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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 approximately 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.

Sarcopenia often co-exists with obesity, and may have additive effects on insulin resistance. Sarcopenic obese individuals could be at increased risk for type 2 diabetes. We performed a study to determine whether sarcopenia is associated with impairment in insulin sensitivity and glucose homeostasis in obese and non-obese individuals. We performed a cross-sectional analysis of National Health and Nutrition Examination Survey III data utilizing subjects of 20 years or older, non-pregnant (N = 14,528). Sarcopenia was identified from bioelectrical impedance measurement of muscle mass. Obesity was identified from body mass index. Outcomes were homeostasis model assessment of insulin resistance (HOMA IR), glycosylated hemoglobin level (HbA1C), and prevalence of pre-diabetes (6.0≤ HbA1C<6.5 and not on medication) and type 2 diabetes. Covariates in multiple regression were age, educational level, ethnicity and sex. Sarcopenia was associated with insulin resistance in non-obese (HOMA IR ratio 1.39, 95% confidence interval (CI) 1.26 to 1.52) and obese individuals (HOMA-IR ratio 1.16, 95% CI 1.12 to 1.18). Sarcopenia was associated with dysglycemia in obese individuals (HbA1C ratio 1.021, 95% CI 1.011 to 1.043) but not in non-obese individuals. Associations were stronger in those under 60 years of age. We acknowledge that the cross-sectional study design limits our ability to draw causal inferences. Sarcopenia, independent of obesity, is associated with adverse glucose metabolism, and the association is strongest in individuals under 60 years of age, which suggests that low muscle mass may be an early predictor of diabetes susceptibility. Given the increasing prevalence of obesity, further research is urgently needed to develop interventions to prevent sarcopenic obesity and its metabolic consequences.

Type 2 Diabetes (T2D) and other chronic diseases are caused by a complex combination of many genetic and environmental factors. Few methods are available to comprehensively associate specific physical environmental factors with disease. We conducted a pilot Environmental-Wide Association Study (EWAS), in which epidemiological data are comprehensively and systematically interpreted in a manner analogous to a Genome Wide Association Study (GWAS). We performed multiple cross-sectional analyses associating 266 unique environmental factors with clinical status for T2D defined by fasting blood sugar (FBG) concentration > or =126 mg/dL. We utilized available Centers for Disease Control (CDC) National Health and Nutrition Examination Survey (NHANES) cohorts from years 1999 to 2006. Within cohort sample numbers ranged from 503 to 3,318. Logistic regression models were adjusted for age, sex, body mass index (BMI), ethnicity, and an estimate of socioeconomic status (SES). As in GWAS, multiple comparisons were controlled and significant findings were validated with other cohorts. We discovered significant associations for the pesticide-derivative heptachlor epoxide (adjusted OR in three combined cohorts of 1.7 for a 1 SD change in exposure amount; p<0.001), and the vitamin gamma-tocopherol (adjusted OR 1.5; p<0.001). Higher concentrations of polychlorinated biphenyls (PCBs) such as PCB170 (adjusted OR 2.2; p<0.001) were also found. Protective factors associated with T2D included beta-carotenes (adjusted OR 0.6; p<0.001). Despite difficulty in ascertaining causality, the potential for novel factors of large effect associated with T2D justify the use of EWAS to create hypotheses regarding the broad contribution of the environment to disease. Even in this study based on prior collected epidemiological measures, environmental factors can be found with effect sizes comparable to the best loci yet found by GWAS.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Changes in gene expression in pancreatic beta-cells from type 2 diabetes (T2D) should provide insights into their abnormal insulin secretion and turnover. Frozen sections were obtained from cadaver pancreases of 10 control and 10 T2D human subjects. Beta-cell enriched samples were obtained by laser capture microdissection (LCM). RNA was extracted, amplified and subjected to microarray analysis. Further analysis was performed with DNA-Chip Analyzer (dChip) and Gene Set Enrichment Analysis (GSEA) software. There were changes in expression of genes linked to glucotoxicity. Evidence of oxidative stress was provided by upregulation of several metallothionein genes. There were few changes in the major genes associated with cell cycle, apoptosis or endoplasmic reticulum stress. There was differential expression of genes associated with pancreatic regeneration, most notably upregulation of members of the regenerating islet gene (REG) family and metalloproteinase 7 (MMP7). Some of the genes found in GWAS studies to be related to T2D were also found to be differentially expressed. IGF2BP2, TSPAN8, and HNF1B (TCF2) were upregulated while JAZF1 and SLC30A8 were downregulated. This study made possible by LCM has identified many novel changes in gene expression that enhance understanding of the pathogenesis of T2D.

