes including Tcerg1l, Pcdh10, and Tmem132e. Our results illustrate how Genomic SEM can integrate genetically correlated yet heterogeneous behavioral measures and enable discovery of loci underlying their shared genetic architecture, highlighting its utility for complex-trait studies in rodents.","rel_num_authors":55,"rel_authors":[{"author_name":"Apurva S. Chitre","author_inst":"University of California San Diego"},{"author_name":"Thiago Missfeldt Sanches","author_inst":"University of California San Diego"},{"author_name":"Gavrila Ang","author_inst":"University of California San Diego"},{"author_name":"Nana K. Amissah","author_inst":"University at Buffalo"},{"author_name":"Rodolfo Avila","author_inst":"University of California San Diego"},{"author_name":"Hannah Bimschleger","author_inst":"University of California San Diego"},{"author_name":"Paola Campo","author_inst":"University of California San Diego"},{"author_name":"Nazzareno Cannella","author_inst":"University of Camerino"},{"author_name":"Denghui Chen","author_inst":"University of California San Diego"},{"author_name":"Riyan Cheng","author_inst":"University of California San Diego"},{"author_name":"Katarina A. Cohen","author_inst":"University of California San Diego"},{"author_name":"Ayteria D. Crow","author_inst":"Medical University of South Carolina"},{"author_name":"Eric Dereschewitz","author_inst":"Medical University of South Carolina"},{"author_name":"Michelle R. Doyle","author_inst":"University of California San Diego"},{"author_name":"Maya Eid","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Anthony M. George","author_inst":"University at Buffalo"},{"author_name":"Aidan P. Horvath","author_inst":"University of Michigan"},{"author_name":"Keita Ishiwari","author_inst":"University at Buffalo"},{"author_name":"Benjamin B. Johnson","author_inst":"University of California San Diego"},{"author_name":"Elaine Keung","author_inst":"University of California San Diego"},{"author_name":"Christopher King","author_inst":"University at Buffalo"},{"author_name":"Connor D. Martin","author_inst":"University at Buffalo"},{"author_name":"Angel Garcia Martinez","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Daniel Munro","author_inst":"University of California San Diego"},{"author_name":"Alesa H. Netzley","author_inst":"University of Michigan"},{"author_name":"Khai-Minh Nguyen","author_inst":"University of California San Diego"},{"author_name":"Beverly Peng","author_inst":"University of California San Diego"},{"author_name":"Dominika Pullmann","author_inst":"New York Medical College"},{"author_name":"Sara R. M. U. Rahman","author_inst":"University of California San Diego"},{"author_name":"Analyse T. Roberts","author_inst":"Medical University of South Carolina"},{"author_name":"Mohammad Sadegi","author_inst":"University of California San Diego"},{"author_name":"Deborah Sevigny-Resetco","author_inst":"Oregon Health & Science University"},{"author_name":"Laura Soverchia","author_inst":"University of Camerino"},{"author_name":"Celine L. St. Pierre","author_inst":"University of California San Diego"},{"author_name":"Nina Suzuki","author_inst":"University of California San Diego"},{"author_name":"Brady M. Thompson","author_inst":"University at Buffalo"},{"author_name":"Shambhavi Tyagi","author_inst":"University of California San Diego"},{"author_name":"Massimo Ubaldi","author_inst":"University of Camerino"},{"author_name":"Robert M. Vogel","author_inst":"University of California San Diego"},{"author_name":"Tengfei Wang","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Yizhi Wang","author_inst":"University of California San Diego"},{"author_name":"Hao Chen","author_inst":"University of Tennessee Health Science Center"},{"author_name":"Roberto Ciccocioppo","author_inst":"University of Camerino"},{"author_name":"Giordano de Guglielmo","author_inst":"University of California San Diego"},{"author_name":"David Dietz","author_inst":"University at Buffalo"},{"author_name":"Shelly B. Flagel","author_inst":"University of Michigan"},{"author_name":"Thomas Jhou","author_inst":"University of Maryland School of Medicine"},{"author_name":"Jicai Jiang","author_inst":"North Carolina State University"},{"author_name":"Peter W. Kalivas","author_inst":"Medical University of South Carolina"},{"author_name":"Brittany N. Kuhn","author_inst":"Medical University of South Carolina"},{"author_name":"Paul J. Meyer","author_inst":"University at Buffalo"},{"author_name":"Suzanne H. Mitchell","author_inst":"Oregon Health & Science University"},{"author_name":"Terry E. Robinson","author_inst":"University of Michigan"},{"author_name":"Oksana Polesskaya","author_inst":"University of California San Diego"},{"author_name":"Abraham A. Palmer","author_inst":"University of California San Diego"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"YY1 phosphorylation links non-apoptotic caspase-8 signaling to MASH fibrosis","rel_doi":"10.64898\/2026.10.05.756806","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756806","rel_abs":"Background & Aims: Metabolic dysfunction-associated steatohepatitis (MASH) is a leading cause of chronic liver disease, and liver fibrosis is the principal determinant of disease progression and clinical outcome. We recently showed that non-apoptotic caspase-8 in hepatocytes is upregulated in MASH and leads to the induction and secretion of meteorin, which promotes hepatic stellate cell (HSC) activation and liver fibrosis. We address here the major mechanistic question arising from this study, namely how non-apoptotic caspase-8 induces pro-fibrotic meteorin in hepatocytes in MASH. Methods: Mechanistic studies were performed using AML12 hepatocytes; primary mouse and human hepatocytes; and diet-induced mouse models of MASH with hepatocyte-specific caspase-8 deletion. YY1 post-translational modifications were identified by LC-MS\/MS and investigated using phosphorylation-defective and phosphomimetic YY1 mutants. Genetic and biochemical approaches were used to interrogate the caspase-8 DED-SRC-GSK3b; pathway, and its relevance was assessed in human MASH liver specimens. Results: In vitro mechanistic studies showed that the amino-terminal death effector domain (DED) of caspase-8 activated a SRC-GSK3b signaling cascade that promoted phosphorylation of YY1 at Ser247, resulting in YY1 nuclear localization and Metrn induction. Disruption of the conserved DED RXDLL motif impaired SRC activation, YY1 phosphorylation, and Metrn expression. Hepatocyte YY1 overexpression increased Metrn expression and fibrosis in wild-type MASH mice but not in hepatocyte-caspase-8-deficient mice. In contrast, phosphomimetic YY1-S247D restored these endpoints even when hepatocyte caspase-8 was lacking. Studies in primary mouse and human hepatocytes and human MASH liver specimens supported conservation of this signaling pathway. Conclusions: These findings identify YY1 Ser247 phosphorylation as a critical molecular event linking non-apoptotic hepatocyte caspase-8 signaling to METRN induction and MASH fibrosis and define a previously unrecognized DED-SRC-GSK3b-YY1 signaling axis with potential therapeutic relevance.","rel_num_authors":6,"rel_authors":[{"author_name":"Xiaobo Wang","author_inst":"Columbia University"},{"author_name":"Eui Jung Jung","author_inst":"Columbia University"},{"author_name":"Lanuza A.P. Faccioli","author_inst":"University of Pittsburgh"},{"author_name":"Dwayne G. Stupack","author_inst":"University of California"},{"author_name":"Alejandro Soto-Gutierrez","author_inst":"University of Pittsburgh"},{"author_name":"Ira Tabas","author_inst":"Columbia University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Coordinated Brain-Heart Dynamics During Human NREM Sleep","rel_doi":"10.64898\/2026.09.29.755384","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.29.755384","rel_abs":"Communication between the brain and cardiovascular system is increasingly recognized as a fundamental determinant of health, yet the mechanisms coordinating neural and cardiac rhythms remain poorly understood. Sleep provides a unique physiological state for investigating neurovisceral integration because cortical slow oscillations (SOs), thalamocortical sleep spindles, and autonomic activity undergo profound reorganization during non-rapid eye movement (NREM) sleep. We analyzed overnight high-density electroencephalography and electrocardiography recordings from 30 healthy adults and quantified interactions among SOs, sleep spindles, cardiac R-peaks, heart rate variability (HRV), spectral slope, and Lempel-Ziv complexity. To assess integrated brain-heart coordination, we developed a Joint Phase-Amplitude Coupling (JPAC) metric that quantifies the corelation between SO phase-dependent modulation of spindle amplitude and cardiac timing. SO-spindle coupling showed the expected fronto-central distribution but was not significantly related to autonomic or cortical state markers. In contrast, SO-R-peak coupling and JPAC systematically tracked physiological state. Stronger JPAC was associated with higher high-frequency HRV, steeper spectral slopes, and lower neural complexity, indicating enhanced coupling during synchronized, parasympathetically dominated NREM sleep. These findings demonstrate coordinated organization of cortical, thalamocortical, and cardiac rhythms within a common oscillatory framework and identify NREM sleep as a state and potential treatment target of large-scale neurovisceral integration.","rel_num_authors":13,"rel_authors":[{"author_name":"Christian A. Mikutta","author_inst":"University of Bern"},{"author_name":"Miriam Planta","author_inst":"UniGE"},{"author_name":"Thomas Koenig","author_inst":"UniBE"},{"author_name":"Kristoffer Feher","author_inst":"UniGE"},{"author_name":"Pauline Henckaerts","author_inst":"UniGe"},{"author_name":"Marie Angelillo","author_inst":"UniGe"},{"author_name":"Elisabeth Hertenstein","author_inst":"UniGe"},{"author_name":"Carlotta L Schneider","author_inst":"UniGe"},{"author_name":"Marzia De Lucia","author_inst":"UniL"},{"author_name":"Dieter Riemann","author_inst":"University of Freiburg i. Br."},{"author_name":"Bernd Feige","author_inst":"University of Freiburg i. Br."},{"author_name":"Vladyslav V Vyazovskiy","author_inst":"University of Oxford"},{"author_name":"Christoph Nissen","author_inst":"HUG, UniGE"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Monitoring the translation initiation process in prokaryotes via large-scale examination using optimized SSU-seq technique","rel_doi":"10.64898\/2026.10.04.756509","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.04.756509","rel_abs":"Translation initiation is a critical stage of protein synthesis in prokaryotes, where ribosomes assemble on mRNA to begin decoding genetic information. The interactions between ribosomal RNA (rRNA) and mRNA significantly influence this process, with features like ribosomal binding site (RBS) affecting ribosomal dynamics. However, direct experimental validation of these types of interaction is yet to be provided. In this study, we developed an optimized small sub-unit sequencing (SSU-seq) protocol for Escherichia coli, enabling the detailed examination of ribosomal complexes and subunits dynamics. Unlike Ribo-seq, which primarily maps fully assembled ribosomes, SSU-seq captures both ribosomal subunits and intact ribosomes, offering a comprehensive view of translation initiation and elongation events. By integrating experimental data with predictive models, our study advances the understanding of translation regulation in prokaryotes and underscores the utility of SSU-seq in decoding the complexities of ribosome-mRNA interactions. Our analysis reveals distinct patterns of small subunit distribution across the entire mRNAs with higher density near positions with stronger rRNA-mRNA hybridization. The results may suggest that rRNA-mRNA hybridization positions along the entire transcript facilitate efficient start codon recognition by maintaining proximity between the small subunit and the mRNA.","rel_num_authors":4,"rel_authors":[{"author_name":"Larissa Fine","author_inst":"Tel Aviv University"},{"author_name":"Alon Diament","author_inst":"Tel Aviv University"},{"author_name":"Rachel Cohen-Kupiec","author_inst":"Tel Aviv University"},{"author_name":"Tamir Tuller","author_inst":"Tel Aviv University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Binding kinetics enable tumor-selective MAPK and growth suppression by a Type 1 RAF Inhibitor","rel_doi":"10.64898\/2026.10.05.756774","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756774","rel_abs":"Therapeutic inhibition of the RAS\/MAPK cascade, an oncogenic driver in over one-third of human cancers, has been limited by a core trade-off: effective pathway blockade in tumors versus dose-limiting toxicity in normal tissues. Although Type 1.5 RAF inhibitors successfully mitigated this trade-off in BRAF-monomer-driven tumors, an equivalent strategy has been lacking for RAF-dimer-driven cancers, including those with RAS mutations. Here, we characterize ELV-3111, a next-generation, potent, and selective Type 1 RAF inhibitor that overcomes this limitation via a distinct mechanism of action. ELV-3111 induces paradoxical MAPK hyperactivation in normal tissues by binding RAF and promoting the active conformation (priming) followed by rapid dissociation (fast off-rate), a biochemical feature that spares RAS-mutant tumors, where RAF is already primed. In these and other RAF dimer-driven tumor models, ELV-3111 achieves potent and selective MAPK and growth suppression. When combined with a MEK inhibitor, ELV-3111 enables complementary pharmacology: additive inhibition in tumors and compensatory effects in normal tissues. The combination produced durable regressions across RAS-mutant and BRAF-mutant models, including a RAS-mutant model refractory to current therapies, while maintaining favorable tolerability. Thus, we uncover a generalizable mechanism that enables Type 1 RAF inhibitor plus MEK inhibitor combinations to achieve tumor-selective MAPK suppression, with the potential to inform targeted therapy design.","rel_num_authors":16,"rel_authors":[{"author_name":"Mathieu Desaunay","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Tara Peters","author_inst":"Enliven Therapeutics"},{"author_name":"Evangelia Matenoglou","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Beau Baars","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Bijaya Gaire","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ana Orive-Ramos","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Li ren","author_inst":"Enliven Therapeutics"},{"author_name":"Joseph P Lyssikatos","author_inst":"Enliven Therapeutics"},{"author_name":"Michael R. Burkard","author_inst":"Enliven Therapeutics"},{"author_name":"Dalton Dacus","author_inst":"Enliven Therapeutics"},{"author_name":"Matthew J. Sale","author_inst":"University of California San Francisco"},{"author_name":"Stuart A. Aaronson","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Frank McCormick","author_inst":"University of California San Francisco, CA, USA"},{"author_name":"Evripidis Gavathiotis","author_inst":"Albert Einstein College of Medicine, NY, USA"},{"author_name":"Stefan Gross","author_inst":"Enliven Therapeutics, CO, USA"},{"author_name":"Poulikos I. Poulikakos","author_inst":"Icahn School of Medicine at Mount Sinai, NY, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Binding kinetics enable tumor-selective MAPK and growth suppression by a Type 1 RAF Inhibitor","rel_doi":"10.64898\/2026.10.05.756774","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756774","rel_abs":"Therapeutic inhibition of the RAS\/MAPK cascade, an oncogenic driver in over one-third of human cancers, has been limited by a core trade-off: effective pathway blockade in tumors versus dose-limiting toxicity in normal tissues. Although Type 1.5 RAF inhibitors successfully mitigated this trade-off in BRAF-monomer-driven tumors, an equivalent strategy has been lacking for RAF-dimer-driven cancers, including those with RAS mutations. Here, we characterize ELV-3111, a next-generation, potent, and selective Type 1 RAF inhibitor that overcomes this limitation via a distinct mechanism of action. ELV-3111 induces paradoxical MAPK hyperactivation in normal tissues by binding RAF and promoting the active conformation (priming) followed by rapid dissociation (fast off-rate), a biochemical feature that spares RAS-mutant tumors, where RAF is already primed. In these and other RAF dimer-driven tumor models, ELV-3111 achieves potent and selective MAPK and growth suppression. When combined with a MEK inhibitor, ELV-3111 enables complementary pharmacology: additive inhibition in tumors and compensatory effects in normal tissues. The combination produced durable regressions across RAS-mutant and BRAF-mutant models, including a RAS-mutant model refractory to current therapies, while maintaining favorable tolerability. Thus, we uncover a generalizable mechanism that enables Type 1 RAF inhibitor plus MEK inhibitor combinations to achieve tumor-selective MAPK suppression, with the potential to inform targeted therapy design.","rel_num_authors":16,"rel_authors":[{"author_name":"Mathieu Desaunay","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Tara Peters","author_inst":"Enliven Therapeutics"},{"author_name":"Evangelia Matenoglou","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Beau Baars","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Bijaya Gaire","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Ana Orive-Ramos","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Li ren","author_inst":"Enliven Therapeutics"},{"author_name":"Joseph P Lyssikatos","author_inst":"Enliven Therapeutics"},{"author_name":"Michael R. Burkard","author_inst":"Enliven Therapeutics"},{"author_name":"Dalton Dacus","author_inst":"Enliven Therapeutics"},{"author_name":"Matthew J. Sale","author_inst":"University of California San Francisco"},{"author_name":"Stuart A. Aaronson","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Frank McCormick","author_inst":"University of California San Francisco, CA, USA"},{"author_name":"Evripidis Gavathiotis","author_inst":"Albert Einstein College of Medicine, NY, USA"},{"author_name":"Stefan Gross","author_inst":"Enliven Therapeutics, CO, USA"},{"author_name":"Poulikos I. Poulikakos","author_inst":"Icahn School of Medicine at Mount Sinai, NY, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Spatially restricted bmp16 in an extra-embryonic syncytium promotes dorsoventral patterning","rel_doi":"10.64898\/2026.10.05.756835","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756835","rel_abs":"How nuclei within a shared cytoplasm organize gene expression programs to direct developmental signaling remains incompletely understood. Here, we combine single-nucleus RNA sequencing, spatial transcriptomic mapping, and functional perturbations to characterize the zebrafish yolk syncytial layer (YSL), an extra-embryonic syncytium that supports embryonic development and patterning. We identify extensive transcriptional covariation among YSL nuclei, revealing coordinated multigene programs organized along dorsoventral and animal-vegetal axes. Within the YSL, we identify an animal-ventral subdomain expressing several BMP ligand transcripts including bmp16, a member of the BMP2\/4 subfamily. We found bmp16 expression to be exclusively extra-embryonic during gastrulation, and functional perturbations reveal that bmp16 is sufficient to ventralize embryos upon overexpression and acts synergistically with bmp2b to promote ventral fates. Ventral YSL expression of Bmp transcripts depends on a transcriptional program downstream of mxtx2 and is maintained independently of BMP pathway autoregulation, while negative regulation by hhex restricts bmp16 expression to the ventral YSL. Together, these findings establish the YSL as a spatially organized syncytium in which coordinated nuclear gene expression programs support localized sources of embryonic patterning signals.","rel_num_authors":4,"rel_authors":[{"author_name":"Haley Couturier","author_inst":"UCSF"},{"author_name":"Hannah Greenfeld","author_inst":"UCSF"},{"author_name":"Jay W Zussman","author_inst":"UCSF"},{"author_name":"Daniel E Wagner","author_inst":"UCSF"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Peroxisome quality control is gated by a dynamic ATF6\u03b1-ABCD3 tether","rel_doi":"10.64898\/2026.10.05.756567","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756567","rel_abs":"The endoplasmic reticulum (ER) coordinates protein folding and lipid biosynthesis, while peroxisomes govern fatty-acid catabolism and redox balance. However, little is known about the mechanisms by which these organelles communicate. Here we show that activating transcription factor 6 (ATF6), a cytoprotective ER-resident sensor of the unfolded protein response (UPR), forms a molecular tether that zippers the ER and peroxisomes together at a 23-nm intermembrane distance. ATF6 achieves this by inserting a short segment of its unstructured N-terminal cytosolic tail into the solvated transmembrane cavity of the peroxisomal ABC-type lipid transporter ABCD3, trapping it in an off-state. This interaction is reinforced by Ceapin, a previously identified small molecule molecular-glue ligand, which promotes ER-peroxisome contact formation. The junctions serve as a scaffold that can initiate peroxisome turnover by p62-triggered autophagy (pexophagy), as enhanced lipid processing resulting from organelle zippering leads to peroxisome damage due to excessive reactive oxygen species (ROS) accumulation. These findings define ATF6 as a non-transcriptional regulator of organelle quality control and provide a template for engineering Ceapin analogues against ATF6\/ABCD3-dependent colorectal and hepatocellular cancers and related diseases.","rel_num_authors":20,"rel_authors":[{"author_name":"Chari M Noddings","author_inst":"Buck Institute for Research on Aging"},{"author_name":"Rukmini Mukherjee","author_inst":"Altos Labs; Buck Institute for Research on Aging (current)"},{"author_name":"Carsten Peukert","author_inst":"Genentech Inc."