An allele of IKZF1 (Ikaros) conferring susceptibility to childhood acute lymphoblastic leukemia protects against type 1 diabetes.

OBJECTIVE: IKZF1 encoding Ikaros, an essential regulator of lymphopoiesis and immune homeostasis, has been implicated in the development of childhood acute lymphoblastic leukemia (C-ALL). Because recent genome-wide association (GWA) studies have linked a region of the 3'-UTR of IKZF1 with C-ALL susceptibility, we tested whether IKZF1 is associated with the autoimmune disease type 1 diabetes. RESEARCH DESIGN AND METHODS: rs10272724 (T>C) near IKZF1 at 7p12 was genotyped in 8,333 individuals with type 1 diabetes, 9,947 control subjects, and 3,997 families of European ancestry. Association was tested using logistic regression in the case-control data and by the transmission disequilibrium test in the families. Expression data for IKZF1 by rs10272724 genotype were obtained using quantitative PCR of mRNA/cDNA generated from peripheral blood mononuclear cells from 88 individuals, whereas expression data for five other neighboring genes were obtained from the online Genevar dataset. RESULTS: The minor allele of rs10272724 (C) was found to be protective from type 1 diabetes (odds ratio 0.87 [95% CI 0.83-0.91]; P = 1.1 × 10(-11)). rs10272724 was not correlated with levels of two transcripts of IKZF1 in peripheral blood mononuclear cells. CONCLUSIONS: The major susceptibility genotype for C-ALL confers protection from type 1 diabetes. Our finding strengthens the link between autoimmunity and lymphoid cancers. Further investigation is warranted for the genetic effect marked by rs10272724, its impact on IKZF1, and the role of Ikaros and other family members, Ailios (IKZF3) and Eos (IKZF4), in autoimmunity

Epigenetic analysis of regulatory T cells using multiplex bisulfite sequencing.

This work was supported by Wellcome Trust Grant 096388, JDRF Grant 9-2011-253, the National Institute for Health Research Cambridge Biomedical Research Centre (BRC) and Award P01AI039671 (to LSW. and JAT.) from the National Institute of Allergy and Infectious Diseases (NIAID). CW is supported by the Wellcome Trust (089989). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of NIAID or the National Institutes of Health. The Cambridge Institute for Medical Research is in receipt of Wellcome Trust Strategic Award 100140. We gratefully acknowledge the participation of all NIHR Cambridge BioResource volunteers. We thank the Cambridge BioResource staff for their help with volunteer recruitment. We thank members of the Cambridge BioResource SAB and Management Committee for their support of our study and the National Institute for Health Research Cambridge Biomedical Research Centre for funding. We thank Fay Rodger and Ruth Littleboy for running the Illumina MiSeq in the Molecular Genetics Laboratories, Addenbrooke's Hospital, Cambridge. This research was supported by the Cambridge NIHR BRC Cell Phenotyping Hub. In particular, we wish to thank Anna Petrunkina Harrison, Simon McCallum, Christopher Bowman, Natalia Savinykh, Esther Perez and Jelena Markovic Djuric for their advice and support in cell sorting. We also thank Helen Stevens, Pamela Clarke, Gillian Coleman, Sarah Dawson, Jennifer Denesha, Simon Duley, Meeta Maisuria-Armer and Trupti Mistry for acquisition and preparation of samples.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/eji.20154564

Investigating the utility of combining Φ29 whole genome amplification and highly multiplexed single nucleotide polymorphism BeadArray™ genotyping

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

Statistical independence of the colocalized association signals for type 1 diabetes and RPS26 gene expression on chromosome 12q13

Following the recent success of genome-wide association studies in uncovering disease-associated genetic variants, the next challenge is to understand how these variants affect downstream pathways. The most proximal trait to a disease-associated variant, most commonly a single nucleotide polymorphism (SNP), is differential gene expression due to the cis effect of SNP alleles on transcription, translation, and/or splicing gene expression quantitative trait loci (eQTL). Several genome-wide SNP–gene expression association studies have already provided convincing evidence of widespread association of eQTLs. As a consequence, some eQTL associations are found in the same genomic region as a disease variant, either as a coincidence or a causal relationship. Cis-regulation of RPS26 gene expression and a type 1 diabetes (T1D) susceptibility locus have been colocalized to the 12q13 genomic region. A recent study has also suggested RPS26 as the most likely susceptibility gene for T1D in this genomic region. However, it is still not clear whether this colocalization is the result of chance alone or if RPS26 expression is directly correlated with T1D susceptibility, and therefore, potentially causal. Here, we derive and apply a statistical test of this hypothesis. We conclude that RPS26 expression is unlikely to be the molecular trait responsible for T1D susceptibility at this locus, at least not in a direct, linear connection

The candidate genes TAF5L, TCF7, PDCD1, IL6 and ICAM1 cannot be excluded from having effects in type 1 diabetes.

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 x 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.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Natural Variation in Interleukin-2 Sensitivity Influences Regulatory T-Cell Frequency and Function in Individuals With Long-standing Type 1 Diabetes.

