Pub Date : 2025-11-27DOI: 10.1038/s41588-025-02414-9
Guido Barzaghi, Aristotelis Tsirigos
A study using single-cell 3D genome mapping reveals phenotypic convergence during mouse Kras-driven lung adenocarcinoma progression and prioritizes clinically actionable driver genes. This highlights the importance of cell-to-cell variation in chromatin architecture as a determinant of cancer evolution.
{"title":"Single-cell 3D architecture maps the drivers of lung adenocarcinoma","authors":"Guido Barzaghi, Aristotelis Tsirigos","doi":"10.1038/s41588-025-02414-9","DOIUrl":"10.1038/s41588-025-02414-9","url":null,"abstract":"A study using single-cell 3D genome mapping reveals phenotypic convergence during mouse Kras-driven lung adenocarcinoma progression and prioritizes clinically actionable driver genes. This highlights the importance of cell-to-cell variation in chromatin architecture as a determinant of cancer evolution.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2948-2949"},"PeriodicalIF":29.0,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609477","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 : 2025-11-27DOI: 10.1038/s41588-025-02413-w
Karsten Suhre, Qingwen Chen, Anna Halama, Kevin Mendez, Amber Dahlin, Nisha Stephan, Gaurav Thareja, Hina Sarwath, Harendra Guturu, Varun B. Dwaraka, Ryan Smith, Serafim Batzoglou, Frank Schmidt, Jessica A. Lasky-Su
Most studies to date of protein quantitative trait loci (pQTLs) have relied on affinity proteomics platforms, which provide only limited information about the targeted protein isoforms and may be affected by genetic variation in their epitope binding. Here we show that mass spectrometry (MS)-based proteomics can complement these studies and provide insights into the role of specific protein isoform and epitope-altering variants. Using the Seer Proteograph nanoparticle enrichment MS platform, we identified and replicated new pQTLs in a genome-wide association study of proteins in blood plasma samples from two cohorts and evaluated previously reported pQTLs from affinity proteomics platforms. We found that >30% of the evaluated pQTLs were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein abundance, whereas another 30% could not be replicated and are possibly due to epitope effects, although alternative explanations for nonreplication need to be considered on a case-by-case basis. Genome-wide association analyses of blood plasma samples using a mass spectrometry-based platform illustrate the complementarity of different proteomics approaches for identifying protein quantitative trait loci.
{"title":"A genome-wide association study of mass spectrometry proteomics using a nanoparticle enrichment platform","authors":"Karsten Suhre, Qingwen Chen, Anna Halama, Kevin Mendez, Amber Dahlin, Nisha Stephan, Gaurav Thareja, Hina Sarwath, Harendra Guturu, Varun B. Dwaraka, Ryan Smith, Serafim Batzoglou, Frank Schmidt, Jessica A. Lasky-Su","doi":"10.1038/s41588-025-02413-w","DOIUrl":"10.1038/s41588-025-02413-w","url":null,"abstract":"Most studies to date of protein quantitative trait loci (pQTLs) have relied on affinity proteomics platforms, which provide only limited information about the targeted protein isoforms and may be affected by genetic variation in their epitope binding. Here we show that mass spectrometry (MS)-based proteomics can complement these studies and provide insights into the role of specific protein isoform and epitope-altering variants. Using the Seer Proteograph nanoparticle enrichment MS platform, we identified and replicated new pQTLs in a genome-wide association study of proteins in blood plasma samples from two cohorts and evaluated previously reported pQTLs from affinity proteomics platforms. We found that >30% of the evaluated pQTLs were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein abundance, whereas another 30% could not be replicated and are possibly due to epitope effects, although alternative explanations for nonreplication need to be considered on a case-by-case basis. Genome-wide association analyses of blood plasma samples using a mass spectrometry-based platform illustrate the complementarity of different proteomics approaches for identifying protein quantitative trait loci.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2987-2996"},"PeriodicalIF":29.0,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02413-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145609479","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 : 2025-11-25DOI: 10.1038/s41588-025-02452-3
Vincent J. Straub, Stefania Benonisdottir, Augustine Kong, Melinda C. Mills
{"title":"Publisher Correction: Realizing the full potential of Our Future Health through data linkage and trans-biobank efforts","authors":"Vincent J. Straub, Stefania Benonisdottir, Augustine Kong, Melinda C. Mills","doi":"10.1038/s41588-025-02452-3","DOIUrl":"10.1038/s41588-025-02452-3","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3201-3201"},"PeriodicalIF":29.0,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02452-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593501","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 : 2025-11-25DOI: 10.1038/s41588-025-02427-4
Robbee Wedow
Creative use of informed statistical genetics methods combined with large-scale genomic data has delivered insights about sorting into educational fields. This study has wide-ranging implications for geneticists, sociogenomicists and social scientists for what can be learned about society within genetic data.
