The relations of alcohol consumption and gene expression remain to be elucidated. We examined cross-sectional associations between alcohol consumption and whole blood derived gene expression levels and between alcohol-associated genes and obesity, hypertension, and diabetes in 5531 Framingham Heart Study (FHS) participants. We identified 25 alcohol-associated genes. We further showed cross-sectional associations of 16 alcohol-associated genes with obesity, nine genes with hypertension, and eight genes with diabetes at P < 0.002. For example, we observed decreased expression of PROK2 (β = −0.0018; 95%CI: −0.0021, −0.0007; P = 6.5e − 5) and PAX5 (β = −0.0014; 95%CI: −0.0021, −0.0007; P = 6.5e − 5) per 1 g/day increase in alcohol consumption. Consistent with our previous observation on the inverse association of alcohol consumption with obesity and positive association of alcohol consumption with hypertension, we found that PROK2 was positively associated with obesity (OR = 1.42; 95%CI: 1.17, 1.72; P = 4.5e − 4) and PAX5 was negatively associated with hypertension (OR = 0.73; 95%CI: 0.59, 0.89; P = 1.6e − 3). We also observed that alcohol consumption was positively associated with expression of ABCA13 (β = 0.0012; 95%CI: 0.0007, 0.0017; P = 1.3e − 6) and ABCA13 was positively associated with diabetes (OR = 2.57; 95%CI: 1.73, 3.84; P = 3.5e − 06); this finding, however, was inconsistent with our observation of an inverse association between alcohol consumption and diabetes. We showed strong cross-sectional associations between alcohol consumption and expression levels of 25 genes in FHS participants. Nonetheless, complex relationships exist between alcohol-associated genes and CVD risk factors.

Background: Alcohol use patterns influence health outcomes. This study examined sex-specific drinking trajectories and their associations with all-cause mortality and coronary heart disease (CHD) in the US-based Framingham Heart Study. Method: Among 6570 participants (mean age: 55 ± 13; 55% women) followed for 15 years, a growth mixture model identified four sex-specific alcohol consumption trajectories. Cox models examined associations of alcohol trajectories with CHD and mortality over 10 years of follow-up, adjusting for covariates. Results: This study identified four distinct, sex-specific alcohol consumption trajectories: the Moderate-Decreasing group (1179 women, 0–14 g/day; 1534 men, 0–28 g/day) showed a declining moderate intake, The Low-to-None group included light or non-drinkers (992 women, 826 men), the Inverse-U group (606 women, 199 men) showed variable intake over time, while the High-Decreasing group (858 women, 376 men) had high initial consumption (women > 14 and men > 28 g/day) that declined over time. Compared with the Moderate-Decreasing group, women in other groups had higher CHD risks (HRs 1.58–1.61) and greater mortality risk in the Low-to-None (HR 1.25) and Inverse-U (HR 1.28) groups. Men in Low-to-None had higher mortality (HR 1.17) and CHD (HR 1.60), while High-Decreasing showed the highest mortality (HR 1.27). Low-to-moderate drinking was associated with lower mortality and CHD risks; however, these findings do not confirm the protective effects of alcohol use. Discussion: Our findings suggest that sustained low to moderate drinking was associated with lower risks of mortality and CHD in both women and men, compared to high-level or fluctuating patterns. Although these associations may not confirm causality, our findings emphasize the importance of investigating long-term drinking patterns in public health. Nevertheless, we caution against promoting moderate alcohol use as a strategy to reduce mortality risk or prevent CHD.

Background: Alcohol use patterns influence health outcomes. This study examined sex-specific drinking trajectories and their associations with all-cause mortality and coronary heart disease (CHD) in the US-based Framingham Heart Study. Method: Among 6,570 participants (mean age: 55±13; 55% women) followed for 15 years, a growth mixture model identified four sex-specific alcohol consumption trajectories. Cox models examined associations of alcohol trajectories with CHD and mortality over 10 years of follow-up, adjusting for covariates. Results: The Moderate-Decreasing group (1,179 women, 0–14 g/day; 1,534 men, 0–28 g/day) showed a declining moderate intake. The Low-to-None group included light or non-drinkers (992 women, 826 men). The Inverse-U group (606 women, 199 men) showed variable intake, while the High-Decreasing group (858 women, 376 men) had high (women >14 and men >28 g/day) but declining consumption. Compared with Moderate-Decreasing, women in other groups had higher CHD risks (HRs 1.58-1.61) and greater mortality in Low-to-None (HR 1.25) and Inverse-U (HR 1.28) groups. Men in Low-to-None had higher mortality (HR 1.17) and CHD (HR 1.60), while High-Decreasing showed the highest mortality (HR 1.27). Low-to-moderate drinking was associated with lower mortality and CHD risks; however, these findings do not confirm the protective effects of alcohol use. Discussion: Our findings suggest that sustained low to moderate drinking was associated with lower risks of mortality and CHD in both women and men, compared to high-level or fluctuating patterns. These results emphasize the importance of understanding long-term drinking patterns in public health, but we caution against interpreting moderate use as a means to lower mortality risk or prevent CHD.

Mediation analysis quantifies how an exposure affects an outcome through an intermediate variable. We extend mediation analysis to capture the cumulative effects of longitudinal predictors on longitudinal outcomes. Our proposed model examines how mediators transmit the effects of the current and previous exposure on the current outcome. We construct a least-squared estimator for cumulative indirect effect (CIE) and used three approaches (exact form, delta method, and bootstrap procedure) to estimate its standard error (SE). The estimator of CIE is unbiased with no unmeasured confounding and independent model errors between mediator model and outcome model at all time points, as shown in statistical inference and in simulations. While three SE estimates are numerically similar, bootstrap procedure is recommended due to its simplicity in implementation. We apply this method to Framingham Heart Study offspring cohort to assess if DNA methylation mediates the association of alcohol consumption with systolic blood pressure over two time points. We identify two CpGs (cg05130679 and cg05465916) as mediators and construct a composite DNA methylation score from 11 CpGs, which mediates for 39% of the cumulative effect. In conclusion, we propose an unbiased estimator for CIE. Future studies will investigate the missingness in mediators and outcomes.