Genetic versus Non-Genetic Regulation of miR-103, miR-143 and miR-483-3p Expression in Adipose Tissue and Their Metabolic Implications-A Twin Study.

Murine models suggest that the microRNAs miR-103 and miR-143 may play central roles in the regulation of subcutaneous adipose tissue (SAT) and development of type 2 diabetes (T2D). The microRNA miR-483-3p may reduce adipose tissue expandability and cause ectopic lipid accumulation, insulin resistance and T2D. We aimed to explore the genetic and non-genetic factors that regulate these microRNAs in human SAT, and to investigate their impact on metabolism in humans. Levels of miR-103, miR-143 and miR-483-3p were measured in SAT biopsies from 244 elderly monozygotic and dizygotic twins using real-time PCR. Heritability estimates were calculated and multiple regression analyses were performed to study associations between these microRNAs and measures of metabolism, as well as between these microRNAs and possible regulating factors. We found that increased BMI was associated with increased miR-103 expression levels. In addition, the miR-103 levels were positively associated with 2 h plasma glucose levels and hemoglobin A1c independently of BMI. Heritability estimates for all three microRNAs were low. In conclusion, the expression levels of miR-103, miR-143 and miR-483-3p in adipose tissue are primarily influenced by non-genetic factors, and miR-103 may be involved in the development of adiposity and control of glucose metabolism in humans

Genome-Wide Analysis of DNA Methylation Differences in Muscle and Fat from Monozygotic Twins Discordant for Type 2 Diabetes

Background: Monozygotic twins discordant for type 2 diabetes constitute an ideal model to study environmental contributions to type 2 diabetic traits. We aimed to examine whether global DNA methylation differences exist in major glucose metabolic tissues from these twins. Methodology/Principal Findings: Skeletal muscle (n = 11 pairs) and subcutaneous adipose tissue (n = 5 pairs) biopsies were collected from 53-80 year-old monozygotic twin pairs discordant for type 2 diabetes. DNA methylation was measured by microarrays at 26,850 cytosine-guanine dinucleotide (CpG) sites in the promoters of 14,279 genes. Bisulfite sequencing was applied to validate array data and to quantify methylation of intergenic repetitive DNA sequences. The overall intra-pair variation in DNA methylation was large in repetitive (LINE1, D4Z4 and NBL2) regions compared to gene promoters (standard deviation of intra-pair differences: 10% points vs. 4% points, P<0.001). Increased variation of LINE1 sequence methylation was associated with more phenotypic dissimilarity measured as body mass index (r = 0.77, P = 0.007) and 2-hour plasma glucose (r = 0.66, P = 0.03) whereas the variation in promoter methylation did not associate with phenotypic differences. Validated methylation changes were identified in the promoters of known type 2 diabetes-related genes, including PPARGC1A in muscle (13.9+/-6.2% vs. 9.0+/-4.5%, P = 0.03) and HNF4A in adipose tissue (75.2+/-3.8% vs. 70.5+/-3.7%, P<0.001) which had increased methylation in type 2 diabetic individuals. A hypothesis-free genome-wide exploration of differential methylation without correction for multiple testing identified 789 and 1,458 CpG sites in skeletal muscle and adipose tissue, respectively. These methylation changes only reached some percentage points, and few sites passed correction for multiple testing. Conclusions/Significance: Our study suggests that likely acquired DNA methylation changes in skeletal muscle or adipose tissue gene promoters are quantitatively small between type 2 diabetic and non-diabetic twins. The importance of methylation changes in candidate genes such as PPARGC1A and HNF4A should be examined further by replication in larger samples

Glucose tolerance is associated with differential expression of microRNAs in skeletal muscle: results from studies of twins with and without type 2 diabetes.

AIMS/HYPOTHESIS: We aimed to identify microRNAs (miRNAs) associated with type 2 diabetes and risk of developing the disease in skeletal muscle biopsies from phenotypically well-characterised twins. METHODS: We measured muscle miRNA levels in monozygotic (MZ) twins discordant for type 2 diabetes using arrays. Further investigations of selected miRNAs included target prediction, pathway analysis, silencing in cells and association analyses in a separate cohort of 164 non-diabetic MZ and dizygotic twins. The effects of elevated glucose and insulin levels on miRNA expression were examined, and the effect of low birthweight (LBW) was studied in rats. RESULTS: We identified 20 miRNAs that were downregulated in MZ twins with diabetes compared with their non-diabetic co-twins. Differences for members of the miR-15 family (miR-15b and miR-16) were the most statistically significant, and these miRNAs were predicted to influence insulin signalling. Indeed, miR-15b and miR-16 levels were associated with levels of key insulin signalling proteins, miR-15b was associated with the insulin receptor in non-diabetic twins and knockdown of miR-15b/miR-16 in myocytes changed the levels of insulin signalling proteins. LBW in twins and undernutrition during pregnancy in rats were, in contrast to overt type 2 diabetes, associated with increased expression of miR-15b and/or miR-16. Elevated glucose and insulin suppressed miR-16 expression in vitro. CONCLUSIONS: Type 2 diabetes is associated with non-genetic downregulation of several miRNAs in skeletal muscle including miR-15b and miR-16, potentially targeting insulin signalling. The paradoxical findings in twins with overt diabetes and twins at increased risk of the disease underscore the complexity of the regulation of muscle insulin signalling in glucose homeostasis.JB-J was supported by a grant from the Danish PhD School for Molecular Metabolism. The study was supported by grants from the Danish Medical Research Council, the Danish Strategic Research Council. The Novo Nordisk Foundation, the Danish Ministry of Science, Technology and Innovation. DSF-T was supported by the Biotechnology and Biological Sciences Research Council project grant BB/F-15364/1. SEO is a British Heart Foundation Senior Fellow (FS/09/029/27902).This is the final version of the article. It was first published by Springer at http://link.springer.com/article/10.1007%2Fs00125-014-3434-

A novel rare CUBN variant and three additional genes identified in Europeans with and without diabetes : results from an exome-wide association study of albuminuria

Aims/hypothesisIdentifying rare coding variants associated with albuminuria may open new avenues for preventing chronic kidney disease and end-stage renal disease, which are highly prevalent in individuals with diabetes. Efforts to identify genetic susceptibility variants for albuminuria have so far been limited, with the majority of studies focusing on common variants.MethodsWe performed an exome-wide association study to identify coding variants in a two-stage (discovery and replication) approach. Data from 33,985 individuals of European ancestry (15,872 with and 18,113 without diabetes) and 2605 Greenlanders were included.ResultsWe identified a rare (minor allele frequency [MAF]: 0.8%) missense (A1690V) variant in CUBN (rs141640975, =0.27, p=1.3x10(-11)) associated with albuminuria as a continuous measure in the combined European meta-analysis. The presence of each rare allele of the variant was associated with a 6.4% increase in albuminuria. The rare CUBN variant had an effect that was three times stronger in individuals with type 2 diabetes compared with those without (p(interaction)=7.0x10(-4), with diabetes=0.69, without diabetes=0.20) in the discovery meta-analysis. Gene-aggregate tests based on rare and common variants identified three additional genes associated with albuminuria (HES1, CDC73 and GRM5) after multiple testing correction (p(Bonferroni)Peer reviewe

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P &lt; 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition