Diabetes-associated Single Nucleotide Polymorphisms Research Articles

In Vivo Reporter Assays Uncover Changes in Enhancer Activity Caused by Type 2 Diabetes-Associated Single Nucleotide Polymorphisms.

Many single nucleotide polymorphisms (SNPs) associated with type 2 diabetes overlap with putative endocrine pancreatic enhancers, suggesting that these SNPs modulate enhancer activity and, consequently, gene expression. We performed in vivo mosaic transgenesis assays in zebrafish to quantitatively test the enhancer activity of type 2 diabetes–associated loci. Six out of 10 tested sequences are endocrine pancreatic enhancers. The risk variant of two sequences decreased enhancer activity, while in another two incremented it. One of the latter (rs13266634) locates in an SLC30A8 exon, encoding a tryptophan-to-arginine substitution that decreases SLC30A8 function, which is the canonical explanation for type 2 diabetes risk association. However, other type 2 diabetes–associated SNPs that truncate SLC30A8 confer protection from this disease, contradicting this explanation. Here, we clarify this incongruence, showing that rs13266634 boosts the activity of an overlapping enhancer and suggesting an SLC30A8 gain of function as the cause for the increased risk for the disease. We further dissected the functionality of this enhancer, finding a single nucleotide mutation sufficient to impair its activity. Overall, this work assesses in vivo the importance of disease-associated SNPs in the activity of endocrine pancreatic enhancers, including a poorly explored case where a coding SNP modulates the activity of an enhancer.

A type 2 diabetes-associated SNP in KCNQ1 (rs163184) modulates the binding activity of the locus for Sp3 and Lsd1/Kdm1a, potentially affecting CDKN1C expression.

Although genome-wide association studies have shown that potassium voltage-gated channel subfamily Q member 1 (KCNQ1) is one of the genes that is most significantly associated with type 2 diabetes mellitus (T2DM), functionally annotating disease-associated single nucleotide polymorphisms (SNPs) remains a challenge. Recently, our group described a novel strategy to identify proteins that bind to SNP-containing loci in an allele-specific manner. The present study successfully applied this strategy to investigate rs163184, a T2DM susceptibility SNP located in the intronic region of KCNQ1. Comparative analysis of DNA-binding proteins revealed that the binding activities for the genomic region containing SNP rs163184 differed between alleles for several proteins, including Sp3 and Lsd1/Kdm1a. Sp3 preferentially bound to the non-risk rs163184 allele and stimulated transcriptional activity in an artificial promoter containing this region. Lsd1/Kdm1a was identified to be preferentially recruited to the non-risk allele of the rs163184 region and reduced Sp3-dependent transcriptional activity in the artificial promoter. In addition, expression of the nearby cyclin-dependent kinase inhibitor 1C (CDKN1C) gene was revealed to be upregulated after SP3 knockdown in cells that possessed non-risk alleles. This suggests that CDKN1C is potentially one of the functional targets of SNP rs163184, which modulates the binding activity of the locus for Sp3 and Lsd1/Kdm1a.

Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs.

The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g., AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues (e.g., adipose, skeletal muscle, pancreas) and biological processes and canonical pathways (e.g., lipid metabolism, leptin, and glucose-insulin signaling pathways) that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism.

