Associations of five obesity metrics with epigenetic age acceleration: Evidence from 2,474 Taiwan Biobank participants

Eight Weeks of Physical Training Decreases 2 Years of DNA Methylation Age of Sedentary Women

Purpose: The acceleration of epigenetic age is a predictor of mortality and contributes to the increase in chronic diseases. Adherence to a healthy lifestyle is a strategy to reduce epigenetic age. The present study aimed to determine whether eight weeks of combined (aerobic and strength) training (CT) can influence the epigenetic age of women between 50 and 70 years old and the differences in sites and methylated regions. Methods: Eighteen women (AARLow: lower age acceleration residual, n = 10; AARHigh: higher age acceleration residual, n = 8) participated in a combined exercise training program (60 minutes, 3× a week) for eight weeks. DNA was extracted from whole blood using the salting out technique. DNA methylation was performed using the array technique (Illumina's Infinium Methylation BeadChip 850k). We used the DNA Methylation Age Calculator platform to calculate the biological epigenetic age. Two-way ANOVA followed by FISHER LSD posthoc was Applied, adopting p < .05. Results: After eight weeks of CT, there were no changes to the epigenetic age acceleration for the AARLow group (PRE: -2.3 ± 3.2 to POST: -2.3 ± 3.6). However, the AARHigh group significantly decreased the age acceleration (PRE: 3.6 ± 2.6 to POST: 2.2 ± 2.7) (group effect, p = .01; time effect, p = .31; group vs. time effect, p = .005). Conclusion: CT for eight weeks benefits the epigenetic clock of women with the most accelerated age.

Life course effects of genetic susceptibility to higher body size on body fat and lean mass: prospective cohort study

BACKGROUND/OBJECTIVES

Different genetic variants are associated with larger body size in childhood vs adulthood. Whether and when these variants predominantly influence adiposity are unknown. We examined how genetic variants influence total body fat and total lean mass trajectories.

METHODS

Data were from the Avon Longitudinal Study of Parents and Children birth cohort (N = 6926). Sex-specific genetic risk scores (GRS) for childhood and adulthood body size were generated, and dual-energy X-ray absorptiometry scans measured body fat and lean mass six times between the ages of 9 and 25 years. Multilevel linear spline models examined associations of GRS with fat and lean mass trajectories.

RESULTS

In males, the sex-specific childhood and adulthood GRS were associated with similar differences in fat mass from 9 to 18 years; 8.3% [95% confidence interval (CI) 5.1, 11.6] and 7.5% (95% CI 4.3, 10.8) higher fat mass at 18 years per standard deviation (SD) higher childhood and adulthood GRS, respectively. In males, the sex-combined childhood GRS had stronger effects at ages 9 to 15 than the sex-combined adulthood GRS. In females, associations for the sex-specific childhood GRS were almost 2-fold stronger than the adulthood GRS from 9 to 18 years: 10.5% (95% CI 8.5, 12.4) higher fat mass at 9 years per SD higher childhood GRS compared with 5.1% (95% CI 3.2, 6.9) per-SD higher adulthood GRS. In females, the sex-combined GRS had similar effects, with slightly larger effect estimates. Lean mass effect sizes were much smaller.

CONCLUSIONS

Genetic variants for body size are more strongly associated with adiposity than with lean mass. Sex-combined childhood variants are more strongly associated with increased adiposity until early adulthood. This may inform future studies that use genetics to investigate the causes and impact of adiposity at different life stages.

Evaluation of Epigenetic Age Acceleration Scores and Their Associations with CVD-Related Phenotypes in a Population Cohort

We evaluated associations between nine epigenetic age acceleration (EAA) scores and 18 cardiometabolic phenotypes using an Eastern European ageing population cohort richly annotated for a diverse set of phenotypes (subsample, n = 306; aged 45-69 years). This was implemented by splitting the data into groups with positive and negative EAAs. We observed strong association between all EAA scores and sex, suggesting that any analysis of EAAs should be adjusted by sex. We found that some sex-adjusted EAA scores were significantly associated with several phenotypes such as blood levels of gamma-glutamyl transferase and low-density lipoprotein, smoking status, annual alcohol consumption, multiple carotid plaques, and incident coronary heart disease status (not necessarily the same phenotypes for different EAAs). We demonstrated that even after adjusting EAAs for sex, EAA-phenotype associations remain sex-specific, which should be taken into account in any downstream analysis involving EAAs. The obtained results suggest that in some EAA-phenotype associations, negative EAA scores (i.e., epigenetic age below chronological age) indicated more harmful phenotype values, which is counterintuitive. Among all considered epigenetic clocks, GrimAge was significantly associated with more phenotypes than any other EA scores in this Russian sample.

Associations of five obesity indicators with cognitive performance in 30,697 Taiwan Biobank participants

Background

Obesity adversely influences the central nervous system and cognitive functions. However, the relationship between various obesity indicators and cognitive performance remains controversial. It is unclear which obesity indicator is more relevant to cognitive impairment.

