PTPN22 Trp620 explains the association of chromosome 1p13 with type 1 diabetes and shows a statistical interaction with HLA class II genotypes

In silico replication of the genome-wide association results of the Type 1 Diabetes Genetics Consortium

Recently, the Type 1 Diabetes Genetics Consortium (T1DGC) reported 22 novel type 1 diabetes (T1D)-associated loci identified by meta-analysis of three genome-wide association studies (GWASs) with a case-control design. However, the association of 10 of these 22 reported loci was not confirmed in the T1DGC family cohort (P > 0.1). To address concerns about potential bias from population stratification, this study aims to replicate the association in three independent GWAS cohorts, one of which was based on the stratification-proof transmission disequilibrium analysis. Three European-descent population samples were included in this study: 483 cases and both parents, a case-control cohort of 514 cases and 2027 controls, and an additional cohort of 1078 cases and 341 controls from the dbGaP database. Among the 22 SNPs reported by the T1DGC, we had high-quality genotypes for 15; the remaining were imputed. T1D association was replicated in seven loci after Bonferroni correction for 22 independent hypotheses. An additional eight loci had nominal (one-sided) significance of P < 0.1 in the same direction, giving a false discovery rate of 3.35%. The genetic susceptibility conferred by non-HLA loci in our family cohort with one affected offspring was higher than the T1DGC multiplex families. Reciprocally, the frequency of strongly predisposing HLA alleles in the multiplex families was higher. This study replicated T1D association with at least as many of these novel loci as expected from the power of our sample size, thus supporting the validity of the new discoveries.

Screen and clean: a tool for identifying interactions in genome-wide association studies

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.

Association between the 1858T allele of the protein tyrosine phosphatase nonreceptor type 22 and type 1 diabetes in a Brazilian population

The 1858T allele of the protein tyrosine phosphatase nonreceptor 22 (PTPN22) gene has been associated to diabetes in different populations. We investigated a possible relationship between this polymorphism and type 1 diabetes in a cohort of Brazilian patients. A significantly higher frequency of the 1858T allele was observed in diabetic patients (n = 211) than in control individuals (n = 241). Additionally, the heterozygote genotype was also increased in the diabetic group. No association was observed between the PTPN22 T allele and gender, or between T carriers and age of onset of T1D. This work describes for the first time a strong association of the 1858T allele with type 1 diabetes in a Brazilian population, reinforcing the role of this variant as an important susceptibility factor for this disease.

Genetic susceptibility to type 2 diabetes is associated with reduced prostate cancer risk

OBJECTIVE

To examine the collective effects of type 1 (T1D) and type 2 diabetes (T2D) risk alleles on prostate cancer (PCa) risk.

METHODS

Using data on 14 and 18 single nucleotide polymorphisms (SNPs) that effect T1D and T2D risk, respectively, we generated risk scores (a 'risk allele count' and a 'genetic relative risk') for both T1D and T2D for 1,171 non-Hispanic white, PSA-screened PCa cases and 1,101 matched controls from the Cancer Genetic Markers of Susceptibility study. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between the diabetes risk scores and PCa risk.

RESULTS

Both T2D risk scores, but neither T1D score, showed an inverse association with PCa (p < 0.01). These associations remained significant after excluding HNF1B SNP rs4430796 (a known PCa risk factor) from the analysis. The highest quartile of the T2D allele count (>20 risk alleles) was associated with reduced PCa risk (OR = 0.77; CI: 0.60-0.99) compared to the lowest category (<17 risk alleles).

CONCLUSIONS

These results suggest that individuals with increased genetic susceptibility to T2D have decreased risk for PCa. This association is consistent with the observation that individuals with T2D are at decreased risk for PCa; however, data on T2D status was not available for this analysis.

rs2476601 T allele (R620W) defines high-risk PTPN22 type I diabetes-associated haplotypes with preliminary evidence for an additional protective haplotype

Protein tyrosine phosphatase non-receptor type 22 (PTPN22) is the third major locus affecting risk of type I diabetes (T1D), after HLA-DR/DQ and INS. The most associated single-nucleotide polymorphism (SNP), rs2476601, has a C->T variant and results in an arginine (R) to tryptophan (W) amino acid change at position 620. To assess whether this, or other specific variants, are responsible for T1D risk, the Type I Diabetes Genetics Consortium analyzed 28 PTPN22 SNPs in 2295 affected sib-pair (ASP) families. Transmission Disequilibrium Test analyses of haplotypes revealed that all three haplotypes with a T allele at rs2476601 were overtransmitted to affected children, and two of these three haplotypes showed statistically significant overtransmission (P=0.003 to P=5.9E-12). Another haplotype had decreased transmission to affected children (P=3.5E-05). All haplotypes containing the rs2476601 T allele were identical for all SNPs across PTPN22 and only varied at centromeric SNPs. When considering rs2476601 'C' founder chromosomes, a second haplotype (AGGGGC) centromeric of PTPN22 in the C1orf178 region was associated with protection from T1D (odds ratio=0.81, P=0.0005). This novel finding requires replication in independent populations. We conclude the major association of PTPN22 with T1D is likely due to the recognized non-synonymous SNP rs2476601 (R620W).

Allelic variants in the PHTF1-PTPN22, C12orf30 and CD226 regions as candidate susceptibility factors for the type 1 diabetes in the Estonian population

BACKGROUND

Type 1 diabetes is a multifactorial disease with a strong genetic component. The aim of the study was to assess the impact of single nucleotide polymorphisms (SNPs) in several genes as susceptible markers in the risk of type 1 diabetes in the Estonian population.

METHODS

The rs6679677 (1p13), rs17696736 (12q24) and rs763361 (18q22) were genotyped in a total of 230 controls and 154 type 1 diabetes patients of Estonian origin.

RESULTS

The rs6679677 A (OR = 2.13, 95%CI = 1.48-3.08, p = 0.00001), rs17696736 G (OR = 1.53, 95%CI = 1.14-2.04, p = 0.0046) and rs763361 T (OR = 1.48, 95%CI = 1.11-1.98, p = 0.0084) alleles were associated with risk of type 1 diabetes.

CONCLUSIONS

The current study supports the rs6679677 (PHTF1-PTPN22), rs17696736 (C12orf30) and rs763361 (CD226) SNPs as susceptibility factors for type 1 diabetes outside the major histocompatibility region (MHC) region. The full study had 80% or above to detect an odds ratio of 1.8 under the assumption of an additive model at type 1 error rate, alpha = 0.05.

Influence of microbial environment on autoimmunity

During protective immune responses, the adaptive arm of the immune system requires activation by signals provided by innate immunity and driven by microbial stimuli. Whether the same rules apply to autoimmune diseases involving clonal self-reactive T and B lymphocytes--a process referred to here as 'adaptive autoimmunity'--is not quite clear. Nevertheless, in these diseases, the innate-adaptive connection is likely to be influenced by the microbial environment. This review integrates the results of experiments analyzing autoimmunity in sterile versus nonsterile conditions and experiments testing the role of innate immune receptor signaling in autoimmunity. It proposes that autoimmune diseases can be divided into two groups, the pathogenesis of which either follows the rules of innate-adaptive connection or does not.

Analysis of 19 genes for association with type I diabetes in the Type I Diabetes Genetics Consortium families

