DNA methylation–based epigenetic age measures have been used as biological aging markers and are associated with a healthy lifespan. Few population-based studies have examined the relation between diet and epigenetic age acceleration. We aimed to investigate the relation between diet quality and epigenetic age acceleration. We analyzed data from 1995 participants (mean age, 67 years; 55% women) of the Framingham Heart Study Offspring Cohort. Cross-sectional associations between the Dietary Approaches to Stop Hypertension (DASH) score and 3 whole-blood DNA methylation–derived epigenetic age acceleration measures—Dunedin Pace of Aging Methylation (DunedinPoAm), GrimAge acceleration (GrimAA), and PhenoAge acceleration (PhenoAA)—were examined. A mediation analysis was conducted to assess the mediating role of epigenetic age acceleration in relation to DASH and all-cause mortality. A higher DASH score was associated with lower levels of DunedinPoAm (β = −0.05; SE = 0.02; P = 0.007), GrimAA (β = −0.09; SE = 0.02; P < 0.001), and PhenoAA (β = −0.07; SE = 0.02; P = 0.001). All 3 epigenetic measures mediated the association between the DASH score and all-cause mortality, with mean proportions of 22.1% for DunedinPoAm (P_mediation = 0.04), 45.1% for GrimAA (P_mediation = 0.001), and 22.9% for PhenoAA (P_mediation = 0.03). An interaction was observed between the DASH score and smoking status in relation to the epigenetic aging markers. The association between the DASH score and epigenetic aging markers tended to be stronger in “ever-smokers” (former and current smokers) compared to “never-smokers.” The proportions of mediation were 31.3% for DunedinPoAm, 46.8% for GrimAA, and 10.3% for PhenoAA in ever-smokers, whereas no significant mediation was observed in never-smokers. Higher diet quality is associated with slower epigenetic age acceleration, which partially explains the beneficial effect of diet quality on the lifespan. Our findings emphasize that adopting a healthy diet is crucial for maintaining healthy aging.

Background: DNA methylation patterns associated with habitual diet have not been well studied. Methods: Diet quality was characterized using a Mediterranean-style diet score and the Alternative Healthy Eating Index score. We conducted ethnicity-specific and trans-ethnic epigenome-wide association analyses for diet quality and leukocyte-derived DNA methylation at over 400 000 CpGs (cytosine-guanine dinucleotides) in 5 population-based cohorts including 6662 European ancestry, 2702 African ancestry, and 360 Hispanic ancestry participants. For diet-associated CpGs identified in epigenome-wide analyses, we conducted Mendelian randomization (MR) analysis to examine their relations to cardiovascular disease risk factors and examined their longitudinal associations with all-cause mortality. Results: We identified 30 CpGs associated with either Mediterranean-style diet score or Alternative Healthy Eating Index, or both, in European ancestry participants. Among these CpGs, 12 CpGs were significantly associated with all-cause mortality (Bonferroni corrected P <1.6×10 ⁻³ ). Hypermethylation of cg18181703 ( SOCS3 ) was associated with higher scores of both Mediterranean-style diet score and Alternative Healthy Eating Index and lower risk for all-cause mortality ( P =5.7×10 ⁻¹⁵ ). Ten additional diet-associated CpGs were nominally associated with all-cause mortality ( P <0.05). MR analysis revealed 8 putatively causal associations for 6 CpGs with 4 cardiovascular disease risk factors (body mass index, triglycerides, high-density lipoprotein cholesterol concentrations, and type 2 diabetes mellitus; Bonferroni corrected MR P <4.5×10 ⁻⁴ ). For example, hypermethylation of cg11250194 ( FADS2 ) was associated with lower triglyceride concentrations (MR, P =1.5×10 ⁻¹⁴ ).and hypermethylation of cg02079413 ( SNORA54 ; NAP1L4 ) was associated with body mass index (corrected MR, P =1×10 ⁻⁶ ). Conclusions: Habitual diet quality was associated with differential peripheral leukocyte DNA methylation levels of 30 CpGs, most of which were also associated with multiple health outcomes, in European ancestry individuals. These findings demonstrate that integrative genomic analysis of dietary information may reveal molecular targets for disease prevention and treatment.

