{"gname":"Vanderbilt University","grp_id":"30","rels":[{"rel_title":"PROTOTYPE-BASED CONTINUAL LEARNING FOR SINGLE-CELL ANNOTATION","rel_doi":"10.64898\/2026.03.05.709973","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709973","rel_abs":"Large-scale single-cell atlases have become indispensable resources for cell-type annotation and biological discovery. However, most existing annotation frameworks rely on static reference data and require re-accessing or retraining on previous datasets as new data emerge, which poses challenges for scalability, data sharing, and knowledge continuity. These methods are further constrained by catastrophic forgetting and batch-specific biases, limiting their ability to integrate knowledge across platforms, tissues, and modalities. Here we introduce scEvolver, a continual learning framework for single-cell annotation. scEvolver refines cell-type representations as class prototypes through memory-guided continual learning, incrementally accumulating knowledge without revisiting historical data. These online prototypes preserve intrinsic and consistent cell-type semantics across datasets while capturing informative within-class heterogeneity. Systematic evaluations demonstrate that scEvolver outperforms other methods in annotation accuracy, while requiring substantially fewer labeled reference samples for external query mapping. The framework maintains strong stability and generalization across diverse real-world scenarios spanning multiple platforms, tissues, and modalities. The application of scEvolver to inflammatory gut disease data reveals metaplastic transitions of epithelial cells, highlighting its potential to uncover context-specific cellular dynamics in complex disease settings.","rel_num_authors":10,"rel_authors":[{"author_name":"Shuang Ge","author_inst":"Tsinghua University"},{"author_name":"Qiming He","author_inst":"Fuzhou University"},{"author_name":"Yiming Ren","author_inst":"Peng Cheng Laboratory"},{"author_name":"Yaxin Xu","author_inst":"Southern University of Science and Technology"},{"author_name":"Mingqing Wang","author_inst":"Tsinghua University"},{"author_name":"Zhiwei Nie","author_inst":"Peking University"},{"author_name":"Huan Xu","author_inst":"Anhui University of Science and Technology"},{"author_name":"Qiang Cheng","author_inst":"University of Kentucky"},{"author_name":"Shuqing Sun","author_inst":"Tsinghua University"},{"author_name":"Zhixiang Ren","author_inst":"Peng Cheng Laboratory"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"MS-BCR-DB: an integrated BCR repertoire database to mine humoral multiple sclerosis signatures","rel_doi":"10.64898\/2026.03.05.709606","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709606","rel_abs":"Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) in which B cells play a critical role. While B-cell receptor (BCR) sequencing studies in MS are increasing, progress in understanding MS-associated BCR repertoire features and convergent patterns across patients has been limited by small cohorts, heterogeneous experimental methodologies, and fragmented data storage. To overcome these challenges, we developed the MS-BCR-Database, the first publicly accessible and uniformly processed collection of human MS BCR sequencing datasets. We harmonized raw BCR-sequencing data into an AIRR-compliant database incorporating clinical and technical metadata, enabling coherent cross-study analyses. Using this resource, we identified putative disease-associated BCR-sequence features, including CNS-biased V-gene usage, marked oligoclonal expansion in cerebrospinal fluid, and convergent clonotype clusters shared exclusively among MS patients. Integration with antigen-annotated BCR databases revealed matches to antibodies recognizing both viral antigens, including Epstein-Barr virus, and CNS self-proteins. The MS-BCR-Database provides a scalable foundation for mechanistic discovery and biomarker development in MS, while establishing a broadly applicable resource for integrative analyses of BCR repertoires.","rel_num_authors":11,"rel_authors":[{"author_name":"Chiara Ballerini","author_inst":"University of Florence"},{"author_name":"Niccolo Cardente","author_inst":"University of Oslo"},{"author_name":"Maria Francesca Abbate","author_inst":"University of Oslo"},{"author_name":"Khang Le Quy","author_inst":"University of Oslo"},{"author_name":"Natalia Rincon","author_inst":"Johns Hopkins University"},{"author_name":"Lina Wolfram","author_inst":"University of OSlo"},{"author_name":"Andreas Lossius","author_inst":"University of Oslo"},{"author_name":"Emilio Portaccio","author_inst":"University of Florence"},{"author_name":"Maria Pia Amato","author_inst":"University of Florence"},{"author_name":"Clara Ballerini","author_inst":"University of Florence"},{"author_name":"Victor Greiff","author_inst":"University of Oslo"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"Autofluorescence lifetime imaging resolves cell heterogeneity within peripheral blood mononuclear cells","rel_doi":"10.64898\/2026.03.06.710224","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.710224","rel_abs":"Significance: Standard methods to characterize peripheral blood mononuclear cells (PBMCs) are often destructive, lack metabolic information, or do not provide single-cell resolution. Label-free tools that non-destructively measure single-cell metabolism within PBMCs can provide new layers of information to characterize disease state and cell therapy potential. Aim: Determine whether non-destructive fluorescence lifetime imaging microscopy (FLIM) of endogenous metabolic co-factors NAD(P)H and FAD, or optical metabolic imaging (OMI), can identify immune cell subsets and activation state within heterogeneous PBMC cultures. Approach: OMI measured single-cell metabolism of PBMCs from 3 different human donors in the quiescent or activated (phorbol 12-myristate 13-acetate and ionomycin) state. Fluorescent antibodies were used as ground truth labels for single-cell classifiers of immune cell subtypes. Results: OMI identified quiescent vs. activated PBMCs with 93% accuracy at only 2 hours post-stimulation, identified monocytes within quiescent and activated PBMCs with 96% and 88% accuracy, respectively, and identified NK cells within quiescent and activated PBMCs with 74% accuracy. Conclusion: OMI identifies activation state and immune cell subpopulations within PBMCs, enabling single-cell and label-free measurements of metabolic heterogeneity within complex PBMC samples. Therefore, OMI could enhance PBMC immunophenotyping for diagnostic and therapeutic applications.","rel_num_authors":5,"rel_authors":[{"author_name":"Jeremiah M Riendeau","author_inst":"University of Wisconsin Madison"},{"author_name":"Lucia Hockerman","author_inst":"Morgridge Institute for Research"},{"author_name":"Elizabeth Maly","author_inst":"Morgridge Institute for Research"},{"author_name":"Kayvan M Samimi","author_inst":"Morgridge Institute for Research"},{"author_name":"Melissa C Skala","author_inst":"Morgridge Institute for Research"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"A population-scale red blood cell proteome reveals genetically encoded aging clocks predictive of hemolysis and blood donor activity","rel_doi":"10.64898\/2026.03.07.710284","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.07.710284","rel_abs":"As the most abundant human cell and the foundation of transfusion medicine, red blood cells (RBCs) offer a unique readout of systemic health, yet they have never been characterized at population scale. We generated a proteome atlas of 13,091 blood donors with multi-omics longitudinal phenotyping, characterizing the influence of demographics and genetic variation on the reproducibility of RBC proteomes across donations. Elastic-net aging clocks captured biological aging with high accuracy and uncovered genetic regulators of {Delta}Age at FN1, C4\/IKZF1, CRAT, PFAS, TRIM58. Across independent cohorts, {Delta}Age was accelerated in G6PD deficiency, sickle cell trait\/disease, and iron deficiency, reversed by iron repletion, and slowed in high-frequency donors, linking molecular aging to brain iron\/myelin and cognitive performance. Molecular aging signatures predicted storage, osmotic, and oxidative hemolysis, hemoglobin increments after transfusion, and long-term donor activity over 12-years. These results establish RBC proteomics as a scalable biomarker of aging, donor healthspan, and transfusion outcomes.","rel_num_authors":23,"rel_authors":[{"author_name":"Monika Dzieciatkowska","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Aaron V Issaian","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Gregory R Keele","author_inst":"RTI International"},{"author_name":"Anthony Saviola","author_inst":"University of Colorado - Anschutz Medical Campus"},{"author_name":"Daniel Stephenson","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Shaun Bevers","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Julie A Reisz","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Zachary B Haiman","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Travis Nemkov","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Fang Fang","author_inst":"RTI International"},{"author_name":"Amy Moore","author_inst":"RTI International"},{"author_name":"Xutao Deng","author_inst":"Vitalant Research Institute"},{"author_name":"Mars Stone","author_inst":"Vitalant Research Institiute"},{"author_name":"Steve Kleinman","author_inst":"University of British Columbia"},{"author_name":"Philip J Norris","author_inst":"Vitalant Research Institute"},{"author_name":"Xunde Wang","author_inst":"NHLBI"},{"author_name":"Swee-Lay Thein","author_inst":"NHLBI"},{"author_name":"Eldad A Hod","author_inst":"Columbia University"},{"author_name":"Michael P Busch","author_inst":"Vitalant Research Institute"},{"author_name":"Nareg H Roubinian","author_inst":"UCSF"},{"author_name":"Grier P Page","author_inst":"RTI International"},{"author_name":"Kirk Hansen","author_inst":"School of Medicine, University of Colorado at Anschutz Medical Center"},{"author_name":"Angelo D'Alessandro","author_inst":"University of Colorado Anschutz Medical Campus"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"A population-scale red blood cell proteome reveals genetically encoded aging clocks predictive of hemolysis and blood donor activity","rel_doi":"10.64898\/2026.03.07.710284","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.07.710284","rel_abs":"As the most abundant human cell and the foundation of transfusion medicine, red blood cells (RBCs) offer a unique readout of systemic health, yet they have never been characterized at population scale. We generated a proteome atlas of 13,091 blood donors with multi-omics longitudinal phenotyping, characterizing the influence of demographics and genetic variation on the reproducibility of RBC proteomes across donations. Elastic-net aging clocks captured biological aging with high accuracy and uncovered genetic regulators of {Delta}Age at FN1, C4\/IKZF1, CRAT, PFAS, TRIM58. Across independent cohorts, {Delta}Age was accelerated in G6PD deficiency, sickle cell trait\/disease, and iron deficiency, reversed by iron repletion, and slowed in high-frequency donors, linking molecular aging to brain iron\/myelin and cognitive performance. Molecular aging signatures predicted storage, osmotic, and oxidative hemolysis, hemoglobin increments after transfusion, and long-term donor activity over 12-years. These results establish RBC proteomics as a scalable biomarker of aging, donor healthspan, and transfusion outcomes.","rel_num_authors":23,"rel_authors":[{"author_name":"Monika Dzieciatkowska","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Aaron V Issaian","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Gregory R Keele","author_inst":"RTI International"},{"author_name":"Anthony Saviola","author_inst":"University of Colorado - Anschutz Medical Campus"},{"author_name":"Daniel Stephenson","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Shaun Bevers","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Julie A Reisz","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Zachary B Haiman","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Travis Nemkov","author_inst":"University of Colorado Anschutz Medical Campus"},{"author_name":"Fang Fang","author_inst":"RTI International"},{"author_name":"Amy Moore","author_inst":"RTI International"},{"author_name":"Xutao Deng","author_inst":"Vitalant Research Institute"},{"author_name":"Mars Stone","author_inst":"Vitalant Research Institiute"},{"author_name":"Steve Kleinman","author_inst":"University of British Columbia"},{"author_name":"Philip J Norris","author_inst":"Vitalant Research Institute"},{"author_name":"Xunde Wang","author_inst":"NHLBI"},{"author_name":"Swee-Lay Thein","author_inst":"NHLBI"},{"author_name":"Eldad A Hod","author_inst":"Columbia University"},{"author_name":"Michael P Busch","author_inst":"Vitalant Research Institute"},{"author_name":"Nareg H Roubinian","author_inst":"UCSF"},{"author_name":"Grier P Page","author_inst":"RTI International"},{"author_name":"Kirk Hansen","author_inst":"School of Medicine, University of Colorado at Anschutz Medical Center"},{"author_name":"Angelo D'Alessandro","author_inst":"University of Colorado Anschutz Medical Campus"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"A Ubiquitin network safeguards cell identity by continuously degrading stem-cell related translational machinery","rel_doi":"10.64898\/2026.03.06.709266","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.709266","rel_abs":"How cell identity is maintained is a fundamental question, and loss of cell identity is a hallmark of aging that is associated with multiple age-related diseases. In the adult Drosophila midgut, we identified a post-transcriptional regulatory layer that supervises enterocyte (EC) identity and fails upon aging. Combining single-cell RNA-seq with lineage tracing in aging ECs and classical genetics we found that aging ECs express genes that unlock the differentiated state. Upon aging, the protein Rogue (CG13928), a translational repressor, orchestrates reactivation of a stem-cell-related translational repression machinery involving p-body-associated RNA-binding proteins that cancels the differentiated state. In young ECs, this machinery is continuously suppressed by the deubiquitinase Non-stop (dUSP22) and the ubiquitin E2 dUbcH8\/Kdo and the E3 enzyme CTLH, together suppress the stem-cell related RNA binding proteins safeguarding EC identity. Upon aging, the levels of dUSP22 decline, dUbcH8\/Kdo and the E3 CTLH complex are cleared via Rogue, and the stem cell-related p-bodies are reactivated, self-destroying EC identity.","rel_num_authors":11,"rel_authors":[{"author_name":"Salwa Daniel","author_inst":"Technion Israel Institute of Technology"},{"author_name":"Raya Ghanem","author_inst":"Technion Israel Institute of Technology"},{"author_name":"Muhammad Makhzumy","author_inst":"Technion Israel Institute of Technology"},{"author_name":"Eliya Bitman-Lotan","author_inst":"Technion Israel Institute of Technology"},{"author_name":"Jelly Soffers","author_inst":"University of Missouri-Kansas City"},{"author_name":"Jesslyn c Henriksen","author_inst":"University of Colorado Anschutz Medical Campus School of Medicine"},{"author_name":"Avital Sarusi-Portuguez","author_inst":"Weizmann Institute of Science"},{"author_name":"Olivia S Rissland","author_inst":"University of Colorado Anschutz Medical Campus School of Medicine"},{"author_name":"Ryan D Mohan","author_inst":"Wayne State University"},{"author_name":"Ayala Shiber","author_inst":"Technion Israel Institute of Technology"},{"author_name":"Amir M Orian","author_inst":"Technion Israel Institute of Technology"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"CEACAM5\/6+ Tumor Cells and IL-1\u03b2+ Macrophages Drive Resistance to Chemo-immunotherapy in Gastric Cancer","rel_doi":"10.64898\/2026.03.05.708917","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.708917","rel_abs":"Chemo-immunotherapy is a first-line treatment for advanced gastric cancer, yet response rates remain limited and resistance mechanisms are poorly defined. Here we generate a single-cell atlas of 542,121 cells from 35 patients treated with anti-PD-1 plus chemotherapy, profiling pre- and post-treatment tumors linked to clinical response. Integrating spatial transcriptomics, immunohistochemistry, and bulk RNA sequencing, we identify two temporally distinct resistance programs. Intrinsic resistance in pre-treatment non-responders is marked by enrichment of CEACAM5\/6 tumor cells that form immune-excluded spatial niches characterized by macrophage recruitment and CD8 T-cell exhaustion. Acquired resistance in post-treatment non-responders is driven by expansion of IL-1{beta} macrophages, which induces coordinated NF-{kappa}B activation across tumor and stromal compartments, promoting PD-L1 upregulation, epithelial-mesenchymal transition, and chronic inflammation. These findings delineate an evolutionary trajectory of resistance and nominate CEACAM5\/6 and IL-1{beta} as predictive biomarkers and therapeutic targets to improve anti-PD-1-based combination strategies.","rel_num_authors":20,"rel_authors":[{"author_name":"Jian Chen","author_inst":"Zhejiang University"},{"author_name":"Liudeng Zhang","author_inst":"The University of Texas MD Anderson Cancer Center"},{"author_name":"Yikai Luo","author_inst":"The University of Texas MD Anderson Cancer Center"},{"author_name":"Xiaying Han","author_inst":"Zhejiang University"},{"author_name":"Muxing Kang","author_inst":"Zhejiang University"},{"author_name":"Jing Chen","author_inst":"Zhejiang University"},{"author_name":"Wei Liu","author_inst":"The University of Texas MD Anderson Cancer Center"},{"author_name":"Zhenzhen Xun","author_inst":"The University of Texas MD Anderson Cancer Center"},{"author_name":"Guofeng Chen","author_inst":"Zhejiang University"},{"author_name":"Ke Chen","author_inst":"Zhejiang University"},{"author_name":"Shenbin Xu","author_inst":"Zhejiang University"},{"author_name":"Chaoyang Zhang","author_inst":"Zhejiang University"},{"author_name":"Zhiwei Wu","author_inst":"Zhejiang University"},{"author_name":"Wenxuan Wu","author_inst":"Zhejiang University"},{"author_name":"Zhixing Hao","author_inst":"Zhejiang University"},{"author_name":"Yaxuan Han","author_inst":"Zhejiang University"},{"author_name":"Qiaowei Lin","author_inst":"Zhejiang University"},{"author_name":"Yewei Xu","author_inst":"Zhejiang University"},{"author_name":"Lie Wang","author_inst":"Zhejiang University"},{"author_name":"Han Liang","author_inst":"MD Anderson"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"Tubulin C-terminal tails are pH sensors that regulate microtubule function","rel_doi":"10.64898\/2026.03.06.710195","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.710195","rel_abs":"Changes in intracellular pH are critical for maintaining homeostasis, mediating signaling pathways, and enabling cellular responses to stress, injury, and disease. There is increasing evidence that clusters of acidic residues, primarily glutamates, are both highly prevalent and conserved in disordered regions of proteins and can play an important role in cellular pH response. Tubulin C-terminal tails (CTTs) are glutamate rich regions which protrude from the microtubule surface. These tails are a primary site of for both post-translational modifications and binding of microtubule-associated proteins. Motivated by these observations, we measured the pH response of tubulin CTTs using NMR spectroscopy, circular dichroism, and computational simulations. We find that glutamate residues in CTTs taken from organisms across eukaryotes exhibit a robust upshift in their pKa values, that the sequential context of glutamate residues creates hot spots for protonation, and that hydrogen bonding between side chains stabilizes interactions that alter the conformation of the CTT. To determine whether the CTT pH response plays a potentially important role in microtubule interactions, we measured the pH dependence of the binding of the yeast kinesin-5, Cin8, to microtubules. We find that Cin8 binding is modulated by pH in a CTT-dependent manner. Our results demonstrate that acidic clusters are important mediators of cellular pH response and establish that pH can regulate interactions at the microtubule surface.","rel_num_authors":10,"rel_authors":[{"author_name":"A. M. Whited","author_inst":"University of Colorado Boulder"},{"author_name":"Patrick DeLear","author_inst":"University of Michigan"},{"author_name":"Ezekiel C Thomas","author_inst":"University of Michigan"},{"author_name":"Jeffre Allen","author_inst":"University of Colorado Boulder"},{"author_name":"G\u00e9nesis Ferrer-Imbert","author_inst":"Unversity of Colorado Boulder"},{"author_name":"Nirbhik Acharya","author_inst":"Syracuse University"},{"author_name":"Carlos A Casta\u0148eda","author_inst":"Syracuse University"},{"author_name":"David Sept","author_inst":"University of Michigan"},{"author_name":"Jeffrey K Moore","author_inst":"University of Colorado School of Medicine"},{"author_name":"Loren E Hough","author_inst":"University of Colorado Boulder"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"Mechanistic Basis for the Selective Recognition of the Fc\u03b3 Receptor IIa by Monoclonal Antibody IV.3","rel_doi":"10.64898\/2026.03.05.709909","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709909","rel_abs":"The monoclonal antibody IV.3 selectively binds the platelet Fc{gamma} receptor IIa (Fc{gamma}RIIa), potently blocking immune complex engagement without cross-reacting with the closely-related Fc{gamma}RIIb. This specificity has made IV.3 invaluable for dissecting Fc{gamma}RIIa-mediated activation in diverse conditions, including infection, autoimmunity, thromboinflammation, and platelet-mediated thrombosis. We combined cryogenic electron microscopy, surface plasmon resonance, alchemical free energy calculations, and molecular dynamics simulations to elucidate IV.3's binding sites on Fc{gamma}RIIa and the mechanistic basis of IV.3 specificity. We find that IV.3 engages a broader Fc{gamma}RIIa epitope than previously recognized, extending beyond residues H\/R134 and L135 (R and S in Fc{gamma}RIIb). Simulations of Fc{gamma}IIa-R134 variants bearing either L135 or S135 reveal that IV.3 specificity arises from hydrophobic stabilization mediated by L135 and disruption of an R134-specific interaction network in the presence of S135. These findings provide a mechanistic framework for rational design of Fc{gamma}RIIa-targeted therapeutics.","rel_num_authors":7,"rel_authors":[{"author_name":"Jialing Wang","author_inst":"The Rockefeller University"},{"author_name":"Sabina Novack","author_inst":"Icahn School of Medicine at Mount Sinai"},{"author_name":"Jihong Li","author_inst":"The Rockefeller University"},{"author_name":"Emily G Niejadlik","author_inst":"The Rockefeller University"},{"author_name":"Stylianos Bournazos","author_inst":"The Rockefeller University"},{"author_name":"Barry S Coller","author_inst":"The Rockefeller University"},{"author_name":"Marta Filizola","author_inst":"Icahn School of Medicine at Mount Sinai"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"Perseus: Lineage-Aware Refinement of Kraken2 Taxonomic Classification for Long Read Metagenomes","rel_doi":"10.64898\/2026.03.06.710148","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.710148","rel_abs":"Motivation: Long-read metagenomic sequencing improves assembly contiguity and enables genome-resolved analysis of complex microbial communities, but accurate taxonomic classification of long reads and assembled contigs remains challenging. Highly scalable k-mer-based classifiers such as Kraken2 frequently over-assign fine-rank taxonomic labels when applied to long-read data, producing high false positive classification rates driven by sparse or localized k-mer matches, particularly in microbiomes with extensive taxonomic novelty. Results: We present Perseus, a lineage-aware confidence estimation framework for taxonomic classification that models the spatial distribution and hierarchical consistency of k-mer evidence along sequences. This formulation reframes taxonomic classification as a hierarchical confidence estimation problem rather than a single-rank prediction task. Perseus refines k-mer-level taxonomic signals from Kraken2 using a multi-headed convolutional neural network that estimates calibrated confidence scores for taxonomic correctness at each canonical rank. Using these estimates, Perseus confirms assignments, backs off to higher taxonomic ranks, or abstains when evidence is insufficient, prioritizing correctness and lineage consistency over overly specific assignments. Across simulations of taxonomic novelty and real-world metagenomic datasets, Perseus consistently and substantially reduces the false assignment rate while improving precision and lineage-consistent accuracy. These improvements are most pronounced for long reads and assembled contigs, where spatial context enables reliable discrimination between consistent taxonomic signal and spurious matches.","rel_num_authors":2,"rel_authors":[{"author_name":"Matthew Nguyen","author_inst":"Johns Hopkins University"},{"author_name":"Michael Schatz","author_inst":"Johns Hopkins University"}],"rel_date":"2026-03-08","rel_site":"biorxiv"},{"rel_title":"Novel Genetic Locus Associated with Resistance to M. tuberculosis Infection: A Multi-Ancestry Genome-Wide Association Study","rel_doi":"10.64898\/2026.03.06.26347614","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.06.26347614","rel_abs":"Understanding host susceptibility to Mycobacterium tuberculosis (Mtb) is critical for the development of new vaccines. Certain individuals \"resist\" becoming infected with Mtb despite intensive exposure; however, it is unknown whether there is a genetic basis for \"resistance\" to Mtb infection across populations. Here we conducted a genome-wide association study (GWAS) of resistance to Mtb infection by carefully characterizing exposure to TB patients among 4,058 close contacts in India, Brazil, and South Africa. 476 (12%) \"resisters\" remained free of Mtb infection despite substantial exposure to highly infectious TB patients. GWAS identified a novel chromosome 13 locus (rs1295104126) associated with resistance across the multi-ancestry meta-analysis. Comparing Mtb-infection to all uninfected contacts, irrespective of exposure, yielded a different locus on chromosome 6 (rs28752534), near the HLA-II region. These findings demonstrate a common genetic basis for resistance to Mtb infection across multi-ancestral cohorts with potential to elucidate novel mechanisms of protection from Mtb infection.","rel_num_authors":30,"rel_authors":[{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mandar Paradkar","author_inst":"Byramjee Jeejeebhoy Government Medical College - Johns Hopkins University Clinical Research Site"},{"author_name":"Nombuyiselo Jennet Mofokeng","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Qin Hui","author_inst":"Emory University"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Tumelo Moloantoa","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Angela Campbell","author_inst":"Emory University"},{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Alexandra Young","author_inst":"Emory University"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Doctor Heitor Vieira Dourado Tropical Medicine Foundation: Fundacao de Medicina Tropical Doutor Heitor Vieira Dourado"},{"author_name":"Sanjay Gaikwad","author_inst":"Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals"},{"author_name":"Rajesh Prabhakar Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Valeria  C Rolla","author_inst":"FIOCRUZ: Fundacao Oswaldo Cruz"},{"author_name":"Afr\u00e2nio  L. Kritski","author_inst":"Universidade Federal do Rio de Janeiro"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"N. Sarita Shah","author_inst":"Emory University"},{"author_name":"James C. M. Brust","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Vijaya Lakshmi Valluri","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Sonali Sarkar","author_inst":"JIPMER: Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Yan V. Sun","author_inst":"Emory University"}],"rel_date":"2026-03-07","rel_site":"medrxiv"},{"rel_title":"Novel Genetic Locus Associated with Resistance to M. tuberculosis Infection: A Multi-Ancestry Genome-Wide Association Study","rel_doi":"10.64898\/2026.03.06.26347614","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.06.26347614","rel_abs":"Understanding host susceptibility to Mycobacterium tuberculosis (Mtb) is critical for the development of new vaccines. Certain individuals \"resist\" becoming infected with Mtb despite intensive exposure; however, it is unknown whether there is a genetic basis for \"resistance\" to Mtb infection across populations. Here we conducted a genome-wide association study (GWAS) of resistance to Mtb infection by carefully characterizing exposure to TB patients among 4,058 close contacts in India, Brazil, and South Africa. 476 (12%) \"resisters\" remained free of Mtb infection despite substantial exposure to highly infectious TB patients. GWAS identified a novel chromosome 13 locus (rs1295104126) associated with resistance across the multi-ancestry meta-analysis. Comparing Mtb-infection to all uninfected contacts, irrespective of exposure, yielded a different locus on chromosome 6 (rs28752534), near the HLA-II region. These findings demonstrate a common genetic basis for resistance to Mtb infection across multi-ancestral cohorts with potential to elucidate novel mechanisms of protection from Mtb infection.","rel_num_authors":30,"rel_authors":[{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mandar Paradkar","author_inst":"Byramjee Jeejeebhoy Government Medical College - Johns Hopkins University Clinical Research Site"},{"author_name":"Nombuyiselo Jennet Mofokeng","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Qin Hui","author_inst":"Emory University"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Tumelo Moloantoa","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Angela Campbell","author_inst":"Emory University"},{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Alexandra Young","author_inst":"Emory University"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Doctor Heitor Vieira Dourado Tropical Medicine Foundation: Fundacao de Medicina Tropical Doutor Heitor Vieira Dourado"},{"author_name":"Sanjay Gaikwad","author_inst":"Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals"},{"author_name":"Rajesh Prabhakar Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Valeria  C Rolla","author_inst":"FIOCRUZ: Fundacao Oswaldo Cruz"},{"author_name":"Afr\u00e2nio  L. Kritski","author_inst":"Universidade Federal do Rio de Janeiro"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"N. Sarita Shah","author_inst":"Emory University"},{"author_name":"James C. M. Brust","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Vijaya Lakshmi Valluri","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Sonali Sarkar","author_inst":"JIPMER: Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Yan V. Sun","author_inst":"Emory University"}],"rel_date":"2026-03-07","rel_site":"medrxiv"},{"rel_title":"Novel Genetic Locus Associated with Resistance to M. tuberculosis Infection: A Multi-Ancestry Genome-Wide Association Study","rel_doi":"10.64898\/2026.03.06.26347614","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.06.26347614","rel_abs":"Understanding host susceptibility to Mycobacterium tuberculosis (Mtb) is critical for the development of new vaccines. Certain individuals \"resist\" becoming infected with Mtb despite intensive exposure; however, it is unknown whether there is a genetic basis for \"resistance\" to Mtb infection across populations. Here we conducted a genome-wide association study (GWAS) of resistance to Mtb infection by carefully characterizing exposure to TB patients among 4,058 close contacts in India, Brazil, and South Africa. 476 (12%) \"resisters\" remained free of Mtb infection despite substantial exposure to highly infectious TB patients. GWAS identified a novel chromosome 13 locus (rs1295104126) associated with resistance across the multi-ancestry meta-analysis. Comparing Mtb-infection to all uninfected contacts, irrespective of exposure, yielded a different locus on chromosome 6 (rs28752534), near the HLA-II region. These findings demonstrate a common genetic basis for resistance to Mtb infection across multi-ancestral cohorts with potential to elucidate novel mechanisms of protection from Mtb infection.","rel_num_authors":30,"rel_authors":[{"author_name":"Neel  R. Gandhi","author_inst":"Emory University School of Public Health"},{"author_name":"Matheus Fernandes Gyorfy","author_inst":"Emory University"},{"author_name":"Mandar Paradkar","author_inst":"Byramjee Jeejeebhoy Government Medical College - Johns Hopkins University Clinical Research Site"},{"author_name":"Nombuyiselo Jennet Mofokeng","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Marina  C Figueiredo","author_inst":"Vanderbilt University Medical Center"},{"author_name":"Senbagavalli Prakash","author_inst":"Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Kamakshi Prudhula Devalraju","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Qin Hui","author_inst":"Emory University"},{"author_name":"Fay Willis","author_inst":"Emory University"},{"author_name":"Vidya Mave","author_inst":"Johns Hopkins University"},{"author_name":"Bruno  B Andrade","author_inst":"FIOCRUZ Bahia: Instituto Goncalo Moniz"},{"author_name":"Tumelo Moloantoa","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Venkata Sanjeev Kumar Neela","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Angela Campbell","author_inst":"Emory University"},{"author_name":"Chang Liu","author_inst":"Emory University School of Public Health"},{"author_name":"Alexandra Young","author_inst":"Emory University"},{"author_name":"Marcelo Cordeiro-Santos","author_inst":"Doctor Heitor Vieira Dourado Tropical Medicine Foundation: Fundacao de Medicina Tropical Doutor Heitor Vieira Dourado"},{"author_name":"Sanjay Gaikwad","author_inst":"Byramjee Jeejeebhoy Government Medical College and Sassoon General Hospitals"},{"author_name":"Rajesh Prabhakar Karyakarte","author_inst":"BJ Government Medical College, Pune"},{"author_name":"Valeria  C Rolla","author_inst":"FIOCRUZ: Fundacao Oswaldo Cruz"},{"author_name":"Afr\u00e2nio  L. Kritski","author_inst":"Universidade Federal do Rio de Janeiro"},{"author_name":"Jeffrey  M. Collins","author_inst":"Emory University School of Medicine"},{"author_name":"N. Sarita Shah","author_inst":"Emory University"},{"author_name":"James C. M. Brust","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Vijaya Lakshmi Valluri","author_inst":"Bhagwan Mahavir Medical Research Centre"},{"author_name":"Sonali Sarkar","author_inst":"JIPMER: Jawaharlal Institute of Postgraduate Medical Education and Research"},{"author_name":"Timothy R Sterling","author_inst":"Vanderbilt University"},{"author_name":"Neil A. Martinson","author_inst":"Perinatal HIV Research Unit (PHRU), University of the Witwatersrand"},{"author_name":"Amita Gupta","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Yan V. Sun","author_inst":"Emory University"}],"rel_date":"2026-03-07","rel_site":"medrxiv"},{"rel_title":"Digital monitoring and action planning to reach zero-dose and under-immunised children: Leveraging data for targeted immunisation responses","rel_doi":"10.64898\/2026.03.03.26346932","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26346932","rel_abs":"Background Persistent inequities in immunisation coverage, particularly among zero-dose and under-immunised children, continue to challenge Pakistan's Expanded Programme on Immunization. Weak feedback loop, inconsistent data quality, and limited real-time monitoring impede effective decision-making. This Implementation Research was conducted under the MAINSTREAM Initiative funded by Alliance for Health Policy and Systems Research (AHPSR) and supported by the Aga Khan Community Health Services Department and National Institutes of Health Pakistan to design, implement, and evaluate a digital monitoring and action planning tool to strengthen data-driven decision-making within routine immunisation systems. Methodology\/Principal Findings A co-creation approach was employed to design a digital monitoring solution through inclusive consultations, key informant interviews, and focus group discussions with EPI Punjab at provincial and district levels. The solution included a customised mobile application for data collection and a Power BI visualisation dashboard to map low-coverage areas, identify drivers of dropouts and zero-dose children, and capture caregivers' information sources to inform targeted communication. The intervention was piloted in 60 households across six clusters of a Union Council of District Lahore. Advanced analytics identified reasons for non-vaccination and missed opportunities, generating tailored recommendations and practical plans for program managers. The analysis assessed acceptability, adoption, fidelity, and perceived scalability through field observations, system use, and stakeholder feedback. The co-developed digital tool enhanced visibility of coverage gaps through UC-level mapping, real-time dashboards, and structured action planning. Pilot testing in Lahore showed strong acceptability, ease of use, fidelity, and adaptability among managers, supervisors, and vaccinators. Scalability and sustainability potential were demonstrated, though barriers included leadership turnover, system fragmentation, workload pressures, and resource constraints. Conclusion The tool demonstrated feasibility to strengthen immunisation equity, accountability, and responsiveness. Co-creation with stakeholders enhanced ownership, operational relevance, and adoption, while complementing existing platforms. Sustainability will depend on effective integration, local ownership, capacity building, and accountability, while scalability requires interoperability, resource commitment, policy support, and alignment with existing workflows.","rel_num_authors":14,"rel_authors":[{"author_name":"Mariam  Zahid Malik","author_inst":"Contech International"},{"author_name":"Naeem  uddin Mian","author_inst":"Contech International"},{"author_name":"Zahid Memon","author_inst":"Aga Khan University"},{"author_name":"Muhammad  Wasim Mirza","author_inst":"Contech International"},{"author_name":"Umer  Farooq Rana","author_inst":"Contech International"},{"author_name":"M.  