Nature genetics最新文献

{"title":"An accidental scientist’s journey from an uncertain beginning to advancing neurogenetics research in Africa","authors":"Guida Landouré","doi":"10.1038/s41588-025-02453-2","DOIUrl":"10.1038/s41588-025-02453-2","url":null,"abstract":"Being an African scientist, I had to overcome several challenges to generate substantial data that shed light on the complexity of genomic medicine in African populations and abroad.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"2-2"},"PeriodicalIF":29.0,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145863840","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":"Aneuploidy-driven vulnerabilities in breast cancer metastasis","authors":"Samuel F. Bakhoum","doi":"10.1038/s41588-025-02444-3","DOIUrl":"10.1038/s41588-025-02444-3","url":null,"abstract":"A study reveals how chromosomal instability and resultant TP53 loss enhance fatty acid metabolism to drive breast cancer brain metastasis. This metabolic dependency provides new insights into therapeutic vulnerabilities of aneuploid tumors.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"14-15"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857391","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":"Unearthing soil biodiversity through collaborative genomic research and education","authors":"The BioDIGS Consortium, Tristen Alberts, Claude F. Albritton, Rosa Alcazar, Zainab Aljabri, Maria Alvarez, Anish Aradhey, Mentewab Ayalew, Nareh Azizian, Yasmeen Balayah, Destiny D. Ball, Efren Barragan, Corey Beshoar, Lyle Best, Emily Biggane, Joseph Biggane, Jesse Blick, Myron Blosser, Alex Kenneth Brown, Michael C. Campbell, Zoe Canizares, Faith N. Chanhuhwa, Yu Chen, Daniel R. Chin, Kamal Chowdhury, Tyler Collins, Blair Compton, Jefferson Da Silva, Nia R. Davis, Natalie DeCaro, Frida Delgadillo, Youping Deng, Joceph Duncan, Arinzechukwu C. Egwu, Grace D. Ekalle, Noha Elnawam, Ray Enke, Naomi Ewhe, Marco A. Ferrel, Janna Fierst, Grace Freymiller, Karla Fuller, Lena Fulton-Wright, Valeriya Gaysinskaya, Torrence Gill, Ellie Gillespie, Perla Gonzalez Moreno, Sara Goodwin, Natajha Graham, Madeline E. Graham, Joseph L. Graves Jr., Emily Grob, Rachael Gutierrez, Aisha Hager, Shazia Tabassum Hakim, Aaliyah Harris, Ava M. Hoffman, Tobias Hoffmann, Alani M. Horton, Allison Hughes, Elizabeth M. Humphries, Josh-Samuel Ikechi-Konkwo, Aadil Ishtiaq, Ryan Jackson, Joshua Ronnie James, Kaitlan James, Sydney A. Jamison, Armando Jimenez, Rachel Johnson, Abigail Kauffman, Harkiran Kaur, Kritika Kc, Analyse Keeton, Olivia E. Kelly, Jennifer Kerr, Nataliya Kucher, Donna Lee Kuehu, Wendy A. Larson, Joslynn Lee, Andrew Lee, Jeffrey T. Leek, Danilo Lemaic, Lincoln E. Liburd II, Alan Fernando Lopez, Mohammadamin Mahmanzar, Karwitha Mamae, Raffi Manjikian, Michael Marone, Katerin Marquez, Amara Martinson, Senem Mavruk Eskipehlivan, Ashley Medrano, Melanie Melendrez-Vallard, Robert Meller, Loyda B. Méndez, Miguel P. Mendez Gonzalez, Nicolli Mesquita, Concepcion Martinez Miller, Isam Mohd-Ibrahim, Peter Mortensen, Stephen Mosher, Alketa Muja, Nadia Nasrin, Masaki Nasu, Matthew H. Nguyen, Ba Thong Nguyen, Michele Nishiguchi, Lance M. O’Connor, Disomi Okie, Tolulope Olowookorun, Alex Ostrovsky, Keyan Ozuna, Asmita Pandey, Shiv B. Patel, Gauri Paul, Shrikant Pawar, Andrea Pearson, Deborah Petrik, Jordan Platero, Carl Pontino, Arjun P. Pratap, Siddharth Pratap, Yujia Qin, Sudhir Kumar Rai, Nisttha Ray, Ethan Repesh, Kristen Rhinehardt, Brennan Roche, Ariana Rodriguez, Shriya Roy, Sourav Roy, Alexa Sawa, Michael C. Schatz, Shurjo K. Sen, Randon Serikawa, Tyler Smith, Loraye Smith, James Sniezek, Ryley D. Stewart, Edu B. Suarez-Martinez, Joelle Taganna, Frederick J. Tan, Nikolaos Tsotakos, Nwanneka Udolisa, Katherine Ulbricht, Tanner Veo, Jennifer Vessio, Lia Walker, Oscar Wang, Qingguo Wang, Robert Wappel, Kalynn Wesby, Malachi Whitford, Nicole Wild, Xianfa Xie, Hua Yang, Sayumi York, Lindsay Zirkle","doi":"10.1038/s41588-025-02442-5","DOIUrl":"10.1038/s41588-025-02442-5","url":null,"abstract":"The BioDIGS project is a nationwide initiative involving students, researchers and educators across more than 40 research and teaching institutions. Participants lead sample collection, computational analysis and results interpretation to understand the relationships between the soil microbiome, environment and health.