Leveraging cross-species transcription factor binding site patterns: from diabetes risk loci to disease mechanisms.

Genome-wide association studies have revealed numerous risk loci associated with diverse diseases. However, identification of disease-causing variants within association loci remains a major challenge. Divergence in gene expression due to cis-regulatory variants in noncoding regions is central to disease susceptibility. We show that integrative computational analysis of phylogenetic conservation with a complexity assessment of co-occurring transcription factor binding sites (TFBS) can identify cis-regulatory variants and elucidate their mechanistic role in disease. Analysis of established type 2 diabetes risk loci revealed a striking clustering of distinct homeobox TFBS. We identified the PRRX1 homeobox factor as a repressor of PPARG2 expression in adipose cells and demonstrate its adverse effect on lipid metabolism and systemic insulin sensitivity, dependent on the rs4684847 risk allele that triggers PRRX1 binding. Thus, cross-species conservation analysis at the level of co-occurring TFBS provides a valuable contribution to the translation of genetic association signals to disease-related molecular mechanisms.

Circulating triglycerides are associated with human adipose tissue DNA methylation of genes linked to metabolic disease.

Dysregulation of circulating lipids is a central element for the metabolic syndrome. However, it is not well established whether human subcutaneous adipose tissue is affected by or affect circulating lipids through epigenetic mechanisms. Hence, our aim was to investigate the association between circulating lipids and DNA methylation levels in human adipose tissue. DNA methylation and gene expression were analysed genome-wide in subcutaneous adipose tissue from two different cohorts, including 85 men and 93 women, respectively. Associations between DNA methylation and circulating levels of triglycerides, low-density lipoprotein, high-density lipoprotein and total cholesterol were analysed. Causal mediation analyses tested if adipose tissue DNA methylation mediates the effects of triglycerides on gene expression or insulin resistance. We found 115 novel associations between triglycerides and adipose tissue DNA methylation, e.g. in the promoter of RFS1, ARID2 and HOXA5 in the male cohort (P ≤ 1.1 × 10-7), and 63 associations, e.g. within the gene body of PTPRN2 and COL6A3 in the female cohort. We further connected these findings to altered mRNA expression levels in adipose tissue (e.g. HOXA5, IL11 and FAM45B). Interestingly, there was no overlap between methylation sites associated with triglycerides in men and the sites found in women, which points towards sex-specific effects of triglycerides on the epigenome. Finally, a causal mediation analysis provided support for adipose tissue DNA methylation as a partial mediating factor between circulating triglycerides and insulin resistance. This study identified novel epigenetic alterations in adipose tissue associated with circulating lipids. Identified epigenetic changes seem to mediate effects of triglycerides on insulin resistance.

Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood.

Increased age, BMI and HbA1c levels are risk factors for several non-communicable diseases. However, the impact of these factors on the genome-wide DNA methylation pattern in human adipose tissue remains unknown. We analyzed the DNA methylation of ∼480 000 sites in human adipose tissue from 96 males and 94 females and related methylation to age, BMI and HbA1c. We also compared epigenetic signatures in adipose tissue and blood. Age was significantly associated with both altered DNA methylation and expression of 1050 genes (e.g. FHL2, NOX4 and PLG). Interestingly, many reported epigenetic biomarkers of aging in blood, including ELOVL2, FHL2, KLF14 and GLRA1, also showed significant correlations between adipose tissue DNA methylation and age in our study. The most significant association between age and adipose tissue DNA methylation was found upstream of ELOVL2. We identified 2825 genes (e.g. FTO, ITIH5, CCL18, MTCH2, IRS1 and SPP1) where both DNA methylation and expression correlated with BMI. Methylation at previously reported HIF3A sites correlated significantly with BMI in females only. HbA1c (range 28-46 mmol/mol) correlated significantly with the methylation of 711 sites, annotated to, for example, RAB37, TICAM1 and HLA-DPB1. Pathway analyses demonstrated that methylation levels associated with age and BMI are overrepresented among genes involved in cancer, type 2 diabetes and cardiovascular disease. Our results highlight the impact of age, BMI and HbA1c on epigenetic variation of candidate genes for obesity, type 2 diabetes and cancer in human adipose tissue. Importantly, we demonstrate that epigenetic biomarkers in blood can mirror age-related epigenetic signatures in target tissues for metabolic diseases such as adipose tissue.

