bioRxivGeneticsPreprint
Meta-analysis of genome-wide DNA methylation and integrative OMICs in human skeletal muscle.
Sarah Amandine Caroline VoisiniD, Macsue JacquesiD, Shanie LandeniD, Nicholas R. HarveyiD, Larisa Margaret HauptiD, Lyn Robyn GriffithsiD, Sofiya GanchevaiD, Meriem OuniiD, Markus JähnertiD, Kevin J. AshtoniD, VG Coffey, Jamie‐Lee M. ThompsoniD, Thomas M. DoeringiD, Anne GaboryiD, Claudine Junien, Robert J. CaiazzoiD, Hélène VerkindtiD, Violeta RaverdyiD, François N. PattouiD, Philippe FrogueliD, Jeffrey Mark CraigiD, Sara Blocquiaux, Martine A. ThomisiD, Adam Philip SharplesiD, Annette SchürmanniD, , Nir EynoniD
Abstract
Knowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by aging in humans. Using a large-scale epigenome-wide association study (EWAS) meta-analysis of age in human skeletal muscle from 10 studies (total n = 908 human muscle methylomes), we identified 9,986 differentially methylated regions at a stringent false discovery rate < 0.005, spanning 8,748 unique genes, many of which related to skeletal muscle structure and development. We then integrated the DNA methylation results with known transcriptomic and proteomic age-related changes in skeletal muscle, and found that even though most differentially methylated genes are not altered at the mRNA or protein level, they are nonetheless strongly enriched for genes showing age-related differential expression. We provide here the most comprehensive picture of DNA methylation aging in human skeletal muscle, and have made our results available as an open-access, user-friendly, web-based tool called MetaMeth (https://sarah-voisin.shinyapps.io/MetaMeth/).
- organism: human
- assay: DNA methylation
- research focus: differential expression
- approach: statistical model
- Citations
- 4
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