Adeel Alvi","author_inst":"Contech International"},{"author_name":"Wardah Ahmed","author_inst":"Aga Khan University"},{"author_name":"Asma Ummad","author_inst":"Aga Khan University"},{"author_name":"Ammarah Ali","author_inst":"Aga Khan University"},{"author_name":"Usama Naveed","author_inst":"Contech Digital"},{"author_name":"Khayyam  Saeed Malik","author_inst":"Contech Digital"},{"author_name":"Muhammad  Sufyan Chaudhary","author_inst":"Contech Digital"},{"author_name":"Maria Waheed","author_inst":"Contech International"},{"author_name":"Amna Sattar","author_inst":"Contech International"}],"rel_date":"2026-03-07","rel_site":"medrxiv"},{"rel_title":"Chromatin tethering to the nuclear envelope enhances its accessibility to RNAPII and promotes chromatin asymmetric organization","rel_doi":"10.64898\/2026.03.06.710131","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.710131","rel_abs":"The intrinsic tendency of chromatin to self-attract competes with its association with RNA Polymerase II (RNAPII), a prerequisite for efficient transcription. Using high-resolution live imaging of chromatin and RNAPII organization in Drosophila larval muscle nuclei, we demonstrate that chromatin tethering to the nuclear envelope via the Linker of Nucleoskeleton and Cytoskeleton (LINC) complex is essential for maintaining chromatin three-dimensional organization. Disruption of chromatin-lamina interactions either in LINC mutants or following knockdown of Barrier-to-Autointegration Factor (BAF) results in enhanced chromatin clustering in the nucleoplasm and reduced RNAPII-chromatin interaction. Consistent with these observations, computer simulations revealed an inverse relationship between the chromatin cluster size and the degree of chromatin tethering to the nuclear lamina. We also measured chromatin distribution with respect to the nuclear lamina and found asymmetry of RNAPII distributions within chromatin clusters, which correlated with their proximity to the nuclear envelope, a relationship that is lost in nuclei lacking a functional LINC complex. Our findings demonstrate that chromatin association with the nuclear envelope counteracts chromatin self-attraction and facilitates RNAPII binding to DNA.","rel_num_authors":6,"rel_authors":[{"author_name":"Dana Lorber","author_inst":"Weizmann Institute of Science"},{"author_name":"Ido Azuri","author_inst":"Weizmann Institute of Science"},{"author_name":"Amit Kumar","author_inst":"Weizmann Institute of Science"},{"author_name":"Ron Rotkopf","author_inst":"Weizmann Institute of Science"},{"author_name":"Sam Safran","author_inst":"Weizmann Institute of Science"},{"author_name":"Talila Volk","author_inst":"Weizmann Institute of Science"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"IFI207 promotes antiviral responses by modulating STING ubiquitination and degradation","rel_doi":"10.64898\/2026.03.05.709838","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709838","rel_abs":"Aim2-like receptors (ALRs) play crucial roles in innate immune signaling pathways and demonstrate strong positive selection likely driven by pathogens. IFI207, an ALR found in all Mus species, enhances interaction with and stabilization of STING, contributing to the control of Murine Leukemia Virus (MLV) infection. We show here that IFI207 enhances the type 1 interferon response by inhibiting activation-induced K63-linked ubiquitination of STING, thereby preventing its recognition by hepatocyte growth factor-regulated tyrosine kinase substrate (HRS), a key component of the ESCRT complex, and its subsequent degradation in lysosomes. IFI207 promotes downstream signaling in the STING pathway in multiple cell types and moreover enhances the STING-dependent response to herpesvirus simplex 1 infection ex vivo and in vivo. We also show that IFI207 likely functions in dendritic cells to suppress MLV infection. Our study reveals that IFI207 acts as a modulator in the STING pathway, strengthening the host defense against viral infections and suggests that the expansion of the Alr locus in mice may have occurred in response to endemic viruses.","rel_num_authors":5,"rel_authors":[{"author_name":"Takuji Enya","author_inst":"Duke University"},{"author_name":"Wenming Zhao","author_inst":"University of Illinois at Chicago College of Medicine"},{"author_name":"Geetanjali Geetanjali","author_inst":"UIC College of Medicine"},{"author_name":"Bin He","author_inst":"UIC College of Medicine"},{"author_name":"Susan R Ross","author_inst":"University of Illinois at Chicago College of Medicine"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Neurocognitive deficits in controlling aversive memory among insomnia disorders","rel_doi":"10.64898\/2026.03.04.709020","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709020","rel_abs":"Background. Insomnia disorder is a common sleep disturbance characterized by adverse daytime cognitive and emotional impairments, such as repetitive negative thinking and increased psychological distress. Memory control, a key self-regulatory ability to control or inhibit unwanted thoughts and memories, plays an essential role in supporting cognitive functions and emotional well-being. Here, we delineate the neurocognitive mechanisms underlying memory control among individuals with insomnia. Methods. 41 participants meeting DSM-5 criteria for insomnia disorder and 40 healthy sleepers completed an emotional Think\/No-Think task, during which participants either retrieved (Think) or suppressed the retrieval (No-Think) of aversive memories in response to memory cues while electroencephalograms were recorded. Results. Linear mixed model analyses with age and depression scores as covariates showed that participants with insomnia exhibited impaired memory control abilities, as evidenced by reduced suppression-induced forgetting in memory recall when compared to healthy sleepers. Electrophysiologically, healthy sleepers showed enhanced right prefrontal theta power in retrieval suppression than in retrieval, indicating elevated needs of inhibitory control during memory control. In sharp contrast, this difference was absent among those with insomnia. Notably, the greater the severity of insomnia symptoms, the smaller the retrieval vs. retrieval suppression theta power differences across participants, linking inefficient top-down control of unwanted memories with low sleep qualities. Conclusion. Individuals with insomnia showed impaired memory control of aversive memories and aberrant electrophysiological activities during retrieval suppression. Future research shall investigate the causal relationship between memory control abilities and insomnia symptoms.","rel_num_authors":14,"rel_authors":[{"author_name":"Xibo Zuo","author_inst":"The University of Hong Kong"},{"author_name":"Xuanyi Lin","author_inst":"Northwestern University"},{"author_name":"Ziqing Yao","author_inst":"The University of Hong Kong"},{"author_name":"Danni Chen","author_inst":"The University of Hong Kong"},{"author_name":"Jing Liu","author_inst":"South China Normal University"},{"author_name":"Sean Guo","author_inst":"The University of Hong Kong"},{"author_name":"Wing Yin Winny Yue","author_inst":"The University of Hong Kong"},{"author_name":"Ying Yang","author_inst":"The First Affiliated Hospital of Jinan University"},{"author_name":"Wei Wang","author_inst":"The Affiliated Brain Hospital, Guangzhou Medical University"},{"author_name":"Hongliang Feng","author_inst":"The Affiliated Brain Hospital, Guangzhou Medical University"},{"author_name":"Jihui Zhang","author_inst":"The Affiliated Brain Hospital, Guangzhou Medical University"},{"author_name":"Michael Anderson","author_inst":"University of Cambridge"},{"author_name":"Shirley Xin Li","author_inst":"The University of Hong Kong"},{"author_name":"Xiaoqing Hu","author_inst":"The University of Hong Kong"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Positive Affect Modulates Early Valuation and Conflict Processing in Social Decision-Making","rel_doi":"10.64898\/2026.03.05.709732","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709732","rel_abs":"Social decision making relies on dynamic affect cognition interactions across distributed brain networks, yet how incidental positive affect modulates these mechanisms at a millisecond timescale remains unclear. This study investigated the impact of music-induced positive emotion on the neural dynamics of decision-making in the Ultimatum Game. Fifty six participants were assigned to either a happy music group or an active control (rain sound) group. Fifty six participants were assigned to either a happy music group or an active control (rain sound) group, while electroencephalography was recorded to capture rapid neural dynamics. Behaviorally, happy music accelerated reaction times (RTs) and decoupled the ERP RT correlations observed in the control condition. Neurally, positive affect amplified event-related potential amplitudes during early conflict detection (220 to 280 ms) and late valuation (520 to 560 ms) stages. Multivariate pattern analysis further revealed that happy music enhanced the neural separability and temporal stability of decision states (accept vs. reject). Moreover, using support vector regression based on functional network features, we found that decision acceptance rates were predicted with significantly higher accuracy in the happy music group (R = 0.60) compared to controls (R = 0.41). Crucially, feature weight analysis indicated a topological shift in decision strategy: while the control group relied on frontal central edges (implicating executive control), the happy music group was characterized by central temporal connections (suggesting integrative processing). Collectively, these findings provide novel evidence that incidental emotion intervenes at the millisecond timescale to bias social choices, offering a dynamic network based account of the affect cognition interaction.","rel_num_authors":5,"rel_authors":[{"author_name":"Zhengxian Liu","author_inst":"Southwest University"},{"author_name":"Yunting Liu","author_inst":"Minnan University of Science and Technology"},{"author_name":"Weixian Li","author_inst":"School of Public Affairs, Xiamen University"},{"author_name":"Ruifang Cui","author_inst":"School of Information Engineering, Huzhou University"},{"author_name":"Xiaobo Liu","author_inst":"McGill University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Early Binding of Anti-Amyloid Antibodies to CAA Drives Complement Activation, Inflammation and ARIA in Mice","rel_doi":"10.64898\/2026.03.04.709591","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709591","rel_abs":"Anti-amyloid antibody treatment for Alzheimers disease is linked to Amyloid-Related Imaging Abnormalities (ARIA), including vasogenic edema (ARIA-E) and microhemorrhages (ARIA-H), especially in ApoE {epsilon} 4\/4 carriers. To investigate mechanisms underlying ARIA, we examined the binding and temporal vascular effects of immunization with 3D6, the precursor to the anti-amyloid antibody bapineuzumab, in two aged Alzheimers disease amyloid mouse models. Acutely, 3D6 bound to cerebral amyloid angiopathy (CAA), resulting in C1q binding and classical complement activation. Weekly short-term immunization over 7 weeks resulted in elevated CAA- and plaque-associated complement deposition, red blood cell extravasation and microhemorrhages, and was accompanied by significant transcriptomic changes in genes related to complement, inflammation, vascular dysfunction, and endothelial lipid responses. Longer-term dosing over 13-15 weeks further increased complement deposition and was associated with blood-brain barrier disruption, MMP-9 upregulation, and microhemorrhages, accompanied by reduced amyloid burden and modest CAA clearance. C3 levels correlated with microhemorrhage severity. Perivascular macrophages co-localized with complement-decorated CAA in 3D6-treated mice. These findings implicate complement activation as an early key driver of ARIA and suggest that therapeutic targeting of complement may reduce ARIA risk.","rel_num_authors":6,"rel_authors":[{"author_name":"Praveen Bathini","author_inst":"Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA"},{"author_name":"Stephan Schilling","author_inst":"Fraunhofer Institute for Cell Therapy and Immunology, Halle (Saale), Anhalt University of Applied Sciences, Kothen, Germany"},{"author_name":"Jens  Ulrich Rahfeld","author_inst":"Fraunhofer Institute for Cell Therapy and Immunology, Halle (Saale), Anhalt University of Applied Sciences, Kothen, Germany"},{"author_name":"David M Holtzman","author_inst":"Washington University School of Medicine, St. Louis, MO, USA"},{"author_name":"Takaomi C. Sado","author_inst":"RIKEN Center for Brain Science, Japan"},{"author_name":"Cynthia A Lemere","author_inst":"Brigham and Womens Hospital, Harvard Medical School, Boston, MA, USA"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Reprogramming of neuronal genome function and phenotype by astrocytes","rel_doi":"10.64898\/2026.03.07.710282","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.07.710282","rel_abs":"Heterotypic cell-cell interactions are critical to governing cellular physiology, disease progression, and responses to the environment and pharmacologic interventions. For example, neurons and astrocytes engage in intricate interactions that are essential for brain development and function. However, the transformation of these extracellular signals into epigenomic regulation that governs cell function is poorly understood. Here, we report that weeks of co-culture between human induced pluripotent stem cell (hiPSC)-derived neurons and mouse cortical astrocytes extensively reprograms gene expression and the chromatin accessibility landscape in neurons, affecting thousands of genes and putative gene regulatory elements (REs), including many transcription factors (TFs). These genes are enriched for functions implicated in neuronal differentiation and maturation, and tend to be impacted in schizophrenia, and autosomal dominant Alzheimer's disease. Through complementary CRISPR interference and activation screens, we recapitulated hundreds of astrocyte-induced transcriptional and chromatin remodeling events in mono-cultured neurons at both promoters and distal regulatory elements (REs) of TF genes. We discovered functional REs for ~50 astrocyte-responsive TF genes, providing a map of gene regulatory network control. Astrocyte-responsive TF genes fall into groups that exert independent or counter-balancing transcriptional effects, highlighting the complex coordination of the neuronal response to astrocytes. Functional effects of specific TFs, including POU3F2 and TFAP2E, on neurite morphology and neuronal electrophysiology are consistent with transcriptional effects, demonstrating the capacity of direct epigenetic control to mimic heterotypic cellular signals. This work illuminates the regulation of neurodevelopment- and disease-relevant gene modules by neuron-astrocyte interactions, and provides a blueprint for applying modern functional genomics to uncover the links between cell microenvironment and epigenomic programming.","rel_num_authors":14,"rel_authors":[{"author_name":"Boxun Li","author_inst":"Duke University"},{"author_name":"Kevin Hagy","author_inst":"Duke University"},{"author_name":"Alexias Safi","author_inst":"Duke University"},{"author_name":"Michael A. Beer","author_inst":"Johns Hopkins University"},{"author_name":"Alejandro Barrera","author_inst":"Duke University"},{"author_name":"Sara Geraghty","author_inst":"Duke University"},{"author_name":"Ruhi Rai","author_inst":"Duke University"},{"author_name":"Alyssa N. Pederson","author_inst":"Duke University"},{"author_name":"Samuel J. Reisman","author_inst":"Duke University"},{"author_name":"Michael I. Love","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Patrick F. Sullivan","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Cagla Eroglu","author_inst":"Duke University"},{"author_name":"Gregory E. Crawford","author_inst":"Duke University"},{"author_name":"Charles A. Gersbach","author_inst":"Duke University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"The Kinetic Intron Hypothesis","rel_doi":"10.64898\/2026.03.04.709683","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709683","rel_abs":"Intron length is a fascinating example of form without function. The vast majority of intronic space within genomes remains without a provided utility. It often fascinates us to find introns performing any function at all, establishing an attention bias against the vast lacking of utility of the remaining intergenic space. In an attempt to better understand the greater breadth of intronic length, I investigate here what I term The Kinetic Intron Hypothesis. This hypothesis investigates hypothetical dynamics of intron RNA synthesis and degradation. It explores how NTPs stored within intron RNA might function in mitosis and NTP resource management. Preliminary testing of the hypothesis leads to trends that warrant further exploration and validation by the scientific community.","rel_num_authors":1,"rel_authors":[{"author_name":"Garrett Tisdale","author_inst":"Johns Hopkins School of Medicine"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Single-molecule spatial genomics reveals the multi-scale organization and plasticity of extrachromosomal DNA in glioblastoma","rel_doi":"10.64898\/2026.03.05.709911","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709911","rel_abs":"Extrachromosomal DNA (ecDNA) is a major driver of intratumoral heterogeneity and is associated with poor clinical outcomes across cancers, yet how individual ecDNA molecules are organized and regulated within intact tumors remains unknown. Here, we leveraged single-molecule, multi-modal spatial genomics to resolve the three-dimensional chromatin organization and transcriptional activity of individual EGFR-containing ecDNA molecules in glioblastoma (GBM) cells in vitro, in orthotopic xenografts, and in patient-derived GBM tissue. At the larger scale, we find that distinct GBM molecular and functional states emerge depending on the local cellular environment. EGFR expression was markedly different between GBM subpopulations, and perturbations of EGFR dosage shifted GBM cellular states. ecDNA expression was modulated by multiple mechanisms, including variation in copy number, chromatin organization, DNA sequence, and chromosomal reintegration, which were simultaneously measured within the same cells. At the single-molecule scale, ecDNA adopts a physically expanded chromatin configuration with larger ecDNA molecules having higher transcriptional activity and interaction with active transcriptional machinery. ecDNA regulation was coordinated within cells and across GBM states, and ecDNA copy number, structure, and transcription were spatially organized across the tumor architecture. Co-culturing GBM cells with neurons recapitulated key features of infiltrative regions, including lower EGFR expression, reduced ecDNA copy number, and increased chromosomal reintegration, suggesting a causal role for the microenvironment in shaping ecDNA regulation. Collectively, these findings support a model in which GBM states and ecDNA are linked, plastic, and influenced by microenvironmental contexts, revealing a previously inaccessible layer of genome organization underlying tumor heterogeneity and malignant cell behavior.","rel_num_authors":24,"rel_authors":[{"author_name":"Brett Taylor","author_inst":"University of California San Diego"},{"author_name":"Weixiu Dong","author_inst":"University of California San Diego"},{"author_name":"Tula Keal","author_inst":"tkeal@health.ucsd.edu"},{"author_name":"Zhaoning Wang","author_inst":"University of California San Diego"},{"author_name":"Bharath Saravanan","author_inst":"University of California San Diego"},{"author_name":"Zane A. Gibbs","author_inst":"University of California San Diego"},{"author_name":"Yohei Miyake","author_inst":"University of California San Diego"},{"author_name":"Daisuke Kawauchi","author_inst":"University of California San Diego"},{"author_name":"Raghavendra Vadla","author_inst":"University of California San Diego"},{"author_name":"Abhinaba Banerjee","author_inst":"University of California San Diego"},{"author_name":"Omar Elkassih","author_inst":"University of California San Diego"},{"author_name":"Sahana Kashyap","author_inst":"University of California San Diego"},{"author_name":"Brandon M Jones","author_inst":"University of California San Diego"},{"author_name":"Kseniya Malukhina","author_inst":"University of California San Diego"},{"author_name":"Mahsa Nafisi","author_inst":"University of California San Diego"},{"author_name":"Timothy H Loe","author_inst":"University of California San Diego"},{"author_name":"Joseph Bendik","author_inst":"University of California San Diego"},{"author_name":"Tom McAllister","author_inst":"University of California San Diego"},{"author_name":"Yang Xie","author_inst":"yangxie@nygenome.org"},{"author_name":"Lei Chang","author_inst":"University of California San Diego"},{"author_name":"Clark Chen","author_inst":"Brown University Health"},{"author_name":"Bing Ren","author_inst":"University of California San Diego"},{"author_name":"Frank Furnari","author_inst":"University of California San Diego"},{"author_name":"Bogdan Bintu","author_inst":"University of California San Diego"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Single-molecule spatial genomics reveals the multi-scale organization and plasticity of extrachromosomal DNA in glioblastoma","rel_doi":"10.64898\/2026.03.05.709911","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709911","rel_abs":"Extrachromosomal DNA (ecDNA) is a major driver of intratumoral heterogeneity and is associated with poor clinical outcomes across cancers, yet how individual ecDNA molecules are organized and regulated within intact tumors remains unknown. Here, we leveraged single-molecule, multi-modal spatial genomics to resolve the three-dimensional chromatin organization and transcriptional activity of individual EGFR-containing ecDNA molecules in glioblastoma (GBM) cells in vitro, in orthotopic xenografts, and in patient-derived GBM tissue. At the larger scale, we find that distinct GBM molecular and functional states emerge depending on the local cellular environment. EGFR expression was markedly different between GBM subpopulations, and perturbations of EGFR dosage shifted GBM cellular states. ecDNA expression was modulated by multiple mechanisms, including variation in copy number, chromatin organization, DNA sequence, and chromosomal reintegration, which were simultaneously measured within the same cells. At the single-molecule scale, ecDNA adopts a physically expanded chromatin configuration with larger ecDNA molecules having higher transcriptional activity and interaction with active transcriptional machinery. ecDNA regulation was coordinated within cells and across GBM states, and ecDNA copy number, structure, and transcription were spatially organized across the tumor architecture. Co-culturing GBM cells with neurons recapitulated key features of infiltrative regions, including lower EGFR expression, reduced ecDNA copy number, and increased chromosomal reintegration, suggesting a causal role for the microenvironment in shaping ecDNA regulation. Collectively, these findings support a model in which GBM states and ecDNA are linked, plastic, and influenced by microenvironmental contexts, revealing a previously inaccessible layer of genome organization underlying tumor heterogeneity and malignant cell behavior.","rel_num_authors":24,"rel_authors":[{"author_name":"Brett Taylor","author_inst":"University of California San Diego"},{"author_name":"Weixiu Dong","author_inst":"University of California San Diego"},{"author_name":"Tula Keal","author_inst":"tkeal@health.ucsd.edu"},{"author_name":"Zhaoning Wang","author_inst":"University of California San Diego"},{"author_name":"Bharath Saravanan","author_inst":"University of California San Diego"},{"author_name":"Zane A. Gibbs","author_inst":"University of California San Diego"},{"author_name":"Yohei Miyake","author_inst":"University of California San Diego"},{"author_name":"Daisuke Kawauchi","author_inst":"University of California San Diego"},{"author_name":"Raghavendra Vadla","author_inst":"University of California San Diego"},{"author_name":"Abhinaba Banerjee","author_inst":"University of California San Diego"},{"author_name":"Omar Elkassih","author_inst":"University of California San Diego"},{"author_name":"Sahana Kashyap","author_inst":"University of California San Diego"},{"author_name":"Brandon M Jones","author_inst":"University of California San Diego"},{"author_name":"Kseniya Malukhina","author_inst":"University of California San Diego"},{"author_name":"Mahsa Nafisi","author_inst":"University of California San Diego"},{"author_name":"Timothy H Loe","author_inst":"University of California San Diego"},{"author_name":"Joseph Bendik","author_inst":"University of California San Diego"},{"author_name":"Tom McAllister","author_inst":"University of California San Diego"},{"author_name":"Yang Xie","author_inst":"yangxie@nygenome.org"},{"author_name":"Lei Chang","author_inst":"University of California San Diego"},{"author_name":"Clark Chen","author_inst":"Brown University Health"},{"author_name":"Bing Ren","author_inst":"University of California San Diego"},{"author_name":"Frank Furnari","author_inst":"University of California San Diego"},{"author_name":"Bogdan Bintu","author_inst":"University of California San Diego"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Single-molecule spatial genomics reveals the multi-scale organization and plasticity of extrachromosomal DNA in glioblastoma","rel_doi":"10.64898\/2026.03.05.709911","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709911","rel_abs":"Extrachromosomal DNA (ecDNA) is a major driver of intratumoral heterogeneity and is associated with poor clinical outcomes across cancers, yet how individual ecDNA molecules are organized and regulated within intact tumors remains unknown. Here, we leveraged single-molecule, multi-modal spatial genomics to resolve the three-dimensional chromatin organization and transcriptional activity of individual EGFR-containing ecDNA molecules in glioblastoma (GBM) cells in vitro, in orthotopic xenografts, and in patient-derived GBM tissue. At the larger scale, we find that distinct GBM molecular and functional states emerge depending on the local cellular environment. EGFR expression was markedly different between GBM subpopulations, and perturbations of EGFR dosage shifted GBM cellular states. ecDNA expression was modulated by multiple mechanisms, including variation in copy number, chromatin organization, DNA sequence, and chromosomal reintegration, which were simultaneously measured within the same cells. At the single-molecule scale, ecDNA adopts a physically expanded chromatin configuration with larger ecDNA molecules having higher transcriptional activity and interaction with active transcriptional machinery. ecDNA regulation was coordinated within cells and across GBM states, and ecDNA copy number, structure, and transcription were spatially organized across the tumor architecture. Co-culturing GBM cells with neurons recapitulated key features of infiltrative regions, including lower EGFR expression, reduced ecDNA copy number, and increased chromosomal reintegration, suggesting a causal role for the microenvironment in shaping ecDNA regulation. Collectively, these findings support a model in which GBM states and ecDNA are linked, plastic, and influenced by microenvironmental contexts, revealing a previously inaccessible layer of genome organization underlying tumor heterogeneity and malignant cell behavior.","rel_num_authors":24,"rel_authors":[{"author_name":"Brett Taylor","author_inst":"University of California San Diego"},{"author_name":"Weixiu Dong","author_inst":"University of California San Diego"},{"author_name":"Tula Keal","author_inst":"tkeal@health.ucsd.edu"},{"author_name":"Zhaoning Wang","author_inst":"University of California San Diego"},{"author_name":"Bharath Saravanan","author_inst":"University of California San Diego"},{"author_name":"Zane A. Gibbs","author_inst":"University of California San Diego"},{"author_name":"Yohei Miyake","author_inst":"University of California San Diego"},{"author_name":"Daisuke Kawauchi","author_inst":"University of California San Diego"},{"author_name":"Raghavendra Vadla","author_inst":"University of California San Diego"},{"author_name":"Abhinaba Banerjee","author_inst":"University of California San Diego"},{"author_name":"Omar Elkassih","author_inst":"University of California San Diego"},{"author_name":"Sahana Kashyap","author_inst":"University of California San Diego"},{"author_name":"Brandon M Jones","author_inst":"University of California San Diego"},{"author_name":"Kseniya Malukhina","author_inst":"University of California San Diego"},{"author_name":"Mahsa Nafisi","author_inst":"University of California San Diego"},{"author_name":"Timothy H Loe","author_inst":"University of California San Diego"},{"author_name":"Joseph Bendik","author_inst":"University of California San Diego"},{"author_name":"Tom McAllister","author_inst":"University of California San Diego"},{"author_name":"Yang Xie","author_inst":"yangxie@nygenome.org"},{"author_name":"Lei Chang","author_inst":"University of California San Diego"},{"author_name":"Clark Chen","author_inst":"Brown University Health"},{"author_name":"Bing Ren","author_inst":"University of California San Diego"},{"author_name":"Frank Furnari","author_inst":"University of California San Diego"},{"author_name":"Bogdan Bintu","author_inst":"University of California San Diego"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"The impact of coinfection on population stability and chaos","rel_doi":"10.64898\/2026.03.06.710155","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.710155","rel_abs":"Parasites play an outsized role in mediating the persistence and stability of host populations. Flour beetles (Tribolium spp.) have long served as classic examples of population dynamics under both disease-free and infected conditions, with elegant combinations of theory and experiments demonstrating, for example, that cannibalism rates can push populations from stability to chaos. As with most organisms in nature, however, flour beetles rarely face just one parasite species, and co-infecting parasites can antagonize or facilitate each other through resources and immunity. To test the prediction that non-neutral interactions would qualitatively alter population stability, we first raised flour beetles (Tribolium castaneum) in infection-free, single-infection, or coinfection microcosms and quantified relative prevalence and parasite intensity. Next, we reworked a classic stage-structured discrete-time model to include single and multiple infections and performed sensitivity and bifurcation analyses to identify the most important (co)infection-associated parameters for population stability. The model predicts that stability is highly sensitive to parasite transmission mode regardless of infection multiplicity, but facilitation among parasites rapidly drives populations into oscillations and chaos under realistic conditions. This study identifies an important mechanism for explaining population variability and highlights the importance of within-host mechanisms for driving dynamics at higher levels of biological organization.","rel_num_authors":3,"rel_authors":[{"author_name":"Fernando J.M. Barahona","author_inst":"Vanderbilt University"},{"author_name":"Edith Simpson","author_inst":"Vanderbilt University"},{"author_name":"Ann T Tate","author_inst":"Vanderbilt University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Invasion histories reveal most North American introduced plants have not yet reached climatic stasis.","rel_doi":"10.64898\/2026.03.05.709936","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709936","rel_abs":"Aim: Analysis of species distributions often rests on the assumption of environmental equilibrium. That is, the distribution of a species (as documented by observation records) captures the full range of environmental conditions under which that species can maintain viable populations. Despite the centrality of this assumption to a variety of biogeographic questions, it is rarely empirically tested. This is particularly critical for recently introduced invasive species that are characterized by rapid expansion in their introduced range, often coupled with a niche shift relative to their native distribution. Defining equilibrium under these dynamic conditions is difficult. We developed the concept of environmental stasis as a more tractable proxy for equilibrium. In the context of species invasions, we define stasis as a prolonged period without an increase in the environmental conditions occupied by a species. Location: North America Time Period: 1614 to 2020. Major Taxa Studied: Invasive plants Methods: We applied the metric of climatic stasis to a suite of 258 invasive plant species in North America. We categorized their invasion trajectories into three classes (linear, two- and three-phase) based on theoretical expectations and then assessed how many had demonstrated environmental (climatic) stasis over a period of at least thirty years. Results: More than 80% of the species were best fit by two- or three-phase models, indicating a declining rate of expansion. Climatic stasis was only documented for 44% of the species. In contrast, 85% of the species were in climatic stasis in their native ranges. The time to reach stasis ranged from 30 to 145 years (mean 90), and species at stasis in their invaded range occupied 97% of the climatic space they occupied in their native range. Main Conclusions: This assessment provides valuable insight into the unrealized threat posed by the majority of invasive plants that have not yet reached stasis, as well as identifying which species can be most appropriately evaluated by methods that depend on the equilibrium assumption. Our work also demonstrates the useful perspective provided by the environmental stasis concept, which enables empirical quantification of one of the key aspects of equilibrium.","rel_num_authors":3,"rel_authors":[{"author_name":"Maisy Roach-Krajewski","author_inst":"University of Ottawa"},{"author_name":"Tyler W. Smith","author_inst":"Agriculture and Agri-Food Canada"},{"author_name":"Heather M. Kharouba","author_inst":"University of Ottawa"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Invasion histories reveal most North American introduced plants have not yet reached climatic stasis.","rel_doi":"10.64898\/2026.03.05.709936","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709936","rel_abs":"Aim: Analysis of species distributions often rests on the assumption of environmental equilibrium. That is, the distribution of a species (as documented by observation records) captures the full range of environmental conditions under which that species can maintain viable populations. Despite the centrality of this assumption to a variety of biogeographic questions, it is rarely empirically tested. This is particularly critical for recently introduced invasive species that are characterized by rapid expansion in their introduced range, often coupled with a niche shift relative to their native distribution. Defining equilibrium under these dynamic conditions is difficult. We developed the concept of environmental stasis as a more tractable proxy for equilibrium. In the context of species invasions, we define stasis as a prolonged period without an increase in the environmental conditions occupied by a species. Location: North America Time Period: 1614 to 2020. Major Taxa Studied: Invasive plants Methods: We applied the metric of climatic stasis to a suite of 258 invasive plant species in North America. We categorized their invasion trajectories into three classes (linear, two- and three-phase) based on theoretical expectations and then assessed how many had demonstrated environmental (climatic) stasis over a period of at least thirty years. Results: More than 80% of the species were best fit by two- or three-phase models, indicating a declining rate of expansion. Climatic stasis was only documented for 44% of the species. In contrast, 85% of the species were in climatic stasis in their native ranges. The time to reach stasis ranged from 30 to 145 years (mean 90), and species at stasis in their invaded range occupied 97% of the climatic space they occupied in their native range. Main Conclusions: This assessment provides valuable insight into the unrealized threat posed by the majority of invasive plants that have not yet reached stasis, as well as identifying which species can be most appropriately evaluated by methods that depend on the equilibrium assumption. Our work also demonstrates the useful perspective provided by the environmental stasis concept, which enables empirical quantification of one of the key aspects of equilibrium.","rel_num_authors":3,"rel_authors":[{"author_name":"Maisy Roach-Krajewski","author_inst":"University of Ottawa"},{"author_name":"Tyler W. Smith","author_inst":"Agriculture and Agri-Food Canada"},{"author_name":"Heather M. Kharouba","author_inst":"University of Ottawa"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Epigenetic Silencing of Carotid Body TRPM7 Attenuates Hypertension in Obese Mice","rel_doi":"10.64898\/2026.03.05.709322","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709322","rel_abs":"Obesity is the most common cause of hypertension. We have previously shown that high levels of circulating leptin in diet-induced obese (DIO) mice induced hypertension by increasing expression of Transient Receptor Potential Melastatin-subfamily member 7 (TRPM7) in the carotid bodies (CB). In addition, we demonstrated in rat PC12 cells that leptin increases Trpm7 gene expression by inducing CpG site-specific demethylation within the 5'' regulatory region containing a signal transducer and activator of transcription 3 (STAT3) binding site. This leptin-induced Trpm7 upregulation was prevented by inhibition of JAK-STAT3 signaling. Based on these findings, we hypothesized that reversing region-specific methylation at the Trpm7 promoter in the CB could attenuate obesity-associated hypertension. Compared with lean controls, DIO