[ Nutrition ]

Genome-Wide Associations between Genetic and Epigenetic Variation Influence mRNA Expression and Insulin Secretion in Human

Originally predicated on the recognition of an increasing prevalence of allergy, the hygiene hypothesis was later found to accommodate the contrasting epidemiologic trends in developed countries for infectious vs autoimmune diseases. It is a complex metabolic disease that is caused by insulin resistance and beta cell dysfunction. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. Dnmt1 binding at the D-loop and Cytb regions of mtDNA was analyzed by chromatin immunoprecipitation. In this study, we report that in lean offspring of non-HFD-fed dams, essential promoter regions for Pomc expression were enriched with 5-hydroxymethylcytosine (5hmC) together with a reduction in the level of 5-methylcytosine (5mC). In cohort 2 (replication) at one of these CpGs, DNAm was still significantly associated. Furthermore, DNA methylation levels of one CpG site located 376 bp upstream of the transcription start site of GLP1R correlated negatively with GLP1R expression (rho=-0.34, p=0.008) but positively with BMI and HbA1c (rho=0.30, p=0.02 and rho=0.30, p=0.03, respectively).

The literature review process to identify relevant evidence to support CPGs is disclosed to the CDA CPG methodology working group to ensure the literature search is reasonably comprehensive, systematic, and free of bias. Whereas methylation mutation patients showed a near-total absence of DNA methylation at the TNDM locus, the patients with no identified molecular anomaly showed no marked methylation variation from controls. Causal inference test (CIT) identified SNP-CpG pairs where DNA methylation in human islets is the potential mediator of the genetic association with gene expression or insulin secretion. Functional analyses further demonstrated that identified candidate genes (GPX7, GSTT1 and SNX19) directly affect key biological processes such as proliferation and apoptosis in pancreatic β-cells. Antigen-presenting cells were studied in nose-draining lymph nodes (mandibular lymph nodes; MLN) after nasal treatment, and T-cell responses were analysed in joint-draining lymph nodes after arthritis induction. Our study demonstrates for the first time how genome-wide genetic and epigenetic variation interacts to influence gene expression, islet function and potential diabetes risk in humans. Inter-individual variation in genetics and epigenetics affects biological processes and disease susceptibility.

Epigenetics often refers to changes in gene expression that take place without a change in the DNA sequence. To identify novel loci affecting islet function and potentially diabetes, we performed the first genome-wide methylation quantitative trait locus (mQTL) analysis in human pancreatic islets including DNA methylation of 468,787 CpG sites located throughout the genome. The CPG for Singapore is a comprehensive report involving various aspects of diabetes care including management of diabetes, its complications and associated metabolic disorders. Furthermore, significant mQTLs cover previously reported diabetes loci including KCNJ11, INS, HLA, PDX1 and GRB10. We also found mQTLs associated with gene expression and insulin secretion in human islets. By performing causality inference tests (CIT), we identified CpGs where DNA methylation potentially mediates the genetic impact on gene expression and insulin secretion. Our functional follow-up experiments further demonstrated that identified mQTLs/genes (GPX7, GSTT1 and SNX19) directly affect pancreatic β-cell function.

Together, our study provides a detailed map of genome-wide associations between genetic and epigenetic variation, which affect gene expression and insulin secretion in human pancreatic islets. Most cells in the human body share the same genetic sequence while the epigenetic pattern varies between different cell types and over time. DNA methylation is one of the most studied epigenetic modifications and it is involved in multiple biological processes such as transcriptional control during embryonic development, X-chromosome inactivation, genomic imprinting and regulation of cell specific gene expression [1]. Female mice of the NOD/LtJ strain were raised and maintained under pathogen-free conditions in the Animal Breeding Center of this institute from breeders supplied by Dr. The present CPGs and CPRs for diabetes and CKD are consistent with those already established for the treatment of diabetes and CVD by the ADA and AHA.34,38 Goals of the management approaches recommended here are intended to mitigate the devastating consequences of the spectrum of vascular complications, including kidney, heart, and others. Inheritance of epigenetic traits between generations has been shown in animals [4], [5]. Previous studies in twins further suggest that genetic factors may affect DNA methylation profiles [6], [7].

Moreover, genetic variation has been shown to influence the inter-individual variation in DNA methylation in the human brain, fibroblast and adipose tissue [8]–[14]. While some of these studies used the Infinium HumanMethylation27 BeadChip which covers ∼14,500 genes [8]–[10], others used the HumanMethylation450 BeadChip and limited the analysis to cis regulatory effects [12]–[14]. 29Endocrinology Associates, Houston, Texas. Pancreatic islets contribute to the regulation of whole body glucose homeostasis by secreting insulin in response to increased plasma glucose concentrations. Deficient insulin secretion, resulting in chronically elevated blood glucose levels, is a characteristic of diabetes mellitus. Recent genome-wide association studies (GWAS) have identified numerous genetic loci associated with diabetes and its related traits [15]–[30]. However, these variants only explain a small proportion of the estimated heritability for diabetes [31], proposing that there are additional genetic factors left to be discovered.

These may include genetic variants interacting with epigenetic mechanisms. To study the interaction between genetics and epigenetics and to identify novel loci affecting islet function and potentially diabetes, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. The specific goals for this study were to: 1) identify single nucleotide polymorphisms (SNPs) associated with altered DNA methylation (mQTLs) in human pancreatic islets; 2) test if identified SNPs in significant mQTLs affect islet gene expression and diabetes related phenotypes; 3) examine the causal relationship between genotype, DNA methylation and gene expression or insulin secretion in human pancreatic islets; 4) test if identified candidate genes, based on our mQTL results, have a functional role in pancreatic β-cells; 5) examine if mQTLs in human pancreatic islets also associate with diabetes and its related traits in GWAS. To reach these goals, we related genome-wide genotype data of SNPs with genome-wide DNA methylation data of ∼470,000 CpG sites covering 21,231 (99%) RefSeq genes and most genomic regions in pancreatic islets of 89 human donors. Here, both cis and trans regulatory effects of SNPs on DNA methylation were analyzed. SNPs found to be associated with DNA methylation levels in the mQTL analysis were then followed-up with an expression quantitative trait locus (eQTL) analysis in the human islets, and related to islet insulin secretion data. In addition, we used a causal inference test (CIT) [32] to model the causal relationships between genotype, DNA methylation and phenotypic outcome.

A number of candidate genes, where both DNA methylation and gene expression were associated with genetic variation, were then selected for functional follow-up analysis in clonal β-cells. Finally, identified mQTLs were examined for overlap with reported diabetes loci in publicly available GWAS data. The study design is described in . Using this approach, we identified significant mQTLs in cis and in trans. Numerous mQTLs were associated with altered mRNA expression and insulin secretion in human islets. Notably, identified mQTLs covered known diabetes loci. Together, our study highlights the importance of integrating genetic and epigenetic data in order to identify new loci affecting biological processes and disease risk.

Tags: , ,