Alexander Drong

The Genetic and Epigenetic Basis of Type 2 Diabetes and Obesity

Type 2 diabetes (T2D) and obesity are complex disorders that constitute major public health problems. The evidence for familial aggregation of both T2D and obesity is substantial. To date, more than 150 genetic loci are associated with the development of monogenic, syndromic, or multifactorial forms of T2D or obesity. However, the proportion of overall trait variance explained by these associated loci is modest (~5–10% for T2D, ~2% for body mass index (BMI)). Some of the familial aggregation not attributable to known genetic variation, as well as many of the effects of environmental exposures, may reflect epigenetic processes. In this review, we discuss the evidence concerning the genetic contribution to individual risk of T2D and obesity, and explore the potential role of epigenetic mechanisms. We also explain how genetics, epigenetics, and environment are likely to interact to define the individual risk of disease.

Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study.

BACKGROUND Indian Asians, who make up a quarter of the worlds population, are at high risk of developing type 2 diabetes. We investigated whether DNA methylation is associated with future type 2 diabetes incidence in Indian Asians and whether differences in methylation patterns between Indian Asians and Europeans are associated with, and could be used to predict, differences in the magnitude of risk of developing type 2 diabetes. METHODS We did a nested case-control study of DNA methylation in Indian Asians and Europeans with incident type 2 diabetes who were identified from the 8-year follow-up of 25 372 participants in the London Life Sciences Prospective Population (LOLIPOP) study. Patients were recruited between May 1, 2002, and Sept 12, 2008. We did epigenome-wide association analysis using samples from Indian Asians with incident type 2 diabetes and age-matched and sex-matched Indian Asian controls, followed by replication testing of top-ranking signals in Europeans. For both discovery and replication, DNA methylation was measured in the baseline blood sample, which was collected before the onset of type 2 diabetes. Epigenome-wide significance was set at p<1 × 10(-7). We compared methylation levels between Indian Asian and European controls without type 2 diabetes at baseline to estimate the potential contribution of DNA methylation to increased risk of future type 2 diabetes incidence among Indian Asians. FINDINGS 1608 (11·9%) of 13 535 Indian Asians and 306 (4·3%) of 7066 Europeans developed type 2 diabetes over a mean of 8·5 years (SD 1·8) of follow-up. The age-adjusted and sex-adjusted incidence of type 2 diabetes was 3·1 times (95% CI 2·8-3·6; p<0·0001) higher among Indian Asians than among Europeans, and remained 2·5 times (2·1-2·9; p<0·0001) higher after adjustment for adiposity, physical activity, family history of type 2 diabetes, and baseline glycaemic measures. The mean absolute difference in methylation level between type 2 diabetes cases and controls ranged from 0·5% (SD 0·1) to 1·1% (0·2). Methylation markers at five loci were associated with future type 2 diabetes incidence; the relative risk per 1% increase in methylation was 1·09 (95% CI 1·07-1·11; p=1·3 × 10(-17)) for ABCG1, 0·94 (0·92-0·95; p=4·2 × 10(-11)) for PHOSPHO1, 0·94 (0·92-0·96; p=1·4 × 10(-9)) for SOCS3, 1·07 (1·04-1·09; p=2·1 × 10(-10)) for SREBF1, and 0·92 (0·90-0·94; p=1·2 × 10(-17)) for TXNIP. A methylation score combining results for the five loci was associated with future type 2 diabetes incidence (relative risk quartile 4 vs quartile 1 3·51, 95% CI 2·79-4·42; p=1·3 × 10(-26)), and was independent of established risk factors. Methylation score was higher among Indian Asians than Europeans (p=1 × 10(-34)). INTERPRETATION DNA methylation might provide new insights into the pathways underlying type 2 diabetes and offer new opportunities for risk stratification and prevention of type 2 diabetes among Indian Asians. FUNDING The European Union, the UK National Institute for Health Research, the Wellcome Trust, the UK Medical Research Council, Action on Hearing Loss, the UK Biotechnology and Biological Sciences Research Council, the Oak Foundation, the Economic and Social Research Council, Helmholtz Zentrum Munchen, the German Research Center for Environmental Health, the German Federal Ministry of Education and Research, the German Center for Diabetes Research, the Munich Center for Health Sciences, the Ministry of Science and Research of the State of North Rhine-Westphalia, and the German Federal Ministry of Health.

