Interleukin-2 gene variation impairs regulatory T cell function and causes autoimmunity.

Autoimmune diseases are thought to result from imbalances in normal immune physiology and regulation. Here, we show that autoimmune disease susceptibility and resistance alleles on mouse chromosome 3 (Idd3) correlate with differential expression of the key immunoregulatory cytokine interleukin-2 (IL-2). In order to test directly that an approximately twofold reduction in IL-2 underpins the Idd3-linked destabilization of immune homeostasis, we show that engineered haplodeficiency of Il2 gene expression not only reduces T cell IL-2 production by twofold but also mimics the autoimmune dysregulatory effects of the naturally occurring susceptibility alleles of Il2. Reduced IL-2 production achieved by either genetic mechanism correlates with reduced function of CD4(+) CD25(+) regulatory T cells, which are critical for maintaining immune homeostasis.

Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes.

The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P < 5 x 10(-7) between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P(follow-up)

Genome-wide analysis of allelic expression imbalance in human primary cells by high-throughput transcriptome resequencing.

Many disease-associated variants identified by genome-wide association (GWA) studies are expected to regulate gene expression. Allele-specific expression (ASE) quantifies transcription from both haplotypes using individuals heterozygous at tested SNPs. We performed deep human transcriptome-wide resequencing (RNA-seq) for ASE analysis and expression quantitative trait locus discovery. We resequenced double poly(A)-selected RNA from primary CD4(+) T cells (n = 4 individuals, both activated and untreated conditions) and developed tools for paired-end RNA-seq alignment and ASE analysis. We generated an average of 20 million uniquely mapping 45 base reads per sample. We obtained sufficient read depth to test 1371 unique transcripts for ASE. Multiple biases inflate the false discovery rate which we estimate to be approximately 50% for random SNPs. However, after controlling for these biases and considering the subset of SNPs that pass HapMap QC, 4.6% of heterozygous SNP-sample pairs show evidence of imbalance (P < 0.001). We validated four findings by both bacterial cloning and Sanger sequencing assays. We also found convincing evidence for allelic imbalance at multiple reporter exonic SNPs in CD6 for two samples heterozygous at the multiple sclerosis-associated variant rs17824933, linking GWA findings with variation in gene expression. Finally, we show in CD4(+) T cells from a further individual that high-throughput sequencing of genomic DNA and RNA-seq following enrichment for targeted gene sequences by sequence capture methods offers an unbiased means to increase the read depth for transcripts of interest, and therefore a method to investigate the regulatory role of many disease-associated genetic variants.

Nonobese diabetic congenic strain analysis of autoimmune diabetes reveals genetic complexity of the Idd18 locus and identifies Vav3 as a candidate gene.

We have used the public sequencing and annotation of the mouse genome to delimit the previously resolved type 1 diabetes (T1D) insulin-dependent diabetes (Idd)18 interval to a region on chromosome 3 that includes the immunologically relevant candidate gene, Vav3. To test the candidacy of Vav3, we developed a novel congenic strain that enabled the resolution of Idd18 to a 604-kb interval, designated Idd18.1, which contains only two annotated genes: the complete sequence of Vav3 and the last exon of the gene encoding NETRIN G1, Ntng1. Targeted sequencing of Idd18.1 in the NOD mouse strain revealed that allelic variation between NOD and C57BL/6J (B6) occurs in noncoding regions with 138 single nucleotide polymorphisms concentrated in the introns between exons 20 and 27 and immediately after the 3' untranslated region. We observed differential expression of VAV3 RNA transcripts in thymocytes when comparing congenic mouse strains with B6 or NOD alleles at Idd18.1. The T1D protection associated with B6 alleles of Idd18.1/Vav3 requires the presence of B6 protective alleles at Idd3, which are correlated with increased IL-2 production and regulatory T cell function. In the absence of B6 protective alleles at Idd3, we detected a second T1D protective B6 locus, Idd18.3, which is closely linked to, but distinct from, Idd18.1. Therefore, genetic mapping, sequencing, and gene expression evidence indicate that alteration of VAV3 expression is an etiological factor in the development of autoimmune beta-cell destruction in NOD mice. This study also demonstrates that a congenic strain mapping approach can isolate closely linked susceptibility genes.