Type 2 Diabetes Genetic Variants and Risk of Diabetic Retinopathy

Genetic association studies to date have not identified any robust risk loci for diabetic retinopathy (DR). We hypothesized that individuals with more diabetes genetic risk alleles have a higher risk of developing DR. Case-control genetic association study. We evaluated the aggregate effects of multiple type 2 diabetes-associated genetic variants on the risk of DR among 1528 participants with diabetes from the Singapore Epidemiology of Eye Diseases Study, of whom 547 (35.8%) had DR. Participants underwent a comprehensive ocular examination, including dilated fundus photography. Retinal photographs were graded using the modified Airlie House classification system to assess the presence and severity of DR following a standardized protocol. We identified 76 previously discovered type 2 diabetes-associated single nucleotide polymorphisms (SNPs) and constructed multilocus genetic risk scores (GRSs) for each individual by summing the number of risk alleles for each SNP weighted by the respective effect estimates on DR. Two GRSs were generated: an overall GRS that included all 76 discovered type 2 diabetes-associated SNPs, and an Asian-specific GRS that included a subset of 55 SNPs previously found to be associated with type 2 diabetes in East and/or South Asian ancestry populations. Associations between the GRSs with DR were determined using logistic regression analyses. Discriminating ability of the GRSs was determined by the area under the receiver operating characteristic curve (AUC). Odds ratios on DR. Participants in the top tertile of the overall GRS were 2.56-fold more likely to have DR compared with participants in the lowest tertile. Participants in the top tertile of the Asian-specific GRS were 2.00-fold more likely to have DR compared with participants in the bottom tertile. Both GRSs were associated with higher DR severity levels. However, addition of the GRSs to traditional risk factors improved the AUC only modestly by 3% to 4%. Type 2 diabetes-associated genetic loci were significantly associated with higher risks of DR, independent of traditional risk factors. Our findings may provide new insights to further our understanding of the genetic pathogenesis of DR.

Comparative analysis of type 2 diabetes-associated SNP alleles identifies allele-specific DNA-binding proteins for the KCNQ1 locus.

Although recent genome-wide association studies (GWAS) have been extremely successful, it remains a big challenge to functionally annotate disease‑associated single nucleotide polymorphisms (SNPs), as the majority of these SNPs are located in non‑coding regions of the genome. In this study, we described a novel strategy for identifying the proteins that bind to the SNP‑containing locus in an allele‑specific manner and successfully applied this method to SNPs in the type 2 diabetes mellitus susceptibility gene, potassium voltage‑gated channel, KQT‑like subfamily Q, member 1 (KCNQ1). DNA fragments encompassing SNPs, and risk or non‑risk alleles were immobilized onto the novel nanobeads and DNA‑binding proteins were purified from the nuclear extracts of pancreatic β cells using these DNA‑immobilized nanobeads. Comparative analysis of the allele-specific DNA-binding proteins indicated that the affinities of several proteins for the examined SNPs differed between the alleles. Nuclear transcription factor Y (NF‑Y) specifically bound the non‑risk allele of the SNP rs2074196 region and stimulated the transcriptional activity of an artificial promoter containing SNP rs2074196 in an allele‑specific manner. These results suggest that SNP rs2074196 modulates the affinity of the locus for NF‑Y and possibly induces subsequent changes in gene expression. The findings of this study indicate that our comparative method using novel nanobeads is effective for the identification of allele‑specific DNA‑binding proteins, which may provide important clues for the functional impact of disease‑associated non‑coding SNPs.

A cautionary tale: the non-causal association between type 2 diabetes risk SNP, rs7756992, and levels of non-coding RNA, CDKAL1-v1.

Aims/hypothesisIntronic single nucleotide polymorphisms (SNPs) in the CDKAL1 gene are associated with risk of developing type 2 diabetes. A strong correlation between risk alleles and lower levels of the non-coding RNA, CDKAL1-v1, has recently been reported in whole blood extracted from Japanese individuals. We sought to replicate this association in two independent cohorts: one using whole blood from white UK-resident individuals, and one using a collection of human pancreatic islets, a more relevant tissue type to study with respect to the aetiology of diabetes.MethodsLevels of CDKAL1-v1 were measured by real-time PCR using RNA extracted from human whole blood (n = 70) and human pancreatic islets (n = 48). Expression with respect to genotype was then determined.ResultsIn a simple linear regression model, expression of CDKAL1-v1 was associated with the lead type 2 diabetes-associated SNP, rs7756992, in whole blood and islets. However, these associations were abolished or substantially reduced in multiple regression models taking into account rs9366357 genotype: a moderately linked SNP explaining a much larger amount of the variation in CDKAL1-v1 levels, but not strongly associated with risk of type 2 diabetes.Conclusions/interpretationContrary to previous findings, we provide evidence against a role for dysregulated expression of CDKAL1-v1 in mediating the association between intronic SNPs in CDKAL1 and susceptibility to type 2 diabetes. The results of this study illustrate how caution should be exercised when inferring causality from an association between disease-risk genotype and non-coding RNA expression.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-015-3508-9) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Role of Type 1 Diabetes-Associated SNPs on Risk of Autoantibody Positivity in the TEDDY Study.