},{"author_name":"Thomas G Laughlin","author_inst":"Altos Labs"},{"author_name":"Jing Wang","author_inst":"Altos Labs"},{"author_name":"Benjamin T Walters","author_inst":"Genentech Inc."},{"author_name":"Tsan-Wen Lu","author_inst":"Altos Labs; Buck Institute for Research on Aging (current)"},{"author_name":"Tristan Croll","author_inst":"Altos Labs"},{"author_name":"Deniz Eismann","author_inst":"Altos Labs"},{"author_name":"Shelly Harel","author_inst":"Altos Labs"},{"author_name":"Angela Xu","author_inst":"Altos Labs"},{"author_name":"Kibeom Kim","author_inst":"Altos Labs"},{"author_name":"Meghna Gupta","author_inst":"Oregon Health & Science University"},{"author_name":"James Crawford","author_inst":"Altos Labs"},{"author_name":"Christopher P Arthur","author_inst":"Altos Labs; FairJourney Bio (current)"},{"author_name":"Daniel Itzhak","author_inst":"Altos Labs"},{"author_name":"Mauro Costa-Mattioli","author_inst":"Altos Labs"},{"author_name":"Joachim Rudolph","author_inst":"Genentech Inc."},{"author_name":"Avi Ashkenazi","author_inst":"Genentech Inc."},{"author_name":"Peter Walter","author_inst":"Altos Labs; Buck Institute for Research on Aging (current)"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Conserved Fibroblast Subsets Drive Shared Fibrotic Mechanisms in Osteoarthritis Synovium and Systemic Sclerosis Skin","rel_doi":"10.64898\/2026.10.05.756653","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756653","rel_abs":"Osteoarthritis (OA) and systemic sclerosis (SSc) are diseases with distinct etiologies but similar disease phenotypes, most prominently fibrosis, a process governed by the pathological activation of fibroblasts. Mechanisms underpinning fibrosis in these diseases are widely studied, though have yet to be directly compared. We employed single-cell RNA-seq and high-resolution spatial transcriptomics to describe the functional plasticity and the range of fibroblast activation states in both diseases. We identified disease-enriched fibroblast subsets conserved in both diseases, including fibrogenic myofibroblast-like cells, chemokine- and cytokine-expressing inflammatory fibroblasts, and lining-like fibroblasts. These subsets exhibited convergent fibrotic programs also observed in idiopathic pulmonary fibrosis, as well as overlapping osteochondral transcriptional programs. Xenium 5K spatial transcriptomics revealed that conserved, disease-associated fibroblasts reside in highly similar anatomic niches in OA synovium and SSc skin. These consisted of a fibrotic ECM-rich niche harboring myofibroblast-like cells and an inflammatory niche containing inflammatory fibroblasts adjacent to infiltrating immune cells. Disease-associated transcriptional remodeling converged on shared functional pathways and common putative upstream molecular regulators. These findings identify conserved cellular states, spatial niches, and regulatory programs across OA and SSc, suggesting that fibrotic disease is underpinned by shared pathogenic stromal states and candidate targets for therapeutic strategies are applicable across both diseases.","rel_num_authors":10,"rel_authors":[{"author_name":"Aanya Mohan","author_inst":"Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland"},{"author_name":"Michael D. Newton","author_inst":"Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Neil Bhate","author_inst":"Department of Orthopaedic Surgery, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Alexandra Khmelevskaya","author_inst":"Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland"},{"author_name":"Tareq M. Hanna","author_inst":"Wayne State University School of Medicine, MI, USA"},{"author_name":"Edward DiCarlo","author_inst":"Hospital for Special Surgery, New York, NY, USA"},{"author_name":"Caroline Ospelt","author_inst":"Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland"},{"author_name":"Dana Orange","author_inst":"Rockefeller University, New York, NY, USA"},{"author_name":"John Varga","author_inst":"Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Tristan Maerz","author_inst":"Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Protein-level mapping reveals novel Immune State Types (ISTs) associated with Chlamydia trachomatis infection, inflammatory remodeling, and scarring in trachoma-hyperendemic Amhara Ethiopia","rel_doi":"10.64898\/2026.09.30.755767","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755767","rel_abs":"ABSTRACT Background: Trachoma remains the leading infectious cause of blindness. Over 100M people are at risk, and 1.9M already live with visual impairment or blindness. Ethiopia bears the greatest burden of disease with ~61M or 59% of the known affected global population. Although Chlamydia trachomatis (Ct) infection initiates disease, infection alone fails to explain why inflammation resolves in some but progresses to irreversible scarring and vision loss in others. Previous studies have largely examined gene expression or limited protein panels, leaving the conjunctival immune protein environment poorly characterized. We hypothesized that distinct conjunctival immune states capture these pathogenic processes and could reveal biomarkers for selecting treatment and surveillance strategies. Methods and Findings: We conducted a cross-sectional study of 667 participants residing in the hyperendemic Amhara region of Ethiopia at least one year after the most recent azithromycin mass drug administration to treat Ct. The upper tarsal conjunctivae was graded for TF and TI, trachomatous inflammation-follicular or intense, respectively; I-TS\/TT, inflammation with scarring with or without trichiasis, defined as one or more eyelashes touching the globe of the eye; and TS and TT, scarring with or without trichiasis but no inflammation. T0 represented no trachoma. The protein concentrations of 41 immune mediators were quantified using Meso Scale Discovery electrochemiluminescence immunoassays. Associations with infection and grade were evaluated using covariate-adjusted models with false discovery rate correction. Bernoulli mixture modeling (BMM) revealed four distinct Immune State Types (ISTs). Both approaches supported a shared biological framework characterized by selective immune activation in Ct infection, broad inflammation in TF\/TI, and chemokine remodeling versus immune quiescence in the scarred conjunctiva. Ct infection was associated with a focused IFN-{gamma}-centered response. IST1 captured this immune response where 51.9% of the participants had Ct; we therefore termed IST1 Quiescent Infection. In contrast, TF\/TI was associated with higher concentrations of proinflammatory, Th1\/Th17, chemokine, regulatory, and remodeling pathways mediators. This profile fit well within IST2, termed Broad Inflammation, where 72.4% of the participants had TF\/TI. TS\/TT retained considerable chemokine activity, whereas I-TS\/TT showed a narrower, IL-17A-dominant inflammatory profile. BMM separated scarring into two states characterized by distinct profiles: IST3, Conjunctival Remodeling, with significantly stronger chemokine and T-cell maintenance signals; and IST4, Quiescent Scarring, with the majority of chemokines being significantly downregulated. This suggests that scarred conjunctiva can retain substantial immune activity or shift toward a more attenuated state. Conclusions: This study establishes the first IST framework for trachoma, revealing biologically distinct immune states with different potential clinical implications. IST1 indicates the need for antibiotic treatment, whereas IST2 suggests that novel immunotherapeutics might be effective in thwarting disease progression. The upregulated chemokines in IST3 may indicate risk of progression to TT necessitating prospective studies and potential novel antifibrotic interventions. Together, our findings provide a strong biological foundation for stratifying patients by immune state and matching them to preventive and therapeutic care. Prospective validation and streamlined biomarker panels will support the translation of this framework into field settings to help avert disease progression and blindness.","rel_num_authors":8,"rel_authors":[{"author_name":"Xiaoyi Charlotte Shi","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Olusola Olagoke","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Brianna Renatte Titiheruw","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Seongwon Chung","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Hiwot Degineh Mengistie","author_inst":"Bahir Dar Specialty Eye Center, Bahir Dar, Ethiopia"},{"author_name":"Kaleb Asfaha","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Timothy D Read","author_inst":"Emory University School of Medicine"},{"author_name":"Deborah Dean","author_inst":"University of California San Francisco School of Medicine"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Protein-level mapping reveals novel Immune State Types (ISTs) associated with Chlamydia trachomatis infection, inflammatory remodeling, and scarring in trachoma-hyperendemic Amhara Ethiopia","rel_doi":"10.64898\/2026.09.30.755767","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.09.30.755767","rel_abs":"ABSTRACT Background: Trachoma remains the leading infectious cause of blindness. Over 100M people are at risk, and 1.9M already live with visual impairment or blindness. Ethiopia bears the greatest burden of disease with ~61M or 59% of the known affected global population. Although Chlamydia trachomatis (Ct) infection initiates disease, infection alone fails to explain why inflammation resolves in some but progresses to irreversible scarring and vision loss in others. Previous studies have largely examined gene expression or limited protein panels, leaving the conjunctival immune protein environment poorly characterized. We hypothesized that distinct conjunctival immune states capture these pathogenic processes and could reveal biomarkers for selecting treatment and surveillance strategies. Methods and Findings: We conducted a cross-sectional study of 667 participants residing in the hyperendemic Amhara region of Ethiopia at least one year after the most recent azithromycin mass drug administration to treat Ct. The upper tarsal conjunctivae was graded for TF and TI, trachomatous inflammation-follicular or intense, respectively; I-TS\/TT, inflammation with scarring with or without trichiasis, defined as one or more eyelashes touching the globe of the eye; and TS and TT, scarring with or without trichiasis but no inflammation. T0 represented no trachoma. The protein concentrations of 41 immune mediators were quantified using Meso Scale Discovery electrochemiluminescence immunoassays. Associations with infection and grade were evaluated using covariate-adjusted models with false discovery rate correction. Bernoulli mixture modeling (BMM) revealed four distinct Immune State Types (ISTs). Both approaches supported a shared biological framework characterized by selective immune activation in Ct infection, broad inflammation in TF\/TI, and chemokine remodeling versus immune quiescence in the scarred conjunctiva. Ct infection was associated with a focused IFN-{gamma}-centered response. IST1 captured this immune response where 51.9% of the participants had Ct; we therefore termed IST1 Quiescent Infection. In contrast, TF\/TI was associated with higher concentrations of proinflammatory, Th1\/Th17, chemokine, regulatory, and remodeling pathways mediators. This profile fit well within IST2, termed Broad Inflammation, where 72.4% of the participants had TF\/TI. TS\/TT retained considerable chemokine activity, whereas I-TS\/TT showed a narrower, IL-17A-dominant inflammatory profile. BMM separated scarring into two states characterized by distinct profiles: IST3, Conjunctival Remodeling, with significantly stronger chemokine and T-cell maintenance signals; and IST4, Quiescent Scarring, with the majority of chemokines being significantly downregulated. This suggests that scarred conjunctiva can retain substantial immune activity or shift toward a more attenuated state. Conclusions: This study establishes the first IST framework for trachoma, revealing biologically distinct immune states with different potential clinical implications. IST1 indicates the need for antibiotic treatment, whereas IST2 suggests that novel immunotherapeutics might be effective in thwarting disease progression. The upregulated chemokines in IST3 may indicate risk of progression to TT necessitating prospective studies and potential novel antifibrotic interventions. Together, our findings provide a strong biological foundation for stratifying patients by immune state and matching them to preventive and therapeutic care. Prospective validation and streamlined biomarker panels will support the translation of this framework into field settings to help avert disease progression and blindness.","rel_num_authors":8,"rel_authors":[{"author_name":"Xiaoyi Charlotte Shi","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Olusola Olagoke","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Brianna Renatte Titiheruw","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Seongwon Chung","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Hiwot Degineh Mengistie","author_inst":"Bahir Dar Specialty Eye Center, Bahir Dar, Ethiopia"},{"author_name":"Kaleb Asfaha","author_inst":"University of California San Francisco School of Medicine"},{"author_name":"Timothy D Read","author_inst":"Emory University School of Medicine"},{"author_name":"Deborah Dean","author_inst":"University of California San Francisco School of Medicine"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"From Network Topology to Parameterization: An Optimized Model of Endothelial Mechanobiology","rel_doi":"10.64898\/2026.10.05.756772","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756772","rel_abs":"Endothelial cells integrate biomechanical and biochemical cues to regulate vascular function, which can be modeled using cell signaling networks. Yet, the extent to which their signaling behavior is determined by network topology versus reaction-specific parameterization remains unclear. We developed a continuous logic-based ordinary differential equation model of vascular endothelial signaling containing 70 species and 123 regulatory reactions assembled from the literature. Model predictions were evaluated against 78 literature-defined directional responses to increased wall stress, wall shear stress, hypoxia, and TNF. We first tested whether a single global parameter triplet describing reaction weight (w), Hill coefficient (n), and half-maximal activation (EC50) could reproduce these observations. Investigator-selected global parameters reproduced 62 of 78 responses (79.49%). Monte Carlo sampling of 100,000 globally constant parameter sets improved agreement to 69 of 78 responses (88.46%), indicating that network topology alone captured most qualitative signaling behavior but remained sensitive to parameter choice. Allowing reaction-specific parameters increased the best agreement to 75 of 78 responses (96.15%). We then used a genetic algorithm to identify the smallest subset of reactions requiring reaction-specific specification while retaining a common constant-parameter spine for the remainder of the network. Complete agreement (100%) with all 78 literature-defined responses was achieved with reaction-specific parameterization of only 10 of 123 reactions. The optimized model was subsequently used to simulate continuous changes in wall shear stress, revealing pathway-dependent nonlinear responses, including monotonic increases in nitric oxide and pSmad1\/5, nonmonotonic responses in endothelin-1 and NF-{kappa}B, and a biphasic pSmad2\/3 response. These findings show that most observed endothelial signaling behavior can be reproduced by a fixed network topology with broadly shared reaction parameters with only a limited subset of interactions requiring quantitative specialization. This framework provides a compact endothelial signaling model for investigating mechanobiological regulation and for future integration with multiscale models of vascular adaptation and disease.","rel_num_authors":5,"rel_authors":[{"author_name":"Pete H Gueldner","author_inst":"Yale University"},{"author_name":"Linda Irons","author_inst":"Astrazeneca"},{"author_name":"Jeremy L. Warren","author_inst":"Yale University"},{"author_name":"David S. Li","author_inst":"University of Nebraska Omaha"},{"author_name":"Jay Humphrey","author_inst":"Yale University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"In situ identification of pre-hematopoietic stem cells and their niche","rel_doi":"10.64898\/2026.10.05.756028","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756028","rel_abs":"Definitive hematopoietic stem cells (HSCs) emerge predominantly along the ventral surface of the dorsal aorta in the embryonic aorta-gonad-mesonephros (AGM) region, yet the spatial organization of the niche underlying this developmental asymmetry remains poorly understood. Defining the native niche of pre-HSCs has also been hindered by their rarity, transient nature and lack of a single definitive marker for their identification in situ. Here, we integrated single-cell and spatial transcriptomics to construct a spatiotemporal atlas of the niche in the AGM. Neural cells and chondrogenic mesenchyme predominated dorsally, whereas N-cadherin mesenchymal stromal cells (N-cad+ MSCs) formed a ventral layer between the aortic endothelium and mesonephric cells. BMP and SHH signaling showed overall dorsal enrichment, whereas WNT, NOTCH and KIT signaling were enriched ventrally, with these cellular and signaling patterns dynamically remodeled across HSC ontogeny. Imaging-based spatial transcriptomics validated the findings and further enabled the identification of individual pre-HSCs in situ and revealed a multicellular niche comprising endothelial cells, N-cad+ MSCs, intra-aortic hematopoietic cluster cells and macrophages. TGF{beta} and NOTCH signals were primarily supplied locally, whereas major sources of BMP and WNT were more distant. Functional perturbation identified niche-derived CD200 as an immune-regulatory signal promoting HSC development, validating a spatially predicted niche interaction. Together, our findings link tissue-scale spatial organization with the local multicellular niche supporting the preferential development of HSCs along the ventral aorta.","rel_num_authors":24,"rel_authors":[{"author_name":"Xinjian Mao","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Ning Zhang","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Laura Bennett","author_inst":"Department of Cell and Developmental Biology, Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, "},{"author_name":"Xi He","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Allison Scott","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Kate Hall","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Kaitlyn Petentler","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Seth Malloy","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Shengping Huang","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Amanda Kroesen","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Sean McKinney","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Athanasios Ploumakis","author_inst":"Spatial Technologies Unit, Department of Pathology, Beth Israel Deaconess Medical Center \/ Harvard Medical School, Boston, MA, USA."