Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease

By A. Khera, C. Emdin, Isabel Drake, P. Natarajan, Alexander G. Bick, Nancy R. Cook, Daniel Chasman, U. Baber, R. Mehran, D. Rader and 6 more. 2016

1,197 citations recorded by the source corpus.

BACKGROUND Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown. METHODS Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts — 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women’s Genome Health Study (WGHS), and 22,389 in the Malmö Diet and Cancer Study (MDCS) — and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet. RESULTS The relative risk of incident coronary events was 91% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7% for an unfavorable lifestyle to 5.1% for a favorable lifestyle in ARIC, from 4.6% to 2.0% in WGHS, and from 8.2% to 5.3% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category. CONCLUSIONS Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.)

Subfields: Genetics

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Citations in the corpus

Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting (2017, result): “Carotid artery plaque burden by polygenic risk score group in 39 BioImage.”
Western Diet Triggers NLRP3-Dependent Innate Immune Reprogramming (2018, background): “and unfavorable environmental triggers, can independently of the genetic risk strongly increase the rate of incident cardiovascular events and increase the susceptibility for other chronic inflammatory diseases (Khera et al., 2016).”
Genome-wide polygenic score to identify a monogenic risk-equivalent for coronary disease (2017, background): “For example, we recently demonstrated that high polygenic risk for coronary disease may be offset by adherence to a healthy lifestyle or cholesterol-lowering therapy with statin medications (8,20,21).”
Lipid-associated macrophages control metabolic homeostasis in a Trem2-dependent manner (2019, background): “As obesity, vascular plaque formation and neurodegeneration share numerous common elements in their pathophysiology (Cai, 2013; Khera et al., 2016; Lee, 2011; Lovren et al., 2015; Spielman et al., 2014), a deeper understanding of the biology of Trem2expressing macrophages may yield fundamental insig”
Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults Implications for Primary Prevention (2019, background): “First, because previously published GRS have utilized only genetic variants of genome-wide significance (4,5,8) or involved genotyping arrays that focused only on pre-selected loci (3), they have not fully utilized genome-wide variation, preventing accurate estimation of the relative contribution of”
Integrative omics for health and disease (2018, methodology): “In the genomics space, with an individual’s genotype and a data-base of results from GWAS, one can compute a polygenic risk score to assess an individual’s risk of disease 4,77 (for recent reviews on methodology, see REFS 22,78 ).”