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"3-8"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857431","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":"p53 inactivation drives breast cancer metastasis to the brain through SCD1 upregulation and increased fatty acid metabolism","authors":"Kathrin Laue, Sabina Pozzi, Johanna Zerbib, Rebecca Bertolio, Yonatan Eliezer, Yael Cohen-Sharir, Tom Winkler, Manuel Caputo, Alessia A. Ricci, Lital Adler, Rami Khoury, Giuseppe Longobardi, Rachel Slutsky, Alicia I. Leikin-Frenkel, Shai Ovadia, Katharina Lange, Alessandra Rustighi, Silvano Piazza, Andrea Sacconi, Rayna Y. Magesh, Faith N. Keller, Jean Berthelet, Alexander Schäffer, Ron Saad, Sahar Israeli Dangoor, Karolina Szczepanowska, Iris Barshack, Yang Liao, Sergey Malitsky, Alexander Brandis, Thomas Broggini, Marcus Czabanka, Wei Shi, Delphine Merino, Emma V. Watson, Giovanni Blandino, Ayelet Erez, Ruth Ashery-Padan, Hind Medyouf, Luca Bertero, Giannino Del Sal, Ronit Satchi-Fainaro, Uri Ben-David","doi":"10.1038/s41588-025-02446-1","DOIUrl":"10.1038/s41588-025-02446-1","url":null,"abstract":"Brain metastasis (BM) carries a poor prognosis, yet the molecular basis of brain tropism remains unclear. Analysis of breast cancer BM (BCBM) revealed pervasive p53 inactivation through mutations and/or aneuploidy, with pathway disruption already present in primary tumors. Functionally, p53 inactivation markedly increased BCBM formation and growth in vivo, causally linking p53 perturbation to BM. Mechanistically, p53 inactivation upregulated SCD1 and fatty acid synthesis (FAS), essential for brain-metastasizing cells; SCD1 knockout abolished the p53-dependent growth advantage. Molecularly, p53 suppressed SCD1 directly through promoter binding and indirectly by downregulating its co-activator DEPDC1. Astrocytes further enhanced FAS by secreting factors that were metabolized in a p53-dependent manner, promoting tumor survival, proliferation and migration. Finally, p53-deficient tumors were sensitive to FAS inhibition ex vivo and in vivo. Thus, we identify p53 inactivation as a driver of BCBM, reveal p53-dependent and astrocyte-dependent FAS modulation and highlight FAS as a therapeutically targetable BCBM vulnerability. This study associates p53 loss and brain metastasis in breast cancer. Mechanistically, p53-null tumors recruit astrocytes that provide substrates for enhanced fatty acid synthesis via upregulated SCD1 expression, representing a targetable axis in the disease.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"116-131"},"PeriodicalIF":29.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145857415","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":"Designing synthetic regulatory elements using the generative AI framework DNA-Diffusion","authors":"Lucas Ferreira DaSilva, Simon Senan, Judith F. Kribelbauer-Swietek, Zain Munir Patel, Lithin Karmel Louis, Aniketh Janardhan Reddy, Sameer Gabbita, Jonathan D. Rosen, Zach Nussbaum, César Miguel Valdez Córdova, Aaron Wenteler, Noah Weber, Tin M. Tunjic, Martino Mansoldo, Talha Ahmad Khan, Gue-Ho Hwang, Vincent Gardeux, David T. Humphreys, Cameron Smith, Matei Bejan, Peter Bromley, Will Connell, Bart Deplancke, Michael I. Love, Emily S. Wong, Wouter Meuleman, Luca