Abstract
Aims/hypothesis
Pathophysiological similarities between latent autoimmune diabetes in adults (LADA) and type 1 diabetes indicate an overlap in genetic susceptibility. HLA-DRB1 and HLA-DQB1 are major susceptibility genes for type 1 diabetes but studies of these genes in LADA have been limited. Our aim was to define patterns of HLA-encoded susceptibility/protection in a large, well characterised LADA cohort, and to establish association with disease and age at diagnosis.
Materials and methods
Patients with LADA (n=387, including 211 patients from the UK Prospective Diabetes Study) and non-diabetic control subjects (n=327) were of British/Irish European origin. The HLA-DRB1 and -DQB1 genes were genotyped by sequence-specific PCR.
Results
As in type 1 diabetes mellitus, DRB1*0301_DQB1*0201 (odds ratio [OR]=3.08, 95% CI 2.32–4.12, p=1.2× 10−16) and DRB1*0401_DQB1*0302 (OR=2.57, 95% CI 1.80–3.73, p=4.5×10−8) were the main susceptibility haplotypes in LADA, and DRB1*1501_DQB1*0602 was protective (OR=0.21, 95% CI 0.13–0.34, p=4.2×10−13). Differential susceptibility was conferred by DR4 subtypes: DRB1*0401 was predisposing (OR=1.79, 95% CI 1.35–2.38, p=2.7×10−5) whereas DRB1*0403 was protective (OR=0.37, 95% CI 0.13–0.97, p=0.033). The highest-risk genotypes were DRB1*0301/DRB1*0401 and DQB1*0201/DQB1*0302 (OR=5.14, 95% CI 2.68–10.69, p=1.3×10−8; and OR=6.88, 95% CI 3.54–14.68, p=1.2×10−11, respectively). These genotypes and those containing DRB1*0401 and DQB1*0302 associated with a younger age at diagnosis in LADA, whereas genotypes containing DRB1*1501 and DQB1*0602 associated with an older age at diagnosis.
Conclusions/interpretation
Patterns of susceptibility at the HLA-DRB1 and HLA-DQB1 loci in LADA are similar to those reported for type 1 diabetes, supporting the hypothesis that autoimmune diabetes occurring in adults is an age-related extension of the pathophysiological process presenting as childhood-onset type 1 diabetes.
Keywords: Age of diagnosis, Genetic susceptibility, Protection, Type 1 diabetes
Introduction
Latent autoimmune diabetes in adults (LADA) and type 1 diabetes mellitus result from islet beta cell autoimmune destruction and are characterised by the presence of circulating islet autoantibodies. However, the later age of onset and the relatively less acute clinical onset of LADA can result in a clinical diagnosis of type 2 diabetes [1]. Differences in genetic susceptibility could contribute to the variation in both age and clinical severity at onset of autoimmune diabetes.
The HLA gene region is the major susceptibility locus in type 1 diabetes, accounting for 42% of the total familial risk; primary susceptibility is conferred by the HLA-DRB1 and HLA-DQB1 genes, and the highest risk is from DRB1*04-DQB1*0302 and DRB1*0301-DQB1*0201 haplotypes, present in ~90% of type 1 diabetic patients [2]. In type 1 diabetes, the DRB1*0301 and DRB1*0401 alleles exhibit positive synergism such that the DRB1*0401/DRB1*0301 genotype confers greater risk than either of the two alleles alone [3]. In addition, DRB1*0301/DRB1*0401 and DQB1*0201/DQB1*0302 genotypes occur more frequently in type 1 diabetic patients diagnosed at earlier ages [4]. Heterogeneity in disease risk conferred by the DRB1*04-DQB1*0302 haplotype depends upon the allelic subtype of the DR4 antigen specificity present on it: DRB1*0401, *0402 and *0405 associate with increased susceptibility, whereas *0403, *0406 and *0407 confer protection [5]. The DRB1*1501-DQB1*0602 haplotype, which is negatively correlated with age at diagnosis, is considered to be protective against type 1 diabetes [6].