mice exhibited increased Trpm7 expression and the STAT3- binding site-specific promoter demethylation in the CB. Administration of methylated DNA oligonucleotides targeting the STAT3 binding site attenuated CpG site-specific DNA demethylation and reduced Trpm7 transcription in the CB of DIO mice. This intervention resulted in decreased carotid sinus nerve activity and reduced arterial blood pressure, especially during the light phase. Our results suggest that targeted modulation of CpG site-specific DNA methylation at the Trpm7 promoter using DNA oligonucleotide may represent a novel therapeutic strategy for obesity-induced hypertension.","rel_num_authors":7,"rel_authors":[{"author_name":"Mi Kyung Shin","author_inst":"George Washington University"},{"author_name":"Arijit Roy","author_inst":"George Washington University"},{"author_name":"Omkar Paudel","author_inst":"Johns Hopkins University"},{"author_name":"Samhita Gudapati","author_inst":"University of Pittsburgh"},{"author_name":"James Sham","author_inst":"Johns Hopkins University"},{"author_name":"Wan-Yee Tang","author_inst":"University of Pittsburgh"},{"author_name":"Vsevolod Polotsky","author_inst":"George Washington University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Epigenetic Silencing of Carotid Body TRPM7 Attenuates Hypertension in Obese Mice","rel_doi":"10.64898\/2026.03.05.709322","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709322","rel_abs":"Obesity is the most common cause of hypertension. We have previously shown that high levels of circulating leptin in diet-induced obese (DIO) mice induced hypertension by increasing expression of Transient Receptor Potential Melastatin-subfamily member 7 (TRPM7) in the carotid bodies (CB). In addition, we demonstrated in rat PC12 cells that leptin increases Trpm7 gene expression by inducing CpG site-specific demethylation within the 5'' regulatory region containing a signal transducer and activator of transcription 3 (STAT3) binding site. This leptin-induced Trpm7 upregulation was prevented by inhibition of JAK-STAT3 signaling. Based on these findings, we hypothesized that reversing region-specific methylation at the Trpm7 promoter in the CB could attenuate obesity-associated hypertension. Compared with lean controls, DIO mice exhibited increased Trpm7 expression and the STAT3- binding site-specific promoter demethylation in the CB. Administration of methylated DNA oligonucleotides targeting the STAT3 binding site attenuated CpG site-specific DNA demethylation and reduced Trpm7 transcription in the CB of DIO mice. This intervention resulted in decreased carotid sinus nerve activity and reduced arterial blood pressure, especially during the light phase. Our results suggest that targeted modulation of CpG site-specific DNA methylation at the Trpm7 promoter using DNA oligonucleotide may represent a novel therapeutic strategy for obesity-induced hypertension.","rel_num_authors":7,"rel_authors":[{"author_name":"Mi Kyung Shin","author_inst":"George Washington University"},{"author_name":"Arijit Roy","author_inst":"George Washington University"},{"author_name":"Omkar Paudel","author_inst":"Johns Hopkins University"},{"author_name":"Samhita Gudapati","author_inst":"University of Pittsburgh"},{"author_name":"James Sham","author_inst":"Johns Hopkins University"},{"author_name":"Wan-Yee Tang","author_inst":"University of Pittsburgh"},{"author_name":"Vsevolod Polotsky","author_inst":"George Washington University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Community assembly explains invasion differences between two contrasting forest types","rel_doi":"10.64898\/2026.03.05.709929","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709929","rel_abs":"Plant communities within a metacommunity can vary widely in their degree of invasion by introduced species. Disturbance, propagule pressure, and biotic resistance are common explanations for this variation, but empirical evidence for these hypotheses is mixed. Alternatively, the community assembly framework predicts that local assembly filters determine both native and exotic composition, but lower trait variation in the introduced species pool may exclude them from certain sites. We examined evidence for this framework using observational data from forests and woodlands of Long Island, NY, USA. These forests vary in vegetation composition and invasion along a soil gradient. They are also highly disturbed and fragmented, yet some stands have almost no introduced plants. Using data collected in 1998 and 2021-22, we quantified relationships between community composition, soil characteristics, and functional traits for native and exotic assemblages, as indicators of environmental filtering. We found similar trait-environment relationships in native and introduced species, suggesting that both groups follow the same local assembly rules. Introduced species were predominantly found in sites with more nutrient-rich soils and were absent from sites with nutrient-poor soils. At the regional scale, the exotic species pool was biased toward trait values favored in more nutrient-rich environments, particularly high growth rates and low leaf C:N ratios, which explains their absence from nutrient-poor environments. These patterns were consistent over time, and stands that were uninvaded in 1998 remained so in 2021-22, supporting the robustness and reliability of short-term studies. This study shows that invasion patterns in plant communities can be explained by the assembly rules that govern native species. By linking local environmental filtering with regional species pool characteristics, this work advances our understanding of how some communities remain uninvaded despite high disturbance and propagule pressure. Overall, these results highlight the utility of the community assembly framework, and emphasize the importance of regional processes in constraining the local distribution of introduced species.","rel_num_authors":7,"rel_authors":[{"author_name":"Urmi Poddar","author_inst":"Stony Brook University"},{"author_name":"Tracey Dong","author_inst":"Stony Brook University"},{"author_name":"Kristi Lam","author_inst":"Columbia University"},{"author_name":"Vivianne Lee","author_inst":"University of Connecticut"},{"author_name":"Paul Wilson","author_inst":"Stony Brook University"},{"author_name":"Jessica Gurevitch","author_inst":"Purdue University"},{"author_name":"Rafael D'Andrea","author_inst":"Stony Brook University"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"A Modular Framework for Automated Segmentation and Analysis of AFM Imaging of Chromatin Organization","rel_doi":"10.64898\/2026.03.06.708946","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.708946","rel_abs":"Chromatin organization underlies essential genome functions, but its nanoscale organization remains challenging to capture and quantify with precision. Atomic force microscopy (AFM) offers direct structural readouts of DNA and chromatin, yet translating these rich images into reproducible biological metrics has been limited by the lack of standardized, scalable analysis tools. Here we present DNAsight, an automated analysis framework that integrates machine learning (ML)-based segmentation with modular, base-pair-calibrated quantification of DNA spatial organization, looping, nucleosome spacing, and protein clustering. Applied across diverse chromatin-associated proteins, DNAsight reveals protein-specific organizational signatures, including topology-dependent compaction by integration host factor (IHF), cofactor-mediated cohesin loop stabilization by precocious dissociation of sisters 5A (PDS5A), and promoter-driven multimerization of GAGA factor (GAF) clusters. The framework further enables direct extraction of nucleosome spacing distributions from raw AFM images, providing a label-free route to investigate chromatin fiber architecture. Together, these advances establish DNAsight as a generalizable and scalable approach for converting AFM measurements into quantitative insights into the physical principles of chromatin organization.","rel_num_authors":23,"rel_authors":[{"author_name":"Emily Winther S\u00f8rensen","author_inst":"University of Copenhagen"},{"author_name":"Sushil Pangeni","author_inst":"Boston Childrens Hospital"},{"author_name":"Raquel Merino-Urteaga","author_inst":"Boston Children's Hospital"},{"author_name":"Peter J. Murray","author_inst":"Boston Children's Hospital"},{"author_name":"Sergei Rudnizky","author_inst":"Boston Children's Hospital"},{"author_name":"Ting-Wei Liao","author_inst":"Boston Children's Hospital"},{"author_name":"Fahad Rashid","author_inst":"John Hopkins University"},{"author_name":"Jihee Hwang","author_inst":"Boston Children's Hospital"},{"author_name":"Maryam Yamadi","author_inst":"John Hopkins University"},{"author_name":"Xinyu A. Feng","author_inst":"John Hopkins University"},{"author_name":"Jonas Z\u00e4hringer","author_inst":"Boston Children's Hospital"},{"author_name":"Stephanie Gu","author_inst":"Boston Children's Hospital"},{"author_name":"Iain F. Davidson","author_inst":"Vienna BioCenter"},{"author_name":"Laura Caccianini","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Manuel Osorio-Valeriano","author_inst":"Harvard Medical School"},{"author_name":"Lucas Farnung","author_inst":"Harvard Medical School"},{"author_name":"Seychelle Vos","author_inst":"Massachusetts Institute of Technology"},{"author_name":"Jan-Michael Peters","author_inst":"Vienna BioCenter"},{"author_name":"James M. Berger","author_inst":"Johns Hopkins School of Medicine"},{"author_name":"Carl Wu","author_inst":"Johns Hopkins University"},{"author_name":"Nikos S. Hatzakis","author_inst":"University of Copenhagen"},{"author_name":"Julius Bier Kirkegaard","author_inst":"University of Copenhagen"},{"author_name":"Taekjip Ha","author_inst":"Boston Children's Hospital"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"An Optimized RNF126-Targeting Covalent Handle for Molecular Glue Degraders","rel_doi":"10.64898\/2026.03.06.709959","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.06.709959","rel_abs":"Molecular glue degraders represent a powerful modality for targeting proteins that are refractory to traditional inhibition. However, rational design principles for molecular glue degraders remain poorly defined. Previously, we reported a chemistry-centric strategy to identify covalent degradative handles that, when appended to established ligands, convert non-degradative inhibitors into molecular glue degraders by engaging permissive E3 ligases. This effort identified a fumarate-based electrophilic handle that covalently modified the E3 ligase RNF126, enabling degradation of multiple protein targets when transplanted across diverse ligands. Despite its conceptual impact, the high intrinsic reactivity and cytotoxicity of the fumarate handle limited its translational utility. Here, we report the development of an optimized and metabolically stabilized RNF126-targeting covalent handle incorporating a trans-cyclobutane linker that exhibits reduced glutathione reactivity and diminished cytotoxicity while retaining robust degradative activity. When appended to the BET bromodomain inhibitor JQ1, this optimized handle yielded a potent and selective BRD4 degrader whose activity was dependent on RNF126. Importantly, transplantation of this handle onto a previously non-inhibitory ligand targeting the androgen receptor (AR) and its truncation variant, AR-V7, enabled selective degradation of both AR and AR-V7 in androgen-independent prostate cancer cells, thereby robustly inhibiting AR transcriptional activity beyond the established AR antagonist enzalutamide. Collectively, these findings demonstrate an optimized RNF126-based covalent handle for the rational development of molecular glue degraders against transcriptional regulators, including undruggable variants such as AR-V7.","rel_num_authors":10,"rel_authors":[{"author_name":"Aman Modi","author_inst":"University of California, Berkeley"},{"author_name":"Ethan S Toriki","author_inst":"University of California, Berkeley"},{"author_name":"Christian E Stieger","author_inst":"University of California, Berkeley"},{"author_name":"Emily A Lau","author_inst":"University of California, Berkeley"},{"author_name":"Claire Song","author_inst":"University of California, Berkeley"},{"author_name":"Alyssa Chew","author_inst":"University of California, Berkeley"},{"author_name":"Amy Tsao","author_inst":"University of California, Berkeley"},{"author_name":"Kaila Nishikawa","author_inst":"University of California, Berkeley"},{"author_name":"Jeffrey McKenna","author_inst":"Novartis"},{"author_name":"Daniel K Nomura","author_inst":"University of California, Berkeley"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"ENS lineage potential is not intrinsically regionalized but is modulated by PTPRZ1 signaling","rel_doi":"10.64898\/2026.03.05.709942","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709942","rel_abs":"The enteric nervous system (ENS) orchestrates critical gastrointestinal functions including peristalsis, fluid exchange, and blood flow regulation, and develops from vagal neural crest (vNC) progenitors that colonize the gut. While the gut epithelium and mesenchyme exhibit pronounced anterior-posterior (A-P) transcriptional patterning and lineage diversification after mid-gestation, whether the ENS itself undergoes comparable regional embryonic transcriptional diversification has remained unclear. Here, we use multiplexed single-cell RNA sequencing and functional perturbations to dissect how the ENS is patterned between E13.5 and E18.5 within the context of a regionally specialized gut. We find that, while the epithelium and mesenchyme display strong and enduring AP-graded gene expression programs, the ENS lacks intrinsic regionalization and instead follows a predominantly temporal maturation trajectory characterized by neuronal and glial differentiation states. Integrative ligand-receptor analyses reveal that mesenchymal populations express A-P patterned microenvironmental cues that correlate with subtle, region-linked transcriptional tuning in ENS cells, despite the absence of intrinsic A-P identities. Among these signals, PTN\/MDK-PTPRZ1 signaling emerges as a major spatial and temporal input to the ENS, with gradients that track both small intestinal region and developmental time. To test the relevance of PTPRZ1 signaling for human ENS development, we perturbed pluripotent stem cell-derived ENS cultures and found that modulating PTPRZ1 signaling impacts proliferative, neurogenic, and neurotransmitter-specification programs, confirming that niche-derived cues fine-tune ENS development. Together, our findings support a model in which the small intestine establishes A-P regionalization through epithelial and mesenchymal patterning, whereas the ENS maintains a relatively uniform core neuroglial program that is secondarily refined by localized microenvironmental signals. This framework highlights how extrinsic, region-specific cues, rather than intrinsic regional transcriptional codes, shape ENS maturation within the small intestine.","rel_num_authors":4,"rel_authors":[{"author_name":"Ali Kalantari","author_inst":"UCSF"},{"author_name":"Ophir Klein","author_inst":"Cedars-Sinai"},{"author_name":"Zev Jordan Gartner","author_inst":"UCSF"},{"author_name":"Faranak Fattahi","author_inst":"UCSF"}],"rel_date":"2026-03-07","rel_site":"biorxiv"},{"rel_title":"Population differences in wearable device wear time: Rescuing data to address biases and advance health equity","rel_doi":"10.64898\/2026.03.06.26347799","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.06.26347799","rel_abs":"Wearable devices present transformative opportunities for personalized healthcare through continuous monitoring of digital biomarkers; however, individual variations in device wear time could mask or otherwise impact signal identification. Despite the widespread adoption of wearable devices in research, no comprehensive framework exists for understanding how wear time varies across populations or for addressing wear time-related biases in analysis. Using Fitbit data from 11,901 participants in the All of Us Research Program, we conducted the first large-scale systematic assessment of wearable device wear time across demographics, social determinants of health, lifestyle factors, mental health symptoms, and disease. Our findings revealed that wear time was higher among males and increased with age, income, and education, but decreased with depressive, anxiety, and anhedonia symptoms, with reductions more pronounced following clinical diagnoses compared to symptom-based classifications. Individuals with chronic conditions displayed differential levels of wear time compared to healthy controls. Critically, we demonstrate that the widely used [&ge;]10-hour daily compliance threshold, while appropriate for some research contexts, can disproportionately exclude days of data from disease populations: among individuals with major depressive disorder, 74.4% of data days were excluded compared to 20.9% for controls. We propose a flexible methodological framework including standard compliance thresholds, wear time covariate adjustment, metric normalization, propensity score matching, and adaptive thresholds that can be applied individually or in combination to optimize wearable data retention across diverse research contexts. These findings establish wear time as a critical methodological consideration for wearable device research and provide guidance for advancing equitable and rigorous digital health analytics.","rel_num_authors":8,"rel_authors":[{"author_name":"Eric Hurwitz","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Evan Connelly","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Miriam Sklerov","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Hiral Master","author_inst":"University of North Carolina at Chapel Hill"},{"author_name":"Harry Hochheiser","author_inst":"University of Pittsburgh"},{"author_name":"Zachary Butzin-Dozier","author_inst":"UC Berkeley School of Public Health"},{"author_name":"Jessilyn Dunn","author_inst":"Duke University"},{"author_name":"Melissa A Haendel","author_inst":"University of North Carolina at Chapel Hill"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Deep untargeted wastewater metagenomic sequencing from sewersheds across the United States","rel_doi":"10.64898\/2026.03.05.26345726","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26345726","rel_abs":"Wastewater monitoring enables non-invasive, population-scale tracking of community infections independent of healthcare-seeking behavior and clinical diagnosis. Metagenomic sequencing extends this capability by enabling broad, pathogen-agnostic detection, genomic characterization, and identification of novel or unexpected threats. Here, we present data from CASPER (the Coalition for Agnostic Sequencing of Pathogens from Environmental Reservoirs), a U.S.-based wastewater metagenomic sequencing network designed for deep, untargeted pathogen monitoring at national scale. This release includes 1,206 samples collected between December 2023 and December 2025 from 27 sites across nine states, covering 13 million people. Deep sequencing (~1 billion read pairs per sample) generated 1.2 trillion read pairs (347 terabases), enabling detection of even rare taxa, with CASPER representing 66% of all untargeted wastewater sequencing data currently available on the NCBI Sequence Read Archive. Virus abundance trends correlate with nationwide wastewater PCR and clinical data for SARS-CoV-2, influenza A, and respiratory syncytial virus, while the pathogen-agnostic approach captures emerging threats, including avian influenza H5N1 during initial dairy cattle outbreaks, West Nile virus, and measles, among hundreds of viral taxa. As the largest publicly available untargeted wastewater sequencing dataset to date, CASPER provides a shared and growing resource for pathogen surveillance and microbial ecology.","rel_num_authors":55,"rel_authors":[{"author_name":"Lennart J. Justen","author_inst":"Massachusetts Institute of Technology, Media Lab, Cambridge, MA, USA; The Charles Stark Draper Laboratory, Inc., Draper Scholar, Cambridge, MA, USA; Broad Insti"},{"author_name":"Clayton Rushford","author_inst":"University of Missouri, Department of Veterinary Pathobiology, Columbia, MO, USA"},{"author_name":"Olivia S. Hershey","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Roisin Floyd-O'Sullivan","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Simon L. Grimm","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"William J. Bradshaw","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Harmon Bhasin","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Daniel P. Rice","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Katherine Stansifer","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Jo D. Faraguna","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Michael R. McLaren","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Alessandro Zulli","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Alejandro Tovar-Mendez","author_inst":"University of Missouri, Department of Molecular Microbiology and Immunology, Columbia, MO, USA"},{"author_name":"Emma Copen","author_inst":"University of Missouri, Department of Molecular Microbiology and Immunology, Columbia, MO, USA"},{"author_name":"Kristen K. Shelton","author_inst":"University of Oklahoma, School of Civil Engineering and Environmental Science, Norman, OK, USA"},{"author_name":"Ayaaz Amirali","author_inst":"University of Miami, Department of Chemical, Environmental, and Materials Engineering, Miami, FL, USA"},{"author_name":"Sherin Kannoly","author_inst":"Queens College of The City University of New York, Biology Department, Flushing, NY, USA"},{"author_name":"Sofia Pesantez","author_inst":"Queens College of The City University of New York, Biology Department, Flushing, NY, USA"},{"author_name":"Aiden Stanciu","author_inst":"Queens College of The City University of New York, Biology Department, Flushing, NY, USA"},{"author_name":"Inigo Caballero Quiroga","author_inst":"Queens College of The City University of New York, Biology Department, Flushing, NY, USA"},{"author_name":"Leopolda Silvera","author_inst":"NYC Health + Hospitals, New York, NY, USA"},{"author_name":"Nicole Greenwood","author_inst":"Riverside Water Quality Control Plant, Riverside, CA, USA"},{"author_name":"Barbra Bongiovi","author_inst":"City of Boise, Boise, ID, USA"},{"author_name":"Austin Walkins","author_inst":"City of Boise, Boise, ID, USA"},{"author_name":"Ryan Love","author_inst":"Inland Empire Utilities Agency, Chino, CA, USA"},{"author_name":"Scott Lening","author_inst":"Inland Empire Utilities Agency, Chino, CA, USA"},{"author_name":"Kaylyn Patterson","author_inst":"Metropolitan Water Reclamation District of Greater Chicago, Chicago, IL, USA"},{"author_name":"Theresa Johnston","author_inst":"Metropolitan Water Reclamation District of Greater Chicago, Chicago, IL, USA"},{"author_name":"Sandra Hernandez","author_inst":"Miami-Dade Water and Sewer Department, Miami, FL, USA"},{"author_name":"Aymara Benitez","author_inst":"Miami-Dade Water and Sewer Department, Miami, FL, USA"},{"author_name":"Billie Jo McCarley","author_inst":"Miami-Dade Water and Sewer Department, Miami, FL, USA"},{"author_name":"Samantha Engelage","author_inst":"City of Palo Alto, Palo Alto, CA, USA"},{"author_name":"Suguna Pillay","author_inst":"City of Palo Alto, Palo Alto, CA, USA"},{"author_name":"Cindy Calender","author_inst":"City of Kansas City Missouri, KC Health, Communicable Disease and Prevention Division, Kansas City, MO"},{"author_name":"Brent Herring","author_inst":"City of Kansas City Missouri, KC Water, Water and Wastewater Operations, Kansas City, MO"},{"author_name":"Carey Robinson","author_inst":"City of Kansas City Missouri, KC Water, Wastewater Treatment Division, Kansas City, MO"},{"author_name":"- Monett Wastewater Treatment Plant","author_inst":"-"},{"author_name":"- Columbia Missouri Wastewater Treatment Plant","author_inst":"-"},{"author_name":"Daniel Cunningham-Bryant","author_inst":"The Charles Stark Draper Laboratory, Inc., Cambridge, MA, USA"},{"author_name":"Gordon Adams","author_inst":"Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts General Hospital, Division of Infectious Diseases, Boston, MA, USA"},{"author_name":"Jillian Paull","author_inst":"Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA"},{"author_name":"Jamie Devlin","author_inst":"Massachusetts General Hospital, Division of Infectious Diseases, Boston, MA, USA"},{"author_name":"Vamsi Thiriveedhi","author_inst":"Massachusetts General Hospital, Department of Pathology, Boston, MA, USA"},{"author_name":"Sarah E. Turbett","author_inst":"Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Department of Pathology, Boston, MA, USA; Massachusetts General Hospital, Division of I"},{"author_name":"Jacob E. Lemieux","author_inst":"Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Medical School, Boston, MA, USA; Massachusetts General Hospital, Division of Infectious Diseases"},{"author_name":"Rose S. Kantor","author_inst":"Lawrence Livermore National Laboratory, Physical and Life Sciences Directorate, Livermore, CA, USA"},{"author_name":"David H. O'Connor","author_inst":"University of Wisconsin-Madison, Department of Pathology and Laboratory Medicine, Madison, WI, USA"},{"author_name":"John J. Dennehy","author_inst":"Queens College of The City University of New York, Biology Department, Flushing, NY, USA; The Graduate Center of The City University of New York, New York, NY, "},{"author_name":"Rachel Poretsky","author_inst":"University of Illinois Chicago, Department of Biological Sciences, Chicago, IL, USA"},{"author_name":"Jason A. Rothman","author_inst":"University of California, Riverside, Department of Microbiology and Plant Pathology, Riverside, CA, USA"},{"author_name":"Helena M. Solo-Gabriele","author_inst":"University of Miami, Department of Chemical, Environmental, and Materials  Engineering, Miami, FL, USA"},{"author_name":"Jason R. Vogel","author_inst":"University of Oklahoma, School of Civil Engineering and Environmental Science, Norman, OK, USA"},{"author_name":"Pardis C. Sabeti","author_inst":"Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard University, Harvard T.H. Chan School of Public Health, Department of Immunology and Infectious D"},{"author_name":"Jeff Kaufman","author_inst":"SecureBio, Cambridge, MA, USA"},{"author_name":"Marc Johnson","author_inst":"University of Missouri, Department of Molecular Microbiology and Immunology, Columbia, MO, USA"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Sex-stratified Integrated Analysis of US lung Cancer Mortality, 1994-2020","rel_doi":"10.64898\/2026.03.01.26347234","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.01.26347234","rel_abs":"Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environmental, socioeconomic, and therapeutic factors and their sex specific contributions remains unclear. Understanding these drivers is essential to sustain progress and reduce persistent disparities. Objective: To quantify how behavioral, environmental, socioeconomic, and therapeutic determinants collectively shaped US lung cancer mortality from 1994 to 2020, assess sex specific differences, and forecast mortality trajectories through 2030 using an integrated machine learning framework. Design, Setting, and Participants: Ecological time series study using publicly available national data from 1994 to 2020. Sex stratified analyses were conducted integrating lung cancer mortality, smoking prevalence, fine particulate matter PM2.5 exposure, Human Development Index HDI, per capita healthcare expenditure, healthcare inflation, insurance coverage, income inequality, and annual drug approvals. Exposures: Behavioral smoking, environmental PM2.5, socioeconomic HDI health expenditure inflation, uninsurance inequality, and therapeutic drug approval indicators. Main Outcomes and Measures: Age-standardized lung cancer mortality per 100000 population. Temporal changes were modeled using Joinpoint regression. Concurrent associations were assessed using multivariable and elastic net regression, and forecasts were estimated with AutoRegressive Integrated Moving Average models with exogenous variables ARIMAX. Results: From 1994 to 2020, mortality declined by 59 percent in men, from 52.9 to 21.7 per 100000, and by 40 percent in women, from 26.7 to 15.9 per 100000, with faster declines after 2015. Smoking and PM2.5 decreased by more than 45 percent but remained strongly correlated with mortality. In elastic net models, PM2.5 was the strongest predictor for men, while smoking was the strongest predictor for women. Per capita expenditure and HDI ranked higher for men, while uninsurance and income inequality were strong predictors for women. Mortality declines occurred during periods of major approvals of lung cancer drugs. Forecasts suggest continued but slower declines through 2030, with projected rates of 20.2 and 14.9 deaths per 100000 in men and women, respectively. Conclusions and Relevance: Sex specific declines in lung cancer mortality reflect different dominant correlates, with air pollution more important in men and smoking more important in women, while socioeconomic conditions and therapeutic advances also influence trends. Continued tobacco control, improved air quality, and equitable access to screening and modern treatment are essential to sustain further reductions in mortality. Keywords: Lung Neoplasms, Sex Factors, Air Pollution, Smoking, Socioeconomic Factors, Machine Learning","rel_num_authors":9,"rel_authors":[{"author_name":"Muhammad Rafiqul Islam","author_inst":"National institute of Cancer Research and Hospital, Bangladesh"},{"author_name":"Sama I Sayin","author_inst":"Sahlgrenska University Hospital, Gothenburg, Sweden"},{"author_name":"Humayera Islam","author_inst":"The University of Chicago,USA"},{"author_name":"Mohammad Hasan Shahriar","author_inst":"The University of Chicago, USA"},{"author_name":"Muhammad Ashique H Chowdhury","author_inst":"The University of Chicago, USA"},{"author_name":"Siara Tasmin","author_inst":"The University of Chicago,  USA"},{"author_name":"Sreenivas Konda","author_inst":"The University of Chicago, USA"},{"author_name":"Syeda Masuma Siddiqua","author_inst":"Unity through population, Bangladesh"},{"author_name":"Habibul Ahsan","author_inst":"The University of Chicago, USA"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Shared multicellular injury programs of acute and chronic kidney disease enable mechanistic patient stratification","rel_doi":"10.64898\/2026.03.05.26347522","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347522","rel_abs":"Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.","rel_num_authors":49,"rel_authors":[{"author_name":"Robin Fallegger","author_inst":"Heidelberg University"},{"author_name":"Sergio A. Gomez-Ochoa","author_inst":"Heidelberg University Hospital, Department of General Internal Medicine and Psychosomatics, Heidelberg, Germany"},{"author_name":"Charlotte Boys","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Ricardo Omar Ramirez Flores","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K."},{"author_name":"Jovan Tanevski","author_inst":"Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Heidelberg, Germany"},{"author_name":"Evanthia Pashos","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Denis Feliers","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Mary Piper","author_inst":"Internal Medicine Research Unit, Pfizer Inc., Cambridge, MA, United States"},{"author_name":"Jennifer A. Schaub","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Zixiang Zhou","author_inst":"Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton"},{"author_name":"Weiguang Mao","author_inst":"Princeton Precision Health, Princeton University, Princeton, NJ 08544, USA"},{"author_name":"Xi Chen","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA; Lewis-Sigler Institute of Integrative Genomics, Princeton Univ"},{"author_name":"Rachel S. G. Sealfon","author_inst":"Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY 10010, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton Unive"},{"author_name":"Rajasree Menon","author_inst":"Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Viji Nair","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Sean Eddy","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Fadhl M Alakwaa","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA"},{"author_name":"Laura Pyle","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Ye Ji Choi","author_inst":"University of Washington Medicine Diabetes Institute, Seattle, WA 98109, USA"},{"author_name":"Petter Bjornstad","author_inst":"University of Washington Medicine Diabetes Institute and Seattle Children's Research Institute, Seattle, WA 98109, USA"},{"author_name":"Charles E. Alpers","author_inst":"Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195"},{"author_name":"Markus Bitzer","author_inst":"University of Michigan"},{"author_name":"Andrew S. Bomback","author_inst":"Division of Nephrology, Columbia University Irving Medical Center, New York, NY, USA"},{"author_name":"M. Luiza Caramori","author_inst":"Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, OH, USA; Department of Internal Medicine, Division of Diabetes, Endocrinolog"},{"author_name":"Dawit Demeke","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Agnes B. Fogo","author_inst":"Dept. Of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA"},{"author_name":"Leal C. Herlitz","author_inst":"Cleveland Clinic"},{"author_name":"Krzysztof Kiryluk","author_inst":"Department of Medicine, Division of Nephrology, Vagelos College of Physicians & Surgeons, Columbia University"},{"author_name":"James P. Lash","author_inst":"Department of Medicine, University of Illinois Chicago, Chicago, Illinois"},{"author_name":"Raghavan Murugan","author_inst":"University of Pittsburgh"},{"author_name":"John F. O'Toole","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Paul M. Palevsky","author_inst":"Renal-Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA"},{"author_name":"Chirag R. Parikh","author_inst":"Department of Medicine, Johns Hopkins School of Medicine, Baltimore, US"},{"author_name":"Sylvia E. Rosas","author_inst":"Kidney and Hypertension Unit, Joslin Diabetes Center and Harvard Medical School, Boston, MA 02215, USA"},{"author_name":"Avi Z Rosenberg","author_inst":"Department of Pathology, Johns Hopkins University School of Medicine Baltimore, MD, USA"},{"author_name":"John R. Sedor","author_inst":"Department of Kidney Medicine, Medical Specialties Institute, Cleveland Clinic & Department of Molecular Medicine, Case Western Reserve University School of Med"},{"author_name":"Miguel A. Vazquez","author_inst":"Nephrology Division, University of Texas Southwestern Medical Center"},{"author_name":"Sushrut S. Waikar","author_inst":"Section of Nephrology, Boston Medical Center and Boston University Chobanian & Avedisian School of Medicine"},{"author_name":"F. Perry Wilson","author_inst":"Clinical and Translational Research Accelerator, Department of Medicine, Yale School of Medicine, New Haven, CT"},{"author_name":"Jeffrey B. Hodgin","author_inst":"Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA"},{"author_name":"Laura Barisoni","author_inst":"Department of Pathology, Division of AI & Computational Pathology, Department of Medicine, Division of Nephrology, Duke University, Durham, NC, USA"},{"author_name":"Jonathan Himmelfarb","author_inst":"Barbara T. Murphy Division of Nephrology, Samuel Bronfman Department of Medicine, Icahn School of Medicine at Mount Sinai"},{"author_name":"Sanjay Jain","author_inst":"Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA;Department of Pathology and Immunology, Washi"},{"author_name":"Wenjun Ju","author_inst":"Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Olga G. Troyanskaya","author_inst":"Department of Computer Science, Princeton University, Princeton, NJ 08544, USA;Lewis-Sigler Institute of Integrative Genomics, Princeton University, Princeton, "},{"author_name":"- Kidney Precision Medicine Project","author_inst":""},{"author_name":"Matthias Kretzler","author_inst":"Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, MI 48109, USA;Department of Computational Medicine and Bioinformatic"},{"author_name":"Michael T. Eadon","author_inst":"Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA."},{"author_name":"Julio Saez-Rodriguez","author_inst":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, U.K.;Heidelberg University, Faculty of Medicine, a"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"An E-value-Informed Sensitivity Analysis Framework for Hybrid Controlled Trials","rel_doi":"10.64898\/2026.03.05.26347653","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347653","rel_abs":"Hybrid controlled trials (HCTs) incorporate real-world data into randomized controlled trials (RCTs) by augmenting the internal control arm with patients receiving the same treatment in routine care. Beyond increasing power, HCTs may improve recruitment by supporting unequal randomization ratios that increase patient access to experimental treatments. However, HCT validity is threatened by bias from unmeasured confounding due to lack of randomization of external controls, leading to outcome non-exchangeability between internal and external control patients. To address this challenge, we developed a sensitivity analysis framework to assess the robustness of HCT results to potential unmeasured confounding. We propose a tipping point analysis that adapts the E-value framework to the HCT setting where trial participation rather than treatment assignment is subject to confounding. To aid interpretation, we also introduce a data-driven benchmark representing the strength of unmeasured confounding reflected by the observed outcome non-exchangeability. We then propose an operational decision rule and evaluate its performance through simulation studies. Finally, we illustrate the approach using an asthma trial augmented by data from electronic health records. Simulation results demonstrate that our decision rule safeguards against Type I error inflation while preserving the power gains achieved by incorporating external data. In settings where moderate unmeasured confounding led to poorer outcomes for external controls, Type I error was controlled near the nominal 5% level, and power increased by 10-20% compared with analyses using RCT data alone. Our approach provides a practical, interpretable method to assess HCT robustness, supporting rigorous inference when integrating external real-world data.","rel_num_authors":6,"rel_authors":[{"author_name":"Chunnan Liu","author_inst":"Department of Biostatistics, School of Public Health, Brown University"},{"author_name":"Melanie Mayer","author_inst":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania"},{"author_name":"Kimberly Lactaoen","author_inst":"Palliative and Advanced Illness (PAIR) Center, University of Pennsylvania"},{"author_name":"Lizbeth Gomez","author_inst":"Rutgers University Center for Climate, Health, and Healthcare"},{"author_name":"Gary Weissman","author_inst":"Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania"},{"author_name":"Rebecca Hubbard","author_inst":"Department of Biostatistics, School of Public Health, Brown University"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"An E-value-Informed Sensitivity Analysis Framework for Hybrid Controlled Trials","rel_doi":"10.64898\/2026.03.05.26347653","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347653","rel_abs":"Hybrid controlled trials (HCTs) incorporate real-world data into randomized controlled trials (RCTs) by augmenting the internal control arm with patients receiving the same treatment in routine care. Beyond increasing power, HCTs may improve recruitment by supporting unequal randomization ratios that increase patient access to experimental treatments. However, HCT validity is threatened by bias from unmeasured confounding due to lack of randomization of external controls, leading to outcome non-exchangeability between internal and external control patients. To address this challenge, we developed a sensitivity analysis framework to assess the robustness of HCT results to potential unmeasured confounding. We propose a tipping point analysis that adapts the E-value framework to the HCT setting where trial participation rather than treatment assignment is subject to confounding. To aid interpretation, we also introduce a data-driven benchmark representing the strength of unmeasured confounding reflected by the observed outcome non-exchangeability. We then propose an operational decision rule and evaluate its performance through simulation studies. Finally, we illustrate the approach using an asthma trial augmented by data from electronic health records. Simulation results demonstrate that our decision rule safeguards against Type I error inflation while preserving the power gains achieved by incorporating external data. In settings where moderate unmeasured confounding led to poorer outcomes for external controls, Type I error was controlled near the nominal 5% level, and power increased by 10-20% compared with analyses using RCT data alone. Our approach provides a practical, interpretable method to assess HCT robustness, supporting rigorous inference when integrating external real-world data.","rel_num_authors":6,"rel_authors":[{"author_name":"Chunnan Liu","author_inst":"Department of Biostatistics, School of Public Health, Brown University"},{"author_name":"Melanie Mayer","author_inst":"Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania"},{"author_name":"Kimberly Lactaoen","author_inst":"Palliative and Advanced Illness (PAIR) Center, University of Pennsylvania"},{"author_name":"Lizbeth Gomez","author_inst":"Rutgers University Center for Climate, Health, and Healthcare"},{"author_name":"Gary Weissman","author_inst":"Division of Pulmonary, Allergy and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania"},{"author_name":"Rebecca Hubbard","author_inst":"Department of Biostatistics, School of Public Health, Brown University"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Human RIG-I Antiviral Deficiency Caused by a Dominant-Negative Variant Locked in a Signaling-Inactive State","rel_doi":"10.64898\/2026.03.02.26347088","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347088","rel_abs":"RIG-I is a cytosolic immune receptor that provides the first line of defense by detecting viral RNA and triggering antiviral responses. Its physiological role in humans remains unclear, as no patients with complete RIG-I deficiency have yet been reported. We identified a critically ill COVID-19 patient with severe RIG-I deficiency caused by heterozygous RIG-I G731R, a novel dominant loss-of-function variant. The G731R mutation in helicase motif VI disrupts the arginine finger, impairing the ATPase activity of RIG-I, but not its RNA-binding ability. However, viral RNA binding fails to expose the signaling domains, thereby impairing the IFN-{beta} response of G731R. Instead, G731R competes with wild-type RIG-I, exerting a dominant negative effect. The loss-of-function is caused by bulky-charged substitutions at G731, as alanine or leucine substitution results in an unexpected gain-of-function phenotype. These findings highlight the importance of uncompromised RIG-I function for human antiviral immunity and the pleiotropic effects of single mutations.","rel_num_authors":20,"rel_authors":[{"author_name":"Mihai Solotchi","author_inst":"Robert Wood Johnson Medical School, Rutgers University"},{"author_name":"Huie Jing","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Emma Gebauer","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Scott J Novick","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Bruce D Pascal","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Wesley Tung","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Pranita Hanpude","author_inst":"Robert Wood Johnson Medical School, Rutgers University"},{"author_name":"Yu Zhang","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Camille Alba","author_inst":"The American Genome Center, Center for Military Precision Health"},{"author_name":"Annalisa Saracino","author_inst":"University of Bari Aldo Moro"},{"author_name":"Paola Laghetti","author_inst":"University of Bari Aldo Moro"},{"author_name":"Elana R Shaw","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Lindsey B Rosen","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Steven M Holland","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Andrea Lisco","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Clifton L Dalgard","author_inst":"Uniformed Services University of the Health Sciences"},{"author_name":"Joseph Marcotrigiano","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Patrick R Griffin","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Helen C Su","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Smita S Patel","author_inst":"Robert Wood Johnson Medical School, Rutgers University"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Human RIG-I Antiviral Deficiency Caused by a Dominant-Negative Variant Locked in a Signaling-Inactive State","rel_doi":"10.64898\/2026.03.02.26347088","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347088","rel_abs":"RIG-I is a cytosolic immune receptor that provides the first line of defense by detecting viral RNA and triggering antiviral responses. Its physiological role in humans remains unclear, as no patients with complete RIG-I deficiency have yet been reported. We identified a critically ill COVID-19 patient with severe RIG-I deficiency caused by heterozygous RIG-I G731R, a novel dominant loss-of-function variant. The G731R mutation in helicase motif VI disrupts the arginine finger, impairing the ATPase activity of RIG-I, but not its RNA-binding ability. However, viral RNA binding fails to expose the signaling domains, thereby impairing the IFN-{beta} response of G731R. Instead, G731R competes with wild-type RIG-I, exerting a dominant negative effect. The loss-of-function is caused by bulky-charged substitutions at G731, as alanine or leucine substitution results in an unexpected gain-of-function phenotype. These findings highlight the importance of uncompromised RIG-I function for human antiviral immunity and the pleiotropic effects of single mutations.","rel_num_authors":20,"rel_authors":[{"author_name":"Mihai Solotchi","author_inst":"Robert Wood Johnson Medical School, Rutgers University"},{"author_name":"Huie Jing","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Emma Gebauer","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Scott J Novick","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Bruce D Pascal","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Wesley Tung","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Pranita Hanpude","author_inst":"Robert Wood Johnson Medical School, Rutgers University"},{"author_name":"Yu Zhang","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Camille Alba","author_inst":"The American Genome Center, Center for Military Precision Health"},{"author_name":"Annalisa Saracino","author_inst":"University of Bari Aldo Moro"},{"author_name":"Paola Laghetti","author_inst":"University of Bari Aldo Moro"},{"author_name":"Elana R Shaw","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Lindsey B Rosen","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Steven M Holland","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Andrea Lisco","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Clifton L Dalgard","author_inst":"Uniformed Services University of the Health Sciences"},{"author_name":"Joseph Marcotrigiano","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Patrick R Griffin","author_inst":"The Wertheim UF Scripps Institute"},{"author_name":"Helen C Su","author_inst":"National Institute of Allergy and Infectious Diseases, National Institutes of Health"},{"author_name":"Smita S Patel","author_inst":"Robert Wood Johnson Medical School, Rutgers University"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Gene Portals: A Framework for Integrating Clinical, Functional, and Structural Evidence into Rare Disease Variant Classification","rel_doi":"10.64898\/2026.03.05.26347086","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347086","rel_abs":"Rare Mendelian disorders affect 300-400 million people globally. Although genetic testing has become widely adopted, gene-specific evidence for tailored variant interpretation remains scattered across resources. We present Gene Portals, a framework for gene-centered multimodal knowledge bases that co-localize expert-harmonized clinical data, functional assays, population variation, structural annotations and gene-specific ACMG\/AMP specifications within a single resource. A modular interface integrates this unified evidence with VCEP-refined ACMG specifications to enable automated gene-specific variant classification, infer molecular mechanisms, and support cross-gene analyses. We demonstrate the framework's utility across five Gene portals spanning eleven neurodevelopmental disorder-associated genes, integrating data from 4,423 individuals with 2,838 unique variants, 36,149 ClinVar submissions, and 1,044 expert-curated molecular readouts. By organizing evidence that is otherwise dispersed across multiple sources into a unified, queryable framework, the SCN, GRIN, CACNA1A, SATB2 and SLC6A1 Gene Portals became widely used community resources and provide an extensible template for standardized rare-disease variant interpretation and mechanism-aware discovery.","rel_num_authors":93,"rel_authors":[{"author_name":"Tobias Br\u00fcnger","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Ilona Krey","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Suyeon Kim","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Chiara Kl\u00f6ckner","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Scott J. A. Myers","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Katrine M. Johannesen","author_inst":"Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, Dianalund, Denmark."},{"author_name":"Arthur Stefanski","author_inst":"Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA."},{"author_name":"Gary Taylor","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Eduardo Perez-Palma","author_inst":"Universidad del Desarrollo, Centro de Gen\u00e9tica y Gen\u00f3mica, Instituto de Ciencias e Innovaci\u00f3n en Medicina, Facultad de Medicina Cl\u00ednica Alemana, Santiago de Chi"},{"author_name":"Marie Macnee","author_inst":"Cologne Center for Genomics (CCG), University of Cologne, Cologne, 50931, Germany."},{"author_name":"Stephanie Schorge","author_inst":"Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK."},{"author_name":"Rebekka S. Dahl","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Hongjie Yuan","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Riley E. Perszyk","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Sukhan Kim","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Sunanjay Bajaj","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Ingo Helbig","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Jen Q. Pan","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Mark Farrant","author_inst":"Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK."},{"author_name":"Lonnie Wollmuth","author_inst":"Department of Neurobiology & Behavior and Biochemistry & Cell Biology, Center for Nervous System Disorders, Stony Brook University, Stony Brook, NY, USA."},{"author_name":"David J. A. Wyllie","author_inst":"Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK."},{"author_name":"Erkin Kurganov","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"David Baez","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Sameer Zuberi","author_inst":"School of Health and Wellbeing and Royal Hospital for Children University of Glasgow, Glasgow, UK."},{"author_name":"Christian M. Bo\u00dfelmann","author_inst":"Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of T\u00fcbingen, 72076, T\u00fcbingen, Germany."},{"author_name":"Holger Lerche","author_inst":"Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of T\u00fcbingen, 72076, T\u00fcbingen, Germany."},{"author_name":"Massimo Mantegazza","author_inst":"Universit\u00e9 C\u00f4te D'Azur, CNRS UMR7275, Inserm U1323, Institute of Molecular and Cellular Pharmacology, Valbonne - Sophia Antipolis, France."},{"author_name":"Sandrine Cest\u00e8le","author_inst":"Universit\u00e9 C\u00f4te D'Azur, CNRS UMR7275, Inserm U1323, Institute of Molecular and Cellular Pharmacology, Valbonne - Sophia Antipolis, France."},{"author_name":"Patrick May","author_inst":"Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg."},{"author_name":"Alina Ivaniuk","author_inst":"Department of Neurology, Mayo Clinic in Florida, Jacksonville, Fl, 32224, USA."},{"author_name":"Mary Anne Meskis","author_inst":"Dravet Syndrome Foundation, Cherry Hill, NJ, USA."},{"author_name":"Veronica Hood","author_inst":"Dravet Syndrome Foundation, Cherry Hill, NJ, USA."},{"author_name":"Leah Schust","author_inst":"FamilieSCN2A Foundation 501(c)(3), Gettysburg, PA, USA."},{"author_name":"Kimberly Goodspeed","author_inst":"Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA."},{"author_name":"Jing-Qiong Kang","author_inst":"Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA."},{"author_name":"Amber Freed","author_inst":"SLC6A1 Connect, 1939 Temperence Hill Drive, Frisco, TX 75034, USA."},{"author_name":"Cornelius Gati","author_inst":"Department of Biological Sciences, Bridge Institute, USC Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA 90089, U"},{"author_name":"Ludovica Montanucci","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Arthur Wuster","author_inst":"BioMarin Pharmaceutical Inc., Novato, CA, USA."},{"author_name":"Marena Trinidad","author_inst":"Innovative Genomics Institute, University of California, Berkeley, CA, USA, 94720"},{"author_name":"Steven Froelich","author_inst":"BioMarin Pharmaceutical Inc., Novato, CA, USA."},{"author_name":"Alexander T. Deng","author_inst":"NHS South East Genomic Medicine Service, Guy's and St Thomas's NHS Foundation Trust, London SE1 9RT, UK"},{"author_name":"\u00c1ngel Aledo-Serrano","author_inst":"Epilepsy Program, Neurology Department, Hospital Ruber Internacional, Madrid 28034, Spain."},{"author_name":"Artem Borovikov","author_inst":"Research and Counseling Department, Research Centre for Medical Genetics, Moscow 115478, Russia."},{"author_name":"Artem Sharkov","author_inst":"Veltischev Research and Clinical Institute for Pediatrics and Pediatric Surgery of the Pirogov Russian National Research Medical University, Russia."},{"author_name":"Arjan Bouman","author_inst":"Department of Clinical Genetics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, Rotterdam 3000 CA, the Netherlands"},{"author_name":"MJ Hajianpour","author_inst":"Department of Pediatrics, Division of Medical Genetics and Genomics, Albany Medical College, Albany Med Health System, Albany, NY 12208, USA."},{"author_name":"Deb K. Pal","author_inst":"Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London SE58AF, UK."},{"author_name":"Leslie Danvoye","author_inst":"Department of Neurology, Universit\u00e9 catholique de Louvain, Cliniques universitaires Saint-Luc, Brussels 1200, Belgium."},{"author_name":"Damien Lederer","author_inst":"Centre de G\u00e9n\u00e9tique Humaine, Institut de Pathologie et de G\u00e9n\u00e9tique, 6041 Charleroi, Belgium."},{"author_name":"Tugce R. Balci","author_inst":"Department of Pediatrics, Division of Medical Genetics, Western University, London, ON N6A3K7, Canada."},{"author_name":"Eveline E. O. Hagebeuk","author_inst":"Stichting Epilepsie Instellingen Nederland (SEIN), Department of Pediatric Neurology, Heemstede, The Netherlands."},{"author_name":"Alexis Heidlebaugh","author_inst":"Department of Developmental Medicine, Geisinger, Danville, PA 17837, USA"},{"author_name":"Kathryn Oetjens","author_inst":"Department of Developmental Medicine, Geisinger, Danville, PA 17837, USA"},{"author_name":"Trevor L. Hoffman","author_inst":"Department of Regional Genetics, Anaheim, Southern California Kaiser Permanente Medical Group, CA 92806, USA."},{"author_name":"Pasquale Striano","author_inst":"Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto Giannina Gaslini, Genoa 16147, Italy"},{"author_name":"Sarah Drewes Williams","author_inst":"Division of Genetic and Genomic Medicine, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA 15224, USA."},{"author_name":"Kalene van Engelen","author_inst":"Medical Genetics Program of Southwestern Ontario, London Health Sciences Centre, London, ON N6A5W9, Canada."},{"author_name":"Katherine Howell","author_inst":"Department of Neurology, Royal Children's Hospital, Melbourne, VIC 3052, Australia"},{"author_name":"Jean Khoury","author_inst":"Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA."},{"author_name":"Tim A. Benke","author_inst":"Department of Pediatrics, Neurology and Pharmacology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA."},{"author_name":"Vincent Strehlow","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Konrad Platzer","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Amy Ramsey","author_inst":"Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada."},{"author_name":"Lisa Manaster","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Sunitha Malepati","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Pangkong Fox","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Jeffrey Noebels","author_inst":"Blue Bird Circle Developmental Neurogenetics Laboratory, Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA."},{"author_name":"Wendy Chung","author_inst":"Department of Neurology, Harvard Medical School, Boston, MA, USA."},{"author_name":"Annapurna Poduri","author_inst":"Department of Neurology, Harvard Medical School, Boston, MA, USA."},{"author_name":"Laina Lusk Stripe","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Sarah M. Ruggiero","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Stacey Cohen","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Lacey Smith","author_inst":"Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA, USA."},{"author_name":"Sylvia Boesch","author_inst":"Center for rare Movement Disorders Innsbruck, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria"},{"author_name":"Olivia Wilmarth","author_inst":"Inova Health System, Falls Church, VA, USA"},{"author_name":"Anna Jenne Prentice","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Esther Cha","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Nikita Budnik","author_inst":"The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA."},{"author_name":"Marina P. Hommersom","author_inst":"Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen 6500 HB, The Netherlands."},{"author_name":"Audra Kramer","author_inst":"Department of Pharmacology and Physiology, University of Maryland School of Medicine, Baltimore, MD 20201, USA"},{"author_name":"Carlos G. Vanoye","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Guo-Qiang Zhang","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Michael Nothnagel","author_inst":"Cologne Center for Genomics (CCG), University of Cologne, Cologne, 50931, Germany."},{"author_name":"Aarno Palotie","author_inst":"The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA."},{"author_name":"Mark J. Daly","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Alfred L. George Jr.","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Yuri A. Zarate","author_inst":"Division of Genetics and Metabolism, University of Kentucky, Lexington, KY, USA."},{"author_name":"Andreas Brunklaus","author_inst":"School of Health and Wellbeing and Royal Hospital for Children University of Glasgow, Glasgow, UK."},{"author_name":"Stephen F. Traynelis","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Rikke S. M\u00f8ller","author_inst":"Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, member of ERN EpiCARE, Dianalund, Denmark."},{"author_name":"Johannes R. Lemke","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Dennis Lal","author_inst":"Center for Innovation in Health Informatics, Cook Children's Health Care System, Fort Worth, TX, USA"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Gene Portals: A Framework for Integrating Clinical, Functional, and Structural Evidence into Rare Disease Variant Classification","rel_doi":"10.64898\/2026.03.05.26347086","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347086","rel_abs":"Rare Mendelian disorders affect 300-400 million people globally. Although genetic testing has become widely adopted, gene-specific evidence for tailored variant interpretation remains scattered across resources. We present Gene Portals, a framework for gene-centered multimodal knowledge bases that co-localize expert-harmonized clinical data, functional assays, population variation, structural annotations and gene-specific ACMG\/AMP specifications within a single resource. A modular interface integrates this unified evidence with VCEP-refined ACMG specifications to enable automated gene-specific variant classification, infer molecular mechanisms, and support cross-gene analyses. We demonstrate the framework's utility across five Gene portals spanning eleven neurodevelopmental disorder-associated genes, integrating data from 4,423 individuals with 2,838 unique variants, 36,149 ClinVar submissions, and 1,044 expert-curated molecular readouts. By organizing evidence that is otherwise dispersed across multiple sources into a unified, queryable framework, the SCN, GRIN, CACNA1A, SATB2 and SLC6A1 Gene Portals became widely used community resources and provide an extensible template for standardized rare-disease variant interpretation and mechanism-aware discovery.","rel_num_authors":93,"rel_authors":[{"author_name":"Tobias Br\u00fcnger","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Ilona Krey","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Suyeon Kim","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Chiara Kl\u00f6ckner","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Scott J. A. Myers","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Katrine M. Johannesen","author_inst":"Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, Dianalund, Denmark."},{"author_name":"Arthur Stefanski","author_inst":"Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA."},{"author_name":"Gary Taylor","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Eduardo Perez-Palma","author_inst":"Universidad del Desarrollo, Centro de Gen\u00e9tica y Gen\u00f3mica, Instituto de Ciencias e Innovaci\u00f3n en Medicina, Facultad de Medicina Cl\u00ednica Alemana, Santiago de Chi"},{"author_name":"Marie Macnee","author_inst":"Cologne Center for Genomics (CCG), University of Cologne, Cologne, 50931, Germany."},{"author_name":"Stephanie Schorge","author_inst":"Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK."},{"author_name":"Rebekka S. Dahl","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Hongjie Yuan","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Riley E. Perszyk","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Sukhan Kim","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Sunanjay Bajaj","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Ingo Helbig","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Jen Q. Pan","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Mark Farrant","author_inst":"Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK."},{"author_name":"Lonnie Wollmuth","author_inst":"Department of Neurobiology & Behavior and Biochemistry & Cell Biology, Center for Nervous System Disorders, Stony Brook University, Stony Brook, NY, USA."},{"author_name":"David J. A. Wyllie","author_inst":"Institute for Neuroscience and Cardiovascular Research, University of Edinburgh, Edinburgh, UK."},{"author_name":"Erkin Kurganov","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"David Baez","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Sameer Zuberi","author_inst":"School of Health and Wellbeing and Royal Hospital for Children University of Glasgow, Glasgow, UK."},{"author_name":"Christian M. Bo\u00dfelmann","author_inst":"Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of T\u00fcbingen, 72076, T\u00fcbingen, Germany."},{"author_name":"Holger Lerche","author_inst":"Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of T\u00fcbingen, 72076, T\u00fcbingen, Germany."},{"author_name":"Massimo Mantegazza","author_inst":"Universit\u00e9 C\u00f4te D'Azur, CNRS UMR7275, Inserm U1323, Institute of Molecular and Cellular Pharmacology, Valbonne - Sophia Antipolis, France."},{"author_name":"Sandrine Cest\u00e8le","author_inst":"Universit\u00e9 C\u00f4te D'Azur, CNRS UMR7275, Inserm U1323, Institute of Molecular and Cellular Pharmacology, Valbonne - Sophia Antipolis, France."},{"author_name":"Patrick May","author_inst":"Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg."},{"author_name":"Alina Ivaniuk","author_inst":"Department of Neurology, Mayo Clinic in Florida, Jacksonville, Fl, 32224, USA."},{"author_name":"Mary Anne Meskis","author_inst":"Dravet Syndrome Foundation, Cherry Hill, NJ, USA."},{"author_name":"Veronica Hood","author_inst":"Dravet Syndrome Foundation, Cherry Hill, NJ, USA."},{"author_name":"Leah Schust","author_inst":"FamilieSCN2A Foundation 501(c)(3), Gettysburg, PA, USA."},{"author_name":"Kimberly Goodspeed","author_inst":"Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA."},{"author_name":"Jing-Qiong Kang","author_inst":"Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37232, USA."},{"author_name":"Amber Freed","author_inst":"SLC6A1 Connect, 1939 Temperence Hill Drive, Frisco, TX 75034, USA."},{"author_name":"Cornelius Gati","author_inst":"Department of Biological Sciences, Bridge Institute, USC Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA 90089, U"},{"author_name":"Ludovica Montanucci","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Arthur Wuster","author_inst":"BioMarin Pharmaceutical Inc., Novato, CA, USA."},{"author_name":"Marena Trinidad","author_inst":"Innovative Genomics Institute, University of California, Berkeley, CA, USA, 94720"},{"author_name":"Steven Froelich","author_inst":"BioMarin Pharmaceutical Inc., Novato, CA, USA."},{"author_name":"Alexander T. Deng","author_inst":"NHS South East Genomic Medicine Service, Guy's and St Thomas's NHS Foundation Trust, London SE1 9RT, UK"},{"author_name":"\u00c1ngel Aledo-Serrano","author_inst":"Epilepsy Program, Neurology Department, Hospital Ruber Internacional, Madrid 28034, Spain."},{"author_name":"Artem Borovikov","author_inst":"Research and Counseling Department, Research Centre for Medical Genetics, Moscow 115478, Russia."},{"author_name":"Artem Sharkov","author_inst":"Veltischev Research and Clinical Institute for Pediatrics and Pediatric Surgery of the Pirogov Russian National Research Medical University, Russia."},{"author_name":"Arjan Bouman","author_inst":"Department of Clinical Genetics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, Rotterdam 3000 CA, the Netherlands"},{"author_name":"MJ Hajianpour","author_inst":"Department of Pediatrics, Division of Medical Genetics and Genomics, Albany Medical College, Albany Med Health System, Albany, NY 12208, USA."},{"author_name":"Deb K. Pal","author_inst":"Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College, London SE58AF, UK."},{"author_name":"Leslie Danvoye","author_inst":"Department of Neurology, Universit\u00e9 catholique de Louvain, Cliniques universitaires Saint-Luc, Brussels 1200, Belgium."},{"author_name":"Damien Lederer","author_inst":"Centre de G\u00e9n\u00e9tique Humaine, Institut de Pathologie et de G\u00e9n\u00e9tique, 6041 Charleroi, Belgium."},{"author_name":"Tugce R. Balci","author_inst":"Department of Pediatrics, Division of Medical Genetics, Western University, London, ON N6A3K7, Canada."},{"author_name":"Eveline E. O. Hagebeuk","author_inst":"Stichting Epilepsie Instellingen Nederland (SEIN), Department of Pediatric Neurology, Heemstede, The Netherlands."},{"author_name":"Alexis Heidlebaugh","author_inst":"Department of Developmental Medicine, Geisinger, Danville, PA 17837, USA"},{"author_name":"Kathryn Oetjens","author_inst":"Department of Developmental Medicine, Geisinger, Danville, PA 17837, USA"},{"author_name":"Trevor L. Hoffman","author_inst":"Department of Regional Genetics, Anaheim, Southern California Kaiser Permanente Medical Group, CA 92806, USA."},{"author_name":"Pasquale Striano","author_inst":"Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto Giannina Gaslini, Genoa 16147, Italy"},{"author_name":"Sarah Drewes Williams","author_inst":"Division of Genetic and Genomic Medicine, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA 15224, USA."},{"author_name":"Kalene van Engelen","author_inst":"Medical Genetics Program of Southwestern Ontario, London Health Sciences Centre, London, ON N6A5W9, Canada."},{"author_name":"Katherine Howell","author_inst":"Department of Neurology, Royal Children's Hospital, Melbourne, VIC 3052, Australia"},{"author_name":"Jean Khoury","author_inst":"Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA."},{"author_name":"Tim A. Benke","author_inst":"Department of Pediatrics, Neurology and Pharmacology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA."},{"author_name":"Vincent Strehlow","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Konrad Platzer","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Amy Ramsey","author_inst":"Department of Pharmacology & Toxicology, University of Toronto, Toronto, Ontario, Canada."},{"author_name":"Lisa Manaster","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Sunitha Malepati","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Pangkong Fox","author_inst":"CACNA1A Foundation, Inc., 31 Point Rd, Norwalk, CT 06854, USA."},{"author_name":"Jeffrey Noebels","author_inst":"Blue Bird Circle Developmental Neurogenetics Laboratory, Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX, USA."},{"author_name":"Wendy Chung","author_inst":"Department of Neurology, Harvard Medical School, Boston, MA, USA."},{"author_name":"Annapurna Poduri","author_inst":"Department of Neurology, Harvard Medical School, Boston, MA, USA."},{"author_name":"Laina Lusk Stripe","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Sarah M. Ruggiero","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Stacey Cohen","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Lacey Smith","author_inst":"Epilepsy Genetics Program, Department of Neurology, Boston Children's Hospital, Boston, MA, USA."},{"author_name":"Sylvia Boesch","author_inst":"Center for rare Movement Disorders Innsbruck, Department of Neurology, Medical University Innsbruck, Innsbruck, Austria"},{"author_name":"Olivia Wilmarth","author_inst":"Inova Health System, Falls Church, VA, USA"},{"author_name":"Anna Jenne Prentice","author_inst":"Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA."},{"author_name":"Esther Cha","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Nikita Budnik","author_inst":"The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA."},{"author_name":"Marina P. Hommersom","author_inst":"Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behaviour, Nijmegen 6500 HB, The Netherlands."},{"author_name":"Audra Kramer","author_inst":"Department of Pharmacology and Physiology, University of Maryland School of Medicine, Baltimore, MD 20201, USA"},{"author_name":"Carlos G. Vanoye","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Guo-Qiang Zhang","author_inst":"Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA."},{"author_name":"Michael Nothnagel","author_inst":"Cologne Center for Genomics (CCG), University of Cologne, Cologne, 50931, Germany."},{"author_name":"Aarno Palotie","author_inst":"The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA."},{"author_name":"Mark J. Daly","author_inst":"Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Boston, MA, USA."},{"author_name":"Alfred L. George Jr.","author_inst":"Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA."},{"author_name":"Yuri A. Zarate","author_inst":"Division of Genetics and Metabolism, University of Kentucky, Lexington, KY, USA."},{"author_name":"Andreas Brunklaus","author_inst":"School of Health and Wellbeing and Royal Hospital for Children University of Glasgow, Glasgow, UK."},{"author_name":"Stephen F. Traynelis","author_inst":"Department of Pharmacology and Chemical Biology, and the Center for Functional Evaluation of Rare Variants (CFERV), Emory University School of Medicine, Atlanta"},{"author_name":"Rikke S. M\u00f8ller","author_inst":"Department of Epilepsy Genetics and Personalized Treatment, Danish Epilepsy Centre, member of ERN EpiCARE, Dianalund, Denmark."},{"author_name":"Johannes R. Lemke","author_inst":"Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany."},{"author_name":"Dennis Lal","author_inst":"Center for Innovation in Health Informatics, Cook Children's Health Care System, Fort Worth, TX, USA"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Modelling the Excess Mortality Associated with Heat Waves in Hong Kong: 2014-2023","rel_doi":"10.64898\/2026.03.05.26347683","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347683","rel_abs":"Introduction Heat waves are increasingly frequent and linked to higher mortality risks in Hong Kong. However, estimates of total excess mortality associated with heat waves remain unavailable. This study quantifies excess deaths associated with heat waves in Hong Kong from 2014 to 2023. Methods Daily age- and sex-specific mortality rates and population data were obtained from the Hong Kong Life Tables and Census and Statistics Department. Temperature data came from the Hong Kong Observatory, and relative risks were derived from local research. A Monte Carlo simulation was used to estimate heat-attributable deaths under different heat wave definitions, calculating total excess deaths and annualized death rates per 100,000 population. Results Between 2014 and 2023, heat exposure resulted in an estimated 1,455 (95% CI: 1,098-1,812) to 3,238 (95% CI: 3,234-3,242) excess deaths. In 2023, annualized excess death rates ranged from 2.95 (95% CI: 2.41-3.50) to 5.09 (95% CI: 5.07-5.12) per 100,000 people. Males and individuals aged 65 or older were disproportionately affected. Conclusion Over the 10-year study period, 1,455 to 3,238 excess deaths in Hong Kong were attributed to extreme heat. Heat waves now rank among the top ten causes of death in Hong Kong, with mortality rates comparable to diabetes. These findings underscore the need for urgent public health interventions to mitigate the impact of extreme heat.","rel_num_authors":5,"rel_authors":[{"author_name":"Zhenyuan Liu","author_inst":"The University of Hong Kong"},{"author_name":"Chao Ren","author_inst":"The University of Hong Kong"},{"author_name":"Jingwen Liu","author_inst":"The University of Adelaide"},{"author_name":"Yurika Kawasaki","author_inst":"The University of Hong Kong"},{"author_name":"David  Makram Bishai","author_inst":"The University of Hong Kong"}],"rel_date":"2026-03-06","rel_site":"medrxiv"},{"rel_title":"Diffusion-ACP39: A Decoder-Adaptive Latent Diffusion Framework for Generative Anticancer Peptide Discovery","rel_doi":"10.64898\/2026.03.04.709539","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709539","rel_abs":"Cancer remains a major global health threat, with its incidence and mortality rates consistently rising in recent years. Anticancer peptides (ACPs) are short amino acid chains that can inhibit the growth or spread of cancer cells. Compared to traditional treatments, ACPs are a promising class of potential cancer therapies due to their multiple mechanisms, potential for combination cancer therapy, enhanced immune function, lower toxicity to normal tissues, fewer side effects, and less drug resistance. Although it is necessary to explore novel ACPs, traditional wet-lab methods for selecting them are labor-intensive, time-consuming, and expensive. To accelerate the discovery of novel ACPs, we proposed Diffusion-ACP39, a latent diffusion-based generative model with synchronized seed autoencoder for anticancer peptide design, capable of generating novel peptides with lengths ranging from 5 to 39 amino acids. Furthermore, we developed RF-ACP39, a random forest classifier model to assess the generative power of Diffusion-ACP39. Finally, Diffusion-ACP39 achieved an accuracy of 94.5% when generating 10,000 peptides with RF-ACP39. We also qualitatively analyzed the differences among true ACPs, random sequences, random peptides, and generated ACPs, demonstrating that the generated ACPs are most similar to true ACPs.","rel_num_authors":7,"rel_authors":[{"author_name":"Jielu Yan","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Qichun Wu","author_inst":"chool of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Yifan Li","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Jianxiu Cai","author_inst":"Faculty of Applied Sciences, Macau Polytechnic University, Rua de Luis Gonzaga Gomes, Macau SAR, China"},{"author_name":"Mingliang Zhou","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Francois-Xavier CACPbell-Valois","author_inst":"Host-Microbe Interactions Laboratory, Center for Chemical and Synthetic Biology, Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa"},{"author_name":"Shirley WI Siu","author_inst":"Faculty of Applied Sciences, Macau Polytechnic University, Rua de Luis Gonzaga Gomes, Macau SAR, China"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Diffusion-ACP39: A Decoder-Adaptive Latent Diffusion Framework for Generative Anticancer Peptide Discovery","rel_doi":"10.64898\/2026.03.04.709539","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709539","rel_abs":"Cancer remains a major global health threat, with its incidence and mortality rates consistently rising in recent years. Anticancer peptides (ACPs) are short amino acid chains that can inhibit the growth or spread of cancer cells. Compared to traditional treatments, ACPs are a promising class of potential cancer therapies due to their multiple mechanisms, potential for combination cancer therapy, enhanced immune function, lower toxicity to normal tissues, fewer side effects, and less drug resistance. Although it is necessary to explore novel ACPs, traditional wet-lab methods for selecting them are labor-intensive, time-consuming, and expensive. To accelerate the discovery of novel ACPs, we proposed Diffusion-ACP39, a latent diffusion-based generative model with synchronized seed autoencoder for anticancer peptide design, capable of generating novel peptides with lengths ranging from 5 to 39 amino acids. Furthermore, we developed RF-ACP39, a random forest classifier model to assess the generative power of Diffusion-ACP39. Finally, Diffusion-ACP39 achieved an accuracy of 94.5% when generating 10,000 peptides with RF-ACP39. We also qualitatively analyzed the differences among true ACPs, random sequences, random peptides, and generated ACPs, demonstrating that the generated ACPs are most similar to true ACPs.","rel_num_authors":7,"rel_authors":[{"author_name":"Jielu Yan","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Qichun Wu","author_inst":"chool of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Yifan Li","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Jianxiu Cai","author_inst":"Faculty of Applied Sciences, Macau Polytechnic University, Rua de Luis Gonzaga Gomes, Macau SAR, China"},{"author_name":"Mingliang Zhou","author_inst":"School of Computer Science, Chongqing University, Shapingba, Chongqing, China"},{"author_name":"Francois-Xavier CACPbell-Valois","author_inst":"Host-Microbe Interactions Laboratory, Center for Chemical and Synthetic Biology, Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa"},{"author_name":"Shirley WI Siu","author_inst":"Faculty of Applied Sciences, Macau Polytechnic University, Rua de Luis Gonzaga Gomes, Macau SAR, China"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Modular Scaffold Crystals for Programmable Installation and Structural Observation of DNA-Binding Proteins","rel_doi":"10.64898\/2026.03.04.709581","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709581","rel_abs":"Inducing biomacromolecules to self-assemble into diffraction-quality crystals remains a major challenge, typically overcome by brute-force experimental screening. Inspired by Seeman's vision of DNA-junction-based scaffolds organizing guest biomacromolecules, we developed a protein-DNA co-crystal combining modular DNA programmability with robust protein-lattice diffraction. Our engineered co-crystals are composed of stacked double-stranded DNA scaffolded by protein columns, surrounding solvent channels designed to enable guest protein diffusion. DNA 'strut' variation allows positionally-controlled installation of diverse DNA binding guest proteins. Experimentally, we simply grow scaffold crystals under standardized conditions, ligate the scaffold, and soak guest proteins. Decoupling crystal growth from guest installation will enable high-throughput structure determination of diverse DNA-binding proteins and protein-macromolecule conjugates. Sub-nanometer position and orientation control of guest macromolecules will also enable functional applications beyond structural biology.","rel_num_authors":8,"rel_authors":[{"author_name":"Ethan T Shields","author_inst":"Colorado State University"},{"author_name":"Caroline K Slaughter","author_inst":"Colorado State University"},{"author_name":"Fadwa Mekkaoui","author_inst":"Clark University"},{"author_name":"Emma N Magna","author_inst":"Colorado State University"},{"author_name":"Cole Shepherd","author_inst":"Colorado State University"},{"author_name":"PHILIP S LUKEMAN","author_inst":"St. John's University"},{"author_name":"Donald Spratt","author_inst":"Clark University"},{"author_name":"Christopher Snow","author_inst":"Colorado State University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"A chromosome-level reference genome for the colonial marine hydrozoan Podocoryna americana","rel_doi":"10.64898\/2026.03.04.709628","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709628","rel_abs":"Cnidarians are important models for the studying the evolution of animal development, regeneration, cell type differentiation, and allorecognition. The marine hydrozoan Podocoryna americana is related to the well-established model species Hydractinia symbiolongicarpus. Although both species possess a sessile polyp stage, P. americana differs in that it also has a free-swimming medusa (jellyfish) stage in its life cycle. We used a combination of PacBio CLR long-read and Illumina Hi-C short-read genome sequencing to produce a chromosome-level genome assembly for P. americana. The final assembly is 327 Mbp in total length with 17 chromosome-scale scaffolds representing 98% of the assembly. Comprehensive functional annotation with BRAKER3 generated a total of 19,085 predicted protein-coding genes in this assembly, covering 91.2% of the metazoan BUCSO gene set. Comparison of the P. americana genome to other chromosome-level cnidarian genome assemblies revealed a high degree of macrosynteny conservation, and ortholog identification and gene family evolution analysis identified 522 expanded and 1,026 contracted gene families in P. americana. This high-quality, chromosome-level genome assembly of P. americana will be an invaluable resource for researchers studying the evolution of development, regeneration, and allorecognition in cnidarians and other metazoans.","rel_num_authors":9,"rel_authors":[{"author_name":"E Sally Chang","author_inst":"King's College London"},{"author_name":"Michael T Connelly","author_inst":"National Human Genome Research Institute"},{"author_name":"Matthew Travert","author_inst":"University of Galway"},{"author_name":"Sofia N Barreira","author_inst":"National Human Genome Research Institute"},{"author_name":"Alberto M Rivera","author_inst":"National Human Genome Research Institute"},{"author_name":"Amanda M Katzer","author_inst":"National Human Genome Research Institute"},{"author_name":"Reynold Yu","author_inst":"National Human Genome Research Institute"},{"author_name":"Paulyn Cartwright","author_inst":"The University of Kansas"},{"author_name":"Andreas D Baxevanis","author_inst":"National Human Genome Research Institute"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Remote homology and functional genetics unmask deeply preserved Scm3\/HJURP orthologs in metazoans","rel_doi":"10.64898\/2026.03.04.709615","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709615","rel_abs":"In most animals and fungi, centromere identity and function depend on the Scm3\/HJURP chaperone, which deposits CENPA at centromeres. However, Scm3\/HJURP orthologs appeared to be missing in insects, nematodes, many vertebrates, and other metazoans, suggesting radical chaperone replacement in these lineages. Here, we combine remote homology detection, AlphaFold-based structural modeling, and functional genetics in zebrafish and Caenorhabditis elegans to identify previously unknown Scm3\/HJURP orthologs that localize to centromeres and whose loss causes catastrophic mitotic failure. We further show that Drosophila CAL1, long considered a functional analog, is instead a highly diverged Scm3\/HJURP ortholog. Despite rapid primary-sequence divergence, predicted and known structures reveal a broadly conserved CENPA-H4-binding scm3 fold across fungi, vertebrates, nematodes, insects, and basally-branching metazoans. Our work demonstrates how rapid divergence can obscure the broad conservation of essential centromere machinery and provides a broadly applicable strategy to unmasking missing orthologs.","rel_num_authors":8,"rel_authors":[{"author_name":"Jeremy Alden Hollis","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Jason A. Stonick","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Irini Topalidou","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Janet M. Young","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Cecilia B. Moens","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Nicolas J. Lehrbach","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Melody G. Campbell","author_inst":"Fred Hutchinson Cancer Center"},{"author_name":"Harmit Singh Malik","author_inst":"Fred Hutchinson Cancer Center"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Trait - climate relations in Themeda triandra: a widely distributed C4 grass and crop wild relative","rel_doi":"10.64898\/2026.03.04.709158","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709158","rel_abs":"Quantifying relationships between traits and climate using plants collected from diverse climatic origins, grown under common conditions, potentially provides valuable insights into climate adaptation. We report on fifteen accessions of kangaroo grass (Themeda triandra), a C4 species distributed across Australia, Asia, the Middle East and Africa from the Andropogoneae clade of grasses that is vital to global agriculture. Plants were grown to maturity in glasshouses under two thermal regimes, with ample water supplied. Numerous physiological, economic and developmental traits were characterised. As expected, plants grown at 20 {degrees} C maxima had lower photosynthetic rates (Asat) and dark respiration rates, reduced leaf expansion, and delayed flowering compared with plants grown at 30 {degrees} C. However, surprisingly few traits varied with climate-of-origin: accessions from colder climates had higher Asat alongside lower leaf mass per area, but only when grown at 20 {degrees} C flowering time showed the strongest correlation with site climate, with plants from wetter, warmer or less variable climates taking longer to flower. Our findings highlight remarkable phenotypic flexibility in key traits of T. triandra; this flexibility is likely key to its wide distribution. The strong relationship between flowering time and climate-of-origin underscores the importance of reproductive phenology as an adaptive trait.","rel_num_authors":7,"rel_authors":[{"author_name":"Vinod Jacob","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, A"},{"author_name":"Brian Atwell","author_inst":"School of Natural Sciences, Macquarie University, NSW 2109, Australia."},{"author_name":"Luke A Yates","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, School of Natural Sciences, University of Tasmania, Sandy Bay, Tasmania 7005, Australia"},{"author_name":"Rachael Gallagher","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, A"},{"author_name":"Emma E Sumner","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, A"},{"author_name":"Travis Britton","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, A"},{"author_name":"Ian J Wright","author_inst":"ARC Centre of Excellence for Plant Success in Nature and Agriculture, Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW 2753, A"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"PAVR: High-Resolution Cellular Imaging via a Physics-Aware Volumetric Reconstruction Framework","rel_doi":"10.64898\/2026.03.04.709609","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709609","rel_abs":"The rapid convergence of advanced microscopy and deep learning is transforming cell biology by enabling imaging systems in which optical encoding and computational inference are jointly optimized for volumetric information capture and interpretation. However, broadly accessible three-dimensional imaging at high spatiotemporal resolution remains constrained by volumetric reconstruction throughput, susceptibility to artifacts, and the burden of collecting modality-matched training data. Here, we introduce PAVR, a physics-aware light-field imaging platform that integrates single-shot volumetric acquisition with fast, end-to-end volumetric reconstruction. PAVR is trained entirely using in silico system responses, avoiding reliance on external high-resolution ground-truth modalities and enabling sample-independent reconstruction across diverse biological contexts. Using fixed and live mammalian cells, we demonstrate multicolor volumetric imaging of subcellular organelles, three-dimensional tracking of autofluorescent particles, and high-speed visualization of organelle remodeling and interactions. We further extend PAVR to quantify coupled morphological and functional dynamics in beating human induced pluripotent stem cell-derived cardiomyocytes under pharmacological perturbation. Together, PAVR establishes a scalable hardware-software platform for high-throughput volumetric imaging and quantitative analysis of dynamic cellular systems in both basic and translational settings.","rel_num_authors":16,"rel_authors":[{"author_name":"Xuanwen Hua","author_inst":"Georgia Institute of Technology"},{"author_name":"Keyi Han","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"Zhi Ling","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"Olivia Reid","author_inst":"Emory University"},{"author_name":"Zijun Gao","author_inst":"Georgia Institute of Technology"},{"author_name":"Hongmanlin Zhang","author_inst":"Georgia Institute of Technology"},{"author_name":"Edward Botchwey","author_inst":"Georgia Institute of Technology"},{"author_name":"Parvin Forghani","author_inst":"Emory University"},{"author_name":"Wenhao Liu","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"Mithila Anil Sawant","author_inst":"Emory University"},{"author_name":"Afsane Radmand","author_inst":"Georgia Institute of Technology"},{"author_name":"Hyejin Kim","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"James E Dahlman","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"Aparna Kesarwala","author_inst":"Emory University"},{"author_name":"Chunhui Xu","author_inst":"Georgia Institute of Technology and Emory University"},{"author_name":"Shu Jia","author_inst":"Georgia Institute of Technology and Emory University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"A Novel Monocyte-derived Antigen Presenting Cell-T regulatory Cell Axis Contributes to Skin Wound healing and is Impaired in Diabetic Mice","rel_doi":"10.64898\/2026.03.04.709590","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709590","rel_abs":"Despite a vast literature on the role of macrophages in wound healing, the role of dermal monocyte (Mo)-derived antigen presenting cells (APC) has received scant attention. Using scRNAseq and flow cytometry, we identify a population of APC that is prominent in wounds of non-diabetic mice but is reduced in wounds of diabetic mice. Using adoptive transfer experiments and Ccr2 knockout mice, we demonstrate that wound APC are derived primarily from Mo and that the diabetic wound environment inhibits differentiation of Mo into APC. We also show that Mo-specific Irf4 knockout mice exhibit reduced differentiation of Mo into APC, decreased levels of IL27 and numbers of activated Treg cells in wounds. and impaired wound healing. Importantly, adoptive transfer of bone marrow Mo that express Irf4 into wounds of Mo-specific Irf4 knockout mice rescued levels of wound APC and activated Treg, as well as wound healing. Local administration of recombinant IL27 into wounds of these mice also rescued levels of activated Treg in wounds, along with wound healing, Together, these findings identify a novel pathway in which IRF4 induces Mo differentiation into APC in wounds, which in turn produce IL27 that activates Treg to promote healing. This pathway is impaired in wounds of diabetic mice, which provides a novel target to improve diabetic wound healing.","rel_num_authors":6,"rel_authors":[{"author_name":"Jingbo Pang","author_inst":"University of Illinois at Chicago"},{"author_name":"Brandon E Lukas","author_inst":"University of Illinois at Chicago"},{"author_name":"Rita Roberts","author_inst":"University of Illinois at Chicago"},{"author_name":"Mark Maienschein-Cline","author_inst":"University of Illinois at Chicago"},{"author_name":"Yang Dai","author_inst":"University of Illinois at Chicago"},{"author_name":"Timothy J Koh","author_inst":"University of Illinois at Chicago"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Extent of damage to descending output from cortex rather than to specific cortical regions drives the emergence of flexor synergy in non-human primates","rel_doi":"10.64898\/2026.03.04.709517","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709517","rel_abs":"Obligate flexor synergies are a defining feature of the hemiparetic phenotype following stroke in humans. Although these intrusive synergies can diminish over time, recovery may plateau, leaving some individuals with movements permanently constrained to synergies. Despite their clinical significance, the neural mechanisms underlying the emergence and persistence of abnormal synergies remain poorly understood. To investigate this mechanistically, three macaque monkeys were trained on a reach and grasp task prior to receiving one of three unilateral lesion types: 1) a focal sensorimotor cortical lesion, 2) a combined sensorimotor cortical and magnocellular red nucleus (RNm) lesion, or 3) a lesion of the internal capsule. Upper limb three-dimensional kinematics and EMG cross correlation were used to measure the intrusion of synergies during 'in synergy' vs 'out of synergy' reaching. A combined RNm and cortical lesion produced weakness but no flexor synergy. A similar-sized cortical lesion generated mild synergies which substantially recovered. By contrast, a large internal capsule lesion produced severe, persistent flexor synergy. Collectively, these findings suggest that the emergence of abnormal synergies is determined by the extent of corticofugal disruption, and their persistence depends on the ability of surviving supraspinal motor pathways to regain selective control over muscle contractions.","rel_num_authors":5,"rel_authors":[{"author_name":"Anna Baines","author_inst":"Newcastle University"},{"author_name":"Isabel S Glover","author_inst":"Newcastle University"},{"author_name":"Anne ME Baker","author_inst":"Newcastle University"},{"author_name":"John W Krakauer","author_inst":"Johns Hopkins University School of Medicine"},{"author_name":"Stuart N Baker","author_inst":"Newcastle University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Single-Cell Genomics Decontamination with CellSweep","rel_doi":"10.64898\/2026.03.04.709349","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709349","rel_abs":"Single-cell genomics technologies enable high-throughput cell profiling, but technical contamination remains an obstacle to accurate downstream analysis. Free-floating ambient molecules released from lysed cells and global bulk contamination introduced during library preparation can distort molecular profiles. These artifacts can obscure cellular identities and reduce the reliability of differential analysis or clustering results. We present an efficient and effective approach to removing ambient and bulk contamination that can be applied to data generated from a wide variety of technologies. We show that our tool, CellSweep, outperforms other methods to remove artifacts using numerous benchmarks.","rel_num_authors":6,"rel_authors":[{"author_name":"Maya Caskey","author_inst":"California Institute of Technology"},{"author_name":"Joseph Rich","author_inst":"California Institute of Technology"},{"author_name":"Ryan Weber","author_inst":"University of California, Irvine"},{"author_name":"Ali Mortazavi","author_inst":"University of California, Irvine"},{"author_name":"Lior Pachter","author_inst":"California Institute of Technology"},{"author_name":"Ingileif B. Hallgrimsdottir","author_inst":"California Institute of Technology"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Cannabis Use by People with HIV is Associated with an Anti-Inflammatory Immunometabolic Phenotype in Monocyte-Derived Macrophages","rel_doi":"10.64898\/2026.03.04.709579","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709579","rel_abs":"Chronic neuroinflammation is associated with comorbidities in people with HIV (PWH) on antiretroviral therapy (ART). While cannabis use is associated with reduced neuroinflammation and neurocognitive impairment (NCI) in PWH, the underlying mechanisms are unknown. To address this gap in knowledge, we analyzed monocyte-derived macrophages (MDMs) from a cohort of 50 PWH and 33 people without HIV (mean age: 61.9 years), categorized by frequency of cannabis use (naive\/low, moderate, daily). We performed immunocytochemistry, RNA sequencing, and qPCR on MDMs and quantified related biomarkers in donor plasma. In this cohort study, daily cannabis use in PWH was associated with less global neurocognitive deficits, and with an anti-inflammatory immunometabolic-phenotype in MDMs characterized by (1) a metabolic shift from glycolysis to oxidative phosphorylation, (2) higher mitochondrial numbers, (3) altered cytokine profiles (pro-inflammatory downregulation, anti-inflammatory upregulation), and (4) higher brain-derived neurotrophic factor (BDNF) expression. These cellular changes were corroborated by a plasma biomarker profile in PWH including (1) lower levels of growth differentiation factor 15 and soluble triggering receptor expressed on myeloid cells 2, and (2) higher mature BDNF\/precursor BDNF ratios that correlated with better cognition. Thus, cannabis use may mitigate NCI in PWH by immunometabolically reprogramming MDM function towards an anti-inflammatory and neuroprotective state.","rel_num_authors":18,"rel_authors":[{"author_name":"Mary Ford","author_inst":"UCSD"},{"author_name":"Peter W Halcrow","author_inst":"UCSD"},{"author_name":"Anna Laird","author_inst":"UCSD"},{"author_name":"Bryant Leyva","author_inst":"UCSD"},{"author_name":"Ali Boustani","author_inst":"UCSD"},{"author_name":"Matthew Spencer","author_inst":"UCSD"},{"author_name":"Jack Melcher","author_inst":"UCSD"},{"author_name":"Kyle Walter","author_inst":"UCSD"},{"author_name":"Derek Hong","author_inst":"UCSD"},{"author_name":"Gail Funk","author_inst":"UCSD"},{"author_name":"Elizabeth Searson","author_inst":"UCSD"},{"author_name":"Alexandria A. Le","author_inst":"UCSD"},{"author_name":"Ronald J. Ellis","author_inst":"University of California, San Diego"},{"author_name":"Scott Letendre","author_inst":"UCSD"},{"author_name":"Maria Cecilia Garibaldi Marcondes","author_inst":"San Diego Biomedical Research Institute"},{"author_name":"Johannes Schlachetzki","author_inst":"UCSD"},{"author_name":"Jennifer Iudicello","author_inst":"UCSD"},{"author_name":"Jerel A Fields","author_inst":"UCSD"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"MetaSAG: A Tool for Multi-level Exploration and Taxonomic Analysis of Microbial Single-Amplified Genomes","rel_doi":"10.64898\/2026.03.04.709444","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709444","rel_abs":"Microbial single-amplified genome (SAG) sequencing technologies have elevated microbial research resolution to the single-cell level. However, neither upstream data processing nor downstream analysis has been fully developed, greatly limiting the research in strain level. Herein, we developed MetaSAG (Multi-level Exploration and Taxonomic Analysis of microbial Single-Amplified Genomes), which enables accurate and rapid taxonomic classification of microbial SAGs. MetaSAG outperforms existing method in species classification certainty, computational efficiency, and sensitivity of low abundance species identification. In addition, MetaSAG enables species-level functional analysis, as well as strain-level evolutionary analysis. With the help of MetaSAG, we discovered the parasitic relationship between phages and bacteria, identifying multiple susceptible bacteria and a broad spectrum of phages. Furthermore, we developed MetaK-Lytic (k-mer-based meta-learning framework to predict phage lytic ability) to achieve accurate prediction of phage lytic activity based on 31-mer short sequences, which is well adapted to the characteristics of incomplete SAG sequences. Overall, we offer a comprehensive integrated tool that can parse microbial SAG data from raw data to the strain level to decipher the functional ecology of microbial dark matter, with broad implications for microbial ecology and phage therapy (https:\/\/github.com\/liangcheng-hrbmu\/MetaSAG).","rel_num_authors":14,"rel_authors":[{"author_name":"Sainan Zhang","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Meiyu Du","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Guanzhi He","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Kai Qian","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Kexin Li","author_inst":"The University of Hong Kong"},{"author_name":"Baifeng Li","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Ping Wang","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Minke Lu","author_inst":"College of Basic Medical Sciences, Harbin Medical University"},{"author_name":"Xiaoliang Wu","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Chao Wang","author_inst":"College of Bioinformatics Science and Technology, Harbin Medical University"},{"author_name":"Hongbin Han","author_inst":"Institute of Medical Technology, Peking University Health Science Center"},{"author_name":"Shuofeng Yuan","author_inst":"The University of Hong Kong"},{"author_name":"Xue Zhang","author_inst":"Harbin Medical University"},{"author_name":"Liang Cheng","author_inst":"Harbin Medical University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"A minimally invasive floating-wire interface for transcranial deep brain stimulation","rel_doi":"10.64898\/2026.03.04.709293","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709293","rel_abs":"Background Non-invasive neuromodulation technologies have advanced considerably. Yet, precise and focal activation of deep brain regions remains challenging due to the rapid attenuation of electric fields across the scalp, skull and brain surface. Objective We present FLOATES (FLOAting Transcranial Electrical Stimulation), a novel approach that employs an untethered wire implanted in the brain which passively relays currents injected transcranially from the brain surface to deep brain regions, achieving focused stimulation deep within the brain. Methods We validated FLOATES through a combination of simulations, benchtop testing, and in vivo rodent studies. The benchtop experiments confirmed the ability to relay the field across the floating wire. Rodent studies demonstrated capability to stimulate deep brain regions in vivo. Results Our simulation and benchtop testing results indicate that FLOATES can deliver significantly higher electric fields to subcortical regions compared to conventional transcranial stimulation approaches. Further in-vivo results demonstrated deep subthalamic nuclei stimulation to evoke limb motor responses and demonstrated a significantly lower motor threshold compared to transcranial stimulation. Finite element simulations reveal that the efficiency of FLOATES depends on several key parameters including input field strength, wire length and diameter, exposed electrode area, impedance, and tip geometry. Simulations using a human-sized head model suggest that electric fields sufficient for brain stimulation can be obtained with reasonable currents injected to the scalp. Conclusion Together, these results establish a theoretical and experimental foundation for FLOATES as a minimally invasive and spatially precise brain stimulation platform in modulating deep neural circuits implicated in neuropsychiatric and movement disorders.","rel_num_authors":4,"rel_authors":[{"author_name":"Vishal Jain","author_inst":"Carnegie Mellon University"},{"author_name":"Mats Forssell","author_inst":"Carnegie Mellon University"},{"author_name":"Pulkit Grover","author_inst":"Carnegie Mellon University"},{"author_name":"Maysam Chamanzar","author_inst":"Carnegie Mellon University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Saturating hepatic clearance drives elevated cfDNA and fragment shortening in cancer","rel_doi":"10.64898\/2026.03.04.709433","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709433","rel_abs":"Liquid biopsy studies consistently report both elevated circulating cell-free DNA (cfDNA) concentrations and shortened fragment lengths in cancer. These features are often attributed to tumor-specific processes, despite tumor-derived cfDNA frequently constituting less than 1\\% of the total. Here, we consider an alternative explanation: Saturation of cfDNA clearance, which prolongs cfDNA circulation time, increases exposure to plasma nucleases and is expected to produce similar fragmentomic signatures independent of tumor burden. By combining a mechanistic model of cfDNA fragmentation with analyses of two independent cancer patient cohorts, and publicly available clearance-perturbation experiments, we demonstrate that elevated cfDNA levels are accompanied by a characteristic leftward shift in fragment length distributions consistent with impaired hepatic clearance. This fragmentation signature becomes more pronounced at higher cfDNA concentrations, is independent of circulating tumor DNA (ctDNA) fraction, is reproducible under experimentally reduced clearance, and is independently prognostic of patient survival. Together, these results identify saturating clearance as a central determinant of cfDNA abundance and fragment length, re-framing cancer-associated fragmentomic patterns as systemic consequences of clearance dynamics rather than tumor burden alone. More broadly, they highlight the value of mechanistic modeling of clearance processes in extracting clinically meaningful signals from cfDNA fragmentation data.","rel_num_authors":14,"rel_authors":[{"author_name":"Thomas Rachman","author_inst":"Carnegie Mellon University"},{"author_name":"William Laframboise","author_inst":"Allegheny Health Network"},{"author_name":"Phillip Gallo","author_inst":"Allegheny Health Network"},{"author_name":"Patricia Petrosko","author_inst":"Allegheny Health Network"},{"author_name":"Daisong Liu","author_inst":"University of Pittsburgh"},{"author_name":"Rahul Kumar","author_inst":"University of Pittsburgh"},{"author_name":"Marija Balic","author_inst":"University of Pittsburgh"},{"author_name":"Steffi Oesterreich","author_inst":"University of Pittsburgh"},{"author_name":"Julia Foldi","author_inst":"University of Pittsburgh"},{"author_name":"Adrian Lee","author_inst":"University of Pittsburgh"},{"author_name":"Patrick Wagner","author_inst":"Allegheny Health Network"},{"author_name":"David Bartlett","author_inst":"Allegheny Health Network"},{"author_name":"Russell Schwartz","author_inst":"Carnegie Mellon University"},{"author_name":"Oana Carja","author_inst":"Carnegie Mellon University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Optimal spatial release strategies for confined gene drives and Wolbachia","rel_doi":"10.64898\/2026.03.04.709515","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709515","rel_abs":"Gene drives are genetic elements that can rapidly spread through populations, offering potential solutions for controlling disease vectors and pests. In some scenarios, it is necessary to utilize drives that can be confined to only target populations. The success of these threshold-dependent gene drives, which require a minimum local frequency to establish, depends critically on the spatial strategy used for introduction. Here, we use a reaction-diffusion model to systematically identify optimal release patterns that maximize the per-capita efficiency for four distinct gene drive designs as well as use of Wolbachia bacteria, which spread similarly to frequency-dependent gene drives. We find that the most efficient release strategy is highly dynamic, transitioning from a broad \"everywhere\" release for short timeframes to a \"multiple-ring\" pattern for intermediate times, and finally to a focused \"center\" release for longer timeframes. These timeframes depend on the specific type of drive, with more powerful variants transitioning more quickly to center releases. Our results demonstrate that these optimized, variable release strategies can be substantially more effective than simple uniform releases. This study provides a quantitative framework for designing effective gene drive implementations, highlighting that a carefully planned spatial strategy is essential for maximizing impact, making optimal use of available resources.","rel_num_authors":2,"rel_authors":[{"author_name":"Ziye Wang","author_inst":"Peking University"},{"author_name":"Jackson Champer","author_inst":"Peking University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Engineered OAA lectins as selective and sensitive high mannose glycan targeting tools","rel_doi":"10.64898\/2026.03.04.709641","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709641","rel_abs":"The Oscillatoria agardhii agglutinin (OAA) lectin interacts with N-glycans through a pentamannose core shared among all high mannose N-glycans (HMGs). Because HMGs only differ by number of mannose sugars, there is a scarcity of tools sensitive enough to resolve each specific HMG structure in their biological context. Here, we investigate the sequence space of OAA to tune the binding properties towards selectivity of Man5GlcNAc2, thus generating a structure-specific detection tool. Using phage display to screen a diverse library of OAA variants, we identify a variant with high selectivity for Man5GlcNAc2 that we further dissect to reveal four mutations necessary for selectivity and two mutations responsible for enhanced affinity for all HMGs. Coupling a crystal structure of the selective variant with binding analysis of specific point mutations, we reveal how co-dependent mutations achieve selectivity. We then demonstrate how variants can be valency-modulated on a single beta-barrel scaffold to improve their binding properties by orders of magnitude. Finally, we showcase the applicability of engineered OAA variants as improved HMG profiling tools and tunable antiviral agents.","rel_num_authors":7,"rel_authors":[{"author_name":"Bryce E Ackermann","author_inst":"University of California San Diego"},{"author_name":"Emerson Hall","author_inst":"University of California San Diego"},{"author_name":"Vanessa T Mariscal","author_inst":"University of California San Diego"},{"author_name":"Alex Clark","author_inst":"University of California San Diego"},{"author_name":"Kevin D Corbett","author_inst":"University of California San Diego"},{"author_name":"Aaron Carlin","author_inst":"University of California San Diego"},{"author_name":"Alex Guseman","author_inst":"University of California San Diego"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Clathrin is an Intrinsic Driver of Membrane Fission","rel_doi":"10.64898\/2026.03.05.709932","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709932","rel_abs":"The extent to which clathrin directly drives membrane curvature during endocytosis has remained a central, longstanding question in the field of endocytosis. Using a synthetic reconstitution system that recruits clathrin to lipid membranes independent of adaptor proteins, we demonstrate that clathrin alone can induce membrane fission and that its capacity to do so is governed by the mechanical properties of the lattice. Counterintuitively, conditions that strengthen lattice assembly suppress fission, whereas weakened assembly enhances fission despite reduced membrane association. Meso-scale Brownian dynamics reveal that assembly dependent changes in triskelion geometry and lattice stiffness dictate curvature generation, corroborating these findings. These principles are further extended when clathrin is recruited by adaptor proteins amphiphyin1 or epsin1, with clathrin either enhancing or restricting fission based on adaptor specific tuning of lattice mechanics. Lastly, perturbations to clathrin assembly in live cells shift endocytic pit dynamics, with Ca2+; and EGTA producing opposing effects on pit lifetime and productive events consistent with modulation of the membrane fission barrier. Together, these results identify protein and lattice mechanics, not simply bound protein density, as the key determinant of clathrin's ability to remodel membranes, elucidating its biophysical impact on vesicle formation during endocytosis.","rel_num_authors":6,"rel_authors":[{"author_name":"Nicoletta Bouzos","author_inst":"University of Southern California"},{"author_name":"Samuel L Foley","author_inst":"Johns Hopkins University"},{"author_name":"Ariadni Potamianos","author_inst":"University of Southern California"},{"author_name":"Ciara O. Jacobs","author_inst":"University of Southern California"},{"author_name":"Margaret E Johnson","author_inst":"Johns Hopkins University"},{"author_name":"Wade F. Zeno","author_inst":"University of Southern California"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Force-modulated structural landscape of the catch bonding F-actin crosslinker \u03b1-actinin-4","rel_doi":"10.64898\/2026.03.04.709699","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709699","rel_abs":"Catch bonds, noncovalent supramolecular interactions whose lifetimes are increased by force, are ubiquitous in mechanical signaling pathways. The structural mechanisms of catch-bonding proteins remain unclear, hampering efforts to decipher how they are dysregulated in disease and exploit them therapeutically. The crosslinker -actinin-4 (ACTN4) forms catch bonds with actin