Objective: Alterations in the serum metabolome may be detectable in at-risk individuals prior to the onset of coronary heart disease (CHD). Identifying metabolomic signatures associated with CHD may provide insight into disease etiology and prevention. Approach and Results: Metabolomic profiling (chromatography-mass spectrometry) was performed in 2,232 African Americans and 1,366 European Americans from the Atherosclerosis Risk in Communities (ARIC) study. We applied Cox regression with least absolute shrinkage and selection operator (LASSO) to select metabolites associated with incident CHD. A metabolite risk score (MRS) was constructed to evaluate whether the MRS predicted CHD risk beyond traditional risk factors (TRFs). After 30 years of follow-up, we observed 633 incident CHD cases. Thirty-two metabolites were selected by LASSO to be associated with CHD, and 19 of the 32 showed significant individual associations with CHD, including a sugar substitute, erythritol. Theophylline (HR [95% CI] = 1.16 [1.09-1.25]) and gamma linolenic acid (HR [95% CI] = 0.89 [0.81-0.97]) showed the greatest positive and negative associations with CHD, respectively. A 1 SD greater standardized MRS was associated with a 1.37 fold higher risk of CHD (HR [95% CI] = 1.37 [1.27-1.47]). Adding the MRS to the TRFs significantly improved model predictive performance (30-year risk prediction: Δ C-statistic [95% CI] = 0.016 [0.008-0.024], continuous net reclassification index [95% CI] = 0.522 [0.480-0.556], integrated discrimination index [95%CI] = 0.038 [0.019-0.065]).
Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.
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