Although the HLA-DRB1 and HLA-DQB1 genes are good candidate loci for LADA, HLA association studies in LADA have been hampered by small sample sizes and low genotyping resolution. Predisposing effects of DRB1*0301 and DRB1*0401 have been demonstrated, but results have been inconsistent [7–9] and a protective effect of DQB1*0602 has not been confirmed throughout [8, 10]. The largest study, using UK Prospective Diabetes Study subjects (UKPDS), employed low-resolution typing restricted to detection of HLA-DRB1 susceptibility variants DRB1*03 and DRB1*04 [7]. This demonstrated an increased frequency of the DRB1*03/DRB1*04 heterozygote in LADA [7]. However, protective variants were not examined and HLA-DQB1 allele analysis was restricted to determination of aspartate-57, a putative susceptibility determinant for type 1 diabetes [7].
This investigation extends the previous study [7] by using higher resolution typing and a larger LADA cohort. The aims were to (1) establish association patterns of HLA with disease and compare these with previously reported observations made in type 1 diabetes and (2) determine the relationship of HLA-DRB1 and HLA-DQB1 genotypes with age at diagnosis.
Subjects and methods
Subjects
LADA subjects (n=378) were from the UKPDS (n=211), the Warren 2 Repository (W2, n=130) [11] and the Exeter Young-Onset Type 2 Diabetes Study (YT2D, n=37) [12]. They were initially diagnosed with type 2 diabetes and were antibody-positive (for GAD and/or islet antigen 2A, IA-2A), with no requirement for insulin within 3 months after diagnosis. The control population comprised normoglycaemic, GADA/IA-2A-negative spouses/friends of probands recruited as part of the Diabetes in Families study (DIF, n=327). All subjects were unrelated and of British/Irish European origin (Table 1). Informed consent was obtained from all subjects, and all studies were carried out in accordance with the principles of the Declaration of Helsinki (1975, 1983, 2000).
Table 1.
Clinical characteristics of study subjects
| Sample (n) |
Study (n) |
Ascertainment criteria |
Age at onset (years) mean±SD (range), |
Duration of diabetes (years), mean±SD |
BMI (kg/m2), mean±SD |
Male (%) |
|---|---|---|---|---|---|---|
| LADA (378) |
UKPDS (211) |
Newly diagnosed type 2 diabetes: not insulin-requiring within 3 months of diagnosis. Ketonuria <3 mmol/l | 46.3±10.6 (25–65) | Studied at diagnosis | 25.1±4.8a | 52 |
| W2 (130) |
Clinical diagnosis of type 2 diabetes: not insulin requiring within 12 months of diagnosis | 47.4±10.0 (26–68) | 8.9±6.7b | 28.6±5.3b | 57 | |
| YT2D (37) |
Clinical diagnosis of type 2 diabetes: not insulin-requiring within 3 months of diagnosis | 38.4±5.4 (29–45) | 11.9±7.7b | 27.5±5.8b | 43 | |
| Control subjects |
DIF (327) |
Spouses/friends of probands collected in the DIF study. Normoglycaemic | 55.3±19.8b (20–91) | N/A | 25.4±4.0b | 46 |
Antibody positivity was defined as a titre >97.5th percentile compared with control samples (UKPDS, YT2D and DIF samples measured in the laboratory of P. J. Bingley, University of Bristol) or >10 U (corresponding to ~8 SD above the mean of 88 normal control subjects) for the W2 samples measured in the laboratory of G. F. Bottazzo (Royal London Hospital). All LADA patients were GADA-positive with the exception of two YT2D patients who were positive for IA-2A only. Control subjects were negative for GADA and IA-2A at sample collection.
At diagnosis
At time of sample collection
Genotyping
The HLA-DRB1 and HLA-DQB1 genes were genotyped using sequence-specific PCR (PCR-SSP) [13]. Samples with inferred haplotypes that were uncommon or did not conform to known linkage disequilibrium patterns in UK Europids were regenotyped (n=27). Duplicate sample (n=15) genotyping concordance was 100% for both loci and success was >95%.
