Search

Abstract The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D), chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC) and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

To the Editor: Copy number variants (CNVs) are duplicated or deleted segments of the genome that vary in size from a few bases to several kilobases and comprise a substantial [...]

This study investigates whether non-HLA loci are shared by type 1 diabetes and celiac disease, which have a common genetic origin. The results indicate that both type 1 diabetes and celiac disease share common alleles, and might exhibit common biological mechanisms.

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as [...]

Author(s): The Wellcome Trust Case Control Consortium; Management Committee; Paul R. Burton [1]; David G. Clayton [2]; Lon R. Cardon [3]; Nick Craddock [4]; Panos Deloukas [5]; Audrey Duncanson [6]; [...]

Background Interleukin-2 (IL-2) has an essential role in the expansion and function of CD4.sup.+ regulatory T cells (Tregs). Tregs reduce tissue damage by limiting the immune response following infection and regulate autoreactive CD4.sup.+ effector T cells (Teffs) to prevent autoimmune diseases, such as type 1 diabetes (T1D). Genetic susceptibility to T1D causes alterations in the IL-2 pathway, a finding that supports Tregs as a cellular therapeutic target. Aldesleukin (Proleukin; recombinant human IL-2), which is administered at high doses to activate the immune system in cancer immunotherapy, is now being repositioned to treat inflammatory and autoimmune disorders at lower doses by targeting Tregs. Methods and Findings To define the aldesleukin dose response for Tregs and to find doses that increase Tregs physiologically for treatment of T1D, a statistical and systematic approach was taken by analysing the pharmacokinetics and pharmacodynamics of single doses of subcutaneous aldesleukin in the Adaptive Study of IL-2 Dose on Regulatory T Cells in Type 1 Diabetes (DILT1D), a single centre, non-randomised, open label, adaptive dose-finding trial with 40 adult participants with recently diagnosed T1D. The primary endpoint was the maximum percentage increase in Tregs (defined as CD3.sup.+ CD4.sup.+ CD25.sup.high CD127.sup.low) from the baseline frequency in each participant measured over the 7 d following treatment. There was an initial learning phase with five pairs of participants, each pair receiving one of five pre-assigned single doses from 0.04 x 10.sup.6 to 1.5 x 10.sup.6 IU/m.sup.2, in order to model the dose-response curve. Results from each participant were then incorporated into interim statistical modelling to target the two doses most likely to induce 10% and 20% increases in Treg frequencies. Primary analysis of the evaluable population (n = 39) found that the optimal doses of aldesleukin to induce 10% and 20% increases in Tregs were 0.101 x 10.sup.6 IU/m.sup.2 (standard error [SE] = 0.078, 95% CI = -0.052, 0.254) and 0.497 x 10.sup.6 IU/m.sup.2 (SE = 0.092, 95% CI = 0.316, 0.678), respectively. On analysis of secondary outcomes, using a highly sensitive IL-2 assay, the observed plasma concentrations of the drug at 90 min exceeded the hypothetical Treg-specific therapeutic window determined in vitro (0.015-0.24 IU/ml), even at the lowest doses (0.040 x 10.sup.6 and 0.045 x 10.sup.6 IU/m.sup.2) administered. A rapid decrease in Treg frequency in the circulation was observed at 90 min and at day 1, which was dose dependent (mean decrease 11.6%, SE = 2.3%, range 10.0%-48.2%, n = 37), rebounding at day 2 and increasing to frequencies above baseline over 7 d. Teffs, natural killer cells, and eosinophils also responded, with their frequencies rapidly and dose-dependently decreased in the blood, then returning to, or exceeding, pretreatment levels. Furthermore, there was a dose-dependent down modulation of one of the two signalling subunits of the IL-2 receptor, the [beta] chain (CD122) (mean decrease = 58.0%, SE = 2.8%, range 9.8%-85.5%, n = 33), on Tregs and a reduction in their sensitivity to aldesleukin at 90 min and day 1 and 2 post-treatment. Due to blood volume requirements as well as ethical and practical considerations, the study was limited to adults and to analysis of peripheral blood only. Conclusions The DILT1D trial results, most notably the early altered trafficking and desensitisation of Tregs induced by a single ultra-low dose of aldesleukin that resolves within 2-3 d, inform the design of the next trial to determine a repeat dosing regimen aimed at establishing a steady-state Treg frequency increase of 20%-50%, with the eventual goal of preventing T1D. Trial Registration ISRCTN Registry ISRCTN27852285; ClinicalTrials.gov NCT01827735, Author(s): John A. Todd 1,*, Marina Evangelou 2, Antony J. Cutler 1, Marcin L. Pekalski 1, Neil M. Walker 1, Helen E. Stevens 1, Linsey Porter 1, Deborah J. Smyth [...]

Abstract Background Linkage and congenic strain analyses using the nonobese diabetic (NOD) mouse as a model for human type 1 autoimmune diabetes (T1D) have identified several NOD mouse Idd (insulin dependent diabetes) loci, including Slc11a1 (formerly known as Nramp1). Genetic variants in the orthologous region encompassing SLC11A1 in human chromosome 2q35 have been reported to be associated with various immune-related diseases including T1D. Here, we have conducted association analysis of this candidate gene region, and then investigated potential correlations between the most T1D-associated variant and RNA expression of the SLC11A1 gene and its splice isoform. Methods Nine SNPs (rs2276631, rs2279015, rs1809231, rs1059823, rs17235409 (D543N), rs17235416 (3'UTR), rs3731865 (INT4), rs7573065 (-237 C→T) and rs4674297) were genotyped using TaqMan genotyping assays and the polymorphic promoter microsatellite (GT)n was genotyped using PCR and fragment length analysis. A maximum of 8,863 T1D British cases and 10,841 British controls, all of white European descent, were used to test association using logistic regression. A maximum of 5,696 T1D families were also tested for association using the transmission/disequilibrium test (TDT). We considered P ≤ 0.005 as evidence of association given that we tested nine variants in total. Upon identification of the most T1D-associated variant, we investigated the correlation between its genotype and SLC11A1 expression overall or with splice isoform ratio using 42 PAXgene whole blood samples from healthy donors by quantitative PCR (qPCR). Results Using the case-control collection, rs3731865 (INT4) was identified to be the variant most associated with T1D (P = 1.55 × 10-6). There was also some evidence of association at rs4674297 (P = 1.57 × 10-4). No evidence of disease association was obtained at any of the loci using the family collections (PTDT ≥ 0.13). We also did not observe a correlation between rs3731865 genotypes and SLC11A1 expression overall or with splice isoform expression. Conclusion We conclude that rs3731685 (INT4) in the SLC11A1 gene may be associated with T1D susceptibility in the European ancestry population studied. We did not observe a difference in SLC11A1 expression at the RNA level based on the genotypes of rs3731865 in whole blood samples. However, a potential correlation cannot be ruled out in purified cell subsets especially monocytes or macrophages.

Abstract Background As genes associated with immune-mediated diseases have an increased prior probability of being associated with other immune-mediated diseases, we tested three such genes, IL23R, IRF5 and CD40, for an association with type 1 diabetes. In addition, we tested seven genes, TAF5L, PDCD1, TCF7, IL12B, IL6, ICAM1 and TBX21, with published marginal or inconsistent evidence of an association with type 1 diabetes. Methods We genotyped reported polymorphisms of the ten genes, nonsynonymous SNPs (nsSNPs) and, for the IL12B and IL6 regions, tag SNPs in up to 7,888 case, 8,858 control and 3,142 parent-child trio samples. In addition, we analysed data from the Wellcome Trust Case Control Consortium genome-wide association study to determine whether there was any further evidence of an association in each gene region. Results We found some evidence of associations between type 1 diabetes and TAF5L, PDCD1, TCF7 and IL6 (ORs = 1.05 – 1.13; P = 0.0291 – 4.16 × 10-4). No evidence of an association was obtained for IL12B, IRF5, IL23R, ICAM1, TBX21 and CD40, although there was some evidence of an association (OR = 1.10; P = 0.0257) from the genome-wide association study for the ICAM1 region. Conclusion We failed to exclude the possibility of some effect in type 1 diabetes for TAF5L, PDCD1, TCF7, IL6 and ICAM1. Additional studies, of these and other candidate genes, employing much larger sample sizes and analysis of additional polymorphisms in each gene and its flanking region will be required to ascertain their contributions to type 1 diabetes susceptibility.