Data on proteomic and metabolomic signatures of healthy dietary patterns are limited. We evaluated the cross-sectional association of serum proteomic and metabolomic markers with three dietary patterns: the Alternative Healthy Eating Index (AHEI), the Dietary Approaches to Stop Hypertension (DASH) diet; and a Mediterranean-style (MDS) diet. We examined participants from the Framingham Offspring Study (mean age; 55 years; 52% women) who had complete proteomic (n = 1713) and metabolomic (n = 2284) data; using food frequency questionnaires to derive dietary pattern indices. Proteins and metabolites were quantified using the SomaScan platform and liquid chromatography/tandem mass spectrometry; respectively. We used multivariable-adjusted linear regression models to relate each dietary pattern index (independent variables) to each proteomic and metabolomic marker (dependent variables). Of the 1373 proteins; 103 were associated with at least one dietary pattern (48 with AHEI; 83 with DASH; and 8 with MDS; all false discovery rate [FDR] ≤ 0.05). We identified unique associations between dietary patterns and proteins (17 with AHEI; 52 with DASH; and 3 with MDS; all FDR ≤ 0.05). Significant proteins enriched biological pathways involved in cellular metabolism/proliferation and immune response/inflammation. Of the 216 metabolites; 65 were associated with at least one dietary pattern (38 with AHEI; 43 with DASH; and 50 with MDS; all FDR ≤ 0.05). All three dietary patterns were associated with a common signature of 24 metabolites (63% lipids). Proteins and metabolites associated with dietary patterns may help characterize intermediate phenotypes that provide insights into the molecular mechanisms mediating diet-related disease. Our findings warrant replication in independent populations

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for type 2 diabetes (T2D). We aimed to identify the peripheral blood DNA methylation signature of hepatic fat. We conducted epigenome-wide association studies of hepatic fat in 3,400 European ancestry (EA) participants and in 401 Hispanic ancestry and 724 African ancestry participants from four population-based cohort studies. Hepatic fat was measured using computed tomography or ultrasound imaging and DNA methylation was assessed at >400,000 cytosine-guanine dinucleotides (CpGs) in whole blood or CD14+ monocytes using a commercial array. We identified 22 CpGs associated with hepatic fat in EA participants at a false discovery rate <0.05 (corresponding P = 6.9 × 10−6) with replication at Bonferroni-corrected P < 8.6 × 10−4. Mendelian randomization analyses supported the association of hypomethylation of cg08309687 (LINC00649) with NAFLD (P = 2.5 × 10−4). Hypomethylation of the same CpG was also associated with risk for new-onset T2D (P = 0.005). Our study demonstrates that a peripheral blood–derived DNA methylation signature is robustly associated with hepatic fat accumulation. The hepatic fat–associated CpGs may represent attractive biomarkers for T2D. Future studies are warranted to explore mechanisms and to examine DNA methylation signatures of NAFLD across racial/ethnic groups.

Background: Life's Essential 8 (LE8) is an enhanced metric for cardiovascular health. The interrelations among LE8, biomarkers of aging, and disease risks are unclear. Methods and Results: LE8 score was calculated for 5682 Framingham Heart Study participants. We implemented 4 DNA methylation‐based epigenetic age biomarkers, with older epigenetic age hypothesized to represent faster biological aging, and examined whether these biomarkers mediated the associations between the LE8 score and cardiovascular disease (CVD), CVD‐specific mortality, and all‐cause mortality. We found that a 1 SD increase in the LE8 score was associated with a 35% (95% CI, 27–41; P =1.8E‐15) lower risk of incident CVD, a 36% (95% CI, 24–47; P =7E‐7) lower risk of CVD‐specific mortality, and a 29% (95% CI, 22–35; P =7E‐15) lower risk of all‐cause mortality. These associations were partly mediated by epigenetic age biomarkers, particularly the GrimAge and the DunedinPACE scores. The potential mediation effects by epigenetic age biomarkers tended to be more profound in participants with higher genetic risk for older epigenetic age, compared with those with lower genetic risk. For example, in participants with higher GrimAge polygenic scores (greater than median), the mean proportion of mediation was 39%, 39%, and 78% for the association of the LE8 score with incident CVD, CVD‐specific mortality, and all‐cause mortality, respectively. No significant mediation was observed in participants with lower GrimAge polygenic score. Conclusions: DNA methylation‐based epigenetic age scores mediate the associations between the LE8 score and incident CVD, CVD‐specific mortality, and all‐cause mortality, particularly in individuals with higher genetic predisposition for older epigenetic age.