IA-2 Autoantibodies in Incident Type I Diabetes Patients Are Associated with a Polyadenylation Signal Polymorphism in GIMAP5

ORIGINAL ARTICLE IA-2 autoantibodies in incident type I diabetes patients are associated with a polyadenylation signal polymorphism in GIMAP5

J-H Shin1, M Janer2, B McNeney1, S Blay1, K Deutsch2, CB Sanjeevi3, I Kockum4,A˚ Lernmark5 and J Graham1, on behalf of the Swedish Childhood Diabetes and the Diabetes Incidence in Sweden Study Groups 1Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada; 2Institute for Systems Biology, Seattle, WA, USA; 3Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; 4Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden and 5Department of Medicine, Robert H. Williams Laboratory, University of Washington, Seattle, WA, USA

In a large case-control study of Swedish incident type I diabetes patients and controls, 0–34 years of age, we tested the hypothesis that the GIMAP5 gene, a key genetic factor for lymphopenia in spontaneous BioBreeding rat diabetes, is associated with type I diabetes; with islet autoantibodies in incident type I diabetes patients or with age at clinical onset in incident type I diabetes patients. Initial scans of allelic association were followed by more detailed logistic regression modeling that adjusted for known type I diabetes risk factors and potential confounding variables. The single nucleotide polymorphism (SNP) rs6598, located in a polyadenylation signal of GIMAP5, was associated with the presence of significant levels of IA-2 autoantibodies in the type I diabetes patients. Patients with the minor allele A of rs6598 had an increased prevalence of IA-2 autoantibody levels compared to patients without the minor allele (OR ¼ 2.2; Bonferroni-corrected P ¼ 0.003), after adjusting for age at clinical onset (P ¼ 8.0 Â 10À13) and the numbers of HLA-DQ A1*0501-B1*0201 haplotypes (P ¼ 2.4 Â 10 À5) and DQ A1*0301-B1*0302 haplotypes (P ¼ 0.002). GIMAP5 polymorphism was not associated with type I diabetes or with GAD65 or insulin autoantibodies, ICA, or age at clinical onset in patients. These data suggest that the GIMAP5 gene is associated with islet autoimmunity in type I diabetes and add to recent findings implicating the same SNP in another autoimmune disease. Genes and Immunity (2007) 8, 503–512; doi:10.1038/sj.gene.6364413; published online 19 July 2007