Abstract Background In an effort to locate susceptibility genes for type 1 diabetes (T1D) several genome-wide linkage scans have been undertaken. A chromosomal region designated IDDM10 retained genome-wide significance in a combined analysis of the main linkage scans. Here, we studied sequence polymorphisms in 23 Mb on chromosome 10p12-q11, including the putative IDDM10 region, to identify genes associated with T1D. Results Initially, we resequenced the functional candidate genes, CREM and SDF1, located in this region, genotyped 13 tag single nucleotide polymorphisms (SNPs) and found no association with T1D. We then undertook analysis of the whole 23 Mb region. We constructed and sequenced a contig tile path from two bacterial artificial clone libraries. By comparison with a clone library from an unrelated person used in the Human Genome Project, we identified 12,058 SNPs. We genotyped 303 SNPs and 25 polymorphic microsatellite markers in 765 multiplex T1D families and followed up 22 associated polymorphisms in up to 2,857 families. We found nominal evidence of association in six loci (P = 0.05 – 0.0026), located near the PAPD1 gene. Therefore, we resequenced 38.8 kb in this region, found 147 SNPs and genotyped 84 of them in the T1D families. We also tested 13 polymorphisms in the PAPD1 gene and in five other loci in 1,612 T1D patients and 1,828 controls from the UK. Overall, only the D10S193 microsatellite marker located 28 kb downstream of PAPD1 showed nominal evidence of association in both T1D families and in the case-control sample (P = 0.037 and 0.03, respectively). Conclusion We conclude that polymorphisms in the CREM and SDF1 genes have no major effect on T1D. The weak T1D association that we detected in the association scan near the PAPD1 gene may be either false or due to a small genuine effect, and cannot explain linkage at the IDDM10 region.

Abstract Background Type 1 diabetes (T1D) is a common autoimmune disease resulting from T-cell mediated destruction of pancreatic beta cells. Decay accelerating factor (DAF, CD55), a glycosylphosphatidylinositol-anchored membrane protein, is a candidate for autoimmune disease susceptibility based on its role in restricting complement activation and evidence that DAF expression modulates the phenotype of mice models for autoimmune disease. In this study, we adopt a linkage disequilibrium (LD) mapping approach to test for an association between the DAF gene and T1D. Results Initially, we used HapMap II genotype data to examine LD across the DAF region. Additional resequencing was required, identifying 16 novel polymorphisms. Combining both datasets, a LD mapping approach was adopted to test for association with T1D. Seven tag SNPs were selected and genotyped in case-control (3,523 cases and 3,817 controls) and family (725 families) collections. Conclusion We obtained no evidence of association between T1D and the DAF region in two independent collections. In addition, we assessed the impact of using only HapMap II genotypes for the selection of tag SNPs and, based on this study, found that HapMap II genotypes may require additional SNP discovery for comprehensive LD mapping of some genes in common disease.

