Abstract
BackgroundCardiovascular disease (CVD) is the leading cause of mortality among US adults. African Americans have higher burden of CVD morbidity and mortality compared to any other racial group. Identifying biomarkers for clinical risk prediction of CVD offers an opportunity for precision prevention and earlier intervention.ResultsUsing linear mixed models, we investigated the cross-sectional association between four measures of epigenetic age acceleration (intrinsic (IEAA), extrinsic (EEAA), PhenoAge (PhenoAA), and GrimAge (GrimAA)) and ten cardiometabolic markers of hypertension, insulin resistance, and dyslipidemia in 1,100 primarily hypertensive African Americans from sibships in the Genetic Epidemiology Network of Arteriopathy (GENOA). We then assessed the association between epigenetic age acceleration and time to self-reported incident CVD using frailty hazard models and investigated CVD risk prediction improvement compared to models with clinical risk scores (Framingham risk score (FRS) and the atherosclerotic cardiovascular disease (ASCVD) risk equation). After adjusting for sex and chronological age, increased epigenetic age acceleration was associated with higher systolic blood pressure (IEAA), higher pulse pressure (EEAA and GrimAA), higher fasting glucose (PhenoAA and GrimAA), higher fasting insulin (EEAA), lower low density cholesterol (GrimAA), and higher triglycerides (GrimAA). A five-year increase in GrimAA was associated with CVD incidence with a hazard ratio of 1.54 (95% CI 1.22–2.01) and remained significant after adjusting for CVD risk factors. The addition of GrimAA to risk score models improved model fit using likelihood ratio tests (P = 0.013 for FRS and P = 0.008 for ASCVD), but did not improve C statistics (P > 0.05). Net reclassification index (NRI) showed small but significant improvement in reassignment of risk categories with the addition of GrimAA to FRS (NRI: 0.055, 95% CI 0.040–0.071) and the ASCVD equation (NRI: 0.029, 95% CI 0.006–0.064).ConclusionsEpigenetic age acceleration measures are associated with traditional CVD risk factors in an African-American cohort with a high prevalence of hypertension. GrimAA was associated with CVD incidence and slightly improved prediction of CVD events over clinical risk scores.
Highlights
Cardiovascular disease (CVD) is the leading cause of mortality among United States (US) adults
HorvathAge was trained using multi-tissue samples from children and adults, while HannumAge was trained using a single tissue from adults. Modified versions of these two measures were later derived to account for confounding by blood cell composition: intrinsic epigenetic age acceleration (IEAA) based on HorvathAge explicitly adjusts for blood cell composition, and extrinsic epigenetic age acceleration (EEAA) based on the HannumAge is a composite measure that includes a weighted average of cell counts known to vary strongly with age [8]
We investigated the relationship between four epigenetic age acceleration measures and ten cardiometabolic markers of hypertension, insulin resistance, and dyslipidemia in 1,100 primarily hypertensive African Americans in the Genetic Epidemiology Network of Arteriopathy (GENOA) study
Summary
Cardiovascular disease (CVD) is the leading cause of mortality among US adults. African Americans have higher burden of CVD morbidity and mortality compared to any other racial group. African Americans have the highest CVD morbidity and mortality burden, a trend which has been consistent over the last few decades [2] Underlying this higher CVD prevalence is a greater burden of a number of risk factors, including hypertension, type 2 diabetes, and obesity [3,4,5]. The first generation of epigenetic aging measures, the HorvathAge [6] and HannumAge [7] epigenetic clocks, were trained on chronological age and are estimated based on 363 and 71 CpG sites selected using elastic net regression modeling, respectively. PhenoAge, a more recent measure based on whole blood from adults, was estimated using 513 CpG sites and was trained on a composite clinical measure of phenotypic age that is based on chronological age and nine biomarkers including albumin, creatinine, serum glucose, and white blood cell counts [9]. These four epigenetic age acceleration measures are hypothesized to be capturing different aspects of aging and are based mostly on unique CpG sites [11]
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