Pub Date : 2024-10-02DOI: 10.1038/s41588-024-01886-5
Immune recognition of cancers can be inhibited if the molecules that present cancer cell-specific antigens are disrupted. We have developed a tool that can detect four different types of disruption. Overall, we find that both genetic and non-genetic disruption of these molecules is common in lung and breast tumors.
{"title":"Genetic and non-genetic HLA disruption is widespread in lung and breast tumors","authors":"","doi":"10.1038/s41588-024-01886-5","DOIUrl":"10.1038/s41588-024-01886-5","url":null,"abstract":"Immune recognition of cancers can be inhibited if the molecules that present cancer cell-specific antigens are disrupted. We have developed a tool that can detect four different types of disruption. Overall, we find that both genetic and non-genetic disruption of these molecules is common in lung and breast tumors.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2008-2009"},"PeriodicalIF":31.7,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142362865","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 : 2024-09-30DOI: 10.1038/s41588-024-01933-1
Sanghyeon Park, Soyeon Kim, Beomsu Kim, Dan Say Kim, Jaeyoung Kim, Yeeun Ahn, Hyejin Kim, Minku Song, Injeong Shim, Sang-Hyuk Jung, Chamlee Cho, Soohyun Lim, Sanghoon Hong, Hyeonbin Jo, Akl C. Fahed, Pradeep Natarajan, Patrick T. Ellinor, Ali Torkamani, Woong-Yang Park, Tae Yang Yu, Woojae Myung, Hong-Hee Won
Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (nobserved = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS. Large-scale multivariate analyses across populations of European ancestry identify risk loci for the metabolic syndrome, improving polygenic prediction models and highlighting associations with diverse traits beyond cardiometabolic diseases.
{"title":"Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome","authors":"Sanghyeon Park, Soyeon Kim, Beomsu Kim, Dan Say Kim, Jaeyoung Kim, Yeeun Ahn, Hyejin Kim, Minku Song, Injeong Shim, Sang-Hyuk Jung, Chamlee Cho, Soohyun Lim, Sanghoon Hong, Hyeonbin Jo, Akl C. Fahed, Pradeep Natarajan, Patrick T. Ellinor, Ali Torkamani, Woong-Yang Park, Tae Yang Yu, Woojae Myung, Hong-Hee Won","doi":"10.1038/s41588-024-01933-1","DOIUrl":"10.1038/s41588-024-01933-1","url":null,"abstract":"Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (nobserved = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse diseases beyond cardiometabolic diseases. Polygenic risk score analysis demonstrated better discrimination of MetS and predictive power in European and East Asian populations. Altogether, our findings will guide future studies aimed at elucidating the genetic architecture of MetS. Large-scale multivariate analyses across populations of European ancestry identify risk loci for the metabolic syndrome, improving polygenic prediction models and highlighting associations with diverse traits beyond cardiometabolic diseases.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 11","pages":"2380-2391"},"PeriodicalIF":31.7,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-01933-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329658","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}
Machine learning (ML) has become increasingly popular in almost all scientific disciplines, including human genetics. Owing to challenges related to sample collection and precise phenotyping, ML-assisted genome-wide association study (GWAS), which uses sophisticated ML techniques to impute phenotypes and then performs GWAS on the imputed outcomes, have become increasingly common in complex trait genetics research. However, the validity of ML-assisted GWAS associations has not been carefully evaluated. Here, we report pervasive risks for false-positive associations in ML-assisted GWAS and introduce Post-Prediction GWAS (POP-GWAS), a statistical framework that redesigns GWAS on ML-imputed outcomes. POP-GWAS ensures valid and powerful statistical inference irrespective of imputation quality and choice of algorithm, requiring only GWAS summary statistics as input. We employed POP-GWAS to perform a GWAS of bone mineral density derived from dual-energy X-ray absorptiometry imaging at 14 skeletal sites, identifying 89 new loci and revealing skeletal site-specific genetic architecture. Our framework offers a robust analytic solution for future ML-assisted GWAS. Post-prediction genome-wide association study (POP-GWAS) is a statistical framework that uses summary statistics from labeled samples with both observed and imputed phenotypes to debias single-nucleotide polymorphism effect size estimates for unlabeled samples with imputed phenotypes only, leading to valid and powerful inference.
机器学习（ML）在包括人类遗传学在内的几乎所有科学学科中都越来越受欢迎。由于样本收集和精确表型方面的挑战，ML 辅助全基因组关联研究（GWAS）在复杂性状遗传学研究中越来越常见，该研究使用复杂的 ML 技术来推算表型，然后对推算结果进行 GWAS。然而，ML 辅助 GWAS 关联的有效性尚未得到仔细评估。在此，我们报告了 ML 辅助 GWAS 中普遍存在的假阳性关联风险，并介绍了预测后 GWAS（POP-GWAS）--一种在 ML 估算结果上重新设计 GWAS 的统计框架。POP-GWAS 不考虑估算质量和算法选择，只需将 GWAS 摘要统计作为输入，就能确保有效且强大的统计推断。我们利用 POP-GWAS 对 14 个骨骼部位的双能 X 射线吸收仪成像得出的骨矿物质密度进行了 GWAS 分析，发现了 89 个新的基因位点，并揭示了骨骼部位特异性遗传结构。我们的框架为未来的 ML 辅助 GWAS 提供了强大的分析解决方案。
{"title":"Valid inference for machine learning-assisted genome-wide association studies","authors":"Jiacheng Miao, Yixuan Wu, Zhongxuan Sun, Xinran Miao, Tianyuan Lu, Jiwei Zhao, Qiongshi Lu","doi":"10.1038/s41588-024-01934-0","DOIUrl":"10.1038/s41588-024-01934-0","url":null,"abstract":"Machine learning (ML) has become increasingly popular in almost all scientific disciplines, including human genetics. Owing to challenges related to sample collection and precise phenotyping, ML-assisted genome-wide association study (GWAS), which uses sophisticated ML techniques to impute phenotypes and then performs GWAS on the imputed outcomes, have become increasingly common in complex trait genetics research. However, the validity of ML-assisted GWAS associations has not been carefully evaluated. Here, we report pervasive risks for false-positive associations in ML-assisted GWAS and introduce Post-Prediction GWAS (POP-GWAS), a statistical framework that redesigns GWAS on ML-imputed outcomes. POP-GWAS ensures valid and powerful statistical inference irrespective of imputation quality and choice of algorithm, requiring only GWAS summary statistics as input. We employed POP-GWAS to perform a GWAS of bone mineral density derived from dual-energy X-ray absorptiometry imaging at 14 skeletal sites, identifying 89 new loci and revealing skeletal site-specific genetic architecture. Our framework offers a robust analytic solution for future ML-assisted GWAS. Post-prediction genome-wide association study (POP-GWAS) is a statistical framework that uses summary statistics from labeled samples with both observed and imputed phenotypes to debias single-nucleotide polymorphism effect size estimates for unlabeled samples with imputed phenotypes only, leading to valid and powerful inference.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 11","pages":"2361-2369"},"PeriodicalIF":31.7,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329615","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 : 2024-09-27DOI: 10.1038/s41588-024-01936-y
Edda G. Schulz, Alexandra Martitz
The mammalian inactive X chromosome shows unusual folding dominated by large-scale structures. A study finds a megadomain structure with a boundary at the Xist locus, preceding the well-known Dxz4-separated megadomains in somatic cells.
