Original Article

Genes and Immunity (2009) 10, 5–10; doi:10.1038/gene.2008.82; published online 30 October 2008

CD226 Gly307Ser association with multiple autoimmune diseases

J P Hafler1, L M Maier2, J D Cooper1, V Plagnol1, A Hinks3, M J Simmonds4, H E Stevens1, N M Walker1, B Healy1, J M M Howson1, M Maisuria1, S Duley1, G Coleman1, S C L Gough4, The International Multiple Sclerosis Genetics Consortium (IMSGC), J Worthington3, V K Kuchroo2, L S Wicker1 and J A Todd1

  1. 1Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
  2. 2Division of Molecular Immunology, Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
  3. 3Arthritis Research Campaign (arc)-Epidemiology Unit, The University of Manchester, Manchester, UK
  4. 4School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK

Correspondence: JP Hafler, Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Addenbrooke's Hospital, University of Cambridge, WT/MRC Bldg, Cambridge CB2 0XY, UK. E-mail: jason.hafler@cimr.cam.ac.uk

Received 10 June 2008; Revised 11 July 2008; Accepted 28 August 2008; Published online 30 October 2008.



Genome-wide association studies provide insight into multigenic diseases through the identification of susceptibility genes and etiological pathways. In addition, the identification of shared variants among autoimmune disorders provides insight into common disease pathways. We previously reported an association of a nonsynonymous single nucleotide polymorphism (SNP) rs763361/Gly307Ser in the immune response gene CD226 on chromosome 18q22 with type 1 diabetes (T1D) susceptibility. Here, we report efforts toward identifying the causal variant by exonic resequencing and tag SNP mapping of the 18q22 region in both T1D and multiple sclerosis (MS). In addition to the analysis of newly available samples in T1D (2088 cases and 3289 controls) and autoimmune thyroid disease (AITD) (821 cases and 1920 controls), resulting in strong support for the Ser307 association with T1D (P=3.46 × 10−9) and continued potential evidence for AITD (P=0.0345), we provide evidence for association of Gly307Ser with MS (P=4.20 × 10−4) and rheumatoid arthritis (RA) (P=0.017). The Ser307 allele of rs763361 in exon 7 of CD226 predisposes to T1D, MS, and possibly AITD and RA, and based on the tag SNP analysis, could be the causal variant.


type 1 diabetes, multiple sclerosis, rheumatoid arthritis, CD226, DNAM-1



Type 1 diabetes (T1D), multiple sclerosis (MS), autoimmune thyroid disease (AITD) and rheumatoid arthritis (RA) are organ-specific autoimmune diseases mediated by self-reactive T cells and other cells of the adaptive and innate immune systems. T1D is characterized by inflammation of the pancreatic islets of Langerhans with the destruction of insulin-producing β-cells,1 whereas in MS and RA, there is selective white matter and joint tissue destruction, respectively.2, 3 Sibling and twin studies indicate a major genetic component of the familial clustering of these common diseases4, 5, 6 with the major susceptibility loci in the human leukocyte antigen region.7, 8, 9, 10 Recent genome-wide association studies have successfully identified many single nucleotide polymorphisms (SNPs) outside the human leukocyte antigen complex associated with common disease susceptibility.11 In addition to the identification of associated SNPs, these investigations provide insight into genes and mechanisms shared among autoimmune diseases. Examples include STAT4 in RA and systemic lupus erythematosus,12 and IL2RA in T1D,13 Graves' disease14 and MS.15, 16

We recently reported a genome-wide association study of nonsynonymous SNPs from across the genome in T1D that provided strong statistical evidence for association at chromosome 18q22.17 In 6021 T1D cases and 6088 controls, Gly307Ser, located in CD226, showed a P-value of 2.82 × 10−8 (odds ratio (OR) for minor allele=1.16, 95% confidence interval (CI)=1.10–1.22) and in 2997 parent–child trios, a P-value of 0.0281 (relative risk=1.08, 95% CI=1.00–1.16). Combining the results obtained from the case–control and family studies yielded a P-value of 1.38 × 10−8.

