Staimez, L. R. | Search bioRxiv

bioRxiv2025

Early-life nutrition supplementation and epigenetic age in middle-adulthood among Guatemalan adults

ObjectivesEpigenetic clocks are biomarkers of aging. Epigenetic clocks are associated with early-life famine exposure. We investigated the impact of a cluster-randomized early-life nutrition intervention on epigenetic age. MethodsWe analyzed follow-up data from participants in the INCAP Nutrition Supplementation Trial, conducted in 4 villages in eastern Guatemala. DNA methylation was measured in buffy coat samples using the Illumina InfiniumTM MethylationEPICv2.0 array and standard quality control procedures. Epigenetic age was quantified using DunedinPACE, PhenoAge, and GrimAge. PhenoAge and GrimAge acceleration were calculated as residuals by regressing epigenetic age on chronological age. We used intent-to-treat difference-in-difference modeling to assess the impact of a protein-energy supplement provided during the first 1,000 days of life (conception to age 2y) on epigenetic age in middle adulthood. Covariates included sex, birth year, the trial supplement type (atole [intervention] vs. fresco [control]), exposure period of supplement (any of the first 1,000 days, other), and a random effect to account for sibships. The primary coefficient of interest was represented by the interaction between supplement type and exposure period. ResultsThe analysis included 1095 participants (mean age 45.0 y (SD 4.3); 60.3 % female, 40.3 % exposed to any atole during the first 1,000 days, mean DunedinPACE 1.2 (SD 0.1), Phenoage 46.7 y (SD 6.7), and GrimAge 56.3 y (SD 4.1). In difference-in-difference analyses, exposure to atole during any of the first 1,000-day period was associated with lower DunedinPACE (- 0.03, 95% CI -0.06, -0.004), PhenoAge acceleration (- 1.91 y, 95% CI -3.43, -0.39), and GrimAge acceleration (-0.85 y, 95% CI -1.53, -0.11) compared to other exposures. Following additional adjustment for cell type proportions, the direction of the coefficients remained the same but were no longer statistically significant. ConclusionsExposure to atole during the first 1,000 days was associated with modest reductions in epigenetic age as measured by DunedinPACE, PhenoAge, and GrimAge. These findings complement prior evidence of epigenetic age acceleration among individuals with early-life famine exposure.

genomics↗

bioRxiv2022

Epigenome-wide meta-analysis of BMI in nine population-based cohorts: examining the utility of methylation as a biomarker of BMI

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential utility of these cytosine-phosphate-guanine (CpG) sites in predicting metabolic health. We pooled summary statistics from six trans-ethnic EWAS of BMI representing nine cohorts (n=17058), replicated these findings in the Womens Health Initiative (WHI, n=4822) and developed an epigenetic prediction score of BMI. In the pooled EWAS, 1265 CpG sites were associated with BMI (p<1E-7), and 1238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European descent and individuals of African descent. We found five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log normalized BMI in the WHI (80% training/20% testing). This model found 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides, and lower HDL-cholesterol and LDL-cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL-cholesterol and lower glucose and triglycerides. This study identified 553 previously identified and 685 novel CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.

genetics↗