{"title":"Exploring educational field sorting using genetics","authors":"Robbee Wedow","doi":"10.1038/s41588-025-02427-4","DOIUrl":"10.1038/s41588-025-02427-4","url":null,"abstract":"Creative use of informed statistical genetics methods combined with large-scale genomic data has delivered insights about sorting into educational fields. This study has wide-ranging implications for geneticists, sociogenomicists and social scientists for what can be learned about society within genetic data.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2946-2947"},"PeriodicalIF":29.0,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593500","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 : 2025-11-25DOI: 10.1038/s41588-025-02425-6
The long-term contribution of human hematopoietic stem cell (HSC) clones to different blood lineages needs to be assessed under steady-state conditions over time. Using retrospective phylogenetic analysis and prospective clonal mutational tracing of all major blood lineages, we show that some HSC clones contribute stably to all lineages, while others show stable, intrinsically programmed lineage restriction.
{"title":"Stable, intrinsically programmed lineage restriction of human hematopoietic stem cells","authors":"","doi":"10.1038/s41588-025-02425-6","DOIUrl":"10.1038/s41588-025-02425-6","url":null,"abstract":"The long-term contribution of human hematopoietic stem cell (HSC) clones to different blood lineages needs to be assessed under steady-state conditions over time. Using retrospective phylogenetic analysis and prospective clonal mutational tracing of all major blood lineages, we show that some HSC clones contribute stably to all lineages, while others show stable, intrinsically programmed lineage restriction.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2958-2959"},"PeriodicalIF":29.0,"publicationDate":"2025-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145599448","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 : 2025-11-24DOI: 10.1038/s41588-025-02428-3
Ariella Angelini Stewart, Rebecca C. Ahrens-Nicklas, Shengdar Q. Tsai, Kiran Musunuru, Petros Giannikopoulos, Claire D. Clelland
CRISPR genetic therapies are revolutionizing the landscape of preclinical research and clinical studies, providing new potential routes for curative intervention for a range of previously untreatable diseases. As with any therapy, the therapeutic benefits and risks must be weighed against consideration of the disease threat. Genome-related adverse events are an inherent risk of CRISPR genetic therapies, including off-target edits. The perception that CRISPR therapies ought to have near-zero off-targets belies clinical medicine, therapy development and biology, which demonstrate that ‘perfect’ therapeutics do not exist. Given that not all genomic off-target events are equal, we provide a practical framework to evaluate and assess off-target safety based on the tools available today and ones that will be developed in the future. With the comprehensive information and assessment gathered using these guidelines, we aim to streamline the transition of CRISPR therapeutics from bench to bedside. This Perspective provides a practical and clinically relevant framework rooted in benefit–risk analyses to evaluate genomic CRISPR off-targets. Such an approach is applicable to currently available as well as future technologies.
