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Background Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of end stage kidney disease (ESKD) in individuals with type 1 diabetes at advanced kidney disease stage. Methods Gene-based exome array analysis of 15,449 genes in 5 large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time-to-ESKD, testing the top gene in a 6th cohort (N=2,372/1,115 events all cohorts) and replicating in two retrospective case-control studies (N=1,072 cases, 752 controls). Deep resequencing of the top associated gene in 5 cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. Results Protein coding variants in the hydroxysteroid 17-beta dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (N=4,196; p-value=3.3x10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other chronic kidney disease-associated renal pathologies. Conclusions HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across cell types. Genome-wide association studies have identified over 200 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements. Here, we applied single-nucleus assay for transposase-accessible chromatin with sequencing to profile 28,316 nuclei across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell-type-specific elements and transcription factors, and prioritized functional CAD risk variants. We identified elements in smooth muscle cell transition states (for example, fibromyocytes) and functional variants predicted to alter smooth muscle cell- and macrophage-specific regulation of MRAS (3q22) and LIPA (10q23), respectively. We further nominated key driver transcription factors such as PRDM16 and TBX2. Together, this single-nucleus atlas provides a critical step towards interpreting regulatory mechanisms across the continuum of CAD risk.

For polygenic traits, associations with genetic variants can be detected over many chromosome regions, owing to the availability oflarge sample sizes. Most variants, however, have small effects on disease risk and, therefore, unravelling the causal variants, target genes, and biology of these variants is challenging. Here, we define the Bigger or False Discovery Rate (BFDR) as the probability that either a variant is a false-positive or a randomly drawn, true-positive association exceeds it in effect size. Using the BFDR, we identified 302 previously unreported signals with larger effect associations with type 1 diabetes and autoimmune thyroid disease. Out of 239 genome-wide significant signals in both diseases, only 66 (28%) show evidence for having a large effect using the BFDR, further demonstrating how using a combination of effect size and significance, rather than significance alone, is important in identifying SNPs and candidate genes for further investigation.

We report the largest and most ancestrally diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 152 regions associated to false discovery rate < 0.01, including 36 regions associated to genome-wide significance for the first time. Credible sets of disease-associated variants are specifically enriched in immune cell accessible chromatin, particularly in CD4+ effector T cells. Colocalization with chromatin accessibility quantitative trait loci (QTL) in CD4+ T cells identified five regions where differences in T1D risk and chromatin accessibility are potentially driven by the same causal variant. Allele-specific chromatin accessibility further refined the set of putative causal variants with functional relevance in CD4+ T cells and integration of whole blood expression QTLs identified candidate T1D genes, providing high-yield targets for mechanistic follow-up. We highlight rs72938038 in BACH2 as a candidate causal T1D variant, where the T1D risk allele leads to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritise potential drug targets by integrating genetic evidence, functional genomic maps, and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D, including proposed genetic regulatory mechanisms of T1D-associated variants and genetic support for therapeutic targets for immune intervention.

Motivation: Twin studies estimate 50% of type 1 diabetes (T1D) risk is genetic. Genetic association has implicated T cells as central to the disease process. Thus, we generated chromatin accessibility profiles from CD4+ T cells isolated from 135 T1D cases and 144 controls and investigated whether (1) there are patterns of chromatin accessibility that differ from T1D patients compared to healthy controls; (2) established T1D risk variants influence chromatin accessibility. Methods: Frozen PBMCs were provided by the Type 1 Diabetes Genetics Consortium (T1DGC). CD4+ T cells were isolated using bead purification and Assay for Transposase Accessible Chromatin (ATAC-seq) was performed. ATAC-seq samples were processed using the PEPATAC pipeline and R packages edgeR and limm. Results: We tested for differences in accessibility between individuals with and without T1D adjusting for sex, age, and experimental variability. We identified 516 chromatin regions peaks with differential accessibility by T1D status (2 with increased and 514 with decreased accessibility at FDR Conclusion: These results provide hypotheses about molecular mechanisms of T1D in CD4+ T cells. Disclosure C.C. Robertson: None. W. Chen: None. S. Onengut-Gumuscu: None. P.J. Concannon: Stock/Shareholder; Self; Amgen. Other Relationship; Self; 10x Genomics. S.S. Rich: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (DK111906)

Genome-wide association studies (GWAS) have identified multiple, shared allelic associations with many autoimmune diseases. However, the pathogenic contributions of variants residing in risk loci remain unresolved. The location of the majority of shared disease-associated variants in noncoding regions suggests they contribute to risk of autoimmunity through effects on gene expression in the immune system. In the current study, we test this hypothesis by applying RNA sequencing to CD4+, CD8+, and CD19+ lymphocyte populations isolated from 81 subjects with type 1 diabetes (T1D). We characterize and compare the expression patterns across these cell types for three gene sets: all genes, the set of genes implicated in autoimmune disease risk by GWAS, and the subset of these genes specifically implicated in T1D. We performed RNA sequencing and aligned the reads to both the human reference genome and a catalog of all possible splicing events developed from the genome, thereby providing a comprehensive evaluation of the roles of gene expression and alternative splicing (AS) in autoimmunity. Autoimmune candidate genes displayed greater expression specificity in the three lymphocyte populations relative to other genes, with significantly increased levels of splicing events, particularly those predicted to have substantial effects on protein isoform structure and function (e.g., intron retention, exon skipping). The majority of single-nucleotide polymorphisms within T1D-associated loci were also associated with one or more cis-expression quantitative trait loci (cis-eQTLs) and/or splicing eQTLs. Our findings highlight a substantial, and previously underrecognized, role for AS in the pathogenesis of autoimmune disorders and particularly for T1D.