Pinello","doi":"10.1038/s41588-025-02441-6","DOIUrl":"10.1038/s41588-025-02441-6","url":null,"abstract":"Systematically designing regulatory elements for precise gene expression control remains a central challenge in genomics and synthetic biology. Here we introduce DNA-Diffusion, a generative artificial intelligence framework that uses machine learning trained on DNA accessibility data from diverse cell lines to design compact regulatory elements with cell-type-specific activity. We show that DNA-Diffusion generates 200-base-pair synthetic elements that recapitulate endogenous transcription factor binding grammar while exhibiting enhanced cell-type specificity. We validated these elements using a 5,850-element STARR-seq library across three cell lines. Moreover, we demonstrated successful endogenous gene modulation using EXTRA-seq, reactivating AXIN2, a leukemia-protective gene, in its native genomic context. Our approach outperforms existing computational methods in balancing functional activity with cell-type specificity while maintaining sequence diversity. This work establishes DNA-Diffusion as a powerful tool for engineering compact, highly specific regulatory elements crucial for advancing gene therapies and understanding gene regulation. The authors present DNA-Diffusion, a generative AI framework that designs synthetic regulatory elements with tunable cell-type specificity. Experimental validation demonstrates their ability to reactivate AXIN2 expression, a leukemia-protective gene, in its native genomic context.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"180-194"},"PeriodicalIF":29.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145808166","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":"Generative AI creates synthetic regulatory DNA sequences for precision gene control","authors":"","doi":"10.1038/s41588-025-02443-4","DOIUrl":"10.1038/s41588-025-02443-4","url":null,"abstract":"We developed DNA-Diffusion, a generative artificial intelligence (AI) method that creates synthetic regulatory elements showing enhanced activity. Multiple synthetic elements demonstrated superior cell-type-specific expression in computational predictions and episomal assays, and when integrated at AXIN2, a leukemia-protective gene, outperformed naturally occurring protective variants, opening new possibilities for precision gene therapies.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"18-19"},"PeriodicalIF":29.0,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813557","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":"Mutation patterns drive mismatch repair-deficient glioma evolution","authors":"","doi":"10.1038/s41588-025-02424-7","DOIUrl":"10.1038/s41588-025-02424-7","url":null,"abstract":"Primary mismatch repair-deficient gliomas are hypermutant but molecularly heterogeneous cancers with poor prognosis. We show that non-random mutational signatures cause somatic mutations in key glioma drivers that define genetic subgroups of this disease. Each subgroup harbors distinct mechanisms of genomic instability that shape their biological behaviors and immunotherapy responses.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"16-17"},"PeriodicalIF":29.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145807959","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":"Patterns of hypermutation shape tumorigenesis and immunotherapy response in mismatch-repair-deficient glioma","authors":"Nicholas R. Fernandez, Yuan Chang, Nuno M. Nunes, Jose R. Dimayacyac, Adrian Levine, Amit Ringel, Logine Negm, Ayse Bahar Ercan, Julian M. Hess, Olfat Ahmad, Caitlin Lee, Lucie Stengs, Vanessa Bianchi, Melissa Edwards, Sheradan Doherty, Jiil Chung, Liana Nobre, Julie Bennett, Andrew J. Dodgshun, David T. W. Jones, Stefan M. Pfister, Anita Villani, David Malkin, Vijay