Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease

Tianxiao Huan (), Roby Joehanes, Ci Song, Fen Peng, Yichen Guo, Michael Mendelson, Chen Yao, Chunyu Liu, Jiantao Ma, Melissa Richard, Golareh Agha, Weihua Guan, Lynn M. Almli, Karen N. Conneely, Joshua Keefe, Shih-Jen Hwang, Andrew D. Johnson, Myriam Fornage, Liming Liang () and Daniel Levy ()
Additional contact information
Tianxiao Huan: The Framingham Heart Study
Roby Joehanes: The Framingham Heart Study
Ci Song: The Framingham Heart Study
Fen Peng: University of Texas Health Science Center at Houston
Yichen Guo: Harvard University
Michael Mendelson: The Framingham Heart Study
Chen Yao: The Framingham Heart Study
Chunyu Liu: Boston University School of Public Health
Jiantao Ma: The Framingham Heart Study
Melissa Richard: University of Texas Health Science Center at Houston
Golareh Agha: Columbia University
Weihua Guan: University of Minnesota
Lynn M. Almli: Emory University School of Medicine
Karen N. Conneely: Emory University School of Medicine
Joshua Keefe: The Framingham Heart Study
Shih-Jen Hwang: The Framingham Heart Study
Andrew D. Johnson: The Framingham Heart Study
Myriam Fornage: University of Texas Health Science Center at Houston
Liming Liang: Harvard University
Daniel Levy: The Framingham Heart Study

Nature Communications, 2019, vol. 10, issue 1, 1-14

Abstract: Abstract Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.

Date: 2019
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DOI: 10.1038/s41467-019-12228-z

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