OBJECTIVE—In stage 1 of our genome-wide association (GWA) study for type 1 diabetes, one locus at 16p13 was detected (P = 1.03 × 10−10) and confirmed in two additional cohorts. Here we describe the results of testing, in these additional cohorts, 23 loci that were next in rank of statistical significance.

RESEARCH DESIGN AND METHODS—Two independent cohorts were studied. The Type 1 Diabetes Genetics Consortium replication cohort consisted of 549 families with at least one child diagnosed with diabetes (946 total affected) and DNA from both parents. The Canadian replication cohort consisted of 364 nuclear family trios with one type 1 diabetes–affected offspring and two parents (1,092 individuals).

RESULTS—One locus at 12q13, with the highest statistical significance among the 23, was confirmed. It involves type 1 diabetes association with the minor allele of rs1701704 (P = 9.13 × 10−10, OR 1.25 [95% CI 1.12–1.40]).

CONCLUSIONS—We have discovered a type 1 diabetes locus at 12q13 that is replicated in an independent cohort of type 1 diabetic patients and confers a type 1 diabetes risk comparable with that of the 16p13 locus we recently reported. These two loci are identical to two loci identified by the whole-genome association study of the Wellcome Trust Case-Control Consortium, a parallel independent discovery that adds further support to the validity of the GWA approach.

Type 1 diabetes, a multifactorial disease with a strong genetic component, is due to the autoimmune destruction of pancreatic β-cells. The major type 1 diabetes susceptibility locus, mapping to the HLA class II genes at 6p21 (1) and encoding highly polymorphic antigen-presenting proteins, accounts for less than half of genetic type 1 diabetes risk (2). The remainder is accounted for by many loci with more modest effects, of which only a few are known. These include 1) the insulin (INS) VNTR (variable number tandem repeats) (3) modulating thymic expression of and tolerance to insulin, a major type 1 diabetes autoantigen (4,5); 2) the Arg620Trp single nucleotide polymorphism (SNP) at PTPN22, which affects the function of a negative regulator of T-cell receptor signaling (6); 3) noncoding SNPs at IL2RA (79), which encodes the α-chain of the IL2 receptor complex (CD25), an important modulator of immunity; and 4) variants in the CTLA4 locus (10) whose protein product transmits inhibitory signals to attenuate T-cell activation. It is worth noting that all of these type 1 diabetes–associated genes are expressed in cells with immune function, and all except INS have been associated with other autoimmune disorders. Together, these loci explain over half of the genetic type 1 diabetes risk, the remaining of which is composed of loci whose number and effect size are still unknown. It is also worth remarking that these known loci represent the “low-hanging fruit,” involving candidate genes whose importance in autoimmunity was already known, thus limiting the value of genetic discovery to generate previously unsuspected physiological insights.

The recent development of high-throughput genotyping array technologies has enabled us (11) and others (12,13) to perform genome-wide association (GWA) studies in search of the remaining type 1 diabetes loci. The first successful use in type 1 diabetes involved the screening of 12,000 nonsynonymous SNPs, which found type 1 diabetes association with rs1990760, involving an Ala946Thr substitution on the IFIH1 (interferon-induced with helicase C domain 1) gene (14). More recently, the Wellcome Trust Case-Control Consortium (WTCCC) tested 2,000 type 1 diabetic case and 3,000 control subjects for 500 k SNPs (Affymetrix GeneChip) (12), and four novel associations (12q24, 12q13, 16p13, and 18p11) were solidly replicated in 4,000 case and 5,000 control subjects, plus an additional 2,997 type 1 diabetic family trios, by the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (13). Our stage 1 results, which have recently been published (11), report one novel type 1 diabetes locus at Chr16p that reached genome-wide significance in stage 1 and coincided with one of the novel WTCCC findings. We used the Illumina Hap550 array to type 550 k SNPs, selected to tag most of the haplotype structure of the human genome, per phase 2 of the International HapMap project (http://www.hapmap.org). A set of 483 subjects with type 1 diabetes and both parents of each subject in addition to 563 type 1 diabetic probands and 1,146 control subjects, all of European ancestry, were examined. For the case-control data, population stratification was corrected by principal component analysis in the EIGENSTRAT implementation (15).

