Philippe Jawinski, Helena Forstbach, Holger Kirsten, Frauke Beyer, Arno Villringer, A Veronica Witte, Markus Scholz, Stephan Ripke, Sebastian Markett
{"title":"对大脑年龄的全基因组分析确定了59个相关位点,并揭示了与精神和身体健康的关系。","authors":"Philippe Jawinski, Helena Forstbach, Holger Kirsten, Frauke Beyer, Arno Villringer, A Veronica Witte, Markus Scholz, Stephan Ripke, Sebastian Markett","doi":"10.1038/s43587-025-00962-7","DOIUrl":null,"url":null,"abstract":"<p><p>Neuroimaging and machine learning are advancing research into the mechanisms of biological aging. In this field, 'brain age gap' has emerged as a promising magnetic resonance imaging-based biomarker that quantifies the deviation between an individual's biological and chronological age of the brain. Here we conducted an in-depth genomic analysis of the brain age gap and its relationships with over 1,000 health traits. Genome-wide analyses in up to 56,348 individuals unveiled a heritability of 23-29% attributable to common genetic variants and highlighted 59 associated loci (39 novel). The leading locus encompasses MAPT, encoding the tau protein central to Alzheimer's disease. Genetic correlations revealed relationships with mental health, physical health, lifestyle and socioeconomic traits, including depressed mood, diabetes, alcohol intake and income. Mendelian randomization indicated a causal role of high blood pressure and type 2 diabetes in accelerated brain aging. Our study highlights key genes and pathways related to neurogenesis, immune-system-related processes and small GTPase binding, laying the foundation for further mechanistic exploration.</p>","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":" ","pages":""},"PeriodicalIF":19.4000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genome-wide analysis of brain age identifies 59 associated loci and unveils relationships with mental and physical health.\",\"authors\":\"Philippe Jawinski, Helena Forstbach, Holger Kirsten, Frauke Beyer, Arno Villringer, A Veronica Witte, Markus Scholz, Stephan Ripke, Sebastian Markett\",\"doi\":\"10.1038/s43587-025-00962-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Neuroimaging and machine learning are advancing research into the mechanisms of biological aging. In this field, 'brain age gap' has emerged as a promising magnetic resonance imaging-based biomarker that quantifies the deviation between an individual's biological and chronological age of the brain. Here we conducted an in-depth genomic analysis of the brain age gap and its relationships with over 1,000 health traits. Genome-wide analyses in up to 56,348 individuals unveiled a heritability of 23-29% attributable to common genetic variants and highlighted 59 associated loci (39 novel). The leading locus encompasses MAPT, encoding the tau protein central to Alzheimer's disease. Genetic correlations revealed relationships with mental health, physical health, lifestyle and socioeconomic traits, including depressed mood, diabetes, alcohol intake and income. Mendelian randomization indicated a causal role of high blood pressure and type 2 diabetes in accelerated brain aging. Our study highlights key genes and pathways related to neurogenesis, immune-system-related processes and small GTPase binding, laying the foundation for further mechanistic exploration.</p>\",\"PeriodicalId\":94150,\"journal\":{\"name\":\"Nature aging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":19.4000,\"publicationDate\":\"2025-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s43587-025-00962-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43587-025-00962-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Genome-wide analysis of brain age identifies 59 associated loci and unveils relationships with mental and physical health.
Neuroimaging and machine learning are advancing research into the mechanisms of biological aging. In this field, 'brain age gap' has emerged as a promising magnetic resonance imaging-based biomarker that quantifies the deviation between an individual's biological and chronological age of the brain. Here we conducted an in-depth genomic analysis of the brain age gap and its relationships with over 1,000 health traits. Genome-wide analyses in up to 56,348 individuals unveiled a heritability of 23-29% attributable to common genetic variants and highlighted 59 associated loci (39 novel). The leading locus encompasses MAPT, encoding the tau protein central to Alzheimer's disease. Genetic correlations revealed relationships with mental health, physical health, lifestyle and socioeconomic traits, including depressed mood, diabetes, alcohol intake and income. Mendelian randomization indicated a causal role of high blood pressure and type 2 diabetes in accelerated brain aging. Our study highlights key genes and pathways related to neurogenesis, immune-system-related processes and small GTPase binding, laying the foundation for further mechanistic exploration.