Genome-wide associations between genetic and epigenetic variation influence mRNA expression and insulin secretion in human pancreatic islets.

Genetic and epigenetic mechanisms may interact and together affect biological processes and disease development. However, most previous studies have investigated genetic and epigenetic mechanisms independently, and studies examining their interactions throughout the human genome are lacking. To identify genetic loci that interact with the epigenome, we performed the first genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human pancreatic islets. We related 574,553 single nucleotide polymorphisms (SNPs) with genome-wide DNA methylation data of 468,787 CpG sites targeting 99% of RefSeq genes in islets from 89 donors. We identified 67,438 SNP-CpG pairs in cis, corresponding to 36,783 SNPs (6.4% of tested SNPs) and 11,735 CpG sites (2.5% of tested CpGs), and 2,562 significant SNP-CpG pairs in trans, corresponding to 1,465 SNPs (0.3% of tested SNPs) and 383 CpG sites (0.08% of tested CpGs), showing significant associations after correction for multiple testing. These include reported diabetes loci, e.g. ADCY5, KCNJ11, HLA-DQA1, INS, PDX1 and GRB10. CpGs of significant cis-mQTLs were overrepresented in the gene body and outside of CpG islands. Follow-up analyses further identified mQTLs associated with gene expression and insulin secretion in human islets. 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 ß-cells. Finally, we found direct correlations between DNA methylation of 22,773 (4.9%) CpGs with mRNA expression of 4,876 genes, where 90% of the correlations were negative when CpGs were located in the region surrounding transcription start site. 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.

Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion.

Impaired insulin secretion is a hallmark of type 2 diabetes (T2D). Epigenetics may affect disease susceptibility. To describe the human methylome in pancreatic islets and determine the epigenetic basis of T2D, we analyzed DNA methylation of 479,927 CpG sites and the transcriptome in pancreatic islets from T2D and non-diabetic donors. We provide a detailed map of the global DNA methylation pattern in human islets, ß- and α-cells. Genomic regions close to the transcription start site showed low degrees of methylation and regions further away from the transcription start site such as the gene body, 3'UTR and intergenic regions showed a higher degree of methylation. While CpG islands were hypomethylated, the surrounding 2 kb shores showed an intermediate degree of methylation, whereas regions further away (shelves and open sea) were hypermethylated in human islets, ß- and α-cells. We identified 1,649 CpG sites and 853 genes, including TCF7L2, FTO and KCNQ1, with differential DNA methylation in T2D islets after correction for multiple testing. The majority of the differentially methylated CpG sites had an intermediate degree of methylation and were underrepresented in CpG islands (∼ 7%) and overrepresented in the open sea (∼ 60%). 102 of the differentially methylated genes, including CDKN1A, PDE7B, SEPT9 and EXOC3L2, were differentially expressed in T2D islets. Methylation of CDKN1A and PDE7B promoters in vitro suppressed their transcriptional activity. Functional analyses demonstrated that identified candidate genes affect pancreatic ß- and α-cells as Exoc3l silencing reduced exocytosis and overexpression of Cdkn1a, Pde7b and Sept9 perturbed insulin and glucagon secretion in clonal ß- and α-cells, respectively. Together, our data can serve as a reference methylome in human islets. We provide new target genes with altered DNA methylation and expression in human T2D islets that contribute to perturbed insulin and glucagon secretion. These results highlight the importance of epigenetics in the pathogenesis of T2D.

Epigenetic markers to further understand insulin resistance.

Epigenetic variation in human adipose tissue has been linked to type 2 diabetes and its related risk factors including age and obesity. Insulin resistance, a key risk factor for type 2 diabetes, may also be associated with altered DNA methylation in visceral and subcutaneous adipose tissue. Furthermore, linking epigenetic variation in target tissues to similar changes in blood cells may identify new blood-based biomarkers. In this issue of Diabetologia, Arner et al studied the transcriptome and methylome in subcutaneous and visceral adipose tissue of 80 obese women who were either insulin-sensitive or -resistant (DOI 10.1007/s00125-016-4074-5 ). While they found differences in gene expression between the two groups, no alterations in DNA methylation were found after correction for multiple testing. Nevertheless, based on nominal p values, their methylation data overlapped with methylation differences identified in adipose tissue of individuals with type 2 diabetes compared with healthy individuals. Differential methylation of these overlapping CpG sites may predispose to diabetes by occurring already in the insulin-resistant state. Furthermore, some methylation changes may contribute to an inflammatory process in adipose tissue since the identified CpG sites were annotated to genes encoding proteins involved in inflammation. Finally, the methylation pattern in circulating leucocytes did not mirror the adipose tissue methylome of these 80 women. Together, identifying novel molecular mechanisms contributing to insulin resistance and type 2 diabetes may help advance the search for new therapeutic alternatives.