Despite finding more than 40 risk loci for type 1 diabetes (T1D), the causative variants and genes remain largely unknown. Here, we sought to identify rare deleterious variants of moderate-to-large effects contributing to T1D. We deeply sequenced 301 protein-coding genes located in 49 previously reported T1D risk loci in 70 T1D cases of European ancestry. These cases were selected from putatively high-risk families that had three or more siblings diagnosed with T1D at early ages. A cluster of rare deleterious variants in PTPN22 was identified, including two novel frameshift mutations (ss538819444 and rs371865329) and two missense variants (rs74163663 and rs56048322). Genotyping in 3,609 T1D families showed that rs56048322 was significantly associated with T1D and that this association was independent of the T1D-associated common variant rs2476601. The risk allele at rs56048322 affects splicing of PTPN22, resulting in the production of two alternative PTPN22 transcripts and a novel isoform of LYP (the protein encoded by PTPN22). This isoform competes with the wild-type LYP for binding to CSK and results in hyporesponsiveness of CD4+ T cells to antigen stimulation in T1D subjects. These findings demonstrate that in addition to common variants, rare deleterious variants in PTPN22 exist and can affect T1D risk.

Genetic studies of type 1 diabetes (T1D) have identified more than 40 risk loci, yet the causative genes in each locus is widely unknown. Here, we investigated a candidate gene in the 10q23.31 risk locus—FAD-dependent amine oxidase (RNLS). Variants in RNLS gene are associated with T1D risk in both European and African ancestry populations, indicating common genetic contributions to T1D. Currently, our understanding of the function of RNLS is very limited and primarily within the context of a few human diseases, most notably hypertension, kidney disease, cardiovascular disease, and cancer. In previous studies a positive RNLS-STAT3 feedback loop has been suggested. With consideration to these reports, and the importance of JAK-STAT signalling in immune-mediated diseases we evaluated if RNLS functions in activation of STAT3. An IFN-β time course was conducted to understand if overexpression of RNLS affects STAT3 levels and phosphorylation levels of STAT3. While we observed no difference in steady-state levels of STAT3 in cells overexpressing RNLS, we did observe increased levels of phospho-STAT3 upon IFN-β stimulation (p: 0.0051). In addition, to understand the function of RNLS in the immune system, we used RNAseq to compare transcriptomes of Jurkat cells expressing endogenous RNLS vs. ones overexpressing RNLS. RNAseq analysis identified 390 genes that were differentially expressed, by more than two-fold, of which 74.1 (289/390) of genes were up-regulated and 25.9 (101/390) were down-regulated in cells overexpressing RNLS. Tissue specific gene network analysis revealed that genes that were up-regulated mainly functioned in pathways related to chromosome segregation and cell division while genes that were down-regulated by RNLS were involved in IFN and NF-kappa B signaling pathways. Overall our results established a role for RNLS in cell-cycle related pathways and immune signaling pathways, providing new mechanistic insights of the role of RNLS in T1D. Disclosure S. Onengut-Gumuscu: None. N. Vogler: None. M. Faidas: None. R.R. Pickin: None. E. Gersz: None. S.S. Rich: None.

Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.

The aims of this study were: (i) to determine to what degree multiple sclerosis-associated loci discovered in European populations also influence susceptibility in African Americans; (ii) to assess the extent to which the unique linkage disequilibrium patterns in African Americans can contribute to localizing the functionally relevant regions or genes; and (iii) to search for novel African American multiple sclerosis-associated loci. Using the ImmunoChip custom array we genotyped 803 African American cases with multiple sclerosis and 1516 African American control subjects at 130 135 autosomal single nucleotide polymorphisms. We conducted association analysis with rigorous adjustments for population stratification and admixture. Of the 110 non-major histocompatibility complex multiple sclerosis-associated variants identified in Europeans, 96 passed stringent quality control in our African American data set and of these, >70% (69) showed over-representation of the same allele amongst cases, including 21 with nominally significant evidence for association (one-tailed test P < 0.05). At a further eight loci we found nominally significant association with an alternate correlated risk-tagging single nucleotide polymorphism from the same region. Outside the regions known to be associated in Europeans, we found seven potentially associated novel candidate multiple sclerosis variants (P < 10(-4)), one of which (rs2702180) also showed nominally significant evidence for association (one-tailed test P = 0.034) in an independent second cohort of 620 African American cases and 1565 control subjects. However, none of these novel associations reached genome-wide significance (combined P = 6.3 × 10(-5)). Our data demonstrate substantial overlap between African American and European multiple sclerosis variants, indicating common genetic contributions to multiple sclerosis risk.

Single nucleotide polymorphisms (SNPs) located in the chromosomal region 16p13.13 have been previously associated with risk for several autoimmune diseases, including type 1 diabetes. To identify and localize specific risk variants for type 1 diabetes in this region and understand the mechanism of their action, we resequenced a 455-kb region in type 1 diabetic patients and unaffected control subjects, identifying 93 novel variants. A panel of 939 SNPs that included 46 of these novel variants was genotyped in 3,070 multiplex families with type 1 diabetes. Forty-eight SNPs, all located in CLEC16A, provided a statistically significant association (P < 5.32 × 10−5) with disease, with rs34306440 being most significantly associated (P = 5.74 × 10−6). The panel of SNPs used for fine mapping was also tested for association with transcript levels for each of the four genes in the region in B lymphoblastoid cell lines. Significant associations were observed only for transcript levels of DEXI, a gene with unknown function. We examined the relationship between the odds ratio for type 1 diabetes and the magnitude of the effect of DEXI transcript levels for each SNP in the region. Among SNPs significantly associated with type 1 diabetes, the common allele conferred an increased risk for disease and corresponded to lower DEXI expression. Our results suggest that the primary mechanism by which genetic variation at CLEC16A contributes to the risk for type 1 diabetes is through reduced expression of DEXI.