CD226 (also known as DNAX accessory molecule 1, DNAM-1) is a 67-kDa type I membrane protein involved in the adhesion and co-stimulation of T cells.18 It belongs to the immunoglobulin supergene family of receptors, containing two Ig-like domains in the extracellular region, and is constitutively expressed on the majority of natural killer cells, CD4+ and CD8+ T cells, monocytes, platelets and a subset of B cells.18 Furthermore, in an experimental model of MS, experimental autoimmune encephalomyelitis, anti-CD226 monoclonal antibody treatment delayed the onset and reduced the severity of experimental autoimmune encephalomyelitis.19 The Gly307Ser variant could alter the expression or signaling of CD226, as it occurs in the molecule's cytoplasmic tail.17 It was, therefore, of interest to explore whether Gly307Ser was the causal variant in the region and a shared risk locus for autoimmune disease.

Here we report an initial fine-mapping study of the 18q22 region in both T1D and MS by means of exonic resequencing and a tag SNP mapping approach based around Gly307Ser. We provide no evidence against the hypothesis that the nonsynonymous SNP (Gly307Ser) is the causal variant in the 18q22 region for MS and T1D. Moreover, we extended this analysis to include RA (and additional AITD samples), suggesting that Ser307 predisposes to a range of human autoimmune diseases.



To increase SNP density and detect as-yet-unknown SNPs in the coding region or identify SNPs that may disrupt intron/exon splice sites present in CD226, we resequenced the exonic regions in the roughly 50kb linkage disequilibrium (LD) block (exons 4, 5, 6 and 7) containing Gly307Ser and 3kb of 3′-flanking sequence in 32 individuals chosen from the HapMap Centre d'Etude du Polymorphisme Humain (CEPH) collection. This led to 7.7kb of DNA being resequenced and the identification of 13 SNPs in three exons and the 3′-flanking sequence (exon 5 was not sequenced due to PCR failures, see Materials and methods). When compared with the publicly available SNPs in dbSNP build 128, two SNPs were found to be novel polymorphisms. They were located in exon 6, namely a nonsynonymous SNP (Ala279Leu, ss102661466) and a synonymous SNP (Gln282Gln, ss102661465) with minor allele frequencies of 0.065 and 0.078, respectively. As these variants are functional candidates, they were genotyped in the T1D case–control collection. The single-locus tests provided little evidence of an association with T1D susceptibility: Ala279Leu P=2.08 × 10−3 (OR=1.15; 95% CI=1.05–1.26) and Gln282Gln P=0.0298 (OR=0.90; 95% CI=0.82–0.99) (Supplementary Table 1). Nor did the forward logistic regression analysis adding either novel SNP to Gly307Ser provide evidence (minimum P=0.0542) of an independent association with T1D susceptibility, whereas Gly307Ser added significantly to both SNPs (minimum P=8.10 × 10−6), indicating that neither of the novel SNPs are independently associated with T1D susceptibility.

Furthermore, we selected and tested a set of tag SNPs (see Materials and methods) to investigate the association identified earlier in the 18q22 region. Gly307Ser was still the one most associated with T1D in 8109 cases and 9377 controls (P=1.32 × 10−8; OR=1.13; 95% CI=1.08–1.18) (Table 1). We conducted a forward logistic regression analysis testing the addition of each SNP to Gly307Ser and found that none added significantly. There was, therefore, no evidence for a known polymorphism (with a minor allele frequency >0.05 and r2 with Gly307Ser >0.25) in the CD226 region that showed stronger association with T1D than Gly307Ser or had an independent effect on T1D susceptibility.

We then proceeded to test Gly307Ser in a cohort of MS samples consisting of 1275 trios, 1063 US cases, 593 US controls, 998 UK cases and 9377 UK controls (UK controls are the same as in our T1D association study). The combined P-value was 4.20 × 10−4 (Table 2). To test the hypothesis that Gly307Ser was the causal variant in MS, we tested the same set of T1D tag SNPs in an extended set of 1318 MS trios, 1769 MS US cases, 2508 US controls and 1003 MS UK cases and used the genotyping data already available for 9377 UK controls. Consistent with our T1D study, we obtained no evidence against the hypothesis that CD226 Gly307Ser is the causal variant associated with MS in the 18q22 region (Table 3).