Adipose tissue transcriptomics and epigenomics in low birthweight men and controls: role of high-fat overfeeding.

AIMS/HYPOTHESIS: Individuals who had a low birthweight (LBW) are at an increased risk of insulin resistance and type 2 diabetes when exposed to high-fat overfeeding (HFO). We studied genome-wide mRNA expression and DNA methylation in subcutaneous adipose tissue (SAT) after 5 days of HFO and after a control diet in 40 young men, of whom 16 had LBW. METHODS: mRNA expression was analysed using Affymetrix Human Gene 1.0 ST arrays and DNA methylation using Illumina 450K BeadChip arrays. RESULTS: We found differential DNA methylation at 53 sites in SAT from LBW vs normal birthweight (NBW) men (false discovery rate <5%), including sites in the FADS2 and CPLX1 genes previously associated with type 2 diabetes. When we used reference-free cell mixture adjustments to potentially adjust for cell composition, 4,323 sites had differential methylation in LBW vs NBW men. However, no differences in SAT gene expression levels were identified between LBW and NBW men. In the combined group of all 40 participants, 3,276 genes (16.5%) were differentially expressed in SAT after HFO (false discovery rate <5%) and there was no difference between LBW men and controls. The most strongly upregulated genes were ELOVL6, FADS2 and NNAT; in contrast, INSR, IRS2 and the SLC27A2 fatty acid transporter showed decreased expression after HFO. Interestingly, SLC27A2 expression correlated negatively with diabetes- and obesity-related traits in a replication cohort of 142 individuals. DNA methylation at 652 CpG sites (including in CDK5, IGFBP5 and SLC2A4) was altered in SAT after overfeeding in this and in another cohort. CONCLUSIONS/INTERPRETATION: Young men who had a LBW exhibit epigenetic alterations in their adipose tissue that potentially influence insulin resistance and risk of type 2 diabetes. Short-term overfeeding influences gene transcription and, to some extent, DNA methylation in adipose tissue; there was no major difference in this response between LBW and control participants.

A six months exercise intervention influences the genome-wide DNA methylation pattern in human adipose tissue.

Epigenetic mechanisms are implicated in gene regulation and the development of different diseases. The epigenome differs between cell types and has until now only been characterized for a few human tissues. Environmental factors potentially alter the epigenome. Here we describe the genome-wide pattern of DNA methylation in human adipose tissue from 23 healthy men, with a previous low level of physical activity, before and after a six months exercise intervention. We also investigate the differences in adipose tissue DNA methylation between 31 individuals with or without a family history of type 2 diabetes. DNA methylation was analyzed using Infinium HumanMethylation450 BeadChip, an array containing 485,577 probes covering 99% RefSeq genes. Global DNA methylation changed and 17,975 individual CpG sites in 7,663 unique genes showed altered levels of DNA methylation after the exercise intervention (q<0.05). Differential mRNA expression was present in 1/3 of gene regions with altered DNA methylation, including RALBP1, HDAC4 and NCOR2 (q<0.05). Using a luciferase assay, we could show that increased DNA methylation in vitro of the RALBP1 promoter suppressed the transcriptional activity (p = 0.03). Moreover, 18 obesity and 21 type 2 diabetes candidate genes had CpG sites with differences in adipose tissue DNA methylation in response to exercise (q<0.05), including TCF7L2 (6 CpG sites) and KCNQ1 (10 CpG sites). A simultaneous change in mRNA expression was seen for 6 of those genes. To understand if genes that exhibit differential DNA methylation and mRNA expression in human adipose tissue in vivo affect adipocyte metabolism, we silenced Hdac4 and Ncor2 respectively in 3T3-L1 adipocytes, which resulted in increased lipogenesis both in the basal and insulin stimulated state. In conclusion, exercise induces genome-wide changes in DNA methylation in human adipose tissue, potentially affecting adipocyte metabolism.

