Assessment of Whole-Genome Regression for Type II Diabetes

Lifestyle and genetic factors play a large role in the development of Type 2 Diabetes (T2D). Despite the important role of genetic factors, genetic information is not incorporated into the clinical assessment of T2D risk. We assessed and compared Whole Genome Regression methods to predict the T2D status of 5,245 subjects from the Framingham Heart Study. For evaluating each method we constructed the following set of regression models: A clinical baseline model (CBM) which included non-genetic covariates only. CBM was extended by adding the first two marker-derived principal components and 65 SNPs identified by a recent GWAS consortium for T2D (M-65SNPs). Subsequently, it was further extended by adding 249,798 genome-wide SNPs from a high-density array. The Bayesian models used to incorporate genome-wide marker information as predictors were: Bayes A, Bayes Cπ, Bayesian LASSO (BL), and the Genomic Best Linear Unbiased Prediction (G-BLUP). Results included estimates of the genetic variance and heritability, genetic scores for T2D, and predictive ability evaluated in a 10-fold cross-validation. The predictive AUC estimates for CBM and M-65SNPs were: 0.668 and 0.684, respectively. We found evidence of contribution of genetic effects in T2D, as reflected in the genomic heritability estimates (0.492±0.066). The highest predictive AUC among the genome-wide marker Bayesian models was 0.681 for the Bayesian LASSO. Overall, the improvement in predictive ability was moderate and did not differ greatly among models that included genetic information. Approximately 58% of the total number of genetic variants was found to contribute to the overall genetic variation, indicating a complex genetic architecture for T2D. Our results suggest that the Bayes Cπ and the G-BLUP models with a large set of genome-wide markers could be used for predicting risk to T2D, as an alternative to using high-density arrays when selected markers from large consortiums for a given complex trait or disease are unavailable.     

Genetic Determinants for Gestational Diabetes Mellitus and Related Metabolic Traits in Mexican Women

Epidemiological and physiological similarities among Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes (T2D) suggest that both diseases, share a common genetic background. T2D risk variants have been associated to GDM susceptibility. However, the genetic architecture of GDM is not yet completely understood. We analyzed 176 SNPs for 115 loci previously associated to T2D, GDM and body mass index (BMI), as well as a set of 118 Ancestry Informative Markers (AIMs), in 750 pregnant Mexican women. Association with GDM was found for two of the most frequently replicated T2D loci: a TCF7L2 haplotype (CTTC: rs7901695, rs4506565, rs7903146, rs12243326; P=2.16x10^-06; OR=2.95) and a KCNQ1 haplotype (TTT: rs2237892, rs163184, rs2237897; P=1.98x10^-05; OR=0.55). In addition, we found two loci associated to glycemic traits: CENTD2 (60’ OGTT glycemia: rs1552224, P=0.03727) and MTNR1B (HOMA B: rs1387153, P=0.05358). Remarkably, a major susceptibility SLC16A11 locus for T2D in Mexicans was not shown to play a role in GDM risk. The fact that two of the main T2D associated loci also contribute to the risk of developing GDM in Mexicans, confirm that both diseases share a common genetic background. However, lack of association with a Native American contribution T2D risk haplotype, SLC16A11, suggests that other genetic mechanisms may be in play for GDM.     

Do Variants Associated with Susceptibility to Pancreatic Cancer and Type 2 Diabetes Reciprocally Affect Risk?