As Gly307Ser was found to be associated with both T1D and MS susceptibility, it was of interest to examine a collection of RA samples and an additional cohort of AITD cases. We tested Gly307Ser in 3595 RA cases and 3214 controls and obtained some evidence of association, at P=0.017 (OR=1.09; 95% CI=1.02–1.16) (Table 2). We obtained no evidence of heterogeneity of association between males and females (P=0.90), nor between RF-positive and RF-negative cases (P=0.86) and nor between anti-CCP-negative and anti-CCP-positive cases (P=0.45). This suggests Gly307Ser is associated with RA and not a sub-phenotype. Furthermore, adding 821 AITD cases to our earlier published data17 (N=2958, N=5431), we obtained potential evidence for association, at P=0.0335 (OR=1.08; 95% CI=1.00–1.15) (the controls are the same used in our T1D association study but matched geographically) (see Supplementary Table 4 for Graves' disease and Hashimoto's disease results reported separately).



Genome-wide association scans in common human autoimmune diseases have recently identified many loci associated with disease susceptibility. Understanding allelic heterogeneity and homogeneity among diseases provides insight into common gene function and pathways. Here, we examined the gene encoding CD226, a molecule expressed on the surface of hematopoietic cells that has independently been implicated in the pathogenesis of animal models of autoimmune diseases. Our resequencing efforts and tagging approach aimed at narrowing the association in the 18q22 region provided no evidence against the hypothesis that CD226 Gly307Ser is the causal variant in T1D and MS. In addition, the International Multiple Sclerosis Genetics Consortium (IMSGC) extended the evidence supporting an association of Gly307Ser with MS. In an additional sample of 3610 MS cases, 324 controls and 1036 trios, the IMSGC further validated Gly307Ser association with MS (P=5.4 × 10−8) (Table 1 in IMSGC paper,30 see editorial31 for complete analysis and overlap between studies). Taken together with our association study of the role of Gly307Ser in a collection of RA cases and additional data for Gly307Ser in AITD (P=0.0345), we provide initial evidence for CD226 to be shared among at least four common human autoimmune diseases.

We note, however, that until a more complete set of polymorphisms is identified and genotyped in a large collection of cases and control subjects, we cannot exclude another variant in LD with Gly307Ser being the causal variant. Future successful resequencing of exon 5 may provide as-yet-undiscovered variants that will need to be assessed for disease susceptibility. In addition, the CD226 region may harbor other independent associations with susceptibility to disease that our tag mapping approach was not designed to identify, as has earlier been shown for another T1D susceptibility locus containing the IL2RA gene,20 although the data indicate that this is not the case for common variants in the CD226 region.

CD226 is implicated in natural killer cell-mediated cytoxicity as well as in Th1 cell-mediated immune response.18, 19 Phosphorylation of the cytoplasmic tail of CD226 assists in co-localization with lymphocyte function-associated antigen-1 (LFA-1) and cell activation.21 Our genetic association data now justify studies of the functional consequences of the Gly307Ser variant in adaptive and innate immune responses. We have earlier hypothesized17 that the SNP could disrupt a splice site enhancer, or silencer, thereby altering RNA splicing, as has been demonstrated for other immune-related genes (human CD45 and mouse Ctla4),22 resulting in either a putative CD226 isoform acting as a non-functional (non-signaling) protein or with a novel function. Alternatively, this amino acid substitution could alter the signaling cascade by affecting the two known phosphorylation sites at positions 322 and 329,21, 23 which share a critical role in CD226 and the immune response.


Materials and methods


All case and control subjects were of self-reported white ethnicity and were enrolled under study protocols approved by the Institutional Review Board of each institution that contributed. Written informed consent was obtained from the participants or their guardians.

T1D collection

T1D cases were recruited as part of the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory's British case collection (Genetic Resource Investigating Diabetes).17 Control samples were obtained from the British 1958 Birth Cohort (B58C) and WTCCC Blood Service controls.11 Cases and controls were matched geographically within Great Britain for statistical analyses of association.