Both studies independently mapped this association to a 300-kb linkage disequilibrium (LD) block on 16p encompassing two genes of unknown function, KIAA0350 (now renamed C-type lectin 16A, symbol CLEC16A) and LOC642451.

Pending completion of a full stage 2, in which the 1,536 markers with the highest statistical significance will be tested in additional cohorts, we decided to fast track 24 SNPs (23 distinct loci) that, in rank of statistical significance, came next to the 16p locus. This number was arbitrarily determined by the multiplexing capacity of our genotyping platform and corresponds to a cut off of ∼10−4 (supplementary Table 1 [available in an online appendix at http://dx.doi.org/10.2337/db07-1305). The power of our GWA to detect a range of effect sizes at that level is given in supplementary Fig. 1.

The sample sets used for GWA scanning have been previously described in detail (11). The Type 1 Diabetes Genetics Consortium replication cohort consisted of 549 families with at least one child diagnosed with diabetes (946 total affected) and DNA from both parents available as of the July 2005 data freeze (https://www.t1dgc.org). The samples were collected in Europe, North America, and Australia, and most subjects were of European ancestry. Criteria were age at diagnosis <35 years and uninterrupted treatment with insulin within 6 months of diagnosis. For siblings of probands diagnosed under the age of 35 years, the age-at-diagnosis limit was extended to 45 years if they were lean and had positive antibodies and/or low C-peptide levels at diagnosis. The Canadian cohort consisted of 364 nuclear family trios with one type 1 diabetes–affected offspring and two parents (1,092 individuals). The samples were collected in pediatric diabetes clinics in Montreal, Toronto, Ottawa, and Winnipeg. All patients were diagnosed under the age of 18 years and were treated with insulin since diagnosis, and none has stopped treatment for any reason since. Ethnic backgrounds were of mixed European descent. The research ethics board of the Montreal Children's Hospital and other participating centers approved the study, and written informed consent was obtained from all subjects.

Genotyping.

Genotypes for this study were obtained using the Sequenom iPLEX assay (Sequenom, Cambridge, MA). The 90 CEUs (European-descent individuals genotyped in HapMap) were included as accuracy control subjects. The call rate of each of the three 12q13 SNPs was >98.2%, and no Mendelian error was found. The genotypes of each SNP were in Hardy-Weinberg equilibrium in the parents.

Statistics.

Type 1 diabetes association was tested by the Family Based Association Test (FBAT) software (http://www.biostat.harvard.edu/∼fbat/fbat.htm) (16), based on the transmission disequilibrium test method. Considering that most of the Type 1 Diabetes Genetics Consortium families have multiple siblings, the option of the empirical variance was used in the FBAT statistics to permit a robust but unbiased test of genetic association. The age-of-onset effect of the SNPs in type 1 diabetic patients was tested by the Kruskal-Wallis test.

As shown in Table 1, the type 1 diabetes association at the 12q13 locus was replicated in both sets, with similar odds ratios. In a combined analysis of the two GWA cohorts and a pool of the two replication cohorts by Fisher's method, all three SNPs attained P values ranging from 2.48 × 10−8 to 9.13 × 10−10 (Table 2). These data provide convincing evidence of a novel type 1 diabetes locus. The other loci fast tracked to stage 2 are shown in supplementary Table 1. While this report was in preparation the WTCCC results were published, reporting four novel type 1 diabetes associations, two of which coincide with our own two novel findings at 16p (13) and the one reported here, 12q13. We consider this simultaneous independent discovery of noncandidate loci a potent validation of the GWA approach.