},{"author_name":"Zhe Yang","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Ruochen Dong","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Jose Javier","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Jeff Haug","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Hua Li","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Zulin Yu","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Anoja Perera","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Ioannis Vlachos","author_inst":"Spatial Technologies Unit, Department of Pathology, Beth Israel Deaconess Medical Center \/ Harvard Medical School, Boston, MA, USA."},{"author_name":"Fei Chen","author_inst":"Broad Institute of Harvard and MIT, Cambridge, MA, USA."},{"author_name":"Paul Trainor","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."},{"author_name":"Nancy A Speck","author_inst":"Department of Cell and Developmental Biology, Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, "},{"author_name":"Linheng Li","author_inst":"Stowers Institute for Medical Research, Kansas City, MO 64110, USA."}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Radiotherapy-induced vascular dysfunction alters neutrophil phenotype to promote tumor cell colonization of mammary adipose tissue","rel_doi":"10.64898\/2026.10.03.756445","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.03.756445","rel_abs":"Recurrence remains a significant clinical challenge for triple-negative breast cancer patients and radiotherapy (RT) is a key therapeutic tool that significantly reduces the risk of relapse. Despite this, patients with chronic lymphopenia and a high neutrophil:lymphocyte ratio (NLR) experience recurrence at significantly higher rates than those whose hematological biomarkers return to baseline post-RT, and there are currently no treatments to prevent this relapse. Here, we utilized in vivo mouse models of lymphocyte-deficiency to identify the mechanism behind systemic immune status and recurrence. Using a model of RT-induced circulating tumor cell (CTC) colonization, we found that neutrophils are sustained in the irradiated, lymphocyte-deficient mammary tissue up to 10 days post-RT. Persistent neutrophil accumulation was accompanied by excessive vascular remodeling and tumor cell colonization of the mammary tissue, both of which were abated upon systemic neutrophil depletion. Neutrophils in the colonization-permissive microenvironment exhibited a state of pathological activation consistent with a polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) phenotype that was not seen in systemic compartments, highlighting a microenvironment-induced phenotype shift. This phenotype was recapitulated in vitro when naive neutrophils were exposed to the secretome of RT-induced senescent endothelial cells (ECs). We found that these activated neutrophils then regulated the dysfunction of irradiated ECs in a canonical NF-kB-dependent manner, increasing their barrier permeability and activating downstream inflammatory signals. Our findings not only establish neutrophils as a critical component of tumor cell colonization in lymphocyte-deficient subjects but also uncover a positive feedback loop between neutrophils and irradiated vasculature that leads to aberrant tissue remodeling and ultimately tumor cell colonization. This work deepens our understanding of how systemic factors influence treatment-damaged microenvironments, which could ultimately lead to identification of molecular targets for prevention of RT failure.","rel_num_authors":11,"rel_authors":[{"author_name":"Shannon E. Martello","author_inst":"Vanderbilt University"},{"author_name":"Bridget H. Stevenson","author_inst":"Vanderbilt University"},{"author_name":"Holden Korbey","author_inst":"Vanderbilt University"},{"author_name":"Kevin C. Corn","author_inst":"Vanderbilt University"},{"author_name":"Tian Zhu","author_inst":"Vanderbilt University"},{"author_name":"Erica J. Lin","author_inst":"Vanderbilt University"},{"author_name":"Marissa Paul","author_inst":"Vanderbilt University"},{"author_name":"Kirsten E. Stubenrauch","author_inst":"Vanderbilt University"},{"author_name":"Jonathan Wang","author_inst":"Vanderbilt University"},{"author_name":"Alessandra Perez","author_inst":"Vanderbilt University"},{"author_name":"Marjan Rafat","author_inst":"Vanderbilt University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"EPHA4 Regulates the Transition between Mesenchymal and Hybrid States in TNBC","rel_doi":"10.64898\/2026.10.04.756472","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.04.756472","rel_abs":"Metastatic progression in triple-negative breast cancer (TNBC) is strongly influenced by epithelial-mesenchymal plasticity (EMP), which enables transitions between epithelial, hybrid epithelial\/mesenchymal (E\/M), and mesenchymal cell states. While mesenchymal cells are highly invasive and resistant to therapy, hybrid E\/M states confer advantages during metastatic colonization. Both mesenchymal and hybrid states therefore contribute to tumor aggressiveness through distinct mechanisms. However, the molecular regulation governing transitions between mesenchymal and hybrid E\/M states remains poorly understood. Here, we identify EPHA4 as a regulator of this transition in TNBC. EPHA4 expression is enriched in mesenchymal TNBC cells, and genetic knockout of EPHA4 in MDA-MB-231 xenograft and 4T1 syngeneic models induces a shift toward hybrid E\/M phenotypes. This transition reduces cellular invasion while enhancing metastatic colonization, consistent with the clinical observations of decreased EPHA4 expression in secondary metastases compared to primary tumors. Despite compensatory changes in other Eph\/ephrin family members following EPHA4 loss, EPHA4 deficiency is sufficient to drive this phenotypic shift. These findings identify EPHA4 as a regulator of cancer cell plasticity in TNBC and highlight the therapeutic complexity of targeting pathways that govern metastatic state transitions.","rel_num_authors":9,"rel_authors":[{"author_name":"Wenchao Liu","author_inst":"University of Chicago"},{"author_name":"Hoi Wan Lee","author_inst":"University of Chicago"},{"author_name":"Madeline H. Bungert","author_inst":"University of Chicago"},{"author_name":"Long Chi Nguyen","author_inst":"University of Chicago"},{"author_name":"Aleksandra Kurowska","author_inst":"University of Chicago"},{"author_name":"Thomas Jiyoung Lee","author_inst":"University of Chicago"},{"author_name":"Geetha P Yerradoddi","author_inst":"University of Chicago"},{"author_name":"Eva Suarez","author_inst":"University of Chicago"},{"author_name":"Marsha Rich Rosner","author_inst":"University of Chicago"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Blood-brain barrier-traversing multivalent TGF\u03b2 trap for anti-cancer immunomodulation of gliomas","rel_doi":"10.64898\/2026.10.05.756837","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756837","rel_abs":"Clinical studies have revealed that glioblastoma (GBM) is refractory to immunotherapy, such as immune checkpoint inhibitors (ICIs), due to the immunosuppressive tumor microenvironment (TME) primarily intensified by intratumoral upregulation of transforming growth factor-{beta} (TGF{beta}). Primary GBM tumor bulks are surgically removed in clinic, but invasive tumor cells infiltrated into surrounding normal brain tissue cannot be eradicated by systemic therapy due to the integral blood-brain barrier (BBB), leading to near-inevitable tumor recurrence. To address these translational challenges, we have engineered a TGF{beta}-inhibiting protein nanocage comprising human heavy-chain ferritin protein and TGF{beta} receptor II ectodomain that enables BBB penetration and multivalent TGF{beta} entrapment, respectively. We demonstrate that the nanocage platform, denoted T{beta}R2-HFt, following systemic administration, traverses the BBB, and extensively modulates immunosuppressive TME, both stromal and immune components, thereby potentiating the therapeutic efficacy of a clinically used ICI in multiple mouse glioma models. Notably, a majority of the glioma-bearing animals that received surgical tumor resection, followed by treatment with T{beta}R2-HFt and the ICI, survived the tumor and resisted tumor rechallenge, providing a potential means to control GBM in a durable manner.","rel_num_authors":15,"rel_authors":[{"author_name":"Daiheon Lee","author_inst":"Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"author_name":"Seung Woo Chung","author_inst":"Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA"},{"author_name":"Byoungjae Kong","author_inst":"Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"author_name":"Yunxuan Xie","author_inst":"Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA"},{"author_name":"Bokyoung Kang","author_inst":"Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"author_name":"Jun Yang","author_inst":"Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA"},{"author_name":"Buwei Huang","author_inst":"Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA"},{"author_name":"Divya Rao","author_inst":"Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA"},{"author_name":"Jong Seob Choi","author_inst":"Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA"},{"author_name":"Eun A. Ra","author_inst":"Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA"},{"author_name":"Pavlos Anastasiadis","author_inst":"Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA"},{"author_name":"Gabsang Lee","author_inst":"Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA"},{"author_name":"Deok-Ho Kim","author_inst":"Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA"},{"author_name":"Michael Lim","author_inst":"Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA 94305, USA"},{"author_name":"Jung Soo Suk","author_inst":"Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Prime editing enables high-throughput identification and characterization of selective MutS\u03b2 inhibitors","rel_doi":"10.64898\/2026.10.05.755959","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.755959","rel_abs":"DNA mismatch repair (MMR) maintains genome stability but paradoxically drives expansion of pathogenic repeats responsible for trinucleotide repeat disorders. Attenuating repeat instability through targeted inhibition of MMR is therefore a therapeutic strategy of interest; however, progress is constrained by a lack of robust methods for defining and isolating MMR subpathways. We exploited features of prime editing to profile the effects of core MMR genes on thousands of programmed DNA mispairs in cells and resolved distinct MMR processes, including a noncanonical, loop-directed mechanism. Guided by these results, we built a set of scalable reporters that detect loss of separable MMR processes and screened ~72,000 small molecules for activity against MutS{beta}-directed MMR. This effort identified a novel series of MutS{beta} inhibitors that reduced (CAG)n expansion in a cell model. Altogether, this study establishes several methods for systematically interrogating MMR, with demonstrated capacity to identify inhibitors of therapeutic value.","rel_num_authors":22,"rel_authors":[{"author_name":"Yangwode Jing","author_inst":"Princeton University"},{"author_name":"Jun Yan","author_inst":"Princeton University"},{"author_name":"Denny Yang","author_inst":"Cambridge University"},{"author_name":"Yanjin Chen","author_inst":"Princeton University"},{"author_name":"Issam Senoussi","author_inst":"Institute for Research in Biomedicine"},{"author_name":"James Woodward","author_inst":"University of Cambridge"},{"author_name":"Katya Williams","author_inst":"Princeton University"},{"author_name":"Hahn Kim","author_inst":"Princeton University"},{"author_name":"Kangning He","author_inst":"University of Cambridge"},{"author_name":"Herwin Daub","author_inst":"Proteros biostructures GmbH"},{"author_name":"Vinay Dahiya","author_inst":"Proteros biostructures GmbH"},{"author_name":"Maren Thomsen","author_inst":"Proteros biostructures GmbH"},{"author_name":"Jia Ling","author_inst":"Princeton University"},{"author_name":"Purnima Ravisankar","author_inst":"Princeton University"},{"author_name":"Yuri Pritykin","author_inst":"Princeton University"},{"author_name":"Gabriel Balmus","author_inst":"University of Cambridge"},{"author_name":"Petr Cejka","author_inst":"Institute for Research in Biomedicine"},{"author_name":"Jeffrey A. Hussmann","author_inst":"Princeton University"},{"author_name":"Longbin Liu","author_inst":"CHDI Foundation"},{"author_name":"Thomas F. Vogt","author_inst":"CHDI Foundation"},{"author_name":"Michael Finley","author_inst":"CHDI Foundation"},{"author_name":"Britt Adamson","author_inst":"Princeton University"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Spiders as natural DNA samplers recover arthropod community diversity and biotic interactions across space and time","rel_doi":"10.64898\/2026.10.05.756666","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.10.05.756666","rel_abs":"Global arthropod decline demands effective biodiversity monitoring strategies. However, most current monitoring approaches do not provide an exhaustive picture of arthropod community structure. In particular, biotic interactions and temporal patterns of biodiversity change are still poorly understood. Here we explore the possibility of addressing these two shortfalls using spiders, one of the most important predators of terrestrial arthropods, as natural samplers for arthropod community DNA. We conducted several experiments comparing the recovered community composition between spider gut contents and traditional monitoring methods. Additionally, we used archived spiders from long-term collections to assess the preservation of prey DNA over time. Spiders proved to be highly efficient natural DNA samplers, with gut content metabarcoding revealing similar community composition and alpha- and beta-diversity like traditional methods. Unique arthropod taxa were detected by spider gut contents and traditional methods respectively, indicating that these two approaches can serve as valuable complements to each other. Well-preserved archived spiders effectively reconstructed historical diets up to 20 years back in time, showing that historical spider collections can act as time capsules of the wider diversity that occurred in the spider's habitat. Spiders as natural samplers overcome critical shortfalls in biodiversity monitoring and contribute to our future understanding of community assembly across space and time.","rel_num_authors":19,"rel_authors":[{"author_name":"Sven Weber","author_inst":"UC Berkeley"},{"author_name":"Anja Carina Melcher","author_inst":"Trier University"},{"author_name":"Jerilyn Calaor","author_inst":"Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia, USA"},{"author_name":"Susan Rachel Kennedy","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Domagoj Gajski","author_inst":"Faculty of Science, Masaryk University"},{"author_name":"Tim Hoerrmann","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Arndt Schmidt","author_inst":"schmidtar@uni-trier.de"},{"author_name":"Lilly Melzl","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Ferdinand Meiss","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Julian Hans","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Lisa Mahla","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Manuel Stothut","author_inst":"Trier University, Department of Biogeography, Trier, Germany"},{"author_name":"Danilo Harms","author_inst":"Museum of Nature Hamburg (Zoology), Leibniz Institute for the Analysis of Biodiversity, Hamburg, Germany"},{"author_name":"Klaus Birkhofer","author_inst":"BTU Cottbus"},{"author_name":"Evan P Economo","author_inst":"Okinawa Institute of Science and Technology Graduate University"},{"author_name":"Haldre Rogers","author_inst":"Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, Virginia, USA"},{"author_name":"Rosemary Gillespie","author_inst":"University of California Berkeley, ESPM, California, USA"},{"author_name":"George Roderick","author_inst":"University of California Berkeley, ESPM, California, USA"},{"author_name":"Henrik Krehenwinkel","author_inst":"Universitat Trier"}],"rel_date":"2026-10-06","rel_site":"biorxiv"},{"rel_title":"Estimating Hepatitis C Virus Prevalence in US States and the District of Columbia, 2017-2020","rel_doi":"10.64898\/2026.09.29.26364309","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364309","rel_abs":"Background State-level estimates of hepatitis C virus (HCV) prevalence are needed to guide resource allocation and to provide a baseline against which to measure progress toward elimination goals. Population prevalence is not directly observable, requiring estimation from indirect data sources. Methods We adapted a Bayesian spatial integrated abundance model to estimate state-level HCV prevalence during 2017-2020 across 48 states and the District of Columbia. The model integrated six HCV-related outcomes: acute and chronic surveillance cases, HCV-related deaths, observations of HCV in [MarketScan] administrative claims data, diagnoses of HCV in Medicaid recipients, and treatment with direct-acting antivirals in Medicaid recipients. Estimates were anchored to a national prevalence estimate, and the model accounted for data