Nature genetics最新文献

{"title":"Multiancestry genome-wide association and multiomics analyses elucidate spatiocellular features of multiple sclerosis genetics","authors":"Rintaro Fujimoto, Kotaro Ogawa, Shinichi Namba, Yosuke Ogawa, Ryuya Edahiro, Kyuto Sonehara, Shiori Tagawa, Mitsuru Watanabe, Tomohiro Yata, Yuya Shirai, Yuji Yamamoto, Go Sato, Chifune Kai, Tatsuhiko Naito, Akiko Hosokawa, Mamoru Yamamoto, Japan MS/NMOSD Biobank, the BioBank Japan Project, Koichi Matsuda, Fumitaka Shimizu, Makoto Kinoshita, Masahito Mihara, Masayuki Nakamori, Yuko Shimizu, Izumi Kawachi, Katsuichi Miyamoto, Masaaki Niino, Atsushi Kumanogoh, Yuji Nakatsuji, Takuya Matsushita, Hideki Mochizuki, Jun-ichi Kira, Tatsusada Okuno, Noriko Isobe, Yukinori Okada","doi":"10.1038/s41588-026-02741-5","DOIUrl":"10.1038/s41588-026-02741-5","url":null,"abstract":"Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination disseminated in space and time. Here we performed a genome-wide association study (GWAS) using 688 MS cases and 205,199 controls from the Japanese population and identified significant associations in the major histocompatibility complex region and a population-specific risk variant in 11q24. Through cross-population GWAS meta-analyses using a total of 29,374 cases and 1,843,563 controls from 4 ancestral populations, we identified 22 novel susceptibility loci. Integration of GWAS and single-cell and single-nucleus RNA sequencing of peripheral blood mononuclear cells and subcortical lesions from patients with MS revealed enrichment of genetic risk factors for MS in CD4+ T helper cell lineage and regulatory T cells, as well as in endothelial cells. Furthermore, spatial transcriptomics of subcortical lesions demonstrated spatial and temporal heterogeneity in associations with MS genetic risk. Our study demonstrates the value of investigation of spatiocellular features of disease genetics across diverse populations and omics modalities. Multiancestry genome-wide association analyses of multiple sclerosis integrated with single-cell, single-nucleus and spatial transcriptomics data yield insights into the cellular, spatial and temporal heterogeneity underlying disease risk.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2192-2200"},"PeriodicalIF":25.5,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-026-02741-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide association analyses highlight the neuronal contribution to multiple sclerosis susceptibility","authors":"Lu Zeng, Atlas Khan, Kathryn C. Fitzgerald, Tsering Lama, Jessy Chen, Ruixi Li, International Multiple Sclerosis Genetics Consortium, Ellen A. Tsai, Ketian Yu, Tanuja Chitnis, Howard L. Weiner, Quentin Le Grand, Stéphanie Debette, Gao Wang, Masashi Fujita, Peter A. Calabresi, Frauke Zipp, Mariko Taga, Krzysztof Kiryluk, Philip L. De Jager","doi":"10.1038/s41588-026-02731-7","DOIUrl":"10.1038/s41588-026-02731-7","url":null,"abstract":"Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease. Previous genetic studies have identified susceptibility loci that primarily impact immune cells and microglia. Here we performed a multi-ancestry genome-wide association study of 20,831 MS cases and 729,220 controls and identified 236 susceptibility variants outside of the major histocompatibility complex, including four novel genomic loci. We also derived a polygenic score for MS; while optimized for European ancestry, it is informative for African American and Latino individuals. Integrating single-cell data from blood and brain tissue, we identified 76 candidate causal genes. Inhibitory neurons emerged as a key target cell type for MS-associated variants, with seven loci, including STAT3, displaying altered expression only in these cells. The STAT3 variant is also associated with cognition and white matter integrity in individuals with no MS and greater sNfL levels in individuals with MS, suggesting that MS susceptibility may reflect reduced central nervous system resilience to inflammatory challenges. Multi-ancestry genome-wide association analyses integrated with single-cell data from blood and brain tissue identify genetic risk variants influencing multiple sclerosis susceptibility and highlight inhibitory neurons as a key target cell type.