The Environmental Determinants of Diabetes in the Young (TEDDY) study prospectively follows 8,677 children enrolled from birth who carry HLA-susceptibility genotypes for development of islet autoantibodies (IA) and type 1 diabetes (T1D). During the median follow-up time of 57 months, 350 children developed at least one persistent IA (GAD antibody, IA-2A, or micro insulin autoantibodies) and 84 of them progressed to T1D. We genotyped 5,164 Caucasian children for 41 non-HLA single nucleotide polymorphisms (SNPs) that achieved genome-wide significance for association with T1D in the genome-wide association scan meta-analysis conducted by the Type 1 Diabetes Genetics Consortium. In TEDDY participants carrying high-risk HLA genotypes, eight SNPs achieved significant association to development of IA using time-to-event analysis (P < 0.05), whereof four were significant after adjustment for multiple testing (P < 0.0012): rs2476601 in PTPN22 (hazard ratio [HR] 1.54 [95% CI 1.27–1.88]), rs2292239 in ERBB3 (HR 1.33 [95% CI 1.14–1.55]), rs3184504 in SH2B3 (HR 1.38 [95% CI 1.19–1.61]), and rs1004446 in INS (HR 0.77 [0.66–0.90]). These SNPs were also significantly associated with T1D in particular: rs2476601 (HR 2.42 [95% CI 1.70–3.44]). Although genes in the HLA region remain the most important genetic risk factors for T1D, other non-HLA genetic factors contribute to IA, a first step in the pathogenesis of T1D, and the progression of the disease.

Association of physical activity with lower type 2 diabetes incidence is weaker among individuals at high genetic risk.

We examined whether or not the association of physical activity with type 2 diabetes incidence differs according to several types of genetic susceptibility. In a large prospective cohort with 821 incident cases of type 2 diabetes, we examined interactions of physical activity with: (1) each of 65 type 2 diabetes-associated single nucleotide polymorphisms (SNPs); (2) a genetic risk score (GRS) comprising all 65 SNPs; (3) two GRSs comprised of SNPs implicated in insulin resistance (IR) and insulin secretion; (4) GRSs for fasting insulin (FI) and fasting glucose. We found a significant interaction of physical activity and the type 2 diabetes GRS (p interaction = 0.016), suggesting a weaker protective effect of physical activity in those at high genetic risk. Based on the interactions observed with the IR GRS (p interaction = 0.046) and the FI GRS (p interaction = 0.042), it appears that the overall type 2 diabetes GRS interaction most likely occurs through genetic susceptibility to IR as opposed to insulin secretion. Furthermore, this interaction was more pronounced in women (p interaction = 0.0025) than in men (p interaction = 0.46). No single SNP stood out as displaying a strong interaction with physical activity. We conclude that although physical activity appears to have an overall protective effect on type 2 diabetes, this putative effect is weakest among individuals with high genetic risk for type 2 diabetes and IR.

Type 2 diabetes-related genetic risk scores associated with variations in fasting plasma glucose and development of impaired glucose homeostasis in the prospective DESIR study.