source-specific selection, heterogeneity in HCV risk factors across states, and geospatial correlation. Results Estimated average prevalence was 1.32% (95% credible interval [CrI]: 0.94%-1.80%), corresponding to 3.33 million (95% CrI: 2.37-4.65 million) adults with HCV infection across 48 states and DC. State estimates ranged from 0.74% in North Dakota to 2.22% in Oklahoma (median state-specific prevalence, 1.27%), with higher prevalence concentrated in South Central states, Appalachia, and the West, and the lower prevalence in the upper Midwest, Southeast, and New England. Ten states accounted for 56% of estimated infections. Estimates were stable in sensitivity analyses (most differences <1 percentage point). Conclusions These estimates quantify state-level HCV burden prior to the 2021 federal expansion of HCV surveillance funding, providing a baseline for monitoring elimination progress. Geographic variation indicates that resource needs will differ by jurisdiction.","rel_num_authors":6,"rel_authors":[{"author_name":"Heather Bradley","author_inst":"Emory University"},{"author_name":"Ya-Hui Yu","author_inst":"Emory University"},{"author_name":"Lanxin Li","author_inst":"University of Edinburgh"},{"author_name":"Shashi N Kapadia","author_inst":"Weill Cornell Medicine"},{"author_name":"Patrick S Sullivan","author_inst":"Emory University"},{"author_name":"Eric William Hall","author_inst":"Oregon Health & Science University"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Measuring enteric pathogen force of infection through antibody responses in children","rel_doi":"10.64898\/2026.09.29.26364344","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364344","rel_abs":"Enteric pathogens account for a substantial global disease burden, yet population-based surveillance remains limited by the transient nature of pathogen shedding, which constrains the sensitivity of stool-based molecular testing to a narrow detection window. Detection of IgG responses in serological surveys could enable new insights into enteric pathogen transmission, but benchmarking serological measures relative to stool-based measures of infection remains a critical evidence gap. We compared measures of disease transmission in longitudinal birth cohort samples using multiplex IgG (1,601 dried blood spots, 370 children) and PCR assays (2,231 stool samples, 370 children) that overlapped for nine pathogens (norovirus GI, GII, Shigella\/enteroinvasive Escherichia coli (EIEC), Campylobacter spp., enterotoxigenic Escherichia coli (LT-ETEC), Salmonella enterica, Giardia spp., Cryptosporidium spp., Entamoeba histolytica). LT-ETEC and Campylobacter ranked highest while E. histolytica and S. enterica ranked lowest by both IgG and PCR measures of infection. Measures of infection were less aligned for norovirus GI, norovirus GII, Cryptosporidium, Shigella\/EIEC, and Giardia. Despite this, for most pathogens, and across both measures, force of infection was lowest in the urban city of Esmeraldas and substantially higher in more rural populations, with relative risks in assay measures (seroconversion rate and PCR detected prevalence) over 2.0 for pathogens with the largest differences (Shigella\/EIEC and norovirus GI). Together, our results suggest that although absolute levels of infection differed between assays, IgG and PCR captured consistent relative risk of infection across geographic strata, suggesting either method can identify high- versus low-transmission settings.","rel_num_authors":25,"rel_authors":[{"author_name":"Nikolina Walas","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Lesly Simba\u00f1a Vivanco","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Stuart Torres Ayala","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Chabier Coleman","author_inst":"Independent consultant"},{"author_name":"E. Brook Goodhew","author_inst":"Independent consultant"},{"author_name":"Kelsey J. Jesser","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Nicolette A. Zhou","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Christine S. Fagnant-Sperati","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jesse Contreras","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Caitlin Hemlock","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jeffrey W. Priest","author_inst":"Retired"},{"author_name":"Richelle C. Charles","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Edward T. Ryan","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Claire Munroe","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Robert L. Atmar","author_inst":"Baylor College of Medicine, Houston, TX, USA"},{"author_name":"Julianna Colado","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Hadley Burroughs","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Manuel Calvopi\u00f1a","author_inst":"Universidad de las Am\u00e9ricas, Facultad de Medicina, Carrera de Medicina, Quito, Ecuador"},{"author_name":"William Cevallos","author_inst":"Universidad Central del Ecuador, Instituto de Biomedicina, Quito, Ecuador"},{"author_name":"Josefina Coloma","author_inst":"School of Public Health, University of California, Berkeley, CA, USA"},{"author_name":"Gwenyth O. Lee","author_inst":"Rutgers Global Health Institute and Department of Biostatistics and Epidemiology, School of Public Health, Rutgers University, New Brunswick, NJ, USA"},{"author_name":"Gabriel Trueba","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Joseph N.S. Eisenberg","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Karen Levy","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Benjamin F. Arnold","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Measuring enteric pathogen force of infection through antibody responses in children","rel_doi":"10.64898\/2026.09.29.26364344","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364344","rel_abs":"Enteric pathogens account for a substantial global disease burden, yet population-based surveillance remains limited by the transient nature of pathogen shedding, which constrains the sensitivity of stool-based molecular testing to a narrow detection window. Detection of IgG responses in serological surveys could enable new insights into enteric pathogen transmission, but benchmarking serological measures relative to stool-based measures of infection remains a critical evidence gap. We compared measures of disease transmission in longitudinal birth cohort samples using multiplex IgG (1,601 dried blood spots, 370 children) and PCR assays (2,231 stool samples, 370 children) that overlapped for nine pathogens (norovirus GI, GII, Shigella\/enteroinvasive Escherichia coli (EIEC), Campylobacter spp., enterotoxigenic Escherichia coli (LT-ETEC), Salmonella enterica, Giardia spp., Cryptosporidium spp., Entamoeba histolytica). LT-ETEC and Campylobacter ranked highest while E. histolytica and S. enterica ranked lowest by both IgG and PCR measures of infection. Measures of infection were less aligned for norovirus GI, norovirus GII, Cryptosporidium, Shigella\/EIEC, and Giardia. Despite this, for most pathogens, and across both measures, force of infection was lowest in the urban city of Esmeraldas and substantially higher in more rural populations, with relative risks in assay measures (seroconversion rate and PCR detected prevalence) over 2.0 for pathogens with the largest differences (Shigella\/EIEC and norovirus GI). Together, our results suggest that although absolute levels of infection differed between assays, IgG and PCR captured consistent relative risk of infection across geographic strata, suggesting either method can identify high- versus low-transmission settings.","rel_num_authors":25,"rel_authors":[{"author_name":"Nikolina Walas","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Lesly Simba\u00f1a Vivanco","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Stuart Torres Ayala","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Chabier Coleman","author_inst":"Independent consultant"},{"author_name":"E. Brook Goodhew","author_inst":"Independent consultant"},{"author_name":"Kelsey J. Jesser","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Nicolette A. Zhou","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Christine S. Fagnant-Sperati","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jesse Contreras","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Caitlin Hemlock","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jeffrey W. Priest","author_inst":"Retired"},{"author_name":"Richelle C. Charles","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Edward T. Ryan","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Claire Munroe","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Robert L. Atmar","author_inst":"Baylor College of Medicine, Houston, TX, USA"},{"author_name":"Julianna Colado","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Hadley Burroughs","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Manuel Calvopi\u00f1a","author_inst":"Universidad de las Am\u00e9ricas, Facultad de Medicina, Carrera de Medicina, Quito, Ecuador"},{"author_name":"William Cevallos","author_inst":"Universidad Central del Ecuador, Instituto de Biomedicina, Quito, Ecuador"},{"author_name":"Josefina Coloma","author_inst":"School of Public Health, University of California, Berkeley, CA, USA"},{"author_name":"Gwenyth O. Lee","author_inst":"Rutgers Global Health Institute and Department of Biostatistics and Epidemiology, School of Public Health, Rutgers University, New Brunswick, NJ, USA"},{"author_name":"Gabriel Trueba","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Joseph N.S. Eisenberg","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Karen Levy","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Benjamin F. Arnold","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Measuring enteric pathogen force of infection through antibody responses in children","rel_doi":"10.64898\/2026.09.29.26364344","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364344","rel_abs":"Enteric pathogens account for a substantial global disease burden, yet population-based surveillance remains limited by the transient nature of pathogen shedding, which constrains the sensitivity of stool-based molecular testing to a narrow detection window. Detection of IgG responses in serological surveys could enable new insights into enteric pathogen transmission, but benchmarking serological measures relative to stool-based measures of infection remains a critical evidence gap. We compared measures of disease transmission in longitudinal birth cohort samples using multiplex IgG (1,601 dried blood spots, 370 children) and PCR assays (2,231 stool samples, 370 children) that overlapped for nine pathogens (norovirus GI, GII, Shigella\/enteroinvasive Escherichia coli (EIEC), Campylobacter spp., enterotoxigenic Escherichia coli (LT-ETEC), Salmonella enterica, Giardia spp., Cryptosporidium spp., Entamoeba histolytica). LT-ETEC and Campylobacter ranked highest while E. histolytica and S. enterica ranked lowest by both IgG and PCR measures of infection. Measures of infection were less aligned for norovirus GI, norovirus GII, Cryptosporidium, Shigella\/EIEC, and Giardia. Despite this, for most pathogens, and across both measures, force of infection was lowest in the urban city of Esmeraldas and substantially higher in more rural populations, with relative risks in assay measures (seroconversion rate and PCR detected prevalence) over 2.0 for pathogens with the largest differences (Shigella\/EIEC and norovirus GI). Together, our results suggest that although absolute levels of infection differed between assays, IgG and PCR captured consistent relative risk of infection across geographic strata, suggesting either method can identify high- versus low-transmission settings.","rel_num_authors":25,"rel_authors":[{"author_name":"Nikolina Walas","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Lesly Simba\u00f1a Vivanco","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Stuart Torres Ayala","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Chabier Coleman","author_inst":"Independent consultant"},{"author_name":"E. Brook Goodhew","author_inst":"Independent consultant"},{"author_name":"Kelsey J. Jesser","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Nicolette A. Zhou","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Christine S. Fagnant-Sperati","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jesse Contreras","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Caitlin Hemlock","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Jeffrey W. Priest","author_inst":"Retired"},{"author_name":"Richelle C. Charles","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Edward T. Ryan","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Claire Munroe","author_inst":"Massachusetts General Hospital, Harvard Medical School, Harvard T.H. Chan School of Public Health, Boston, MA, USA"},{"author_name":"Robert L. Atmar","author_inst":"Baylor College of Medicine, Houston, TX, USA"},{"author_name":"Julianna Colado","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Hadley Burroughs","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"},{"author_name":"Manuel Calvopi\u00f1a","author_inst":"Universidad de las Am\u00e9ricas, Facultad de Medicina, Carrera de Medicina, Quito, Ecuador"},{"author_name":"William Cevallos","author_inst":"Universidad Central del Ecuador, Instituto de Biomedicina, Quito, Ecuador"},{"author_name":"Josefina Coloma","author_inst":"School of Public Health, University of California, Berkeley, CA, USA"},{"author_name":"Gwenyth O. Lee","author_inst":"Rutgers Global Health Institute and Department of Biostatistics and Epidemiology, School of Public Health, Rutgers University, New Brunswick, NJ, USA"},{"author_name":"Gabriel Trueba","author_inst":"Institute of Microbiology, Colegio de Ciencias Biol\u00f3gicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador"},{"author_name":"Joseph N.S. Eisenberg","author_inst":"Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA"},{"author_name":"Karen Levy","author_inst":"Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, USA"},{"author_name":"Benjamin F. Arnold","author_inst":"Francis I. Proctor Foundation, University of California, San Francisco, CA, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Escaping the Negative Attentional Bias in Depression with Real-Time Neurofeedback","rel_doi":"10.64898\/2026.09.30.26363896","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26363896","rel_abs":"Individuals with major depressive disorder (MDD) show an attentional bias toward negatively valenced stimuli and thoughts. In this study, we applied a closed-loop neurofeedback procedure designed to reduce this bias. Participants were shown composite negative faces and neutral scenes with variable opacity and were instructed to attend to the neutral scene while ignoring the negative face. Internal attentional states were decoded in real time from functional magnetic resonance imaging (fMRI) data. When a participant's decoded attentional state indicated a failure to ignore the negative faces, the faces became more visible (higher opacity), thus externalizing the brain's attentional lapse in that moment. Forty-eight individuals with MDD were randomly assigned to a real neurofeedback training group (N = 24) or a sham control group (N = 24); the control group received feedback yoked to a participant in the real group. All participants completed three fMRI neurofeedback sessions. The main outcome quantified the extent to which participants got ``stuck'' in the most negative attentional state of focusing strongly on the negative faces. We hypothesized that the real neurofeedback group would learn to escape that state by the end of training, relative to the sham control group. Consistent with our hypothesis, neurofeedback training reduced the probability of getting stuck in the most negative attentional state. In offline analyses, training reduced fMRI activity in the precuneus\/posterior cingulate and the medial prefrontal cortex when participants successfully attended to scenes and ignored faces. These results demonstrate the efficacy of remediating the negative attentional bias in depression with closed-loop neurofeedback from real-time fMRI.","rel_num_authors":9,"rel_authors":[{"author_name":"Nitzan Lubianiker","author_inst":"Department of Psychology, Yale University, New Haven, CT, USA"},{"author_name":"Brendan Woods","author_inst":"Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"},{"author_name":"Frederick Nitchie","author_inst":"Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"},{"author_name":"Alexandra Batzdorf","author_inst":"Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"},{"author_name":"Anne Mennen","author_inst":"Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA"},{"author_name":"Qi Lin","author_inst":"Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea"},{"author_name":"Kenneth A. Norman","author_inst":"Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA"},{"author_name":"Nicholas B. Turk-Browne","author_inst":"Department of Psychology, Yale University, New Haven, CT, USA"},{"author_name":"Yvette I. Sheline","author_inst":"Center for Neuromodulation in Depression and Stress, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Metabolic Signatures of Resistance to Mycobacterium Tuberculosis Infection: Insights from a Multi-Country Plasma Metabolomics Study","rel_doi":"10.64898\/2026.09.29.26364337","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364337","rel_abs":"Background: Tuberculosis (TB) remains the leading infectious disease cause of mortality worldwide. A subset of individuals exposed to Mycobacterium tuberculosis (Mtb) remain TST\/IGRA-negative despite sustained exposure, termed \"TB resisters\". The biological mechanisms underlying this resistance remain poorly understood. We applied untargeted high-resolution metabolomics to determine whether systemic metabolic profiles differ between TB resisters and matched Mtb-infected close contacts. Methods: We compared untargeted high-resolution plasma metabolomics using liquid chromatography mass spectrometry between 269 TB resisters and 269 matched Mtb-infected close contacts, enrolled across Brazil, India, and South Africa. TB resisters were defined as highly exposed close contacts who slept in the same room or spent at least 5 hours indoors per day with an infectious pulmonary TB index patient, but remained TST\/IGRA-negative. Mtb-infected close contacts were those who were TST\/IGRA positive. Metabolome-wide association studies (MWAS) were conducted using paired t-tests. Results: There were 1,787 features with nominal differences between TB resisters and matched Mtb-infected contacts (p < 0.05). Pathway enrichment identified fructose and mannose metabolism and bile acid biosynthesis in the overall cohort, while lipid-related pathways were enriched in Brazil. Among metabolites with confirmed chemical identities, glyceric acid concentrations were higher in TB resisters by 0.53 uM, whereas hydroxyproline was lower by 0.90 uM, butyrobetaine was lower by 0.06 uM, and homogentisate was lower by 0.0036 uM at false discovery rate of 0.2. Conclusions: Plasma metabolomic profiles differed between TB resisters and matched Mtb-infected close contacts. These findings indicate that systemic metabolic differences are associated with resistance to Mtb infection.","rel_num_authors":22,"rel_authors":[{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mariana Araujo Pereira","author_inst":"Fundacao Oswaldo Cruz"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Universidade