The presence of methylation quantitative trait loci indicates a direct genetic influence on the level of DNA methylation in adipose tissue.

Genetic variants that associate with DNA methylation at CpG sites (methylation quantitative trait loci, meQTLs) offer a potential biological mechanism of action for disease associated SNPs. We investigated whether meQTLs exist in abdominal subcutaneous adipose tissue (SAT) and if CpG methylation associates with metabolic syndrome (MetSyn) phenotypes. We profiled 27,718 genomic regions in abdominal SAT samples of 38 unrelated individuals using differential methylation hybridization (DMH) together with genotypes at 5,227,243 SNPs and expression of 17,209 mRNA transcripts. Validation and replication of significant meQTLs was pursued in an independent cohort of 181 female twins. We find that, at 5% false discovery rate, methylation levels of 149 DMH regions associate with at least one SNP in a ±500 kilobase cis-region in our primary study. We sought to validate 19 of these in the replication study and find that five of these significantly associate with the corresponding meQTL SNPs from the primary study. We find that none of the 149 meQTL top SNPs is a significant expression quantitative trait locus in our expression data, but we observed association between expression levels of two mRNA transcripts and cis-methylation status. Our results indicate that DNA CpG methylation in abdominal SAT is partly under genetic control. This study provides a starting point for future investigations of DNA methylation in adipose tissue.

A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies

DNA methylation plays a fundamental role in the regulation of the genome, but the optimal strategy for analysis of genome-wide DNA methylation data remains to be determined. We developed a comprehensive analysis pipeline for epigenome-wide association studies (EWAS) using the Illumina Infinium HumanMethylation450 BeadChip, based on 2,687 individuals, with 36 samples measured in duplicate. We propose new approaches to quality control, data normalisation and batch correction through control-probe adjustment and establish a null hypothesis for EWAS using permutation testing. Our analysis pipeline outperforms existing approaches, enabling accurate identification of methylation quantitative trait loci for hypothesis driven follow-up experiments.

Mouse-human experimental epigenetic analysis unmasks dietary targets and genetic liability for diabetic phenotypes.

Using a functional approach to investigate the epigenetics of type 2 diabetes (T2D), we combine three lines of evidence-diet-induced epigenetic dysregulation in mouse, epigenetic conservation in humans, and T2D clinical risk evidence-to identify genes implicated in T2D pathogenesis through epigenetic mechanisms related to obesity. Beginning with dietary manipulation of genetically homogeneous mice, we identify differentially DNA-methylated genomic regions. We then replicate these results in adipose samples from lean and obese patients pre- and post-Roux-en-Y gastric bypass, identifying regions where both the location and direction of methylation change are conserved. These regions overlap with 27 genetic T2D risk loci, only one of which was deemed significant by GWAS alone. Functional analysis of genes associated with these regions revealed four genes with roles in insulin resistance, demonstrating the potential general utility of this approach for complementing conventional human genetic studies by integrating cross-species epigenomics and clinical genetic risk.

Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10−8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Insights into the Genetic Susceptibility to Type 2 Diabetes from Genome-Wide Association Studies of Obesity-Related Traits

Obesity and type 2 diabetes (T2D) are common and complex metabolic diseases, which are caused by an interchange between environmental and genetic factors. Recently, a number of large-scale genome-wide association studies (GWAS) have improved our knowledge of the genetic architecture and biological mechanisms of these diseases. Currently, more than ~250 genetic loci have been found for monogenic, syndromic, or common forms of T2D and/or obesity-related traits. In this review, we discuss the implications of these GWAS for obesity and T2D, and investigate the overlap of loci for obesity-related traits and T2D, highlighting potential mechanisms that affect T2D susceptibility.

