Pub Date : 2025-12-23DOI: 10.1038/s41588-025-02441-6
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
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.
{"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}
Pub Date : 2025-12-23DOI: 10.1038/s41588-025-02443-4
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.
{"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}
Pub Date : 2025-12-22DOI: 10.1038/s41588-025-02424-7
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.
{"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}
Pub Date : 2025-12-22DOI: 10.1038/s41588-025-02420-x
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
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.
{"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}
Pub Date : 2025-12-19DOI: 10.1038/s41588-025-02397-7
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
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.
基因对正常主动脉瓣功能的影响及其对主动脉瓣狭窄风险的影响是非常有趣的。我们使用深度学习来测量磁共振成像的峰值速度、平均梯度和主动脉瓣面积，并在英国生物银行的59,571名参与者中进行了全基因组关联研究（GWAS）。利用多性状分析（MTAG），我们确定了166个不同的基因座（134个与主动脉瓣性状相关，134个与主动脉瓣狭窄相关，166个在所有GWAS中都有独特的基因座），包括PCSK9和LDLR。MTAG主动脉狭窄PGS与我们所有人的主动脉狭窄相关（前5%的风险比(HR) = 3.32, P = 8.8 × 10-22）和Mass General Brigham Biobank （HR = 2.76, P = 7.8 × 10-15）。通过孟德尔随机化，我们发现了支持Lp(a)和LDL对主动脉瓣功能潜在因果作用的证据。这些发现提示了主动脉瓣狭窄的早期发病机制，并建议将可改变的途径作为预防治疗的目标。
{"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}
Pub Date : 2025-12-19DOI: 10.1038/s41588-025-02417-6
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
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.
{"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}
Pub Date : 2025-12-18DOI: 10.1038/s41588-025-02408-7
Georgios Kanellos, Chiara Giacomelli, Alexander Raven, Nikola Vlahov, Hu Jin, Pauline Herviou, Sudhir B. Malla, Nadia Nasreddin, Patricia P. Centeno, Constantinos Alexandrou, Kathryn Gilroy, Rachel L. Baird, Kathryn Pennel, June Munro, Joseph A. Waldron, Holly Hall, Leah Officer-Jones, Sheila Bryson, Douglas Strathdee, Sergio Lilla, Sara Zanivan, Vivienne Morrison, Colin Nixon, Rachel A. Ridgway, Crispin Miller, John R. P. Knight, Andrew D. Campbell, Philip D. Dunne, John Le Quesne, Joanne Edwards, Peter J. Park, Martin Bushell, Owen J. Sansom
Nucleophosmin (NPM1), a nucleolar protein frequently mutated in hematopoietic malignancies, is overexpressed in several solid tumors with poorly understood functional roles. Here, we demonstrate that Npm1 is upregulated after APC loss in WNT-responsive tissues and supports WNT-driven intestinal and liver tumorigenesis. Mechanistically, NPM1 loss induces ribosome pausing and accumulation at the 5’-end of coding sequences, triggering a protein synthesis stress response and p53 activation, which mediate this antitumorigenic effect. Collectively, our data identify NPM1 as a critical WNT effector that sustains WNT-driven hyperproliferation and tumorigenesis by attenuating the integrated stress response and p53 activation. Notably, NPM1 expression correlates with elevated WNT signaling and proliferation in human colorectal cancer (CRC), while CRCs harboring NPM1 deletions exhibit preferential TP53 inactivation, underscoring the clinical relevance of our findings. Being dispensable for adult epithelial homeostasis, NPM1 represents a promising therapeutic target in p53-proficient WNT-driven tumors, including treatment-refractory KRAS-mutant CRC, and hepatic cancers. Npm1 promotes tumor formation via attenuating the integrated stress response and p53 activation in mouse WNT-driven intestinal and liver tumorigenesis.
{"title":"Nucleophosmin supports WNT-driven hyperproliferation and tumor initiation","authors":"Georgios Kanellos, Chiara Giacomelli, Alexander Raven, Nikola Vlahov, Hu Jin, Pauline Herviou, Sudhir B. Malla, Nadia Nasreddin, Patricia P. Centeno, Constantinos Alexandrou, Kathryn Gilroy, Rachel L. Baird, Kathryn Pennel, June Munro, Joseph A. Waldron, Holly Hall, Leah Officer-Jones, Sheila Bryson, Douglas Strathdee, Sergio Lilla, Sara Zanivan, Vivienne Morrison, Colin Nixon, Rachel A. Ridgway, Crispin Miller, John R. P. Knight, Andrew D. Campbell, Philip D. Dunne, John Le Quesne, Joanne Edwards, Peter J. Park, Martin Bushell, Owen J. Sansom","doi":"10.1038/s41588-025-02408-7","DOIUrl":"10.1038/s41588-025-02408-7","url":null,"abstract":"Nucleophosmin (NPM1), a nucleolar protein frequently mutated in hematopoietic malignancies, is overexpressed in several solid tumors with poorly understood functional roles. Here, we demonstrate that Npm1 is upregulated after APC loss in WNT-responsive tissues and supports WNT-driven intestinal and liver tumorigenesis. Mechanistically, NPM1 loss induces ribosome pausing and accumulation at the 5’-end of coding sequences, triggering a protein synthesis stress response and p53 activation, which mediate this antitumorigenic effect. Collectively, our data identify NPM1 as a critical WNT effector that sustains WNT-driven hyperproliferation and tumorigenesis by attenuating the integrated stress response and p53 activation. Notably, NPM1 expression correlates with elevated WNT signaling and proliferation in human colorectal cancer (CRC), while CRCs harboring NPM1 deletions exhibit preferential TP53 inactivation, underscoring the clinical relevance of our findings. Being dispensable for adult epithelial homeostasis, NPM1 represents a promising therapeutic target in p53-proficient WNT-driven tumors, including treatment-refractory KRAS-mutant CRC, and hepatic cancers. Npm1 promotes tumor formation via attenuating the integrated stress response and p53 activation in mouse WNT-driven intestinal and liver tumorigenesis.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"100-115"},"PeriodicalIF":29.0,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02408-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770712","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}
Pub Date : 2025-12-17DOI: 10.1038/s41588-025-02445-2
Kevin T. Mintz
In 1990, I was diagnosed with cerebral palsy. Like many in the community, my parents were told explicitly that the condition has no genetic roots. Now, as research suggests that up to 30% of cases have genetic etiologies, robust community engagement is needed to ensure that the perspectives of the community shape the future of genetic research into cerebral palsy.