Ramaswamy, Annie Huang, Eric Bouffet, Melyssa Aronson, Peter B. Dirks, Adam Shlien, Gad Getz, Yosef E. Maruvka, Birgit Ertl-Wagner, Cynthia Hawkins, Anirban Das, Uri Tabori","doi":"10.1038/s41588-025-02420-x","DOIUrl":"10.1038/s41588-025-02420-x","url":null,"abstract":"Primary mismatch-repair-deficient high-grade gliomas (priMMRD-HGG) are lethal tumors characterized by hypermutation, resistance to chemoradiation and variable response to immunotherapy. To investigate the mechanisms governing the emergence of driver mutations and their impact on gliomagenesis and patient outcomes, we analyzed genomic and clinical data from 162 priMMRD-HGG. Here we identified three subgroups defined by secondary driver mutations in replicative DNA polymerases or IDH1. These subgroups converge on glioma drivers through distinct combinations of genomic instability–generating mechanisms, displaying an inverse correlation between point mutations and copy number alterations. MMRD signatures drive the emergence of specific mutations in TP53 and IDH1, notably excluding common pediatric glioma drivers. Global hypomethylation stratifies priMMRD-HGG into a unique methylation cluster. DNA-polymerasemut priMMRD-HGG exhibit ultrahypermutation, an immune-hot microenvironment and immunotherapy responsiveness, whereas IDH1mut priMMRD-HGG are immune-cold and immunotherapy resistant. MMRD-driven gliomagenesis defines the role of nonrandom mutagenesis patterns in cancer development, providing frameworks for targeted and immune-therapeutics. The authors analyze 162 primary mismatch-repair-deficient gliomas and identify three subgroups underpinned by distinct somatic mutations in replicative DNA polymerases and IDH1.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"132-142"},"PeriodicalIF":29.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145801595","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":"Multitrait analyses identify genetic variants associated with aortic valve function and aortic stenosis risk","authors":"Shinwan Kany, Joel T. Rämö, Cody Hou, Sean J. Jurgens, Shaan Khurshid, Victor Nauffal, Jonathan W. Cunningham, Emily S. Lau, Satoshi Koyama, FinnGen, Jennifer E. Ho, Jeffrey E. Olgin, Sammy Elmariah, Aarno Palotie, Mark E. Lindsay, Patrick T. Ellinor, James P. Pirruccello","doi":"10.1038/s41588-025-02397-7","DOIUrl":"10.1038/s41588-025-02397-7","url":null,"abstract":"The genetic influences on normal aortic valve function and their impact on aortic stenosis risk are of substantial interest. We used deep learning to measure peak velocity, mean gradient and aortic valve area from magnetic resonance imaging and conducted genome-wide association studies (GWAS) in 59,571 participants in the UK Biobank. Incorporating the aortic valve measurement GWAS with aortic stenosis GWAS using multitrait analysis of GWAS (MTAG), we identified 166 distinct loci (134 with aortic valve traits, 134 with aortic stenosis and 166 unique loci across all GWAS), including PCSK9 and LDLR. The MTAG aortic stenosis PGS was associated with aortic stenosis in All of Us (hazard ratio (HR) = 3.32 for top 5% versus all others, P = 8.8 × 10−22) and Mass General Brigham Biobank (HR = 2.76, P = 7.8 × 10−15). Using Mendelian randomization, we found evidence supporting a potential causal role for Lp(a) and LDL on aortic valve function. These findings have implications for the early pathogenesis of aortic stenosis and suggest modifiable pathways as targets for preventive therapy. Genome-wide association studies (GWAS) of deep learning-derived measurements of aortic valve function, along with multitrait analyses incorporating disease-based GWAS, identify 166 genetic loci associated with aortic valve function or aortic stenosis.