Statistical methods
Homogeneity (between LADA groups) and case–control association testing was performed using standard contingency table methods in StatXact 6 (Cytel Software, Cambridge, MA, USA). As appropriate, exact p values were calculated. Haplotype frequencies were estimated using the expectation maximization algorithm implemented in HelixTree (Golden Helix, Bozeman, MT, USA). For diplotype analyses, the most probable haplotype pair was assigned to each individual and >97.8% of assigned haplotypes had posterior probabilities >0.999. Distributions of allele, genotype, haplotype and diplotype frequencies between cases and controls were assessed by 2×n contingency tables (pooling categories with frequencies <1%). Where global tests of association indicated significant differences, variants with frequency >5% were tested for disease association by 2×2 contingency table analysis. Association of age at diagnosis with genotype was initially explored using recursive partitioning, as implemented in HelixTree. Linear regression modelling (SPSS, version 13.0; SPSS, Chicago, IL, USA) was subsequently performed for genotypes containing alleles associated with type 1 diabetes and/or shown to be associated with age at diagnosis. Power calculations (Quanto, version 1.0; http://hydra.usc.edu/gxe, last accessed in September 2006) indicated that our sample size provided >80% power to detect an odds ratio (OR) >1.85 for a minor allele frequency of 5% under the additive model. No corrections for multiple testing were applied and a p value of <0.05 was deemed significant.
Results
Allele frequency distributions between the UKPDS, W2 and YT2D LADA groups did not significantly differ at HLA-DRB1 and HLA-DQB1 (p=0.20 and 0.81, respectively). Accordingly, genotyping data of the three patient groups were combined, forming a single group (‘LADA’), and compared with control subjects.
The overall distribution of allele frequencies at HLA-DRB1 and HLA-DQB1 differed significantly between LADA and control subjects (both p<0.0001). Analysis of individual alleles showed predisposing effects of DRB1*0301 (OR=3.08, 95% CI 2.32–4.11), DRB1*0401 (OR=1.79, 95% CI 1.35–2.38), DQB1*0201 (OR=3.19, 95% CI 2.40–4.26) and DQB1*0302 (OR=2.38, 95% CI 1.77–3.25) (Table 2). Protection was conferred by DRB1*0403(06/07) (OR=0.37, 95% CI 0.13–0.97), DRB1*1101(04) (OR = 0.25, 95% CI 0.12–0.48), DRB1*1501-06 (OR = 0.20, 95% CI 0.13–0.32), DQB1*0301 (OR=0.51, 95% CI 0.37–0.69), DQB1*0303 (OR=0.29, 95% CI 0.14–0.57) and DQB1*0602 (OR=0.21, 95% CI 0.13–0.34) (Table 2).
Table 2.
HLA-DRB1 and HLA-DQB1 allele frequencies and associated OR and p values
| LADA (n=756)a,b | Control subjects (n=654)a | OR (95% CI) | p value | |
|---|---|---|---|---|
| DRB1 allele | ||||
| *0101 | 53 (0.070) | 64 (0.098) | 0.70 (0.47–1.03) | 0.066 |
| *0103 | 4 (0.005) | 3 (0.005) | ND | |
| *0301 | 236 (0.312) | 84 (0.128) | 3.08 (2.32–4.11) | 9.1×10−17 |
