ArticleProceedings of the National Academy of Sciences of the United States of America2019
Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 3 of them syntheses that pooled it.
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Who cites it
104 citing papers in PubMed, 3 syntheses or guidelines pooled it, 190 citations in OpenAlex.
- Skeletal muscle eQTL meta-analysis implicates genes in the genetic architecture of muscular and cardiometabolic traits.American journal of human genetics · 2025Pooled it
- Integration of GWAS, QTLs and keratinocyte functional assays reveals molecular mechanisms of atopic dermatitis.Nature communications · 2025Pooled it
- Meta-analysis of genome-wide DNA methylation and integrative omics of age in human skeletal muscle.Journal of cachexia, sarcopenia and muscle · 2021Pooled it
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- Integrated Genomic and Transcriptomic Study RevealsCirculation. Genomic and precision medicine · 2026Article
- eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.bioRxiv : the preprint server for biology · 2026Article
- Ultra-fast genetic colocalisation across millions of association signals.PLoS genetics · 2026Article
- EPAS1 is associated with human muscle fiber composition and endurance phenotypes.Physiological reports · 2026Article
- Estimating in silico causal effects of DNA methylation on gene expression through genetic anchors in airway epithelium in asthma.Science advances · 2026Article
- Context-specific regulatory genetic variation in MTOR dampens neutrophil-T cell crosstalk in pneumonia-associated sepsis.Nature communications · 2026Article
- Genetic regulation of exosome biogenesis pathway in human adipose and muscle tissue and association with obesity and insulin resistance.International journal of obesity (2005) · 2026Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- Transcriptomic profiling of chlorogenic acid and taurine treatment in human skin cells provides insights into cellular senescence mechanisms.Frontiers in molecular biosciences · 2026Article
- A novel high-dimensional model for identifying regional DNA methylation QTLs.Biostatistics (Oxford, England) · 2025Article
- Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.Cell genomics · 2025Article
- Association analysis of indel variants and gene expression identifies MDM4 as a novel locus for skeletal muscle hypertrophy and power athlete status.Experimental physiology · 2025Article
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- Integrated fibre-specific methylome and proteome profiling of human skeletal muscle across males and females with fibre-type deconvolution.Skeletal muscle · 2025Article
44 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
22 authors at 8 institutions in 4 countries.
Funding
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
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.