Genome-wide analysis of DNA methylation in subjects with type 1 diabetes identifies epigenetic modifications associated with proliferative diabetic retinopathy.

BACKGROUND: Epigenetic variation has been linked to several human diseases. Proliferative diabetic retinopathy (PDR) is a major cause of vision loss in subjects with diabetes. However, studies examining the association between PDR and the genome-wide DNA methylation pattern are lacking. Our aim was to identify epigenetic modifications that associate with and predict PDR in subjects with type 1 diabetes (T1D). METHODS: DNA methylation was analyzed genome-wide in 485,577 sites in blood from cases with PDR (n = 28), controls (n = 30), and in a prospective cohort (n = 7). False discovery rate analysis was used to correct the data for multiple testing. Study participants with T1D diagnosed before 30 years of age and insulin treatment within 1 year from diagnosis were selected based on 1) subjects classified as having PDR (cases) and 2) subjects with T1D who had had diabetes for at least 10 years when blood DNA was sampled and classified as having no/mild diabetic retinopathy also after an 8.7-year follow-up (controls). DNA methylation was also analyzed in a prospective cohort including seven subjects with T1D who had no/mild diabetic retinopathy when blood samples were taken, but who developed PDR within 6.3 years (converters). The retinopathy level was classified by fundus photography. RESULTS: We identified differential DNA methylation of 349 CpG sites representing 233 unique genes including TNF, CHI3L1 (also known as YKL-40), CHN2, GIPR, GLRA1, GPX1, AHRR, and BCOR in cases with PDR compared with controls. The majority of these sites (79 %) showed decreased DNA methylation in cases with PDR. The Natural Killer cell-mediated cytotoxicity pathway was found to be significantly (P = 0.006) enriched among differentially methylated genes in cases with PDR. We also identified differential DNA methylation of 28 CpG sites representing 17 genes (e.g. AHRR, GIPR, GLRA1, and BCOR) with P <0.05 in the prospective cohort, which is more than expected by chance (P = 0.0096). CONCLUSIONS: Subjects with T1D and PDR exhibit altered DNA methylation patterns in blood. Some of these epigenetic changes may predict the development of PDR, suggesting that DNA methylation may be used as a prospective marker of PDR.

Effects of palmitate on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets.

BACKGROUND: Circulating free fatty acids are often elevated in patients with type 2 diabetes (T2D) and obese individuals. Chronic exposure to high levels of saturated fatty acids has detrimental effects on islet function and insulin secretion. Altered gene expression and epigenetics may contribute to T2D and obesity. However, there is limited information on whether fatty acids alter the genome-wide transcriptome profile in conjunction with DNA methylation patterns in human pancreatic islets. To dissect the molecular mechanisms linking lipotoxicity to impaired insulin secretion, we investigated the effects of a 48 h palmitate treatment in vitro on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets. METHODS: Genome-wide mRNA expression was analyzed using Affymetrix GeneChip(®) Human Gene 1.0 ST whole transcript-based array (n = 13) and genome-wide DNA methylation was analyzed using Infinium HumanMethylation450K BeadChip (n = 13) in human pancreatic islets exposed to palmitate or control media for 48 h. A non-parametric paired Wilcoxon statistical test was used to analyze mRNA expression. Apoptosis was measured using Apo-ONE(®) Homogeneous Caspase-3/7 Assay (n = 4). RESULTS: While glucose-stimulated insulin secretion was decreased, there was no significant effect on apoptosis in human islets exposed to palmitate. We identified 1,860 differentially expressed genes in palmitate-treated human islets. These include candidate genes for T2D, such as TCF7L2, GLIS3, HNF1B and SLC30A8. Additionally, genes in glycolysis/gluconeogenesis, pyruvate metabolism, fatty acid metabolism, glutathione metabolism and one carbon pool by folate were differentially expressed in palmitate-treated human islets. Palmitate treatment altered the global DNA methylation level and DNA methylation levels of CpG island shelves and shores, 5'UTR, 3'UTR and gene body regions in human islets. Moreover, 290 genes with differential expression had a corresponding change in DNA methylation, for example, TCF7L2 and GLIS3. Importantly, out of the genes differentially expressed due to palmitate treatment in human islets, 67 were also associated with BMI and 37 were differentially expressed in islets from T2D patients. CONCLUSION: Our study demonstrates that palmitate treatment of human pancreatic islets gives rise to epigenetic modifications that together with altered gene expression may contribute to impaired insulin secretion and T2D.