Abstract Background The identification of the HLA class II, insulin (INS), CTLA-4 and PTPN22 genes as determinants of type 1 diabetes (T1D) susceptibility indicates that fine tuning of the immune system is centrally involved in disease development. Some genes have been shown to affect several immune-mediated diseases. Therefore, we tested the hypothesis that alleles of susceptibility genes previously associated with other immune-mediated diseases might perturb immune homeostasis, and hence also associate with predisposition to T1D. Methods We resequenced and genotyped tag single nucleotide polymorphisms (SNPs) from two genes, CRP and FCER1B, and genotyped 27 disease-associated polymorphisms from thirteen gene regions, namely FCRL3, CFH, SLC9A3R1, PADI4, RUNX1, SPINK5, IL1RN, IL1RA, CARD15, IBD5-locus (including SLC22A4), LAG3, ADAM33 and NFKB1. These genes have been associated previously with susceptibility to a range of immune-mediated diseases including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Graves' disease (GD), psoriasis, psoriatic arthritis (PA), atopy, asthma, Crohn disease and multiple sclerosis (MS). Our T1D collections are divided into three sample subsets, consisting of set 1 families (up to 754 families), set 2 families (up to 743 families), and a case-control collection (ranging from 1,500 to 4,400 cases and 1,500 to 4,600 controls). Each SNP was genotyped in one or more of these subsets. Our study typically had approximately 80% statistical power for a minor allele frequency (MAF) >5% and odds ratios (OR) of 1.5 with the type 1 error rate, α = 0.05. Results We found no evidence of association with T1D at most of the loci studied 0.02

Abstract Background The aetiology of the autoimmune disease type 1 diabetes (T1D) involves many genetic and environmental factors. Evidence suggests that innate immune responses, including the action of interferons, may also play a role in the initiation and/or pathogenic process of autoimmunity. In the present report, we have adopted a linkage disequilibrium (LD) mapping approach to test for an association between T1D and three regions encompassing 13 interferon alpha (IFNA) genes, interferon omega-1 (IFNW1), interferon beta-1 (IFNB1), interferon gamma (IFNG) and the interferon consensus-sequence binding protein 1 (ICSBP1). Results We identified 238 variants, most, single nucleotide polymorphisms (SNPs), by sequencing IFNA, IFNB1, IFNW1 and ICSBP1, 98 of which where novel when compared to dbSNP build 124. We used polymorphisms identified in the SeattleSNP database for INFG. A set of tag SNPs was selected for each of the interferon and interferon-related genes to test for an association between T1D and this complex gene family. A total of 45 tag SNPs were selected and genotyped in a collection of 472 multiplex families. Conclusion We have developed informative sets of SNPs for the interferon and interferon related genes. No statistical evidence of a major association between T1D and any of the interferon and interferon related genes tested was found.

Abstract Background Sustainable DNA resources and reliable high-throughput genotyping methods are required for large-scale, long-term genetic association studies. In the genetic dissection of common disease it is now recognised that thousands of samples and hundreds of thousands of markers, mostly single nucleotide polymorphisms (SNPs), will have to be analysed. In order to achieve these aims, both an ability to boost quantities of archived DNA and to genotype at low costs are highly desirable. We have investigated Φ29 polymerase Multiple Displacement Amplification (MDA)-generated DNA product (MDA product), in combination with highly multiplexed BeadArray™ genotyping technology. As part of a large-scale BeadArray genotyping experiment we made a direct comparison of genotyping data generated from MDA product with that from genomic DNA (gDNA) templates. Results Eighty-six MDA product and the corresponding 86 gDNA samples were genotyped at 345 SNPs and a concordance rate of 98.8% was achieved. The BeadArray sample exclusion rate, blind to sample type, was 10.5% for MDA product compared to 5.8% for gDNA. Conclusions We conclude that the BeadArray technology successfully produces high quality genotyping data from MDA product. The combination of these technologies improves the feasibility and efficiency of mapping common disease susceptibility genes despite limited stocks of gDNA samples.