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.

T1DBase: integration and presentation of complex data for type 1 diabetes research.

T1DBase (http://T1DBase.org) [Smink et al. (2005) Nucleic Acids Res., 33, D544-D549; Burren et al. (2004) Hum. Genomics, 1, 98-109] is a public website and database that supports the type 1 diabetes (T1D) research community. T1DBase provides a consolidated T1D-oriented view of the complex data world that now confronts medical researchers and enables scientists to navigate from information they know to information that is new to them. Overview pages for genes and markers summarize information for these elements. The Gene Dossier summarizes information for a list of genes. GBrowse [Stein et al. (2002) Genome Res., 10, 1599-1610] displays genes and other features in their genomic context, and Cytoscape [Shannon et al. (2003) Genome Res., 13, 2498-2504] shows genes in the context of interacting proteins and genes. The Beta Cell Gene Atlas shows gene expression in beta cells, islets, and related cell types and lines, and the Tissue Expression Viewer shows expression across other tissues. The Microarray Viewer shows expression from more than 20 array experiments. The Beta Cell Gene Expression Bank contains manually curated gene and pathway annotations for genes expressed in beta cells. T1DMart is a query tool for markers and genotypes. PosterPages are 'home pages' about specific topics or datasets. The key challenge, now and in the future, is to provide powerful informatics capabilities to T1D scientists in a form they can use to enhance their research.

T1DBase, a community web-based resource for type 1 diabetes research.

T1DBase (http://T1DBase.org) is a public website and database that supports the type 1 diabetes (T1D) research community. The site is currently focused on the molecular genetics and biology of T1D susceptibility and pathogenesis. It includes the following datasets: annotated genome sequence for human, rat and mouse; information on genetically identified T1D susceptibility regions in human, rat and mouse, and genetic linkage and association studies pertaining to T1D; descriptions of NOD mouse congenic strains; the Beta Cell Gene Expression Bank, which reports expression levels of genes in beta cells under various conditions, and annotations of gene function in beta cells; data on gene expression in a variety of tissues and organs; and biological pathways from KEGG and BioCarta. Tools on the site include the GBrowse genome browser, site-wide context dependent search, Connect-the-Dots for connecting gene and other identifiers from multiple data sources, Cytoscape for visualizing and analyzing biological networks, and the GESTALT workbench for genome annotation. All data are open access and all software is open source.

Discovery, linkage disequilibrium and association analyses of polymorphisms of the immune complement inhibitor, decay-accelerating factor gene (DAF/CD55) in type 1 diabetes.

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.

Polymorphism discovery and association analyses of the interferon genes in type 1 diabetes.

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.

Remapping the insulin gene/IDDM2 locus in type 1 diabetes.

Type 1 diabetes susceptibility at the IDDM2 locus was previously mapped to a variable number tandem repeat (VNTR) 5' of the insulin gene (INS). However, the observation of associated markers outside a 4.1-kb interval, previously considered to define the limits of IDDM2 association, raised the possibility that the VNTR association might result from linkage disequilibrium (LD) with an unknown polymorphism. We therefore identified a total of 177 polymorphisms and obtained genotypes for 75 of these in up to 434 pedigrees. We found that, whereas disease susceptibility did map to within the 4.1-kb region, there were two equally likely candidates for the causal variant, -23HphI and +1140A/C, in addition to the VNTR. Further analyses in 2,960 pedigrees did not support the difference in association between VNTR lineages that had previously enabled the exclusion of these two polymorphisms. Therefore, we were unable to rule out -23HphI and +1140A/C having an etiological effect. Our mapping results using robust regression methods show how precisely a variant for a common disease can be mapped, even within a region of strong LD, and specifically that IDDM2 maps to one or more of three common variants in a approximately 2-kb region of chromosome 11p15.