Keywords: type I diabetes; GIMAP5; IA-2 autoantibodies; polyadenylation signal

Introduction years1,5 suggest that genetic factors alone do not explain the increased occurrence of type I diabetes. Type I diabetes is associated with an irreversible Environmental exposures triggering type I diabetes in autoimmune destruction of the pancreatic islet beta cells. genetically susceptible individuals remain to be estab- Therefore, patients depend entirely on daily insulin lished, although it has long been known that type I injection replacement therapy to regulate their blood diabetes may be diagnosed in conjunction with viral glucose levels. The etiology of type I diabetes is not infections.1 Also, maternal enterovirus infections have completely understood, but it is recognized that genetic been shown to increase risk for type I diabetes in their and environmental factors contribute to development offspring.1 and progression of the disease.1 The tendency for familial The association between HLA, the major histocompat- clustering2 and concordance rates in monozygotic com- ibility complex (MHC), and type I diabetes is well pared to dizygotic twins1,3 suggest that genetic factors established in humans and spontaneously diabetic play a role in etiology. However, the fact that only rodents.6 From sib-pair analyses, HLA-DR-DQ loci are 10–15% of children diagnosed with type I diabetes have a estimated to confer about 40%7 of genetic clustering to first degree relative with the disease,1,4 the low con- type I diabetes. Therefore, other susceptibility loci are cordance rates in identical diabetic twins1 and the needed to account for the remainder of genetic risk.8 worldwide increase in type I diabetes incidence in recent Four other genetic factors have been shown to confer risk to type I diabetes: the insulin gene on chromosome 11 (IDDM29,10), CTLA-4 on chromosome 2 (IDDM1211,12), Correspondence: Professor J Graham, Department of Statistics and PTPN22 on chromosome 113 and ITPR3 on chromosome Actuarial Science, Simon Fraser University, 8888 University Drive, 6.14 In addition, several candidate regions have been Burnaby, British Columbia, Canada V5A 1S6. 15 E-mail: [email protected] identified by linkage analysis with different degrees Received 30 April 2007; revised and accepted 20 June 2007; of confirmation.16,17 A recent meta-analysis of several published online 19 July 2007 independent genome scans conducted by the type I Association between IA-2A and GIMAP5 J-H Shin et al 504 diabetes genetics consortium (TIDGC) confirmed linkage prevalences in type I diabetes patients were: IAA 35%, at the HLA locus, chromosome 10, chromosome 16 and GADA 56%, IA-2A 57% and ICA 76%. Very high IA-2A chromosome 2.8 The positional cloning of genetic factors were found in 41% and very high ICA in 9% of patients. conferring risk is complicated in humans and candidate Age at onset ranged from 1.1 to 34.8 years, with a mean genes such as the INS VNTR,9 PTPN2213 as well as of 16.9 years. ITPR314 were identified in association rather than linkage studies. A recent genome-wide association study18 in Analysis strategy 2000 British type I diabetes patients and 3000 controls To investigate associations between the 56 SNPs in the identified, apart from HLA, CTLA-4, PTPN22, IL2RA/ GIMAP region and the 8 outcomes, one way to proceed CD25 and IFIH1/MDAS but not INS VNTR, five would be to test each of the 56 Â 8 ¼ 448 associations after independent association signals at chromosome 12q13, appropriate adjustment for confounding variables and 12q24, 16p13, 4q27 and 12p13. Furthermore, two addi- known risk factors. To make such adjustments, however, tional autoimmunity-related associations at 18p11 and detailed statistical modeling would be required for each 10p1518 were observed through the combined analysis of the eight outcomes. Therefore, we opted instead for a of autoimmune patients, including those with type I two-stage strategy in which suggestive unadjusted diabetes, indicating that autoimmunity also contributes associations between an outcome and SNPs were to type I diabetes risk. It is well known that islet identified in an initial screening step. Then, in the autoimmunity predicts and may precede the clinical second stage, associations between any outcomes and onset of type I diabetes by several years.19 It cannot be SNPs identified in the first stage were analyzed more excluded that, apart from genetic factors that confer risk carefully by adjusting for confounding variables and for type I diabetes, there are also genetic factors that known risk factors. contribute to islet autoimmunity. Candidate genes of autoimmune diabetes are also Allelic association scans identified in studies of spontaneously nonobese diabetic The results of allelic association scans are summarized in (NOD) mice20 and BioBreeding (BB) rats.21 While MHC Table 1. The strongest evidence for association was found class II genes are critical elements to both the NOD22 and between very high IA-2A and rs6598; the corresponding the BB rat,23 CTLA-4 in the NOD mouse22 and the association profile is shown in Figure 3, along with the lymphopenia gene GIMAP5 in the BB rat21 are contribut- 95% critical value adjusted for multiple testing of SNPs, ing genetic factors. drawn as a horizontal line. All four of the significantly In BB rats, lymphopenia, which is essential for associated SNPs are in or proximal to the last exon of diabetes, has been shown to be due to a frameshift GIMAP5 and are in high LD with one another (min mutation in the GIMAP5 gene, a member of a multigene r2 ¼ 0.94). There is one SNP in this subregion, rs2286899, family of antiapoptopic genes.21,24 In the present study, that was not in LD with any of the associated SNPs (max we investigated whether GIMAP5 (human ortholog of BB r2 ¼ 0.37) and was not associated with very high IA-2A rat GIMAP5) affects type I diabetes, by analyzing (adjusted P ¼ 0.98). The remaining SNPs in this sub- associations between single nucleotide polymorphisms region are associated with very high IA-2A and form a (SNPs) in the 400 kb region spanning the human GIMAP signal centered at rs6598, the most strongly associated gene family and outcomes related to type I diabetes, SNP (see Figure 3). Proceeding in the 50–30 direction, one including islet autoantibodies, taking into account of the associated SNPs (rs1046355) is a synonymous SNP potential confounding variables and known risk factors in the coding region of the exon of GIMAP5, two of the such as HLA-DQ haplotypes. associated SNPs (rs10361, rs6598) are in the 30 untranslated region (30-UTR) of GIMAP5, and the last of the associated SNPs (rs2286898) is approximately 140 base Results pairs downstream of the last exon in an intergenic region. The 30-UTR of GIMAP5 has two polyadenylation Selected SNPs signals (PAS) listed in the PolyA_DB. The SNP rs6598 is A total of 67 SNPs spanning the human cluster of GIMAP the fifth base of six in the upstream PAS. According to genes were typed. Five SNPs failed the test of Hardy– dbSNP (build 127), in non-African populations, the Weinberg proportions (HWP) in controls at the 1% level major allele of rs6598 is G and the minor allele is A. and 11 failed at the 5% level. To be conservative, we Interestingly, the minor allele of rs6598 yields the removed the 11 SNPs that failed at the 5% level, leaving canonical PAS (AATAAA) associated with approxi- 56 SNPs for analysis. The positions of these SNPs relative mately 58.2% of polyadenylated expressed sequence tags to genes in the GIMAP region are displayed in Figure 1, (ESTs), while the major allele yields a rare PAS along with pairwise measures of their linkage disequili- (AATAGA) associated with only 0.7% of polyadenylated brium (LD) in control subjects. ESTs.25 Thus, in the Swedish population, the SNP rs6598 causes a switch from a rare PAS with the major G-allele Outcome measures to the canonical PAS with the minor A-allele. Eight outcome measures were investigated: type I diabetes status (case or control); islet autoantibody Detailed association analysis positivity in incident type I diabetes patients for The only outcome with suggestive associations (Po0.05) autoantibodies (IAA), glutamate decarboxylase (GADA), was very high IA-2A, with four associated SNPs. From IA-2A, islet cell antibodies (ICA), very high IA-2A and these four SNPs, we chose the most strongly associated, very high ICA and age at clinical onset in incident type I that is rs6598, for detailed analysis. The high pairwise LD diabetes patients. The autoantibody cutoff levels used in between the four SNPs (see Figure 1) suggests that our analyses are shown in Figure 2. Autoantibody detailed analyses of the associations between very high