Genome-wide association studies have firmly established 65 independent European-derived loci associated with type 2 diabetes and 36 loci contributing to variations in fasting plasma glucose (FPG). Using individual data from the Data from an Epidemiological Study on the Insulin Resistance Syndrome (DESIR) prospective study, we evaluated the contribution of three genetic risk scores (GRS) to variations in metabolic traits, and to the incidence and prevalence of impaired fasting glycaemia (IFG) and type 2 diabetes. Three GRS (GRS-1, 65 type 2 diabetes-associated single nucleotide polymorphisms [SNPs]; GRS-2, GRS-1 combined with 24 FPG-raising SNPs; and GRS-3, FPG-raising SNPs alone) were analysed in 4,075 DESIR study participants. GRS-mediated effects on longitudinal variations in quantitative traits were assessed in 3,927 nondiabetic individuals using multivariate linear mixed models, and on the incidence and prevalence of hyperglycaemia at 9years using Cox and logistic regression models. The contribution of each GRS to risk prediction was evaluated using the C-statistic and net reclassification improvement (NRI) analysis. The two most inclusive GRS were significantly associated with increased FPG (β = 0.0011mmol/l per year per risk allele, p GRS-1 = 8.2 × 10(-5) and p GRS-2 = 6.0 × 10(-6)), increased incidence of IFG and type 2 diabetes (per allele: HR GRS-1 1.03, p = 4.3 × 10(-9) and HR GRS-2 1.04, p = 1.0 × 10(-16)), and the 9year prevalence (OR GRS-1 1.13 [95% CI 1.10, 1.17], p = 1.9 × 10(-14) for type 2 diabetes only; OR GRS-2 1.07 [95% CI 1.05, 1.08], p = 7.8 × 10(-25), for IFG and type 2 diabetes). No significant interaction was found between GRS-1 or GRS-2 and potential confounding factors. Each GRS yielded a modest, but significant, improvement in overall reclassification rates (NRI GRS-1 17.3%, p = 6.6 × 10(-7); NRI GRS-2 17.6%, p = 4.2 × 10(-7); NRI GRS-3 13.1%, p = 1.7 × 10(-4)). Polygenic scores based on combined genetic information from type 2 diabetes risk and FPG variation contribute to discriminating middle-aged individuals at risk of developing type 2 diabetes in a general population.

Allele-Specific Transcriptional Activity at Type 2 Diabetes–Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus

Translation of noncoding common variant association signals into meaningful molecular and biological mechanisms explaining disease susceptibility remains challenging. For the type 2 diabetes association signal in JAZF1 intron 1, we hypothesized that the underlying risk variants have cis-regulatory effects in islets or other type 2 diabetes–relevant cell types. We used maps of experimentally predicted open chromatin regions to prioritize variants for functional follow-up studies of transcriptional activity. Twelve regions containing type 2 diabetes–associated variants were tested for enhancer activity in 832/13 and MIN6 insulinoma cells. Three regions exhibited enhancer activity and only rs1635852 displayed allelic differences in enhancer activity; the type 2 diabetes risk allele T showed lower transcriptional activity than the nonrisk allele C. This risk allele showed increased binding to protein complexes, suggesting that it functions as part of a transcriptional repressor complex. We applied DNA affinity capture to identify factors in the complex and determined that the risk allele preferentially binds the pancreatic master regulator PDX1. These data suggest that the rs1635852 region in JAZF1 intron 1 is part of a cis-regulatory complex and that maps of open chromatin are useful to guide identification of variants with allelic differences in regulatory activity at type 2 diabetes loci.

Identification of CpG-SNPs associated with type 2 diabetes and differential DNA methylation in human pancreatic islets