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10−3), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10−4). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10−4) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.

The influence of menstrual cycle and endometriosis on endometrial methylome.

BackgroundAlterations in endometrial DNA methylation profile have been proposed as one potential mechanism initiating the development of endometriosis. However, the normal endometrial methylome is influenced by the cyclic hormonal changes, and the menstrual cycle phase-dependent epigenetic signature should be considered when studying endometrial disorders. So far, no studies have been performed to evaluate the menstrual cycle influences and endometriosis-specific endometrial methylation pattern at the same time.ResultsInfinium HumanMethylation 450K BeadChip arrays were used to explore DNA methylation profiles of endometrial tissues from various menstrual cycle phases from 31 patients with endometriosis and 24 healthy women. The DNA methylation profile of patients and controls was highly similar and only 28 differentially methylated regions (DMRs) between patients and controls were found. However, the overall magnitude of the methylation differences between patients and controls was rather small (Δβ ranging from –0.01 to –0.16 and from 0.01 to 0.08, respectively, for hypo- and hypermethylated CpGs). Unsupervised hierarchical clustering of the methylation data divided endometrial samples based on the menstrual cycle phase rather than diseased/non-diseased status. Further analysis revealed a number of menstrual cycle phase-specific epigenetic changes with largest changes occurring during the late-secretory and menstrual phases when substantial rearrangements of endometrial tissue take place. Comparison of cycle phase- and endometriosis-specific methylation profile changes revealed that 13 out of 28 endometriosis-specific DMRs were present in both datasets.ConclusionsThe results of our study accentuate the importance of considering normal cyclic epigenetic changes in studies investigating endometrium-related disease-specific methylation patterns.

Variability of genome-wide DNA methylation and mRNA expression profiles in reproductive and endocrine disease related tissues

ABSTRACT Genome-wide association studies in the fields of reproductive medicine and endocrinology are yielding robust genetic variants associated with disease. Integrated genomic, transcriptomic, and epigenomic molecular profiling studies are common methodologies used to understand the biologic pathways perturbed by these variants. However, molecular profiling resources do not include the tissue most relevant to many female reproductive traits, the endometrium, while the parameters influencing variability of results from its molecular profiling are unclear. We investigated the sources of DNA methylation and RNA expression profile variability in endometrium (n = 135), endometriotic disease tissue (endometriosis), and subcutaneous abdominal fat samples from 24 women, quantifying between-individual, within-tissue (cellular heterogeneity), and technical variation. DNA samples (n = 96) were analyzed using Illumina HumanMethlylation450 BeadChip arrays; RNA samples (n = 39) were analyzed using H12-expression arrays. Variance-component analyses showed that, for the top 10–50% variable DNA methylation/RNA expression sites, between-individual variation far exceeded within-tissue and technical variation. Menstrual-phase accounted for most variability in methylation/expression patterns in endometrium (Pm = 7.8 × 10−3, Pe = 8.4 × 10−5) but not in fat and endometriotic tissue; age was significantly associated with DNA methylation profile of endometrium (Pm = 9 × 10−5) and endometriotic disease tissue (Pm = 2.4 × 10−5); and smoking was significantly associated with DNA methylation in adipose tissue (Pm = 1.8 × 10−3). Hierarchical cluster analysis showed significantly different methylation signatures between endometrium and endometriotic tissue enriched for WNT signaling, angiogenesis, cadherin signaling, and gonadotropin-releasing-hormone-receptor pathways. Differential DNA methylation/expression analyses suggested detection of a limited number of sites with large fold changes (FC > 4), but power calculations accounting for different sources of variability showed that for robust detection >500 tissue samples are required. These results enable appropriate study design for large-scale expression and methylation tissue-based profiling relevant to many reproductive and endocrine traits.