ObjectivesAlthough type 2 diabetes mellitus is a known risk factor for pancreatic cancer, the existence of shared genetic susceptibility is largely unknown. We evaluated whether any reported genetic risk variants of either disease found by genome-wide association studies reciprocally confer susceptibility.MethodsData that were generated in previous genome-wide association studies (GENEVA Type 2 Diabetes; PanScan) were obtained through the National Institutes of Health database of Genotypes and Phenotypes (dbGaP). Using the PanScan datasets, we tested for association of 38 variants within 37 genomic regions known to be susceptibility factors for type 2 diabetes. We further examined whether type 2 diabetes variants predispose to pancreatic cancer risk stratified by diabetes status. Correspondingly, we examined the association of fourteen pancreatic cancer susceptibility variants within eight genomic regions in the GENEVA Type 2 Diabetes dataset.ResultsFour plausible associations of diabetes variants and pancreatic cancer risk were detected at a significance threshold of p = 0.05, and one pancreatic cancer susceptibility variant was associated with diabetes risk at threshold of p = 0.05, but none remained significant after correction for multiple comparisons.ConclusionCurrently identified GWAS susceptibility variants are unlikely to explain the potential shared genetic etiology between Type 2 diabetes and pancreatic cancer.     

Genetic architecture of type 2 diabetes

Genome-wide association studies (GWAS) have identified over 70 loci associated with type 2 diabetes (T2D). Most genetic variants associated with T2D are common variants with modest effects on T2D and are shared with major ancestry groups. To what extent the genetic component of T2D can be explained by common variants relies upon the shape of the genetic architecture of T2D. Fine mapping utilizing populations with different patterns of linkage disequilibrium and functional annotation derived from experiments in relevant tissues are mandatory to track down causal variants responsible for the pathogenesis of T2D.     

Low Frequency Variants in the Exons Only Encoding Isoform A of HNF1A Do Not Contribute to Susceptibility to Type 2 Diabetes

Background

There is considerable interest in the hypothesis that low frequency, intermediate penetrance variants contribute to the proportion of Type 2 Diabetes (T2D) susceptibility not attributable to the common variants uncovered through genome-wide association approaches. Genes previously implicated in monogenic and multifactorial forms of diabetes are obvious candidates in this respect. In this study, we focussed on exons 8–10 of the HNF1A gene since rare, penetrant mutations in these exons (which are only transcribed in selected HNF1A isoforms) are associated with a later age of diagnosis of Maturity onset diabetes of the young (MODY) than mutations in exons 1–7. The age of diagnosis in the subgroup of HNF1A-MODY individuals with exon 8–10 mutations overlaps with that of early multifactorial T2D, and we set out to test the hypothesis that these exons might also harbour low-frequency coding variants of intermediate penetrance that contribute to risk of multifactorial T2D.

Methodology and Principal Findings

We performed targeted capillary resequencing of HNF1A exons 8–10 in 591 European T2D subjects enriched for genetic aetiology on the basis of an early age of diagnosis (≤45 years) and/or family history of T2D (≥1 affected sibling). PCR products were sequenced and compared to the published HNF1A sequence. We identified several variants (rs735396 [IVS9−24T>C], rs1169304 [IVS8+29T>C], c.1768+44C>T [IVS9+44C>T] and rs61953349 [c.1545G>A, p.T515T] but no novel non-synonymous coding variants were detected.

Conclusions and Significance

We conclude that low frequency, nonsynonymous coding variants in the terminal exons of HNF1A are unlikely to contribute to T2D-susceptibility in European samples. Nevertheless, the rationale for seeking low-frequency causal variants in genes known to contain rare, penetrant mutations remains strong and should motivate efforts to screen other genes in a similar fashion.     

Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study

BackgroundType 2 diabetes (T2D) is highly prevalent in British South Asians, yet they are underrepresented in research. Genes & Health (G&H) is a large, population study of British Pakistanis and Bangladeshis (BPB) comprising genomic and routine health data. We assessed the extent to which genetic risk for T2D is shared between BPB and European populations (EUR). We then investigated whether the integration of a polygenic risk score (PRS) for T2D with an existing risk tool (QDiabetes) could improve prediction of incident disease and the characterisation of disease subtypes.Methods and findingsIn this observational cohort study, we assessed whether common genetic loci associated with T2D in EUR individuals were replicated in 22,490 BPB individuals in G&H. We replicated fewer loci in G&H (n = 76/338, 22%) than would be expected given power if all EUR-ascertained loci were transferable (n = 101, 30%; p = 0.001). Of the 27 transferable loci that were powered to interrogate this, only 9 showed evidence of shared causal variants. We constructed a T2D PRS and combined it with a clinical risk instrument (QDiabetes) in a novel, integrated risk tool (IRT) to assess risk of incident diabetes. To assess model performance, we compared categorical net reclassification index (NRI) versus QDiabetes alone. In 13,648 patients free from T2D followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval (CI): 2.0% to 4.4%). IRT performed best in reclassification of individuals aged less than 40 years deemed low risk by QDiabetes alone (NRI 5.6%, 95% CI 3.6% to 7.6%), who tended to be free from comorbidities and slim. After adjustment for QDiabetes score, PRS was independently associated with progression to T2D after gestational diabetes (hazard ratio (HR) per SD of PRS 1.23, 95% CI 1.05 to 1.42, p = 0.028). Using cluster analysis of clinical features at diabetes diagnosis, we replicated previously reported disease subgroups, including Mild Age-Related, Mild Obesity-related, and Insulin-Resistant Diabetes, and showed that PRS distribution differs between subgroups (p = 0.002). Integrating PRS in this cluster analysis revealed a Probable Severe Insulin Deficient Diabetes (pSIDD) subgroup, despite the absence of clinical measures of insulin secretion or resistance. We also observed differences in rates of progression to micro- and macrovascular complications between subgroups after adjustment for confounders. Study limitations include the absence of an external replication cohort and the potential biases arising from missing or incorrect routine health data.ConclusionsOur analysis of the transferability of T2D loci between EUR and BPB indicates the need for larger, multiancestry studies to better characterise the genetic contribution to disease and its varied aetiology. We show that a T2D PRS optimised for this high-risk BPB population has potential clinical application in BPB, improving the identification of T2D risk (especially in the young) on top of an established clinical risk algorithm and aiding identification of subgroups at diagnosis, which may help future efforts to stratify care and treatment of the disease.

Sam Hodgson and colleagues investigate whether the common genetic differences associated with type 2 diabetes in people of European ancestry can be transferred to people of British Pakistani and Bangladeshi ancestry, integrating a novel polygenic risk score with an established clinical risk score.     

Type 2 diabetes: new genes, new understanding

Over the past two years, there has been a spectacular change in the capacity to identify common genetic variants that contribute to predisposition to complex multifactorial phenotypes such as type 2 diabetes (T2D). The principal advance has been the ability to undertake surveys of genome-wide association in large study samples. Through these and related efforts, approximately 20 common variants are now robustly implicated in T2D susceptibility. Current developments, for example in high-throughput resequencing, should help to provide a more comprehensive view of T2D susceptibility in the near future. Although additional investigation is needed to define the causal variants within these novel T2D-susceptibility regions, to understand disease mechanisms and to effect clinical translation, these findings are already highlighting the predominant contribution of defects in pancreatic beta-cell function to the development of T2D.     

Association of type 2 diabetes susceptibility loci with one-year weight loss in the look AHEAD clinical trial

The importance of lifestyle intervention for the prevention and treatment of type 2 diabetes (T2D) has been underscored by the limited benefit of pharmacologic therapies. We sought to determine whether genetic variants that contribute to T2D risk modify the response of weight and waist circumference to an intensive lifestyle intervention (ILI) in patients with obesity and T2D. Look AHEAD (Action for Health in Diabetes) is a randomized clinical trial comparing an ILI with a control condition on the risk of cardiovascular disease in overweight adults with T2D. We analyzed 28 single-nucleotide polymorphisms (SNPs) at/near 17 T2D-susceptibility genes in 3,903 consented participants. We genetically characterized the cohort by assessing whether T2D-susceptibility loci were overrepresented compared with a nondiabetic community-based cohort (N = 1,016). We evaluated the association of individual variants and a composite genetic risk score (GRS) with anthropometric traits at baseline and after 1-year of intervention. Look AHEAD subjects carried more T2D-susceptibility alleles than the control population. At baseline, TCF7L2 risk alleles and the highest GRS were associated with lower BMI and waist circumference. Nominally significant genotype-by-intervention interactions were detected for 1-year change in waist circumference with JAZF1, MTNR1B, and IRS1, and BMI with JAZF1. Highest GRS was associated with a greater reduction in waist circumference at year 1, although the variance in change attributable to the GRS was small. This study shows that the genetic burden associated with T2D risk does not undermine the effect of lifestyle intervention and suggests the existence of additional genomic regions, distinct from the T2D-susceptibility loci, which may enhance or mitigate weight loss.     