Aims/hypothesis: The genetic risk of type 1 diabetes has been extensively studied. However, the genetic determinants of age at diagnosis (AAD) of type 1 diabetes remain relatively unexplained. Identification of AAD genes and pathways could provide insight into the earliest events in the disease process. Methods: Using ImmunoChip data from 15,696 cases, we aimed to identify regions in the genome associated with AAD. Results: Two regions were convincingly associated with AAD ( p < 5 × 10): the MHC on 6p21, and 6q22.33. Fine-mapping of 6q22.33 identified two AAD-associated haplotypes in the region nearest to the genes encoding protein tyrosine phosphatase receptor kappa ( PTPRK) and thymocyte-expressed molecule involved in selection ( THEMIS). We examined the susceptibility to type 1 diabetes at these SNPs by performing a meta-analysis including 19,510 control participants. Although these SNPs were not associated with type 1 diabetes overall ( p > 0.001), the SNP most associated with AAD, rs72975913, was associated with susceptibility to type 1 diabetes in those individuals diagnosed at less than 5 years old ( p = 2.3 × 10). Conclusion/interpretation: PTPRK and its neighbour THEMIS are required for early development of the thymus, which we can assume influences the initiation of autoimmunity. Non-HLA genes may only be detectable as risk factors for the disease in individuals diagnosed under the age 5 years because, after that period of immune development, their role in disease susceptibility has become redundant. [ABSTRACT FROM AUTHOR]

Determining whether potential causal variants for related diseases are shared can identify overlapping etiologies of multifactorial disorders. Colocalization methods disentangle shared and distinct causal variants. However, existing approaches require independent data sets. Here we extend two colocalization methods to allow for the shared-control design commonly used in comparison of genome-wide association study results across diseases. Our analysis of four autoimmune diseases-type 1 diabetes (T1D), rheumatoid arthritis, celiac disease and multiple sclerosis-identified 90 regions that were associated with at least one disease, 33 (37%) of which were associated with 2 or more disorders. Nevertheless, for 14 of these 33 shared regions, there was evidence that the causal variants differed. We identified new disease associations in 11 regions previously associated with one or more of the other 3 disorders. Four of eight T1D-specific regions contained known type 2 diabetes (T2D) candidate genes (COBL, GLIS3, RNLS and BCAR1), suggesting a shared cellular etiology. [ABSTRACT FROM AUTHOR]

Identification of candidate causal variants in regions associated with risk of common diseases is complicated by linkage disequilibrium (LD) and multiple association signals. Nonetheless, accurate maps of these variants are needed, both to fully exploit detailed cell specific chromatin annotation data to highlight disease causal mechanisms and cells, and for design of the functional studies that will ultimately be required to confirm causal mechanisms. We adapted a Bayesian evolutionary stochastic search algorithm to the fine mapping problem, and demonstrated its improved performance over conventional stepwise and regularised regression through simulation studies. We then applied it to fine map the established multiple sclerosis (MS) and type 1 diabetes (T1D) associations in the IL-2RA (CD25) gene region. For T1D, both stepwise and stochastic search approaches identified four T1D association signals, with the major effect tagged by the single nucleotide polymorphism, rs12722496. In contrast, for MS, the stochastic search found two distinct competing models: a single candidate causal variant, tagged by rs2104286 and reported previously using stepwise analysis; and a more complex model with two association signals, one of which was tagged by the major T1D associated rs12722496 and the other by rs56382813. There is low to moderate LD between rs2104286 and both rs12722496 and rs56382813 (r2 ≃ 0:3) and our two SNP model could not be recovered through a forward stepwise search after conditioning on rs2104286. Both signals in the two variant model for MS affect CD25 expression on distinct subpopulations of CD4+ T cells, which are key cells in the autoimmune process. The results support a shared causal variant for T1D and MS. Our study illustrates the benefit of using a purposely designed model search strategy for fine mapping and the advantage of combining disease and protein expression data. [ABSTRACT FROM AUTHOR]