哺乳动物的非活性 X 染色体显示出以大规模结构为主的不寻常折叠。一项研究发现，在体细胞中众所周知的Dxz4分隔的巨型结构之前，Xist基因座上有一个具有边界的巨型结构。
{"title":"Structural remodeling of the inactive X chromosome during early mouse development","authors":"Edda G. Schulz, Alexandra Martitz","doi":"10.1038/s41588-024-01936-y","DOIUrl":"10.1038/s41588-024-01936-y","url":null,"abstract":"The mammalian inactive X chromosome shows unusual folding dominated by large-scale structures. A study finds a megadomain structure with a boundary at the Xist locus, preceding the well-known Dxz4-separated megadomains in somatic cells.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2004-2005"},"PeriodicalIF":31.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321964","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 : 2024-09-27DOI: 10.1038/s41588-024-01918-0
We identified methylated tandem repeat expansions that resemble the FMR1 CGG repeat that causes fragile X syndrome and investigated their association with traits in the UK Biobank. AFF3 expansion carriers had a 2.4-fold reduced probability of completing secondary education and were enriched in a cohort of individuals with intellectual disability.
{"title":"Methylated GCC repeat expansion in AFF3 associates with intellectual disability","authors":"","doi":"10.1038/s41588-024-01918-0","DOIUrl":"10.1038/s41588-024-01918-0","url":null,"abstract":"We identified methylated tandem repeat expansions that resemble the FMR1 CGG repeat that causes fragile X syndrome and investigated their association with traits in the UK Biobank. AFF3 expansion carriers had a 2.4-fold reduced probability of completing secondary education and were enriched in a cohort of individuals with intellectual disability.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 11","pages":"2302-2303"},"PeriodicalIF":31.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321967","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 : 2024-09-27DOI: 10.1038/s41588-024-01887-4
Primary cell cultures need to be frequently passaged, which limits the study of long-term biological processes, such as how mutant clones colonize aging epithelia. Esophageal epithelioids self-maintain for months, recapitulating progenitor cell behavior in vivo. Epithelioid CRISPR–Cas9 screens reveal genes encoding molecules that control cell fitness.
{"title":"Long-term 3D primary epithelioid cultures reveal genes that regulate esophageal cell fitness","authors":"","doi":"10.1038/s41588-024-01887-4","DOIUrl":"10.1038/s41588-024-01887-4","url":null,"abstract":"Primary cell cultures need to be frequently passaged, which limits the study of long-term biological processes, such as how mutant clones colonize aging epithelia. Esophageal epithelioids self-maintain for months, recapitulating progenitor cell behavior in vivo. Epithelioid CRISPR–Cas9 screens reveal genes encoding molecules that control cell fitness.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2010-2011"},"PeriodicalIF":31.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321978","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 : 2024-09-27DOI: 10.1038/s41588-024-01935-z
Cory Abate-Shen
A co-factor for the androgen receptor, NSD2, provides insights into context-specific functions of the androgen receptor and is a new target for intervention.
{"title":"Context-specific targeting of the androgen receptor in prostate cancer","authors":"Cory Abate-Shen","doi":"10.1038/s41588-024-01935-z","DOIUrl":"10.1038/s41588-024-01935-z","url":null,"abstract":"A co-factor for the androgen receptor, NSD2, provides insights into context-specific functions of the androgen receptor and is a new target for intervention.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2000-2001"},"PeriodicalIF":31.7,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321968","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 : 2024-09-26DOI: 10.1038/s41588-024-01909-1
Laurie Rumker, Saori Sakaue, Yakir Reshef, Joyce B. Kang, Seyhan Yazar, Jose Alquicira-Hernandez, Cristian Valencia, Kaitlyn A. Lagattuta, Annelise Mah-Som, Aparna Nathan, Joseph E. Powell, Po-Ru Loh, Soumya Raychaudhuri
Disease risk alleles influence the composition of cells present in the body, but modeling genetic effects on the cell states revealed by single-cell profiling is difficult because variant-associated states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce Genotype–Neighborhood Associations (GeNA), a statistical tool to identify cell-state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of single-cell RNA sequencing peripheral blood profiling from 969 individuals, GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (P = 1.96 × 10−11) associates with increased abundance of natural killer cells expressing tumor necrosis factor response programs. This csaQTL colocalizes with increased risk for psoriasis, an autoimmune disease that responds to anti-tumor necrosis factor treatments. Flexibly characterizing csaQTLs for granular cell states may help illuminate how genetic background alters cellular composition to confer disease risk. GeNA identifies cell-state abundance quantitative trait loci (csaQTLs) in single-cell RNA sequencing data. Applied to OneK1K, GeNA identifies natural killer cell and myeloid csaQTLs and implicates interferon-α-related cell states using a polygenic risk score for systemic lupus erythematosus.