Variants at the endocannabinoid receptor CB1 gene (CNR1) and insulin sensitivity, type 2 diabetes, and coronary heart disease

Inhibition of the endocannabinoid receptor CB1 improves insulin sensitivity, lowers glycemia, and slows atherosclerosis. We analyzed whether common variants in the gene encoding CB1, CNR1, are associated with insulin resistance, risk of type 2 diabetes (T2D) or coronary heart disease (CHD). We studied 2,411 participants of the Framingham Offspring Study (mean age 60 years, 52% women) for quantitative traits and CHD, and the Framingham SHARe database for T2D risk. We genotyped 19 single-nucleotide polymorphisms (SNPs) that tagged 85% (at r(2) = 0.8) of common (>5%) CNR1 SNPs. Fasting blood glucose and insulin at the 7th (1999-2001) exam were collected. We used age-, sex-, BMI-adjusted models to test additive associations of genotype with homeostasis model assessment of insulin resistance (HOMA(IR)) (linear mixed-effect models), T2D, or CHD. To account for multiple tests of SNPs, we generated empirical P values. The C allele at SNP rs806365 (frequency, 57.4%), ~4.1 kb 3' from CNR1, was associated with increased HOMA(IR) (n = 2,261, β = 0.05 per C, empirical P = 0.01), risk of T2D (674 cases, odds ratio = 1.19 per C, nominal P = 0.01) and CHD (237 cases, hazard ratio = 1.23 per C, nominal P = 0.04). The association of rs806365 with HOMA(IR) was replicated in a meta-analysis of two independent cohorts (National Health and Nutrition Examination Survey III genetic cohort (NHANES-III) plus Partners Case-Control Diabetes Study; 2,540 white individuals, β = 0.037, nominal P = 0.007), but not in the large Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) Consortium (n = 29,248, nominal P = 0.74). The association of rs806365 was not replicated either with T2D in Diabetes Genetics Replication and Meta-analysis (DIAGRAM) (n = 10,128, nominal P = 0.31), or with CHD in PROCARDIS (n = 13,614, nominal P = 0.37). Although supported by initial results, we found no reproducible statistical association of common variation at CNR1 with insulin resistance, T2D, or CHD.     

Pathway Analysis of GWAS Provides New Insights into Genetic Susceptibility to 3 Inflammatory Diseases

Although the introduction of genome-wide association studies (GWAS) have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn''s disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC). The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10⁻³–10⁻²⁰) with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes) for T1D, 350 SNPs (189 genes) for RA and 493 SNPs (277 genes) for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC) and RA (85% AUC), and weakly predictive of CD (60% AUC). The predictive ability of the T1D model (without any parameter refitting) had good predictive ability (79% AUC) in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.     