Genetic studies of type 1 diabetes (T1D) have identified 50 susceptibility regions, finding major pathways contributing to risk, with some loci shared across immune disorders. To make genetic comparisons across autoimmune disorders as informative as possible, a dense genotyping array, the Immunochip, was developed, from which we identified four new T1D-associated regions (P < 5 × 10−8). A comparative analysis with 15 immune diseases showed that T1D is more similar genetically to other autoantibody-positive diseases, significantly most similar to juvenile idiopathic arthritis and significantly least similar to ulcerative colitis, and provided support for three additional new T1D risk loci. Using a Bayesian approach, we defined credible sets for the T1D-associated SNPs. The associated SNPs localized to enhancer sequences active in thymus, T and B cells, and CD34+ stem cells. Enhancer-promoter interactions can now be analyzed in these cell types to identify which particular genes and regulatory sequences are causal. [ABSTRACT FROM AUTHOR]

Background: A barrier to the successful development of new disease treatments is the timely recruitment of participants to experimental medicine studies that are primarily designed to investigate biological mechanisms rather than evaluate clinical efficacy. The aim of this study was to analyse the performance of three recruitment sources and the effect of publicity events during the Adaptive study of IL-2 dose on regulatory T cells in type 1 diabetes (DILT1D). Methods: The final study outcome, demography, disease duration, residence and the effect of publicity events on the performance of three recruitment sources (clinics, type 1 diabetes (T1D) disease register and the internet) were analysed from a bespoke DILT1D recruitment database. For the internet source, the origin of website hits in relation to publicity events was also evaluated. Results: A total of 735 potentially eligible participants were approached to identify the final 45 DILT1D participants. A total of 477 (64%) were identified via the disease register, but only 59 (12%) responded to contact. A total of 317 individuals registered with the DILT1D study team. Self-referral via the study website generated 170 (54%) registered individuals and was the most popular and successful source, with 88 (28%) sourced from diabetes clinics and 59 (19%) from the disease register. Of those with known T1D duration (N = 272), the internet and clinics sources identified a larger number (57, 21%) of newly diagnosed T1D (<100 days post-diagnosis) compared to the register (1, 0.4%). The internet extended the geographical reach of the study, enabling both national and international participation. Targeted website posts and promotional events from organisations supporting T1D research and treatment during the trial were essential to the success of the internet recruitment strategy. Conclusions: Analysis of the DILT1D study recruitment outcomes illustrates the utility of an active internet recruitment strategy, supported by patient groups and charities, funding agencies and sponsors, in successfully conducting an early phase study in T1D. This recruitment strategy should now be evaluated in late-stage trials to develop treatments for T1D and other diseases. [ABSTRACT FROM AUTHOR]

Introduction: CD4 T regulatory cells (Tregs) are crucial for the maintenance of self-tolerance and are deficient in many common autoimmune diseases such as type 1 diabetes (T1D). Interleukin 2 (IL-2) plays a major role in the activation and function of Tregs and treatment with ultra-low dose (ULD) IL-2 could increase Treg function to potentially halt disease progression in T1D. However, prior to embarking on large phase II/III clinical trials it is critical to develop new strategies for determining the mechanism of action of ULD IL-2 in participants with T1D. In this mechanistic study we will combine a novel trial design with a clinical grade Treg assay to identify the best doses of ULD IL-2 to induce targeted increases in Tregs. Method and analysis: Adaptive study of IL-2 dose on regulatory T cells in type 1 diabetes (DILT1D) is a single centre non-randomised, single dose, open label, adaptive dose-finding trial. The primary objective of DILT1D is to identify the best doses of IL-2 to achieve a minimal or maximal Treg increase in participants with T1D (N=40). The design has an initial learning phase where pairs of participants are assigned to five preassigned doses followed by an interim analysis to determine the two Treg targets for the reminder of the trial. This will then be followed by an adaptive phase which is fully sequential with an interim analysis after each participant is observed to determine the choice of dose based on the optimality criterion to minimise the determinant of covariance of the estimated target doses. A dose determining committee will review all data available at the interim(s) and then provide decisions regarding the choice of dose to administer to subsequent participants. Ethics and dissemination: Ethical approval for the study was granted on 18 February 2013. Results: The results of this study will be reported through peer-reviewed journals, conference presentations and an internal organisational report. Trial registration numbers: NCT01827735, ISRCTN27852285, DRN767. [ABSTRACT FROM AUTHOR]