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 505

LR8

GIMAP3P rs6598 GIMAP5

GIMAP1

GIMAP2

GIMAP6 LOC643852

GIMAP4

ATQL3

GIMAP7

GIMAP8

LOC728743 (Physical Length:469kb) MGC33584 REPIN1

RARRES2 C7orf29 Color Key LRRC61

0 0.2 0.4 0.6 0.8 1 Figure 1 Heat map of pairwise linkage disequilibria (LD) for 56 single nucleotide polymorphisms (SNPs) spanning the GIMAP family of genes in Swedish controls. The relative positions of the SNPs are indicated on the inner diagonal line, by line segments. The relative positions of all genes known in the region are indicated on the outer diagonal line. Each pixel represents pairwise linkage disequilibrium (LD), which is measured by the squared allelic correlation coefficient r2 between two SNPs. The pixel in the ith row from the bottom and the jth row from the left represents LD between the (i þ 1) and jth SNPs, proceeding from the bottom left to the top right corner on the diagonal line. As indicated by the color key, stronger LD is represented by red and weaker by white.

IA-2A and each of these SNPs would be very similar. higher in younger than older patients: 50% of 0- to Moreover, rs6598 appears to be the most plausible as a 6-year-olds (95% CI 41–59), 54% of 7- to 13-year-olds functional polymorphism in GIMAP5. We used multiple (47–60), 40% of 14- to 20-year-olds (33–48), 28% of 21- logistic regression modeling26 to examine the association to 27-year-olds (21–36) and 16% of 28- to 34-year-olds between very high IA-2A and rs6598, taking into account (9–22). Likelihood ratio tests of regression coefficients in potential confounding variables gender and age and the base model confirmed that very high IA-2A were HLA-DQ haplotypes, which are known risk factors. For negatively associated with DQ2 (P ¼ 2.5 Â 10À5) and age this detailed analysis, we considered 669 type I diabetes at onset (P ¼ 8.0 Â 10À13), and positively associated with patients with information on IA-2A, gender, HLA-DQ DQ8 (P ¼ 0.002). haplotypes, age at onset and rs6598 genotypes. Our next step was to add rs6598 to the base model as a A base logistic regression model relating very high IA- predictor of very high IA-2A. To avoid problems with 2A to gender, HLA-DQ haplotypes and age at onset, but sparse data for A/A genotypes (Table 2), we combined excluding rs6598, was determined as described in the A/A and G/A genotypes into one category. The final Supplementary material. The resulting model included model after forward selection included a term for rs6598 terms for HLA-DQ2, HLA-DQ8 and age. The unadjusted (zero versus one or more copies of the A allele), but frequencies of very high IA-2A support the base model. no statistical interactions involving rs6598. As shown These frequencies decrease with the number of DQ2 in Table 2, the unadjusted frequencies of very high haplotypes: 50% of patients with no DQ2 haplotypes IA-2A were higher in patients with at least one copy (95% CI 44–55), 36% of patients with one DQ2 haplotype of the minor allele A of rs6598. A likelihood ratio (95% CI 31–42) and 9% of patients with two DQ2 test confirmed the association between IA-2A and haplotypes (95% CI 2–25); and increase with the number rs6598 (P ¼ 7.2 Â 10À6). After Bonferroni correction for of DQ8 haplotypes: 28% of patients with no DQ8 56 Â 8 ¼ 448 tests, the association was still significant haplotypes (95% CI 22–35), 46% of patients with one (P ¼ 0.003). Fitted prevalences of very high IA-2A, by DQ8 haplotype (95% CI 41–51) and 59% of patients with rs6598 genotype group in patients with 0 DQ2 and 1 DQ8 two DQ8 haplotypes (95% CI 45–72). Frequencies are haplotype, are shown in Figure 4, plotted against age at