{"title":"Measurement and clinical interpretation of CRISPR off-targets","authors":"Ariella Angelini Stewart, Rebecca C. Ahrens-Nicklas, Shengdar Q. Tsai, Kiran Musunuru, Petros Giannikopoulos, Claire D. Clelland","doi":"10.1038/s41588-025-02428-3","DOIUrl":"10.1038/s41588-025-02428-3","url":null,"abstract":"CRISPR genetic therapies are revolutionizing the landscape of preclinical research and clinical studies, providing new potential routes for curative intervention for a range of previously untreatable diseases. As with any therapy, the therapeutic benefits and risks must be weighed against consideration of the disease threat. Genome-related adverse events are an inherent risk of CRISPR genetic therapies, including off-target edits. The perception that CRISPR therapies ought to have near-zero off-targets belies clinical medicine, therapy development and biology, which demonstrate that ‘perfect’ therapeutics do not exist. Given that not all genomic off-target events are equal, we provide a practical framework to evaluate and assess off-target safety based on the tools available today and ones that will be developed in the future. With the comprehensive information and assessment gathered using these guidelines, we aim to streamline the transition of CRISPR therapeutics from bench to bedside. This Perspective provides a practical and clinically relevant framework rooted in benefit–risk analyses to evaluate genomic CRISPR off-targets. Such an approach is applicable to currently available as well as future technologies.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"58 1","pages":"20-27"},"PeriodicalIF":29.0,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583024","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 : 2025-11-24DOI: 10.1038/s41588-025-02407-8
Ziyu Li, Gang Luo, Changpei Gan, Huayu Zhang, Ling Li, Xiaoxun Zhang, Xudong Xing, Simeng Hu, Xu Tan, Jingjing Ding, Liangjun Zhang, Ying Peng, Ziqian Xu, Qiong Pan, Christopher D. Byrne, Giovanni Targher, Xiao-Zhi Jin, Wei Xie, Xinshou Ouyang, Ming-Hua Zheng, Fan Bai, Jin Chai
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. We generated single-cell and spatial transcriptomic and metabolomic maps from 61 human livers, including controls (n = 10), metabolic dysfunction-associated steatotic liver (MASL) (n = 17) and metabolic dysfunction-associated steatohepatitis (MASH) (n = 34). We identified microphthalmia-associated transcription factor (MITF) as a key regulator of the lipid-handling capacity of lipid-associated macrophages (LAMs), and further revealed a hepato-protective role of LAMs mediated through hepatocyte growth factor secretion. Unbiased deconvolution of spatial transcriptomics delineated a fibrosis-associated gene program enriched in advanced MASH, suggesting profibrotic crosstalk between central vein endothelial and hepatic stellate cells within fibrotic regions. Mass spectrometry imaging-based spatial metabolomics demonstrated MASLD-specific accumulation of phospholipids, potentially linked to lipoprotein-associated phospholipase A2-mediated phospholipid metabolism in LAMs. This spatially resolved multi-omics atlas of human MASLD, which can be queried at the Human Masld Spatial Multiomics Atlas , provides a valuable resource for mechanistic and therapeutic studies. Spatially resolved transcriptomic, metabolomic and proteomic analyses of human liver samples highlight the role of lipid-associated macrophages in metabolic dysfunction-associated steatotic liver disease.
{"title":"Spatially resolved multi-omics of human metabolic dysfunction-associated steatotic liver disease","authors":"Ziyu Li, Gang Luo, Changpei Gan, Huayu Zhang, Ling Li, Xiaoxun Zhang, Xudong Xing, Simeng Hu, Xu Tan, Jingjing Ding, Liangjun Zhang, Ying Peng, Ziqian Xu, Qiong Pan, Christopher D. Byrne, Giovanni Targher, Xiao-Zhi Jin, Wei Xie, Xinshou Ouyang, Ming-Hua Zheng, Fan Bai, Jin Chai","doi":"10.1038/s41588-025-02407-8","DOIUrl":"10.1038/s41588-025-02407-8","url":null,"abstract":"Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. We generated single-cell and spatial transcriptomic and metabolomic maps from 61 human livers, including controls (n = 10), metabolic dysfunction-associated steatotic liver (MASL) (n = 17) and metabolic dysfunction-associated steatohepatitis (MASH) (n = 34). We identified microphthalmia-associated transcription factor (MITF) as a key regulator of the lipid-handling capacity of lipid-associated macrophages (LAMs), and further revealed a hepato-protective role of LAMs mediated through hepatocyte growth factor secretion. Unbiased deconvolution of spatial transcriptomics delineated a fibrosis-associated gene program enriched in advanced MASH, suggesting profibrotic crosstalk between central vein endothelial and hepatic stellate cells within fibrotic regions. Mass spectrometry imaging-based spatial metabolomics demonstrated MASLD-specific accumulation of phospholipids, potentially linked to lipoprotein-associated phospholipase A2-mediated phospholipid metabolism in LAMs. This spatially resolved multi-omics atlas of human MASLD, which can be queried at the Human Masld Spatial Multiomics Atlas , provides a valuable resource for mechanistic and therapeutic studies. Spatially resolved transcriptomic, metabolomic and proteomic analyses of human liver samples highlight the role of lipid-associated macrophages in metabolic dysfunction-associated steatotic liver disease.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3112-3125"},"PeriodicalIF":29.0,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02407-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583019","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 : 2025-11-24DOI: 10.1038/s41588-025-02412-x
Sarah C. Nelson, Stephanie M. Gogarten, Jacklyn M. Dahlquist, Stephanie M. Fullerton
To inform deliberations around use of the Human Genome Diversity Project (HGDP) and related legacy data, we conducted a literature review of HGDP-derived data use from 2010 to 2024. Our analysis suggests broad re-use, possibly inconsistent with the original consent understandings. We urge caution with use of those data and similar datasets of unclear provenance.