Predicting type 2 diabetes via machine learning integration of multiple omics from human pancreatic islets.

Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple layers of biomedical information, such as different Omics, may allow more accurate understanding of complex diseases such as T2D. Our aim was to explore and use Machine Learning to integrate multiple sources of biological/molecular information (multiOmics), in our case RNA-sequening, DNA methylation, SNP and phenotypic data from islet donors with T2D and non-diabetic controls. We exploited Machine Learning to perform multiOmics integration of DNA methylation, expression, SNPs, and phenotypes from pancreatic islets of 110 individuals, with ~ 30% being T2D cases. DNA methylation was analyzed using Infinium MethylationEPIC array, expression was analyzed using RNA-sequencing, and SNPs were analyzed using HumanOmniExpress arrays. Supervised linear multiOmics integration via DIABLO based on Partial Least Squares (PLS) achieved an accuracy of 91 ± 15% of T2D prediction with an area under the curve of 0.96 ± 0.08 on the test dataset after cross-validation. Biomarkers identified by this multiOmics integration, including SACS and TXNIP DNA methylation, OPRD1 and RHOT1 expression and a SNP annotated to ANO1, provide novel insights into the interplay between different biological mechanisms contributing to T2D. This Machine Learning approach of multiOmics cross-sectional data from human pancreatic islets achieved a promising accuracy of T2D prediction, which may potentially find broad applications in clinical diagnostics. In addition, it delivered novel candidate biomarkers for T2D and links between them across the different Omics.

Genes with epigenetic alterations in human pancreatic islets impact mitochondrial function, insulin secretion, and type 2 diabetes.

Epigenetic dysregulation may influence disease progression. Here we explore whether epigenetic alterations in human pancreatic islets impact insulin secretion and type 2 diabetes (T2D). In islets, 5,584 DNA methylation sites exhibit alterations in T2D cases versus controls and are associated with HbA1c in individuals not diagnosed with T2D. T2D-associated methylation changes are found in enhancers and regions bound by ß-cell-specific transcription factors and associated with reduced expression of e.g. CABLES1, FOXP1, GABRA2, GLR1A, RHOT1, and TBC1D4. We find RHOT1 (MIRO1) to be a key regulator of insulin secretion in human islets. Rhot1-deficiency in ß-cells leads to reduced insulin secretion, ATP/ADP ratio, mitochondrial mass, Ca2+, and respiration. Regulators of mitochondrial dynamics and metabolites, including L-proline, glycine, GABA, and carnitines, are altered in Rhot1-deficient ß-cells. Islets from diabetic GK rats present Rhot1-deficiency. Finally, RHOT1methylation in blood is associated with future T2D. Together, individuals with T2D exhibit epigenetic alterations linked to mitochondrial dysfunction in pancreatic islets.

Type 2 diabetes candidate genes, including PAX5, cause impaired insulin secretion in human pancreatic islets.

Type 2 diabetes (T2D) is caused by insufficient insulin secretion from pancreatic ß cells. To identify candidate genes contributing to T2D pathophysiology, we studied human pancreatic islets from approximately 300 individuals. We found 395 differentially expressed genes (DEGs) in islets from individuals with T2D, including, to our knowledge, novel (OPRD1, PAX5, TET1) and previously identified (CHL1, GLRA1, IAPP) candidates. A third of the identified expression changes in islets may predispose to diabetes, as expression of these genes associated with HbA1c in individuals not previously diagnosed with T2D. Most DEGs were expressed in human ß cells, based on single-cell RNA-Seq data. Additionally, DEGs displayed alterations in open chromatin and associated with T2D SNPs. Mouse KO strains demonstrated that the identified T2D-associated candidate genes regulate glucose homeostasis and body composition in vivo. Functional validation showed that mimicking T2D-associated changes for OPRD1, PAX5, and SLC2A2 impaired insulin secretion. Impairments in Pax5-overexpressing ß cells were due to severe mitochondrial dysfunction. Finally, we discovered PAX5 as a potential transcriptional regulator of many T2D-associated DEGs in human islets. Overall, we have identified molecular alterations in human pancreatic islets that contribute to ß cell dysfunction in T2D pathophysiology.