In recent years the pace of discovery of genetic associations with type I diabetes (T1D) has accelerated, with the total number of confirmed loci, including the major histocompatibility complex (MHC) region, reaching 43. However, much of the deciphering of the associations at these, and the established T1D loci, has yet to be performed in sufficient numbers of samples or with sufficient markers. Here, 257 single-nucleotide polymorphisms (SNPs) have been genotyped in 19 candidate genes (INS, PTPN22, IL2RA, CTLA4, IFIH1, SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21, CAPSL, Q7Z4c4(5Q), FOXP3, EFHB) in 2300 affected sib-pair families and tested for association with T1D as part of the Type I Diabetes Genetics Consortium's candidate gene study. The study had approximately 80% power at alpha=0.002 and a minor allele frequency of 0.2 to detect an effect with a relative risk (RR) of 1.20, which drops to just 40% power for a RR of 1.15. At the INS gene, rs689 (-23 HphI) was the most associated SNP (P=3.8 x 10(-31)), with the estimated RR=0.57 (95% confidence interval, 0.52-0.63). In addition, rs689 was associated with age-at-diagnosis of T1D (P=0.001), with homozygosity for the T1D protective T allele, delaying the onset of T1D by approximately 2 years in these families. At PTPN22, rs2476601 (R620W), in agreement with previous reports, was the most significantly associated SNP (P=6.9 x 10(-17)), with RR=1.55 (1.40-1.72). Evidence for association with T1D was observed for the IFIH1 SNP, rs1990760 (P=7.0 x 10(-4)), with RR=0.88 (0.82-0.95) and the CTLA4 SNP rs1427676 (P=0.0005), with RR=1.14 (1.06-1.23). In contrast, no convincing evidence of association was obtained for SUMO4, VDR, PAX4, OAS1, IRS1, IL4, IL4R, IL13, IL12B, CEACAM21 or CAPSL gene regions (http://www.T1DBase.org).

No association of multiple type 2 diabetes loci with type 1 diabetes

AIMS/HYPOTHESIS

We used recently confirmed type 2 diabetes gene regions to investigate the genetic relationship between type 1 and type 2 diabetes, in an average of 7,606 type 1 diabetic individuals and 8,218 controls, providing >80% power to detect effects as small as an OR of 1.11 at a false-positive rate of 0.003.

METHODS

The single nucleotide polymorphisms (SNPs) with the most convincing evidence of association in 12 type 2 diabetes-associated gene regions, PPARG, CDKAL1, HNF1B, WFS1, SLC30A8, CDKN2A-CDKN2B, IGF2BP2, KCNJ11, TCF7L2, FTO, HHEX-IDE and THADA, were analysed in type 1 diabetes cases and controls. PPARG and HHEX-IDE were additionally tested for association in 3,851 type 1 diabetes families. Tests for interaction with HLA class II genotypes, autoantibody status, sex, and age-at-diagnosis of type 1 diabetes were performed with all 12 gene regions.

RESULTS

Only PPARG and HHEX-IDE showed any evidence of association with type 1 diabetes cases and controls (p = 0.004 and p = 0.003, respectively; p > 0.05 for other SNPs). The potential association of PPARG was supported by family analyses (p = 0.003; p (combined) = 1.0 x 10(-4)). No SNPs showed evidence of interaction with any covariate (p > 0.05).

CONCLUSIONS/INTERPRETATION

We found no convincing genetic link between type 1 and type 2 diabetes. An association of PPARG (rs1801282/Pro12Ala) could be consistent with its known function in inflammation. Hence, our results reinforce evidence suggesting that type 1 diabetes is a disease of the immune system, rather than being due to inherited defects in beta cell function or regeneration or insulin resistance.

Expression profiling of human genetic and protein interaction networks in type 1 diabetes

Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have previously identified sets of genes, likely to represent distinct cellular pathways involved in T1D risk. Here we evaluate the candidate genes involved in these putative interaction networks not only at the single gene level, but also in the context of the networks of which they form an integral part. mRNA expression levels for each gene were evaluated and profiling was performed by measuring and comparing constitutive expression in human islets versus cytokine-stimulated expression levels, and for lymphocytes by comparing expression levels among controls and T1D individuals. We identified differential regulation of several genes. In one of the networks four out of nine genes showed significant down regulation in human pancreatic islets after cytokine exposure supporting our prediction that the interaction network as a whole is a risk factor. In addition, we measured the enrichment of T1D associated SNPs in each of the four interaction networks to evaluate evidence of significant association at network level. This method provided additional support, in an independent data set, that two of the interaction networks could be involved in T1D and highlights the following processes as risk factors: oxidative stress, regulation of transcription and apoptosis. To understand biological systems, integration of genetic and functional information is necessary, and the current study has used this approach to improve understanding of T1D and the underlying biological mechanisms.

Genetics of type 1 diabetes and autoimmune thyroid disease

The search for the susceptibility alleles for the complex genetic conditions of type 1 diabetes and autoimmune thyroid diseases has gained momentum in recent years. Studies have revealed several novel disease susceptibility alleles of relevance to both conditions, which brings the total number of genetic variants contributing to type 1 diabetes to ten. Additional genetic loci remain to be discovered, particularly in the autoimmune thyroid diseases. In the future, the density and coverage of single nucleotide polymorphisms available for high throughput genotyping will improve, and detailed analysis of the role of copy number variants in these diseases will shed new light on the pathogenesis of these common endocrinopathies.

Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes

Type 1 diabetes (T1D) is a common autoimmune disorder that arises from the action of multiple genetic and environmental risk factors. We report the findings of a genome-wide association study of T1D, combined in a meta-analysis with two previously published studies. The total sample set included 7,514 cases and 9,045 reference samples. Forty-one distinct genomic locations provided evidence for association with T1D in the meta-analysis (P < 10(-6)). After excluding previously reported associations, we further tested 27 regions in an independent set of 4,267 cases, 4,463 controls and 2,319 affected sib-pair (ASP) families. Of these, 18 regions were replicated (P < 0.01; overall P < 5 × 10(-8)) and 4 additional regions provided nominal evidence of replication (P < 0.05). The many new candidate genes suggested by these results include IL10, IL19, IL20, GLIS3, CD69 and IL27.

IL-2 and its high-affinity receptor: genetic control of immunoregulation and autoimmunity

Type 1 diabetes (T1D) is an organ-specific autoimmune disease featured by destruction of the insulin producing beta-cells of the pancreas by autoreactive T-lymphocytes. Putative environmental triggers conspire with a constellation of genetic elements scattered throughout the genome to elicit a multifactorial autoimmune response involving virtually every cell type of the immune system against pancreatic beta-cells. Recent highly powered genome-wide association studies have confirmed and identified fifteen chromosomal regions harboring several candidate T1D-associated gene loci. Here, we summarize what we know about the genetics of T1D with an emphasis on the contributions of mouse Il2 and human IL2RA polymorphisms and the IL-2-IL-2R pathway to autoimmunity and, more specifically, Treg development and function.

Genome-wide association studies in type 2 diabetes

Despite numerous candidate gene and linkage studies, the field of type 2 diabetes (T2D) genetics had until recently succeeded in identifying few genuine disease-susceptibility loci. The advent of genome-wide association (GWA) scans has transformed the situation, leading to an expansion in the number of established, robustly replicating T2D loci to almost 20. These novel findings offer unique insights into the pathogenesis of T2D and in the main point toward the etiologic importance of disorders of beta-cell development and function. All associated variants have common allele frequencies in the discovery populations, and exert modest to small effects on the risk of disease, characteristics that limit their prognostic and diagnostic potential. However, ongoing studies focusing on the role of copy number variation and targeting low-frequency polymorphisms should identify additional T2D susceptibility loci, some of which may have larger effect sizes and offer better individual prediction of disease risk.

Mannose binding lectin gene polymorphisms and associated auto-immune diseases in type 1 diabetes Brazilian patients

In our study we investigated the possible role of MBL2 functional single nucleotide polymorphisms (SNPs) in the augmented susceptibility to develop other autoimmune diseases in presence of type 1 diabetes (T1D) in a group of Brazilian patients. Patients were stratified for the presence of autoimmune diseases known to be associated with T1D, such as autoimmune thyroid disease (AITD) and celiac disease (CD), and compared with healthy controls (HC). Our findings suggest that MBL2 functional SNPs are more closely related to AITD than to T1D, being MBL2 SNPs frequencies in T1D patients not affected by AITD comparable to the HC ones, while significantly different between AITD patients and patients not affected by the disease. Thus, the association between MBL2 polymorphisms and T1D that we previously reported, seems to result from the stronger association of MBL2 SNPs with another autoimmune disease, the AITD, frequently associated with T1D.

