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An epigenetic clock for human skeletal muscle.

ABSTRACT: BACKGROUND:Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue. METHODS:To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle. RESULTS:The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ? = 0.62 between actual and predicted age across datasets (vs. ? = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies. CONCLUSIONS:We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes.

SUBMITTER: Voisin S

PROVIDER: S-EPMC7432573 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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An epigenetic clock for human skeletal muscle.

Voisin Sarah S Harvey Nicholas R NR Haupt Larisa M LM Griffiths Lyn R LR Ashton Kevin J KJ Coffey Vernon G VG Doering Thomas M TM Thompson Jamie-Lee M JM Benedict Christian C Cedernaes Jonathan J Lindholm Malene E ME Craig Jeffrey M JM Rowlands David S DS Sharples Adam P AP Horvath Steve S Eynon Nir N

Journal of cachexia, sarcopenia and muscle 20200217 4

<h4>Background</h4>Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue.<h4>Methods</h4>To address this, we developed a more accurate, muscle-specific epigenetic clock ...[more]

PMID: 32067420

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Project description:Transcriptome wide changes in human skeletal muscle after acute (anabolic) and chronic resistance exercise (RE) induced hypertrophy have been extensively determined in the literature. We have also recently undertaken DNA methylome analysis (850,000?+?CpG sites) in human skeletal muscle after acute and chronic RE, detraining and retraining, where we identified an association between DNA methylation and epigenetic memory of exercise induced skeletal muscle hypertrophy. However, it is currently unknown as to whether all the genes identified in the transcriptome studies to date are also epigenetically regulated at the DNA level after acute, chronic or repeated RE exposure. We therefore aimed to undertake large scale bioinformatical analysis by pooling the publicly available transcriptome data after acute (110 samples) and chronic RE (181 samples) and comparing these large data sets with our genome-wide DNA methylation analysis in human skeletal muscle after acute and chronic RE, detraining and retraining. Indeed, after acute RE we identified 866 up- and 936 down-regulated genes at the expression level, with 270 (out of the 866 up-regulated) identified as being hypomethylated, and 216 (out of 936 downregulated) as hypermethylated. After chronic RE we identified 2,018 up- and 430 down-regulated genes with 592 (out of 2,018 upregulated) identified as being hypomethylated and 98 (out of 430 genes downregulated) as hypermethylated. After KEGG pathway analysis, genes associated with 'cancer' pathways were significantly enriched in both bioinformatic analysis of the pooled transcriptome and methylome datasets after both acute and chronic RE. This resulted in 23 (out of 69) and 28 (out of 49) upregulated and hypomethylated and 12 (out of 37) and 2 (out of 4) downregulated and hypermethylated 'cancer' genes following acute and chronic RE respectively. Within skeletal muscle tissue, these 'cancer' genes predominant functions were associated with matrix/actin structure and remodelling, mechano-transduction (e.g. PTK2/Focal Adhesion Kinase and Phospholipase D- following chronic RE), TGF-beta signalling and protein synthesis (e.g. GSK3B after acute RE). Interestingly, 51 genes were also identified to be up/downregulated in both the acute and chronic RE pooled transcriptome analysis as well as significantly hypo/hypermethylated after acute RE, chronic RE, detraining and retraining. Five genes; FLNB, MYH9, SRGAP1, SRGN, ZMIZ1 demonstrated increased gene expression in the acute and chronic RE transcriptome and also demonstrated hypomethylation in these conditions. Importantly, these 5 genes demonstrated retained hypomethylation even during detraining (following training induced hypertrophy) when exercise was ceased and lean mass returned to baseline (pre-training) levels, identifying them as genes associated with epigenetic memory in skeletal muscle. Importantly, for the first time across the transcriptome and epigenome combined, this study identifies novel differentially methylated genes associated with human skeletal muscle anabolism, hypertrophy and epigenetic memory.

Dataset Information

An epigenetic clock for human skeletal muscle.

Publications

An epigenetic clock for human skeletal muscle.

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