MS collection

Healthy adult control subjects were recruited through the Brigham and Women's Hospital, the University of Cambridge and the University of California at San Francisco, as described earlier.15 All were unrelated individuals having no history of chronic inflammatory disease. MS cases were collected as described in our recent investigation of patients with MS.15 Subjects with MS all meet McDonald's criteria for MS.24

RA collection

DNA from UK RA patients, over 18 years old and satisfying the American College of Rheumatology criteria for RA, was available from six centers in the United Kingdom and five of these centers provided controls as described in our recent investigation.25 The samples collected from six centers in the United Kingdom raise the possibility that the results were affected by population substructure and heterogeneity. A stratified analysis by center revealed that the association of Gly307Ser with RA was independently observed in four of the five centers tested (one center had no controls, and therefore association could not be statistically tested for this center). No heterogeneity was detected among the samples from the different centers, and combined evidence from the different centers (using a Cochran–Mantel–Haenszel test) attained a significance level virtually the same as that from the combined samples.

AITD collection

As reported earlier17 as part of the AITD UK National Collection, 2958 unrelated individuals were recruited including 2295 with Graves' disease and 663 with Hashimoto's thyroiditis. Cases and controls were chosen such that they were matched geographically.


Polymorphisms were identified by resequencing 32 CEPH DNA samples, which are the same samples used by HapMap (http://www.hapmap.org). Sequencing was performed using Applied Biosystems' (Foster City, CA, USA) BigDye chemistry (version 3.1), and the sequences resolved using an Applied Biosystems 3700 Genetic Analyzer. Analyses of the sequence traces were performed using the Staden package, and traces were scored independently by a second operator by hand. Annotations are available from T1DBase (see URLs), together with sequence and polymorphism data at the T1DBase PosterPages (see URL). Primer sequences are available on request. Owing to problems with the design of primers to amplify exon 5, this exon could not be successfully sequenced and any as-yet-undiscovered variants that may reside in this exon are not part of our association analysis.


SNPs were genotyped using the iPLEX Sequenom MassARRAY platform or TaqMan (Applied Biosystems) in accordance with the manufacturer's instructions. Cases and controls were genotyped and data scored twice to minimize error, with the second operator being unaware of case–control status or family structure. None of the SNPs significantly deviated from the Hardy–Weinberg disequilibrium in controls and unaffected parents (P>0.05) (except for rs17208112, see ‘Tag SNP selection’ section).

Statistical analyses

All statistical analyses were performed in Stata or R statistical packages (see URLs).

Logistic regression analyses

The case–control data were analyzed using logistic regression models stratified by 12 geographical regions across England, Scotland and Wales to minimize loss of power due to geography.26 When analyzing a single SNP, we performed a one degree of freedom (1 d.f.) likelihood ratio test to determine whether a 1 d.f. multiplicative allelic effects model or a 2 d.f. genotypic effects model better fit the data.27

We used forward logistic regression to assess the evidence against the most significant SNP being the sole associated variant in the region (in other words, whether this SNP alone was sufficient to model the association). For the purposes of this analysis, we did not assume any specific mode of inheritance for the most associated SNP (A>a) or for any additional SNPs with significant independent effects on T1D; hence, genotype risks of A/A and A/a were modeled relative to the a/a genotype. We then used a 1-d.f. test for adding each of the remaining SNPs to the model by assuming multiplicative allelic effects for the additional SNPs.

Tag SNP selection

To delimit the disease-associated region and select an informative set of tags, we analyzed the LD (using r2 and D28) structure of CD226 in DNA samples obtained from 32 individuals from the CEPH collection genotyped by the International HapMap project (http://www.hapmap.org).29 The tagging strategy involved the selection of SNPs with minor allele frequencies >0.05 and r2 values >0.25 with Gly307Ser. Available data allowed for the analysis of 205 SNPs within CD226. Of the 135 SNPs in the LD block, 43 had MAFs >0.05 and r2>0.25 with Gly307Ser. Eleven SNPs were sufficient to pairwise tag this LD block (r2>0.80) as determined in HapMap (release 21). If associations were not observed in 5500 cases and 5500 controls, the SNP would not be genotyped in additional cases.

rs17208112, a singleton SNP tagging itself, failed quality control tests in both our T1D and UK MS cohorts because of an adjacent SNP disrupting the binding specificity of the probe and was hence removed from the data set.

