DNA Methylation Signatures of Cardiovascular Health Provide Insights Into Diseases
Abstract
BACKGROUND: The association of overall cardiovascular health (CVH) with changes in DNA methylation (DNAm) has not been well characterized. METHODS: We calculated the American Heart Association’s Life’s Essential 8 score to reflect CVH in 5 cohorts with diverse backgrounds (mean age 54 years, 55% women, and enrollment year ranging from 1989 to 2012). Epigenome-wide association studies (EWAS) for Life’s Essential 8 score were conducted, followed by bioinformatic analyses. DNAm loci significantly associated with Life’s Essential 8 score were used to calculate a CVH DNAm score. We examined the association of the CVH DNAm score with incident cardiovascular disease (CVD), cardiovascular disease–specific mortality, and all-cause mortality. RESULTS: We identified 609 cytosine-phosphate-guanines (CpGs) associated with Life’s Essential 8 score at false discovery rate<0.05 in the discovery analysis and at Bonferroni-corrected P <0.05 in the multicohort replication stage. Most had low to moderate heterogeneity (414 CpGs [68.0%] with heterogeneity <0.2) in replication analysis. Pathway enrichment analyses and a phenome-wide association study search associated these CpGs with inflammatory or autoimmune phenotypes. We observed enrichment for phenotypes in the Epigenome-Wide Association Study Catalog, with 29-fold enrichment for stroke ( P =2.4e−15) and 21-fold for ischemic heart disease ( P =7.4e−38). Two-sample Mendelian randomization (MR) analysis showed significant association between 141 CpGs and ten phenotypes (261 CpG-phenotype pairs) at false discovery rate<0.05. For example, hypomethylation at cg20544516 ( MIR33B [microRNA 33b] and SREBF1 [sterol regulatory element–binding transcription factor 1]) is associated with a lower risk of stroke ( P =8.1e−6). In multivariable prospective analyses, the CVH DNAm score was consistently associated with clinical outcomes across participating cohorts. Per SD increase in the CVH DNAm score, the decrease in risk of incident cardiovascular disease, cardiovascular disease mortality, and all-cause mortality ranged from 19% to 32%, 28% to 40%, and 27% to 45%, respectively. CONCLUSIONS: We identified new DNAm signatures for CVH across diverse cohorts. Our analyses indicate that multiple biological pathways may be relevant to the observed association between CVH and clinical outcomes.
Article Details
Authors (48)
Madeleine Carbonneau
Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD (M.C., T.H., R.J., D.L.).
Yi Li
Yishu Qu
Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL (Y.Q., Y.Z., J.W., H.N., L.H., D.L.-J.).
Yinan Zheng
Alexis C. Wood
Mengyao Wang
Key Laboratory of Applied Surface and Colloid Chemistry (MOE), School of Chemistry and Chemical Engineering
Chunyu Liu
Department of Psychiatry, State University of New York Upstate Medical University
Tianxiao Huan
Roby Joehanes
Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
Xiuqing Guo
Jie Yao
Kent D. Taylor
The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Russell P. Tracy
Laboratory for Clinical Biochemistry Research, Larner College of Medicine, University of Vermont, Burlington, VT, USA.
Peter Durda
Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA.
Yongmei Liu
Division of Cardiology, Department of Medicine, School of Medicine, Duke University, Durham, NC, USA.
W. Craig Johnson
Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA.
Wendy S. Post
Tom Blackwell
Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI (T.B.).
Jerome I. Rotter
Stephen S. Rich
Department of Genome Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA.
Susan Redline
Myriam Fornage
Jun Wang
Hongyan Ning
NORTHWESTERN UNIVERSITY, Chicago, Illinois, United States
Lifang Hou
Donald Lloyd-Jones
Framingham Center for Population and Prevention Science, Framingham, MA
Kendra Ferrier
Yuan-I. Min
Department of Medicine, University of Mississippi Medical Center, Jackson, MS (Y.-I.M., A.P.C.).
April P. Carson
Laura M. Raffield
Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Alexander Teumer
Hans J. Grabe
Henry Völzke
Matthias Nauck
Marcus Dörr
Arce Domingo-Relloso
Amanda Fretts
University of Washington School of Public Health, Seattle, Washington, United States
Maria Tellez-Plaza
Department of Chronic Disease Epidemiology, National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain (M.T.-P.).
Shelley A. Cole
Population Health Program, Texas Biomedical Research Institute, San Antonio, TX (S.A.C.).
Ana Navas-Acien
Columbia University, New York, New York, United States
Meng Wang
Joanne M. Murabito
Nancy L. Heard-Costa
Brenton Prescott
Boston University, Boston, Massachusetts, United States
Vanessa Xanthakis
Dariush Mozaffarian
Food Is Medicine Institute, Friedman School of Nutrition Science and Policy, Tufts University, Boston
Daniel Levy
Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
Jiantao Ma