Insulin promoter DNA methylation correlates negatively with insulin gene expression and positively with HbA1c levels in human pancreatic islets

Aims/hypothesis: Although recent studies propose that epigenetic factors influence insulin expression, the regulation of the insulin gene in type 2 diabetic islets is still not fully understood. Here, we examined DNA methylation of the insulin gene promoter in pancreatic islets from patients with type 2 diabetes and non-diabetic human donors and related it to insulin expression, HbA levels, BMI and age. Methods: DNA methylation was analysed in 25 CpG sites of the insulin promoter and insulin mRNA expression was analysed using quantitative RT-PCR in pancreatic islets from nine donors with type 2 diabetes and 48 non-diabetic donors. Results: Insulin mRNA expression (p = 0.002), insulin content (p = 0.004) and glucose-stimulated insulin secretion (p = 0.04) were reduced in pancreatic islets from patients with type 2 diabetes compared with non-diabetic donors. Moreover, four CpG sites located 234 bp, 180 and 102 bp upstream and 63 bp downstream of the transcription start site (CpG -234, -180, -102 and +63, respectively), showed increased DNA methylation in type 2 diabetic compared with non-diabetic islets (7.8%, p = 0.03; 7.1%, p = 0.02; 4.4%, p = 0.03 and 9.3%, p = 0.03, respectively). While insulin mRNA expression correlated negatively (p < 1 × 10), the level of HbA correlated positively (p ≤ 0.01) with the degree of DNA methylation for CpG -234, -180 and +63. Furthermore, DNA methylation for nine additional CpG sites correlated negatively with insulin mRNA expression (p ≤ 0.01). Also, exposure to hyperglycaemia for 72 h increased insulin promoter DNA methylation in clonal rat beta cells (p = 0.005). Conclusions/interpretations: This study demonstrates that DNA methylation of the insulin promoter is increased in patients with type 2 diabetes and correlates negatively with insulin gene expression in human pancreatic islets

Common Inherited Variation in Mitochondrial Genes Is Not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits

Mitochondrial dysfunction has been observed in skeletal muscle of people with diabetes and insulin-resistant individuals. Furthermore, inherited mutations in mitochondrial DNA can cause a rare form of diabetes. However, it is unclear whether mitochondrial dysfunction is a primary cause of the common form of diabetes. To date, common genetic variants robustly associated with type 2 diabetes (T2D) are not known to affect mitochondrial function. One possibility is that multiple mitochondrial genes contain modest genetic effects that collectively influence T2D risk. To test this hypothesis we developed a method named Meta-Analysis Gene-set Enrichment of variaNT Associations (MAGENTA; http://www.broadinstitute.org/mpg/magenta). MAGENTA, in analogy to Gene Set Enrichment Analysis, tests whether sets of functionally related genes are enriched for associations with a polygenic disease or trait. MAGENTA was specifically designed to exploit the statistical power of large genome-wide association (GWA) study meta-analyses whose individual genotypes are not available. This is achieved by combining variant association p-values into gene scores and then correcting for confounders, such as gene size, variant number, and linkage disequilibrium properties. Using simulations, we determined the range of parameters for which MAGENTA can detect associations likely missed by single-marker analysis. We verified MAGENTA's performance on empirical data by identifying known relevant pathways in lipid and lipoprotein GWA meta-analyses. We then tested our mitochondrial hypothesis by applying MAGENTA to three gene sets: nuclear regulators of mitochondrial genes, oxidative phosphorylation genes, and ∼1,000 nuclear-encoded mitochondrial genes. The analysis was performed using the most recent T2D GWA meta-analysis of 47,117 people and meta-analyses of seven diabetes-related glycemic traits (up to 46,186 non-diabetic individuals). This well-powered analysis found no significant enrichment of associations to T2D or any of the glycemic traits in any of the gene sets tested. These results suggest that common variants affecting nuclear-encoded mitochondrial genes have at most a small genetic contribution to T2D susceptibility

Actos Now for the prevention of diabetes (ACT NOW) study

Abstract Background Impaired glucose tolerance (IGT) is a prediabetic state. If IGT can be prevented from progressing to overt diabetes, hyperglycemia-related complications can be avoided. The purpose of the present study was to examine whether pioglitazone (ACTOS®) can prevent progression of IGT to type 2 diabetes mellitus (T2DM) in a prospective randomized, double blind, placebo controlled trial. Methods/Design 602 IGT subjects were identified with OGTT (2-hour plasma glucose = 140–199 mg/dl). In addition, IGT subjects were required to have FPG = 95–125 mg/dl and at least one other high risk characteristic. Prior to randomization all subjects had measurement of ankle-arm blood pressure, systolic/diastolic blood pressure, HbA1C, lipid profile and a subset had frequently sampled intravenous glucose tolerance test (FSIVGTT), DEXA, and ultrasound determination of carotid intima-media thickness (IMT). Following this, subjects were randomized to receive pioglitazone (45 mg/day) or placebo, and returned every 2–3 months for FPG determination and annually for OGTT. Repeat carotid IMT measurement was performed at 18 months and study end. Recruitment took place over 24 months, and subjects were followed for an additional 24 months. At study end (48 months) or at time of diagnosis of diabetes the OGTT, FSIVGTT, DEXA, carotid IMT, and all other measurements were repeated. Primary endpoint is conversion of IGT to T2DM based upon FPG ≥ 126 or 2-hour PG ≥ 200 mg/dl. Secondary endpoints include whether pioglitazone can: (i) improve glycemic control (ii) enhance insulin sensitivity, (iii) augment beta cell function, (iv) improve risk factors for cardiovascular disease, (v) cause regression/slow progression of carotid IMT, (vi) revert newly diagnosed diabetes to normal glucose tolerance. Conclusion ACT NOW is designed to determine if pioglitazone can prevent/delay progression to diabetes in high risk IGT subjects, and to define the mechanisms (improved insulin sensitivity and/or enhanced beta cell function) via which pioglitazone exerts its beneficial effect on glucose metabolism to prevent/delay onset of T2DM. Trial Registration clinical trials.gov identifier: NCT0022096

A reference panel of 64,976 haplotypes for genotype imputation.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution

Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Correction to: Nature Communications https://doi.org/10.1038/s41467-020-19366-9, published online 5 January 2021. The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article