URLs: British 1958 Birth Cohort: http://www.b58cgene.sgul.ac.uk/; T1DBase: http://www.t1dbase.org (and UK mirror site, http://www.dil.t1dbase.org) Stata: http://www.stata.com/; R: http://www.r-project.org/; rpart: http://cran.r-project.org/; Haploview: http://www.broad.mit.edu/mpg/haploview/; gbrowse: http://www.gmod.org/; bioconductor: http://www.bioconductor.org/; dbSNP: http://www.ncbi.nlm.nih.gov/projects/SNP/.



  1. Haller MJ, Atkinson MA, Schatz D. Type 1 diabetes mellitus: etiology, presentation, and management. Pediatr Clin North Am 2005; 52: 1553–1578. | Article | PubMed |
  2. Prineas JW, Wright RG. Macrophages, lymphocytes, and plasma cells in the perivascular compartment in chronic multiple sclerosis. Lab Invest 1978; 38: 409–421. | PubMed | ISI | ChemPort |
  3. Stastny P. Mixed lymphocyte cultures in rheumatoid arthritis. J Clin Invest 1976; 57: 1148–1157. | Article | PubMed | ISI | ChemPort |
  4. Doolittle TH, Myers RH, Lehrich JR, Birnbaum G, Sheremata W, Franklin GM et al. Multiple sclerosis sibling pairs: clustered onset and familial predisposition. Neurology 1990; 40: 1546–1552. | PubMed | ChemPort |
  5. Silman AJ, MacGregor AJ, Thomson W, Holligan S, Carthy D, Farhan A et al. Twin concordance rates for rheumatoid arthritis: results from a nationwide study. Br J Rheumatol 1993; 32: 903–907. | Article | PubMed | ISI | ChemPort |
  6. Hyttinen V, Kaprio J, Kinnunen L, Koskenvuo M, Tuomilehto J. Genetic liability of type 1 diabetes and the onset age among 22,650 young Finnish twin pairs: a nationwide follow-up study. Diabetes 2003; 52: 1052–1055. | Article | PubMed | ISI | ChemPort |
  7. Todd JA, Bell JI, McDevitt HO. HLA-DQ beta gene contributes to susceptibility and resistance to insulin-dependent diabetes mellitus. Nature 1987; 329: 599–604. | Article | PubMed | ISI | ChemPort |
  8. Stastny P. Association of the B-cell alloantigen DRw4 with rheumatoid arthritis. N Engl J Med 1978; 298: 869–871. | PubMed | ISI | ChemPort |
  9. Jersild C, Svejgaard A, Fog T. HL-A antigens and multiple sclerosis. Lancet 1972; 1: 1240–1241. | Article | PubMed | ISI | ChemPort |
  10. Simmonds MJ, Howson JM, Heward JM, Carr-Smith J, Franklyn JA, Todd JA et al. A novel and major association of HLA-C in Graves' disease that eclipses the classical HLA-DRB1 effect. Hum Mol Genet 2007; 16: 2149–2153. | Article | PubMed | ChemPort |
  11. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447: 661–678. | Article | PubMed | ISI | ChemPort |
  12. Remmers EF, Plenge RM, Lee AT, Graham RR, Hom G, Behrens TW et al. STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus. N Engl J Med 2007; 357: 977–986. | Article | PubMed | ISI | ChemPort |
  13. Vella A, Cooper JD, Lowe CE, Walker N, Nutland S, Widmer B et al. Localization of a type 1 diabetes locus in the IL2RA/CD25 region by use of tag single-nucleotide polymorphisms. Am J Hum Genet 2005; 76: 773–779. | Article | PubMed | ISI | ChemPort |
  14. Brand OJ, Lowe CE, Heward JM, Franklyn JA, Cooper JD, Todd JA et al. Association of the interleukin-2 receptor alpha (IL-2Ralpha)/CD25 gene region with Graves' disease using a multilocus test and tag SNPs. Clin Endocrinol (Oxf) 2007; 66: 508–512. | PubMed | ChemPort |
  15. Hafler DA, Compston A, Sawcer S, Lander ES, Daly MJ, De Jager PL et al. Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med 2007; 357: 851–862. | Article | PubMed | ISI | ChemPort |
  16. Weber F, Fontaine B, Cournu-Rebeix I, Kroner A, Knop M, Lutz S et al. IL2RA and IL7RA genes confer susceptibility for multiple sclerosis in two independent European populations. Genes Immun 2008; 9: 259–263. | Article | PubMed | ChemPort |
  17. Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet 2007; 39: 857–864. | Article | PubMed | ChemPort |
  18. Shibuya A, Campbell D, Hannum C, Yssel H, Franz-Bacon K, McClanahan T et al. DNAM-1, a novel adhesion molecule involved in the cytolytic function of T lymphocytes. Immunity 1996; 4: 573–581. | Article | PubMed | ISI | ChemPort |