Epigenetics of type 2 diabetes mellitus and weight change - a tool for precision medicine?

Pioneering studies performed over the past few decades demonstrate links between epigenetics and type 2 diabetes mellitus (T2DM), the metabolic disorder with the most rapidly increasing prevalence in the world. Importantly, these studies identified epigenetic modifications, including altered DNA methylation, in pancreatic islets, adipose tissue, skeletal muscle and the liver from individuals with T2DM. As non-genetic factors that affect the risk of T2DM, such as obesity, unhealthy diet, physical inactivity, ageing and the intrauterine environment, have been associated with epigenetic modifications in healthy individuals, epigenetics probably also contributes to T2DM development. In addition, genetic factors associated with T2DM and obesity affect the epigenome in human tissues. Notably, causal mediation analyses found DNA methylation to be a potential mediator of genetic associations with metabolic traits and disease. In the past few years, translational studies have identified blood-based epigenetic markers that might be further developed and used for precision medicine to help patients with T2DM receive optimal therapy and to identify patients at risk of complications. This Review focuses on epigenetic mechanisms in the development of T2DM and the regulation of body weight in humans, with a special focus on precision medicine.

The expression of myosin heavy chain (MHC) genes in human skeletal muscle is related to metabolic characteristics involved in the pathogenesis of type 2 diabetes.

Type 2 diabetes patients exhibit a reduction in oxidative muscle fibres and an increase in glycolytic muscle fibres. In this study, we investigated whether both genetic and non-genetic factors influence the mRNA expression levels of three myosin heavy chain (MHC) genes represented in different fibre types. Specifically, we examined the MHC7 (slow-twitch oxidative fibre), MHCIIa (fast-twitch oxidative fibre) and MHCIIx/d (fast-twitch glycolytic fibre) genes in human skeletal muscle. We further investigated the use of MHC mRNA expression as a proxy to determine fibre-type composition, as measured by traditional ATP staining. Two cohorts of age-matched Swedish men were studied to determine the relationship of muscle mRNA expression of MHC7, MHCIIa, and MHCIIx/d with muscle fibre composition. A classical twin approach, including young and elderly Danish twin pairs, was utilised to examine if differences in expression levels were due to genetic or environmental factors. Although MHCIIx/d mRNA expression correlated positively with the level of type IIx/d muscle fibres in the two cohorts (P<0.05), a relatively low magnitude of correlation suggests that mRNA does not fully correlate with fibre-type composition. Heritability estimates and genetic analysis suggest that the levels of MHC7, MHCIIa and MHCIIx/d expression are primarily under non-genetic influence, and MHCIIa indicated an age-related decline. PGC-1α exhibited a positive relationship with the expression of all three MHC genes (P<0.05); meanwhile, PGC-1ß related positively with MHCIIa expression and negatively with MHCIIx/d expression (P<0.05). While MHCIIa expression related positively with insulin-stimulated glucose uptake (P<0.01), MHCIIx/d expression related negatively with insulin-stimulated glucose uptake (P<0.05). Our findings suggest that the expression levels of the MHC genes are associated with age and both PGC-1α and PGC-1ß and indicate that the MHC genes may to some extent be used to determine fibre-type composition in human skeletal muscle.

Genetic and epigenetic factors are associated with expression of respiratory chain component NDUFB6 in human skeletal muscle.

Insulin resistance and type 2 diabetes are associated with decreased expression of genes that regulate oxidative phosphorylation in skeletal muscle. To determine whether this defect might be inherited or acquired, we investigated the association of genetic, epigenetic, and nongenetic factors with expression of NDUFB6, a component of the respiratory chain that is decreased in muscle from diabetic patients. Expression of NDUFB6 was influenced by age, with lower gene expression in muscle of elderly subjects. Heritability of NDUFB6 expression in muscle was estimated to be approximately 60% in twins. A polymorphism in the NDUFB6 promoter region that creates a possible DNA methylation site (rs629566, A/G) was associated with a decline in muscle NDUFB6 expression with age. Although young subjects with the rs629566 G/G genotype exhibited higher muscle NDUFB6 expression, this genotype was associated with reduced expression in elderly subjects. This was subsequently explained by the finding of increased DNA methylation in the promoter of elderly, but not young, subjects carrying the rs629566 G/G genotype. Furthermore, the degree of DNA methylation correlated negatively with muscle NDUFB6 expression, which in turn was associated with insulin sensitivity. Our results demonstrate that genetic, epigenetic, and nongenetic factors associate with NDUFB6 expression in human muscle and suggest that genetic and epigenetic factors may interact to increase age-dependent susceptibility to insulin resistance.