Recursive organizer (ROR): an analytic framework for sequence-based association analysis

The advent of next-generation sequencing technologies affords the ability to sequence thousands of subjects cost-effectively, and is revolutionizing the landscape of genetic research. With the evolving genotyping/sequencing technologies, it is not unrealistic to expect that we will soon obtain a pair of diploidic fully phased genome sequences from each subject in the near future. Here, in light of this potential, we propose an analytic framework called, recursive organizer (ROR), which recursively groups sequence variants based upon sequence similarities and their empirical disease associations, into fewer and potentially more interpretable super sequence variants (SSV). As an illustration, we applied ROR to assess an association between HLA-DRB1 and type 1 diabetes (T1D), discovering SSVs of HLA-DRB1 with sequence data from the Wellcome Trust Case Control Consortium. Specifically, ROR reduces 36 observed unique HLA-DRB1 sequences into 8 SSVs that empirically associate with T1D, a fourfold reduction of sequence complexity. Using HLA-DRB1 data from Type 1 Diabetes Genetics Consortium as cases and data from Fred Hutchinson Cancer Research Center as controls, we are able to validate associations of these SSVs with T1D. Further, SSVs consist of nine nucleotides, and each associates with its corresponding amino acids. Detailed examination of these selected amino acids reveals their potential functional roles in protein structures and possible implication to the mechanism of T1D.     

Vitamin A levels are decreased but not influenced by glucose- or lipid-lowering medications in subjects with type 2 diabetes

Background and aimType 2 diabetes (T2D) is a complex polygenic disease with unclear mechanisms. Clinical studies on the association of vitamin A with T2D in humans are still controversial. Herein, we aimed to investigate the plasma levels of vitamin A, predictor factors, and its correlations with clinical phenotypes in Emirati population. The effect of glucose-and lipid-lowering medications on vitamin A levels was also studied.MethodsA cross-sectional cohort comprised 158 T2D-subjects and 90 healthy controls were recruited from the United Arab Emirates National Diabetes Study (UAEDIAB). All anthropometric, clinical, and biomedical measurements were collected. Plasma levels of vitamin A were determined using ELISA assay.ResultsLevels of vitamin A were significantly lower in T2D-subjects compared to healthy control (p < 0.01). Vitamin A levels were unaffected by gender base and inversely correlated with age, fasting blood glucose (FBG), glycated hemoglobin (HbA1c), waist circumference, triglycerides, and body mass index (BMI). Regression analysis revealed that HbA1c and age are predictors for vitamin A. Intake of glucose- or lipid-lowering medications showed no effect on vitamin A levels.ConclusionHbA1c and age are predictors for low levels of vitamin A among Emirati-T2D subjects. No influence of glucose and lipid-lowering medications on the plasma levels of vitamin A.     

Shared molecular and functional frameworks among five complex human disorders: a comparative study on interactomes linked to susceptibility genes

Background

Genome-wide association studies (gwas) are invaluable in revealing the common variants predisposing to complex human diseases. Yet, until now, the large volumes of data generated from such analyses have not been explored extensively enough to identify the molecular and functional framework hosting the susceptibility genes.

Methodology/Principal Findings

We investigated the relationships among five neurodegenerative and/or autoimmune complex human diseases (Parkinson''s disease-Park, Alzheimer''s disease-Alz, multiple sclerosis-MS, rheumatoid arthritis-RA and Type 1 diabetes-T1D) by characterising the interactomes linked to their gwas-genes. An initial study on the MS interactome indicated that several genes predisposing to the other autoimmune or neurodegenerative disorders may come into contact with it, suggesting that susceptibility to distinct diseases may converge towards common molecular and biological networks. In order to test this hypothesis, we performed pathway enrichment analyses on each disease interactome independently. Several issues related to immune function and growth factor signalling pathways appeared in all autoimmune diseases, and, surprisingly, in Alzheimer''s disease. Furthermore, the paired analyses of disease interactomes revealed significant molecular and functional relatedness among autoimmune diseases, and, unexpectedly, between T1D and Alz.

Conclusions/Significance

The systems biology approach highlighted several known pathogenic processes, indicating that changes in these functions might be driven or sustained by the framework linked to genetic susceptibility. Moreover, the comparative analyses among the five genetic interactomes revealed unexpected genetic relationships, which await further biological validation. Overall, this study outlines the potential of systems biology to uncover links between genetics and pathogenesis of complex human disorders.     