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 506 Control subjects T1D patients 550

200 IAA 100

–0.4 0.80 10 73.8 –0.4 0.80 10 73.8

650

400

GADA 200

048048

Frequency 375

200

IA–2A 100

–0.020.05 0.39 1 2 –0.02 0.05 0.39 1 2

700

200 ICA 100

0 0 300 570000 0 300 570000 Antibody measurement Figure 2 Histograms of antibody measurements in control subjects and incident patients with type I diabetes. Control subjects are shown in the left column and patients in the right column. Of 702 control subjects, 668 (95.2%), 682 (97.2%), 700 (99.7%) and 671 (96.5%) individuals had antibody measurements on autoantibodies (IAA), glutamate decarboxylase (GADA), ICA512/IA-2A and islet cell antibodies (ICA), respectively. Of 1006 patients, 964 (95.8%), 973 (96.7%), 1004 (99.8%) and 937 (93.1%) had antibody measurements on IAA, GADA, ICA512/ IA-2A and ICA, respectively. Each horizontal axis describes the log-transformed antibody measurements but is labeled in the original scale of measurement. Cutoffs declaring antibody-positivity are indicated by dashed lines, and are 40.8, 40.07, 40.05 and 40 in the original scale of measurement for IAA, GADA, IA-2A and ICA, respectively. Cutoffs declaring very high antibody status are indicated by dot-and-dashed lines, and are 40.39 and 4511 for ICA512/IA-2A and ICA, respectively, in the original scale of measurement.

onset. After controlling for DQ2, DQ8 and age at onset, significant finding.28 We extended the FPRP to multiple the odds of very high IA-2A for patients with the minor testing of associations in a candidate region by defining

allele of rs6598 were estimated to be 2.2 times those for FPRPM to be the chance that no associations are true patients without the minor allele (Bonferroni-corrected given at least one significant finding. As recommended,28

95% CI 1.1–4.2). we selected the significance level so that FPRPM would be less than 50% for all Bonferroni-corrected P-values Incorporating prior probability of association lower than the level. Since the GIMAP5 homologous In light of an increasing number of nonreplicable region is linked to type I diabetes in the BB rat, we association reports, there has been a call to incorporate propose a prior probability of association in humans of at prior probabilities of association into the determination least 1/10, but to be conservative we also considered of significance levels to maintain reasonable rates of true prior probabilities as low as 1/50. To control the FPRPM positive findings.27 Appropriate significance levels for at 50% with prior probabilities of 1/10, 1/20 and 1/50, the Bonferroni-corrected P-value were determined using the appropriate levels against which to compare the the concept of the false-positive report probability Bonferroni-corrected P-value are 0.034, 0.0121, and (FPRP), the probability of no true association between a 0.0034, respectively. Our P-value of 0.003 is less than all genetic variant and an outcome given a statistically these levels.

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 507 Table 1 Summary of the strongest allelic association in the Table 2 Distribution of very high IA-2A status in patients GIMAP region for each outcome according to rs6598 genotype

Outcome Most significant association P-valuea Number (%) of patients

Type I diabetes rs1047575 0.21 Very high IA-2A

b Positive antibody status and age Yes No GADA rs3757409 0.27 ICA512/IA-2A rs1047575 0.07 ICA hCV222137 0.10 Total 280 (41.9) 389 (58.1) IAA rs3757410 0.68 Age rs3735169 0.05 Original genotype A/A 33 (45.8) 39 (54.2) Very high antibody statusb G/A 147 (50.9) 142 (49.1) ICA512/IA-2A rs6598 0.02c G/G 100 (32.5) 208 (67.5) ICA hCV11565157 0.83 Combined genotype A+ (A/A or G/A) 180 (49.9) 181 (50.1) Abbreviations: GADA, glutamate decarboxylase autoantibodies; AÀ (G/G) 100 (32.5) 208 (67.5) IA-2A, islet antigen-2 autoantibodies; ICA, islet cell autoantibodies; IAA, insulin autoantibodies. aAdjusted for multiple testing of 56 single nucleotide polymorph- 1 isms but not for multiple testing of 8 outcomes. 0 DQ2 & 1 DQ8 A+ (A/A or G/A) bIn type I diabetes patients only. cMinor allele (A) more frequent in type I diabetes patients with very A: Minor allele high IA-2A (A 38%, G 62%) than in patients without very high IA- 2A (A 29%, G 71%). 0.8