{"title":"Human Genome Diversity Project data use and implications for the governance of legacy genomic data","authors":"Sarah C. Nelson, Stephanie M. Gogarten, Jacklyn M. Dahlquist, Stephanie M. Fullerton","doi":"10.1038/s41588-025-02412-x","DOIUrl":"10.1038/s41588-025-02412-x","url":null,"abstract":"To inform deliberations around use of the Human Genome Diversity Project (HGDP) and related legacy data, we conducted a literature review of HGDP-derived data use from 2010 to 2024. Our analysis suggests broad re-use, possibly inconsistent with the original consent understandings. We urge caution with use of those data and similar datasets of unclear provenance.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2937-2941"},"PeriodicalIF":29.0,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583023","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 : 2025-11-24DOI: 10.1038/s41588-025-02395-9
Johanna L. Smith, Clement A. Adebamowo, Sally N. Adebamowo, Burcu F. Darst, Stephanie M. Fullerton, Stephanie M. Gogarten, Marwan E. Hamed, Jibril B. Hirbo, Micah R. Hysong, Angad Singh Johar, Alyna T. Khan, Iftikhar J. Kullo, Iain R. Konigsberg, Peter Kraft, Leslie A. Lange, Yun Li, Alicia R. Martin, Sarah C. Nelson, Ananyo Choudhury, Michèle Ramsay, Ewan K. Cobran, Daniel J. Schaid, Jayati Sharma, Ying Wang, Genevieve L. Wojcik, Polygenic Risk Methods Development (PRIMED) Consortium, Quan Sun
The recent report from the National Academies of Sciences, Engineering and Medicine emphasizes the importance of detailed and tailored use of population descriptors in genomic analyses, but specific guidance for genomic data analysts is still lacking. In this Perspective, we focus on polygenic risk score (PRS) development and demonstrate that population descriptors are explicitly or implicitly involved in every step of the process. Attention to this matter is both an analytical concern and an ethical concern, as each decision has an impact on PRS results and performance across diverse populations. Drawing from the experience of the Polygenic Risk Methods Development (PRIMED) Consortium, we offer recommendations for applying population descriptors throughout the entire process of PRS development, validation and application. We urge the research community, particularly data analysts, to critically evaluate and justify their choices when using these descriptors to ensure both scientific rigor and research integrity. In this Perspective, authors from the Polygenic Risk Methods Development (PRIMED) Consortium highlight the ethical and analytical impact of population descriptors in polygenic risk score development and advocate for documenting detailed justifications.