The three SNPs are located in a 250-kb block of tight LD on Chr12q and are highly correlated (r2 = 0.608–0.855). Type 1 diabetes risk was conferred by the minor allele in all three. The OR (95% CI) of the haplotype of the three SNPs’ minor alleles was 1.25 (1.12–1.40). The genotypic association of the SNPs best fits an additive model of susceptibility on a log scale (supplementary Table 2). There was a trend, with borderline statistical significance, of an effect on age-of-onset of type 1 diabetes (supplementary Table 3): homozygotes of the risk allele may have the disease onset 1 year earlier than the homozygotes of the protective allele. This is clearly the same locus as the one reported by Todd et al. (13), as the type 1 diabetes–associated rs2292239 is in tight LD with our markers (supplementary Fig. 2). In addition, imputed genotype counts for our three significant markers in the WTCCC data showed highly significant type 1 diabetes association, as shown in a meta-analysis of the two studies for the 12q13 locus (supplementary Table 4). Significance was increased by several orders of magnitude. None of the other loci tested in this report (supplementary Table 1) achieved statistical significance as a result of this joint analysis.

The associated 250-kb LD block encompasses several genes that now become candidates for the type 1 diabetes association (Fig. 1 and supplementary Fig. 3). RAB5B (MIM:179514) encodes a member of the RAS oncogene family that may be involved in vesicular trafficking at the plasma membrane (17). SUOX (MIM:606887) encodes a liver-specific sulfite oxidase involved in the degradation of sulfur-containing amino acids. Neither gene has known function in immunity or pancreatic development. IKZF4 (MIM:606239) encodes a better functional candidate, a zinc finger protein specifically expressed in lymphocytes and implicated in the control of lymphoid development. ERBB3 (MIM:190151) encodes a member of the epidermal growth factor receptor family of receptor tyrosine kinases involved in the regulation of cell proliferation or differentiation. Interestingly, it interacts with proteins with important immune functions, such as Lyn, Itk, and Fer (18). CDK2 (MIM: 116953) encodes a member of the Ser/Thr protein kinase family whose activity is regulated by its protein phosphorylation; members of this gene family have been recently implicated in GWA studies of type 2 diabetes (1922). Fine mapping and functional studies will be required to identify the causative variant and generate functional insights from this genetic finding.

A more immediate conclusion from this finding is the support it provides to the robustness of the GWA approach, through identification of the same loci in two independent studies. Further, it is worth noting that our power to include in this fast-track replication a locus of magnitude comparable with the one reported here was only 38%. This means that our full second stage, plus future stages and combined meta-analyses, are likely to reveal additional such loci.

FIG. 1.

Type 1 diabetes association in the 12q13 region. The combined results of type 1 diabetes association tests of the case-control cohort and the family cohort is shown. The red bars, corresponding to –log10(P) values, represent the SNPs of significant type 1 diabetes association with P < 0.05. The LD map is based on our genotyping data of the family cohort. D′ values (%) are shown in the boxes, and for the empty boxes D′ = 1. The gray scale represents the r2 values. The type 1 diabetes–associated SNPs map to an LD region in the middle of the figure, while the strongest association is from the region around the RAB5B gene. The r2 values drastically drop beyond the two ends of the block containing the type 1 diabetes–associated SNPs. Relatively high D′ values continue for an additional ∼250 kb in the telomeric direction, but beyond the block shown there is no type 1 diabetes–associated SNP and no HapMap SNPs with substantial r2 values to those in the block shown (extended LD diagram in supplementary Fig. 3).

FIG. 1.

Type 1 diabetes association in the 12q13 region. The combined results of type 1 diabetes association tests of the case-control cohort and the family cohort is shown. The red bars, corresponding to –log10(P) values, represent the SNPs of significant type 1 diabetes association with P < 0.05. The LD map is based on our genotyping data of the family cohort. D′ values (%) are shown in the boxes, and for the empty boxes D′ = 1. The gray scale represents the r2 values. The type 1 diabetes–associated SNPs map to an LD region in the middle of the figure, while the strongest association is from the region around the RAB5B gene. The r2 values drastically drop beyond the two ends of the block containing the type 1 diabetes–associated SNPs. Relatively high D′ values continue for an additional ∼250 kb in the telomeric direction, but beyond the block shown there is no type 1 diabetes–associated SNP and no HapMap SNPs with substantial r2 values to those in the block shown (extended LD diagram in supplementary Fig. 3).

