Aging CellMolecular BiologyPeer-reviewed journal article
Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle
Sarah Amandine Caroline VoisiniD, Kirsten SealeiD, Macsue JacquesiD, Shanie LandeniD, Nicholas R. HarveyiD, Larisa Margaret HauptiD, Lyn Robyn GriffithsiD, Kevin J. AshtoniD, Vernon G. CoffeyiD, Jamie‐Lee M. ThompsoniD, Thomas M. DoeringiD, Maléne E. LindholmiD, Colum P. WalshiD, Gareth W. DavisoniD, Rachelle E IrwiniD, Catherine McBride, Ola HanssoniD, Olof AsplundiD, Aino HeikkineniD, Päivi Liisa PiiriläiD, Kirsi Hannele PietiläineniD, Miina OllikaineniD, Sara Blocquiaux, Martine A. ThomisiD, Dawn K. ColettaiD, , Nir EynoniD
Abstract
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 = 3,176). 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 towards 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 towards a younger state after exercise training interventions, while the transcriptome shifted towards 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.
- organism: human
- assay: DNA methylation
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 77
- FWCI
- 2.03
- Field percentile
- top 10%
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