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to ≤5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

To define potentially causal variants for autoimmune disease, we fine-mapped1,2 76 rheumatoid arthritis (11,475 cases, 15,870 controls)3 and type 1 diabetes loci (9,334 cases, 11,111 controls)4. After sequencing 799 1-kilobase regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We defined credible sets of ≤5 causal variants at 5 rheumatoid arthritis and 10 type 1 diabetes loci. We identified potentially causal missense variants at DNASE1L3, PTPN22, SH2B3, and TYK2, and noncoding variants at MEG3, CD28–CTLA4, and IL2RA. We also identified potential candidate causal variants at SIRPG and TNFAIP3. Using functional assays, we confirmed allele-specific protein binding and differential enhancer activity for three variants: the CD28–CTLA4 rs117701653 SNP, MEG3 rs34552516 indel, and TNFAIP3 rs35926684 indel.

Background We conducted a genome-wide association study (GWAS) of subclinical interstitial lung disease (ILD), defined as high attenuation areas (HAA) on CT, in the population-based Multi-Ethnic Study of Atherosclerosis Study. Methods We measured the percentage of high attenuation areas (HAA) in the lung fields on cardiac CT scan defined as voxels with CT attenuation values between -600 and -250 HU. Genetic analyses were performed in MESA combined across race/ethnic groups: non-Hispanic White (n = 2,434), African American (n = 2,470), Hispanic (n = 2,065) and Chinese (n = 702), as well as stratified by race/ethnicity. Results Among 7,671 participants, regions at genome-wide significance were identified for basilar peel-core ratio of HAA in FLJ35282 downstream of ANRIL (rs7852363, P = 2.1x10−9) and within introns of SNAI3-AS1 (rs140142658, P = 9.6x10−9) and D21S2088E (rs3079677, P = 2.3x10−8). Within race/ethnic groups, 18 additional loci were identified at genome-wide significance, including genes related to development (FOXP4), cell adhesion (ALCAM) and glycosylation (GNPDA2, GYPC, GFPT1 and FUT10). Among these loci, SNP rs6844387 near GNPDA2 demonstrated nominal evidence of replication in analysis of n = 1,959 participants from the Framingham Heart Study (P = 0.029). FOXP4 region SNP rs2894439 demonstrated evidence of validation in analysis of n = 228 White ILD cases from the Columbia ILD Study compared to race/ethnicity-matched controls from MESA (one-sided P = 0.007). In lung tissue from 15 adults with idiopathic pulmonary fibrosis compared to 15 adults without lung disease. ANRIL (P = 0.001), ALCAM (P = 0.03) and FOXP4 (P = 0.046) were differentially expressed. Conclusions Our results suggest novel roles for protein glycosylation and cell cycle disinhibition by long non-coding RNA in the pathogenesis of ILD. Electronic supplementary material The online version of this article (doi:10.1186/s12931-017-0581-2) contains supplementary material, which is available to authorized users.

Analysis of the ImmunoChip single nucleotide polymorphism (SNP) array in 2816 individuals, comprising the most common subtypes (oligoarticular and RF negative polyarticular) of juvenile idiopathic arthritis (JIA) and 13056 controls strengthens the evidence for association to three known JIA-risk loci (HLA, PTPN22 and PTPN2) and has identified fourteen risk loci reaching genome-wide significance (p < 5 × 10-8) for the first time. Eleven additional novel regions showed suggestive evidence for association with JIA (p < 1 × 10-6). Dense-mapping of loci along with bioinformatic analysis has refined the association to one gene for eight regions, highlighting crucial pathways, including the IL-2 pathway, in JIA disease pathogenesis. The entire ImmunoChip loci, HLA region and the top 27 loci (p < 1 × 10-6) explain an estimated 18%, 13% and 6% risk of JIA, respectively. Analysis of the ImmunoChip dataset, the largest cohort of JIA cases investigated to date, provides new insight in understanding the genetic basis for this childhood autoimmune disease.

There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P1 × 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P1 × 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected PBUHMBOX0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P1 × 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (PBUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P1 × 10(-4)) that was not explained by subgroup heterogeneity (PBUHMBOX = 0.28; 9,238 MDD cases).

OBJECTIVES: There are significant geographical differences in the prevalence and incidence of celiac disease that cannot be explained by HLA alone. More than 40 loci outside of the HLA region have been associated with celiac disease. We investigated the roles of these non-HLA genes in the development of tissue transglutaminase autoantibodies (tTGA) and celiac disease in a large international prospective cohort study. METHODS: A total of 424,788 newborns from the US and European general populations and first-degree relatives with type 1 diabetes were screened for specific HLA genotypes. Of these, 21,589 carried 1 of the 9 HLA genotypes associated with increased risk for type 1 diabetes and celiac disease; we followed 8676 of the children in a 15 y prospective follow-up study. Genotype analyses were performed on 6010 children using the Illumina ImmunoChip. Levels of tTGA were measured in serum samples using radio-ligand binding assays; diagnoses of celiac disease were made based on persistent detection of tTGA and biopsy analysis. Data were analyzed using Cox proportional hazards analyses. RESULTS: We found 54 single-nucleotide polymorphisms (SNPs) in 5 genes associated with celiac disease (TAGAP, IL18R1, RGS21, PLEK, and CCR9) in time to celiac disease analyses (10-4>P>5.8x10-6). The hazard ratios (HR) for the SNPs with the smallest P values in each region were 1.59, 1.45, 2.23, 2.64, and 1.40, respectively. Outside of regions previously associated with celiac disease, we identified 10 SNPs in 8 regions that could also be associated with the disease (P

