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Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle.

ABSTRACT: We integrate comeasured gene expression and DNA methylation (DNAme) in 265 human skeletal muscle biopsies from the FUSION study with >7 million genetic variants and eight physiological traits: height, waist, weight, waist-hip ratio, body mass index, fasting serum insulin, fasting plasma glucose, and type 2 diabetes. We find hundreds of genes and DNAme sites associated with fasting insulin, waist, and body mass index, as well as thousands of DNAme sites associated with gene expression (eQTM). We find that controlling for heterogeneity in tissue/muscle fiber type reduces the number of physiological trait associations, and that long-range eQTMs (>1 Mb) are reduced when controlling for tissue/muscle fiber type or latent factors. We map genetic regulators (quantitative trait loci; QTLs) of expression (eQTLs) and DNAme (mQTLs). Using Mendelian randomization (MR) and mediation techniques, we leverage these genetic maps to predict 213 causal relationships between expression and DNAme, approximately two-thirds of which predict methylation to causally influence expression. We use MR to integrate FUSION mQTLs, FUSION eQTLs, and GTEx eQTLs for 48 tissues with genetic associations for 534 diseases and quantitative traits. We identify hundreds of genes and thousands of DNAme sites that may drive the reported disease/quantitative trait genetic associations. We identify 300 gene expression MR associations that are present in both FUSION and GTEx skeletal muscle and that show stronger evidence of MR association in skeletal muscle than other tissues, which may partially reflect differences in power across tissues. As one example, we find that increased RXRA muscle expression may decrease lean tissue mass.

SUBMITTER: Taylor DL

PROVIDER: S-EPMC6561151 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle.

Taylor D Leland DL Jackson Anne U AU Narisu Narisu N Hemani Gibran G Erdos Michael R MR Chines Peter S PS Swift Amy A Idol Jackie J Didion John P JP Welch Ryan P RP Kinnunen Leena L Saramies Jouko J Lakka Timo A TA Laakso Markku M Tuomilehto Jaakko J Parker Stephen C J SCJ Koistinen Heikki A HA Davey Smith George G Boehnke Michael M Scott Laura J LJ Birney Ewan E Collins Francis S FS

Proceedings of the National Academy of Sciences of the United States of America 20190510 22

We integrate comeasured gene expression and DNA methylation (DNAme) in 265 human skeletal muscle biopsies from the FUSION study with >7 million genetic variants and eight physiological traits: height, waist, weight, waist-hip ratio, body mass index, fasting serum insulin, fasting plasma glucose, and type 2 diabetes. We find hundreds of genes and DNAme sites associated with fasting insulin, waist, and body mass index, as well as thousands of DNAme sites associated with gene expression (eQTM). We ...[more]

PMID: 31076557

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Project description:BackgroundKnowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by ageing in humans.MethodsWe 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).ResultsWe 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.ConclusionsWe 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/).

Project description:BackgroundSex differences are known to impact muscle phenotypes, metabolism, and disease risk. Skeletal muscle stem cells (satellite cells) are important for muscle repair and to maintain functional skeletal muscle. Here we studied, for the first time, effects of sex on DNA methylation and gene expression in primary human myoblasts (activated satellite cells) before and after differentiation into myotubes.MethodWe used an array-based approach to analyse genome-wide DNA methylation and gene expression in myoblasts and myotubes from 13 women and 13 men. The results were followed up with a reporter gene assay.ResultsGenome-wide DNA methylation and gene expression differences between the sexes were detected in both myoblasts and myotubes, on the autosomes as well as the X-chromosome, despite lack of exposure to sex hormones and other factors that differ between sexes. Pathway analysis revealed higher expression of oxidative phosphorylation and other metabolic pathways in myoblasts from women compared to men. Oxidative phosphorylation was also enriched among genes with higher expression in myotubes from women. Forty genes in myoblasts and 9 in myotubes had differences in both DNA methylation and gene expression between the sexes, including LAMP2 and SIRT1 in myoblasts and KDM6A in myotubes. Furthermore, increased DNA methylation of LAMP2 promoter had negative effects on reporter gene expression. Five genes (CREB5, RPS4X, SYAP1, XIST, and ZRSR2) showed differential DNA methylation and gene expression between the sexes in both myoblasts and myotubes. Interestingly, differences in DNA methylation and expression between women and men were also found during differentiation (myoblasts versus myotubes), e.g., in genes involved in energy metabolism. Interestingly, more DNA methylation changes occur in women compared to men on autosomes.ConclusionAll together, we show that epigenetic and transcriptional differences exist in human myoblasts and myotubes as well as during differentiation between women and men. We believe that these intrinsic differences might contribute to sex dependent differences in muscular phenotypes.

Project description:BackgroundSarcopenia is a disease diagnosed in the elderly. In patients with sarcopenia, the muscle mass decreases every year. The occurrence of sarcopenia is greatly affected by extrinsic factors such as eating habits, exercise, and lifestyle. The present study aimed to determine the relationship between muscle mass traits and genes affected by epigenetic factors with three different adjustment methods using Korean Genome and Epidemiology Study (KOGES) data.ResultsWe conducted a demographic study and DNA methylation profiling by three studies according to the muscle mass index (MMI) adjustment methods: appendicular skeletal muscle mass divided by body weight (MMI1); appendicular skeletal muscle mass divided by square of height (MMI2); appendicular skeletal muscle mass divided by BMI (MMI3). We analyzed differentially methylated regions (DMRs) for each group. We then restricted our subjects to be top 30% (T30) and bottom 30% (B30) based on each MMI adjustment method. Additionally, we performed enrichment analysis using PathfindR to evaluate the relationship between identified DMRs and sarcopenia. A total of 895 subjects were included in the demographic study. The values of BMI, waist, and hip showed a significant difference in all three groups. Among 446 participants, 44 subjects whose DNA methylation profiles were investigated were included for DNA methylation analysis. The results of enrichment analysis showed differences between groups. In the women group through MMI1 method, only the glutamatergic synapse pathway showed a significant result. In the men group through MMI2 method, the adherens junction pathway was the most significant. Women group through MMI2 method showed similar results, having an enriched Rap1 signaling pathway. In men group through MMI3 method, the Fc epsilon RI signaling pathway was the most enriched. Particularly, the notch signaling pathway was significantly enriched in women group through MMI3 method.ConclusionThis study presents results about which factor should be concerned first in muscle mass index (MMI) adjustment. The present study suggested that GAB2 and JPH3 in MMI1 method, HLA-DQB1 and TBCD in MMI2 method, GAB2, NDUFB4 and ISPD in MMI3 method are potential genes that can have an impact on muscle mass. It could enable future epigenetic studies of genes based on annotation results. The present study is a nationwide study in Korea with the largest size up to date that compares adjustment indices for MMI in epigenetic research.

Dataset Information

Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle.

Publications

Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle.

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