Natural genetic variants influencing type 1 diabetes in humans and in the NOD mouse.

The understanding of the genetic basis of type 1 diabetes and other autoimmune diseases and the application of that knowledge to their treatment, cure and eventual prevention has been a difficult goal to reach. Cumulative progress in both mouse and human are finally giving way to some successes and significant insights have been made in the last few years. Investigators have identified key immune tolerance-associated phenotypes in convincingly reliable ways that are regulated by specific diabetes-associated chromosomal intervals. The combination of positional genetics and functional studies is a powerful approach to the identification of downstream molecular events that are causal in disease aetiology. In the case of type 1 diabetes, the availability of several animal models, especially the NOD mouse, has complemented the efforts to localize human genes causing diabetes and has shown that some of the same genes and pathways are associated with autoimmunity in both species. There is also growing evidence that the initiation or progression of many autoimmune diseases is likely to be influenced by some of the same genes.

Cell-specific protein phenotypes for the autoimmune locus IL2RA using a genotype-selectable human bioresource.

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.

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)).

Resequencing and association analysis of the SP110 gene in adult pulmonary tuberculosis.

Recently, the Intracellular pathogen resistance 1 (Ipr1) gene was shown to control susceptibility to Mycobacterium tuberculosis in mice. We examined whether common sequence variants of its human orthologue, the SP110 gene, are associated with susceptibility to tuberculosis in a human population. We resequenced SP110 exons in 96 individuals and identified new polymorphisms. Then, we combined our sequence and HapMap data for 83 distinct polymorphisms and selected tags that capture information for all common variants in the 100 kb region around SP110. We genotyped 29 single nucleotide polymorphisms including seven amino-acid changing variants in 1,912 HIV-negative culture-confirmed adult pulmonary tuberculosis patients and 2,104 adult healthy controls from Russia and found no evidence of association. Our results indicate that common polymorphisms of the SP110 gene have no major effect on susceptibility to tuberculosis in this population.

Type 1 diabetes genes and pathways shared by humans and NOD mice.

The identification of causative genes for the autoimmune disease type 1 diabetes (T1D) in humans and candidate genes in the NOD mouse has made significant progress in recent years. In addition to sharing structural aspects of the MHC class II molecules that confer susceptibility or resistance to T1D, genes and pathways contributing to autoimmune pathogenesis are held in common by the two species. There are data demonstrating a similar need to establish central tolerance to insulin. Gene variants for the interacting molecules IL2 and CD25, members of a pathway that is essential for immune homeostasis, are present in mice and humans, respectively. Variation of two molecules that negatively regulate T cells, CTLA-4 and the tyrosine phosphatase LYP/PEP, are associated with susceptibility to human and NOD T1D. These observations underscore the value of the NOD mouse model for mechanistic studies on human T1D-associated molecular and cellular pathways.

Development of an integrated genome informatics, data management and workflow infrastructure: a toolbox for the study of complex disease genetics.

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.

Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease.

Genes and mechanisms involved in common complex diseases, such as the autoimmune disorders that affect approximately 5% of the population, remain obscure. Here we identify polymorphisms of the cytotoxic T lymphocyte antigen 4 gene (CTLA4)--which encodes a vital negative regulatory molecule of the immune system--as candidates for primary determinants of risk of the common autoimmune disorders Graves' disease, autoimmune hypothyroidism and type 1 diabetes. In humans, disease susceptibility was mapped to a non-coding 6.1 kb 3' region of CTLA4, the common allelic variation of which was correlated with lower messenger RNA levels of the soluble alternative splice form of CTLA4. In the mouse model of type 1 diabetes, susceptibility was also associated with variation in CTLA-4 gene splicing with reduced production of a splice form encoding a molecule lacking the CD80/CD86 ligand-binding domain. Genetic mapping of variants conferring a small disease risk can identify pathways in complex disorders, as exemplified by our discovery of inherited, quantitative alterations of CTLA4 contributing to autoimmune tissue destruction.