{"title":"My call for community-engaged genetic research into cerebral palsy","authors":"Kevin T. Mintz","doi":"10.1038/s41588-025-02445-2","DOIUrl":"10.1038/s41588-025-02445-2","url":null,"abstract":"In 1990, I was diagnosed with cerebral palsy. Like many in the community, my parents were told explicitly that the condition has no genetic roots. Now, as research suggests that up to 30% of cases have genetic etiologies, robust community engagement is needed to ensure that the perspectives of the community shape the future of genetic research into cerebral palsy.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"1-1"},"PeriodicalIF":29.0,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145770713","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}
Enhancer-promoter (E-P) interactions regulate transcription during cell fate determination. However, the regulatory mechanisms underlying E-P interactions have remained elusive. Here we present a chromatin-interaction-based proteomic approach, LoopID, to profile proteins (termed the looposome) at certain E-P anchors. We find that histone demethylase JMJD2, a key looposome component, can regulate E-P interactions and the looposome in a catalytic-independent manner through formation of biomolecular condensates. Furthermore, we introduce a system to engineer E-P interactions by assembling JMJD2 condensates at certain genomic loci, enabling construction of cell-type-specific E-P interactions to promote cellular reprogramming into pluripotent or two-cell-like cells. Our findings reveal a noncanonical function of a histone demethylase in regulation of chromatin organization and provide a strategy to regulate cell fate transitions through E-P interactions.
{"title":"JMJD2 regulates enhancer-promoter interactions via biomolecular condensate formation.","authors":"Shaoshuai Jiang,Xinyi Liu,Zhuheng Zhang,Mingzhu Yang,Xing Zhu,Lin Ma,Longying Zhao,Xiaoru Ling,Ziqiang Zhou,Ziqiang Wu,Jiale Qu,Haochen Li,Jiawei Liang,Zhiheng Deng,Qi Tian,Xiaona Huang,Xianglin Huang,Jin Tan,Jun Sun,Jia Wang,Diana Guallar,Partha Pratim Das,Luca Pinello,Liang Wang,Hongfu Wu,Dong-Feng Huang,Jichang Wang,Hancheng Lin,Jin Bai,Lili Fan,Wei Chi,Xue Xiao,Junjun Ding","doi":"10.1038/s41588-025-02415-8","DOIUrl":"https://doi.org/10.1038/s41588-025-02415-8","url":null,"abstract":"Enhancer-promoter (E-P) interactions regulate transcription during cell fate determination. However, the regulatory mechanisms underlying E-P interactions have remained elusive. Here we present a chromatin-interaction-based proteomic approach, LoopID, to profile proteins (termed the looposome) at certain E-P anchors. We find that histone demethylase JMJD2, a key looposome component, can regulate E-P interactions and the looposome in a catalytic-independent manner through formation of biomolecular condensates. Furthermore, we introduce a system to engineer E-P interactions by assembling JMJD2 condensates at certain genomic loci, enabling construction of cell-type-specific E-P interactions to promote cellular reprogramming into pluripotent or two-cell-like cells. Our findings reveal a noncanonical function of a histone demethylase in regulation of chromatin organization and provide a strategy to regulate cell fate transitions through E-P interactions.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"1 1","pages":""},"PeriodicalIF":30.8,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145765286","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}
Pub Date : 2025-12-16DOI: 10.1038/s41588-025-02477-8
Takeo Narita, Sinan Kilic, Yoshiki Higashijima, Natalie M. Scherer, Georgios Pappas, Elina Maskey, Chunaram Choudhary
{"title":"Author Correction: Disentangling the architectural and non-architectural functions of CTCF and cohesin in gene regulation","authors":"Takeo Narita, Sinan Kilic, Yoshiki Higashijima, Natalie M. Scherer, Georgios Pappas, Elina Maskey, Chunaram Choudhary","doi":"10.1038/s41588-025-02477-8","DOIUrl":"10.1038/s41588-025-02477-8","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"230-230"},"PeriodicalIF":29.0,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02477-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145768676","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}
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