Alcohol Consumption and Methylation-Based Measures of Biological Age.

Epigenetic age acceleration is considered a measure of biological aging based on genome-wide patterns of DNA methylation. Although age acceleration has been associated with the incidence of diseases and death, less is known about how it is related to lifestyle behaviors. Among 2316 women, we evaluate associations between self-reported alcohol consumption and various metrics of epigenetic age acceleration. Recent average alcohol consumption was defined as the mean number of drinks consumed per week within the past year; lifetime average consumption was estimated as the mean number of drinks per year drinking. Whole-blood genome-wide DNA methylation was measured with HumanMethylation450 BeadChips and used to assess 4 epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) and their corresponding metrics of epigenetic age acceleration (Hannum AgeAccel, Horvath AgeAccel, PhenoAgeAccel, and GrimAgeAccel). Although alcohol consumption showed little association with most age acceleration metrics, both lifetime and recent average consumption measures were positively associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: ß = 0.30 years, 95% confidence interval [CI]: 0.11, 0.48, p = .002; recent, per additional 5 drinks/week: ß = 0.19 years, 95% CI: 0.01, 0.37, p = .04). In a mutually adjusted model, only average lifetime alcohol consumption remained associated with GrimAgeAccel (lifetime, per additional 135 drinks/year: ß = 0.27 years, 95% CI: 0.04, 0.50, p = .02; recent, per 5 additional drinks/week: ß = 0.05 years, 95% CI: -0.16, 0.26, p = .64). Although alcohol use does not appear to be strongly associated with biological age measured by most epigenetic clocks, lifetime average consumption is associated with higher biological age assessed by the GrimAge epigenetic clock.

Associations of Body Composition and Physical Activity Level With Multiple Measures of Epigenetic Age Acceleration.

Epigenetic clocks use DNA methylation to estimate biological age. Whether body composition and physical activity are associated with these clocks is not well understood. Using blood samples collected at enrollment (2003-2009) from 2,758 women in the US nationwide Sister Study, we calculated 6 epigenetic age acceleration metrics using 4 epigenetic clocks (Hannum, Horvath, PhenoAge, GrimAge). Recreational physical activity was self-reported, and adiposity measures were assessed by trained medical examiners (body mass index (BMI), waist-to-hip ratio (WtH), waist circumference). In cross-sectional analyses, all adiposity measures were associated with epigenetic age acceleration. The strongest association was for BMI and PhenoAge, a measure of biological age that correlates with chronic disease (BMI of ≥35.0 vs. 18.5-24.9, ß = 3.15 years, 95% confidence interval (CI): 2.41, 3.90; P for trend < 0.001). In a mutual-adjustment model, both were associated with PhenoAge age acceleration (BMI of ≥35.0 vs. 18.5-24.9, ß = 2.69 years, 95% CI: 1.90, 3.48; P for trend < 0.001; quartile 4 vs.1 WtH, ß = 1.00 years, 95% CI: 0.34, 1.65; P for trend < 0.008). After adjustment, physical activity was associated only with GrimAge (quartile 4 vs. 1, ß = -0.42 years, 95% CI: -0.70, -0.14; P for trend = 0.001). Physical activity attenuated the waist circumference associations with PhenoAge and GrimAge. Excess adiposity was associated with epigenetic age acceleration; physical activity might attenuate associations with waist circumference.