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"47-56"},"PeriodicalIF":29.0,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02397-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786290","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":"Genomic and transcriptomic analyses of aortic stenosis enhance therapeutic target discovery and disease prediction","authors":"Aeron M. Small, Ta-Yu Yang, Shinsuke Itoh, Sébastien Thériault, Line Dufresne, Ryo Kurosawa, Issei Komuro, Koichi Matsuda, Ha My T. Vy, Eric H. Farber-Eger, Lauren Lee Shaffer, Kristin M. Boulier, Kristin M. Corey, Megan E. Ramaker, Fabien Laporte, Jean-Jacques Schott, Solena Le Scouarnec, Sasha A. Singh, Abhijeet R. Sonawane, Harry A. Smith, Nicholas Rafaels, Colorado Center for Personalized Medicine, Jonas Ghouse, Anna A. Raja, Sisse R. Ostrowski, Erik Sørensen, Christina Mikkelsen, Ole B. Pedersen, Christian Erikstrup, Henrik Ullum, DBDS Genomic Consortium, Gardar Sveinbjornsson, Daniel F. Gudbjartsson, Erik Abner, Estonian Biobank Research Team, Jiwoo Lee, Andrea Ganna, Ulrike Nowak-Göttl, Sarah Finer, Genes & Health Research Team, Johannes Schumacher, Carlo Maj, Baravan Al-Kassou, Georg Nickenig, Teresa Trenkwalder, Martina Dreβen, Markus Krane, Markus M. Nöthen, Marta R. Moksnes, Ben M. Brumpton, Stacey Knight, Kirk U. Knowlton, Lincoln Nadauld, Radek Debiec, Muntaser D. Musameh, Peter S. Braund, Christopher P. Nelson, Tomasz Czuba, Olle Melander, Margaret Sunitha Selvaraj, Satoshi Koyama, Rohan Bhukar, Yunfeng Ruan, Johan Ljungberg, Scott M. Damrauer, Michael G. Levin, Andre Franke, Klaus Berger, Christian T. Ruff, Giorgio E. M. Melloni, Frederick K. Kamanu, Kaoru Ito, Ron Do, Ruth J. F. Loos, Heribert Schunkert, Quinn S. Wells, Svati H. Shah, Thierry Le Tourneau, David Messika-Zeitoun, Christopher Gignoux, Henning Bundgaard, Susanna C. Larsson, Karl Michaëlsson, Hilma Holm, Anna Helgadottir, Tonu Esko, David A. van Heel, Patrick Mathieu, Nilesh J. Samani, J. Gustav Smith, Stefan Söderberg, Daniel J. Rader, Nicholas A. Marston, Marc S. Sabatine, Bogdan Pasaniuc, Kelly Cho, Peter W. F. Wilson, Christopher J. O’Donnell, Kari Stefansson, Yohan Bossé, Elena Aikawa, James C. Engert, Gina M. Peloso, Pradeep Natarajan, George Thanassoulis","doi":"10.1038/s41588-025-02417-6","DOIUrl":"10.1038/s41588-025-02417-6","url":null,"abstract":"Aortic stenosis (AS) is a common valvular heart disease and has no pharmacological therapies. We performed a multi-ancestry genome-wide association meta-analysis of 86,864 AS cases among 2,853,408 individuals, discovering 241 autosomal independent risk loci and 3 X chromosome risk loci. We additionally performed sex-stratified and ancestry-stratified genome-wide association studies (GWASs), identifying an additional 5 sex-specific risk loci, 11 risk loci in European ancestry individuals and 1 risk locus in African ancestry individuals. We also performed a transcriptome-wide association study using expression quantitative trait loci from human aortic valves, discovering 54 new genes for which genetically predicted expression influences the risk of AS. We then generated a new polygenic risk score for AS. Finally, we performed gene silencing experiments targeting biologically relevant genes identified by our GWAS. Silencing of CMKLR1 and LTBP4 in human valvular interstitial cells substantially decreased mineralization, implicating a role for polyunsaturated fatty acids and transforming growth factor β signaling in AS. Multi-ancestry genome-wide and transcriptome-wide association studies of aortic stenosis identify more than 200 independent risk loci and provide insights into its genetic architecture.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"57-66"},"PeriodicalIF":29.0,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02417-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786201","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}