DNAmFitAge: biological age indicator incorporating physical fitness

Abstract

Physical fitness is a well-known correlate of health and the aging process and DNA methylation (DNAm) data can capture aging via epigenetic clocks. However, current epigenetic clocks did not yet use measures of mobility, strength, lung, or endurance fitness in their construction. We develop blood-based DNAm biomarkers for fitness parameters gait speed (walking speed), maximum handgrip strength, forced expiratory volume in one second (FEV1), and maximal oxygen uptake (VO2max) which have modest correlation with fitness parameters in five large-scale validation datasets (average r between 0.16-0.48). We then use these DNAm fitness parameter biomarkers with DNAmGrimAge, a DNAm mortality risk estimate, to construct DNAmFitAge, a new biological age indicator that incorporates physical fitness. DNAmFitAge is associated with low-intermediate physical activity levels across validation datasets (p = 6.4E-13), and younger/fitter DNAmFitAge corresponds to stronger DNAm fitness parameters in both males and females. DNAmFitAge is lower (p = 0.046) and DNAmVO2max is higher (p = 0.023) in male body builders compared to controls. Physically fit people have a younger DNAmFitAge and experience better age-related outcomes: lower mortality risk (p = 7.2E-51), coronary heart disease risk (p = 2.6E-8), and increased disease-free status (p = 1.1E-7). These new DNAm biomarkers provide researchers a new method to incorporate physical fitness into epigenetic clocks.

Keywords: DNA methylation; aging; biological age; epigenetics; physical fitness.

Figure 1

Scatterplots of DNAm fitness biomarker models versus true values in test datasets. Pink indicates females, and blue indicates males. When original variables were unavailable, best alternative variables are plotted against the DNAm fitness estimates. Each panel corresponds to the performance of one DNAm-based model built with chronological age across test datasets displayed with Pearson correlation and p-values. (A) DNAmGaitspeed with performance in InChianti dataset displayed, (B) DNAmGripmax with performance in WHI dataset, (C) DNAmFEV1, (D) DNAmVO2max. (A–C) (DNAmGaitspeed, DNAmGripmax, and DNAmFEV1) were built in each sex separately while (D) (DNAmVO2max) was built in both sexes jointly.

Figure 2

Scatterplots of DNAmFitAge versus age separated by sex. Pink indicates females, and blue indicates males. (A–F) Each panel corresponds to the performance of DNAmFitAge in one validation dataset displayed with Pearson correlation to chronological age and corresponding p-values. DNAmFitAge models applied to the same sex it was built in (i.e., DNAmFitAge built for females tested in females and DNAmFitAge built for males tested in males). DNAmFitAge is centered on chronological age with high correlation across all test sets.

Figure 3

Meta-analysis forest plots for FitAgeAcceleration to age-related conditions adjusted for age and sex. Each panel reports a meta analysis forest plot for combining hazard ratios or regression coefficients across dataset cohorts. (A) Time-to-death with number of events, (B) time-to-coronary heart disease with number of events, (C) type 2 diabetes, (D) comorbidity count, and (E) disease free status. Meta-analysis p-values are displayed in the header of each panel, and test of heterogeneity Cochran Q test p-value (Het. P) are displayed for fixed effect models. Fixed effects models were used for (A–C) and Stouffer’s method was used for (D, E).

Figure 4

Meta-analysis forest plots for DNAmFitAge and DNAm fitness parameters relationship to physical activity or physical functioning in people with low to intermediate physical activity. Each panel reports the Stouffer’s meta-analysis p-value for combining coefficients across dataset cohorts after adjusting for chronological age. (A) DNAmFitAge, (B) DNAmGaitspeed, (C) DNAmGripmax, (D) DNAmFEV1, and (E) DNAmVO2max. DNAmFitAge, DNAmGaitSpeed, DNAmGripmax, and DNAmFEV1 are predictive of physical activity in low to intermediate physically active individuals.

Figure 5

Boxplots showing spread of DNAm biomarkers between male controls (n = 149) and male body builders (n = 66) in the Polish study. (A) DNAmFitAge is younger on average in the male body builders, (B) DNAmVO2max is fitter on average in the male body builders, (C) FitAge Acceleration and (D) DNAmGaitspeed are suggestively improved in body builders but not significantly different at 0.05.