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2177-2191"},"PeriodicalIF":25.5,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148899591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable, generalizable and uncertainty-aware integration of spatial multiomics across diverse modalities and platforms with SCIGMA","authors":"Seowon Chang, Alexander Fleischmann, Ying Ma","doi":"10.1038/s41588-026-02706-8","DOIUrl":"10.1038/s41588-026-02706-8","url":null,"abstract":"Recent advances in spatial omics technologies have enabled simultaneous profiling of transcriptomic, proteomic, epigenomic, metabolomic and imaging data at high spatial resolution, offering unprecedented opportunities to dissect tissue complexity. However, integrating these diverse and large-scale spatial multimodal datasets remains a major computational challenge. We present SCIGMA, a scalable and generalizable deep learning framework for spatial multiomics integration. SCIGMA introduces an uncertainty-aware contrastive learning objective and multiview graph neural networks to preserve modality-specific signals while learning biologically meaningful joint representations. Unlike previous methods, SCIGMA provides spatially resolved uncertainty estimates, interpretably identifying regions of biological or technical heterogeneity. SCIGMA supports integration of up to five modalities, and its modular framework is extensible to future technologies with even more modalities. It also scales to more than 1 million spatial locations, enabling analysis of high-resolution datasets such as Visium HD and Xenium Prime. We evaluated SCIGMA across 19 datasets spanning 8 modalities, 10 tissues and 9 platforms. On benchmarkable datasets, SCIGMA outperformed other methods in spatial domain detection, modality preservation, feature reconstruction and reproducibility. SCIGMA identifies biologically meaningful structures, refined spatial domains and modality-specific regulatory programs, providing a robust, flexible and future-ready solution for scalable spatial multimodal integration. SCIGMA is a scalable and flexible deep learning framework that integrates up to five spatial omics modalities, preserving modality-specific signals, improving spatial domain detection and enabling robust, interpretable multimodal analysis.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2284-2302"},"PeriodicalIF":25.5,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148888043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal lineage tracing reveals the dynamic spatial architecture of tumor growth and metastasis","authors":"Matthew G. Jones, Dawei Sun, Kyung Hoi Joseph Min, William N. Colgan, Haoyu Wang, Tivadar Török, Juliano Ribeiro, Jessie Xue, Erik C. Cardoso, Yao Rong, Luyi Tian, Jackson A. Weir, Victor Z. Chen, Luke W. Koblan, Kathryn E. Yost, Nicolas Mathey-Andrews, Edridge D’Souza, Andrew J. C. Russell, Robert R. Stickels, Karol S. Balderrama, William M. Rideout III, Min Dai, Giovanni Marrero, Vipin Kumar, Anjali Saqi, Benjamin Herzberg, Benjamin Izar, Howard Y. Chang, Joo-Hyeon Lee, Tyler Jacks, Fei Chen, Jonathan S. Weissman, Nir Yosef, Dian Yang","doi":"10.1038/s41588-026-02739-z","DOIUrl":"10.1038/s41588-026-02739-z","url":null,"abstract":"Tumor progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Here we integrate high-resolution spatial transcriptomics and evolving lineage-tracing technologies to elucidate how tumor expansion, plasticity and metastasis co-evolve with microenvironmental remodeling in a Kras;Trp53-driven mouse model of lung adenocarcinoma. We find that subclonal expansion contributes to a hypoxic, immunosuppressive and fibrotic microenvironment that is associated with the emergence of prometastatic cancer cell states. We use tumor phylogeography to delineate intercellular interactions that are rewired in the expanding tumor niche and use co-culture systems to dissect how intercellular interactions and hypoxia influence cancer cell state. Furthermore, we find that metastases arise from spatially confined primary tumor subclones and remodel the distant metastatic niche into a fibrotic, collagen-rich microenvironment. Together, we present a comprehensive dataset integrating spatial assays and lineage tracing to elucidate how sequential changes in cancer cell state and microenvironmental structures cooperate to promote tumor progression. Tumors are driven by dynamic interactions between cancer cells and their environment. The authors use spatial lineage tracing to map the spatiotemporal trajectories of a lung adenocarcinoma model and dissect how extrinsic signals drive progression.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2398-2410"},"PeriodicalIF":25.5,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148880248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanisms and functional implications of long-range enhancer-dependent gene regulation","authors":"Marianna Iliadou, Endika Haro, Alvaro Rada-Iglesias","doi":"10.1038/s41588-026-02721-9","DOIUrl":"10.1038/s41588-026-02721-9","url":null,"abstract":"Metazoan development relies on the coordinated establishment of diverse gene regulatory programs that drive the formation of specific cell types, tissues and organs. The temporal and spatial control of gene expression is achieved through the concerted activity of multiple classes of cis-regulatory