Evidence is accumulating for a role of vitamin D in maintaining normal glucose homeostasis. However, studies that prospectively examined circulating concentrations of 25-hydroxyvitamin D (25-[OH] D) in relation to diabetes risk are limited. Our objective is to determine the association between maternal plasma 25-[OH] D concentrations in early pregnancy and the risk for gestational diabetes mellitus (GDM). A nested case-control study was conducted among a prospective cohort of 953 pregnant women. Among them, 57 incident GDM cases were ascertained and 114 women who were not diagnosed with GDM were selected as controls. Controls were frequency matched to cases for the estimated season of conception of the index pregnancy. Among women who developed GDM, maternal plasma 25-[OH] D concentrations at an average of 16 weeks of gestation were significantly lower than controls (24.2 vs. 30.1 ng/ml, P<0.001). This difference remained significant (3.62 ng/ml lower on average in GDM cases than controls (P value = 0.018)) after the adjustment for maternal age, race, family history of diabetes, and pre-pregnancy BMI. Approximately 33% of GDM cases, compared with 14% of controls (P<0.001), had maternal plasma 25-[OH] D concentrations consistent with a pre-specified diagnosis of vitamin D deficiency (<20 ng/ml). After adjustment for the aforementioned covariates including BMI, vitamin D deficiency was associated with a 2.66-fold (OR (95% CI): 2.66 (1.01-7.02)) increased GDM risk. Moreover, each 5 ng/ml decrease in 25-[OH] D concentrations was related to a 1.29-fold increase in GDM risk (OR (95% CI): 1.29 (1.05-1.60)). Additional adjustment for season and physical activity did not change findings substantially. Findings from the present study suggest that maternal vitamin D deficiency in early pregnancy is significantly associated with an elevated risk for GDM.

A fundamental challenge in human health is the identification of disease-causing genes. Recently, several studies have tackled this challenge via a network-based approach, motivated by the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process and are restricted to inferring single gene associations. Here, we provide a global, network-based method for prioritizing disease genes and inferring protein complex associations, which we call PRINCE. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. We exploit this function to predict not only genes but also protein complex associations with a disease of interest. We test our method on gene-disease association data, evaluating both the prioritization achieved and the protein complexes inferred. We show that our method outperforms extant approaches in both tasks. Using data on 1,369 diseases from the OMIM knowledgebase, our method is able (in a cross validation setting) to rank the true causal gene first for 34% of the diseases, and infer 139 disease-related complexes that are highly coherent in terms of the function, expression and conservation of their member proteins. Importantly, we apply our method to study three multi-factorial diseases for which some causal genes have been found already: prostate cancer, alzheimer and type 2 diabetes mellitus. PRINCE's predictions for these diseases highly match the known literature, suggesting several novel causal genes and protein complexes for further investigation.

Recent multi-dimensional approaches to the study of complex disease have revealed powerful insights into how genetic and epigenetic factors may underlie their aetiopathogenesis. We examined genotype-epigenotype interactions in the context of Type 2 Diabetes (T2D), focussing on known regions of genomic susceptibility. We assayed DNA methylation in 60 females, stratified according to disease susceptibility haplotype using previously identified association loci. CpG methylation was assessed using methylated DNA immunoprecipitation on a targeted array (MeDIP-chip) and absolute methylation values were estimated using a Bayesian algorithm (BATMAN). Absolute methylation levels were quantified across LD blocks, and we identified increased DNA methylation on the FTO obesity susceptibility haplotype, tagged by the rs8050136 risk allele A (p = 9.40×10(-4), permutation p = 1.0×10(-3)). Further analysis across the 46 kb LD block using sliding windows localised the most significant difference to be within a 7.7 kb region (p = 1.13×10(-7)). Sequence level analysis, followed by pyrosequencing validation, revealed that the methylation difference was driven by the co-ordinated phase of CpG-creating SNPs across the risk haplotype. This 7.7 kb region of haplotype-specific methylation (HSM), encapsulates a Highly Conserved Non-Coding Element (HCNE) that has previously been validated as a long-range enhancer, supported by the histone H3K4me1 enhancer signature. This study demonstrates that integration of Genome-Wide Association (GWA) SNP and epigenomic DNA methylation data can identify potential novel genotype-epigenotype interactions within disease-associated loci, thus providing a novel route to aid unravelling common complex diseases.