TABLE 1

The type 1 diabetes–associated 12q13 SNPs in two independent cohorts

SNPMinor alleleFrequencyInformative families*SE(S)Var(S)§ZP
Consortium set         
    rs773107 0.322 217 329 290 208 2.73 0.006400 
    rs10876864 0.417 226 395 350 229 2.98 0.002885 
    rs1701704 0.346 216 341 296 211 3.09 0.002019 
Canadian set         
    rs773107 0.339 200 180 160 75 2.37 0.017736 
    rs10876864 0.452 212 210 191 87 2.09 0.036293 
    rs1701704 0.357 216 189 169 81 2.22 0.026268 
Combined         
    rs773107 0.329 417 509 449 283 3.56 0.000374 
    rs10876864 0.432 438 605 540 316 3.64 0.000278 
    rs1701704 0.350 432 530 465 292 3.80 0.000148 
SNPMinor alleleFrequencyInformative families*SE(S)Var(S)§ZP
Consortium set         
    rs773107 0.322 217 329 290 208 2.73 0.006400 
    rs10876864 0.417 226 395 350 229 2.98 0.002885 
    rs1701704 0.346 216 341 296 211 3.09 0.002019 
Canadian set         
    rs773107 0.339 200 180 160 75 2.37 0.017736 
    rs10876864 0.452 212 210 191 87 2.09 0.036293 
    rs1701704 0.357 216 189 169 81 2.22 0.026268 
Combined         
    rs773107 0.329 417 509 449 283 3.56 0.000374 
    rs10876864 0.432 438 605 540 316 3.64 0.000278 
    rs1701704 0.350 432 530 465 292 3.80 0.000148 
*

Number of nuclear families informative for (with a non-zero contribution to) FBAT analysis.

Observed allele number in the affected offspring.

Expected allele number in the affected offspring.

§

Variance of allele distribution among the affected offspring.

TABLE 2

The combined P values of type 1 diabetes association of the three 12q13 SNPs

SNPChromosomePositionGWA case-control*GWA familiesStage 2Combined
rs773107 12 54,655,773 2.89 × 10−5 7.81 × 10−3 3.74 × 10−4 2.48 × 10−8 
rs10876864 12 54,687,352 8.39 × 10−5 2.97 × 10−4 2.78 × 10−4 2.47 × 10−9 
rs1701704 12 54,698,754 9.89 × 10−6 1.62 × 10−3 1.48 × 10−4 9.13 × 10−10 
SNPChromosomePositionGWA case-control*GWA familiesStage 2Combined
rs773107 12 54,655,773 2.89 × 10−5 7.81 × 10−3 3.74 × 10−4 2.48 × 10−8 
rs10876864 12 54,687,352 8.39 × 10−5 2.97 × 10−4 2.78 × 10−4 2.47 × 10−9 
rs1701704 12 54,698,754 9.89 × 10−6 1.62 × 10−3 1.48 × 10−4 9.13 × 10−10 

Data are P values.

*

Corrected by the EIGENSTRAT method (ref. 15).

Published ahead of print at http://diabetes.diabetesjournals.org on 15 January 2008. DOI: 10.2337/db07-1305.

Additional information for this article can be found in an online appendix at http://dx.doi.org/10.2337/db07-1305.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We gratefully acknowledge the use of DNA samples from the Type 1 Diabetes Genetics Consortium, funded by National Institutes of Health Grant U01-DK62418. This work was funded by the Children's Hospital of Philadelphia, the Juvenile Diabetes Research Foundation International and Genome Canada through the Ontario Genomics Institute. H.Q.Q. is supported by a fellowship from the Canadian Institutes of Health Research.

We thank all the patients and their parents and the healthy control subjects for their participation in the study.

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Supplementary data