do Estado do Amazonas, Manaus, Brazil"},{"author_name":"Artur Trancoso Lopo de Queiroz","author_inst":"Laboratorio de Pesquisa Clinica e Translacional, Instituto Goncalo Moniz, Fundacao Oswaldo Cruz, Salvador, Brazil"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Rajesh Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Jerrold J. Ellner","author_inst":"Department of Medicine, Division of Infectious Diseases, Rutgers New Jersey Medical School, Rutgers Health, Newark, New Jersey, USA"},{"author_name":"James C.M. Brust","author_inst":"Division of General Internal Medicine, Albert Einstein College of Medicine, Bronx, NY, USA"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Yan V. Sun","author_inst":"Emory University"},{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"- TB GWAS collaboration","author_inst":""}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Metabolic Signatures of Resistance to Mycobacterium Tuberculosis Infection: Insights from a Multi-Country Plasma Metabolomics Study","rel_doi":"10.64898\/2026.09.29.26364337","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364337","rel_abs":"Background: Tuberculosis (TB) remains the leading infectious disease cause of mortality worldwide. A subset of individuals exposed to Mycobacterium tuberculosis (Mtb) remain TST\/IGRA-negative despite sustained exposure, termed \"TB resisters\". The biological mechanisms underlying this resistance remain poorly understood. We applied untargeted high-resolution metabolomics to determine whether systemic metabolic profiles differ between TB resisters and matched Mtb-infected close contacts. Methods: We compared untargeted high-resolution plasma metabolomics using liquid chromatography mass spectrometry between 269 TB resisters and 269 matched Mtb-infected close contacts, enrolled across Brazil, India, and South Africa. TB resisters were defined as highly exposed close contacts who slept in the same room or spent at least 5 hours indoors per day with an infectious pulmonary TB index patient, but remained TST\/IGRA-negative. Mtb-infected close contacts were those who were TST\/IGRA positive. Metabolome-wide association studies (MWAS) were conducted using paired t-tests. Results: There were 1,787 features with nominal differences between TB resisters and matched Mtb-infected contacts (p < 0.05). Pathway enrichment identified fructose and mannose metabolism and bile acid biosynthesis in the overall cohort, while lipid-related pathways were enriched in Brazil. Among metabolites with confirmed chemical identities, glyceric acid concentrations were higher in TB resisters by 0.53 uM, whereas hydroxyproline was lower by 0.90 uM, butyrobetaine was lower by 0.06 uM, and homogentisate was lower by 0.0036 uM at false discovery rate of 0.2. Conclusions: Plasma metabolomic profiles differed between TB resisters and matched Mtb-infected close contacts. These findings indicate that systemic metabolic differences are associated with resistance to Mtb infection.","rel_num_authors":22,"rel_authors":[{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mariana Araujo Pereira","author_inst":"Fundacao Oswaldo Cruz"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Universidade do Estado do Amazonas, Manaus, Brazil"},{"author_name":"Artur Trancoso Lopo de Queiroz","author_inst":"Laboratorio de Pesquisa Clinica e Translacional, Instituto Goncalo Moniz, Fundacao Oswaldo Cruz, Salvador, Brazil"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Rajesh Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Jerrold J. Ellner","author_inst":"Department of Medicine, Division of Infectious Diseases, Rutgers New Jersey Medical School, Rutgers Health, Newark, New Jersey, USA"},{"author_name":"James C.M. Brust","author_inst":"Division of General Internal Medicine, Albert Einstein College of Medicine, Bronx, NY, USA"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Yan V. Sun","author_inst":"Emory University"},{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"- TB GWAS collaboration","author_inst":""}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Metabolic Signatures of Resistance to Mycobacterium Tuberculosis Infection: Insights from a Multi-Country Plasma Metabolomics Study","rel_doi":"10.64898\/2026.09.29.26364337","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364337","rel_abs":"Background: Tuberculosis (TB) remains the leading infectious disease cause of mortality worldwide. A subset of individuals exposed to Mycobacterium tuberculosis (Mtb) remain TST\/IGRA-negative despite sustained exposure, termed \"TB resisters\". The biological mechanisms underlying this resistance remain poorly understood. We applied untargeted high-resolution metabolomics to determine whether systemic metabolic profiles differ between TB resisters and matched Mtb-infected close contacts. Methods: We compared untargeted high-resolution plasma metabolomics using liquid chromatography mass spectrometry between 269 TB resisters and 269 matched Mtb-infected close contacts, enrolled across Brazil, India, and South Africa. TB resisters were defined as highly exposed close contacts who slept in the same room or spent at least 5 hours indoors per day with an infectious pulmonary TB index patient, but remained TST\/IGRA-negative. Mtb-infected close contacts were those who were TST\/IGRA positive. Metabolome-wide association studies (MWAS) were conducted using paired t-tests. Results: There were 1,787 features with nominal differences between TB resisters and matched Mtb-infected contacts (p < 0.05). Pathway enrichment identified fructose and mannose metabolism and bile acid biosynthesis in the overall cohort, while lipid-related pathways were enriched in Brazil. Among metabolites with confirmed chemical identities, glyceric acid concentrations were higher in TB resisters by 0.53 uM, whereas hydroxyproline was lower by 0.90 uM, butyrobetaine was lower by 0.06 uM, and homogentisate was lower by 0.0036 uM at false discovery rate of 0.2. Conclusions: Plasma metabolomic profiles differed between TB resisters and matched Mtb-infected close contacts. These findings indicate that systemic metabolic differences are associated with resistance to Mtb infection.","rel_num_authors":22,"rel_authors":[{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mariana Araujo Pereira","author_inst":"Fundacao Oswaldo Cruz"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Universidade do Estado do Amazonas, Manaus, Brazil"},{"author_name":"Artur Trancoso Lopo de Queiroz","author_inst":"Laboratorio de Pesquisa Clinica e Translacional, Instituto Goncalo Moniz, Fundacao Oswaldo Cruz, Salvador, Brazil"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Rajesh Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Jerrold J. Ellner","author_inst":"Department of Medicine, Division of Infectious Diseases, Rutgers New Jersey Medical School, Rutgers Health, Newark, New Jersey, USA"},{"author_name":"James C.M. Brust","author_inst":"Division of General Internal Medicine, Albert Einstein College of Medicine, Bronx, NY, USA"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Yan V. Sun","author_inst":"Emory University"},{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"- TB GWAS collaboration","author_inst":""}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Metabolic Signatures of Resistance to Mycobacterium Tuberculosis Infection: Insights from a Multi-Country Plasma Metabolomics Study","rel_doi":"10.64898\/2026.09.29.26364337","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364337","rel_abs":"Background: Tuberculosis (TB) remains the leading infectious disease cause of mortality worldwide. A subset of individuals exposed to Mycobacterium tuberculosis (Mtb) remain TST\/IGRA-negative despite sustained exposure, termed \"TB resisters\". The biological mechanisms underlying this resistance remain poorly understood. We applied untargeted high-resolution metabolomics to determine whether systemic metabolic profiles differ between TB resisters and matched Mtb-infected close contacts. Methods: We compared untargeted high-resolution plasma metabolomics using liquid chromatography mass spectrometry between 269 TB resisters and 269 matched Mtb-infected close contacts, enrolled across Brazil, India, and South Africa. TB resisters were defined as highly exposed close contacts who slept in the same room or spent at least 5 hours indoors per day with an infectious pulmonary TB index patient, but remained TST\/IGRA-negative. Mtb-infected close contacts were those who were TST\/IGRA positive. Metabolome-wide association studies (MWAS) were conducted using paired t-tests. Results: There were 1,787 features with nominal differences between TB resisters and matched Mtb-infected contacts (p < 0.05). Pathway enrichment identified fructose and mannose metabolism and bile acid biosynthesis in the overall cohort, while lipid-related pathways were enriched in Brazil. Among metabolites with confirmed chemical identities, glyceric acid concentrations were higher in TB resisters by 0.53 uM, whereas hydroxyproline was lower by 0.90 uM, butyrobetaine was lower by 0.06 uM, and homogentisate was lower by 0.0036 uM at false discovery rate of 0.2. Conclusions: Plasma metabolomic profiles differed between TB resisters and matched Mtb-infected close contacts. These findings indicate that systemic metabolic differences are associated with resistance to Mtb infection.","rel_num_authors":22,"rel_authors":[{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mariana Araujo Pereira","author_inst":"Fundacao Oswaldo Cruz"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit, University of the Witwatersrand, Johannesburg, South Africa"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Universidade do Estado do Amazonas, Manaus, Brazil"},{"author_name":"Artur Trancoso Lopo de Queiroz","author_inst":"Laboratorio de Pesquisa Clinica e Translacional, Instituto Goncalo Moniz, Fundacao Oswaldo Cruz, Salvador, Brazil"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre, Hyderabad, India"},{"author_name":"Rajesh Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Jerrold J. Ellner","author_inst":"Department of Medicine, Division of Infectious Diseases, Rutgers New Jersey Medical School, Rutgers Health, Newark, New Jersey, USA"},{"author_name":"James C.M. Brust","author_inst":"Division of General Internal Medicine, Albert Einstein College of Medicine, Bronx, NY, USA"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Yan V. Sun","author_inst":"Emory University"},{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"- TB GWAS collaboration","author_inst":""}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"A Framework to Monitor Editing of Artificial Intelligence-Generated Medical Documentation","rel_doi":"10.64898\/2026.09.30.26364427","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364427","rel_abs":"Objective: To develop and evaluate a framework for characterizing clinician editing of Artificial Intelligence (AI)-generated[KS1.1] documentation and assess its feasibility for health system-level monitoring of AI scribes. Materials and Methods: We analyzed outpatient encounters in which an AI scribe was used at a single academic health system, examining the History of Present Illness (HPI) and Assessment and Plan (A&P) sections of notes. We characterized edits on three dimensions[KS2.1][AG2.2]: lexical edit intensity based on Levenshtein distance, embedding edit intensity BERT[KS3.1]Score, and clinical edit intensity based on removed and added UMLS[KS4.1][AG4.2] concepts.[KS5.1][AG5.2] We analyzed the Positive Predictive Value (PPV) of clinical edit intensity as a measure of clinically meaningful editing using clinicians as the gold standard, examined correlations among dimensions, and designed exponentially weighted moving-average control charts to monitor longitudinal changes in clinician editing behavior.[KS6.1][AG6.2] Results: 268,379 encounters were included (267,654 HPI, 267,594 A&P). Clinical edit intensity [&ge;]1 had an 88.9% PPV for clinically meaningful editing. Lexical and embedding edit intensity were highly correlated (Spearman {rho} 0.95), while clinical edit intensity was less strongly correlated with both ({rho} 0.77-0.81). Longitudinal monitoring detected changes coinciding with system-wide rollout.[KS7.1][AG7.2] Discussion:[KS8.1][AG8.2] Clinicians edited A&Ps more heavily than HPIs, potentially reflecting greater attention to content involving clinical decision-making. Over one-third of sections involved clinical concept changes, and clinical edit intensity identified clinically meaningful edits while providing information complementary to lexical editing measures. Conclusion: Clinician editing can be characterized at scale using complementary editing dimensions, providing a scalable signal for post-deployment surveillance of the human-AI documentation process.","rel_num_authors":17,"rel_authors":[{"author_name":"Augusto Garcia-Agundez","author_inst":"University of California San Francisco"},{"author_name":"Siyu Zhou","author_inst":"University of California San Francisco"},{"author_name":"Jessica Pourian","author_inst":"University of California San Francisco"},{"author_name":"Catherine Blebea","author_inst":"University of California San Francisco"},{"author_name":"Parnaz Daneshpajouhnejad","author_inst":"University of California San Francisco"},{"author_name":"Elizabeth Dente","author_inst":"University of California San Francisco"},{"author_name":"Kevin Shi","author_inst":"University of California San Francisco"},{"author_name":"Sarah Pollet","author_inst":"University of California San Francisco"},{"author_name":"Fan Xia","author_inst":"University of California San Francisco"},{"author_name":"Xu Shi","author_inst":"University of Michigan"},{"author_name":"Robert Thombley","author_inst":"University of California San Francisco"},{"author_name":"Cynthia Fenton","author_inst":"University of California San Francisco"},{"author_name":"Sara G Murray","author_inst":"University of California San Francisco"},{"author_name":"Julia Adler-Milstein","author_inst":"University of California San Francisco"},{"author_name":"Gabriela Schmajuk","author_inst":"University of California San Francisco"},{"author_name":"Jean Feng","author_inst":"University of California San Francisco"},{"author_name":"Jinoos Yazdany","author_inst":"University of California San Francisco"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Cohort-scale Spatial Host-Microbiome Predicts Post-Resection Recurrence in Colorectal Cancer","rel_doi":"10.64898\/2026.09.29.26363734","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26363734","rel_abs":"The tumor microenvironment in colorectal cancer (CRC) is a heterogeneous ecosystem in which host cells and microbial communities interact dynamically, influencing disease progression. However, the clinical utility is limited by the lack of a scalable spatial host-microbiome technique and by insufficient integration of artificial intelligence for the interpretation of high-dimensional multi-omics data. To overcome the barriers, we present AlphaFISH, a platform technology integrating both technical and computational innovations for multi-omics spatial analysis of clinical biopsies at subcellular resolution. The system uses a sequencing-free, high-throughput, spatial profiling technique to construct, to date, the largest clinical spatial transcriptomics and spatial microbiome datasets acquired from 149 colorectal biopsies from 68 human subjects, supported by a comprehensive scRNA-seq atlas covering 4.27 million cells across 650 patients for robust cell annotation. Deep learning of the cohort-scale dual-omics data, consisting of more than 10 million subcellular sampling vectors, enables the development of a transformer model with joint embeddings of gene expression, spatial architecture, and the microbial microenvironment in colon tissues, achieving nearly 90% accuracy in predicting CRC-associated pathological features using unseen spatial omics inputs. The AI interrogation further predicts tumour recurrence at 81% accuracy in 28 patients followed within 1 year post tumor resection period. AlphaFISH reveals that spatial interactions between Fusobacterium and cellular niche consisting of tumor and T cells serve as key markers of CRC malignancy, progression, and recurrence, indicating the critical role of spatial bacterial-immune crosstalks.","rel_num_authors":13,"rel_authors":[{"author_name":"Feng Guo","author_inst":"City University of Hong Kong"},{"author_name":"Hailiang Sun","author_inst":"City University of Hong Kong"},{"author_name":"Chenxi Hu","author_inst":"Tsinghua University; Institute for AI Industry Research, Tsinghua University"},{"author_name":"Minsheng Hao","author_inst":"Tsinghua University"},{"author_name":"Youyang Wan","author_inst":"City University of Hong Kong"},{"author_name":"Chuxiao Xiong","author_inst":"City University of Hong Kong"},{"author_name":"Feng Gao","author_inst":"The Sixth Affiliated Hospital, Sun Yat-sen University"},{"author_name":"Lung-Yi Mak","author_inst":"University of Hong Kong"},{"author_name":"Xin Deng","author_inst":"City University of Hong Kong"},{"author_name":"Ajay Goel","author_inst":"City of Hope Comprehensive Cancer Center"},{"author_name":"Jia Ke","author_inst":"The Sixth Affiliated Hospital, Sun Yat-sen University"},{"author_name":"Jianzhu Ma","author_inst":"Institute for AI Industry Research, Tsinghua University; Department of Electronic Engineering, Tsinghua University"},{"author_name":"Peng Shi","author_inst":"City University of Hong Kong; Hong Kong Centre for Cerebro-Cardiovascular Health Engineering; COSDAF, City University of Hong Kong; Shenzhen Research Institute,"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Functional near infrared spectroscopy-based dual-stream adaptive language mapping in adults with and without post-stroke aphasia","rel_doi":"10.64898\/2026.09.28.26364106","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.28.26364106","rel_abs":"In aphasia, variability in lesion location and post-stroke network reorganization complicates efforts to identify the regions that support semantic versus phonological processing. In prior work, researchers have often examined these domains in separate patient cohorts, further limiting direct comparison of their neural substrates within aphasia. To address this gap, we investigated the degree of overlap and specialization within semantic and phonological networks in adults with and without aphasia and examined how neural activity relates to task performance and lesion profiles. Sixteen neurologically healthy adults and 15 participants with aphasia following left hemisphere stroke completed adaptive Semantic Matching and Rhyme Judgment tasks during functional near-infrared spectroscopy (fNIRS) recording. Changes in oxyhemoglobin and deoxyhemoglobin were measured within regions of interest, and activation was related to standardized task performance and damage to left ventral and dorsal language pathways in participants with aphasia. Controls showed largely distinct activation patterns consistent with prior fMRI findings: Semantic Matching preferentially recruited ventral stream regions, particularly left temporal cortex, whereas Rhyme Judgment more strongly recruited dorsal regions, including left inferior frontal and inferior parietal cortex. Participants with aphasia showed greater inter-individual variability and no clear group-level segregation of dorsal and ventral activity. Better Semantic Matching performance was associated with less left ventral stream damage and greater left dorsal activation, whereas