filaments (F-actin) to support the function of kidney podocytes, and its force-insensitive K255E variant causes autosomal dominant focal segmental glomerulosclerosis (FSGS). Using cryo-electron microscopy (cryo-EM), we find that wild-type ACTN4 engages F-actin in two modes, which biochemical experiments and molecular dynamics simulations assign as strong- and weak-binding states, while K255E ACTN4 only populates the strong binding state. By implementing a cryo-EM platform for applying tension across crosslinker-F-actin interfaces using myosin motors, we find that force promotes a weak-to-strong binding transition for wild-type ACTN4, consistent with a two-state catch bond model. Beyond providing mechanistic insight into how the K255E mutation disrupts ACTN4 F-actin catch-bonding in FSGS, this approach enables structural dissection of force-sensitive actin-binding proteins.","rel_num_authors":5,"rel_authors":[{"author_name":"Alfred C Chin","author_inst":"The Rockefeller University"},{"author_name":"Fatemah Mukadum","author_inst":"New York University"},{"author_name":"Matthew J Reynolds","author_inst":"The Rockefeller University"},{"author_name":"Glen M Hocky","author_inst":"New York University"},{"author_name":"Gregory M Alushin","author_inst":"The Rockefeller University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Force-modulated structural landscape of the catch bonding F-actin crosslinker \u03b1-actinin-4","rel_doi":"10.64898\/2026.03.04.709699","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709699","rel_abs":"Catch bonds, noncovalent supramolecular interactions whose lifetimes are increased by force, are ubiquitous in mechanical signaling pathways. The structural mechanisms of catch-bonding proteins remain unclear, hampering efforts to decipher how they are dysregulated in disease and exploit them therapeutically. The crosslinker -actinin-4 (ACTN4) forms catch bonds with actin filaments (F-actin) to support the function of kidney podocytes, and its force-insensitive K255E variant causes autosomal dominant focal segmental glomerulosclerosis (FSGS). Using cryo-electron microscopy (cryo-EM), we find that wild-type ACTN4 engages F-actin in two modes, which biochemical experiments and molecular dynamics simulations assign as strong- and weak-binding states, while K255E ACTN4 only populates the strong binding state. By implementing a cryo-EM platform for applying tension across crosslinker-F-actin interfaces using myosin motors, we find that force promotes a weak-to-strong binding transition for wild-type ACTN4, consistent with a two-state catch bond model. Beyond providing mechanistic insight into how the K255E mutation disrupts ACTN4 F-actin catch-bonding in FSGS, this approach enables structural dissection of force-sensitive actin-binding proteins.","rel_num_authors":5,"rel_authors":[{"author_name":"Alfred C Chin","author_inst":"The Rockefeller University"},{"author_name":"Fatemah Mukadum","author_inst":"New York University"},{"author_name":"Matthew J Reynolds","author_inst":"The Rockefeller University"},{"author_name":"Glen M Hocky","author_inst":"New York University"},{"author_name":"Gregory M Alushin","author_inst":"The Rockefeller University"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Prophase Chromosomes Relocalizes to Nuclear Periphery for Protection in Depletion of Nucleoporin NPP-3\/NUP205 Through the Spindle Assembly Checkpoint Activity, Centromere-Kinetochore Proteins and BAF-1-LEM-2","rel_doi":"10.64898\/2026.03.04.709728","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.04.709728","rel_abs":"The nuclear envelope (NE) mediates transport between nucleus and cytoplasm in eukaryotic cells and protects genetic materials against cytoplasmic enzymes. Nuclear pore complexes (NPCs) regulate chromosome architecture, genome integrity, gene transcription, and cell division. In Caenorhabditis elegans embryos, depletion of NPP-3\/NUP205 causes NE rupture, premature chromosome condensation, and relocalization of condensed chromosomes to the nuclear periphery, similar to responses during anoxia and quiescence. This chromosomal relocalization depends on the spindle assembly checkpoint (SAC), inner kinetochore proteins, and partially on the NE rupture repair proteins BAF-1 and LEM-2. NPP-3 depletion prolongs prophase and prometaphase, as mediated by SAC proteins MDF-1 and MDF-2. Additionally, NPP-3 depletion alters MDF-1 localization, removing it from NE and increasing its nuclear accumulation, while reducing import of kinetochore components such as KNL-1, BUB-1, and HCP-1. In 20-30 cell-stage embryos, MDF-1 foci are observed on peripheral chromosomes during prophase. Both MDF-1 and MDF-2 accumulate on chromosomes during prometaphase. The increased incidence of lagging chromosomes, DNA damage, and micronuclei upon NPP-3 and MDF-1 depletion, suggesting that peripheral chromosome localization may serve as a protective mechanism against DNA damage. These findings shed light into cellular responses to NE rupture, with potential implications for laminopathies and cancers involving nuclear envelope defects.","rel_num_authors":3,"rel_authors":[{"author_name":"Ling Jiang","author_inst":"The University of Hong Kong"},{"author_name":"Yu Chung Tse","author_inst":"The Hong Kong University of Science and Technology"},{"author_name":"Karen Wing Yee Yuen","author_inst":"The University of Hong Kong"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"Transitory enhancement of GATA2 chromatin engagement during early erythroid differentiation","rel_doi":"10.64898\/2026.03.05.709895","rel_link":"http:\/\/biorxiv.org\/content\/10.64898\/2026.03.05.709895","rel_abs":"Erythroid differentiation requires precise regulation of transcription factor binding to chromatin targets as hematopoietic progenitors relinquish multipotency and activate lineage programs. GATA2 maintains progenitor identity and is thought to be progressively silenced as GATA1 levels rise. However, the precise changes in GATA2 chromatin binding kinetics during this transition remain undefined. Here, we combined live-cell single-molecule imaging in cell lines and primary mouse progenitors with CUT&Tag chromatin profiling to define GATA2 activity during erythropoiesis. Single-molecule tracking resolved two interaction modes: short-lived (<1s) searching interactions and long-lived (>5 s) binding. Surprisingly, early erythroid differentiation was characterized by a transitory strengthening of long-lived GATA2 chromatin engagement. This manifested as increased residence time of GATA2 bound to chromatin in G1E-ER4 cells and an expansion of the long-lived bound population in HPC7 cells and primary mouse progenitors. This transitory phase of enhanced engagement declined upon further differentiation. Genome-wide mapping identified regulatory elements selectively occupied by GATA2 during this early transition state, revealing promoter-proximal sites enriched for GATA\/RUNX motifs and distal elements containing composite GATA\/E-box signatures. Together, our imaging and chromatin profiling indicate that GATA2 chromatin engagement is kinetically remodeled at the onset of differentiation, with early recruitment targets partitioning into distinct promoter- and enhancer-associated subclasses. These results support a model in which transcription factor kinetics constitute a dynamic chromatin engagement layer that characterizes the GATA2-to-GATA1 transition.","rel_num_authors":7,"rel_authors":[{"author_name":"John W Hobbs IV","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Samuel J Taylor","author_inst":"WashU Medicine"},{"author_name":"Rajni Kumari","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Nayem Haque","author_inst":"Albert Einstein College of Medicine"},{"author_name":"LouLou Victor","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Ulrich Steidl","author_inst":"Albert Einstein College of Medicine"},{"author_name":"Robert A Coleman","author_inst":"Albert Einstein College of Medicine"}],"rel_date":"2026-03-06","rel_site":"biorxiv"},{"rel_title":"A Common Missense Variant, W335S, in \u03b22-Glycoprotein I (APOH) is Associated with Increased Autoantibody Levels but Reduced Venous Thromboembolism Risk","rel_doi":"10.64898\/2026.03.04.26347632","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347632","rel_abs":"Anti-{beta}2-glycoprotein I (anti-{beta}2GPI) antibodies are central to the pathogenesis of antiphospholipid syndrome (APS), an autoimmune disease characterized by a strong predisposition to venous thromboembolism (VTE). In this study, we conducted a multi-ancestry genome-wide association study (GWAS) of quantitative total anti-{beta}2GPI levels in 5,969 participants enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) and identified a genome-wide significant association at the APOH locus. Paradoxically, genetically determined increases in anti-{beta}2GPI levels at this locus were associated with lower VTE risk. Fine-mapping and functional genomics prioritized the missense variant rs1801690 (W335S) in {beta}2GPI (apolipoprotein H, [APOH]) as the most likely causal variant. This variant has an allele frequency of 5-6% in European and East Asian ancestries but only 1% in African ancestries. Integrating prior experimental studies, molecular dynamics simulations and structure-based epitope prediction, we propose a dual-effect mechanism whereby W335S reduces thrombotic risk by disrupting phospholipid binding in Domain V, yet increases autoantibody production through conformational changes that enhance epitope exposure in Domains I and II. These findings mechanistically uncouple autoantibody formation from thrombotic risk in carriers of the W335S variant, and suggest that APOH genotype may represent a clinically relevant genetic biomarker with potential utility for thrombotic risk stratification in anti-{beta}2GPI-positive individuals.","rel_num_authors":10,"rel_authors":[{"author_name":"Christophe Lalaurie","author_inst":"University College London"},{"author_name":"Lili Liu","author_inst":"University of Michigan"},{"author_name":"Atlas Khan","author_inst":"Columbia University Medical Center"},{"author_name":"Chen Wang","author_inst":"Columbia University"},{"author_name":"Steve Rich","author_inst":"Virginia"},{"author_name":"R Graham Barr","author_inst":"Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center"},{"author_name":"Elana Bernstein","author_inst":"Columbia University"},{"author_name":"Krzysztof Kiryluk","author_inst":"Columbia University"},{"author_name":"Thomas C R McDonnell","author_inst":"University College London"},{"author_name":"Yiming Luo","author_inst":"Columbia University Irving Medical Center"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Longer Sleep Duration Predicts Progression to Bipolar or Psychotic Disorders in Youth accessing Early Intervention Mental Health Services","rel_doi":"10.64898\/2026.03.04.26347669","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347669","rel_abs":"BackgroundWhile growing evidence implicates sleep-wake and circadian rhythm disturbances (SCRDs) in the onset and course of mood and psychotic disorders, longitudinal studies using objective measures are limited. This clinical cohort study examined whether actigraphy-derived SCRDs (sleep duration, timing, and efficiency) predicted transition to (i) any full-threshold mental disorders; and then specifically: (ii) full-threshold bipolar or psychotic disorders or (iii) other full-threshold (i.e. depressive or anxiety) disorders, in youth accessing mental health care.\n\nMethodsActigraphy monitoring was completed for 5-23 days in 250 participants (aged 12-30) presenting to youth-focused early intervention services in Sydney, Australia. Participants were followed longitudinally as part of the Optymise cohort for 6+ months (up to 8 years; median 2.5 years). Logistic regression and Cox proportional hazard models estimated associations between SCRDs and illness progression, after controlling for relevant baseline clinical and demographic covariates (e.g., age, sex, social and occupational functioning, mania-like and psychotic-like experiences, medication use).\n\nResultsLonger sleep duration at baseline predicted higher odds of transition (OR = 2.23 [95%CI = 1.38-3.74]), and shorter time-to-transition (HR = 2.05 [95%CI = 1.23-3.40]) to full-threshold bipolar or psychotic disorders. This effect remained significant after controlling for clinical covariates. Later sleep midpoint predicted transition to any full-threshold mental disorder (OR = 1.46 [95%CI = 1.02-2.17]) at the uncorrected significance level.\n\nConclusionsExcessive sleep duration may represent an early marker of vulnerability for progression to severe mental illness. Findings support the prognostic utility of objective measures of SCRDs to guide indicated prevention and early intervention.","rel_num_authors":10,"rel_authors":[{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, University of Sydney"},{"author_name":"Jacob J Crouse","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Mathew Varidel","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Emiliana Tonini","author_inst":"Brain and Mind Centre, The University of Sydney"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, University of Sydney"},{"author_name":"Natalia Zmicerevska","author_inst":"Brain and Mind Centre, University of Sydney"},{"author_name":"Daniel F Hermens","author_inst":"University of the Sunshine Coast"},{"author_name":"Kathleen R Merikangas","author_inst":"National Institute of Mental Health"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, University of Sydney"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, University of Sydney"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Associations of Blood Biomarkers of Bone Turnover with Static Histomorphometry Parameters at the Hip in Patients with Chronic Kidney Disease Undergoing Surgery for Hip Fracture","rel_doi":"10.64898\/2026.03.04.26347613","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347613","rel_abs":"Individuals with chronic kidney disease (CKD) have higher rates of hip fracture and post-fracture mortality. Although they may develop age-related osteoporosis similar to those without CKD, they may also exhibit CKD-related metabolic bone disease (MBD), characterized by low, high, or mixed turnover at similar levels of bone mineral density (BMD). Because BMD does not provide information about turnover status, clinical decision-making is challenging. This study evaluated the associations between circulating bone-turnover biomarkers and static histomorphometry in patients undergoing hip-fracture surgery.\n\nIn this cross-sectional study, we enrolled adults with and without CKD, defined as estimated glomerular filtration rate (eGFR) [&le;]60 ml\/min\/1.73m{superscript 2} (CKD-EPI 2021), undergoing hip-fracture surgery. Blood samples, bone specimens from the femoral head or greater trochanter, and demographic and clinical data were collected at the time of surgery. Plasma biomarkers included -Klotho, bone alkaline phosphatase (BAP), dickkopf-related protein 1 (DKK-1), fibroblast growth factor 23 (FGF23), tartrate-resistant acid phosphatase 5b (TRAP5b), parathyroid hormone (PTH), and sclerostin. Logistic regression models, adjusted for age, gender, eGFR, and osteoporosis, assessed associations with CKD status. Tertiles of osteoblast surface (Ob.S\/BS) and eroded surface (ES\/BS) were defined in participants without CKD and applied to the full cohort. Multinomial and multivariable linear regression evaluated associations of biomarkers with these histomorphometry parameters.\n\nAmong 97 enrolled participants (mean age 80 {+\/-} 11 years; 67% female), 68% had CKD. Of 75 with complete biomarker and histomorphometry data, 96% demonstrated low bone turnover. CKD was associated with lower trabecular thickness (Tb.Th) and higher osteoid thickness (O.Th), osteoid volume (OV\/BV), and osteoid surface (OS\/BS), suggesting thinner, largely unmineralized trabeculae. Higher BAP (222.2% difference per doubling; 95% CI 77.2-485.8) and TRAP5b (319.3%; 95% CI 128.3-669.5) were directly associated with Ob.S\/BS and ES\/BS, whereas sclerostin was inversely associated with ES\/BS (-28.9%; 95% CI -44.8 to -7.1). PTH was not associated with bone-turnover measures.\n\nThese findings suggest that BAP, TRAP5b, and sclerostin may provide useful adjunct information alongside PTH for assessing bone turnover and guiding therapy in patients with and without CKD.","rel_num_authors":10,"rel_authors":[{"author_name":"Jan M Hughes-Austin","author_inst":"University of California, San Diego"},{"author_name":"Lauren Claravall","author_inst":"University of California, San Diego"},{"author_name":"Ronit Katz","author_inst":"University of Washington"},{"author_name":"Deborah M Kado","author_inst":"Stanford University"},{"author_name":"Alexandra K Schwartz","author_inst":"University of California, San Diego"},{"author_name":"William T Kent","author_inst":"University of California, San Diego"},{"author_name":"Paul Girard","author_inst":"University of California, San Diego"},{"author_name":"Renata C Pereira","author_inst":"University of California Los Angeles"},{"author_name":"Isidro B Salusky","author_inst":"University of California Los Angeles"},{"author_name":"Joachim H Ix","author_inst":"University of California, San Diego"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Elimination drives recovery in amatoxin-induced acute liver failure A globally applicable management framework: preserving toxin elimination enables transplant-free recovery","rel_doi":"10.64898\/2026.03.05.26345777","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26345777","rel_abs":"Amatoxin-induced acute liver failure complicates misidentified foraged mushroom ingestion worldwide; abrupt multisystem collapse punctuates apparent improvement. Our prospective single-arm clinical trial investigated proactive toxicokinetic-based management to preserve elimination capacity: sustained enhanced hydration to maintain renal clearance; fasting plus octreotide to suppress meal-driven enterohepatic circulation; and intravenous silibinin to inhibit OATP1B3-mediated hepatic uptake, enabling safe passage and elimination of gallbladder-confined amatoxin-laden bile. Safety population (N=99) transplant-free recovery (TFR): 88.0% (87 recoveries, 6 transplants, 6 deaths). Protocol-adherent Efficacy population (n=86) TFR: 98.8% (85 recoveries, 1 transplant, 0 deaths). Multivariable analysis identified uninterrupted hydration as strongest TFR predictor (P<0.001), followed by earlier silibinin initiation (P=0.003); octreotide shortened INR recovery by 11 hours (P=0.033). These findings support a toxin elimination model in which preserved renal clearance and biliary sequestration are central recovery determinants. The kinetic balance between renal clearance and hepatic uptake governs both recovery and collapse.","rel_num_authors":4,"rel_authors":[{"author_name":"S Todd Mitchell","author_inst":"Dominican Hospital; Santa Cruz, CA"},{"author_name":"Dan Spyker","author_inst":"Oregon Health & Science University, University of Virginia, University of Minnesota"},{"author_name":"Glenn Robbins","author_inst":"Dominican Hospital; Santa Cruz, CA"},{"author_name":"Barry Rumack","author_inst":"Rocky Mountain Poison and Drug Center, University of Colorado School of Medicine, The University of Chicago"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Elimination drives recovery in amatoxin-induced acute liver failure A globally applicable management framework: preserving toxin elimination enables transplant-free recovery","rel_doi":"10.64898\/2026.03.05.26345777","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26345777","rel_abs":"Amatoxin-induced acute liver failure complicates misidentified foraged mushroom ingestion worldwide; abrupt multisystem collapse punctuates apparent improvement. Our prospective single-arm clinical trial investigated proactive toxicokinetic-based management to preserve elimination capacity: sustained enhanced hydration to maintain renal clearance; fasting plus octreotide to suppress meal-driven enterohepatic circulation; and intravenous silibinin to inhibit OATP1B3-mediated hepatic uptake, enabling safe passage and elimination of gallbladder-confined amatoxin-laden bile. Safety population (N=99) transplant-free recovery (TFR): 88.0% (87 recoveries, 6 transplants, 6 deaths). Protocol-adherent Efficacy population (n=86) TFR: 98.8% (85 recoveries, 1 transplant, 0 deaths). Multivariable analysis identified uninterrupted hydration as strongest TFR predictor (P<0.001), followed by earlier silibinin initiation (P=0.003); octreotide shortened INR recovery by 11 hours (P=0.033). These findings support a toxin elimination model in which preserved renal clearance and biliary sequestration are central recovery determinants. The kinetic balance between renal clearance and hepatic uptake governs both recovery and collapse.","rel_num_authors":4,"rel_authors":[{"author_name":"S Todd Mitchell","author_inst":"Dominican Hospital; Santa Cruz, CA"},{"author_name":"Dan Spyker","author_inst":"Oregon Health & Science University, University of Virginia, University of Minnesota"},{"author_name":"Glenn Robbins","author_inst":"Dominican Hospital; Santa Cruz, CA"},{"author_name":"Barry Rumack","author_inst":"Rocky Mountain Poison and Drug Center, University of Colorado School of Medicine, The University of Chicago"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Dental teachers perspectives on Extended Reality in dental education: an international survey","rel_doi":"10.64898\/2026.03.05.26347677","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.05.26347677","rel_abs":"IntroductionDigital technologies are reshaping how health professionals are trained, and extended reality (XR) has gained attention as a tool for skills development in dental education. Yet, successful integration depends largely on educators perceptions, readiness, and working conditions. This study aimed to explore dental educators views of the educational value of XR, what barriers they experience, and how familiarity with immersive technologies relates to their use in teaching.\n\nMaterials and MethodsA cross-sectional, web-based survey was conducted among dental educators. The questionnaire included items on demographics, familiarity and frequency of XR use, and perceptions of educational value, barriers, and curricular integration. Descriptive statistics were calculated, and Spearman correlation analyses were performed to explore associations between familiarity, use, and perceived benefits of XR.\n\nResultsRespondents reported positive attitudes toward XR, particularly for improving students understanding of complex anatomy (mean = 6.02\/7), skill development (5.68\/7), and confidence and preparedness for clinical practice (5.08-5.20\/7). XR was mainly viewed as a complement to traditional teaching rather than a replacement (mean = 3.77\/7). Strong correlations were observed between perceived improvements in confidence, skills, and clinical readiness (r = 0.71 - 0.89, P < 0.0001). High costs, limited technical support, and time constraints were the most prominent barriers to usage.\n\nConclusionOverall, dental educators appear open to XR but constrained by structural and organizational factors rather than a lack of interest. Faculty development, hands-on training opportunities, and institutional support may therefore be essential to translating positive perceptions into meaningful and sustained integration of immersive technologies in dental curricula.","rel_num_authors":6,"rel_authors":[{"author_name":"Ruza Bjelovucic","author_inst":"Department of Dentistry and Oral Health, Aarhus University, Aarhus, Denmark"},{"author_name":"Bruna Neves de Freitas","author_inst":"Department of Dentistry and Oral Health, Aarhus University, Aarhus, Denmark, Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark"},{"author_name":"Sven Erik Norholt","author_inst":"Department of Dentistry and Oral Health, Aarhus University, Aarhus, Denmark, Department of Oral and Maxillofacial Surgery, Aarhus University Hospital, Aarhus, D"},{"author_name":"Pankaj Taneja","author_inst":"Sydney Dental Hospital, Sydney, New South Wales, Australia, Sydney Dental School, University of Sydney, Australia"},{"author_name":"Mette Terp Hoybye","author_inst":"Interacting Minds Centre, Department of Clinical Medicine, Aarhus University, University Research Clinic for Interdisciplinary Orthopedic Pathways (UCOP), Silke"},{"author_name":"Ruben Pauwels","author_inst":"Department of Dentistry and Oral Health, Aarhus University, Aarhus, Denmark"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"A Qualitative Study of Patient and Healthcare Provider Perspectives on Mobile Health Assessments for Cervical Spondylotic Myelopathy","rel_doi":"10.64898\/2026.03.04.26347622","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347622","rel_abs":"Objective: Evaluating and monitoring patients with cervical spondylotic myelopathy (CSM) remains a challenge due to limited tools for assessing objective neurological disability longitudinally and in the home environment. Given their prevalence and low cost, mobile health (mHealth), and specifically smartphone technologies offer a promising approach to fill this gap. This study explored stakeholder perspectives on the role of mHealth in CSM monitoring to inform development of a smartphone-based assessment application. Methods: We conducted semi-structured interviews with 15 patients with CSM and 14 healthcare providers (spine surgeons, physical therapists, and occupational therapists). Interviews explored current assessment practices, perceived limitations, and attitudes toward mHealth integration. Data were analyzed using thematic analysis. Results: Two major themes emerged from provider interviews: (1) diagnosing and monitoring CSM is challenging due to limitations in current tools, and (2) mHealth presents significant opportunities but requires thoughtful integration. Providers described current methods and technologies, clinical signs and symptoms, and challenges evaluating patients. Current tools were viewed as inadequate for precision medicine, with inter-rater variability and inability to capture real-world function. Within the second theme, providers identified ways mHealth could improve care, challenges for integration, and practical implementation considerations. Patients expressed strong interest in objective, longitudinal monitoring of gait, dexterity, and daily function. Conclusions: Stakeholders recognized substantial potential for mHealth to address unmet needs in CSM assessment. Successful implementation will require intuitive design, electronic medical record integration, and attention to accessibility. These findings provide a foundation for user-centered development of digital health tools in CSM care.","rel_num_authors":21,"rel_authors":[{"author_name":"Pranay Singh","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Sriharsha Gonuguntla","author_inst":"University of South Florida Morsani College of Medicine, Tampa, Florida, USA"},{"author_name":"Erdong Chen","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Aryan Pradhan","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Isaac Becker","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Nathan Xu","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Benjamin Steel","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Faraz Arkam","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Salim Yakdan","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Braeden Benedict","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Haris Naveed","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Zhuoran Wang","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Wenwen Guo","author_inst":"Saint Louis University School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Zachary Wilt","author_inst":"Rothman Orthopaedics, Philadelphia, Pennsylvania, USA"},{"author_name":"Jetan Badhiwala","author_inst":"Department of Surgery, University of Toronto, Toronto, Ontario, Canada"},{"author_name":"Daniel Hafez","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"John Ogunlade","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Wilson Z Ray","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"},{"author_name":"Zoher Ghogawala","author_inst":"Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA."},{"author_name":"Caitlin Kelleher","author_inst":"Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA."},{"author_name":"Jacob K Greenberg","author_inst":"Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA"}],"rel_date":"2026-03-05","rel_site":"medrxiv"},{"rel_title":"Integrative screening identifies functional variants and VNTRs underlying GWAS signals at the 5p15.33 multi-cancer susceptibility locus","rel_doi":"10.64898\/2026.03.03.26347427","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347427","rel_abs":"Chromosome 5p15.33 harbors several independent association signals which demonstrate antagonistic pleiotropy across cancer types, with causal mechanisms largely unresolved. To identify functional variants and enhancer elements at this locus, we performed statistical fine-mapping followed by massively parallel reporter assays (MPRA) and proliferation based CRISPRi screens. This approach identified eight multi-cancer functional variants (MCFVs) across three GWAS signals. Targeting rs421629 (part of the CLPTM1L signal marked by rs465498) with CRISPRi revealed opposing effects on TERT expression in pancreatic versus lung cancer cells, consistent with the antagonistic pleiotropy observed for this signal. Furthermore, CRISPRi nominated an intronic CLPTM1L variable number tandem repeat (VNTR) as a potent enhancer. Long-read sequencing established VNTR polymorphisms as potential causal variants for the rs465498 signal. We showed that Hippo-pathway transcription factors mediate VNTR enhancer activity in lung and pancreatic cancer cells. Together, these findings indicate that cancer susceptibility at 5p15.33 may be mediated by both SNPs and VNTRs and provide an integrated framework for resolving complex pleiotropic loci.","rel_num_authors":47,"rel_authors":[{"author_name":"Aidan O'Brien","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Hyunkyung Kong","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Harsh Patel","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Michelle Ho","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Minal B Patel","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Jun Zhong","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Mai Xu","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Brenen W Papenberg","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Katelyn E Connelly","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Irene Collins","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Rebecca Hennessey","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Rohit Thakur","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Hayley Sowards","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Karen Funderburk","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Thong Luong","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Oscar Florez-Vargas","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Timothy Myers","author_inst":"Laboratory of Genetic Susceptibility, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Ashley Jermusyk","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Bryan Gorman","author_inst":"Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Wen Luo","author_inst":"Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Kristine Jones","author_inst":"Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Sudipto Das","author_inst":"CCR Protein and Metabolite Characterization Core (PMCC), Frederick National Laboratory for Cancer Research, National Cancer Institute"},{"author_name":"Qing Lan","author_inst":"Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Nathaniel Rothman","author_inst":"Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"James D McKay","author_inst":"International Agency for Research on Cancer, , World Health Organization"},{"author_name":"Rayjean J Hung","author_inst":"Lunenfeld-Tanenbaum Research Institute, , Sinai Health"},{"author_name":"Christopher I Amos","author_inst":"Department of Internal Medicine, , University of New Mexico"},{"author_name":"Mark M Iles","author_inst":"Leeds Institute for Data Analytics, , University of Leeds"},{"author_name":"Stella Koutros","author_inst":"Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Maria Teresa Landi","author_inst":"Trans-Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Matthew H Law","author_inst":"Statistical Genetics, , QIMR Berghofer Medical Research Institute"},{"author_name":"Rachael Z Stolzenberg-Solomon","author_inst":"Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Brian Wolpin","author_inst":"Department of Medical Oncology, , Dana-Farber Harvard Cancer Center"},{"author_name":"Manal Hassan","author_inst":"Department of Gastrointestinal Medical Oncology, Division of Cancer Prevention and Population Sciences, MD Anderson Cancer Center"},{"author_name":"Alison P Klein","author_inst":"Departments of Oncology, Pathology and Medicine, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine"},{"author_name":"Samuel O Antwi","author_inst":"Department of Quantitative Health Sciences, Division of Epidemiology,, Mayo Clinic"},{"author_name":"Nick Orr","author_inst":"The Johnston Cancer Research Centre, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast"},{"author_name":"Stephen J Chanock","author_inst":"Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Sara Lindstroem","author_inst":"Department of Epidemiology, , University of Washington"},{"author_name":"Jason W Hoskins","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Marc-Henri Stern","author_inst":"Inserm U1339 UMR3666, DNA Repair and Uveal Melanoma (D.R.U.M.), Institut Curie, PSL Research University"},{"author_name":"Thorkell Andresson","author_inst":"CCR Protein and Metabolite Characterization Core (PMCC), Frederick National Laboratory for Cancer Research, National Cancer Institute"},{"author_name":"Jianxin Shi","author_inst":"Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Ludmila Prokunina-Olsson","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Jiyeon Choi","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Kevin M Brown","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"},{"author_name":"Laufey T Amundadottir","author_inst":"Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Can AI Match Human Experts? Evaluating LLM-Generated Feedback on Resident Scholarly Projects","rel_doi":"10.64898\/2026.03.04.26346878","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26346878","rel_abs":"BackgroundDelivering timely, high-quality feedback on resident scholarly projects is labour-intensive, especially in large programmes. We developed an AI-assisted evaluation system, powered by the open-weight LLaMA-3.1 large-language model (LLM), to generate formative feedback on Family Medicine residents scholarly projects and compared its performance with expert human evaluators.\n\nMethodsWe evaluated whether the AI-generated feedback achieves comparable quality to expert feedback. The tool ingests heterogeneous resident submissions (PDFs, scans, photographs) via OCR and produces section-by-section feedback aligned with programme rubrics. In a three-phase study we evaluated 240 feedback reports (Short, Question and Timeline, Final; n = 80 each). Within each phase, 40 reports were AI-generated and 40 produced by research experts across four project types: Quality Improvement, Survey-Based, Research, and Literature Review. Blinded raters used a 25-item survey across five constructs: understanding & reasoning, trust & confidence, quality of information, expression style & persona, safety & harm.\n\nResultsSurvey reliability was high across phases ( = .71-.98). Human feedback generally out-scored AI. In short reports, humans led on quality (Mean {+\/-} SD; 4.14 {+\/-} 0.57 vs 3.09 {+\/-} 1.05) and trust (3.96 {+\/-} 0.71 vs 2.78 {+\/-} 1.15). In final reports, differences become small for quality (4.09 {+\/-} 0.65 vs 3.49 {+\/-} 0.68) and persona (4.16 {+\/-} 0.40 vs 3.91 {+\/-} 0.50), while AI was preferred for safety (4.50 {+\/-} 0.60 vs 4.36 {+\/-} 0.56). Performance varied by project type: in survey-based final reports the AI led on quality (4.28 {+\/-} 0.50 vs 3.98 {+\/-} 0.44) and safety (4.58 {+\/-} 0.40 vs 4.24 {+\/-} 0.67), whereas in quality-improvement short reports humans were markedly superior in reasoning (4.27 {+\/-} 0.68 vs 2.33 {+\/-} 1.00).\n\nConclusionsAn open-weight LLM with curated prompts can generate rubric-aligned feedback at scale that approaches the quality of expert human feedback. While expert feedback remained superior overall, AI surpassed humans in selected contexts and safety assessments. Performance of the tool will increase over time as newer and more capable open-weight models are released. Our code and systems prompts are open source.","rel_num_authors":9,"rel_authors":[{"author_name":"Zack van Allen","author_inst":"University of Ottawa"},{"author_name":"Sylvie Forgues-Martel","author_inst":"University of Ottawa"},{"author_name":"Maddie J Venables","author_inst":"University of Ottawa"},{"author_name":"Yosr Ghanney","author_inst":"College La Cite"},{"author_name":"Alexandre Villeneuve","author_inst":"College La Cite"},{"author_name":"Jarvis Dongmo","author_inst":"University of Ottawa"},{"author_name":"Meherin Ahmed","author_inst":"University of Ottawa"},{"author_name":"Douglas Archibald","author_inst":"University of Ottawa"},{"author_name":"Kheira Jolin-Dahel","author_inst":"University of Ottawa"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Can AI Match Human Experts? Evaluating LLM-Generated Feedback on Resident Scholarly Projects","rel_doi":"10.64898\/2026.03.04.26346878","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26346878","rel_abs":"BackgroundDelivering timely, high-quality feedback on resident scholarly projects is labour-intensive, especially in large programmes. We developed an AI-assisted evaluation system, powered by the open-weight LLaMA-3.1 large-language model (LLM), to generate formative feedback on Family Medicine residents scholarly projects and compared its performance with expert human evaluators.