TY - JOUR
T1 - Meta-analysis of genome-wide DNA methylation and integrative omics of age in human skeletal muscle
AU - Voisin, Sarah
AU - Jacques, Macsue
AU - Landen, Shanie
AU - Harvey, Nicholas R.
AU - Haupt, Larisa M.
AU - Griffiths, Lyn R.
AU - Gancheva, Sofiya
AU - Ouni, Meriem
AU - Jähnert, Markus
AU - Ashton, Kevin J.
AU - Coffey, Vernon G.
AU - Thompson, Jamie Lee M.
AU - Doering, Thomas M.
AU - Gabory, Anne
AU - Junien, Claudine
AU - Caiazzo, Robert
AU - Verkindt, Hélène
AU - Raverdy, Violetta
AU - Pattou, François
AU - Froguel, Philippe
AU - Craig, Jeffrey M.
AU - Blocquiaux, Sara
AU - Thomis, Martine
AU - Sharples, Adam P.
AU - Schürmann, Annette
AU - Roden, Michael
AU - Horvath, Steve
AU - Eynon, Nir
N1 - Funding Information:
We are grateful for the support of the Australian National Health and Medical Research Council (NHMRC) via S.V.'s Early Career Research Fellowship (APP11577321) and N.E.'s Career Development Fellowship (APP1140644). We are also grateful for the support of the Jack Brockoff Foundation via S.V.'s medical grant. We also thank the Australian Research Council (ARC) for supporting this study (DP190103081 and DP200101830). The Gene SMART and LITER studies were both supported by the Collaborative Research Network for Advancing Exercise and Sports Science (201202) from the Department of Education and Training, Australia. N.R.H. and Ms J.‐L.M.T. were supported by a PhD stipend also provided by Bond University CRN‐AESS. This research was also supported by infrastructure purchased with Australian Government EIF Super Science Funds as part of the Therapeutic Innovation Australia—Queensland Node project (L.R.G.). A.P.S. was supported by GlaxoSmithKline, North Staffordshire Medical Institute, the Society fort Endocrinology, the Medical Research Council (MRC) and Engineering and Physical Sciences Research Council (EPSRC), UK Doctoral Training Centre, and the Norwegian School of Sport Sciences (Norges Idrettshøgskole). The work was also supported by the German Federal Ministry of Education and Research [Bundesministerium für Bildung und Forschung (BMBF): DZD Grant 82DZD00302] and the Brandenburg State (Germany). The EPIK study was supported by the Foundation Scientific Research—Flanders (FWO Grant F.0898.15).
Publisher Copyright:
© 2021 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders.
PY - 2021/8
Y1 - 2021/8
N2 - 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/).
AB - 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/).
UR - http://www.scopus.com/inward/record.url?scp=85108893357&partnerID=8YFLogxK
U2 - 10.1002/jcsm.12741
DO - 10.1002/jcsm.12741
M3 - Article
C2 - 34196129
AN - SCOPUS:85108893357
SN - 2190-5991
VL - 12
SP - 1064
EP - 1078
JO - Journal of Cachexia, Sarcopenia and Muscle
JF - Journal of Cachexia, Sarcopenia and Muscle
IS - 4
ER -