{"title":"Recommendations for responsible use of population descriptors in polygenic risk score development","authors":"Johanna L. Smith, Clement A. Adebamowo, Sally N. Adebamowo, Burcu F. Darst, Stephanie M. Fullerton, Stephanie M. Gogarten, Marwan E. Hamed, Jibril B. Hirbo, Micah R. Hysong, Angad Singh Johar, Alyna T. Khan, Iftikhar J. Kullo, Iain R. Konigsberg, Peter Kraft, Leslie A. Lange, Yun Li, Alicia R. Martin, Sarah C. Nelson, Ananyo Choudhury, Michèle Ramsay, Ewan K. Cobran, Daniel J. Schaid, Jayati Sharma, Ying Wang, Genevieve L. Wojcik, Polygenic Risk Methods Development (PRIMED) Consortium, Quan Sun","doi":"10.1038/s41588-025-02395-9","DOIUrl":"10.1038/s41588-025-02395-9","url":null,"abstract":"The recent report from the National Academies of Sciences, Engineering and Medicine emphasizes the importance of detailed and tailored use of population descriptors in genomic analyses, but specific guidance for genomic data analysts is still lacking. In this Perspective, we focus on polygenic risk score (PRS) development and demonstrate that population descriptors are explicitly or implicitly involved in every step of the process. Attention to this matter is both an analytical concern and an ethical concern, as each decision has an impact on PRS results and performance across diverse populations. Drawing from the experience of the Polygenic Risk Methods Development (PRIMED) Consortium, we offer recommendations for applying population descriptors throughout the entire process of PRS development, validation and application. We urge the research community, particularly data analysts, to critically evaluate and justify their choices when using these descriptors to ensure both scientific rigor and research integrity. In this Perspective, authors from the Polygenic Risk Methods Development (PRIMED) Consortium highlight the ethical and analytical impact of population descriptors in polygenic risk score development and advocate for documenting detailed justifications.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"2962-2971"},"PeriodicalIF":29.0,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145596580","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 : 2025-11-24DOI: 10.1038/s41588-025-02400-1
Rose Orenbuch, Courtney A. Shearer, Aaron W. Kollasch, Aviv D. Spinner, Thomas Hopf, Lood van Niekerk, Dinko Franceschi, Mafalda Dias, Jonathan Frazer, Debora S. Marks
Missense variants remain a challenge in genetic interpretation owing to their subtle and context-dependent effects. Although current prediction models perform well in known disease genes, their scores are not calibrated across the proteome, limiting generalizability. To address this knowledge gap, we developed popEVE, a deep generative model combining evolutionary and human population data to estimate variant deleteriousness on a proteome-wide scale. popEVE achieves state-of-the-art performance without overestimating the burden of deleterious variants and identifies variants in 442 genes in a severe developmental disorder cohort, including 123 novel candidates. These genes are functionally similar to known disease genes, and their variants often localize to critical regions. Remarkably, popEVE can prioritize likely causal variants using only child exomes, enabling diagnosis even without parental sequencing. This work provides a generalizable framework for rare disease variant interpretation, especially in singleton cases, and demonstrates the utility of calibrated, evolution-informed scoring models for clinical genomics. popEVE is a proteome-wide deep generative model to identify and predict pathogenicity of missense mutations causing genetic disorders.
{"title":"Proteome-wide model for human disease genetics","authors":"Rose Orenbuch, Courtney A. Shearer, Aaron W. Kollasch, Aviv D. Spinner, Thomas Hopf, Lood van Niekerk, Dinko Franceschi, Mafalda Dias, Jonathan Frazer, Debora S. Marks","doi":"10.1038/s41588-025-02400-1","DOIUrl":"10.1038/s41588-025-02400-1","url":null,"abstract":"Missense variants remain a challenge in genetic interpretation owing to their subtle and context-dependent effects. Although current prediction models perform well in known disease genes, their scores are not calibrated across the proteome, limiting generalizability. To address this knowledge gap, we developed popEVE, a deep generative model combining evolutionary and human population data to estimate variant deleteriousness on a proteome-wide scale. popEVE achieves state-of-the-art performance without overestimating the burden of deleterious variants and identifies variants in 442 genes in a severe developmental disorder cohort, including 123 novel candidates. These genes are functionally similar to known disease genes, and their variants often localize to critical regions. Remarkably, popEVE can prioritize likely causal variants using only child exomes, enabling diagnosis even without parental sequencing. This work provides a generalizable framework for rare disease variant interpretation, especially in singleton cases, and demonstrates the utility of calibrated, evolution-informed scoring models for clinical genomics. popEVE is a proteome-wide deep generative model to identify and predict pathogenicity of missense mutations causing genetic disorders.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 12","pages":"3165-3174"},"PeriodicalIF":29.0,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41588-025-02400-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145583025","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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