Background Individuals with dyslipidemia often develop type 2 diabetes, and diabetic patients often have dyslipidemia. It remains to be determined whether there are genetic connections between the 2 disorders. Methods A female F2 cohort, generated from BALB/cJ (BALB) and SM/J (SM) Apoe-deficient (Apoe−/−) strains, was started on a Western diet at 6 weeks of age and maintained on the diet for 12 weeks. Fasting plasma glucose and lipid levels were measured before and after 12 weeks of Western diet. 144 genetic markers across the entire genome were used for quantitative trait locus (QTL) analysis. Results One significant QTL on chromosome 9, named Bglu17 [26.4 cM, logarithm of odds ratio (LOD): 5.4], and 3 suggestive QTLs were identified for fasting glucose levels. The suggestive QTL near the proximal end of chromosome 9 (2.4 cM, LOD: 3.12) was replicated at both time points and named Bglu16. Bglu17 coincided with a significant QTL for HDL (high-density lipoprotein) and a suggestive QTL for non-HDL cholesterol levels. Plasma glucose levels were inversely correlated with HDL but positively correlated with non-HDL cholesterol levels in F2 mice on either chow or Western diet. A significant correlation between fasting glucose and triglyceride levels was also observed on the Western diet. Haplotype analysis revealed that “lipid genes” Sik3, Apoa1, and Apoc3 were probable candidates for Bglu17. Conclusions We have identified multiple QTLs for fasting glucose and lipid levels. The colocalization of QTLs for both phenotypes and the sharing of potential candidate genes demonstrate genetic connections between dyslipidemia and type 2 diabetes. Electronic supplementary material The online version of this article (doi:10.1186/s12863-015-0292-y) contains supplementary material, which is available to authorized users.

Shared genetic architecture between phenotypes may be driven by a common genetic basis (pleiotropy) or a subset of genetically similar individuals (heterogeneity). We developed BUHMBOX, a well-powered statistical method to distinguish pleiotropy from heterogeneity using genotype data. We observed a shared genetic basis between 11 of 17 tested autoimmune diseases and type I diabetes (T1D, p0.2 using 6,670 T1D cases and 7,279 RA cases), suggesting that shared genetic features in autoimmunity are due to pleiotropy. We observed a shared genetic basis between seronegative and seropostive RA (p

Genome-wide association studies have identified associations between type 1 diabetes and single nucleotide polymorphisms (SNPs) at chromosome 12q13, surrounding the gene ERBB3. Our objective was to fine map this region to further localize causative variants. Re-sequencing identified more than 100 putative SNPs in an 80 kb region at 12q13. By genotyping 42 SNPs, spanning approximately 214 kb, in 382 affected sibling pair type 1 diabetes families, we were able to genotype or tag 67 common SNPs (MAF ≥ 0.05) identified from HapMap CEU data and CEU data from the 1000 Genomes Project, plus additional rare coding variants identified from our re-sequencing efforts. Fifteen SNPs provided nominal evidence for association (P≤ 0.05) with type 1 diabetes. The most significant associations were observed with rs2271189 (P = 4.22×10−5), located in exon 27 of the ERBB3 gene, and an intergenic SNP rs11171747 (P= 1.70×10−4). Follow-up genotyping of these SNPs in 2 740 multiplex type 1 diabetes families validated these findings. After analyzing variants spanning more than 200 kb, we have replicated associations from previous GWAS and provide evidence for novel associations with type 1 diabetes. The associations across this region could be entirely accounted for by two common SNPs, rs2271189 and rs11171747.

OBJECTIVE— The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods. RESEARCH DESIGN AND METHODS— A total of 2,496 multiplex families with type 1 diabetes were genotyped with a panel of 6,090 single nucleotide polymorphisms (SNPs). Evidence of association to disease was evaluated by the pedigree disequilibrium test. Significant results were followed up by genotyping and analyses in two independent sets of samples: 2,214 parent-affected child trio families and a panel of 7,721 case and 9,679 control subjects. RESULTS— Three of the SNPs most strongly associated with type 1 diabetes localized to previously identified type 1 diabetes risk loci: INS, IFIH1, and KIAA0350. A fourth strongly associated SNP, rs876498 (P = 1.0 × 10−4), occurred in the sixth intron of the UBASH3A locus at chromosome 21q22.3. Support for this disease association was obtained in two additional independent sample sets: families with type 1 diabetes (odds ratio [OR] 1.06 [95% CI 1.00–1.11]; P = 0.023) and case and control subjects (1.14 [1.09–1.19]; P = 7.5 × 10−8). CONCLUSIONS— The T1DGC 6K SNP scan and follow-up studies reported here confirm previously reported type 1 diabetes associations at INS, IFIH1, and KIAA0350 and identify an additional disease association on chromosome 21q22.3 in the UBASH3A locus (OR 1.10 [95% CI 1.07–1.13]; P = 4.4 × 10−12). This gene and its flanking regions are now validated targets for further resequencing, genotyping, and functional studies in type 1 diabetes.