Chlamydia muridarum infection subverts dendritic cell function to promote Th2 immunity and airways hyperreactivity

There is strong epidemiological evidence that Chlamydia infection can lead to exacerbation of asthma. However, the mechanism(s) whereby chlamydial infection, which normally elicits a strong Th type 1 (Th1) immune response, can exacerbate asthma, a disease characterized by dominant Th type 2 (Th2) immune responses, remains unclear. In the present study, we show that Chlamydia muridarum infection of murine bone marrow-derived dendritic cells (BMDC) modulates the phenotype, cytokine secretion profile, and Ag-presenting capability of these BMDC. Chlamydia-infected BMDC express lower levels of CD80 and increased CD86 compared with noninfected BMDC. When infected with Chlamydia, BMDC secrete increased TNF-alpha, IL-6, IL-10, IL-12, and IL-13. OVA peptide-pulsed infected BMDC induced significant proliferation of transgenic CD4(+) DO11.10 (D10) T cells, strongly inhibited IFN-gamma secretion by D10 cells, and promoted a Th2 phenotype. Intratracheal transfer of infected, but not control noninfected, OVA peptide-pulsed BMDC to naive BALB/c mice, which had been i.v. infused with naive D10 T cells, resulted in increased levels of IL-10 and IL-13 in bronchoalveolar lavage fluid. Recipients of these infected BMDC showed significant increases in airways resistance and decreased airways compliance compared with mice that had received noninfected BMDC, indicative of the development of airways hyperreactivity. Collectively, these data suggest that Chlamydia infection of DCs allows the pathogen to deviate the induced immune response from a protective Th1 to a nonprotective Th2 response that could permit ongoing chronic infection. In the setting of allergic airways inflammation, this infection may then contribute to exacerbation of the asthmatic phenotype.     

Genetic Approaches to the Study of Gene Variants and Their Impact on the Pathophysiology of Type 2 Diabetes

Diabetes mellitus is an incurable progressive disease, characterized by elevated blood glucose levels, which lead to the development of micro- and macrovascular complications. Although the etiopathology of the disease remains unclear, it seems to be multifactorial, with an important interaction between genetics and environmental causes. Currently, the genetics of type 2 diabetes (T2D) is poorly understood. The recent advance of the genetic technologies and with a better understanding of genetics, more than 120 distinct genetic loci, with more than 150 variants, have been identified that may be involved in the pathogenesis of T2D. However, as these variants can account for only approximately 20% of the heritability of T2D, there is an obvious need for additional approaches to identify susceptibility genes or genetic mechanisms involved in the development of this disease. There is a growing number of genes found to be related to T2D; however, their individual impact on the pathogenesis of the disease appears to be low, while silencing of protective genes may also contribute to the development of this disease. The present review attempts to summarize our current knowledge in the field of genetics of T2D, highlighting the possible practical applications for each approach.     

Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes,and Cytokine Signaling Genes in Crohn's Disease

Pathway analyses of genome-wide association studies aggregate information over sets of related genes, such as genes in common pathways, to identify gene sets that are enriched for variants associated with disease. We develop a model-based approach to pathway analysis, and apply this approach to data from the Wellcome Trust Case Control Consortium (WTCCC) studies. Our method offers several benefits over existing approaches. First, our method not only interrogates pathways for enrichment of disease associations, but also estimates the level of enrichment, which yields a coherent way to promote variants in enriched pathways, enhancing discovery of genes underlying disease. Second, our approach allows for multiple enriched pathways, a feature that leads to novel findings in two diseases where the major histocompatibility complex (MHC) is a major determinant of disease susceptibility. Third, by modeling disease as the combined effect of multiple markers, our method automatically accounts for linkage disequilibrium among variants. Interrogation of pathways from eight pathway databases yields strong support for enriched pathways, indicating links between Crohn''s disease (CD) and cytokine-driven networks that modulate immune responses; between rheumatoid arthritis (RA) and “Measles” pathway genes involved in immune responses triggered by measles infection; and between type 1 diabetes (T1D) and IL2-mediated signaling genes. Prioritizing variants in these enriched pathways yields many additional putative disease associations compared to analyses without enrichment. For CD and RA, 7 of 8 additional non-MHC associations are corroborated by other studies, providing validation for our approach. For T1D, prioritization of IL-2 signaling genes yields strong evidence for 7 additional non-MHC candidate disease loci, as well as suggestive evidence for several more. Of the 7 strongest associations, 4 are validated by other studies, and 3 (near IL-2 signaling genes RAF1, MAPK14, and FYN) constitute novel putative T1D loci for further study.     