better Rhyme Judgment performance was associated with lower right hemisphere ventral and dorsal activation. These findings suggest that post-stroke language performance reflects residual specialization, lesion-dependent constraints, and flexible recruitment of surviving tissue. Overall, fNIRS shows promise as an alternative to fMRI for language mapping in post-stroke aphasia, although replication in larger samples with more extensive cortical coverage is warranted.","rel_num_authors":8,"rel_authors":[{"author_name":"Erin L. Meier","author_inst":"Northeastern University"},{"author_name":"Veronica Fletcher","author_inst":"Northeastern University"},{"author_name":"Caela Hung","author_inst":"Northeastern University"},{"author_name":"Esprit Ange Andraos","author_inst":"Northeastern University"},{"author_name":"Leanna Ugent","author_inst":"Northeastern University"},{"author_name":"Gengchen Wei","author_inst":"Northeastern University"},{"author_name":"David J. Lin","author_inst":"Massachusetts General Hospital"},{"author_name":"Meryem A. Y\u00fccel","author_inst":"Boston University"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Diurnal Heart Rate Range and Heart Rate Excursions: Novel Characterizations of Wearable Heart Rate Variability With an Application to Aging","rel_doi":"10.64898\/2026.09.29.26364190","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.29.26364190","rel_abs":"Background Wearable heart rate (HR) monitors collect minute-level HR continuously across days, yet these data are commonly reduced to scalars such as resting HR (RHR) and heart rate reserve (HRR), defined as the difference between maximum HR and RHR. This discards two dimensions of within-day HR dynamics: how HR range varies across the day and the magnitude and duration of individual HR rises and declines. We introduce diurnal heart rate range (dHRR), a time-of-day-specific measure of HR range across repeated days, and heart rate excursions (HREs), individual HR rises and declines characterized by amplitude and duration. Methods We analyzed minute-level HR from 750 participants in the Baltimore Longitudinal Study of Aging (mean [SD] age, 66 [12] years). We estimated the 5th, 50th, and 95th HR percentiles at each minute of the 24-hour cycle across repeated days, defining diurnal HR (dHR) as the median curve and dHRR as the 95th minus 5th percentile curve. A moving-average algorithm segmented HR into HREs. Function-on-scalar regression modeled dHR and dHRR by age, sex,and BMI across the day; local polynomial regression examined age and sex differences in HRR and HREs. Results Conventional HRR decreased with age, indicating a smaller overall observed HR range. Age-related differences in dHR varied substantially across the day: between ages 40 and 80, fitted dHR was approximately 2 bpm lower at 3:00 AM but 8 bpm lower at 6:00 PM. dHRR showed that this contraction was not uniform across the day: the evening peak near 6:00 PM at younger ages was largely absent by age 70, while the morning peak shifted from approximately 9:00 AM toward noon. At the event level, HREs showed two parallel age-related changes: between ages 40 and 80, mean excursion amplitude decreased from approximately 40 to 32 bpm, while mean excursion duration increased from approximately 90 to 104 minutes. Conclusions Aging was characterized by a smaller global HR range, compression and reorganization of HR range across the day, and smaller, longer-lasting HREs. dHRR and HREs provide complementary views of the diurnal organization and event-level dynamics of wearable HR and are implemented in the open-source ihr R package.","rel_num_authors":8,"rel_authors":[{"author_name":"Samuel D Fansler","author_inst":"Johns Hopkins University Bloomberg School of Public Health"},{"author_name":"Owen Yoo","author_inst":"University of Michigan College of Literature, Science, and the Arts"},{"author_name":"Shuiqing Han","author_inst":"University of Michigan College of Literature, Science, and the Arts"},{"author_name":"Luigi Ferrucci","author_inst":"NIH-NIA"},{"author_name":"Eleanor Simonsick","author_inst":"NIH-NIA"},{"author_name":"Jennifer A Schrack","author_inst":"Johns Hopkins University Bloomberg School of Public Health"},{"author_name":"Irina Gaynanova","author_inst":"University of Michigan School of Public Health"},{"author_name":"Vadim Zipunnikov","author_inst":"Johns Hopkins University Bloomberg School of Public Health"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Rare coding variation implicates thirteen genes in bipolar disorder across 232,536 individuals from global populations","rel_doi":"10.64898\/2026.09.30.26364416","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.30.26364416","rel_abs":"Bipolar disorder (BD) is highly heritable, yet the contribution of rare coding variation remains incompletely characterized. We analyzed sequencing data from 64,435 individuals with BD and 168,101 controls spanning multiple ancestries and 22 countries, representing the largest and most global sequencing resource with a 6.7-fold increase in effective sample size over the previous study iteration. We observe enrichment of protein-truncating and damaging missense variants in constrained genes and curated neuropsychiatric gene sets, with no enrichment of synonymous variation. These enrichment signals were consistent across ancestry groups, suggesting that genetic risk factors for BD are consistent worldwide. Gene-level analyses identified 13 exome-wide significant genes and an additional 20 genes at FDR < 0.05. These genes showed convergence with common and rare variant risk across other neuropsychiatric disorders. Expression analyses also showed preferential brain expression and increased developmental expression during early childhood. Modelling 3D protein structures further highlighted clustering of ultra-rare missense variants at a predicted interaction interfaces in two Bonferroni-significant genes, DOP1A and ATP9A; a potential mechanism linking membrane trafficking to BD risk. Together, these results implicate a constellation of rare variants that map onto neuronal biology and demonstrate that diverse global populations converge on shared genetic signals underlying BD risk.","rel_num_authors":88,"rel_authors":[{"author_name":"Calwing Liao","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "},{"author_name":"Robert Ye","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Julia M Sealock","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Toni Boltz","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Franjo Ivankovic","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Hilary Finucane","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Daniel Howrigan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Yijia Christiana Liu","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"F Kyle Satterstrom","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Arsalan Hassan","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Melkam Alemayehu","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Stella Gichuru","author_inst":"Aga Khan University Medical College, East Africa, Nairobi, Kenya"},{"author_name":"Rehema Mwende","author_inst":"Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Charles Newton","author_inst":"Kenya Medical Research Institute (KEMRI), Nairobi, Kenya"},{"author_name":"Nastassja Koen","author_inst":"Dept of Psychiatry and Neuroscience Institute, University of Cape Town, South Africa"},{"author_name":"Zukiswa Zingela","author_inst":"Nelson Mandela University, Gqeberha, South Africa"},{"author_name":"Ana M Diaz-Zuluaga","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Ana M Ramirez-Diaz","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Victor I Reus","author_inst":"Department of Psychiatry and Behavioral Sciences, School of Medicine, University of California, San Francisco, San Francisco, California, USA; Laboratory of Neu"},{"author_name":"Terri Teshiba","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Aarno Palotie","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Eija Hamalainen","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland"},{"author_name":"Olli Pietilainen","author_inst":"Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland"},{"author_name":"Penelope A Lind","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Dan J Siskind","author_inst":"Addiction and Mental Health Service, Metro South Health, Brisbane, Qld, Australia; Faculty of Health, Medicine and Behavioural Sciences, University of Queenslan"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia"},{"author_name":"Pamela Morales-Cedillo","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Joanna Jimenez-Pavon","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico"},{"author_name":"Marco Antonio Sanabrais-Jimenez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlo Esteban Sotelo-Ramirez","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Eric Hahn","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Van Phi Nguyen","author_inst":"Hanoi Medical University, Vietnam, National Geriatric Hospital"},{"author_name":"Elizabeth Karlson","author_inst":"Harvard Medical School, Mass General Brigham (MGB), Brigham and Women's Hospital, Boston, Massachusetts, USA"},{"author_name":"Chiao-Erh Chang","author_inst":"Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; Stanley Center for Psychiatric Research, Broad Institute, Cambrid"},{"author_name":"Hsi-Chung Chen","author_inst":"School of Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwa"},{"author_name":"Martin Alda","author_inst":"Dalhousie University"},{"author_name":"Mikael Landen","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Jordan W Smoller","author_inst":"Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Psychiatry, Harvard Medical School, "},{"author_name":"Nicholas Craddock","author_inst":"Cardiff University, Cardiff, Wales, UK"},{"author_name":"Marquis P Vawter","author_inst":"University of California, Irvine, Irvine, California, USA"},{"author_name":"David Curtis","author_inst":"UCL Genetics Institute, University College London, London, UK"},{"author_name":"Andrew McQuillin","author_inst":"University College London, London, UK"},{"author_name":"Rene S Kahn","author_inst":"Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA"},{"author_name":"Roel A Ophoff","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Annabel Vreeker","author_inst":"Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, Netherlands; "},{"author_name":"Christina Hultman","author_inst":"Karolinska Institutet, Stockholm, Sweden"},{"author_name":"Patrick F Sullivan","author_inst":"Karolinska Institutet, Stockholm, Sweden; University of North Carolina, Chapel Hill, North Carolina, USA"},{"author_name":"Michael E Talkowski","author_inst":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"author_name":"Douglas H Blackwood","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Andrew McIntosh","author_inst":"University of Edinburgh, Edinburgh, UK"},{"author_name":"Ann E Pulver","author_inst":"School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Bruce Cohen","author_inst":"McLean Hospital, Harvard Medical School, Belmont, Massachusetts, USA"},{"author_name":"Rolf Adolfsson","author_inst":"Department of Clinical Sciences, Psychiatry, Umea University, Umea, Sweden"},{"author_name":"Andreas Reif","author_inst":"Department of Psychiatry, Universitatsklinikum Frankfurt, Frankfurt, Germany"},{"author_name":"Fernando Goes","author_inst":"Johns Hopkins University"},{"author_name":"Robert Yolken","author_inst":"Stanley Division of Developmental Neurovirology, Johns Hopkins University, Baltimore, Maryland, USA"},{"author_name":"Aiden P Corvin","author_inst":"Trinity College Dublin, Dublin, Ireland"},{"author_name":"Derek W Morris","author_inst":"University of Galway, Galway, Ireland"},{"author_name":"- BIPEX Collection Scientists","author_inst":""},{"author_name":"Felecia Cerrato","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Sinead B Chapman","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Analytic and Translational Genetics Unit, Depart"},{"author_name":"Caroline Cusick","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Zhenglin Guo","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Ana Maria Olivares","author_inst":"Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA"},{"author_name":"Guy A Rouleau","author_inst":"McGill University, Montreal, Quebec, Canada"},{"author_name":"Biju Viswanath","author_inst":"National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India"},{"author_name":"Po-Hsiu Kuo","author_inst":"Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan"},{"author_name":"Van Tuan Nguyen","author_inst":"Hanoi Medical University"},{"author_name":"Thi Minh Tam Ta","author_inst":"Charite - Universitatsmedizin Berlin, Berlin, Germany; Hanoi Medical University, Hanoi, Vietnam"},{"author_name":"Beatriz Camarena","author_inst":"Instituto Nacional de Psiquiatria Ramon de la Fuente Muniz, Mexico City, Mexico"},{"author_name":"Carlos N Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Michele T Pato","author_inst":"Rutgers University, New Brunswick, New Jersey, USA; BD2: Breakthrough Discoveries for Thriving with Bipolar Disorder, Santa Monica, California, USA"},{"author_name":"Sarah E Medland","author_inst":"QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia"},{"author_name":"Nelson Freimer","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Loes Olde Loohuis","author_inst":"Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles,"},{"author_name":"Carlos Lopez-Jaramillo","author_inst":"Department of Psychiatry, School of Medicine, Universidad de Antioquia, Medellin, Antioquia, Colombia; Research Group in Psychiatry, Department of Psychiatry, S"},{"author_name":"Rocky Stroud II","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Lukoye Atwoli","author_inst":"Department of Medicine, Aga Khan University Medical College East Africa, Nairobi, Kenya; Brain and Mind Institute, Aga Khan University, Nairobi, Kenya"},{"author_name":"Akena Dickens","author_inst":"Makerere University, Kampala, Uganda"},{"author_name":"Karestan C Koenen","author_inst":"Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA; Stanley Center for Psychiatric Research, The Broad Institute"},{"author_name":"Symon M Kariuki","author_inst":"African Population and Health Research Center, Nairobi, Kenya"},{"author_name":"Solomon Teferra","author_inst":"Addis Ababa University, Addis Ababa, Ethiopia"},{"author_name":"Dan J Stein","author_inst":"South African Medical Research Council (SAMRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University "},{"author_name":"Muhammad Ayub","author_inst":"Division of Psychiatry, University College London, London, UK"},{"author_name":"James Knowles","author_inst":"Rutgers University, New Brunswick, New Jersey, USA"},{"author_name":"Mark J Daly","author_inst":"Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Department of Medic"},{"author_name":"Hailiang Huang","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Stanley Center for Psychiatric Res"},{"author_name":"Benjamin M Neale","author_inst":"Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA; Program in Medical and Population "}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Release-aware, SAS-equivalent Elixhauser comorbidity scoring in R: cross-implementation validation and application to Texas inpatient discharges","rel_doi":"10.64898\/2026.10.01.26364551","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364551","rel_abs":"The Elixhauser comorbidity measures are among the most widely used risk adjusters in administrative health data. Their reference implementation, published by the Agency for Healthcare Research and Quality (AHRQ) as SAS programs, has eleven annual releases in two families, one screening pre-existing conditions on the present-on-admission (POA) indicator and the earlier one on Medicare Severity Diagnosis-Related Group, and no implementation of every release existed outside SAS. We developed `ecsr10`, an open-source R package covering all eleven releases of both families, with a browser-based application over the same functions, and validated it against AHRQ's own SAS programs over 40,027,114 value-level comparisons with zero disagreements. Two existing open-source reimplementations scored on the same dataset showed reproducible defects. We then used the package to quantify two choices AHRQ's software leaves to the analyst and studies seldom report, the release and the handling of diagnoses not present on admission, on the Texas Inpatient Public Use Data File, 2016 Q1-2019 Q4 (8,585,244 adult discharges from 726 hospitals), scoring one predefined cohort under every release and pre-existing-condition setting. POA handling dominated: disabling POA changed the comorbidity profile of 56.7% of admissions, and a POA-naive mortality index scored higher on discrimination (area under the curve 0.807 versus 0.789; difference 0.0183, 95% confidence interval 0.0161-0.0204) by counting in-hospital complications as pre-existing disease. POA reporting was bimodal across hospitals, so pooled hospital comparisons on such a file partly compare documentation practice. Because the cohort predates every release compared, the release contrast is a lower bound: the release chosen between v2022.1 and v2026.1 changed at least one comorbidity flag for 0.0036% of admissions, yet a single revision of ten mortality weights changed the comorbidity index for 42.4% of them. An exactly validated implementation makes such choices measurable; release, POA handling and the implementation used should be reported as study characteristics.","rel_num_authors":2,"rel_authors":[{"author_name":"Minh Tran","author_inst":"University of Kansas Medical Center"},{"author_name":"Dong Pei","author_inst":"University of Kansas Medical Center"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Safety & Effectiveness of Mifepristone for Medication Abortion in a National Claims Cohort, 2017-2023","rel_doi":"10.64898\/2026.10.02.26364611","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364611","rel_abs":"BACKGROUND Extensive research has documented medication abortion safety. Large-scale insurance claims data offer an important complement to clinical studies by assessing real-world outcomes in routine practice. In claims data, researchers must infer mifepristone use, clinical outcomes, and event severity from diagnosis, treatment, and utilization codes. Understanding how these analytic choices influence safety and effectiveness estimates is important for interpreting evidence used to inform care delivery and medication policy. METHODS We conducted a retrospective cohort study of mifepristone use with national multipayer claims data, both medical and pharmacy, from 2017 through 2023. We identified both a broad cohort and a more specific medication-abortion cohort after excluding evidence of other indications. We classified potential safety events, effectiveness outcomes, and health care utilization within 45 days of mifepristone use. Serious adverse events required claims-observable consequences consistent with FDA seriousness criteria. RESULTS The broad cohort included 869,409 mifepristone uses among 698,780 unique patients for medication abortion or other indications. After restriction to uses with additional evidence of medication abortion, 775,931 uses among 626,443 unique patients remained. In the medication-abortion cohort, 3,306 uses were followed by at least one serious adverse event, resulting in an absolute 45-day risk of 0.43%. Serious bleeding or