\n\nMethodsWe evaluated whether the AI-generated feedback achieves comparable quality to expert feedback. The tool ingests heterogeneous resident submissions (PDFs, scans, photographs) via OCR and produces section-by-section feedback aligned with programme rubrics. In a three-phase study we evaluated 240 feedback reports (Short, Question and Timeline, Final; n = 80 each). Within each phase, 40 reports were AI-generated and 40 produced by research experts across four project types: Quality Improvement, Survey-Based, Research, and Literature Review. Blinded raters used a 25-item survey across five constructs: understanding & reasoning, trust & confidence, quality of information, expression style & persona, safety & harm.\n\nResultsSurvey reliability was high across phases ( = .71-.98). Human feedback generally out-scored AI. In short reports, humans led on quality (Mean {+\/-} SD; 4.14 {+\/-} 0.57 vs 3.09 {+\/-} 1.05) and trust (3.96 {+\/-} 0.71 vs 2.78 {+\/-} 1.15). In final reports, differences become small for quality (4.09 {+\/-} 0.65 vs 3.49 {+\/-} 0.68) and persona (4.16 {+\/-} 0.40 vs 3.91 {+\/-} 0.50), while AI was preferred for safety (4.50 {+\/-} 0.60 vs 4.36 {+\/-} 0.56). Performance varied by project type: in survey-based final reports the AI led on quality (4.28 {+\/-} 0.50 vs 3.98 {+\/-} 0.44) and safety (4.58 {+\/-} 0.40 vs 4.24 {+\/-} 0.67), whereas in quality-improvement short reports humans were markedly superior in reasoning (4.27 {+\/-} 0.68 vs 2.33 {+\/-} 1.00).\n\nConclusionsAn open-weight LLM with curated prompts can generate rubric-aligned feedback at scale that approaches the quality of expert human feedback. While expert feedback remained superior overall, AI surpassed humans in selected contexts and safety assessments. Performance of the tool will increase over time as newer and more capable open-weight models are released. Our code and systems prompts are open source.","rel_num_authors":9,"rel_authors":[{"author_name":"Zack van Allen","author_inst":"University of Ottawa"},{"author_name":"Sylvie Forgues-Martel","author_inst":"University of Ottawa"},{"author_name":"Maddie J Venables","author_inst":"University of Ottawa"},{"author_name":"Yosr Ghanney","author_inst":"College La Cite"},{"author_name":"Alexandre Villeneuve","author_inst":"College La Cite"},{"author_name":"Jarvis Dongmo","author_inst":"University of Ottawa"},{"author_name":"Meherin Ahmed","author_inst":"University of Ottawa"},{"author_name":"Douglas Archibald","author_inst":"University of Ottawa"},{"author_name":"Kheira Jolin-Dahel","author_inst":"University of Ottawa"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"A tool to evaluate the impact of lived experience involvement in research: the Brain and Genomics Hub: Impact Log literature review and protocol.","rel_doi":"10.64898\/2026.03.04.26347596","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347596","rel_abs":"BackgroundDespite widespread recognition of the value of lived experience (LE) involvement in healthcare research and increased LE involvement activity, we lack established implementation methods and instruments for reporting and evaluating impact. We present a protocol for an innovative LE-led Impact Log tool and co-production framework, which may help to address some fundamental barriers to co-production. The Impact Log will be implemented within a five-year multidisciplinary transdiagnostic research project on severe mental illness, the Brain and Genomics Hub of the UKRI Mental Health Platform, and is also designed for wider adaptation and use. Part I presents a short narrative review of literature pertaining to defining, evaluating, and enhancing the impact of co-production, to provide in-depth background and aid future development. Part II presents the Impact Log protocol.\n\nMethodsThe Impact Log framework is designed to integrate inclusive and impactful co-production throughout all research stages, and to record and evaluate its impact across three domains using an accessible short form. The three research domains are: design and delivery; interpersonal and environmental aspects; systems and processes. Impact Log design and implementation is led by LE study leads and a specialist advisory panel, who are integrated fully within the wider research team, and all have combined research experience and LE of bipolar or psychotic disorders. All Hub research participants will be offered accessible opportunities for remunerated lived experience input, and there will be outreach to ensure diverse representation, aided by the Hubs charity partners. Data collection and analysis will be LE led and will include iterative analysis to inform continuing development. Diverse formal and informal dissemination throughout the project will maximise wider stakeholder engagement.\n\nDiscussionThe potential value of this research is to implement a novel tool and framework for facilitating, recording and evaluating co-production in complex mental health research, which can be adapted for wider use. Strengths in design are LE leadership and cross-cutting LE research integration, incorporation of multiple domains, and a focus on facilitating diversity and inclusion within co-production. Potential limitations for this project and wider adaptation may include limited resources, risk of bias and health challenges.\n\nLay SummaryWe have provided a brief lay summary to help people without a research background understand our project.\n\nThis article explains our plan to develop and test a new way of understanding how research changes when people with personal experience of a mental health condition are part of the research team. We are a team of mental health researchers and many of us have direct experience of bipolar and psychosis. We work alongside other researchers, including people who might also have worked in mental health services or in charities that provide support. Our research project aims to better understand what is happening in the brain, body, lives and experiences of people who have bipolar and psychosis. Many people believe that research is better when it includes the views of people who have direct experience of the health condition being studied. This is called \"lived experience\". We have developed a structured approach to make sure that people with lived experience are meaningfully involved in our research team. We have also created a simple tool, called the Impact Log, to record when lived experience members contribute and to help us understand how their involvement influences the research. Finally, we wanted to better understand what other researchers have said about lived experience involvement. We reviewed many published academic studies and reports and brought their findings together in what is called a \"narrative review\". This review summarises what is already known about the difference lived experience involvement can make in research.","rel_num_authors":19,"rel_authors":[{"author_name":"Tania Gergel","author_inst":"University College London"},{"author_name":"Talen Wright","author_inst":"University of Ottawa"},{"author_name":"Lavenda Geshica","author_inst":"University of Glasgow"},{"author_name":"Emily Vicary","author_inst":"University of Manchester"},{"author_name":"Jaycee Kennett","author_inst":"University College London"},{"author_name":"Oli Delgaram-Nejad","author_inst":"Independent Researcher"},{"author_name":"Carina Edwards","author_inst":"Independent Researcher"},{"author_name":"Hashwin Ganesh","author_inst":"Caprich International Ltd."},{"author_name":"Thomas Kabir","author_inst":"University of Oxford"},{"author_name":"Chloe L. Harrison","author_inst":"Adferiad"},{"author_name":"James Heard","author_inst":"Adferiad"},{"author_name":"Georgia Dash","author_inst":"Cardiff University"},{"author_name":"Catherine Bresner","author_inst":"Cardiff University"},{"author_name":"Ian Jones","author_inst":"Cardiff University"},{"author_name":"Jeremy Hall","author_inst":"Cardiff University"},{"author_name":"Ann John","author_inst":"Swansea University"},{"author_name":"Neil Harrison","author_inst":"Cardiff University"},{"author_name":"James T.R. Walters","author_inst":"Cardiff University"},{"author_name":"Sophie E. Legge","author_inst":"Cardiff University"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"A tool to evaluate the impact of lived experience involvement in research: the Brain and Genomics Hub: Impact Log literature review and protocol.","rel_doi":"10.64898\/2026.03.04.26347596","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347596","rel_abs":"BackgroundDespite widespread recognition of the value of lived experience (LE) involvement in healthcare research and increased LE involvement activity, we lack established implementation methods and instruments for reporting and evaluating impact. We present a protocol for an innovative LE-led Impact Log tool and co-production framework, which may help to address some fundamental barriers to co-production. The Impact Log will be implemented within a five-year multidisciplinary transdiagnostic research project on severe mental illness, the Brain and Genomics Hub of the UKRI Mental Health Platform, and is also designed for wider adaptation and use. Part I presents a short narrative review of literature pertaining to defining, evaluating, and enhancing the impact of co-production, to provide in-depth background and aid future development. Part II presents the Impact Log protocol.\n\nMethodsThe Impact Log framework is designed to integrate inclusive and impactful co-production throughout all research stages, and to record and evaluate its impact across three domains using an accessible short form. The three research domains are: design and delivery; interpersonal and environmental aspects; systems and processes. Impact Log design and implementation is led by LE study leads and a specialist advisory panel, who are integrated fully within the wider research team, and all have combined research experience and LE of bipolar or psychotic disorders. All Hub research participants will be offered accessible opportunities for remunerated lived experience input, and there will be outreach to ensure diverse representation, aided by the Hubs charity partners. Data collection and analysis will be LE led and will include iterative analysis to inform continuing development. Diverse formal and informal dissemination throughout the project will maximise wider stakeholder engagement.\n\nDiscussionThe potential value of this research is to implement a novel tool and framework for facilitating, recording and evaluating co-production in complex mental health research, which can be adapted for wider use. Strengths in design are LE leadership and cross-cutting LE research integration, incorporation of multiple domains, and a focus on facilitating diversity and inclusion within co-production. Potential limitations for this project and wider adaptation may include limited resources, risk of bias and health challenges.\n\nLay SummaryWe have provided a brief lay summary to help people without a research background understand our project.\n\nThis article explains our plan to develop and test a new way of understanding how research changes when people with personal experience of a mental health condition are part of the research team. We are a team of mental health researchers and many of us have direct experience of bipolar and psychosis. We work alongside other researchers, including people who might also have worked in mental health services or in charities that provide support. Our research project aims to better understand what is happening in the brain, body, lives and experiences of people who have bipolar and psychosis. Many people believe that research is better when it includes the views of people who have direct experience of the health condition being studied. This is called \"lived experience\". We have developed a structured approach to make sure that people with lived experience are meaningfully involved in our research team. We have also created a simple tool, called the Impact Log, to record when lived experience members contribute and to help us understand how their involvement influences the research. Finally, we wanted to better understand what other researchers have said about lived experience involvement. We reviewed many published academic studies and reports and brought their findings together in what is called a \"narrative review\". This review summarises what is already known about the difference lived experience involvement can make in research.","rel_num_authors":19,"rel_authors":[{"author_name":"Tania Gergel","author_inst":"University College London"},{"author_name":"Talen Wright","author_inst":"University of Ottawa"},{"author_name":"Lavenda Geshica","author_inst":"University of Glasgow"},{"author_name":"Emily Vicary","author_inst":"University of Manchester"},{"author_name":"Jaycee Kennett","author_inst":"University College London"},{"author_name":"Oli Delgaram-Nejad","author_inst":"Independent Researcher"},{"author_name":"Carina Edwards","author_inst":"Independent Researcher"},{"author_name":"Hashwin Ganesh","author_inst":"Caprich International Ltd."},{"author_name":"Thomas Kabir","author_inst":"University of Oxford"},{"author_name":"Chloe L. Harrison","author_inst":"Adferiad"},{"author_name":"James Heard","author_inst":"Adferiad"},{"author_name":"Georgia Dash","author_inst":"Cardiff University"},{"author_name":"Catherine Bresner","author_inst":"Cardiff University"},{"author_name":"Ian Jones","author_inst":"Cardiff University"},{"author_name":"Jeremy Hall","author_inst":"Cardiff University"},{"author_name":"Ann John","author_inst":"Swansea University"},{"author_name":"Neil Harrison","author_inst":"Cardiff University"},{"author_name":"James T.R. Walters","author_inst":"Cardiff University"},{"author_name":"Sophie E. Legge","author_inst":"Cardiff University"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Associations of alcohol use in early and middle adulthood with mid- and late-life cognition - a synthetic cohort approach","rel_doi":"10.64898\/2026.02.27.26346914","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.02.27.26346914","rel_abs":"OBJECTIVEUsing two cohorts and synthetic datasets, we estimated effects of prospectively reported alcohol use on memory outcomes across middle age.\n\nMETHODSData were from National Longitudinal Study of Youth 1979 (NLSY79, n=7540, alcohol reports from ages 18-26), Health and Retirement Study (HRS age 50-56 at enrollment, n=13,090), and a synthetic cohort matching early life exposure information from 3,259 NLSY79 participants to later life memory information from 5,451 HRS participants. Covariate-adjusted linear mixed models regressed memory (word list recall) on alcohol use (none, light\/moderate, heavy).\n\nRESULTSIn NLSY, we found no evidence that associations between light\/moderate drinking in early adulthood and mid-life memory score significantly differed from associations between drinking abstention ({beta} = -0.09 (95% CI: -0.30, 0.11)) or heavy drinking ({beta} = -0.26 (-0.48, -0.04)) with memory score. In HRS, both abstaining from alcohol ({beta} = -0.14 (-0.25, -0.02)) and heavy drinking ({beta} = -0.25 (-0.42, -0.07)) were negatively associated with cognitive level. Results from the synthetic cohort mirrored NLSY, suggesting no significant association between abstention ({beta} = 0.13 (-0.10,0.36)) nor heavy drinking ({beta} = 0.02 (-0.25,0.28)) with mid-to-late life memory score.\n\nDISCUSSIONAlcohol consumption may not have an effect on memory until later life, though associations may be affected by residual confounding.","rel_num_authors":5,"rel_authors":[{"author_name":"Peter Toyokazu Buto","author_inst":"Department of Epidemiology, Boston University School of Public Health"},{"author_name":"Scott C Zimmerman","author_inst":"Department of Epidemiology, Boston University School of Public Health"},{"author_name":"Katrina Kezios","author_inst":"Department of Epidemiology, Boston University School of Public Health"},{"author_name":"Adina Zeki Al Hazzouri","author_inst":"Mailman School of Public Health, Columbia University"},{"author_name":"M Maria Glymour","author_inst":"Department of Epidemiology, Boston University School of Public Health"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Suicidality and Drug Use Behavior Among Perinatal Individuals in Recovery","rel_doi":"10.64898\/2026.03.03.26347368","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347368","rel_abs":"IntroductionMaternal mental health conditions, comprising maternal suicide and drug overdose, are currently the leading cause of maternal mortality in the United States. However, the relationship between suicidality and drug use behavior in the perinatal period is not well understood. We examined the association between suicidality and drug use behavior among perinatal individuals. Given the racial disparities in both drug use and suicide rates in the U.S., we also examined any differences in suicidality and drug use behavior by race.\n\nMethodsParticipants were recruited from a High-Risk Obstetric & Gynecological Clinic in the Midwestern U.S that specializes in providing obstetric care to perinatal individuals who have histories or current use of opioids and other illicit drugs. Participants (N = 66) were a sub-sample of a larger cohort enrolled in an mHealth intervention to support recovery from opioid and stimulant use disorders. We performed chi-square tests and t-tests to examine any significant associations between lifetime suicidality and drug use behavior during the perinatal period.\n\nResultsThe final analytic sample included participants who had responded to the suicidality survey questions (n=43). Nearly 40% (n=16) of our sample endorsed a lifetime history of suicidal thoughts and behaviors (SITB). Of those, 87% (n=15) reported a previous suicide attempt. SITB was significantly associated with cravings for opioids during the perinatal period (p = .01) as well as comorbidities with perinatal anxiety symptoms? ( p < .05), depression symptoms? (p < .05), and bipolar disorder (p < .05). A higher proportion of recent cannabis use was found among mothers with SITB, compared to those without SITB (p=0.04). Mothers with SITB also had a strong positive correlation between preconception and postnatal nicotine use compared to mothers without SITB (p < .01). Finally, while white mothers endorsed more lifetime overdoses (p= 0.01), Black mothers endorsed higher cravings for opioids during pregnancy (p = 0.03).\n\nConclusionsA history of SITB is a distinct risk factor for both illicit and recreational drug use behavior in the perinatal period, and frequently co-occurs with other perinatal mental health conditions. Further research is needed to better understand the directionality of this relationship and the complex interplay between high risk drug use behavior and suicidality.","rel_num_authors":5,"rel_authors":[{"author_name":"Anna Constantino-Pettit","author_inst":"Washington University in St. Louis"},{"author_name":"Xiao Li","author_inst":"Washington University in St. Louis"},{"author_name":"Hannah Szlyk","author_inst":"Washington University in St. Louis"},{"author_name":"Erin Kasson","author_inst":"Washington University in St. Louis"},{"author_name":"Patricia Cavazos-Rehg","author_inst":"Washington University in St. Louis"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Health insurance in Nigeria: Findings from the People's Voice Survey","rel_doi":"10.64898\/2026.03.03.26347555","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347555","rel_abs":"The recent Lancet Commission on Nigerias health system highlighted high out of pocket expenditures on health and underfunding of the public health sector as major obstacles to Nigerias achievement of the Sustainable Development Goals. Nigeria has sought to address these gaps by extending health insurance coverage. This paper measures health insurance coverage and access to care in Nigeria circa 2023, using the first round of the Peoples Voice Survey (PVS). We analyze health insurance coverage by calculating coverage rates and using multivariate logistic regression to estimate associations between insurance coverage, socioeconomic characteristics, and health system utilization. In 2023, only 2% of Nigerians had insurance from the National Health Insurance Scheme; higher education and higher income levels were the most notable predictors of NHIS access. Chronic illness and self-reported health were not associated with insurance status. Respondents with insurance were less likely to use public sector primary care providers as their usual source of care, and were more likely to use private hospitals. Those with insurance are also more likely to have had an inpatient hospitalization in the preceding year, and more likely to have received key preventive screenings. While those with insurance receive more and better care in Nigeria, insurance access has been limited to relatively advantaged population groups. Rapid mobile phone-based surveys such as PVS could help policymakers in Nigeria track insurance coverage and whether it contributes to reversal of these trends over time.","rel_num_authors":7,"rel_authors":[{"author_name":"Kevin Croke","author_inst":"Harvard University"},{"author_name":"Chike Nwangwu","author_inst":"NOI Polls"},{"author_name":"Olufunke Bamidele Fasawe","author_inst":"Clinton Health Access Initiative"},{"author_name":"Ifeyinwa Aniebo","author_inst":"African Center for Excellence in the Genomics of Infectious Disease"},{"author_name":"Karima Ladhani","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Oyebanji Filani","author_inst":"Ekiti State Ministry of Health and Human Services"},{"author_name":"Margaret  E. Kruk","author_inst":"Washington University In St Louis: Washington University in St Louis"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Health insurance in Nigeria: Findings from the People's Voice Survey","rel_doi":"10.64898\/2026.03.03.26347555","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347555","rel_abs":"The recent Lancet Commission on Nigerias health system highlighted high out of pocket expenditures on health and underfunding of the public health sector as major obstacles to Nigerias achievement of the Sustainable Development Goals. Nigeria has sought to address these gaps by extending health insurance coverage. This paper measures health insurance coverage and access to care in Nigeria circa 2023, using the first round of the Peoples Voice Survey (PVS). We analyze health insurance coverage by calculating coverage rates and using multivariate logistic regression to estimate associations between insurance coverage, socioeconomic characteristics, and health system utilization. In 2023, only 2% of Nigerians had insurance from the National Health Insurance Scheme; higher education and higher income levels were the most notable predictors of NHIS access. Chronic illness and self-reported health were not associated with insurance status. Respondents with insurance were less likely to use public sector primary care providers as their usual source of care, and were more likely to use private hospitals. Those with insurance are also more likely to have had an inpatient hospitalization in the preceding year, and more likely to have received key preventive screenings. While those with insurance receive more and better care in Nigeria, insurance access has been limited to relatively advantaged population groups. Rapid mobile phone-based surveys such as PVS could help policymakers in Nigeria track insurance coverage and whether it contributes to reversal of these trends over time.","rel_num_authors":7,"rel_authors":[{"author_name":"Kevin Croke","author_inst":"Harvard University"},{"author_name":"Chike Nwangwu","author_inst":"NOI Polls"},{"author_name":"Olufunke Bamidele Fasawe","author_inst":"Clinton Health Access Initiative"},{"author_name":"Ifeyinwa Aniebo","author_inst":"African Center for Excellence in the Genomics of Infectious Disease"},{"author_name":"Karima Ladhani","author_inst":"Harvard T.H. Chan School of Public Health"},{"author_name":"Oyebanji Filani","author_inst":"Ekiti State Ministry of Health and Human Services"},{"author_name":"Margaret  E. Kruk","author_inst":"Washington University In St Louis: Washington University in St Louis"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Modelling the impact of long-acting monoclonal antibody, maternal vaccine and hybrid programs of RSV immunisation in temperate Western Australia","rel_doi":"10.64898\/2026.03.02.26347477","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347477","rel_abs":"BackgroundTwo RSV immunisations products: a maternal vaccine, Abrysvo, and a long-acting monoclonal antibody, nirsevimab, both designed to prevent RSV illness in infants, have recently become available. Modelling evidence is required to inform how to optimally use these products in immunisation programs to reduce the burden of RSV in young children.\n\nMethodsWe extend a dynamic transmission model calibrated to RSV-hospitalisation data of children aged < 5 years in temperate Western Australia (WA) to simulate a range of potential RSV immunisation programs. Using our model, we estimate the impact of both single-product and hybrid RSV immunisation programs. The analysis considers timing of administration, coverage levels and targeting of high-risk groups. Impact on RSV burden is analysed in the context of the WA setting and the possible significant cost differences between the two products.\n\nResultsAll programs analysed were effective in reducing RSV burden. Programs using nirsevimab for newborn infants at similar coverage levels to the Abrysvo programs, averted more RSV-hospitalisations annually. Seasonal programs that focused on protection during high RSV activity and programs targeting high-risk infants were the most efficient in reducing RSV burden. When dose cost is considered alongside program impact on RSV burden, we find evidence to support further economic analysis of hybrid programs as they could mitigate the cost differential between the two products while remaining highly effective in reducing RSV burden.\n\nConclusionsOur study is the first to comprehensively analyse hybrid RSV immunisation programs that use Abrysvo and nirsevimab. RSV immunisation programs can substantially reduce the burden of RSV in young children. Our modelling analysis provides evidence on immunisation type, timing, coverage, high-risk groups and dosage cost that will support decision makers and can be used in economic evaluations.","rel_num_authors":5,"rel_authors":[{"author_name":"Fiona Giannini","author_inst":"The Kids Research Institute Australia"},{"author_name":"Alexandra B Hogan","author_inst":"UNSW Sydney"},{"author_name":"Christopher C Blyth","author_inst":"The Kids Research Institute Australia"},{"author_name":"Kathryn Glass","author_inst":"Australian National University"},{"author_name":"Hannah C. Moore","author_inst":"The Kids Research Institute Australia"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Insights from the second season of collaborative influenza forecasting in Italy with updated targets incorporating virological information","rel_doi":"10.64898\/2026.03.04.26347601","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.04.26347601","rel_abs":"We present results from the second season of Influcast, a multi-model collaborative forecasting hub focused on influenza in Italy. During the 2024\/25 winter season, Influcast collected one-to four-week-ahead probabilistic forecasts of influenza-like illness (ILI) incidence alongside influenza A and B ILI+ incidence signals. New ILI+ targets were constructed integrating syndromic surveillance data with virological detections collected weekly by the Italian National Institute of Health. Forecasts were submitted by six independent models (including compartmental, metapopulation, and statistical approaches) and combined into an ensemble. Ensemble forecasts for ILI+ consistently outperformed both the baseline (a naive persistence model) and most individual models in terms of Weighted Interval Score (WIS), Absolute Error (AE), and prediction coverage. Importantly, ensemble ILI+ forecasts achieved significantly lower WIS and AE ratios (i.e., ratio between the ensemble and the baseline models) and improved calibration compared to ILI forecasts. Our findings support the integration of virological surveillance data in forecasting target definition to improve the reliability of epidemic forecasts and strengthen their utility for situational awareness, communication, and targeted intervention.","rel_num_authors":23,"rel_authors":[{"author_name":"Stefania Fiandrino","author_inst":"Sapienza University of Rome; ISI Foundation"},{"author_name":"Tommaso Bertola","author_inst":"Department of Physics and Astronomy \"Galileo Galilei\", University of Padua, Padova, Italy; Istituto Nazionale di Fisica Nucleare, Sez., Padova, Italy; Center fo"},{"author_name":"Valeria D'Andrea","author_inst":"Department of Physics and Astronomy \"Galileo Galilei\", University of Padua, Padova, Italy; Istituto Nazionale di Fisica Nucleare, Sez., Padova, Italy"},{"author_name":"Manlio De Domenico","author_inst":"Department of Physics and Astronomy \"Galileo Galilei\", University of Padua, Padova, Italy; Istituto Nazionale di Fisica Nucleare, Sez., Padova, Italy; Padua Cen"},{"author_name":"Elisa Viola","author_inst":"Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy; ISI Foundation, Turin, Italy"},{"author_name":"Lorenzo Zino","author_inst":"Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy"},{"author_name":"Mattia Mazzoli","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Alessandro Rizzo","author_inst":"Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy"},{"author_name":"Yuhan Li","author_inst":"School of Mathematical Sciences, Queen Mary University of London, UK"},{"author_name":"Nicola Perra","author_inst":"School of Mathematical Sciences, Queen Mary University of London, UK"},{"author_name":"Marika Sartore","author_inst":"Department of Physics and Astronomy \"Galileo Galilei\", University of Padua, Padova, Italy"},{"author_name":"Razieh Masoumi","author_inst":"Department of Molecular Medicine, University of Padova, Padova, Italy; University of Pittsburgh, School of Computing and Information, Pittsburgh, PA, USA"},{"author_name":"Chiara Poletto","author_inst":"Department of Molecular Medicine, University of Padova, Padova, Italy"},{"author_name":"Alberto Mateo Urdiales","author_inst":"Istituto Superiore di Sanita'"},{"author_name":"Antonino Bella","author_inst":"Istituto Superiore di Sanita'"},{"author_name":"Corrado Gioannini","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Paolo Milano","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Daniela Paolotti","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Marco Quaggiotto","author_inst":"Department of Design, Politecnico di Milano, Italy; ISI Foundation, Turin, Italy"},{"author_name":"Luca Rossi","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Ivan Vismara","author_inst":"ISI Foundation, Turin, Italy"},{"author_name":"Alessandro Vespignani","author_inst":"Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA; ISI Foundation, Turin, Italy"},{"author_name":"Nicolo' Gozzi","author_inst":"ISI Foundation, Turin, Italy"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Distinct Inflammatory Profiles in Angiography-Negative Subarachnoid Hemorrhage: A Focused Case Series","rel_doi":"10.64898\/2026.03.02.26347456","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347456","rel_abs":"ObjectiveTo compare early cerebrospinal fluid (CSF) cytokine profiles in intracerebral hemorrhage (ICH) versus subarachnoid hemorrhage (SAH), with a focus on angiography-negative SAH (anSAH).\n\nMethodsWe conducted a retrospective observational cohort study of adults with spontaneous hemorrhagic stroke (ICH or SAH). For cytokine analyses, we included patients with external ventricular drains (EVDs) and analyzed the first CSF sample obtained within 72 hours of symptom onset. Cytokines were measured using a multiplex bead-based assay and included interleukin-6 (IL-6), interleukin-8 (IL-8), vascular endothelial growth factor A (VEGF-A), C-C motif chemokine ligand-2 (CCL2), and granulocyte colony-stimulating factor (G-CSF). Cytokine concentrations were log-transformed due to non-normal distribution. Functional outcomes were assessed using the modified Rankin Scale (mRS) at discharge and 3 months.\n\nResultsCSF cytokine analyses included 120 patients with available CSF samples (43 ICH and 77 SAH), while functional outcome analyses included a broader cohort of 490 patients with ICH or SAH to characterize discharge and 3-month outcomes across hemorrhage subtypes. Compared with SAH, ICH demonstrated higher early CSF log[IL-8] and log[VEGF-A] and had worse functional outcomes at discharge and 3 months. Within SAH, anSAH had higher log[IL-8] and log[VEGF-A] than aSAH, and its cytokine profile more closely aligned with that of primary ICH in hemorrhages without vascular malformations.\n\nDiscussionEarly CSF cytokine patterns suggest anSAH shares a more ICH-like inflammatory signature than aneurysmal SAH, supporting anSAH as a potentially biologically distinct SAH phenotype.","rel_num_authors":15,"rel_authors":[{"author_name":"Will Remillard","author_inst":"Yale University School of Medicine"},{"author_name":"Gracey Sorensen","author_inst":"Yale University School of Medicine"},{"author_name":"Lauren Grychowski","author_inst":"Yale University School of Medicine"},{"author_name":"David Vargas","author_inst":"Yale University School of Medicine"},{"author_name":"Beatrice Hadiwidjaja","author_inst":"Yale University School of Medicine"},{"author_name":"Abdelaziz Amllay","author_inst":"Yale University School of Medicine"},{"author_name":"Jennifer Yan","author_inst":"Yale University School of Medicine"},{"author_name":"Lena O'Keefe","author_inst":"Yale University School of Medicine"},{"author_name":"Jennifer Kim","author_inst":"Yale University School of Medicine"},{"author_name":"Nils Petersen","author_inst":"Yale University School of Medicine"},{"author_name":"Charles Matouk","author_inst":"Yale University School of Medicine"},{"author_name":"Guido J. Falcone","author_inst":"Yale University School of Medicine"},{"author_name":"Kevin Sheth","author_inst":"Yale University School of Medicine"},{"author_name":"Lauren H. Sansing","author_inst":"Yale University School of Medicine"},{"author_name":"Jessica Magid-Bernstein","author_inst":"Yale University School of Medicine"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Student Scholarly Research Programs in US Medical Schools: Cross-sectional Web Audit","rel_doi":"10.64898\/2026.03.03.26347497","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347497","rel_abs":"BackgroundParticipating in research during medical school is supported by institutional programs and may influence subsequent professional development.\n\nObjectiveWe aimed to describe the current status and heterogeneity of scholarly research programs for medical students in the United States, including expectations, support, and key structural features.\n\nMethodsWe conducted a cross-sectional web audit of official webpages for all accredited US MD- and DO-granting medical schools (search performed September 2024 to January 2025). Extracted variables included participation requirements, mentorship, timing and duration (overall and dedicated research time), expected scholarly outputs, funding sources, stipend information, and stated program goals. We compared Carnegie tier R1 (Very high research activity) versus other institutions, QS Top-50 versus other institutions, and MD versus DO schools using {chi}2\/Fisher exact tests for 2x2 tables and exact trend or Freeman-Halton tests for multicategory variables.\n\nResultsPrograms were identified for all 202 institutions. Funding was explicitly mentioned by 61.9% (125\/202) of programs, 27.0% (51\/189) were compulsory, 98.9% (188\/190) reported faculty mentorship, and 91.0% (171\/188) were exclusive for medical students. Program duration, dedicated time, expected outcomes, stipend reporting, funding sources, and stated goals varied widely. Carnegie R1 institutions had longer duration (P=.002) and tended to report external funding more often than other institutions (25\/104, 24.0% vs 9\/98, 9.2%; OR 3.13, 95% CI 1.38-7.10; P=.008). QS Top-50 institutions were more likely to require compulsory participation than other institutions (11\/19, 57.9% vs 40\/170, 23.5%; OR 4.47, 95% CI 1.68-11.87; P=.003). No significant differences were observed between MD and DO programs across most measured characteristics.\n\nConclusionsScholarly research programs for medical students are ubiquitous across US medical schools but heterogeneous in structure, expectations, and support. Research-intensive and top-ranked institutions may have more external funding and sometimes may put together longer and compulsory programs Further evaluation of student experiences and outcomes is warranted.","rel_num_authors":8,"rel_authors":[{"author_name":"Dongyoon Lee","author_inst":"Catholic University of Korea"},{"author_name":"Changyoon Lee","author_inst":"Yonsei University"},{"author_name":"Sarah S Oh","author_inst":"Yonsei University"},{"author_name":"Keeheon Lee","author_inst":"Creative Technology Management, Underwood International College, Yonsei University"},{"author_name":"Chul  S Hyun","author_inst":"Yale University"},{"author_name":"Jae  Il Shin","author_inst":"Yonsei University College of Medicine"},{"author_name":"Shinki An","author_inst":"Yonsei University College of Medicine"},{"author_name":"John Ioannidis","author_inst":"Stanford University"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Incorporation of Visit-to-Visit Blood Pressure Variability into Cardiovascular Disease Risk Prediction","rel_doi":"10.64898\/2026.03.03.26347482","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347482","rel_abs":"BACKGROUNDVisit-to-visit blood pressure variability (VVV BPV) is an important yet underutilised risk factor for cardiovascular disease (CVD) risk prediction. Incorporating VVV BPV in the model predicting CVD could improve its performance. This study aims to incorporate VVV BPV into a CVD risk prediction model and to evaluate its performance by comparing the discrimination and calibration of models using a single BP measurement versus those incorporating VVV BPV\n\nMETHODSThis prospective cohort study included data from the electronic practice-based research network (ePBRN) in Southwestern Sydney, focusing on patients aged 18-55 years with at least five BP readings, excluding those with incomplete data or no follow-up after 55. VVV BPV measured by standard deviation (SD) and coefficient of variation (CV). The main outcome is the first occurrence of CVD. We developed the models using Cox proportional hazards regression with 10-fold cross-validation on all imputed datasets. Model performance was evaluated for discrimination and calibration. Discrimination was assessed using Harrells C-index and time-varying AUC for five-year CVD prediction. Calibration was assessed using calibration slopes and Brier scores, which were also evaluated annually.