3.5 rs6598 0.6

3.0 adjusted p value 0.05 0.4 2.5

2.0 0.2

1.5

0 Association signal

1.0 0 5 10 15 20 25 30 35

0.5 Figure 4 Fitted prevalences of very high IA-2A (ICA512) against age at onset by rs6598 genotype grouping in type I diabetes patients with 0 DQ2 and 1 DQ8 haplotype. The effect of rs6598 is significant 0.0 after adjusting for 56 Â 8 ¼ 448 tests (unadjusted P ¼ 7.2 Â 10À6; Bonferroni-corrected P ¼ 0.003). 149400 149500 149600 149700 149800 149900 Physical distance (kb)

Figure 3 Profile of allelic association between very high IA-2A islet autoimmunity to overt hyperglycemia. Indeed, (ICA512) and GIMAP single nucleotide polymorphisms (SNPs) in patients. The P-value threshold has been adjusted for multiple high-level IA-2A have been reported as the best marker testing of 56 SNPs, but not for multiple testing of 8 outcomes. for ensuing hyperglycemia in subjects at risk for type I diabetes.30 The SNP resides in a PAS of the GIMAP5 gene, with the minor allele (A) leading to the canonical Discussion PAS and the major allele (G) leading to a noncanonical PAS.25 After adjusting for HLA-DQ2 (P ¼ 2.4 Â 10À5) and Type I diabetes is often viewed as a ‘two-step’ disease: -DQ8 (P ¼ 0.002) haplotypes, as well as age at onset the first step is to trigger islet autoimmunity. The second (P ¼ 8.0 Â 10À13), patients having one or two copies of the step, which may take months to years, is progression canonical PAS are more likely to have very high IA-2A from islet autoimmunity to overt hyperglycemia. In the than patients homozygous for the noncanonical PAS present study, we confirm a lack of association between (unadjusted P ¼ 7.2 Â 10À6,OR¼ 2.2, 95% CI ¼ 1.5–3.0). type I diabetes and GIMAP5.29 However, we do find that Adjusting for HLA-DQ haplotypes is important because high-level IA-2A are associated with the SNP rs6598 in we have previously shown31 that IA-2A levels in patients newly diagnosed patients. Thus, we speculate that this are negatively associated with HLA-DQ2 but positively SNP is associated with the first step triggering islet associated with HLA-DQ8. After a conservative Bonfer- autoimmunity, but not the second step progressing from roni correction for 56 Â 8 ¼ 448 association tests, the