hemorrhage occurred after 0.24% of uses, serious infection or sepsis after 0.05%, serious hypersensitivity or anaphylaxis after 0.01%, and serious ectopic-pregnancy outcomes after 0.05%. CONCLUSIONS Serious adverse events after mifepristone use were rare in this national study. Applying established, clinically grounded criteria markedly reduced the number of events classified as serious.","rel_num_authors":6,"rel_authors":[{"author_name":"Liana R Woskie","author_inst":"Department of Community Health, Tufts University, Medford, Massachusetts, USA"},{"author_name":"Julia Strasser","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Risa Griffin","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Qian (Eric) Luo","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Maria I. Rodriguez","author_inst":"Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, Oregon, USA"},{"author_name":"Ushma Upadhyay","author_inst":"Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, San Francisco, California, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Safety & Effectiveness of Mifepristone for Medication Abortion in a National Claims Cohort, 2017-2023","rel_doi":"10.64898\/2026.10.02.26364611","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364611","rel_abs":"BACKGROUND Extensive research has documented medication abortion safety. Large-scale insurance claims data offer an important complement to clinical studies by assessing real-world outcomes in routine practice. In claims data, researchers must infer mifepristone use, clinical outcomes, and event severity from diagnosis, treatment, and utilization codes. Understanding how these analytic choices influence safety and effectiveness estimates is important for interpreting evidence used to inform care delivery and medication policy. METHODS We conducted a retrospective cohort study of mifepristone use with national multipayer claims data, both medical and pharmacy, from 2017 through 2023. We identified both a broad cohort and a more specific medication-abortion cohort after excluding evidence of other indications. We classified potential safety events, effectiveness outcomes, and health care utilization within 45 days of mifepristone use. Serious adverse events required claims-observable consequences consistent with FDA seriousness criteria. RESULTS The broad cohort included 869,409 mifepristone uses among 698,780 unique patients for medication abortion or other indications. After restriction to uses with additional evidence of medication abortion, 775,931 uses among 626,443 unique patients remained. In the medication-abortion cohort, 3,306 uses were followed by at least one serious adverse event, resulting in an absolute 45-day risk of 0.43%. Serious bleeding or hemorrhage occurred after 0.24% of uses, serious infection or sepsis after 0.05%, serious hypersensitivity or anaphylaxis after 0.01%, and serious ectopic-pregnancy outcomes after 0.05%. CONCLUSIONS Serious adverse events after mifepristone use were rare in this national study. Applying established, clinically grounded criteria markedly reduced the number of events classified as serious.","rel_num_authors":6,"rel_authors":[{"author_name":"Liana R Woskie","author_inst":"Department of Community Health, Tufts University, Medford, Massachusetts, USA"},{"author_name":"Julia Strasser","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Risa Griffin","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Qian (Eric) Luo","author_inst":"Fitzhugh Mullan Institute for Health Workforce Equity, The George Washington University, Washington, DC, USA"},{"author_name":"Maria I. Rodriguez","author_inst":"Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, Oregon, USA"},{"author_name":"Ushma Upadhyay","author_inst":"Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, San Francisco, California, USA"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Three Cerebellar Imaging Subtypes in Schizophrenia with Distinct Spatiotemporal Trajectories and Biological Characteristics","rel_doi":"10.64898\/2026.10.03.26364634","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.03.26364634","rel_abs":"The potential role of the cerebellum in the pathophysiology of schizophrenia (SCZ) has received relatively insufficient attention. Prior studies characterized cerebellar abnormalities mainly at the group level, without fully considering the heterogeneity of the disease. Here, we applied a machine learning approach (Subtype and Stage Inference, SuStaIn) to cross-sectional 3D volumetric MRIs of the cerebellum, including 1,588 individuals with SCZ (638 females; mean age: 31.9 +\/- 12.0 years) and 2,341 healthy controls (HC) (1,041 females; mean age: 33.3 +\/- 13.6 years), from 17 sites worldwide. SuStaIn identified three distinct spatiotemporal trajectories in cerebellar gray matter volume (GMV) reduction, respectively originating in lobule X (subtype 1), lobule III (subtype 2) and lobule VIIb (subtype 3), with subtypes 1 and 3 corresponding to the posterior lobe and subtype 2 to the anterior lobe. These cross-sectionally inferred trajectories were replicated in two independent samples of 1,334 and 530 patients, respectively. Multimodal analyses using neuroimaging, transcriptomic and behavioral data revealed subtype-specific biological characteristics in brain morphological patterns, cerebellar-cortical connectivity, gene expression and clinical symptoms. Specifically, subtype-related genes were enriched in metabolism-related processes and immunity-related processes, respectively, in subtype 1 and subtype 2; subtype 3 showed more severe brain abnormalities and worse cognitive symptoms. Treatment data from 381 patients, with up to 12 months of follow-up, revealed poorer response to antipsychotic medications (APM) in subtype 2 and subtype 3, but better response to transcranial magnetic stimulation (TMS) in subtype 1, which also had worse emotion-related symptoms. Together, our findings offer a comprehensive characterization of the heterogeneity of cerebellar pathophysiological progresses in SCZ, which may help in developing future clinical stratification and targeted intervention strategies.","rel_num_authors":69,"rel_authors":[{"author_name":"Zhaoyun Liu","author_inst":"School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, PR China"},{"author_name":"Zhenyu Huang","author_inst":"School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, PR China"},{"author_name":"Xinjia Lin","author_inst":"School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, PR China"},{"author_name":"Jingyu Zhou","author_inst":"School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, PR China"},{"author_name":"Hao Hu","author_inst":"Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China"},{"author_name":"Qian Guo","author_inst":"Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China"},{"author_name":"Yingying Tang","author_inst":"Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China"},{"author_name":"Tianhong Zhang","author_inst":"Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China"},{"author_name":"Jijun Wang","author_inst":"Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, PR China"},{"author_name":"Weihua Yue","author_inst":"Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, PR China."},{"author_name":"Yuyanan Zhang","author_inst":"Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, PR China."},{"author_name":"Xin Yu","author_inst":"Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, PR China."},{"author_name":"Long-Biao Cui","author_inst":"Schizophrenia Imaging Lab, Xijing 986 Hospital, Fourth Military Medical University, Xi'an, PR China"},{"author_name":"Xiao Chang","author_inst":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China."},{"author_name":"Huan Huang","author_inst":"huan_huang17@163.com"},{"author_name":"Cheng Luo","author_inst":"The Clinical Hospital of Chengdu Brain Science Institute, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chen"},{"author_name":"Dezhong Yao","author_inst":"The Clinical Hospital of Chengdu Brain Science Institute, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chen"},{"author_name":"Ryota Hashimoto","author_inst":"Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan."},{"author_name":"Junya Matsumoto","author_inst":"Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Japan."},{"author_name":"Kiyotaka Nemoto","author_inst":"Department of Medical Informatics and Management and Psychiatry, Institute of Medicine, University of Tsukuba, Tsukuba, Japan."},{"author_name":"Tilo Kircher","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Florian Thomas-Odenthal","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany"},{"author_name":"Paula Usemann","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Lea Teutenberg","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Benjamin Straube","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Igor Nenadi\u0107","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Frederike Stein","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany"},{"author_name":"Nina Alexander","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Andreas Jansen","author_inst":"Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany."},{"author_name":"Hamidreza Jamalabadi","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Nooshin Javaheripour","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Jannik Lepper","author_inst":"Department of Psychiatry and Psychotherapy, Marburg University, Marburg, Germany."},{"author_name":"Udo Dannlowski","author_inst":"Department of Psychiatry, Medical School and University Medical Center OWL, Protestant Hospital of the Bethel Foundation, Bielefeld University."},{"author_name":"Dominik Grotegerd","author_inst":"Institute for Translational Psychiatry, University of Munster, Munster, Germany."},{"author_name":"Susanne Meinert","author_inst":"Institute for Translational Psychiatry, University of Munster, Munster, Germany."},{"author_name":"Kira Flinkenflugel","author_inst":"Institute for Translational Psychiatry, University of Munster, Munster, Germany"},{"author_name":"Rebekka Lencer","author_inst":"Institute for Translational Psychiatry, University of Munster, Munster, Germany"},{"author_name":"Michael Ziller","author_inst":"Department of Psychiatry, University of Munster, 48149 Munster, Germany."},{"author_name":"Ali Saffet Gonul","author_inst":"Ege University school of medicine SoCAT Lab, Izmir, Turkey."},{"author_name":"Asli Ceren Hinc","author_inst":"Ege University school of medicine SoCAT Lab, Izmir, Turkey."},{"author_name":"Kang Sim","author_inst":"West Region, Institute of Mental Health, Singapore, Singapore."},{"author_name":"Qian Hui Chew","author_inst":"West Region, Institute of Mental Health, Singapore, Singapore."},{"author_name":"Yann Quid\u00e9","author_inst":"NeuroRecovery Research Hub, School of Psychology, The Unversity of New South Wales (UNSW) Sydney, Sydney, NSW, Australia; Centre for Pain IMPACT, Neuroscience R"},{"author_name":"Melissa J. Green","author_inst":"School of Clinical Medicine, Discipline of Psychiatry and Mental Health, The University of New South Wales (UNSW) Sydney, Sydney, NSW, Australia."},{"author_name":"Young-Chul chung","author_inst":"Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Republic of Korea."},{"author_name":"Woo-Sung Kim","author_inst":"Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Republic of Korea."},{"author_name":"Soyolsaikhan Odkhuu","author_inst":"Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Republic of Korea."},{"author_name":"Felice Iasevoli","author_inst":"Section of Psychiatry - Department of Neuroscience and Reproductive Science and Dentistry - University \"Federico II\", Naples, Italy."},{"author_name":"Giuseppe Pontillo","author_inst":"Department of Advanced Biomedical Sciences - University \"Federico II\", Naples, Italy."},{"author_name":"Andrea de Bartolomeis","author_inst":"Section of Psychiatry - Department of Neuroscience and Reproductive Science and Dentistry - University \"Federico II\", Naples, Italy."},{"author_name":"Sirio Cocozza","author_inst":"Department of Advanced Biomedical Sciences - University \"Federico II\", Naples, Italy"},{"author_name":"Annarita Barone","author_inst":"Section of Psychiatry - Department of Neuroscience and Reproductive Science and Dentistry - University \"Federico II\", Naples, Italy."},{"author_name":"Arturo Brunetti","author_inst":"Department of Advanced Biomedical Sciences - University \"Federico II\", Naples, Italy"},{"author_name":"Mariateresa Ciccarelli","author_inst":"Section of Psychiatry - Department of Neuroscience and Reproductive Science and Dentistry - University \"Federico II\", Naples, Italy."},{"author_name":"Mario Tranfa","author_inst":"Department of Advanced Biomedical Sciences - University \"Federico II\", Naples, Italy"},{"author_name":"Tamsyn E.Van Rheenen","author_inst":"Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, MEL, Australia."},{"author_name":"Susan L Rossell","author_inst":"Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia."},{"author_name":"Matthew Hughes","author_inst":"Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia."},{"author_name":"Will Woods","author_inst":"Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia."},{"author_name":"Sean Carruthers","author_inst":"Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia."},{"author_name":"Philip J. Sumner","author_inst":"Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia."},{"author_name":"Elysha Ringin","author_inst":"Department of Psychiatry, University of Melbourne, Parkville, Australia."},{"author_name":"Georgia Caruana","author_inst":"Department of Psychiatry, University of Melbourne, Parkville, Australia."},{"author_name":"Jessica A. Turner","author_inst":"Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States."},{"author_name":"Theo G.M. van Erp","author_inst":"Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine Hall, room 109, Irvine, CA,"},{"author_name":"Lena Palaniyappan","author_inst":"Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada."},{"author_name":"Paul M. Thompson","author_inst":"Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA"},{"author_name":"Jianfeng Feng","author_inst":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China."},{"author_name":"Yuchao Jiang","author_inst":"School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, PR China"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"An Open-Label Multidose Psilocybin Intervention for Obsessive-Compulsive Disorder.","rel_doi":"10.64898\/2026.10.01.26364511","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.01.26364511","rel_abs":"Importance: Obsessive-Compulsive Disorder (OCD) has a 2% global prevalence, but only about 50% of patients respond to conventional treatment, underscoring the need for additional effective interventions. Objective: To assess the feasibility, safety, and preliminary evidence for efficacy of repeated psilocybin administration in OCD patients who had previously attempted psychotherapy or pharmacotherapy. Design: Waitlist-controlled open label randomized clinical trial. Setting: Data were collected at the Johns Hopkins University School of Medicine. Participants: Data were analyzed from 30 participants (total randomized N=37, by age, sex and OCD severity) with a failed previous attempt at either pharmacotherapy or evidence-based psychotherapies such as exposure response prevention (ERP). Intervention: Participants received two psilocybin doses over two weeks (20 mg followed by 30 mg, if well-tolerated) under supportive conditions. The immediate-treatment arm received the drug within a month following enrollment, and the waitlist-control arm received identical support and dosing after an 8-week waiting period. Main Outcomes: Clinician-administered Y-BOCS scores was collected one week post each drug administration and one month post session 2. Self-assessed reports were collected for acute subjective effects (Mystical Experience Questionnaire (MEQ), Challenging Experience Questionnaire (CEQ), and 11-Dimensional Altered States of Consciousness (11D-ASC)), State-Trait Anxiety Inventory (STAI), Beck Depression Inventory-II (BDI-II), and Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q). Results: A total of 37 participants were enrolled in the study (age[SD] years:38.4[11.6] years; 21 [56.75%] female), with 30 [81.08%] completing the 1-month follow-up. We show that two successive doses of psilocybin over two weeks were well-tolerated, leading to improvements in OCD symptoms. Compared with the waitlist group (N=14), the immediate-treatment group (N=16) showed a greater reduction in the Y-BOCS scores (F(2,56)=16.17, p<0.001). After crossover, this improvement persisted one month after the second psilocybin dose for both groups (F(3,84)=29.91, p<0.001). Reductions in Y-BOCS score post sessions were correlated with several acute subjective effects measures, including total scores on MEQ, and individual factors on CEQ and 11D-ASC. Conclusions and Relevance: Repeated psilocybin administration is tolerable and potentially efficacious in reducing OCD symptoms. These results support further investigation of multidose psilocybin protocols as a viable therapeutic approach. Trial Registration: ClinicalTrials.gov Identifier NCT05546658","rel_num_authors":12,"rel_authors":[{"author_name":"Praachi Tiwari","author_inst":"Johns Hopkins Medicine"},{"author_name":"Sandeep M Nayak","author_inst":"Johns Hopkins Medicine"},{"author_name":"Nathan D Sepeda","author_inst":"Johns Hopkins Medicine"},{"author_name":"Rebecca Ehrenkranz","author_inst":"Johns Hopkins Medicine"},{"author_name":"Michael A Levine","author_inst":"Johns Hopkins Medicine"},{"author_name":"Julia S Rohde","author_inst":"Johns Hopkins Medicine"},{"author_name":"Eliza Miller","author_inst":"Johns Hopkins Medicine"},{"author_name":"Carina M Beritela","author_inst":"Johns Hopkins Hospital"},{"author_name":"Jeremy V Scott","author_inst":"Johns Hopkins Medicine"},{"author_name":"Gerald Nestadt","author_inst":"Johns Hopkins Medicine"},{"author_name":"Frederick S Barrett","author_inst":"Johns Hopkins Medicine"},{"author_name":"David B Yaden","author_inst":"Johns Hopkins Medicine"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Chest Pain Hospitalizations: How Varying Emergency Clinician Tendencies Impact Care, Outcomes, and Costs","rel_doi":"10.64898\/2026.10.02.26364626","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364626","rel_abs":"Background: The practice of hospitalizing emergency department (ED) patients with chest pain after ruling out acute myocardial infarction (AMI) varies widely. The long-term outcome and cost implications of this variation are uncertain. Methods: Analyzing 2007-2021 claims from a national commercial insurer, we identified 223,569 adults (18 years or older) ED visits with a principal diagnosis of chest pain without major secondary cardiopulmonary diagnoses, seen by 19,001 clinicians in 2,273 EDs. Within each ED, clinicians with the highest and lowest terciles of risk-adjusted hospitalization rates were classified as high- versus low-admitting. Primary outcomes were 30- and 180-day subsequent AMI hospitalizations. Secondary outcomes included 7-day cardiac testing, 30-day coronary intervention, and 30-day total and out-of-pocket costs. We estimated adjusted rate ratios (aRRs) and relative cost differences using generalized estimating equations, adjusting for patient and visit characteristics. Results: Patients had a mean age of 48.6 years, and 53.9% were female; measured characteristics were similar between