Author Correction: ATAC-seq reveals alterations in open chromatin in pancreatic islets from subjects with type 2 diabetes.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Epigenetic Changes in Islets of Langerhans Preceding the Onset of Diabetes.

The identification of individuals with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention. Here, we used a translational approach and prediction criteria to identify changes in DNA methylation visible before the development of T2D. Islets of Langerhans were isolated from genetically identical 10-week-old female New Zealand Obese mice, which differ in their degree of hyperglycemia and in liver fat content. The application of a semiexplorative approach identified 497 differentially expressed and methylated genes (P = 6.42e-09, hypergeometric test) enriched in pathways linked to insulin secretion and extracellular matrix-receptor interaction. The comparison of mouse data with DNA methylation levels of incident T2D cases from the prospective European Prospective Investigation of Cancer (EPIC)-Potsdam cohort, revealed 105 genes with altered DNA methylation at 605 cytosine-phosphate-guanine (CpG) sites, which were associated with future T2D. AKAP13, TENM2, CTDSPL, PTPRN2, and PTPRS showed the strongest predictive potential (area under the receiver operating characteristic curve values 0.62-0.73). Among the new candidates identified in blood cells, 655 CpG sites, located in 99 genes, were differentially methylated in islets of humans with T2D. Using correction for multiple testing detected 236 genes with an altered DNA methylation in blood cells and 201 genes in diabetic islets. Thus, the introduced translational approach identified novel putative biomarkers for early pancreatic islet aberrations preceding T2D.

Epigenetics in Human Obesity and Type 2 Diabetes.

Epigenetic mechanisms control gene activity and the development of an organism. The epigenome includes DNA methylation, histone modifications, and RNA-mediated processes, and disruption of this balance may cause several pathologies and contribute to obesity and type 2 diabetes (T2D). This Review summarizes epigenetic signatures obtained from human tissues of relevance for metabolism-i.e., adipose tissue, skeletal muscle, pancreatic islets, liver, and blood-in relation to obesity and T2D. Although this research field is still young, these comprehensive data support not only a role for epigenetics in disease development, but also epigenetic alterations as a response to disease. Genetic predisposition, as well as aging, contribute to epigenetic variability, and several environmental factors, including exercise and diet, further interact with the human epigenome. The reversible nature of epigenetic modifications holds promise for future therapeutic strategies in obesity and T2D.

Fasting unmasks differential fat and muscle transcriptional regulation of metabolic gene sets in low versus normal birth weight men.

BACKGROUND: Individuals born with low birth weight (LBW) have an increased risk of metabolic diseases when exposed to diets rich in calories and fat but may respond to fasting in a metabolically preferential manner. We hypothesized that impaired foetal growth is associated with differential regulation of gene expression and epigenetics in metabolic tissues in response to fasting in young adulthood. METHODS: Genome-wide expression and DNA methylation were analysed in subcutaneous adipose tissue (SAT) and skeletal muscle from LBW and normal birth weight (NBW) men after 36 h fasting and after an isocaloric control study using microarrays. FINDINGS: Transcriptome analyses revealed that expression of genes involved in oxidative phosphorylation (OXPHOS) and other key metabolic pathways were lower in SAT from LBW vs NBW men after the control study, but paradoxically higher in LBW vs NBW men after 36 h fasting. Thus, fasting was associated with downregulated OXPHOS and metabolic gene sets in NBW men only. Likewise, in skeletal muscle only NBW men downregulated OXPHOS genes with fasting. Few epigenetic changes were observed in SAT and muscle between the groups. INTERPRETATION: Our results provide insights into the molecular mechanisms in muscle and adipose tissue governing a differential metabolic response in subjects with impaired foetal growth when exposed to fasting in adulthood. The results support the concept of developmental programming of metabolic diseases including type 2 diabetes. FUND: The Swedish Research Council, the Danish Council for Strategic Research, the Novo Nordisk foundation, the Swedish Foundation for Strategic Research, The European Foundation for the Study of Diabetes, The EU 6th Framework EXGENESIS grant and Rigshospitalet.