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 508 adjusted association that was observed between very diabetes may be explained through two distinct path- high IA-2A and rs6598 was still significant (P ¼ 0.003). ways distinguished by IA-2A status. Positivity for DQ2/ The SNP rs6598 is in one of two PASs in the 30-UTR of 8 heterozygosity and IA-2A defined in their study a more GIMAP5; the PAS in which it resides leads to the shorter homogeneous high-risk population.30 This is consistent transcript. Since both PASs are in the 30-UTR, the short with several reports indicating that the appearance of IA- and long transcripts code for the same protein. The SNP 2A is the best marker for the clinical onset.38 High-level rs6598 has recently been implicated in systemic lupus IA-2A as a particular risk factor now needs to be erythematosus.32 These authors found that variation at explored in relation to the GIMAP5 gene and the way this SNP has no effect on transcript levels, but that the GIMAP5 protein affects T-cell development and individuals with one or two copies of the canonical PAS survival.39 (A) tend to have a higher proportion of the shorter The observation that islet autoantibodies are asso- mRNA transcript than individuals homozygous for the ciated with genetic factors that also contribute to the risk noncanonical PAS (G). Therefore, the association that we for type I diabetes is not novel. We were the first to have observed with very high IA-2A suggests that an demonstrate,31 as later confirmed by others,40 that the increased proportion of the shorter mRNA transcript INS VNTR on chromosome 11 is associated with IAA. increases the risk for very high IA-2A. Differential The association between INS VNTR and IAA is thought transcript length may affect levels of the translated to be linked to levels of insulin expressed in the thymus protein, for example, through differences in stability or and the ability of individuals to delete self-reactive T translatability of transcripts of different lengths,33 and cells. Recent studies suggest furthermore that PTPN22 on has been linked to a variety of diseases such as mantle chromosome 1, which strongly regulates T-cell function, cell lymphoma.34 Alternately, rs6598 may have no effect is associated not only with type I diabetes, but also with on the risk for very high IA-2A, but rather could be in LD IAA and progression to disease.41 The present study as with an unobserved functional polymorphism that does well as those of PTPN22 and INS VNTR therefore have effect. underscores the importance of dissecting type I diabetes GIMAP5 is believed to contribute to T-cell develop- risk not only with clinical onset as an end point, but also ment and survival through apoptosis. Some studies35,36 with islet autoantibodies as disease markers. Such an suggest that GIMAP5 is antiapoptotic. However, a recent approach may elucidate mechanisms that trigger islet report37 has shown that transient overexpression of autoimmunity, progression to clinical disease or both. In human GIMAP5 is apoptotic in naive T cells. These large, at-risk cohorts such as those of the DPT-1 and authors hypothesize that the apoptotic effect of GIMAP5 ENDIT trials or the longitudinal TEDDY study, it will be depends on the context and factors such as activation of interest to explore the possible role of the PAS status of the T cell, availability of growth factors and the polymorphism and other polymorphisms in the GIMAP5 presence of toxic compounds. Given the apparent gene in the development of high-level IA-2A. complexity of the effect of GIMAP5 on T-cell develop- In conclusion, the present study suggests that the ment and survival, it is difficult to speculate on a specific GIMAP5 gene, which contributes to T-cell development mechanism by which it influences IA-2 autoantibody and survival, may be associated with an increased risk levels. Over- or underexpression of GIMAP5 may for the development of high-level IA-2A. The appearance promote apoptosis and death of regulatory T cells that of IA-2A are reported to be associated with clinical onset protect from autoimmunity, or may prevent IA-2 auto- of type I diabetes and it will be of interest in future reactive T cells from dying by apoptosis. studies of individuals with increased HLA genetic risk A novel feature of the statistical analysis was our for type I diabetes to determine the possible importance attempt to control the probability that a significant result of the GIMAP5 gene for IA-2A as a marker of subsequent reflects a true association. Controlling this FPRP28 has clinical onset. been proposed as a way to reduce the number of nonreplicable association reports for complex genetic disorders.27 We determined levels of statistical significance taking into account the prior probability of an Research design and methods association with GIMAP5. Since the GIMAP5 homolo- Subjects gous region is linked to lymphopenia and type I diabetes The current study is based on two Swedish population- in the BB rat, we propose a prior probability of based matched case-control studies described else- association in humans of at least 1/10. To be conserva- where.4,42 The first study included incident type I tive, however, prior probabilities as low as 1/50 were diabetes patients who were younger than 15 years and considered. For this range of prior probabilities, the diagnosed anywhere in Sweden between 1 September chance that the reported association with GIMAP5 is 1986 and 31 December 1987. In the second case-control false is below 50%. Hence, the observed association study, the incident type I diabetes patients were aged between rs6598 and very high IA-2A in patients is 15–34 years and diagnosed between 1 January 1987 and noteworthy. 31 December 1988. All patients were diagnosed and To our knowledge, this is the first time a genetic factor classified according to the World Health Organization such as GIMAP5 known to be important to spontaneous (WHO) criteria. For patients older than 7 years, up to two diabetes in the BB rat21,24 is found to be associated with controls matched by age, gender and geographic region IA-2A, an islet autoantibody that is strongly associated were selected from the Swedish national population with type I diabetes risk. Moreover, the association is registry. For patients aged 7 or less, a matched control with high-level IA-2A, reported by others to be the best treated at the hospital for reasons other than diabetes predictor of the clinical onset of type I diabetes.30 These was selected as described.4 Since regional systems for the authors reported that the HLA-DQ-inferred risk of two studies did not coincide, subjects from the study of

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 509 Table 3 Number (%) of incident type I diabetes patients and p0.1 in the Swedish population were discarded. Three control subjects in relation to age, gender and geographical location other failed SNP assays were also discarded. Our aim was to cover all genes in the region and have at least 1 Control subjects Patients SNP every 10–15 kb for the intergenic regions. We achieved this goal for most intergenic regions. Total 702 (100) 1006 (100) A total of 67 SNPs covering the GIMAP cluster of genes on human chromosome 7 were genotyped using Age distribution (years) 0–6 54 (7.7) 131 (13.0) the MassArray genotyping system (Sequenom Inc., San 14 7–13 310 (44.2) 315 (31.3) Diego, CA, USA) as described. In brief, multiplex 14–20 154 (21.9) 220 (21.9) SNP assays were designed using SpectroDESIGNER 21–27 74 (10.5) 179 (17.8) software (Sequenom), and 384-well plates containing 28–34 109 (15.5) 158 (15.7) 5 ng of DNA in each well were amplified by PCR Missing 1 (0.1) 3 (0.3) following Sequenom’s specifications. Allele discrimina- Gender distribution tion was accomplished through primer extension reac- 46 Female 339 (48.3) 417 (41.5) tions using the HME chemistry. Following the Male 363 (51.7) 589 (58.5) extension assays, genotypes were determined by spot- ting 15 nl of each sample onto a 384 SpectroCHIP and Geographical distribution (north to south) reading the chip using the matrix assisted laser deso- Umea˚ 102 (14.5) 128 (12.7) rption/ionization time-of-flight (MALDI-TOF) mass Uppsala 152 (21.7) 205 (20.4) Stockholm 105 (15.0) 206 (20.5) spectrometer. Mass determination and correlated geno- Linko¨ping 118 (16.8) 140 (13.9) type were determined in real time with MassARRAY RT Go¨teborg 129 (18.4) 198 (19.7) software. Genotyping failure rates for the 67 SNPs Lund 96 (13.7) 129 (12.8) ranged from 3 to 16%; failure rates for the 56 SNPs used in our analyses ranged from 3 to 11%.