groups. Compared with low-admitting clinicians, visits to high-admitting clinicians had higher 7-day cardiac testing (13.1% vs 10.8%; aRR 1.22, 95% CI 1.17-1.27) and 30-day coronary interventions (4.3% vs 3.8%; aRR 1.16, 95% CI 1.09-1.23). AMI hospitalization did not differ at 30 days (0.60% vs 0.60%; aRR 1.00, 95% CI 0.84-1.15) or 180 days (0.85% vs 0.87%; aRR 0.97, 95% CI 0.85-1.10). Thirty-day total costs were higher after visits to high-admitting clinicians (relative change 11.3%, 95% CI 8.8-13.8), and out-of-pocket costs $1,000 or more were more common (32.0% vs 29.6%; relative change 8.2%, 95% CI 6.1-10.3). Conclusions: Higher clinician hospitalizing tendency for ED chest pain is associated with greater downstream testing, more coronary interventions, and higher costs without lower short- or intermediate-term AMI risk. Reducing marginal admissions among high-admitting clinicians may decrease spending and practice variation with minimal impact on AMI outcomes.","rel_num_authors":4,"rel_authors":[{"author_name":"Shih-Chuan Chou","author_inst":"UCSF"},{"author_name":"Renee Y Hsia","author_inst":"UCSF"},{"author_name":"Fang Zhang","author_inst":"Harvard Pilgrim Health Care Institute"},{"author_name":"J. Frank Wharam","author_inst":"Duke University"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Cell type specific enrichment of substance use and substance use disorder heritability","rel_doi":"10.64898\/2026.10.02.26364595","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364595","rel_abs":"Genome-wide association studies (GWAS) have identified numerous loci associated with substance use disorders (SUDs). To connect common genetic variation to cell type- and region-specific gene expression and chromatin accessibility, we examined the enrichment of genetic liability for several SUDs (alcohol, cannabis, tobacco, and opioid use disorders) and substance consumption phenotypes (drinks per week, cannabis ever-use, and cigarettes per day) in available single-nucleus RNAseq data spanning 10 brain regions and snATACseq data spanning 42 brain regions. Significant cell-type enrichment after multiple testing corrections was observed only for drinks per week and tobacco use disorder in the snRNAseq data and for cannabis use disorder and problematic alcohol use in snATACseq data. Across both transcriptomic and chromatin accessibility annotations, enrichment patterns were concentrated in excitatory neuronal populations, particularly upper layer intratelencephalic neurons, amygdala excitatory neurons, and regionally resolved striatal medium spiny neuron subtypes. Drinks per week, problematic alcohol use, and cannabis use disorder showed enrichment values that were significantly correlated within cell-type across snRNAseq and snATACseq, suggesting convergent biological signals across independent single-nucleus modalities. These findings implicate chromatin-mediated expression differences in specific excitatory neuronal populations as potential mediators of SUD genetic liability and highlight the value of integrating transcriptomic and chromatin accessibility data for characterising the neurobiology of addiction.","rel_num_authors":7,"rel_authors":[{"author_name":"Nithya Sarabudla","author_inst":"Washington University School of Medicine"},{"author_name":"Pamela N Romero Villela","author_inst":"Washington University School of Medicine"},{"author_name":"Ronald P. Hart","author_inst":"Rutgers University"},{"author_name":"Yang E. Li","author_inst":"Washington University School of Medicine"},{"author_name":"Zhiping P. Pang","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Arpana Agrawal","author_inst":"Washington University School of Medicine"},{"author_name":"Emma C Johnson","author_inst":"Washington University School of Medicine"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Cell type specific enrichment of substance use and substance use disorder heritability","rel_doi":"10.64898\/2026.10.02.26364595","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364595","rel_abs":"Genome-wide association studies (GWAS) have identified numerous loci associated with substance use disorders (SUDs). To connect common genetic variation to cell type- and region-specific gene expression and chromatin accessibility, we examined the enrichment of genetic liability for several SUDs (alcohol, cannabis, tobacco, and opioid use disorders) and substance consumption phenotypes (drinks per week, cannabis ever-use, and cigarettes per day) in available single-nucleus RNAseq data spanning 10 brain regions and snATACseq data spanning 42 brain regions. Significant cell-type enrichment after multiple testing corrections was observed only for drinks per week and tobacco use disorder in the snRNAseq data and for cannabis use disorder and problematic alcohol use in snATACseq data. Across both transcriptomic and chromatin accessibility annotations, enrichment patterns were concentrated in excitatory neuronal populations, particularly upper layer intratelencephalic neurons, amygdala excitatory neurons, and regionally resolved striatal medium spiny neuron subtypes. Drinks per week, problematic alcohol use, and cannabis use disorder showed enrichment values that were significantly correlated within cell-type across snRNAseq and snATACseq, suggesting convergent biological signals across independent single-nucleus modalities. These findings implicate chromatin-mediated expression differences in specific excitatory neuronal populations as potential mediators of SUD genetic liability and highlight the value of integrating transcriptomic and chromatin accessibility data for characterising the neurobiology of addiction.","rel_num_authors":7,"rel_authors":[{"author_name":"Nithya Sarabudla","author_inst":"Washington University School of Medicine"},{"author_name":"Pamela N Romero Villela","author_inst":"Washington University School of Medicine"},{"author_name":"Ronald P. Hart","author_inst":"Rutgers University"},{"author_name":"Yang E. Li","author_inst":"Washington University School of Medicine"},{"author_name":"Zhiping P. Pang","author_inst":"Rutgers Robert Wood Johnson Medical School"},{"author_name":"Arpana Agrawal","author_inst":"Washington University School of Medicine"},{"author_name":"Emma C Johnson","author_inst":"Washington University School of Medicine"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Predicting the efficacy of Ervebo against Bundibugyo virus disease","rel_doi":"10.64898\/2026.10.02.26364627","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364627","rel_abs":"There is currently no clinical data for the effectiveness of the only licensed Ebola virus disease vaccine (Ervebo) against Bundibugyo virus disease. A number of studies have shown immune cross-reactivity with Bundibugyo virus after Ervebo vaccination. However, antibody recognition of Bundibugyo is around 2.8-fold lower than recognition of Ebola virus. Here, we aimed to infer how a 2.8-fold drop in immune recognition may affect Ervebo protection against Bundibugyo virus disease based on analysis of data on Ervebo immunogenicity and protection from Ebola virus disease. This work has three main components. Firstly, we analysed the timing of vaccine protection in the Ervebo pivotal ring vaccination clinical trial. Secondly, we performed a systematic review and meta-analysis of antibody responses to Ebola virus after Ervebo vaccination over time. Thirdly, we combined these data with previously reported data on the cross-reactivity to Bundibugyo virus to infer protection of Ervebo against Bundibugyo virus disease. We find that the clinical trial data for Ervebo supports vaccine protection beginning earlier than 10 days after vaccination. Secondly, binding antibody levels against Ebola virus on day 28 post vaccination (peak responses) were on average 12.9-fold (95% confidence interval, CI: 6.4 - 26.0) higher than on day 7, 6.3-fold (95% CI: 3.7 -10.8) higher than on day 10, and 2.5-fold (95% CI: 1.4 - 4.4) higher than on day 14 (neutralising antibodies showed similar results). Finally, we consider the scenarios where antibody levels to Ebola virus at day 7 or 10 are putative protective thresholds against Ebola virus disease, and we assume these thresholds also apply for Bundibugyo virus disease. Then, with a 2.8-fold reduction of responses to Bundibugyo compared to Ebola virus, we predict antibody responses to Bundibugyo virus after Ervebo vaccination are likely above these putative protective thresholds.","rel_num_authors":13,"rel_authors":[{"author_name":"Karen M Elias","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Ece Egilmezer","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Shanchita R Khan","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Ainslie Mitchell","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Arnold Reynaldi","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Matthew T Berry","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Timothy E Schlub","author_inst":"Faculty of Medicine and Health, Sydney School of Public Health, University of Sydney"},{"author_name":"Bronwyn A Bailey","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Deborah Cromer","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Tari Turner","author_inst":"School of Public Health and Preventive Medicine, Monash University"},{"author_name":"Eva Stadler","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Miles Philip Davenport","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"David S Khoury","author_inst":"Kirby Institute, UNSW Sydney"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Predicting the efficacy of Ervebo against Bundibugyo virus disease","rel_doi":"10.64898\/2026.10.02.26364627","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364627","rel_abs":"There is currently no clinical data for the effectiveness of the only licensed Ebola virus disease vaccine (Ervebo) against Bundibugyo virus disease. A number of studies have shown immune cross-reactivity with Bundibugyo virus after Ervebo vaccination. However, antibody recognition of Bundibugyo is around 2.8-fold lower than recognition of Ebola virus. Here, we aimed to infer how a 2.8-fold drop in immune recognition may affect Ervebo protection against Bundibugyo virus disease based on analysis of data on Ervebo immunogenicity and protection from Ebola virus disease. This work has three main components. Firstly, we analysed the timing of vaccine protection in the Ervebo pivotal ring vaccination clinical trial. Secondly, we performed a systematic review and meta-analysis of antibody responses to Ebola virus after Ervebo vaccination over time. Thirdly, we combined these data with previously reported data on the cross-reactivity to Bundibugyo virus to infer protection of Ervebo against Bundibugyo virus disease. We find that the clinical trial data for Ervebo supports vaccine protection beginning earlier than 10 days after vaccination. Secondly, binding antibody levels against Ebola virus on day 28 post vaccination (peak responses) were on average 12.9-fold (95% confidence interval, CI: 6.4 - 26.0) higher than on day 7, 6.3-fold (95% CI: 3.7 -10.8) higher than on day 10, and 2.5-fold (95% CI: 1.4 - 4.4) higher than on day 14 (neutralising antibodies showed similar results). Finally, we consider the scenarios where antibody levels to Ebola virus at day 7 or 10 are putative protective thresholds against Ebola virus disease, and we assume these thresholds also apply for Bundibugyo virus disease. Then, with a 2.8-fold reduction of responses to Bundibugyo compared to Ebola virus, we predict antibody responses to Bundibugyo virus after Ervebo vaccination are likely above these putative protective thresholds.","rel_num_authors":13,"rel_authors":[{"author_name":"Karen M Elias","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Ece Egilmezer","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Shanchita R Khan","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Ainslie Mitchell","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Arnold Reynaldi","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Matthew T Berry","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Timothy E Schlub","author_inst":"Faculty of Medicine and Health, Sydney School of Public Health, University of Sydney"},{"author_name":"Bronwyn A Bailey","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Deborah Cromer","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Tari Turner","author_inst":"School of Public Health and Preventive Medicine, Monash University"},{"author_name":"Eva Stadler","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"Miles Philip Davenport","author_inst":"Kirby Institute, UNSW Sydney"},{"author_name":"David S Khoury","author_inst":"Kirby Institute, UNSW Sydney"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Predictive markers of response and toxicity to tarlatamab in patients with extensive stage small cell lung cancer: a multi-institutional real-world analysis","rel_doi":"10.64898\/2026.10.02.26364624","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.10.02.26364624","rel_abs":"Purpose Tarlatamab, a bispecific T-cell engager, has generated favorable response and survival outcomes in relapsed small cell lung cancer (SCLC). Factors influencing tarlatamab-associated treatment outcomes and toxicity have yet to be established. We performed a multivariate analysis to identify biomarkers associated with cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS) and integrated these variables into a novel risk stratification tool to identify patients at high risk of clinically significant toxicity. Patients and Methods Logistic and ordinal regression analyses evaluated the predictive value of variables contributing to the presence and severity, respectively, of CRS and ICANS in 115 patients with ES-SCLC receiving tarlatamab. Selected variables were then tuned using 5-fold cross-validation and incorporated into novel elastic net-based prediction models. Results Rates of observed CRS, ICANS, and dysgeusia were 46%, 28%, and 47%, respectively. ORR (overall response rate) and DCR (disease control rate) were 44% and 58.2%, while 6-month PFS (progression free survival) and OS (overall survival) rates were 30.4% and 54.9%, respectively. Excluding patients on tarlatamab <30 days, presence of dysgeusia was associated with a lower rate of disease progression (HR 0.44, p=0.00691) and death (HR 0.34, p=0.0145). The presence of, increased size and number of extracranial metastases as well as elevated baseline LDH were significantly associated with increased likelihood of CRS. Increased ECOG performance status, increased volume of brain metastases, development of CRS, and elevated baseline LDH were all associated with increased risk of developing ICANS. Our cross-validated risk model successfully predicted CRS grade [&ge;]2 and ICANS events with 90.9% and 75% sensitivity, respectively. Conclusions This exploratory analysis identified several predictive biomarkers of toxicity that successfully stratified low and high-risk populations as part of an internally validated novel risk scoring tool.","rel_num_authors":14,"rel_authors":[{"author_name":"Graeme Fenton","author_inst":"University of Maryland Medical Center"},{"author_name":"Wanru Guo","author_inst":"University of Maryland Greenebaum Comprehensive Cancer Center"},{"author_name":"Daniel L. Hess","author_inst":"Duke Department of Medicine, Duke University School of Medicine"},{"author_name":"Annie L. Zhang","author_inst":"Case Western Reserve University"},{"author_name":"Curtis Tatsuoka","author_inst":"University of Maryland Baltimore"},{"author_name":"Alexis L. Green","author_inst":"Duke Department of Medicine, Duke University School of Medicine"},{"author_name":"Michelle Sittig","author_inst":"University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center"},{"author_name":"Ranee Mehra","author_inst":"University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center"},{"author_name":"Alexandra Simms","author_inst":"University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center"},{"author_name":"Afshin Dowlati","author_inst":"University Hospitals Seidman Cancer Center and Case Western Reserve University"},{"author_name":"Taofeek K. Owonikoko","author_inst":"University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center"},{"author_name":"Melinda Hsu","author_inst":"University Hospitals Seidman Cancer Center and Case Western Reserve University"},{"author_name":"Laura Alder","author_inst":"Duke Cancer Institute"},{"author_name":"Samuel Rosner","author_inst":"University of Maryland Greenebaum Comprehensive Cancer Center"}],"rel_date":"2026-10-05","rel_site":"medrxiv"},{"rel_title":"Resection of highly functionally connected glioma regions predicts long-term cognitive preservation","rel_doi":"10.64898\/2026.09.28.26363885","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.09.28.26363885","rel_abs":"Background. Glioma surgery requires balancing maximal tumor resection against preservation of neurological and cognitive function. Intraoperative direct electrical stimulation guides this balance but is invasive and not always feasible. Preoperative magnetoencephalography (MEG) can identify tumor regions with high functional connectivity (HFC) to the rest of the brain. These HFC areas contain more malignant glioma cells and relate to poorer short-term outcome when resected. We aimed to determine whether HFC voxel resection relates to postoperative neurological and cognitive outcomes. Methods. In this preregistered analysis, 54 adults with diffuse glioma underwent resting-state MEG before resection. Imaginary coherence identified voxels with significantly higher connectivity against their contralateral controls, and these HFC voxels within the resection cavity were counted. Neurological status was assessed at short-term (~1 week) and long-term (~1 year) follow-up, and neuropsychological assessment took place at baseline and long-term follow-up. Logistic regressions related resected HFC voxels to decline at each timepoint, adjusting for Karnofsky performance status, sex and resectability index. Results. Resected HFC voxels were not associated with neurological decline at short-term (48% declined; odds ratio [OR] 0.98, P = .50) or long-term follow-up (27% declined; OR 0.99). For cognition, more resected HFC voxels were associated with less long-term decline (48% declined; OR 0.85, P = .02); a binarized analysis was consistent (OR 0.076, P = .01), indicating that tumor volume did not drive this result. Conclusions. Resecting more HFC voxels associates with preserved long-term cognition, without apparent neurological cost. Non-invasive MEG connectivity mapping may help optimize the onco-functional balance in glioma surgery.","rel_num_authors":9,"rel_authors":[{"author_name":"Marike Roos van Lingen","author_inst":"Amsterdam UMC, Vrije Universiteit Amsterdam"},{"author_name":"Amit Jaiswal","author_inst":"MEGIN"},{"author_name":"Srikantan Nagarajan","author_inst":"University of California, San Francisco"},{"author_name":"Velmurugan Jayabal","author_inst":"University of California, San Francisco"},{"author_name":"Martin Klein","author_inst":"Amsterdam UMC, Vrije Universiteit Amsterdam"},{"author_name":"Niels Verburg","author_inst":"AmsterdamUMC, Vrije Universiteit Amsterdam"},{"author_name":"Philip de Witt Hamer","author_inst":"AmsterdamUMC, Vrije Universiteit Amsterdam"},{"author_name":"Arjan Hillebrand","author_inst":"AmsterdamUMC, Vrije Universiteit Amsterdam"},{"author_name":"Linda Douw","author_inst":"AmsterdamUMC, Vrije Universiteit Amsterdam"}],"rel_date":"2026-10-05","rel_site":"medrxiv"}]}