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., Author Summary Genetic association studies have identified many DNA sequence variants that associate with disease risk. By exploiting the known correlation that exists between neighbouring variants in the genome, inference can be extended beyond those individual variants tested to identify sets within which a causal variant is likely to reside. However, this correlation, particularly in the presence of multiple disease causing variants in relative proximity, makes disentangling the specific causal variants difficult. Statistical approaches to this fine mapping problem have traditionally taken a stepwise search approach, beginning with the most associated variant in a region, then iteratively attempting to find additional associated variants. We adapted a stochastic search approach that avoids this stepwise process and is explicitly designed for dealing with highly correlated predictors to the fine mapping problem. We showed in simulated data that it outperforms its stepwise counterpart and other variable selection strategies such as the lasso. We applied our approach to understand the association of two immune-mediated diseases to a region on chromosome 10p15. We identified a model for multiple sclerosis containing two variants, neither of which was found through a stepwise search, and functionally linked both of these to the neighbouring candidate gene, IL2RA, in independent data. Our approach can be used to aid fine mapping of other disease-associated regions, which is critical for design of functional follow-up studies required to understand the mechanisms through which genetic variants influence disease.

A recent addition to the list of widely confirmed type 1 diabetes risk loci is the PTPN22 gene encoding a lymphoid-specific phosphatase (Lyp). However, evidence supporting a role for PTPN22 in type 1 diabetes derives entirely from the study of just one coding single nucleotide polymorphism, 1858C/T. In the current study, the haplotype structure of the PTPN22 region was determined, and individual haplotypes were tested for association with type 1 diabetes in family-based tests. The 1858T risk allele occurred on only a single haplotype that was strongly associated with type 1 diabetes (P = 7.9 × 10−5). After controlling for the effects of this allele, two other haplotypes were observed to be weakly associated with type 1 diabetes (P < 0.05). Sequencing of the coding region of PTPN22 on these haplotypes revealed a novel variant (2250G/C) predicted to result in a nonsynonymous amino acid substitution. Analysis of PTPN22 transcripts from a subject heterozygous for this variant indicated that it interfered with normal mRNA splicing, resulting in a premature termination codon after exon 17. These results support the conclusion that the 1858C/T allele is the major risk variant for type 1 diabetes in the PTPN22 locus, but they suggest that additional infrequent coding variants at PTPN22 may also contribute to type 1 diabetes risk.

Type 1 diabetes (T1D), a disorder of glucose homeostasis, is caused by autoimmune destruction of the essential insulin-secreting beta cells in the pancreas. Both genetic and environmental factors contribute to the risk of T1D and, for decades, this complexity has challenged investigators interested in identifying the genes that contribute to this risk. Nevertheless, in recent years, a number of well-supported T1D risk loci have been identified and replicated. Owing to development of more powerful study designs, the availability of dense marker maps, progress in high-throughput genotyping and a better basic understanding of the roles of genes in the immune system, this trend is likely to continue.

A collection of 767 multiplex type 1 diabetes families from the US and UK were tested for linkage to the IRS1 gene and for allelic association with a specific variant of IRS1, G972R. Pedigree disequilibrium testing revealed preferential transmission of the 972R allele to affected offspring in these families (P = 0.02). Linkage analyses conditioning on status at IRS1 position 972 suggest the possibility of interaction with an unidentified locus on chromosome 8.

Summary: Type 1 diabetes (T1D) arises from autoimmune destruction of the β cells of the pancreas leading to a complete dependence on exogenous insulin for survival. Like many autoimmune disorders, the etiology of T1D is complex, resulting from the action of multiple genes and environmental factors. Identification of genes that contribute to T1D susceptibility should improve disease prediction and contribute to the understanding of the underlying pathology of the disorder. Two regions of the human genome, the human leukocyte antigen (HLA) region and the insulin gene region are generally thought to contain susceptibility loci for T1D. Although additional putative T1D loci have been reported, the supporting evidence has often been of modest significance and findings have displayed poor reproducibility across multiple studies. This review summarizes the current state of genetic linkage and association studies in T1D and suggests future directions. We argue that much of the difficulty in mapping T1D susceptibility loci has resulted from inadequate sample sizes and we illustrate the substantial gains in power that can be achieved by pooling data across studies. These findings suggest that substantial progress toward the identification of susceptibility genes in T1D and other genetically complex disorders may be achieved through increased collaboration and consortium mapping efforts.

Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge-purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 (P = 3.01 x 10(-7)) in SOX2OT and rs17030795 (P = 5.84 x 10(-6)) in PPP3CA. Two additional signals were specific to Europeans: rs1523921 (P = 5.76 x 10(-6)) between CUL3 and FAM124B and rs1886797 (P = 8.05 x 10(-6)) near SPATA13. Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance (P= 4x10(-6)), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.