Aims/hypothesisTo date, the molecular function of most of the reported type 2 diabetes-associated loci remains unknown. The introduction or removal of cytosine–phosphate–guanine (CpG) dinucleotides, which are possible sites of DNA methylation, has been suggested as a potential mechanism through which single-nucleotide polymorphisms (SNPs) can affect gene function via epigenetics. The aim of this study was to examine if any of 40 SNPs previously associated with type 2 diabetes introduce or remove a CpG site and if these CpG-SNPs are associated with differential DNA methylation in pancreatic islets of 84 human donors.MethodsDNA methylation was analysed using pyrosequencing.ResultsWe found that 19 of 40 (48%) type 2 diabetes-associated SNPs introduce or remove a CpG site. Successful DNA methylation data were generated for 16 of these 19 CpG-SNP loci, representing the candidate genes TCF7L2, KCNQ1, PPARG, HHEX, CDKN2A, SLC30A8, DUSP9, CDKAL1, ADCY5, SRR, WFS1, IRS1, DUSP8, HMGA2, TSPAN8 and CHCHD9. All analysed CpG-SNPs were associated with differential DNA methylation of the CpG-SNP site in human islets. Moreover, six CpG-SNPs, representing TCF7L2, KCNQ1, CDKN2A, ADCY5, WFS1 and HMGA2, were also associated with DNA methylation of surrounding CpG sites. Some of the type 2 diabetes CpG-SNP sites that exhibit differential DNA methylation were further associated with gene expression, alternative splicing events determined by splice index, and hormone secretion in the human islets. The 19 type 2 diabetes-associated CpG-SNPs are in strong linkage disequilibrium (r 2 > 0.8) with a total of 295 SNPs, including 91 CpG-SNPs.Conclusions/interpretationOur results suggest that the introduction or removal of a CpG site may be a molecular mechanism through which some of the type 2 diabetes SNPs affect gene function via differential DNA methylation and consequently contributes to the phenotype of the disease.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-012-2815-7) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Allele-Specific Transcriptional Activity at Type 2 Diabetes-Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus

Allele-Specific Transcriptional Activity at Type 2 Diabetes-Associated Single Nucleotide Polymorphisms in Regions of Pancreatic Islet Open Chromatin at the JAZF1 Locus

Two SNPs Associated with Type 2 Diabetes and Obesity at Melanocortin-4 Receptor Gene Loci Exhibited High Fst Values and Natural Selection

Background: Human adaptation to environmental changes in food supply, lifestyle, and geography may have initiated the selection of genes associated with the metabolism of glucose, lipids, carbohydrates, and energy. Obesity is significantly associated with type 2 diabetes mellitus, metabolic syndrome, hypertension, stroke, and cardiovascular diseases. The worldwide prevalence of obesity and type 2 diabetes is increasing steadily. Obesity and type 2 diabetes are highly heritable diseases that cause serious health problems. The melanocortin-4 receptor gene is one of the major obesity genes, and common genetic variations near the melanocortin-4 receptor gene were found to be associated with obesity, type 2 diabetes, and insulin resistance. We aimed to uncover evidence of selection at melanocortin-4 receptor gene loci using single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes and obesity. Methods: We analyzed melanocortin-4 receptor gene loci in HapMap populations to detect selection using a 3-step test: Wright’s F-statistics (Fst) as a measure of population differentiation, the long-range haplotype (LRH) test to obtain evidence of positive selection by testing haplotypes, and integrated haplotype score (iHS). Results: We observed one body mass index (BMI)-associated SNP (rs7227255) and one type 2 diabetesassociated SNP (rs11873305) that exhibited high Fst values, and showed high population differentiation and natural selection at the melanocortin-4 receptor gene loci. Conclusion: This is the first report that SNPs associated with type 2 diabetes and obesity exhibited high Fst values in one-gene loci. Most of the SNPs associated with type 2 diabetes and obesity that were reported did not demonstrate high Fst values. Our findings are important for clinical medicine. We suggest that melanocortin-4 receptor agonists may be useful drugs for the treatment of obesity and type 2 diabetes, and that further studies should examine the adaptive evolution of obesity, type 2 diabetes, and insulin resistance genes.

Design of a randomized trial of diabetes genetic risk testing to motivate behavior change: the Genetic Counseling/lifestyle Change (GC/LC) Study for Diabetes Prevention.

