Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

被引:0
作者
Amena Keshawarz
Helena Bui
Roby Joehanes
Jiantao Ma
Chunyu Liu
Tianxiao Huan
Shih-Jen Hwang
Brandon Tejada
Meera Sooda
Paul Courchesne
Peter J. Munson
Cumhur Y. Demirkale
Chen Yao
Nancy L. Heard-Costa
Achilleas N. Pitsillides
Honghuang Lin
Ching-Ti Liu
Yuxuan Wang
Gina M. Peloso
Jessica Lundin
Jeffrey Haessler
Zhaohui Du
Michael Cho
Craig P. Hersh
Peter Castaldi
Laura M. Raffield
Jia Wen
Yun Li
Alexander P. Reiner
Mike Feolo
Nataliya Sharopova
Ramachandran S. Vasan
Dawn L. DeMeo
April P. Carson
Charles Kooperberg
Daniel Levy
机构
[1] Framingham Heart Study,Population Sciences Branch, Division of Intramural Research
[2] National Heart,Friedman School of Nutrition Science and Policy
[3] Lung,Department of Biostatistics
[4] and Blood Institute,Department of Ophthalmology and Visual Sciences
[5] National Institutes of Health,Mathematical and Statistical Computing Laboratory, Office of Intramural Research, Center for Information Technology
[6] Tufts University,Department of Neurology
[7] Boston University School of Public Health,Division of Clinical Informatics, Department of Medicine
[8] University of Massachusetts Chan Medical School,Channing Division of Network Medicine, Brigham and Women’s Hospital
[9] National Institutes of Health,Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital
[10] Boston University School of Medicine,General Medicine and Primary Care, Brigham and Women’s Hospital
[11] University of Massachusetts Chan Medical School,Department of Genetics
[12] Fred Hutchinson Cancer Center,Department of Biostatistics
[13] Harvard Medical School,Department of Epidemiology
[14] Harvard Medical School,National Center for Biotechnology Information
[15] Harvard Medical School,Department of Medicine, Preventive Medicine and Epidemiology
[16] University of North Carolina at Chapel Hill,Department of Medicine
[17] University of North Carolina at Chapel Hill,undefined
[18] University of Washington,undefined
[19] National Institutes of Health,undefined
[20] Boston University School of Medicine,undefined
[21] University of Mississippi Medical Center,undefined
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摘要
Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E−7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E−14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women’s Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.
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