Genome-wide association studies (GWAS) for type 1 diabetes (T1D) have successfully identified more than 40 independent T1D associated tagging single nucleotide polymorphisms (SNPs). However, owing to technical limitations of copy number variants (CNVs) genotyping assays, the assessment of the role of CNVs has been limited to the subset of these in high linkage disequilibrium with tag SNPs. The contribution of untagged CNVs, often multi-allelic and difficult to genotype using existing assays, to the heritability of T1D remains an open question. To investigate this issue, we designed a custom comparative genetic hybridization array (aCGH) specifically designed to assay untagged CNV loci identified from a variety of sources. To overcome the technical limitations of the case control design for this class of CNVs, we genotyped the Type 1 Diabetes Genetics Consortium (T1DGC) family resource (representing 3,903 transmissions from parents to affected offspring) and used an association testing strategy that does not necessitate obtaining discrete genotypes. Our design targeted 4,309 CNVs, of which 3,410 passed stringent quality control filters. As a positive control, the scan confirmed the known T1D association at the INS locus by direct typing of the 5′ variable number of tandem repeat (VNTR) locus. Our results clarify the fact that the disease association is indistinguishable from the two main polymorphic allele classes of the INS VNTR, class I-and class III. We also identified novel technical artifacts resulting into spurious associations at the somatically rearranging loci, T cell receptor, TCRA/TCRD and TCRB, and Immunoglobulin heavy chain, IGH, loci on chromosomes 14q11.2, 7q34 and 14q32.33, respectively. However, our data did not identify novel T1D loci. Our results do not support a major role of untagged CNVs in T1D heritability., Author Summary For many complex traits, and in particular type 1 diabetes (T1D), the genome-wide association study (GWAS) design has been successful at detecting a large number of loci that contribute disease risk. However, in the case of T1D as well as almost all other traits, the sum of these loci does not fully explain the heritability estimated from familial studies. This observation raises the possibility that additional variants exist but have not yet been found because they have not effectively been targeted by the GWAS design. Here, we focus on a specific class of large deletions/duplications called copy number variants (CNVs), and more precisely to the subset of these loci that mutate rapidly, which are highly polymorphic. A consequence of this high level of polymorphism is that these variants have typically not been captured by previous GWAS studies. We use a family based design that is optimized to capture these previously untested variants. We then perform a genome-wide scan to assess their contribution to T1D. Our scan was technically successful but did not identify novel associations. This suggests that little was missed by the GWAS strategy, and that the remaining heritability of T1D is most likely driven by a large number of variants, either rare of common, but with a small individual contribution to disease risk.

To access publisher's full text version of this article click on the hyperlink at the bottom of the page Primary sclerosing cholangitis (PSC) is a severe liver disease of unknown etiology leading to fibrotic destruction of the bile ducts and ultimately to the need for liver transplantation. We compared 3,789 PSC cases of European ancestry to 25,079 population controls across 130,422 SNPs genotyped using the Immunochip. We identified 12 genome-wide significant associations outside the human leukocyte antigen (HLA) complex, 9 of which were new, increasing the number of known PSC risk loci to 16. Despite comorbidity with inflammatory bowel disease (IBD) in 72% of the cases, 6 of the 12 loci showed significantly stronger association with PSC than with IBD, suggesting overlapping yet distinct genetic architectures for these two diseases. We incorporated association statistics from 7 diseases clinically occurring with PSC in the analysis and found suggestive evidence for 33 additional pleiotropic PSC risk loci. Together with network analyses, these findings add to the genetic risk map of PSC and expand on the relationship between PSC and other immune-mediated diseases. Norwegian PSC Research Center German Ministry of Education and Research through the National Genome Research Network 01GS0809-GP7 Deutsche Forschungsgemeinschaft FR 2821/2-1 Integrated Research and Treatment Center-Transplantation 01EO0802 PopGen Biobank Wellcome Trust 098051 info:eu-repo/grantAgreement/EC/FP7/262055

Recent advances in the identification of susceptibility genes and environmental exposures provide broad support for a post-infectious autoimmune basis for narcolepsy/hypocretin (orexin) deficiency. We genotyped loci associated with other autoimmune and inflammatory diseases in 1,886 individuals with hypocretin-deficient narcolepsy and 10,421 controls, all of European ancestry, using a custom genotyping array (ImmunoChip). Three loci located outside the Human Leukocyte Antigen (HLA) region on chromosome 6 were significantly associated with disease risk. In addition to a strong signal in the T cell receptor alpha (TRA@), variants in two additional narcolepsy loci, Cathepsin H (CTSH) and Tumor necrosis factor (ligand) superfamily member 4 (TNFSF4, also called OX40L), attained genome-wide significance. These findings underline the importance of antigen presentation by HLA Class II to T cells in the pathophysiology of this autoimmune disease., Author Summary While there is now broad consensus that narcolepsy-hypocretin deficiency results from a highly specific autoimmune attack on hypocretin cells, little is understood regarding the initiation and progression of the underlying autoimmune process. We have taken advantage of a unique high-density genotyping platform (the ImmunoChip) designed to study variants in genes known to be important to autoimmune and inflammatory diseases. Our study of nearly 2000 narcolepsy cases compared to 10,000 controls underscored important roles for HLA DQB1*06:02 and the T cell receptor alpha genes and implicated two additional genes, Cathepsin H and TNFSF4/OX40L, in disease pathogenesis. These findings are particularly important, as these encoded proteins have key roles in antigen processing, presentation, and T cell response, and they suggest that specific interactions at the immunological synapse constitute the pathway to the disease. Further studies of these genes and encoded proteins may therefore reveal the mechanism leading to this highly selective and unique autoimmune disease.