Background Killer Immunoglobulin-like Receptors (KIRs) are surface receptors of natural killer cells that bind to their corresponding Human Leukocyte Antigen (HLA) class I ligands, making them interesting candidate genes for HLA-associated autoimmune diseases, including type 1 diabetes (T1D). However, allelic and copy number variation in the KIR region effectively mask it from standard genome-wide association studies: single nucleotide polymorphism (SNP) probes targeting the region are often discarded by standard genotype callers since they exhibit variable cluster numbers. Quantitative Polymerase Chain Reaction (qPCR) assays address this issue. However, their cost is prohibitive at the sample sizes required for detecting effects typically observed in complex genetic diseases. Results We propose a more powerful and cost-effective alternative, which combines signals from SNPs with more than three clusters found in existing datasets, with qPCR on a subset of samples. First, we showed that noise and batch effects in multiplexed qPCR assays are addressed through normalisation and simultaneous copy number calling of multiple genes. Then, we used supervised classification to impute copy numbers of specific KIR genes from SNP signals. We applied this method to assess copy number variation in two KIR genes, KIR3DL1 and KIR3DS1, which are suitable candidates for T1D susceptibility since they encode the only KIR molecules known to bind with HLA-Bw4 epitopes. We find no association between KIR3DL1/3DS1 copy number and T1D in 6744 cases and 5362 controls; a sample size twenty-fold larger than in any previous KIR association study. Due to our sample size, we can exclude odds ratios larger than 1.1 for the common KIR3DL1/3DS1 copy number groups at the 5% significance level. Conclusion We found no evidence of association of KIR3DL1/3DS1 copy number with T1D, either overall or dependent on HLA-Bw4 epitope. Five other KIR genes, KIR2DS4, KIR2DL3, KIR2DL5, KIR2DS5 and KIR2DS1, in high linkage disequilibrium with KIR3DL1 and KIR3DS1, are also unlikely to be significantly associated. Our approach could potentially be applied to other KIR genes to allow cost effective assaying of gene copy number in large samples. [ABSTRACT FROM AUTHOR]

Background: Linkage and congenic strain analyses using the nonobese diabetic (NOD) mouse as a model for human type 1 autoimmune diabetes (T1D) have identified several NOD mouse Idd (insulin dependent diabetes) loci, including Slc11a1 (formerly known as Nramp1). Genetic variants in the orthologous region encompassing SLC11A1 in human chromosome 2q35 have been reported to be associated with various immune-related diseases including T1D. Here, we have conducted association analysis of this candidate gene region, and then investigated potential correlations between the most T1D-associated variant and RNA expression of the SLC11A1 gene and its splice isoform. Methods: Nine SNPs (rs2276631, rs2279015, rs1809231, rs1059823, rs17235409 (D543N), rs17235416 (3'UTR), rs3731865 (INT4), rs7573065 (-237 C®T) and rs4674297) were genotyped using TaqMan genotyping assays and the polymorphic promoter microsatellite (GT)n was genotyped using PCR and fragment length analysis. A maximum of 8,863 T1D British cases and 10,841 British controls, all of white European descent, were used to test association using logistic regression. A maximum of 5,696 T1D families were also tested for association using the transmission/disequilibrium test (TDT). We considered P ≤ 0.005 as evidence of association given that we tested nine variants in total. Upon identification of the most T1D-associated variant, we investigated the correlation between its genotype and SLC11A1 expression overall or with splice isoform ratio using 42 PAXgene whole blood samples from healthy donors by quantitative PCR (qPCR). Results: Using the case-control collection, rs3731865 (INT4) was identified to be the variant most associated with T1D (P = 1.55 × 10-6). There was also some evidence of association at rs4674297 (P = 1.57 × 10-4). No evidence of disease association was obtained at any of the loci using the family collections (PTDT ≥ 0.13). We also did not observe a correlation between rs3731865 genotypes and SLC11A1 expression overall or with splice isoform expression. Conclusion: We conclude that rs3731685 (INT4) in the SLC11A1 gene may be associated with T1D susceptibility in the European ancestry population studied. We did not observe a difference in SLC11A1 expression at the RNA level based on the genotypes of rs3731865 in whole blood samples. However, a potential correlation cannot be ruled out in purified cell subsets especially monocytes or macrophages. [ABSTRACT FROM AUTHOR]

