Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease

被引:0
作者
Jiantao Ma
Roby Joehanes
Chunyu Liu
Amena Keshawarz
Shih-Jen Hwang
Helena Bui
Brandon Tejada
Meera Sooda
Peter J. Munson
Cumhur Y. Demirkale
Paul Courchesne
Nancy L. Heard-Costa
Achilleas N. Pitsillides
Mike Feolo
Nataliya Sharopova
Ramachandran S. Vasan
Tianxiao Huan
Daniel Levy
机构
[1] Tufts University,Division of Nutrition Epidemiology and Data Science, Friedman School of Nutrition Science and Policy
[2] National Institutes of Health,Population Sciences Branch, National Heart, Lung, and Blood Institute
[3] Framingham Heart Study,Department of Biostatistics, School of Public Health
[4] Boston University,National Heart, Lung, and Blood Institute
[5] Boston University,Critical Care Medicine Department, Clinical Center
[6] Framingham Heart Study,Boston University School of Medicine
[7] National Institutes of Health,Department of Ophthalmology and Visual Sciences
[8] Boston University,undefined
[9] National Center for Biotechnology Information,undefined
[10] University of Massachusetts Medical School,undefined
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Scientific Reports | / 12卷
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摘要
DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e−7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e−14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e−99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e−13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute’s BioData Catalyst.
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