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

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...

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Bibliographic Details
Published in:	Proceedings of the National Academy of Sciences - PNAS 2019-05, Vol.116 (22), p.10883-10888
Main Authors:	Taylor, D. Leland, Jackson, Anne U., Narisu, Narisu, Hemani, Gibran, Erdos, Michael R., Chines, Peter S., Swift, Amy, Idol, Jackie, Didion, John P., Welch, Ryan P., Kinnunen, Leena, Saramies, Jouko, Lakka, Timo A., Laakso, Markku, Tuomilehto, Jaakko, Parker, Stephen C. J., Koistinen, Heikki A., Smith, George Davey, Boehnke, Michael, Scott, Laura J., Birney, Ewan, Collins, Francis S.
Format:	Article
Language:	eng
Subjects:	Biological Sciences Blood Glucose - analysis Body mass Body mass index Body size Body Weights and Measures Deoxyribonucleic acid Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 DNA DNA methylation DNA Methylation - genetics Fasting Gene expression Gene Expression - genetics Gene mapping Genes Genetic diversity Genetic variance Genome-Wide Association Study - methods Genomics - methods Glucose Heterogeneity Hip Humans Insulin Insulin - analysis Muscle, Skeletal - chemistry Muscle, Skeletal - physiology Muscles Musculoskeletal system Physiology Quantitative trait loci Quantitative Trait Loci - genetics Regulators Retinoid X receptor α Skeletal muscle Tissues
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Summary:	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.
ISSN:	0027-8424 1091-6490