Methods

The Taiwan Biobank (TWB) administered the Chinese version of the Mini-Mental State Examination (MMSE) to 30,697 participants (12,094 males and 18,603 females) aged 60 to 70 years. A total of 3,454 (11.25%) individuals with MMSE < = 24 were classified as having poor cognitive performance. This cross-sectional study investigates the associations of five obesity indicators with cognitive performance. Five separate logistic regression models were fitted for males and another five for females. Covariates adjusted in all models included age, smoking status, drinking status, regular exercise, chronic disease status (diabetes, cardiovascular diseases, heart diseases, stroke, or Parkinson’s disease), depression status, blood pressure level, total cholesterol, fasting glucose, and educational attainment. The five obesity indicators included body mass index (BMI), body fat percentage (BFP), waist circumference (WC), hip circumference (HC), and waist-hip ratio (WHR).

Results

Abdominal obesity defined by WHR was significantly associated with poor cognitive performance. Male WHR > = 0.90 had a higher risk of poor cognitive performance than male WHR < 0.90 (odds ratio [OR] = 1.233; p = 0.007); female WHR > = 0.85 had an increased risk of poor cognitive performance compared with female WHR < 0.85 (OR = 1.221; p = 3.9E-4). HC and general obesity (defined by BMI and BFP) were not significantly associated with cognitive performance.

Conclusion

The results consistently agreed that preventing abdominal obesity is associated with better cognitive performance in both males and females.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03457-x.

BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index

BACKGROUND

Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality.

OBJECTIVES

We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment.

METHODS AND RESULTS

Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 × 10^-12 ) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (ΔBMI >3 kg/m² ) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 × 10^-25 ) from adjusted models.

CONCLUSION

We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.

Cardiovascular health and four epigenetic clocks

BACKGROUND

Cardiovascular health (CVH) was defined by the American Heart Association as an integrative idealness of seven clinical or lifestyle factors. Based on populations of European ancestry, recent studies have shown that ideal CVH is associated with a slower aging rate. The aging rate is measured by levels of epigenetic age acceleration (EAA), usually obtained from the residuals of regressing DNA methylation (DNAm) age on chronological age. However, little has been known about the association of CVH with biological aging in Asian populations.

METHODS AND RESULTS

We here analyzed blood DNAm data and clinical/lifestyle factors of 2474 Taiwan Biobank (TWB) participants, to investigate the association of CVH with EAA. CVH was assessed by seven components: smoking status, physical activity, dietary habits, body mass index, total cholesterol, fasting glucose, and blood pressure levels. Four measures of EAA were applied, among which two were based on the first-generation DNAm clocks (HannumEAA and IEAA) and two were based on the second-generation clocks (PhenoEAA and GrimEAA). After excluding 276 individuals with cardiovascular diseases, we regressed EAA on the CVH score (ranging from 0 to 7, integrating the abovementioned seven components) while adjusting for sex, drinking status, and educational attainment. Our results showed that a decrease in one point in the CVH score was associated with a 0.350-year PhenoEAA (p = 4.5E-4) and a 0.499-year GrimEAA (p = 4.2E-15). By contrast, HannumEAA and IEAA were not significantly associated with the CVH score. We have obtained consistent results within each generation of epigenetic clocks.

CONCLUSIONS

This is one of the first studies to comprehensively investigate the associations of CVH with four epigenetic clocks. Our TWB data showed that ideal CVH is associated with lower levels of EAA calculated according to the second-generation epigenetic clocks (PhenoEAA and GrimEAA). Having an ideal CVH status can lower EAA and reduce the risk of aging-related disorders.

Genome-wide association study for four measures of epigenetic age acceleration and two epigenetic surrogate markers using DNA methylation data from Taiwan biobank

To highlight the genetic architecture for epigenetic aging, McCartney et al. recently identified 137 significant SNPs based on genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and two epigenetic surrogate markers. However, none Asian ancestry studies have been included in this or previous meta-analyses. I performed a GWAS on blood DNA methylation (DNAm) levels of 2309 Taiwan Biobank (TWB) participants. Owing to the fact that the sample size of an individual GWAS of DNAm data is still not large, I adopted the "prioritized subset analysis" (PSA) method to boost the power of a GWAS. The four epigenetic clocks and the two epigenetic surrogate markers were investigated, respectively. I replicated 21 out of the 137 aging-associated genetic loci by applying the PSA method to the TWB DNAm data. Moreover, I identified five novel loci, including rs117530284 that was associated with the "epigenetic age acceleration" (EAA) according to Lu et al.'s GrimAge (called "GrimEAA"). Considering 16 covariates (sex, BMI, smoking status, drinking status, regular exercise, educational attainment, and the first 10 ancestry principal components), each "A" allele of rs117530284 in the IBA57 gene was found to be associated with a 1.5943-year GrimEAA (95% C.I. = [1.0748, 2.1138]). IBA57 is a protein coding gene and is associated with multiple mitochondrial dysfunctions syndromes. A decline in mitochondrial activity and quality is associated with aging and many age-related diseases. This is one of the first DNAm GWAS for individuals of Asian ancestry.