{"title":"Identifying genetic variants that influence the abundance of cell states in single-cell data","authors":"Laurie Rumker, Saori Sakaue, Yakir Reshef, Joyce B. Kang, Seyhan Yazar, Jose Alquicira-Hernandez, Cristian Valencia, Kaitlyn A. Lagattuta, Annelise Mah-Som, Aparna Nathan, Joseph E. Powell, Po-Ru Loh, Soumya Raychaudhuri","doi":"10.1038/s41588-024-01909-1","DOIUrl":"10.1038/s41588-024-01909-1","url":null,"abstract":"Disease risk alleles influence the composition of cells present in the body, but modeling genetic effects on the cell states revealed by single-cell profiling is difficult because variant-associated states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce Genotype–Neighborhood Associations (GeNA), a statistical tool to identify cell-state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of single-cell RNA sequencing peripheral blood profiling from 969 individuals, GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (P = 1.96 × 10−11) associates with increased abundance of natural killer cells expressing tumor necrosis factor response programs. This csaQTL colocalizes with increased risk for psoriasis, an autoimmune disease that responds to anti-tumor necrosis factor treatments. Flexibly characterizing csaQTLs for granular cell states may help illuminate how genetic background alters cellular composition to confer disease risk. GeNA identifies cell-state abundance quantitative trait loci (csaQTLs) in single-cell RNA sequencing data. Applied to OneK1K, GeNA identifies natural killer cell and myeloid csaQTLs and implicates interferon-α-related cell states using a polygenic risk score for systemic lupus erythematosus.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"2068-2077"},"PeriodicalIF":31.7,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321138","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 : 2024-09-26DOI: 10.1038/s41588-024-01937-x
Samuel A. Lambert, Benjamin Wingfield, Joel T. Gibson, Laurent Gil, Santhi Ramachandran, Florent Yvon, Shirin Saverimuttu, Emily Tinsley, Elizabeth Lewis, Scott C. Ritchie, Jingqin Wu, Rodrigo Cánovas, Aoife McMahon, Laura W. Harris, Helen Parkinson, Michael Inouye
Polygenic scores (PGSs) have transformed human genetic research and have numerous potential clinical applications. Here we present a series of recent enhancements to the PGS Catalog and highlight the PGS Catalog Calculator, an open-source, scalable and portable pipeline for reproducibly calculating PGSs that democratizes equitable PGS applications.
{"title":"Enhancing the Polygenic Score Catalog with tools for score calculation and ancestry normalization","authors":"Samuel A. Lambert, Benjamin Wingfield, Joel T. Gibson, Laurent Gil, Santhi Ramachandran, Florent Yvon, Shirin Saverimuttu, Emily Tinsley, Elizabeth Lewis, Scott C. Ritchie, Jingqin Wu, Rodrigo Cánovas, Aoife McMahon, Laura W. Harris, Helen Parkinson, Michael Inouye","doi":"10.1038/s41588-024-01937-x","DOIUrl":"10.1038/s41588-024-01937-x","url":null,"abstract":"Polygenic scores (PGSs) have transformed human genetic research and have numerous potential clinical applications. Here we present a series of recent enhancements to the PGS Catalog and highlight the PGS Catalog Calculator, an open-source, scalable and portable pipeline for reproducibly calculating PGSs that democratizes equitable PGS applications.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 10","pages":"1989-1994"},"PeriodicalIF":31.7,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142321137","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：