IFIH1 (interferon induced with helicase C domain 1), also known as MDA5 (melanoma differentiation-associated protein 5), is one of a family of intracellular proteins known to recognise viral RNA and mediate the innate immune response. IFIH1 is causal in type 1 diabetes based on the protective associations of four rare variants, where the derived alleles are predicted to reduce gene expression or function. Originally, however, T1D protection was mapped to the common IFIH1 nsSNP, rs1990760 or Thr946Ala. This common amino acid substitution does not cause a loss of function and evidence suggests the protective allele, Ala946, may mark a haplotype with reduced expression of IFIH1 in line with the protection conferred by the four rare loss of function alleles. We have performed allele specific expression analysis that supports this hypothesis: the T1D protective haplotype correlates with reduced IFIH1 transcription in interferon-b stimulated peripheral blood mononuclear cells (overall p = 0.012). In addition, we have used multiflow cytometry analysis and quantitative PCR assays to prove reduced expression of IFIH1 in individuals heterozygous for three of the T1D-associated rare alleles: a premature stop codon, rs35744605 (Glu627X) and predicted splice variants, rs35337543 (IVS8+1) and rs35732034 (IVS14+1). We also show that the nsSNP, Ile923V, does not alter pre-mRNA levels of IFIH1. These results confirm and extend the new autoimmune disease pathway of reduced IFIH1 expression and protein function protecting from T1D. [ABSTRACT FROM AUTHOR]

Genome-wide association (GWA) studies to map common disease susceptibility loci have been hugely successful, with over 300 reproducibly associated loci reported to date. However, these studies have not yet provided convincing evidence for any susceptibility locus subject to parent-of-origin effects. Using imputation to extend existing GWA datasets, we have obtained robust evidence at rs941576 for paternally inherited risk of type 1 diabetes (T1D; ratio of allelic effects for paternal versus maternal transmissions = 0.75; 95% confidence interval (CI) = 0.71–0.79). This marker is in the imprinted region of chromosome 14q32.2, which contains the functional candidate gene DLK1. Our meta-analysis also provided support at genome-wide significance for a T1D locus at chromosome 19p13.2. The highest association was at marker rs2304256 (odds ratio (OR) = 0.86; 95%CI = 0.82–0.90) in the TYK2 gene, which has previously been associated with systemic lupus erythematosus and multiple sclerosis. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have identified over 300 regions associated with more than 70 common diseases. However, identifying causal genes within an associated region remains a major challenge. One approach to resolving causal genes is through the dissection of gene-phenotype correlations. Here we use polychromatic flow cytometry to show that differences in surface expression of the human interleukin-2 (IL-2) receptor alpha (IL2RA, or CD25) protein are restricted to particular immune cell types and correlate with several haplotypes in the IL2RA region that have previously been associated with two autoimmune diseases, type 1 diabetes (T1D) and multiple sclerosis. We confirm our strongest gene-phenotype correlation at the RNA level by allele-specific expression (ASE). We also define key parameters for the design and implementation of post-GWAS gene-phenotype investigations and demonstrate the usefulness of a large bioresource of genotype-selectable normal donors from whom fresh, primary cells can be analyzed. [ABSTRACT FROM AUTHOR]