Wanheng Zhang, Xiao Zhang, Chuan Qiu, Zichen Zhang, Kuan-Jui Su, Zhe Luo, Minghui Liu, Bingxin Zhao, Lang Wu, Qing Tian, Hui Shen, Chong Wu, Hong-Wen Deng
{"title":"An atlas of genetic effects on the monocyte methylome across European and African populations.","authors":"Wanheng Zhang, Xiao Zhang, Chuan Qiu, Zichen Zhang, Kuan-Jui Su, Zhe Luo, Minghui Liu, Bingxin Zhao, Lang Wu, Qing Tian, Hui Shen, Chong Wu, Hong-Wen Deng","doi":"10.1101/2024.08.12.24311885","DOIUrl":null,"url":null,"abstract":"<p><p>Elucidating the genetic architecture of DNA methylation is crucial for decoding complex disease etiology. However, current epigenomic studies are often limited by incomplete methylation coverage and heterogeneous tissue samples. Here, we present the first comprehensive, multi-ancestry human methylome atlas of purified human monocytes, generated through integrated whole-genome bisulfite sequencing and whole-genome sequencing from 298 European Americans (EA) and 160 African Americans (AA). By analyzing over 25 million methylation sites, we identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in <i>cis-</i> regions for EA and AA populations, respectively, revealing both shared (880,108 sites) and population-specific regulatory patterns. Furthermore, we developed population-specific DNAm imputation models, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. These models were validated through multi-ancestry analysis of 41 complex traits from the Million Veteran Program. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .</p>","PeriodicalId":94281,"journal":{"name":"medRxiv : the preprint server for health sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11361221/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv : the preprint server for health sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.12.24311885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Elucidating the genetic architecture of DNA methylation is crucial for decoding complex disease etiology. However, current epigenomic studies are often limited by incomplete methylation coverage and heterogeneous tissue samples. Here, we present the first comprehensive, multi-ancestry human methylome atlas of purified human monocytes, generated through integrated whole-genome bisulfite sequencing and whole-genome sequencing from 298 European Americans (EA) and 160 African Americans (AA). By analyzing over 25 million methylation sites, we identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in cis- regions for EA and AA populations, respectively, revealing both shared (880,108 sites) and population-specific regulatory patterns. Furthermore, we developed population-specific DNAm imputation models, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. These models were validated through multi-ancestry analysis of 41 complex traits from the Million Veteran Program. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .