Chengcheng Li, Jiaze Tang, Junshuan Cui, Niya Long, Wu Cen, Qibo Wu, Ming Yang, Liangzhao Chu, Xingwang Zhou
{"title":"大脑对表观遗传年龄加速的遗传影响:大规模遗传相关研究的证据。","authors":"Chengcheng Li, Jiaze Tang, Junshuan Cui, Niya Long, Wu Cen, Qibo Wu, Ming Yang, Liangzhao Chu, Xingwang Zhou","doi":"10.1007/s10522-025-10314-y","DOIUrl":null,"url":null,"abstract":"<p><p>The relationship between the brain and aging remains unclear. Our objective is to explore the causal connections between brain structure,gene expression, and traits associated with aging. Mendelian randomization(MR) analysis was conducted to explore the associations between brain structures and aging-related traits including GrimAge acceleration(GrimAA), PhenoAge acceleration (PhenoAA), HannumAge acceleration(HannumAA), HorvathAge acceleration(HorvathAA), and leukocyte telomere length(LTL). The Linkage Disequilibrium Score Regression(LDSC) method was employed to identify the shared genetic etiology between brain structures and aging. The Summary Data-based Mendelian Randomization(SMR) was utilized to investigate which brain genes have a causal influence on aging. We also examined the expression of the 8 genes derived from the SMR analysis across different cell types in post-mortem human brain specimens. The phenotypes potentially linked to genetics, as indicated by the LDSC outcomes, are as follows:148 phenotypes with GrimAA,150 phenotypes with HannumAA, 160 phenotypes with HorvathAA, 160 phenotypes with PhenoAA,and 110 phenotypes with LTL. Concerning the causal link between brain structures and aging-related traits, 7 brain structures consistently demonstrated a causative effect on GrimAA, while 29 brain structures exerted a causal influence on PhenoAA.Additionally, 7 BIDs revealed a causal relationship with HannumAA. There are 10 and 14 brain structures have a causative effect on HorvathAA and LTL, respectively. SMR revealed that 8 genes(CCDC144B, SHMT1, FAM106A, FAIM, CTD-2303H24.2, EBAG9P1, USP32P2 and OGFOD3) expression in different brain regions affected aging. These genes exhibit different expression patterns in various cells. Our results are in line with the possibility of a causal connection between aging and brain structure.</p>","PeriodicalId":8909,"journal":{"name":"Biogerontology","volume":"26 5","pages":"174"},"PeriodicalIF":4.1000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic influence of the brain on epigenetic age acceleration: evidence of a large-scale genetic correlation study.\",\"authors\":\"Chengcheng Li, Jiaze Tang, Junshuan Cui, Niya Long, Wu Cen, Qibo Wu, Ming Yang, Liangzhao Chu, Xingwang Zhou\",\"doi\":\"10.1007/s10522-025-10314-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The relationship between the brain and aging remains unclear. Our objective is to explore the causal connections between brain structure,gene expression, and traits associated with aging. Mendelian randomization(MR) analysis was conducted to explore the associations between brain structures and aging-related traits including GrimAge acceleration(GrimAA), PhenoAge acceleration (PhenoAA), HannumAge acceleration(HannumAA), HorvathAge acceleration(HorvathAA), and leukocyte telomere length(LTL). The Linkage Disequilibrium Score Regression(LDSC) method was employed to identify the shared genetic etiology between brain structures and aging. The Summary Data-based Mendelian Randomization(SMR) was utilized to investigate which brain genes have a causal influence on aging. We also examined the expression of the 8 genes derived from the SMR analysis across different cell types in post-mortem human brain specimens. The phenotypes potentially linked to genetics, as indicated by the LDSC outcomes, are as follows:148 phenotypes with GrimAA,150 phenotypes with HannumAA, 160 phenotypes with HorvathAA, 160 phenotypes with PhenoAA,and 110 phenotypes with LTL. Concerning the causal link between brain structures and aging-related traits, 7 brain structures consistently demonstrated a causative effect on GrimAA, while 29 brain structures exerted a causal influence on PhenoAA.Additionally, 7 BIDs revealed a causal relationship with HannumAA. There are 10 and 14 brain structures have a causative effect on HorvathAA and LTL, respectively. SMR revealed that 8 genes(CCDC144B, SHMT1, FAM106A, FAIM, CTD-2303H24.2, EBAG9P1, USP32P2 and OGFOD3) expression in different brain regions affected aging. These genes exhibit different expression patterns in various cells. Our results are in line with the possibility of a causal connection between aging and brain structure.</p>\",\"PeriodicalId\":8909,\"journal\":{\"name\":\"Biogerontology\",\"volume\":\"26 5\",\"pages\":\"174\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biogerontology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10522-025-10314-y\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GERIATRICS & GERONTOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biogerontology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10522-025-10314-y","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
Genetic influence of the brain on epigenetic age acceleration: evidence of a large-scale genetic correlation study.
The relationship between the brain and aging remains unclear. Our objective is to explore the causal connections between brain structure,gene expression, and traits associated with aging. Mendelian randomization(MR) analysis was conducted to explore the associations between brain structures and aging-related traits including GrimAge acceleration(GrimAA), PhenoAge acceleration (PhenoAA), HannumAge acceleration(HannumAA), HorvathAge acceleration(HorvathAA), and leukocyte telomere length(LTL). The Linkage Disequilibrium Score Regression(LDSC) method was employed to identify the shared genetic etiology between brain structures and aging. The Summary Data-based Mendelian Randomization(SMR) was utilized to investigate which brain genes have a causal influence on aging. We also examined the expression of the 8 genes derived from the SMR analysis across different cell types in post-mortem human brain specimens. The phenotypes potentially linked to genetics, as indicated by the LDSC outcomes, are as follows:148 phenotypes with GrimAA,150 phenotypes with HannumAA, 160 phenotypes with HorvathAA, 160 phenotypes with PhenoAA,and 110 phenotypes with LTL. Concerning the causal link between brain structures and aging-related traits, 7 brain structures consistently demonstrated a causative effect on GrimAA, while 29 brain structures exerted a causal influence on PhenoAA.Additionally, 7 BIDs revealed a causal relationship with HannumAA. There are 10 and 14 brain structures have a causative effect on HorvathAA and LTL, respectively. SMR revealed that 8 genes(CCDC144B, SHMT1, FAM106A, FAIM, CTD-2303H24.2, EBAG9P1, USP32P2 and OGFOD3) expression in different brain regions affected aging. These genes exhibit different expression patterns in various cells. Our results are in line with the possibility of a causal connection between aging and brain structure.
期刊介绍:
The journal Biogerontology offers a platform for research which aims primarily at achieving healthy old age accompanied by improved longevity. The focus is on efforts to understand, prevent, cure or minimize age-related impairments.
Biogerontology provides a peer-reviewed forum for publishing original research data, new ideas and discussions on modulating the aging process by physical, chemical and biological means, including transgenic and knockout organisms; cell culture systems to develop new approaches and health care products for maintaining or recovering the lost biochemical functions; immunology, autoimmunity and infection in aging; vertebrates, invertebrates, micro-organisms and plants for experimental studies on genetic determinants of aging and longevity; biodemography and theoretical models linking aging and survival kinetics.