\n\nRESULTSThe study involved 3,065 patients, with 45.41% women. Incorporating VVV BPV improved the prediction of CVD risk in people aged 55 years. The model with a single systolic blood pressure (SBP) measurement had a Harrel C-Index of 0.716 (95% CI: 0.658 - 0.775), while those using SD and CV scored higher at 0.833 (95% CI: 0.804 - 0.862) and 0.837 (95% CI: 0.810 - 0.864), respectively. Five years AUC for SBP was 0.852 (95% CI: 0.820 - 0.885) for SD and 0.856 (95% CI: 0.824 - 0.888) for CV. In contrast, the single SBP model had a lower AUC of 0.757 (95% CI: 0.700 - 0.815). No significant difference was observed in calibration slopes and Brier scores between the model using single BP and VVV BPV.\n\nCONCLUSIONSThis study developed a model for CVD risk estimation using VVV BPV instead of a single blood pressure measurement. Replacing a single BP measure with VVV BPV significantly enhanced the models predictive accuracy.","rel_num_authors":6,"rel_authors":[{"author_name":"Mifetika Lukitasari","author_inst":"University of New South Wales"},{"author_name":"Nickson Ning","author_inst":"University of New South Wales"},{"author_name":"Siaw-Teng Liaw","author_inst":"University of New South Wales"},{"author_name":"Bin Jalaludin","author_inst":"University of New South Wales"},{"author_name":"Joel Rhee","author_inst":"University of New South Wales"},{"author_name":"Jitendra Jonnagaddala","author_inst":"University of New South Wales"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"The minimum number of blood pressure measurements needed and thresholds for visit-to-visit blood pressure variability to predict cardiovascular disease in primary care patients","rel_doi":"10.64898\/2026.03.02.26347458","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347458","rel_abs":"ObjectivesVisit-to-visit blood pressure variability (VVV BPV) is an underutilised risk factor for cardiovascular disease (CVD). This study aims to determine the minimum number of BP measurements needed and to identify cut-off values for the standard deviation (SD), coefficient of variation (CV), and average real variability (ARV) of systolic and diastolic VVV BPV to predict CVD risk in primary care.\n\nMethodsWe analysed data from the electronic practice-based research network (ePBRN) in Southwestern Sydney, including patients aged 18-55 with at least eight BP readings. Patients with incomplete data or no follow-up beyond age 55 were excluded. The agreement between SD calculated from 3-5 measurements and 8 measurements (reference) was evaluated using Pearsons correlation coefficient and the intraclass correlation coefficient. Then, after identifying that a minimum of five BP measurements is needed, another cohort with at least five BP measurements was developed. Percentile-based cut-offs (10th - 90 th, 5-percentile increments) were derived for systolic and diastolic BPV (SD, CV, ARV). Predictive accuracy was assessed using the C-statistic. The outcome was the first CVD occurrence.\n\nResultsA total of 1,549 patients were included in the first study. Five BP measurements showed good agreement with eight measurements (ICC: 0.79; correlation: 0.80). A total of 3,022 patients were included (55.2% women). Higher VVV BPV (SD, CV. ARV) was associated with increased CVD risk. Optimal cut-off values for systolic BP were 19 mmHg (SD), 14% (CV), and 15 mmHg (ARV), and for diastolic BP were 11 mmHg (SD), 12% (CV), and 11 mmHg (ARV). Predictive performance was consistent across time frames.\n\nConclusionsThese BPV cut-offs provide clinically relevant thresholds for CVD risk prediction. At least five BP measurements are sufficient to estimate BPV for this purpose.","rel_num_authors":6,"rel_authors":[{"author_name":"Mifetika Lukitasari","author_inst":"UNSW: University of New South Wales"},{"author_name":"Reza Argha","author_inst":"UNSW: University of New South Wales"},{"author_name":"Siaw-Teng Liaw","author_inst":"UNSW: University of New South Wales"},{"author_name":"Bin Jalaludin","author_inst":"UNSW: University of New South Wales"},{"author_name":"Joel Rhee","author_inst":"UNSW: University of New South Wales"},{"author_name":"Jitendra Jonnagaddala","author_inst":"UNSW:  University of New South Wales"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Effects of morning and evening narrowband blue light and myopic defocus on axial length in humans","rel_doi":"10.64898\/2026.03.03.26347502","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347502","rel_abs":"PurposeTo investigate the effects of morning and evening narrowband blue light exposure on axial length, and to examine the short-term effect of morning blue light combined with myopic defocus on axial length.\n\nMethodsFor objective 1, 18 individuals underwent 60 minutes of narrowband blue light exposure (460nm) in the morning (9:00-11:00AM) and evening (5:00-7:00PM) of the same day. The axial length values were normalized to the average of the morning and evening axial length values. For objective 2, 27 young adults were exposed to 60 minutes of narrowband blue light and broadband white light while wearing a +3.00 D lens over the right eye. Axial length was measured using Lenstar LS900.\n\nResultsA significant reduction in axial length was observed after exposure to morning blue light compared to evening blue light (-10.0{+\/-}3.96{micro}m vs.-0.67{+\/-}3.30{micro}m; p=0.02), whereas no such effect was observed with broadband white light exposure (0.0{+\/-}3.53 {micro}m vs. -2.50{+\/-}4.23{micro}m, p=0.70). While the broadband white light exposure did not alter the normal diurnal variation in axial length (+2.35{+\/-}1.82{micro}m vs.-6.25{+\/-}2.21{micro}m, p=0.04), blue light diminished such a pattern (-4.12{+\/-}1.72{micro}m vs. - 2.00{+\/-}2.00{micro}m, p=0.48). The myopic defocus did not influence axial length under either narrowband blue or broadband white light conditions.\n\nConclusionThe short-term narrowband blue light exposure led to a significant decrease in axial length in the morning than evening exposure, with a likely influence on the diurnal rhythm of axial length. Morning blue light exposure with lens-induced myopic defocus did not provide additional short-term modulation of axial length.","rel_num_authors":4,"rel_authors":[{"author_name":"Swapnil Thakur","author_inst":"LV Prasad Eye Institute"},{"author_name":"Harnish Khudkhudia","author_inst":"LV Prasad Eye Institute"},{"author_name":"Padmaja Sankaridurg","author_inst":"School of Optometry and Vision Science, University of New South Wales, Sydney, New South Wales, Australia."},{"author_name":"Pavan Kumar Verkicharla","author_inst":"LV Prasad Eye Institute"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Securitized Health and Zero Dose Children: Structural and Service Contact Determinants of Non-Vaccination in Nigeria","rel_doi":"10.64898\/2026.03.02.26347396","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347396","rel_abs":"BackgroundZero-dose children, defined as those who have not received a first dose of a diphtheria-pertussis-tetanus (DPT)-containing vaccine, represent one of the sharpest manifestations of inequity in immunisation systems. Nigeria remains one of the largest contributors to the global zero-dose burden, with North-East Nigeria facing intersecting crises of conflict, population displacement, governance fragility, and weakened primary health care. Existing research has largely focused on structural determinants such as poverty, maternal education, and rural residence, with far less attention to relational mechanisms and governance dynamics that shape caregiver decisions.\n\nMethodsWe conducted a cross-sectional secondary analysis of the 2023 Nigeria Demographic and Health Survey (NDHS) Childrens Recode dataset. Weighted descriptive statistics and survey-adjusted logistic regression models were used to estimate zero-dose prevalence and identify structural and health system-contact determinants among children aged 12-23 months\n\nResultsThe weighted national zero-dose prevalence was 37.1% (95% CI: 35.2-39.0), meaning more than one in three eligible children had never received a DPT-containing vaccine. The strongest independent predictors of zero-dose status were no ANC visits (aOR = 6.68, 95% CI: 5.52-8.09), no maternal education (aOR = 4.70, 95% CI: 2.89- 7.67), poorest wealth quintile (aOR = 2.79, 95% CI: 1.82-4.27), home delivery (aOR = 1.41, 95% CI: 1.18-1.69), and rural residence (aOR = 1.45, 95% CI: 1.18-1.75). Crude regional disparities were marked but attenuated after adjustment, suggesting that the apparent North-East effect is largely mediated through structural and service-contact pathways.\n\nConclusionZero-dose status in Nigeria reflects deep structural exclusion and fragmented early contact with the health system, rather than isolated individual preferences. ANC utilisation and place of delivery emerge as pivotal touchpoints where health systems can either build or erode trust and continuity of care. These findings provide a quantitative foundation for future research exploring relational and contextual mechanisms shaping immunisation exclusion.","rel_num_authors":1,"rel_authors":[{"author_name":"Ibrahim  Ali Mohammed","author_inst":"University of Illinois Chicago"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Clinical outcomes and mortality risk among inborn and referred newborns admitted to hospitals in Kenya","rel_doi":"10.64898\/2026.03.03.26347492","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.03.26347492","rel_abs":"BackgroundNewborns requiring inpatient care, particularly small and sick newborns (SSNBs), face high risk of mortality. Newborns referred from other facilities may experience worse outcomes than those born and managed within the same hospital (inborn newborns). Understanding factors contributing to this disparity in outcomes could support efforts to scale-up care and accelerate progress towards achieving Sustainable Development Goals target 3.2.\n\nMethodsData on 130,773 newborns admitted to 13 hospitals implementing with NEST360 in Kenya were obtained from the Neonatal Inpatient Dataset, between January 2019-October 2024. We described characteristics and primary diagnoses. Logistic regression was used to evaluate factors associated with mortality.\n\nResultsAmong admissions, 114,084 (87.2%) were inborn and 16,689 (12.8%) referred. Referred newborns were more likely to be extremely preterm (6.1% vs 3.1%), have extremely low birthweight (<1,000g) (4.6% vs 2.6%) and present with respiratory distress (26.2% vs 15.0%) and hypoxia (23.2% vs 15.3%) compared to those inborn. Only 59.6% of referred newborns were admitted on first day of life compared to 80.2% inborn newborns. Unadjusted mortality among referred newborns was 29.0% compared to 11.3% in those inborn. Risk factors associated with mortality among referred newborns included being extremely low birthweight (odds ratio [OR] 13.57, 95% CI 11.19-16.44), respiratory distress (OR 4.07, 95% CI 3.77-4.39), and congenital anomalies (OR 1.66, 95% CI 1.41-1.95). Prematurity and intrapartum-related complications were also associated with increased odds of death. In multivariable analysis, being referred remained strongly associated with mortality (adjusted OR [aOR] 2.54, 95% CI 2.39-2.71).\n\nConclusionReferred newborns had nearly three times higher odds of mortality compared to those inborn. This may highlight referral selection bias amongst this group and could also be related to inadequate pre-referral stabilisation, unsafe neonatal transportation and admission delays. If successfully implemented, a strong hub-and-spoke approach may improve care at lower levels of care and decongest receiving facilities. Overall, improving quality of care across the continuum of referral process is a cornerstone in strategies to reduce neonatal mortality towards attainment of national and global newborn survival targets.\n\nKEY FINDINGSO_ST_ABS1. WHAT WAS KNOWN?C_ST_ABSO_LINeonatal mortality remains high in sub-Saharan Africa and newborns referred from other health facilities may experience poorer outcomes than those born and managed within the same hospital.\nC_LIO_LIThere is limited evidence on morbidity and mortality outcomes among inborn and referred newborns. This is important to inform specialised newborn care and targeted improvements in referral.\nC_LI\n\n2. WHAT WAS DONE THAT IS NEW?O_LIThis study analysed routinely collected clinical data on 130,773 newborns admitted to 13 hospitals implementing with NEST360 in Kenya between 2019 and 2024.\nC_LIO_LIDiagnoses outcomes and neonatal characteristics were described and compared between inborn and referred newborns. Factors associated with neonatal mortality were also examined using logistic regression analysis.\nC_LI\n\n3. WHAT WAS FOUND?O_LIReferred newborns had higher unadjusted mortality rate than inborn newborns (29.0% vs 11.3%; p<0.001), with 3 times higher odds of death in univariable logistic regression analysis (OR 3.20, 95% CI 3.08-3.33).\nC_LIO_LIReferred newborns were more clinically vulnerable at admission and had higher proportions of extreme prematurity (6.1% vs 3.1%), very preterm birth (14.0% vs 8.6%), and extremely low birthweight (4.6% vs 2.6%). Among both groups, key risk factors associated with mortality included birthweight, gestational age, respiratory distress, hypothermia, and clinical diagnoses.\nC_LIO_LIAmong referred newborns some of the risk factors associated with mortality included being extremely low birthweight (OR 13.57, 95% CI 11.19-16.44), respiratory distress (OR 4.07, 95% CI 3.77-4.39), congenital anomalies (OR 1.66, 95% CI 1.41-1.95), and intrapartum-related complications (OR 1.35, 95% CI 1.20-1.52).\nC_LI\n\n4. WHAT NEXT?O_LIStrengthen neonatal referral systems through clearer referral criteria, improved pre-referral stabilisation, better neonatal transport, and prompt triage on arrival at receiving hospitals. Routine clinical data should be used to monitor referral processes and outcomes and to guide continuous quality improvement.\nC_LIO_LIFurther research is needed to capture referral to admission time, transport characteristics, and quality of pre-referral stabilisation. Linking neonatal admission data with maternal records and assessing outcomes beyond hospital discharge would also improve understanding of referral pathways and long-term outcomes.\nC_LI","rel_num_authors":12,"rel_authors":[{"author_name":"Judy Baariu","author_inst":"Newcastle University"},{"author_name":"Sarah Murless-Collins","author_inst":"Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"},{"author_name":"George Okello","author_inst":"Rice360 Institute for Global Health Technologies, Rice University, Nairobi, Kenya"},{"author_name":"Dolphine Mochache","author_inst":"Department of Paediatrics, Aga Khan University, Nairobi, Kenya"},{"author_name":"Franklin Okech","author_inst":"Kenya Medical Research Institute, Wellcome Trust Research Programme, Nairobi, Kenya"},{"author_name":"Lucas Malla","author_inst":"Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"},{"author_name":"James H. Cross","author_inst":"Department of Infectious Disease Epidemiology and International Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"},{"author_name":"David Gathara","author_inst":"Kenya Medical Research Institute, Wellcome Trust Research Programme, Nairobi, Kenya"},{"author_name":"Joy E. Lawn","author_inst":"Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"},{"author_name":"Eric O. Ohuma","author_inst":"Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"},{"author_name":"William M. Macharia","author_inst":"Department of Paediatrics, Aga Khan University, Nairobi, Kenya"},{"author_name":"Rebecca E. Penzias","author_inst":"Centre for Maternal, Adolescent, Reproductive, & Child Health, London School of Hygiene & Tropical Medicine, London, United Kingdom"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Dim light sensitivity and delayed sleep timing in young people with emerging mental disorders","rel_doi":"10.64898\/2026.03.02.26347467","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347467","rel_abs":"BackgroundLight plays a critical role in mental health, as the primary input to the circadian system, which regulates mood, energy, and the sleep-wake cycle. Altered light sensitivity is a potential mechanism in circadian-associated mental disorders.\n\nMethodsActigraphy-derived sleep, physical activity, and circadian rhythm correlates of the pupillary light reflex were explored in young people with emerging mental disorders. Participants were 27 healthy controls (Mean age=25.67 {+\/-} 2.83, 52% female) and 155 young people from the Neurobiology Youth Follow-up Study (Mean age=25.48 {+\/-} 5.65; 60% female), recruited from an early intervention mental health service. 32% of the latter group were re-assessed over 12 months. Pupil constriction, average and maximal constriction velocity, and constriction latency were recorded by the PLR-3000 monocular pupillometer in response to dim ([~]10 lux) and bright ([~]1500 lux) pulses.\n\nResultsCompared to healthy controls, young people with emerging mental disorders had a smaller change in pupil diameter (p=0.037) and a slower maximal constriction velocity (p=0.018) in response to dim light. In the full sample, decreased dim light sensitivity was correlated with later timing of actigraphy-derived sleep midpoint. Within the clinical cases, increased genetic risk for bipolar disorder was correlated with increased dim light sensitivity, and higher insomnia clinical scores were correlated with decreased dim light sensitivity. Pupillometry measures were stable across time and seasons.\n\nConclusionAltered light sensitivity may be associated with the emergence of mood disorder in young people and with altered sleep-wake timing.","rel_num_authors":22,"rel_authors":[{"author_name":"Emiliana Tonini","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Alissa Nichles","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Natalia Zmicerevska","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Elie Jeon","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Gabrielle Hindmarsh","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Elizabeth Phung","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Connie Janiszewski","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Tian Lin","author_inst":"Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia"},{"author_name":"Elise M McGlashan","author_inst":"Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia"},{"author_name":"Sean W Cain","author_inst":"Flinders Health and Medical Research Institute (Sleep Health), Flinders University, Bedford Park, SA, Australia"},{"author_name":"Jan Scott","author_inst":"Academic Psychiatry, Institute of Neuroscience, University of Newcastle, UK"},{"author_name":"Joey WY Chan","author_inst":"Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR"},{"author_name":"Frank Iorfino","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Haley M LaMonica","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Yun Ju (Christine) Song","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"- 23andMe Research Team","author_inst":"-"},{"author_name":"Naomi R Wray","author_inst":"Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Jacob J Crouse","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"Dim light sensitivity and delayed sleep timing in young people with emerging mental disorders","rel_doi":"10.64898\/2026.03.02.26347467","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.02.26347467","rel_abs":"BackgroundLight plays a critical role in mental health, as the primary input to the circadian system, which regulates mood, energy, and the sleep-wake cycle. Altered light sensitivity is a potential mechanism in circadian-associated mental disorders.\n\nMethodsActigraphy-derived sleep, physical activity, and circadian rhythm correlates of the pupillary light reflex were explored in young people with emerging mental disorders. Participants were 27 healthy controls (Mean age=25.67 {+\/-} 2.83, 52% female) and 155 young people from the Neurobiology Youth Follow-up Study (Mean age=25.48 {+\/-} 5.65; 60% female), recruited from an early intervention mental health service. 32% of the latter group were re-assessed over 12 months. Pupil constriction, average and maximal constriction velocity, and constriction latency were recorded by the PLR-3000 monocular pupillometer in response to dim ([~]10 lux) and bright ([~]1500 lux) pulses.\n\nResultsCompared to healthy controls, young people with emerging mental disorders had a smaller change in pupil diameter (p=0.037) and a slower maximal constriction velocity (p=0.018) in response to dim light. In the full sample, decreased dim light sensitivity was correlated with later timing of actigraphy-derived sleep midpoint. Within the clinical cases, increased genetic risk for bipolar disorder was correlated with increased dim light sensitivity, and higher insomnia clinical scores were correlated with decreased dim light sensitivity. Pupillometry measures were stable across time and seasons.\n\nConclusionAltered light sensitivity may be associated with the emergence of mood disorder in young people and with altered sleep-wake timing.","rel_num_authors":22,"rel_authors":[{"author_name":"Emiliana Tonini","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Ian B Hickie","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Mirim Shin","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Joanne S Carpenter","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Alissa Nichles","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Natalia Zmicerevska","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Elie Jeon","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Gabrielle Hindmarsh","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Elizabeth Phung","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Connie Janiszewski","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Tian Lin","author_inst":"Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia"},{"author_name":"Elise M McGlashan","author_inst":"Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, VIC, Australia"},{"author_name":"Sean W Cain","author_inst":"Flinders Health and Medical Research Institute (Sleep Health), Flinders University, Bedford Park, SA, Australia"},{"author_name":"Jan Scott","author_inst":"Academic Psychiatry, Institute of Neuroscience, University of Newcastle, UK"},{"author_name":"Joey WY Chan","author_inst":"Li Chiu Kong Family Sleep Assessment Unit, Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR"},{"author_name":"Frank Iorfino","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Haley M LaMonica","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Yun Ju (Christine) Song","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"- 23andMe Research Team","author_inst":"-"},{"author_name":"Naomi R Wray","author_inst":"Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia"},{"author_name":"Elizabeth M Scott","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"},{"author_name":"Jacob J Crouse","author_inst":"Brain and Mind Centre, The University of Sydney, NSW, Australia"}],"rel_date":"2026-03-04","rel_site":"medrxiv"},{"rel_title":"NT-proBNP Thresholds for Early Heart Failure Detection in Asian Patients With Type 2 Diabetes","rel_doi":"10.64898\/2026.02.27.26347295","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.02.27.26347295","rel_abs":"BackgroundHeart failure (HF) is an increasingly common complication among patients with type 2 diabetes (T2D), yet its early detection remains challenging, especially in those with concomitant chronic kidney disease (CKD). NT-proBNP is a key biomarker for diagnosing and prognosticating HF, but its reference thresholds are influenced by renal function, age, and ethnicity. Current guideline cutoffs, largely derived from Western populations, may not apply to Asian patients.\n\nMethodsThis retrospective cohort study included 10,587 adults with T2D who underwent NT-proBNP testing between 2006 and 2021 at the National Taiwan University Hospital. Patients with prior HF were excluded. Generalized additive models identified NT-proBNP thresholds associated with HF hospitalization, and Kaplan-Meier analysis validated outcome separation. Subgroup analyses were stratified by age, sex, body mass index (BMI), and estimated glomerular filtration rate (eGFR).\n\nResultsDuring a mean follow-up of 3.5 years, 1,892 (17.9%) patients were hospitalized for HF. NT-proBNP levels of 179 pg\/mL (outpatient) and 728 pg\/mL (emergency) marked inflection points for rising event risk (log-rank p < 0.0001). Age-specific analyses showed progressive increases in optimal thresholds: from 85 (<50 years old), 150 (50-74 years old) and 290 pg\/mL ([&ge;]75 years old) in outpatients, and from 310, 600 and 1,165 pg\/mL, respectively, in emergency settings. In the BMI-stratified analysis, NT-proBNP thresholds demonstrated an inverse relation with BMI. Considering renal function, the optimal cutoffs were 100, 310, and 935 pg\/mL for eGFR > 60, 30-60, and < 30 mL\/min\/1.73 m{superscript 2}, respectively; in the emergency cohort, the corresponding thresholds were 290, 835, and 3,905 pg\/mL.\n\nConclusionsThis large Asian cohort defines setting- and renal function-specific NT-proBNP thresholds for predicting HF hospitalization in patients with T2D. The lower optimal cutoffs compared with Western guidelines highlight the need for ethnicity-adjusted diagnostic criteria to improve early identification and risk stratification of HF in clinical practice.\n\nWhat is new?O_LIIn a large real-world Asian cohort of patients with type 2 diabetes, we identified setting-specific NT-proBNP thresholds (179 pg\/mL outpatient; 728 pg\/mL emergency) associated with heart failure hospitalization risk.\nC_LIO_LIAge-, BMI-, and kidney function-stratified cutoffs revealed substantial heterogeneity in optimal NT-proBNP thresholds.\nC_LIO_LICompared with guideline-recommended values, Asian-specific thresholds were consistently lower ([~]30-40%), supporting ethnic differences in natriuretic peptide biology.\nC_LIO_LIA generalized additive model (GAM) captured nonlinear biomarker-risk relationships, enabling data-driven and clinically interpretable cutoff identification.\nC_LI\n\nWhat are the clinical implications?O_LIUse of ethnicity- and context-specific NT-proBNP thresholds may improve early detection of heart failure in Asian patients with type 2 diabetes.\nC_LIO_LIIncorporating kidney function and BMI into NT-proBNP interpretation enhances risk stratification, particularly in patients with CKD.\nC_LIO_LIReliance on Western guideline cutoffs may underestimate heart failure risk in Asian populations.\nC_LIO_LIThese findings support a precision medicine approach to biomarker interpretation and highlight the need for population-specific guideline refinement.\nC_LI","rel_num_authors":6,"rel_authors":[{"author_name":"Tai-Shuan Lai","author_inst":"Department of Internal Medicine, National Taiwan University Hospital"},{"author_name":"Chia-Ling Tseng","author_inst":"Fu Jen Catholic University College of Medicine"},{"author_name":"Cho-Kai Wu","author_inst":"National Taiwan University College of Medicine and Hospital"},{"author_name":"Liang-Ting Chiang","author_inst":"Fu Jen Catholic University Hospital"},{"author_name":"Yong-Chen Chen","author_inst":"Fu Jen Catholic University College of Medicine"},{"author_name":"Wan-Lun Hsu","author_inst":"College of Medicine, Fu Jen Catholic University"}],"rel_date":"2026-03-03","rel_site":"medrxiv"},{"rel_title":"Insights Into Parkinsons Disease Genetics in African Populations: Expanded GWAS Identifies Ancestry-Specific and Cross-Population Risk Loci","rel_doi":"10.64898\/2026.03.01.26347367","rel_link":"http:\/\/medrxiv.org\/content\/10.64898\/2026.03.01.26347367","rel_abs":"IntroductionGenome-wide association studies (GWAS) have identified over 130 risk loci for Parkinsons disease (PD), yet the majority derive from studies performed in European ancestry populations. African (AFR) and African admixed (AAC) ancestry individuals remain underrepresented in PD genetics research, limiting our understanding of ancestry-specific genetic architecture and the generalizability of known risk factors.\n\nMethodsWe conducted GWAS in AFR and AAC populations by integrating individual-level genotype data from the Global Parkinsons Genetics Program (GP2) with summary statistics from 23andMe Research Institute and the Million Veterans Program. The combined dataset included 3,975 cases and 319,883 controls, representing a 64% increase in total sample size compared with prior analyses. We performed separate GWAS for AFR and AAC cohorts as well as a combined AFR\/AAC meta-analysis.\n\nResultsThe intronic GBA1 variant rs3115534 was the most significant association across all analyses, reaching genome-wide significance in AAC individuals for the first time. In the AFR-only analysis, five loci achieved genome-wide significance: GBA1 (rs3115534), the SNCA signal previously reported in European ancestry GWAS (rs356182), a new protein-coding association at LRRK2 (rs72546327, p.T1410M), a non-coding RPL10P13 variant (rs12302417), and a novel signal on chromosome 16 (rs113244182). The combined AFR\/AAC meta-analysis identified four genome-wide significant associations at GBA1 (rs3115534), SNCA (rs356182), SCARB2 (rs11547135), and LRRK2 (rs139283662, which is in LD with p.T1410M).\n\nConclusionsThis study reports the largest GWAS of PD in AFR and AAC populations to date. Our findings confirm trans-ancestry risk loci (GBA1 and SCARB2) and identify an ancestry-enriched coding variant at LRRK2. This convergence of evidence around genes involved in glucocerebrosidase (GCase) trafficking and alpha-synuclein clearance supports current therapeutic strategies targeting this pathway and provides critical targets for developing precision medicine in African ancestry populations. Importantly, the identification of a novel association between a LRRK2 coding variant with disease in the AFR and AAC populations opens up a traditionally underrepresented population for ongoing LRRK2 targeted trials. Furthermore, the identification of novel ancestry-specific loci, including those that are directly relevant to current therapeutic deployment, underlines the importance of understanding the basis of disease in all populations.","rel_num_authors":85,"rel_authors":[{"author_name":"Njideka Okubadejo","author_inst":"University of Lagos"},{"author_name":"Oluwadamilola O Ojo","author_inst":"College of Medicine of the University of Lagos"},{"author_name":"Oladunni Abiodun","author_inst":"General Hospital"},{"author_name":"Sani Abubakar","author_inst":"Ahmadu Bello University"},{"author_name":"Fatimah Abdulai","author_inst":"University of Abuja Teaching Hospital"},{"author_name":"Charles Achoru","author_inst":"Jos University Teaching Hospital"},{"author_name":"Osigwe Agabi","author_inst":"College of Medicine, University of Lagos"},{"author_name":"Uchechi Agulanna","author_inst":"Lagos University Teaching Hospital"},{"author_name":"Rufus Akinyemi","author_inst":"Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training, College of Medicine, University of Ibadan"},{"author_name":"Wemimo Alaofin","author_inst":"University of Ilorin"},{"author_name":"Roosevelt Anyanwu","author_inst":"College of Medicine, University of Lagos"},{"author_name":"Cyril Erameh","author_inst":"Irrua Specialist Teaching Hospital"},{"author_name":"Daniel Ezuduemoih","author_inst":"Lagos University Teaching Hospital"},{"author_name":"Abdullahi Ibrahim","author_inst":"Federal University of Health Sciences Teaching Hospital"},{"author_name":"Erica Ikwenu","author_inst":"Lagos University Teaching Hospital"},{"author_name":"Frank Imarhiagbe","author_inst":"University of Benin"},{"author_name":"Ismaila Ishola","author_inst":"College of Medicine, University of Lagos"},{"author_name":"Emmanuel Iwuozo","author_inst":"Benue State University"},{"author_name":"Morenikeji Komolafe","author_inst":"Obafemi Awolowo University"},{"author_name":"Alero Nnama","author_inst":"University of Port Harcourt Teaching Hospital"},{"author_name":"Paul Nwani","author_inst":"Nnamdi Azikiwe University Teaching Hospital"},{"author_name":"Franscisca Nwaokorie","author_inst":"College of Medicine, University of Lagos"},{"author_name":"Ernest Nwazor","author_inst":"Rivers State University Teaching Hospital"},{"author_name":"Yahaya Obiabo","author_inst":"Federal University of Health Sciences"},{"author_name":"Nkechi Obianozie","author_inst":"University of Abuja Teaching Hospital"},{"author_name":"Olanike Odeniyi","author_inst":"General Hospital"},{"author_name":"Francis Odiase","author_inst":"University of Benin"},{"author_name":"Ewere Marie Ogbimi","author_inst":"Delta State University"},{"author_name":"Adebimpe Ogunmodede","author_inst":"Federal Medical Center"},{"author_name":"Francis Ojini","author_inst":"University of Lagos"},{"author_name":"Rashidat Olanigan","author_inst":"Lagos State University Teaching Hospital"},{"author_name":"Adedunni Olusanya","author_inst":"College of Medicine, University of Lagos & R-Jolad Hospital"},{"author_name":"Chiamaka Okereke","author_inst":"University of Nigeria Teaching Hospital"},{"author_name":"Gerald Onwuegbuzie","author_inst":"University of Abuja"},{"author_name":"Godwin Osaigbovo","author_inst":"Jos University Teaching Hospital"},{"author_name":"Nosakhare Osemwegie","author_inst":"University of Port Harcourt"},{"author_name":"Olajumoke Oshinaike","author_inst":"Lagos State University College of Medicine"},{"author_name":"Lukman Owolabi","author_inst":"Bayero University Kano"},{"author_name":"Raymond Owolabi","author_inst":"Federal Medical Center"},{"author_name":"Shyngle Oyakhire","author_inst":"National Hospital"},{"author_name":"Simon Izuchukwu Ozomma","author_inst":"University of Calabar Teaching Hospital"},{"author_name":"Fadimatu Sa'Ad","author_inst":"Federal Teaching Hospital"},{"author_name":"Funmilola Taiwo","author_inst":"University College Hospital"},{"author_name":"Kolawole Wahab","author_inst":"University of Ilorin"},{"author_name":"Mie Rizig","author_inst":"Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London"},{"author_name":"Stella Aslibekyan","author_inst":"23andMe Research Institute"},{"author_name":"Matt Kmiecik","author_inst":"23andMe Research Institute"},{"author_name":"Karl Heilbron","author_inst":"23andMe Research Institute"},{"author_name":"- 23andMe Research Team","author_inst":"-"},{"author_name":"Kamalini Ghosh Galvelis","author_inst":"Parkinsons Foundation, New York, NY"},{"author_name":"Cyrus P Zabetian","author_inst":"VA Puget Sound Health Care System, Seattle, WA"},{"author_name":"Kathryn Step","author_inst":"Stellenbosch University, Cape Town, South Africa"},{"author_name":"Jonathan Carr","author_inst":"Stellenbosch University, Cape Town, South Africa"},{"author_name":"Soraya Bardien","author_inst":"Stellenbosch University, Cape Town, South Africa"},{"author_name":"Pawel Lis","author_inst":"MRC Protein Phosphorylation and Ubiquitylation Unit, University of Dundee, Dundee, UK"},{"author_name":"Lana Chahine","author_inst":"University of Pittsburgh, Pittsburgh, PA"},{"author_name":"Naomi Louie","author_inst":"The Michael J Fox Foundation for Parkinsons Research, New York, NY"},{"author_name":"Alyssa O'Grady","author_inst":"The Michael J Fox Foundation for Parkinsons Research, New York, NY"},{"author_name":"Shivika Chandra","author_inst":"The University of Texas Health Science Center at Houston, Houston, TX, USA"},{"author_name":"Marissa Dean","author_inst":"University of Alabama at Birmingham, Birmingham, AL"},{"author_name":"Elizabeth Disbrow","author_inst":"Louisiana State University Health Sciences Center Shreveport, Shreveport, LA"},{"author_name":"Deborah Hall","author_inst":"Rush University Medical Center, Chicago, IL"},{"author_name":"Vanessa Hinson","author_inst":"Medical University of South Carolina, Charleston, SC"},{"author_name":"Camilla Kilbane","author_inst":"University Hospitals Cleveland Medical Center, Cleveland, OH"},{"author_name":"Scott Norris","author_inst":"Washington University in St. Louis, St. Louis, MO"},{"author_name":"Ashley Rawls","author_inst":"University of Florida, Gainesville, FL"},{"author_name":"Ejaz Shamim","author_inst":"Kaiser Permanente Mid-Atlantic States, Largo, MD"},{"author_name":"Lisa Shulman","author_inst":"University of Maryland, Baltimore, MD"},{"author_name":"Julia Staisch","author_inst":"Ochsner Clinic Foundation, New Orleans, LA"},{"author_name":"Tao Xie","author_inst":"University of Chicago, Chicago, IL"},{"author_name":"Andrew Ameri","author_inst":"Medical University of South Carolina, Charleston, SC"},{"author_name":"Erin Foster","author_inst":"Washington University in St. Louis, St. Louis, MO"},{"author_name":"Erin Furr Stimming","author_inst":"The University of Texas Health Science Center at Houston, Houston, TX, USA"},{"author_name":"Natalia Pessoa Rocha","author_inst":"The University of Texas Health Science Center at Houston, Houston, TX, USA"},{"author_name":"Lietsel Jones","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"Lara M Lange","author_inst":"Institute of Neurogenetics, University of Luebeck, Luebeck, Germany"},{"author_name":"Zih-Hua Fang","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"Kristin Levine","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"Huw Morris","author_inst":"UCL Queen Square Institute of Neurology, London, UK"},{"author_name":"Mike A Nalls","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"Cornelis Blauwendraat","author_inst":"The Global Parkinsons Genetics Program (GP2)"},{"author_name":"Andrew B Singleton","author_inst":"The Global Parkinsons Genetics Program (GP2)"},{"author_name":"Hampton L Leonard","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"Mary B Makarious","author_inst":"DataTecnica, Washington, DC, USA"},{"author_name":"- Global Parkinsons Genetics Program","author_inst":"-"}],"rel_date":"2026-03-03","rel_site":"medrxiv"}]}