Immune markers 0- to 14-year-olds were reassigned to the six regions Insulin antibodies. IAA as well as antibodies to insulin defined for the study of 15- to 34-year-olds based on the were measured by radiobinding assay using acid– location of the referring hospital. Combination of the charcoal extraction and cold insulin displacement as studies leads to a total of 1006 incident patients with type described.47 IAA-D percent measurements were available I diabetes and 702 control subjects (Table 3). For the on 964 of the 1006 patients (96%) and 668 of the 702 current investigation of GIMAP5, sufficient DNA was control subjects (95%). However, in 210 patients with available to genotype 819 of these type I diabetes patients IAA measurements, sera were sampled 3 weeks after and 595 of the controls. beginning insulin therapy, precluding reliable IAA testing.42 These patients were therefore excluded from Genetic markers the analysis of IAA. Between 73 and 80% of patients with HLA (IDDM1). HLA typing of DQA1 and DQB1 was IAA measurements were genotyped at each of the 56 performed by PCR amplification of the second exon of SNPs considered in our analysis of GIMAP5. the genes followed by dot blot hybridizations of sequence-specific oligo probes and by restriction frag- GADA autoantibodies. Antibodies to radiolabeled hu- ment-length polymorphism using DR- and DQ-based man Mr 65 000 GADA were quantified by fluid-phase probes to establish haplotypes.43,44 HLA-DQ genotypes immunoprecipitation assay using fluorographic densito- were already available on 871 of the 1006 patients (87%) metry as described48,49 except that for 15- to 35-year-olds, and 620 of the 702 control subjects (88%). GAD65 were radiolabeled by coupled in vitro transcription and translation, as described.50,51 The two assay GTPase of the immunity-associated protein family member formats correlate well, and autoantibody levels are 5 (GIMAP5). Other aliases for GIMAP5 include expressed as GADA index,50 using the WHO–Juvenile IAN4, Ian4l1 and Ian5. SNPs spanning the GIMAP family Diabetes Foundation (JDF) standard52 as the positive of genes were selected from publicly available SNPs control. GADA measurements were available on 973 of in the dbSNP (http://www.ncbi.nlm.nih.gov/SNP/), the 1006 patients (97%) and 682 of the 702 control HGVbase (http://hgvbase.cgb.ki.se/) and Celera (no subjects (97%). Between 72 and 78% of patients with longer in existence) databases. SNPs within the approxi- GADA measurements were genotyped at each of the 56 mately 500 kb containing the human cluster of GIMAP SNPs considered in our analysis of GIMAP5. genes (Chr7: 149335490–149813248, Golden Path, April 2003) were downloaded into our in-house database Islet antigen-2 (IA-2) or ICA512 autoantibodies. Antibo- SBEAMS-SNP and merged onto a common reference dies to IA-2 (ICA512)53,54 were measured by radiobinding sequence (Golden Path sequence, April 2003). A subset immunoassay.55 The 30 portion of the ICA512 cDNA56 was selected for typing by using the MAGMA algo- corresponding to the cytoplasmic portion of the protein rithm.45 The SNP selection was optimized to cover the (residues 602–979) was amplified by RT-PCR from targeted region such that SNPs within genes were human HTB-14 glioblastoma cells as described.53 After prioritized over those in intergenic regions and to select expression in DH10B Escherichia coli, sequenced plasmid SNPs with higher validation status. A total of 90 SNPs DNA was identical to GenBank sequence L18983. In vitro were initially identified by this process and were translation with 35S-methionine50 yielded a 46-kDa IA-2 validated on 32 samples. After validation, 20 SNPs that polypeptide highly precipitable by diabetes sera. Radio- either were constant or had minor allele frequencies binding assays used protein A-Sepharose to separate