IL2RA genetic heterogeneity in multiple sclerosis and type 1 diabetes susceptibility and soluble interleukin-2 receptor production

Multiple sclerosis (MS) and type 1 diabetes (T1D) are organ-specific autoimmune disorders with significant heritability, part of which is conferred by shared alleles. For decades, the Human Leukocyte Antigen (HLA) complex was the only known susceptibility locus for both T1D and MS, but loci outside the HLA complex harboring risk alleles have been discovered and fully replicated. A genome-wide association scan for MS risk genes and candidate gene association studies have previously described the IL2RA gene region as a shared autoimmune locus. In order to investigate whether autoimmunity risk at IL2RA was due to distinct or shared alleles, we performed a genetic association study of three IL2RA variants in a DNA collection of up to 9,407 healthy controls, 2,420 MS, and 6,425 T1D subjects as well as 1,303 MS parent/child trios. Here, we report "allelic heterogeneity" at the IL2RA region between MS and T1D. We observe an allele associated with susceptibility to one disease and risk to the other, an allele that confers susceptibility to both diseases, and an allele that may only confer susceptibility to T1D. In addition, we tested the levels of soluble interleukin-2 receptor (sIL-2RA) in the serum from up to 69 healthy control subjects, 285 MS, and 1,317 T1D subjects. We demonstrate that multiple variants independently correlate with sIL-2RA levels.

Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci

We carried out a meta-analysis of data from three genome-wide association (GWA) studies of type 1 diabetes (T1D), testing 305,090 SNPs in 3,561 T1D cases and 4,646 controls of European ancestry. We obtained further support for 4q27 (IL2-IL21, P = 1.9 x 10(-8)) and, after genotyping an additional 6,225 cases, 6,946 controls and 2,828 families, convincing evidence for four previously unknown and distinct risk loci in chromosome regions 6q15 (BACH2, P = 4.7 x 10(-12)), 10p15 (PRKCQ, P = 3.7 x 10(-9)), 15q24 (CTSH, P = 3.2 x 10(-15)) and 22q13 (C1QTNF6, P = 2.0 x 10(-8)).

Worldwide population differentiation at disease-associated SNPs

BACKGROUND

Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).

METHODS

We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.

RESULTS

On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.

CONCLUSION

Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.

Gene-gene interactions in the NOD mouse model of type 1 diabetes

Human genome wide association studies (GWAS) have recently identified at least four new, non-MHC-linked candidate genes or gene regions causing type one diabetes (T1D), highlighting the need for functional models to investigate how susceptibility alleles at multiple common genes interact to mediate disease. Progress in localizing genes in congenic strains of the nonobese diabetic (NOD) mouse has allowed the reproducible testing of gene functions and gene-gene interactions that can be reflected biologically as intrapathway interactions, for example, IL-2 and its receptor CD25, pathway-pathway interactions such as two signaling pathways within a cell, or cell-cell interactions. Recent studies have identified likely causal genes in two congenic intervals associated with T1D, Idd3, and Idd5, and have documented the occurrence of gene-gene interactions, including "genetic masking", involving the genes encoding the critical immune molecules IL-2 and CTLA-4. The demonstration of gene-gene interactions in congenic mouse models of T1D has major implications for the understanding of human T1D since such biological interactions are highly likely to exist for human T1D genes. Although it is difficult to detect most gene-gene interactions in a population in which susceptibility and protective alleles at many loci are randomly segregating, their existence as revealed in congenic mice reinforces the hypothesis that T1D alleles can have strong biological effects and that such genes highlight pathways to consider as targets for immune intervention.