A search for variants in coding exons of 25 genome-wide association study risk genes in a large cohort of autoimmune patients finds that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility, arguing against the previously proposed rare-variant synthetic genome-wide association hypothesis. Although many common variants of modest-effect size have been identified in genome-wide association studies (GWAS), much of the heritability of complex traits remains unexplained. These authors looked for variants in coding exons of 25 GWAS risk genes in a large cohort of subjects with six autoimmune disease phenotypes and controls, and show that rare coding-region variants at known loci have at most a minor role in common autoimmune disease susceptibility. These results do not support the theory that the missing heritability for common autoimmune diseases is attributable to rare coding mutations at known loci, but are consistent with disease caused by many common-variant loci of weak effect. Genome-wide association studies (GWAS) have identified common variants of modest-effect size at hundreds of loci for common autoimmune diseases; however, a substantial fraction of heritability remains unexplained, to which rare variants may contribute1,2. To discover rare variants and test them for association with a phenotype, most studies re-sequence a small initial sample size and then genotype the discovered variants in a larger sample set3,4,5. This approach fails to analyse a large fraction of the rare variants present in the entire sample set. Here we perform simultaneous amplicon-sequencing-based variant discovery and genotyping for coding exons of 25 GWAS risk genes in 41,911 UK residents of white European origin, comprising 24,892 subjects with six autoimmune disease phenotypes and 17,019 controls, and show that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility. These results do not support the rare-variant synthetic genome-wide-association hypothesis6 (in which unobserved rare causal variants lead to association detected at common tag variants). Many known autoimmune disease risk loci contain multiple, independently associated, common and low-frequency variants, and so genes at these loci are a priori stronger candidates for harbouring rare coding-region variants than other genes. Our data indicate that the missing heritability for common autoimmune diseases may not be attributable to the rare coding-region variant portion of the allelic spectrum, but perhaps, as others have proposed, may be a result of many common-variant loci of weak effect7,8,9,10.

Inflammation, which is directly regulated by interleukin-6 (IL-6) signaling, is implicated in the etiology of several chronic diseases. Although a common, non-synonymous variant in the IL-6 receptor gene (IL6R Asp358Ala; rs2228145 A>C) is associated with the risk of several common diseases, with the 358Ala allele conferring protection from coronary heart disease (CHD), rheumatoid arthritis (RA), atrial fibrillation (AF), abdominal aortic aneurysm (AAA), and increased susceptibility to asthma, the variant's effect on IL-6 signaling is not known. Here we provide evidence for the association of this non-synonymous variant with the risk of type 1 diabetes (T1D) in two independent populations and confirm that rs2228145 is the major determinant of the concentration of circulating soluble IL-6R (sIL-6R) levels (34.6% increase in sIL-6R per copy of the minor allele 358Ala; rs2228145 [C]). To further investigate the molecular mechanism of this variant, we analyzed expression of IL-6R in peripheral blood mononuclear cells (PBMCs) in 128 volunteers from the Cambridge BioResource. We demonstrate that, although 358Ala increases transcription of the soluble IL6R isoform (P = 8.3×10−22) and not the membrane-bound isoform, 358Ala reduces surface expression of IL-6R on CD4+ T cells and monocytes (up to 28% reduction per allele; P≤5.6×10−22). Importantly, reduced expression of membrane-bound IL-6R resulted in impaired IL-6 responsiveness, as measured by decreased phosphorylation of the transcription factors STAT3 and STAT1 following stimulation with IL-6 (P≤5.2×10−7). Our findings elucidate the regulation of IL-6 signaling by IL-6R, which is causally relevant to several complex diseases, identify mechanisms for new approaches to target the IL-6/IL-6R axis, and anticipate differences in treatment response to IL-6 therapies based on this common IL6R variant., Author Summary Interleukin-6 (IL-6) is a complex cytokine, which plays a critical role in the regulation of inflammatory responses. Genetic variation in the IL-6 receptor gene is associated with the risk of several human diseases with an inflammatory component, including coronary heart disease, rheumatoid arthritis, and asthma. A common non-synonymous single nucleotide polymorphism in this gene (Asp358Ala) has been suggested to be the causal variant in this region by affecting the circulatory concentrations of soluble IL-6R (sIL-6R). In this study we extend the genetic association of this variant to type 1 diabetes and provide evidence that this variant exerts its functional mechanism by regulating the balance between sIL-6R (generated through cleavage of the surface receptor and by alternative splicing of a soluble IL6R isoform) and membrane-bound IL-6R. These data show for the first time that the minor allele of this non-synonymous variant (Ala358) directly controls the surface levels of IL-6R on individual immune cells and that these differences in protein levels translate into a functional impairment in IL-6R signaling. These findings may have implications for clinical trials targeting inflammatory mechanisms involving IL-6R signaling and may provide tools for identifying patients with specific benefit from therapeutic intervention in the IL-6R signaling pathway.

Background: Nearly 21 million people in the United States, or 7% of the population, are estimated to have diabetes. The incidence and prevalence of diabetes differ by ethnicity; however, both type 1 diabetes (T1D) and type 2 diabetes (T2D) occur in all groups. The etiology of diabetes is multifactorial, involving both genetic and environmental factors. Advances in technology, leading to the identification of over a dozen candidate genes, have accelerated the search for genetic factors contributing to the risk of diabetes. To date, surprisingly little data exist to suggest there are common genetic pathways leading to development of T1D and T2D. These common forms of diabetes have complex genetic (and environmental) risk factors, making prediction and prevention difficult. Nonetheless, detection of diabetes susceptibility genes may facilitate identification of novel pathways that can serve as therapeutic targets and lead to disease prevention.

Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (ncases = 5,337), type 1 diabetes (T1D; ncases = 5,567), psoriasis vulgaris (ncases = 3,089), idiopathic achalasia (ncases = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 × 10(-12); T1D, P = 2.4 × 10(-10); psoriasis, P = 5.9 × 10(-6); celiac disease, P = 1.2 × 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 × 10(-3); T1D, P = 8.6 × 10(-27); celiac disease, P = 6.0 × 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model. ispartof: Nature Genetics vol:47 issue:9 pages:1085-90 ispartof: location:United States status: published

Type I diabetes (T1D) is a complex disorder, which arises from the autoimmune destruction of the insulin-secreting beta cells of the pancreas leading to a life-long dependence on exogenous insulin. A recent study of T1D cases and controls provided evidence for association between an allele of a functional single-nucleotide polymorphism (SNP) in the PTPN22 gene and T1D. In the current study, this SNP was genotyped in a collection of 406 multiplex T1D families. Significant evidence of the combined presence of association and linkage to T1D was obtained (P = 2.5 x 10(-5)). Linkage studies in subsets of families defined by PTPN22 SNP genotypes suggest possible interaction with loci on chromosomes 3 and 21. Previous genome scans in this collection of T1D families, and others, have not yielded significant evidence of linkage in the region of the PTPN22 locus. However, the highly significant evidence of allelic association suggests that variation at, or near, this functional SNP contributes to the risk of T1D.

DNA sequence variation within human leukocyte antigen (HLA) genes mediate susceptibility to a wide range of human diseases. The complex genetic structure of the major histocompatibility complex (MHC) makes it difficult, however, to collect genotyping data in large cohorts. Long-range linkage disequilibrium between HLA loci and SNP markers across the major histocompatibility complex (MHC) region offers an alternative approach through imputation to interrogate HLA variation in existing GWAS data sets. Here we describe a computational strategy, SNP2HLA, to impute classical alleles and amino acid polymorphisms at class I (HLA-A ,- B ,- C) and class II (-DPA1 ,- DPB1 ,- DQA1 ,- DQB1, and -DRB1) loci. To characterize performance of SNP2HLA, we constructed two European ancestry reference panels, one based on data collected in HapMap-CEPH pedigrees (90 individuals) and another based on data collected by the Type 1 Diabetes Genetics Consortium (T1DGC, 5,225 individuals). We imputed HLA alleles in an independent data set from the British 1958 Birth Cohort (N=918) with gold standard four-digit HLA types and SNPs genotyped using the Affymetrix GeneChip 500 K and Illumina Immunochip microarrays. We demonstrate that the sample size of the reference panel, rather than SNP density of the genotyping platform, is critical to achieve high imputation accuracy. Using the larger T1DGC reference panel, the average accuracy at four-digit resolution is 94.7% using the low-density Affymetrix GeneChip 500 K, and 96.7% using the highdensity Illumina Immunochip. For amino acid polymorphisms within HLA genes, we achieve 98.6% and 99.3% accuracy using the Affymetrix GeneChip 500 K and Illumina Immunochip, respectively. Finally, we demonstrate how imputation and association testing at amino acid resolution can facilitate fine-mapping of primary MHC association signals, giving a specific example from type 1 diabetes.

Background: Studies have confirmed associations with TNFSF15 and CD in Caucasian and Asian populations, but these studies have been limited by the number of markers tested. Decoy Receptor 3 (DcR3), previously identified as a susceptibility gene from a Caucasian pediatric CD GWAS, is a decoy receptor that can neutralize pro-inflammatory ligands including, TL1A (TNFSF15). Aim: To perform transethnic fine mapping across TNFSF15 and DcR3 in Caucasian, Puerto Rican and Korean CD. Methods: Genotyping was performed in Non-Jewish Caucasians (NJ; 779 CD, 4182 controls), Ashkenazi-Jews (AJ; 492 CD, 395 controls), Puerto Ricans (PR; 300 CD, 235 controls), and South Koreans (SK; 729 CD, 469 controls) using the 200K SNP ImmunoChip genotyping array. Analysis of TNFSF15 (416 SNPs) and DcR3 (13 SNPs) was conducted. Principal components analysis controlled for population structure, and logistic regression models tested for association of each SNP with CD. Results: TNFSF15 analyses: 4 rare variants (MAF,1%) and 9 common variants (MAF= 27.7-34.9%) were significantly associated with NJ CD after correction for multiple-testing. Analyses in NJ CD confirmed that rare and common variants associations could each be tagged by a single SNP (rare: rs1322057, MAF=0.83%, p=3.02E-6, OR=6.97; common: rs7869487, MAF=22.6%, p=7.26E-5, OR=0.78). Further, the associations with CD of these SNPs were independent of each other. All 13 NJ CD SNP associations were replicated in SK CD (all P ,3.15E-10) but with higher MAF (0.13% vs 34.6% for rs1322057 and 32.4% vs 40.9% for rs7869487 in controls). The independence of the 2 SNPs seen in NJ was replicated in SK. The rare variants were also associated with PR CD but with higher MAF than in NJ (6.6% for rs1322057, p=3.19E-2, OR=1.62), but no association was seen at 9 common variants in PR. No significant SNP associations were observed with AJ CD. DcR3 analyses: rs6062496, located in intron 6 of DcR3, was significantly associated with NJ CD (p=5.83E-4, OR=1.22). This association was confirmed in SK CD (p=2.01E-2, OR=1.32) but not in AJ or PR CD. The associated SNP was also significantly associated with protection against stricturing CD (p=2.95E-2, OR=0.75). There were no significant gene-gene interactions between rs6062496 in DCR3 and the 2 independent SNPs from TNFSF15 in both NJ (p.0.18) and SK CD (p.0.61). Conclusion: We have identified novel associations of rare variants in TNFSF15 with NJ CD that are independent of previously reported common variants, and are also found in PR and SK. These variants are more common in SK and also associated with SK CD, perhaps explaining the ‘dominant' role of this locus in Asian IBD susceptibility. DcR3 is significantly associated with NJ CD, a finding replicated in SK and variation at this locus modifies a stricturing phenotype.