Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

Michael M. Mendelson, Riccardo E. Marioni, Roby Joehanes, Chunyu Liu, Åsa K. Hedman, Stella Aslibekyan, Ellen W. Demerath, Weihua Guan, Degui Zhi, Chen Yao, Tianxiao Huan, Christine Willinger, Brian Chen, Paul Courchesne, Michael Multhaup, Marguerite R. Irvin, Ariella Cohain, Eric E. Schadt, Megan L. Grove, Jan BresslerKari North, Johan Sundström, Stefan Gustafsson, Sonia Shah, Allan F. McRae, Sarah E. Harris, Jude Gibson, Paul Redmond, Janie Corley, Lee Murphy, John M. Starr, Erica Kleinbrink, Leonard Lipovich, Peter M. Visscher, Naomi R. Wray, Ronald M. Krauss, Daniele Fallin, Andrew Feinberg, Devin M. Absher, Myriam Fornage, James S. Pankow, Lars Lind, Caroline Fox, Erik Ingelsson, Donna K. Arnett, Eric Boerwinkle, Liming Liang, Daniel Levy, Ian J. Deary

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

Background: The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain. Methods and Findings: We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination. Conclusions: We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.

Original languageEnglish (US)
Article numbere1002215
JournalPLoS Medicine
Volume14
Issue number1
DOIs
StatePublished - Jan 2017

Bibliographical note

Funding Information:
The Framingham Heart Study is funded by National Institutes of Health contract N01-HC-25195 and HHSN268201500001I. The Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) epigenetics study is funded by the NIH National Heart, Lung, and Blood Institute grant R01 HL 104135-01. The Atherosclerosis Risk in Communities (ARIC) study is carried out as a collaborative study supported by the National Heart, Lung, and Blood Institute (NHLBI) contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN2682011000010C, HHSN2682011000011C, HHSN2682011000012C). Funding support for ?Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium? was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). The laboratory work for this investigation was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, and by a Director?s Challenge Award, National Institutes of Health (DL, PI). The analytical component of this project was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, and the Center for Information Technology, National Institutes of Health, Bethesda, MD. This study utilized the computational resources of the Biowulf system at the National Institutes of Health, Bethesda, MD (http://biowulf.nih.gov). MMM is partly supported by the Tommy Kaplan Fund, Boston Children?s Hospital. LL is partially supported by NIH grant (P30 DK46200). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the UK?s Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Age UK (The Disconnected Mind project). Methylation typing was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. REM, SEH, PMV, JMS, and IJD are members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE). CCACE is supported by funding from the BBSRC, the Economic and Social Research Council (ESRC), the Medical Research Council (MRC), and the University of Edinburgh as part of the cross-council Lifelong Health and Wellbeing initiative (MR/K026992/1). Research reported in this publication was supported by National Health and Medical Research Council (NHMRC) project grants 613608, APP496667, APP1010374 and APP1046880. NHMRC Fellowships to PMV, and NRW (613602) and Australian Research Council (ARC) Future Fellowship to NRW (FT0991360). AFM is supported by the NHMRC fellowship scheme (1083656). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data on adiposity traits have been contributed by GIANT investigators and have been downloaded from https://www.broadinstitute.org/collaboration/giant/index.php/. Data on glycemic traits have been contributed by MAGIC investigators and have been downloaded from https://www.magicinvestigators.org. Data on diabetes traits have been contributed by the DIAGRAM consortium and have been downloaded from http://diagram-consortium.org/. Data on coronary artery disease/myocardial infarction have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from http://www.cardiogramplusc4d.org/. The views expressed in this paper are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the US Department of Health and Human Services. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Health and Medical Research Council or the Australian Research Council.

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