elements encoded in the genome. Among these, enhancers enable the establishment of specific and precise gene expression patterns and control gene expression over long linear distances, a property often referred to as distance-independent regulatory activity. However, enhancer activity is, in fact, inversely correlated with linear genomic distance, and target gene expression and transcriptional precision decrease with increasing enhancer–promoter linear distances. Here, we highlight emerging insights into multiple mechanisms that enable enhancers to precisely and robustly activate gene expression across large genomic distances. Finally, we provide a more speculative perspective on the potential advantages that long-range regulation might confer during the establishment of developmental gene expression programs. Development depends on gene regulation by enhancers across long genomic distances. This Perspective discusses mechanisms enabling long-range enhancer–promoter communication and the potential advantages that distal enhancer positioning might confer.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2104-2117"},"PeriodicalIF":25.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OmicsPred as a centralized resource for genetic prediction of multi-omic traits","authors":"Carles Foguet, Laurent Gil, Yu Xu, Sofía Salazar-Magaña, Scott C. Ritchie, Elodie Persyn, Hae Kyung Im, Michael Inouye, Samuel A. Lambert","doi":"10.1038/s41588-026-02726-4","DOIUrl":"10.1038/s41588-026-02726-4","url":null,"abstract":"We present OmicsPred, an open platform for the deposition and dissemination of genetic prediction models of multi-omic traits, with key metadata required for reproducibility and independent applications. We illustrate the utility of the resource for target discovery with a multi-omic multi-ancestry phenome-wide association analysis using data from the Million Veterans Program.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 10","pages":"2416-2421"},"PeriodicalIF":25.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A single-cell atlas of multiple myeloma defines malignant archetypes and proliferative states","authors":"Mor Zada, Anna Kurilovich, Noam Shapira, Shuang-Yin Wang, Reut Sharet-Eshed, Shlomit Kfir-Erenfeld, Miriam Schlossberg, Elina Zorde, Nathalie Asherie, Chamutal Gur, Paulina Chalan, Rotem Shalita, Maya Ben Yehuda, Pascale Zwicky, Michelle von Locquenghien, Florian Ingelfinger, Kfir Mazuz, Eyal David, Anna Gurevich-Shapiro, Natan Melamed, Iuliana Vaxman, Irit Avivi, Assaf Weiner, Polina Stepensky, Yael Cohen, Ido Amit","doi":"10.1038/s41588-026-02725-5","DOIUrl":"10.1038/s41588-026-02725-5","url":null,"abstract":"Multiple myeloma (MM) is a plasma-cell malignancy with extensive genomic and transcriptional heterogeneity, limiting disease classification and precision therapy. Here we generated a clinically annotated, population-scale, single-cell atlas of MM from 341 individuals spanning the disease and treatment continuum. We identified five recurrent malignant transcriptional archetypes and an orthogonal proliferative program associated with genomic features, therapeutic resistance and clinical outcomes. Validation in the independent CoMMpass cohort demonstrated robustness, prognostic relevance and portability across platforms. We developed a single-cell, target-discovery pipeline prioritizing malignant enrichment, cell-type specificity and tissue restriction, identifying FCRL2 as a plasma-restricted or B cell-lineage-restricted surface target expressed by malignant plasma cells. FCRL2-targeted chimeric antigen receptor T cells demonstrated antigen-specific activity in vitro and survival benefit in vivo. Together, these data provide a clinically actionable blueprint for patient stratification and precision target nomination in plasma-cell malignancies. A single-cell transcriptomic analysis of samples from 341 patients with multiple myeloma presents a classification system with five archetypes, overlaid with a proliferation score that is used to build an improved risk stratifier. FCRL2 is highlighted as a putative target for immune therapies.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2254-2269"},"PeriodicalIF":25.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From single-site to pan-histone lysine mutagenesis in mammals","authors":"Ben Vanderkruk, Shelley L. Berger","doi":"10.1038/s41588-026-02730-8","DOIUrl":"10.1038/s41588-026-02730-8","url":null,"abstract":"Price et al. forge the path for simultaneous mutagenesis of any lysine(s) across all histone H3 gene copies in mammalian cells.