The efficacy of diabetes genetic risk testing to motivate behavior change for diabetes prevention is currently unknown. This paper presents key issues in the design and implementation of one of the first randomized trials (The Genetic Counseling/Lifestyle Change (GC/LC) Study for Diabetes Prevention) to test whether knowledge of diabetes genetic risk can motivate patients to adopt healthier behaviors. Because individuals may react differently to receiving 'higher' vs 'lower' genetic risk results, we designed a 3-arm parallel group study to separately test the hypotheses that: (1) patients receiving 'higher' diabetes genetic risk results will increase healthy behaviors compared to untested controls, and (2) patients receiving 'lower' diabetes genetic risk results will decrease healthy behaviors compared to untested controls. In this paper we describe several challenges to implementing this study, including: (1) the application of a novel diabetes risk score derived from genetic epidemiology studies to a clinical population, (2) the use of the principle of Mendelian randomization to efficiently exclude 'average' diabetes genetic risk patients from the intervention, and (3) the development of a diabetes genetic risk counseling intervention that maintained the ethical need to motivate behavior change in both 'higher' and 'lower' diabetes genetic risk result recipients. Diabetes genetic risk scores were developed by aggregating the results of 36 diabetes-associated single nucleotide polymorphisms. Relative risk for type 2 diabetes was calculated using Framingham Offspring Study outcomes, grouped by quartiles into 'higher', 'average' (middle two quartiles) and 'lower' genetic risk. From these relative risks, revised absolute risks were estimated using the overall absolute risk for the study group. For study efficiency, we excluded all patients receiving 'average' diabetes risk results from the subsequent intervention. This post-randomization allocation strategy was justified because genotype represents a random allocation of parental alleles ('Mendelian randomization'). Finally, because it would be unethical to discourage participants to participate in diabetes prevention behaviors, we designed our two diabetes genetic risk counseling interventions (for 'higher' and 'lower' result recipients) so that both groups would be motivated despite receiving opposing results. For this initial assessment of the clinical implementation of genetic risk testing we assessed intermediate outcomes of attendance at a 12-week diabetes prevention course and changes in self-reported motivation. If effective, longer term studies with larger sample sizes will be needed to assess whether knowledge of diabetes genetic risk can help patients prevent diabetes. We designed a randomized clinical trial designed to explore the motivational impact of disclosing both higher than average and lower than average genetic risk for type 2 diabetes. This design allowed exploration of both increased risk and false reassurance, and has implications for future studies in translational genomics.

Expression analysis of loci associated with type 2 diabetes in human tissues.

Genetic mapping has identified over 20 loci contributing to genetic risk of type 2 diabetes. The next step is to identify the genes and mechanisms regulating the contributions of genetic risk to disease. The goal of this study was to evaluate the effect of age, height, weight and risk alleles on expression of candidate genes in diabetes-associated regions in three relevant human tissues. We measured transcript abundance for WFS1, KCNJ11, TCF2 (also known as HNF1B), PPARG, HHEX, IDE, CDKAL1, CDKN2A, CDKN2B, IGF2BP2, SLC30A8 and TCF7L2 by quantitative RT-PCR in human pancreas (n = 50), colon (n = 195) and liver (n = 50). Tissue samples were genotyped for single nucleotide polymorphisms (SNPs) associated with type 2 diabetes. The effects of age, height, weight, tissue and SNP on RNA expression were tested by linear modelling. Expression of all genes exhibited tissue bias. Immunohistochemistry confirmed the findings for HHEX, IDE and SLC30A8, which showed strongest tissue-specific mRNA expression bias. Neither age, height nor weight were associated with gene expression. We found no evidence that type 2 diabetes-associated SNPs affect neighbouring gene expression (cis-expression quantitative trait loci) in colon, pancreas and liver. This study provides new evidence that tissue-type, but not age, height, weight or SNPs in or near candidate genes associated with increased risk of type 2 diabetes are strong contributors to differential gene expression in the genes and tissues examined.