  19. Dardalhon V, Schubart AS, Reddy J, Meyers JH, Monney L, Sabatos CA et al. CD226 is specifically expressed on the surface of Th1 cells and regulates their expansion and effector functions. J Immunol 2005; 175: 1558–1565. | PubMed | ChemPort |
  20. Lowe CE, Cooper JD, Brusko T, Walker NM, Smyth DJ, Bailey R et al. Large-scale genetic fine mapping and genotype–phenotype associations implicate polymorphism in the IL2RA region in type 1 diabetes. Nat Genet 2007; 39: 1074–1082. | Article | PubMed | ChemPort |
  21. Shibuya K, Lanier LL, Phillips JH, Ochs HD, Shimizu K, Nakayama E et al. Physical and functional association of LFA-1 with DNAM-1 adhesion molecule. Immunity 1999; 11: 615–623. | Article | PubMed | ISI | ChemPort |
  22. Ueda H, Howson JM, Esposito L, Heward J, Snook H, Chamberlain G et al. Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature 2003; 423: 506–511. | Article | PubMed | ISI | ChemPort |
  23. Shirakawa J, Shibuya K, Shibuya A. Requirement of the serine at residue 329 for lipid raft recruitment of DNAM-1 (CD226). Int Immunol 2005; 17: 217–223. | Article | PubMed | ChemPort |
  24. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD et al. Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001; 50: 121–127. | Article | PubMed | ISI | ChemPort |
  25. Thomson W, Barton A, Ke X, Eyre S, Hinks A, Bowes J et al. Rheumatoid arthritis association at 6q23. Nat Genet 2007; 39: 1431–1433. | Article | PubMed | ChemPort |
  26. Clayton DG, Walker NM, Smyth DJ, Pask R, Cooper JD, Maier LM et al. Population structure, differential bias and genomic control in a large-scale, case–control association study. Nat Genet 2005; 37: 1243–1246. | Article | PubMed | ISI | ChemPort |
  27. Cordell HJ, Clayton DG. A unified stepwise regression procedure for evaluating the relative effects of polymorphisms within a gene using case/control or family data: application to HLA in type 1 diabetes. Am J Hum Genet 2002; 70: 124–141. | Article | PubMed | ISI | ChemPort |
  28. Lewontin RC. The interaction of selection and linkage. I. General considerations; heterotic models. Genetics 1964; 49: 49–67. | PubMed | ISI | ChemPort |
  29. Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007; 449: 851–861. | Article | PubMed | ChemPort |
  30. IMSGC. The expanding genetic overlap between multiple sclerosis and type 1 diabetes. Genes Immun, 2008
  31. Seldin MF, Amos CI. Shared susceptibility variations in autoimmune diseases: A brief perspective on common issues. Genes Immun 2008.


We thank the Juvenile Diabetes Research Foundation, the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre and the Wellcome Trust for funding. We gratefully acknowledge the participation of all the patients and control subjects. We acknowledge use of the DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council and Wellcome Trust. We also thank The Avon Longitudinal Study of Parents and Children laboratory in Bristol and the British 1958 Birth Cohort team, including S Ring, R Jones, M Pembrey, W McArdle, D Strachan and P Burton for preparing and providing the control DNA samples. We thank Cristin Aubin at the Broad Institute. We thank Helen Schuilenburg and Nigel Ovington for data support as well as Oliver Burren for bioinformatics support. DNA samples were prepared by P Clarke, J Denesha, D Harrison, S Hawkins, M Himsworth, T Mistry, N Taylor and N Ubani. This study makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk. LSW is a Juvenile Diabetes Research Foundation/Wellcome Trust Principal Research Fellow. The Cambridge Institute for Medical Research is the recipient of a Wellcome Trust Strategic Award (079895).

Supplementary Information accompanies the paper on Genes and Immunity website (http://www.nature.com/gene)