Genes and Immunity Association between IA-2A and GIMAP5 J-H Shin et al 510 antibody bound from free IA-2, and autoantibody levels high LD was observed between some pairs of SNPs in are expressed as an IA-2A index,50 using the WHO–JDF the GIMAP region (Figure 2). The peak association signal standard as a positive control.52 IA-2A measurements (that is, minimum P-value) over all SNPs was used as the were available on 937 of the 1006 patients (93%) and 671 test statistic and its null distribution was estimated from of the 702 control subjects (96%). Between 71 and 78% of 10 000 permutations of the outcome. The 95% critical patients with IA-2A measurements were genotyped at value accounting for multiple testing of SNPs, but not for each of the 56 SNPs considered in our analysis of multiple testing of outcomes, is the 5th percentile of this GIMAP5. permutation null distribution. A P-value accounting for multiple testing of SNPs is taken as the percentile of Islet cell (cytoplasmic) antibodies. ICA were determined this permutation null distribution corresponding to the by indirect two-color immunofluorescence using blood observed P-value from the association scan. This correc- group O frozen human pancreas.56 The same pancreas tion for multiple testing of SNPs will be conservative for was used throughout the study. Coded slides were all but the minimum P-value observed. evaluated by two independent observers. Samples were titered in doubling dilutions to determine end points for Incorporating the prior probability of association.We conversion into JDF units57 as described.56 ICA of 0 JDF extended the concept of the FPRP28 to multiple testing

units corresponded to no detectable antibody. ICA of associations by defining FPRPM to be the chance that measurements were available on 1004 of the 1006 no associations are true given at least one significant patients (99.8%) and 700 of the 702 control subjects finding. To simplify calculations, we made the conserva- (99.7%). Between 71 and 77% of patients with ICA tive assumptions of independent association tests and at measurements were genotyped at each of the 56 SNPs most a single causal association. The same prior considered in our analysis of GIMAP5. probability of association was assumed for each possible SNP-outcome combination. Under these assumptions, Statistical and bioinformatical methods the P-value threshold depends on the prior probability of All statistical analyses were performed in the freely an association with the genomic region, the specified 58 available R statistical computing environment with FPRPM value (for example, 50%) and the average power user-contributed add-on packages. The genetics pack- of the tests. Power to detect associations with type I age59 was used to test for HWP in controls at level 5%. diabetes was calculated assuming a multiplicative odds Patterns of LD in controls were visualized using the model, an odds ratio (OR) of 1.5 and HWP. We used the LDheatmap package60 and the r2 measure.61 The posi- observed number of patients and controls genotyped at tions of SNPs were investigated with the UC Santa Cruz an SNP and the observed minor allele frequency in Genome Browser62 using the most recent available controls. Power to detect associations with antibody reference sequence (NCBI Build 36.1, March 2006). status was similarly calculated based on the numbers of Further information on GIMAP5 poly(A) sites and their patients with positive antibody status genotyped at an signals was obtained from PolyA_DB.63 SNP, the observed minor allele frequency in patients with negative antibody status and an OR of 1.5. Power Outcome measures. Cutoffs for declaring antibody posi- to detect associations with age-at-onset in patients was tivity were determined as described,31 by examining calculated based on a t-test constructed from the quantile–quantile (Q–Q) plots of log-transformed anti- estimated regression coefficient in an ordinary least body measurements in patients and controls. Antibody- squares regression of age onto the number of copies of positive patients were classified as moderate or very the minor allele, under the alternative hypothesis that the high based on histograms of the log-transformed true regression coefficient had a value of 1.5. measurements in patients. If neither Q–Q plots nor histograms suggested distinct subpopulations of antibody-positive individuals, very high antibody status was not determined. The outcome measures considered for Acknowledgements analysis were type I diabetes status (case or control); antibody positivity in patients for IAA, GADA, IA-2A, The MAGENTA study was funded by Juvenile Diabetes ICA, very high IA-2A and very high ICA and age at Research Foundation International grant 1-2001-873 to onset in patients. A˚ L. JS, BM and SB also received support from Canadian Institutes of Health Research grants NPG-64869 and Allelic association scans. Association scans were run for ATF-66667, Natural Sciences and Engineering Research each of the eight outcome measures. Each scan com- Council of Canada grants 213124-03 and 227972-00 prised P-values from association tests at 56 SNPs. For and the Mathematics of Information Technology and type I diabetes and antibody status in patients, each Complex Systems, Canadian Networks of Centres of P-value was obtained from a chi-square test of allelic Excellence. JS and JG have fellowships from the Michael association. For type I diabetes age at clinical onset in Smith Foundation for Health Research. CBS is supported patients, the P-value was obtained from a t-test of the by a grant from the Swedish Medical Research Council regression coefficient in an ordinary linear regression of (K2006-72X-14740-04-3). IK is supported by a career age onto the number of copies of the minor allele. Each development award from the Juvenile Diabetes Founda- SNP-specific P-value was transformed to reflect the tion International (2-2000-570). We thank William Hago- strength of evidence for association by taking the pian, Mona Landin-Olsson and Jerry Palmer for access to negative base-ten logarithm. For each of the eight data on the autoantibody markers. outcomes considered, we adopted a permutation ap- The following authors are from the Diabetes Incidence proach to adjust for multiple testing of 56 SNPs, since in Sweden Study Group: Hans Arnqvist, Department of

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