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2079-2080"},"PeriodicalIF":25.5,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multiancestry polygenic risk score for Alzheimer’s disease is associated with cognitive decline and neuropathological hallmarks in diverse populations","authors":"Nuzulul Kurniansyah, Shinya Tasaki, Habbibur Rehman, Congcong Zhu, John Farrell, Richard Sherva, Richard Hauger, Victoria C. Merritt, Matthew Panizzon, Rui Zhang, J. Michael Gaziano, Jungsoo Gim, Kunho Lee, Dong Yong Lee, Kwansik Nho, Ricardo A. Vialle, Shubhabrata Mukherjee, Emily H. Trittschuh, Annie J. Lee, Adam M. Brickman, Carlos Cruchaga, Shannon Risacher, Douglas N. Greve, Paul Crane, Eden Martin, William S. Bush, Richard Mayeux, Jonathan L. Haines, Margaret A. Pericak-Vance, Mark Logue, David A. Bennett, Lisa L. Barnes, Andrew Saykin, Timothy Hohman, Li-San Wang, Gerard D. Schellenberg, Ting Fang Alvin Ang, Rhoda Au, Jesse Mez, Kathryn L. Lunetta, Xiaoling Zhang, Lindsay A. Farrer","doi":"10.1038/s41588-026-02722-8","DOIUrl":"10.1038/s41588-026-02722-8","url":null,"abstract":"Previously derived polygenic risk scores (PRSs) for Alzheimer’s disease (AD) perform inconsistently across diverse ancestries. We developed an APOE-independent multiancestry AD PRS using genome-wide association study summary statistics applied to European ancestry, African American, Caribbean Hispanic and East Asian cohorts. PRS performance was evaluated in a large independent multiancestry dataset and validated in several additional multiancestry cohorts. The PRS was significantly associated with AD in European ancestry, African American, Caribbean Hispanic and Native American Hispanic groups with adjusted odds ratios between 1.14 and 1.52 per PRS standard deviation. PRS performance was validated in the replication cohorts (odds ratios: 1.21–1.65). The PRS was also associated with poorer memory, executive function and language performance, greater AD-related neuropathological burden, reduced hippocampal volume, lower cerebrospinal fluid amyloid-β42 and elevated total tau and phosphorylated tau, with stronger phosphorylated tau associations observed in women. Our findings support the value of ancestry-aware PRSs as a component of broader multimodal risk stratification frameworks. An APOE-independent polygenic risk score for Alzheimer’s disease derived from multiancestry GWAS summary statistics shows consistent associations with cognitive, imaging, biomarker and neuropathological features in diverse populations.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2141-2151"},"PeriodicalIF":25.5,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-026-02722-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148840962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dissecting pleiotropy between major depressive disorder and physical disease comorbidities","authors":"Damian J. Woodward, William R. Reay, Briar Wormington, Santiago Diaz-Torres, Jue-Sheng Ong, Zachary F. Gerring, Jackson G. Thorp, Eske M. Derks","doi":"10.1038/s41588-026-02735-3","DOIUrl":"10.1038/s41588-026-02735-3","url":null,"abstract":"Major depressive disorder (MDD) is characterized by substantial comorbidity with medical conditions. To achieve better outcomes for patients with MDD, an improved understanding of the mechanisms underlying pervasive comorbidities is required. Here, to this end, we mapped patterns of pleiotropy by defining four clusters of physical diseases (cardiovascular, metabolic, gastrointestinal and immune) and analyzed their genetic relationships with MDD using genomic structural equation modeling. Three disease clusters exhibited independent associations with MDD and accounted for 47% of MDD h2SNP, with the gastrointestinal disease cluster having the strongest association (β = 0.63, s.e. = 0.05, P = 3.04 × 10−30). In addition, we identified independent loci associated with the shared genetic liability between each disease cluster and MDD, revealing different pleiotropic components. Characterization of these loci revealed previously unidentified associations with MDD and physical disease traits, along with unique biological pathways, drug groups, cell types and genes associated with each disease–MDD cluster. Our findings reveal genetic connections implicating the gut–brain axis as a key mechanism underlying the comorbidity of physical diseases in MDD. This work advances our understanding of MDD by highlighting unique and shared genetic components across different disease systems. This study uses genomic structural equation modeling to analyze genetic relationships between major depressive disorder and physical disease comorbidities and identifies independent loci associated with their shared genetic liability.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 9","pages":"2201-2210"},"PeriodicalIF":25.5,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-026-02735-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148830696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}