Genome-wide analysis of histone modifications in human pancreatic islets

The global diabetes epidemic poses a major challenge. Epigenetic events contribute to the etiology of diabetes; however, the lack of epigenomic analysis has limited the elucidation of the mechanistic basis for this link. To determine the epigenetic architecture of human pancreatic islets we mapped the genome-wide locations of four histone marks: three associated with gene activation-H3K4me1, H3K4me2, and H3K4me3-and one associated with gene repression, H3K27me3. Interestingly, the promoters of the highly transcribed insulin and glucagon genes are occupied only sparsely by H3K4me2 and H3K4me3. Globally, we identified important relationships between promoter structure, histone modification, and gene expression. We demonstrated co-occurrences of histone modifications including bivalent marks in mature islets. Furthermore, we found a set of promoters that is differentially modified between islets and other cell types. We also use our histone marks to determine which of the known diabetes-associated single-nucleotide polymorphisms are likely to be part of regulatory elements. Our global map of histone marks will serve as an important resource for understanding the epigenetic basis of type 2 diabetes.

Quantitative trait analysis of type 2 diabetes susceptibility loci identified from whole genome association studies in the Insulin Resistance Atherosclerosis Family Study.

Evaluate type 2 diabetes susceptibility variants identified from genome-wide association studies in Hispanic Americans and African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) for association with quantitative measures of glucose homeostasis and determine their biological role in vivo. Seventeen type 2 diabetes-associated single nucleotide polymorphisms (SNPs) were genotyped in 1,268 Hispanic- and 581 African-American participants from the IRAS-FS. SNPs were tested for association with quantitative measures of glucose homeostasis, including insulin sensitivity index (S(I)), acute insulin response (AIR), and disposition index. Previously identified risk variants in cyclin-dependent kinase 5 regulatory subunit associated protein 1-like 1 (CDKAL1) were associated with reduced AIR (P < 0.0046) in Hispanic Americans. Additionally in Hispanic Americans, the variant in a hypothetical gene (chromosome 11; LOC387761) was significantly associated with AIR (P = 0.0046) with the risk allele showing protective effects, i.e., increased AIR. In both Hispanic- and African-American populations, risk variants at the solute carrier family 30, member 8 (SLC30A8) locus were nominally associated with decreased disposition index (P < 0.078). Risk variants in the insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) locus were associated with a decreased disposition index (P = 0.011) exclusively in Hispanic Americans. These data indicate a distinct, limited number of diabetes-related genes, more specifically the SNPs in the genes identified in European-derived populations, with modest evidence for association with glucose homeostasis traits in Hispanic Americans and African Americans. We observe evidence that diabetes risk for CDKAL1, SLC30A8, IGF2BP2, and LOC387761 is specifically mediated through defects in insulin secretion. The mechanisms of other predisposing genes remain to be elucidated.

Screening of 134 Single Nucleotide Polymorphisms (SNPs) Previously Associated With Type 2 Diabetes Replicates Association With 12 SNPs in Nine Genes

More than 120 published reports have described associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. However, multiple studies of the same variant have often been discordant. From a literature search, we identified previously reported type 2 diabetes-associated SNPs. We initially genotyped 134 SNPs on 786 index case subjects from type 2 diabetes families and 617 control subjects with normal glucose tolerance from Finland and excluded from analysis 20 SNPs in strong linkage disequilibrium (r(2) > 0.8) with another typed SNP. Of the 114 SNPs examined, we followed up the 20 most significant SNPs (P < 0.10) on an additional 384 case subjects and 366 control subjects from a population-based study in Finland. In the combined data, we replicated association (P < 0.05) for 12 SNPs: PPARG Pro12Ala and His447, KCNJ11 Glu23Lys and rs5210, TNF -857, SLC2A2 Ile110Thr, HNF1A/TCF1 rs2701175 and GE117881_360, PCK1 -232, NEUROD1 Thr45Ala, IL6 -598, and ENPP1 Lys121Gln. The replication of 12 SNPs of 114 tested was significantly greater than expected by chance under the null hypothesis of no association (P = 0.012). We observed that SNPs from genes that had three or more previous reports of association were significantly more likely to be replicated in our sample (P = 0.03), although we also replicated 4 of 58 SNPs from genes that had only one previous report of association.