MicroRNAs (miRNAs) are small non-coding RNAs, that play important regulatory roles in a variety of biological processes, including development, differentiation, apoptosis, and metabolism. In mammals, miRNAs have been shown to modulate adipocyte differentiation. Therefore, we performed a global miRNA gene expression assay in different fat depots of overweight and obese individuals to investigate whether miRNA expression in human adipose tissue is fat-depot specific and associated with parameters of obesity and glucose metabolism. Paired samples of abdominal subcutaneous (SC) and intraabdominal omental adipose tissue were obtained from fifteen individuals with either normal glucose tolerance (NGT, n = 9) or newly diagnosed type 2 diabetes (T2D, n = 6). Expression of 155 miRNAs was carried out using the TaqMan(R)MicroRNA Assays Human Panel Early Access Kit (Applied Biosystems, Darmstadt, Germany). We identified expression of 106 (68%) miRNAs in human omental and SC adipose tissue. There was no miRNA exclusively expressed in either fat depot, suggesting common developmental origin of both fat depots. Sixteen miRNAs (4 in NGT, 12 in T2D group) showed a significant fat depot specific expression pattern. We identified significant correlations between the expression of miRNA-17-5p, -132, -99a, -134, 181a, -145, -197 and both adipose tissue morphology and key metabolic parameters, including visceral fat area, HbA(1c), fasting plasma glucose, and circulating leptin, adiponectin, interleukin-6. In conclusion, microRNA expression differences may contribute to intrinsic differences between omental and subcutaneous adipose tissue. In addition, human adipose tissue miRNA expression correlates with adipocyte phenotype, parameters of obesity and glucose metabolism.

Sub-Saharan Africa is facing rapidly increasing prevalences of cardiovascular disease, obesity, diabetes and hypertension. Previous and ongoing undernutrition among pregnant women may contribute to this development as suggested by epidemiological studies from high income countries linking undernutrition in fetal life with increased burden of non-communicable diseases in later life. We undertook to study the risks for hypertension, glucose intolerance and overweight forty years after fetal exposure to famine afflicted Biafra during the Nigerian civil war (1967-1970). Cohort study performed in June 27-July 31, 2009 in Enugu, Nigeria. Adults (n = 1,339) born before (1965-67), during (1968-January 1970), or after (1971-73) the years of famine were included. Blood pressure (BP), random plasma glucose (p-glucose) and anthropometrics, as well as prevalence of hypertension (BP>140/90 mmHg), impaired glucose tolerance (IGT; p-glucose 7.8-11.0 mmol/l), diabetes (DM; p-glucose ≥11.1 mmol/l), or overweight (BMI>25 kg/m(2)) were compared between the three groups. Fetal-infant exposure to famine was associated with elevated systolic (+7 mmHg; p<0.001) and diastolic (+5 mmHg; p<0.001) BP, increased p-glucose (+0.3 mmol/L; p<0.05) and waist circumference (+3 cm, p<0.001), increased risk of systolic hypertension (adjusted OR 2.87; 95% CI 1.90-4.34), IGT (OR 1.65; 95% CI 1.02-2.69) and overweight (OR 1.41; 95% CI 1.03-1.93) as compared to people born after the famine. Limitations of this study include the lack of birth weight data and the inability to separate effects of fetal and infant famine. Fetal and infant undernutrition is associated with significantly increased risk of hypertension and impaired glucose tolerance in 40-year-old Nigerians. Prevention of undernutrition during pregnancy and in infancy should therefore be given high priority in health, education, and economic agendas.