Defective immune homeostasis in the balance between FOXP3+ regulatory T cells (Tregs) and effector T cells is a likely contributing factor in the loss of self-tolerance observed in type 1 diabetes (T1D). Given the importance of interleukin-2 (IL-2) signaling in the generation and function of Tregs, observations that polymorphisms in genes in the IL-2 pathway associate with T1D and that some individuals with T1D exhibit reduced IL-2 signaling indicate that impairment of this pathway may play a role in Treg dysfunction and the pathogenesis of T1D. Here, we have examined IL-2 sensitivity in CD4+ T-cell subsets in 70 individuals with long-standing T1D, allowing us to investigate the effect of low IL-2 sensitivity on Treg frequency and function. IL-2 responsiveness, measured by STAT5a phosphorylation, was a very stable phenotype within individuals but exhibited considerable interindividual variation and was influenced by T1D-associated PTPN2 gene polymorphisms. Tregs from individuals with lower IL-2 signaling were reduced in frequency, were less able to maintain expression of FOXP3 under limiting concentrations of IL-2, and displayed reduced suppressor function. These results suggest that reduced IL-2 signaling may be used to identify patients with the highest Treg dysfunction and who may benefit most from IL-2 immunotherapy.This work was supported by the JDRF UK Centre for Diabetes Genes, Autoimmunity and Prevention (D-GAP; 4-2007-1003), the Wellcome Trust (WT061858/091157) and the NIHR Cambridge Biomedical Research Centre (CBRC). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (100140).This is the author accepted manuscript. The final version is available from the American Diabetes Association via http://dx.doi.org/10.2337/db15-051

The PTPN22 Locus and Rheumatoid Arthritis: No Evidence for an Effect on Risk Independent of Arg620Trp

The Trp(620) allotype of PTPN22 confers susceptibility to rheumatoid arthritis (RA) and certain other classical autoimmune diseases. There has been a report of other variants within the PTPN22 locus that alter risk of RA; protective haplotype '5', haplotype group '6-10' and susceptibility haplotype '4', suggesting the possibility of other PTPN22 variants involved in the pathogenesis of RA independent of R620W (rs2476601). Our aim was to further investigate this possibility.A total of 4,460 RA cases and 4,481 controls, all European, were analysed. Single nucleotide polymorphisms rs3789607, rs12144309, rs3811021 and rs12566340 were genotyped over New Zealand (NZ) and UK samples. Publically-available Wellcome Trust Case Control Consortium (WTCCC) genotype data were used.The protective effect of haplotype 5 was confirmed (rs3789607; (OR = 0.91, P = 0.016), and a second protective effect (possibly of haplotype 6) was observed (rs12144309; OR = 0.90, P = 0.021). The previously reported susceptibility effect of haplotype 4 was not replicated; instead a protective effect was observed (rs3811021; OR = 0.85, P = 1.4×10(-5)). Haplotypes defined by rs3789607, rs12144309 and rs3811021 coalesced with the major allele of rs12566340 within the adjacent BFK (B-cell lymphoma 2 (BCL2) family kin) gene. We, therefore, tested rs12566340 for association with RA conditional on rs2476601; there was no evidence for an independent effect at rs12566340 (P = 0.76). Similarly, there was no evidence for an independent effect at rs12566340 in type 1 diabetes (P = 0.85).We have no evidence for a common variant additional to rs2476601 within the PTPN22 locus that influences the risk of RA. Arg620Trp is almost certainly the single common causal variant

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.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available.This is the final version. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/gepi.21853/abstract

Widespread seasonal gene expression reveals annual differences in human immunity and physiology.

Seasonal variations are rarely considered a contributing component to human tissue function or health, although many diseases and physiological process display annual periodicities. Here we find more than 4,000 protein-coding mRNAs in white blood cells and adipose tissue to have seasonal expression profiles, with inverted patterns observed between Europe and Oceania. We also find the cellular composition of blood to vary by season, and these changes, which differ between the United Kingdom and The Gambia, could explain the gene expression periodicity. With regards to tissue function, the immune system has a profound pro-inflammatory transcriptomic profile during European winter, with increased levels of soluble IL-6 receptor and C-reactive protein, risk biomarkers for cardiovascular, psychiatric and autoimmune diseases that have peak incidences in winter. Circannual rhythms thus require further exploration as contributors to various aspects of human physiology and disease.The Gambian study providing data for analysis was supported by core funding MC-A760-5QX00 to the International Nutrition Group by the UK Medical Research Council (MRC) and the UK Department for the International Development (DFID) under the MRC/DFID Concordat agreement. This work was supported by the JDRF UK Centre for Diabetes-Genes, Autoimmunity and Prevention (D-GAP; 4-2007-1003), the JDRF (9-2011-253), the Wellcome Trust (WT061858/091157), the National Institute for Health Research Cambridge Biomedical Research Centre (CBRC) and the Medical Research Council (MRC) Cusrow Wadia Fund. The research leading to these results has received funding from the European Union’s 7th Framework Programme (FP7/2007–2013) under grant agreement no.241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award (WT100140). X.C.D. was a University of Cambridge/Wellcome Trust Infection and Immunity PhD student. R.C.F. is funded by a JDRF post-doctoral fellowship (3-2011-374). C.W. and H.G are funded by the Wellcome Trust (WT089989). The BABYDIET study was supported by grants from the Deutsche Forschungsgemeinschaft (DFG ZI-310/14-1 to-4), the JDRF (JDRF 17-2012-16 and 1-2006-665) and the German Center for Diabetes Research (DZD e.V.). E.B. is supported by the DFG Research Center and Cluster of Excellence—Center for Regenerative Therapies Dresden (FZ 111).This is the final published version. It first appeared at http://www.nature.com/ncomms/2015/150512/ncomms8000/full/ncomms8000.html