Genetic variants entail type 2 diabetes as an innate immune disorder

Type 2 Diabetes (T2D) is characterized by alteration in the circulatory levels of key inflammatory proteins, where our body strives to eliminate the perturbing factor through inflammation as a final resort to restore homeostasis. Plasma proteins play a crucial role to orchestrate this immune response. Over the past two decades, rigorous genetic efforts taken to comprehend T2D physiology have been partially successful and have left behind a dearth of knowledge of its causality. Here, we have investigated how the reported genetic variants of T2D are associated with circulatory levels of key plasma proteins. We identified 99 T2D genetic variants that serve as strong pQTL (protein Quantitative Trait Loci) for 72 plasma proteins, of which 4 proteins namely Small nuclear ribonucleoprotein F [SNRPF] (p = 2.99 × 10⁻¹⁴), Platelet endothelial cell adhesion molecule [PECAM1] (p = 1.9 × 10⁻⁴⁵), Trypsin-2 [PRSS2] (p = 7.6 × 10⁻⁴³) and Trypsin-3 [PRSS3] (p = 5.7 × 10⁻⁸) were previously not reported for association to T2D. The genes that encode these 72 proteins were observed to be highly expressed in at least one of the four T2D relevant tissues - liver, pancreas, adipose and whole blood. Comparative analysis of interactions of the studied proteins amongst these four tissues revealed distinct molecular connectivity. Assessment of biological function by gene-set enrichment highlighted innate immune system as the lead process enacted by the identified proteins (FDR q = 3.7 × 10⁻¹⁶). To validate the findings, we analyzed Coronary Artery Disease (CAD) and Rheumatoid Arthritis (RA) individually and as expected, we observed innate immune system as a top enriched pathway for RA but not for CAD. Our study illuminates strong regulation of plasma proteome by the established genetic variants of T2D.     

Genome-wide analysis of copy number variation in type 1 diabetes

Type 1 diabetes (T1D) tends to cluster in families, suggesting there may be a genetic component predisposing to disease. However, a recent large-scale genome-wide association study concluded that identified genetic factors, single nucleotide polymorphisms, do not account for overall familiality. Another class of genetic variation is the amplification or deletion of >1 kilobase segments of the genome, also termed copy number variations (CNVs). We performed genome-wide CNV analysis on a cohort of 20 unrelated adults with T1D and a control (Ctrl) cohort of 20 subjects using the Affymetrix SNP Array 6.0 in combination with the Birdsuite copy number calling software. We identified 39 CNVs as enriched or depleted in T1D versus Ctrl. Additionally, we performed CNV analysis in a group of 10 monozygotic twin pairs discordant for T1D. Eleven of these 39 CNVs were also respectively enriched or depleted in the Twin cohort, suggesting that these variants may be involved in the development of islet autoimmunity, as the presently unaffected twin is at high risk for developing islet autoimmunity and T1D in his or her lifetime. These CNVs include a deletion on chromosome 6p21, near an HLA-DQ allele. CNVs were found that were both enriched or depleted in patients with or at high risk for developing T1D. These regions may represent genetic variants contributing to development of islet autoimmunity in T1D.     

Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ～50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ～2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.