A Genome-Wide mQTL Analysis in Human Adipose Tissue Identifies Genetic Variants Associated with DNA Methylation, Gene Expression and Metabolic Traits

Abstract

Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.

Epigenetic markers to further understand insulin resistance

“…Regardless of which is the case, there may be a use for the identified epigenetic markers in diagnostics, but if it is found that the alterations are secondary to insulin resistance, their use in prevention or treatment is less pronounced. Importantly, the degree of methylation in adipose tissue also seems to mediate the impact of common genetic variants (single nucleotide polymorphisms [SNPs]) on metabolic traits, including insulin sensitivity measured by HOMA-IR [12]. Hence, further studies examining how interactions between genetics and epigenetics affect insulin sensitivity may identify additional important loci for disease development.…”

Nutriepigenomics Advances into Personalized Nutrition

“…The prenatal exposure to the Dutch famine has been repeatedly shown to be related to the impaired metabolic phenotypes such as elevated levels of plasma lipids and body mass index (BMI), as well as enhanced risks of obesity and cardiovascular disease (CVD) later in life. Severe malnourishment during late gestation was also related to impaired glucose tolerance of the offspring into adult life [6,[11][12][13][14].…”

“…Subsequently, this observation has been extended by examination of a set of 15 additional candidate loci responsible for development of metabolic and cardiovascular phenotypes. Levels of methylation of six of these loci (GNASAS, IL10, LEP, ABCA1, INSIGF and MEG3) have been found to be associated with prenatal exposure to famine [6,11,13,14].…”

“…These eight PPL-associatedmethylation sites, also correlated with fasting TG, account for a substantially greater amount of phenotypic variance (14.9%) in PPL and fasting TG (16.3%) when compared with the genetic contribution of loci identified by a previous GWAS (4.5%). In summary, the epigenomeis a large contributor to the variation in PPL, and this has the potential to be used to modulate PPL and reduce CVD [3,6,[13][14][15].…”

Epigenetic effects of environmental chemicals: Insights from zebrafish

“…There are widespread associations between single nucleotide polymorphisms (SNPs), the most common source of genetic variation, and DNA methylation in humans [62], but the consequences are poorly understood. It is recently demonstrated that SNPs at CpG sites can impact transcription factor binding [63].…”