Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.

Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late-life exercise mitigates epigenetic aging in rodent muscle. Whether exercise training can decelerate, or reverse epigenetic aging in humans is unknown. Here, we performed a powerful meta-analysis of the methylome and transcriptome of an unprecedented number of human skeletal muscle samples (n = 3176). We show that: (1) individuals with higher baseline aerobic fitness have younger epigenetic and transcriptomic profiles, (2) exercise training leads to significant shifts of epigenetic and transcriptomic patterns toward a younger profile, and (3) muscle disuse "ages" the transcriptome. Higher fitness levels were associated with attenuated differential methylation and transcription during aging. Furthermore, both epigenetic and transcriptomic profiles shifted toward a younger state after exercise training interventions, while the transcriptome shifted toward an older state after forced muscle disuse. We demonstrate that exercise training targets many of the age-related transcripts and DNA methylation loci to maintain younger methylome and transcriptome profiles, specifically in genes related to muscle structure, metabolism, and mitochondrial function. Our comprehensive analysis will inform future studies aiming to identify the best combination of therapeutics and exercise regimes to optimize longevity.

Meta-analysis of genome-wide DNA methylation and integrative omics of age in human skeletal muscle.

BACKGROUND: Knowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by ageing in humans. METHODS: We conducted a large-scale epigenome-wide association study meta-analysis of age in human skeletal muscle from 10 studies (total n = 908 muscle methylomes from men and women aged 18-89 years old). We explored the genomic context of age-related DNA methylation changes in chromatin states, CpG islands, and transcription factor binding sites and performed gene set enrichment analysis. We then integrated the DNA methylation data with known transcriptomic and proteomic age-related changes in skeletal muscle. Finally, we updated our recently developed muscle epigenetic clock (https://bioconductor.org/packages/release/bioc/html/MEAT.html). RESULTS: We identified 6710 differentially methylated regions at a stringent false discovery rate <0.005, spanning 6367 unique genes, many of which related to skeletal muscle structure and development. We found a strong increase in DNA methylation at Polycomb target genes and bivalent chromatin domains and a concomitant decrease in DNA methylation at enhancers. Most differentially methylated genes were not altered at the mRNA or protein level, but they were nonetheless strongly enriched for genes showing age-related differential mRNA and protein expression. After adding a substantial number of samples from five datasets (+371), the updated version of the muscle clock (MEAT 2.0, total n = 1053 samples) performed similarly to the original version of the muscle clock (median of 4.4 vs. 4.6 years in age prediction error), suggesting that the original version of the muscle clock was very accurate. CONCLUSIONS: We provide here the most comprehensive picture of DNA methylation ageing in human skeletal muscle and reveal widespread alterations of genes involved in skeletal muscle structure, development, and differentiation. We have made our results available as an open-access, user-friendly, web-based tool called MetaMeth (https://sarah-voisin.shinyapps.io/MetaMeth/).

The effect of resistance training, detraining and retraining on muscle strength and power, myofibre size, satellite cells and myonuclei in older men.

INTRODUCTION: Ageing is associated with an attenuated hypertrophic response to resistance training and periods of training interruptions. Hence, elderly would benefit from the 'muscle memory' effects of resistance training on muscle strength and mass during detraining and retraining. As the underlying mechanisms are not yet clear, this study investigated the role of myonuclei during training, detraining and retraining by using PCM1 labelling in muscle cross-sections of six older men. METHODS: Knee extension strength and power were measured in 30 older men and 10 controls before and after 12 weeks resistance training and after detraining and retraining of similar length. In a subset, muscle biopsies from the vastus lateralis were taken for analysis of fibre size, fibre type distribution, Pax7+ satellite cell number and myonuclear domain size. RESULTS: Resistance training increased knee extension strength and power parameters (+10 to +36%, p < .001) and decreased the frequency of type IIax fibres by half (from 20 to 10%, p = .034). Detraining resulted in a modest loss of strength and power (-5 to -15%, p ≤ .004) and a trend towards a fibre-type specific decrease in type II fibre cross-sectional area (-17%, p = .087), type II satellite cell number (-30%, p = .054) and type II myonuclear number (-12%, p = .084). Less than eight weeks of retraining were needed to reach the post-training level of one-repetition maximum strength. Twelve weeks of retraining were associated with type II fibre hypertrophy (+29%, p = .050), which also promoted an increase in the number of satellite cells (+72%, p = .036) and myonuclei (+13%, p = .048) in type II fibres. Changes in the type II fibre cross-sectional area were positively correlated with changes in the myonuclear number (Pearson's r between 0.40 and 0.73), resulting in a stable myonuclear domain. CONCLUSION: Gained strength and power and fibre type changes were partially preserved following 12 weeks of detraining, allowing for a fast recovery of the 1RM performance following retraining. Myonuclear number tended to follow individual changes in type II fibre size, which is in support of the myonuclear domain theory.

Intensity-Specific Differential Leukocyte DNA Methylation in Physical (In)Activity: An Exploratory Approach.

The aim of this exploratory study was to investigate how sedentary behavior (SB) and physical activity (PA) influence DNA methylation at a global, gene-specific, and health-related pathway level. SB, light PA (LPA), and moderate-to-vigorous PA (MVPA) were assessed objectively for 41 Flemish men using the SenseWear Pro 3 Armband. CpG site-specific methylation in leukocytes was determined using the Illumina HumanMethylation 450 BeadChip. Correlations were calculated between time spent on the three PA intensity levels and global DNA methylation, using a z-score-based method to determine global DNA methylation levels. To determine whether CpG site-specific methylation can be predicted by these three PA intensity levels, linear regression analyses were performed. Based on the significantly associated CpG sites at α = 0.005, lists were created including all genes with a promoter region overlapping these CpG sites. A biological pathway analysis determined to what extent these genes are overrepresented within several pathways. No significant associations were observed between global DNA methylation and SB (r = 0.084), LPA (r = -0.168), or MVPA (r = -0.125), although the direction of the correlation coefficients is opposite to what is generally reported in literature. SB has a different impact on global and gene-specific methylation than PA, but also LPA and MVPA affect separate genes and pathways. Furthermore, the function of a pathway seems to determine its association with SB, LPA, or MVPA. Multiple PA intensity levels, including SB, should be taken into account in future studies investigating the effect of physical (in)activity on human health through epigenetic mechanisms.