| *0302 | 0 | 1 (0.002) | ND | |
| *0401 | 178 (0.235) | 96 (0.147) | 1.79 (1.35–2.38) | 2.7×10−5 |
| *0402 | 4 (0.005) | 2 (0.003) | ND | |
| *0403(06/07) | 7 (0.009) | 16 (0.024) | 0.37 (0.13–0.97) | 0.033 |
| *0404 | 34 (0.045) | 22 (0.034) | ND | |
| *0405 | 8 (0.011) | 3 (0.005) | ND | |
| *0701 | 100 (0.132) | 94 (0.144) | 0.91 (0.66–1.25) | 0.54 |
| *0801 | 16 (0.021) | 22 (0.034) | ND | |
| *0901(02) | 6 (0.008) | 9 (0.014) | ND | |
| *1001 | 1 (0.001) | 1 (0.002) | ND | |
| *1101(04) | 13 (0.017) | 43 (0.066) | 0.25 (0.12–0.48) | 3.4×10−6 |
| *1102(03) | 15 (0.020) | 7 (0.011) | ND | |
| *1201 | 3 (0.004) | 10 (0.015) | ND | |
| *1301 | 20 (0.026) | 27 (0.041) | ND | |
| *1302 | 22 (0.029) | 30 (0.046) | ND | |
| *1303 | 1 (0.001) | 1 (0.002) | ND | |
| *1401 | 5 (0.007) | 12 (0.018) | ND | |
| *1501-06 | 26 (0.034) | 97 (0.148) | 0.20 (0.13–0.32) | 2.1×10−14 |
| *1601 | 4 (0.005) | 10 (0.015) | ND | |
| DQB1 allele | ||||
| *0201 | 239 (0.317) | 83 (0.127) | 3.19 (2.40–4.26) | 7.1×10−18 |
| *0202 | 82 (0.109) | 66 (0.101) | 1.09 (0.76–1.56) | 0.66 |
| *0301 | 82 (0.109) | 127 (0.194) | 0.51 (0.37–0.69) | 8.3×10−6 |
| *0302 | 178 (0.236) | 75 (0.115) | 2.38 (1.77–3.25) | 2.5×10−9 |
| *0303 | 13 (0.017) | 37 (0.057) | 0.29 (0.14–0.57) | 7.2×10−5 |
| *0401 | 1 (0.001) | 0 | ND | |
| *0402 | 16 (0.021) | 21 (0.032) | ND | |
| *0501 | 59 (0.078) | 68 (0.104) | 0.73 (0.50–1.07) | 0.094 |
| *0502 | 3 (0.004) | 10 (0.015) | ND | |
| *0503 | 4 (0.005) | 12 (0.018) | ND | |
| *0504 | 1 (0.001) | 0 | ND | |
| *0601 | 0 | 4 (0.006) | ND | |
| *0602 | 25 (0.033) | 91 (0.139) | 0.21 (0.13–0.34) | 2.5×10−13 |
| *0603 | 15 (0.020) | 30 (0.046) | ND | |
| *0604 | 36 (0.048) | 30 (0.046) | ND |
All OR were calculated under the multiplicative model and are presented as LADA vs control subjects. Genotyping was checked by two independent researchers.
ND denotes an association not determined because frequencies were <5% in both LADA and control groups.
Data are given as number of chromosomes (frequency).
LADA n=754 for DQB1 allele.
The distribution of HLA-DRB1 and HLA-DQB1 genotypes differed significantly between LADA and control subjects (p<0.0001; see Electronic supplementary material [ESM] Tables 1 and 2, respectively). Specifically, increased susceptibility to LADA was conferred by genotypes, DRB1*0301/DRB1*0401 (OR=5.14, 95% CI 2.68–10.69), DRB1*0301/DRB1*0301 (OR=4.51, 95% CI 1.93–12.23), DRB1*0301/DRB1*0701 (OR=2.38, 95% CI 1.13–5.38), DQB1*0201/DQB1*0302 (OR=6.88, 95% CI 3.54–14.68), DQB1*0201/DQB1*0201 (OR=5.11, 95% CI 2.21–13.77), DQB1*0201/DQB1*0202 (OR= 2.47, 95% CI 1.04–6.51), DQB1*0201/DQB1*0501 (OR=2.84, 95% CI 1.07–8.79) and DQB1*0302/DQB1*0302 (OR=2.84, 95% CI 1.07–8.79) (Table 3). Additionally, protective effects of DRB1*0701/DRB1*1501-06 (OR=0.05, 95% CI 0.001–0.31) and DQB1*0301/DQB1*0602 (OR=0.11, 95% CI 0.02–0.38) were observed (Table 3). The highest point estimate for genotypic risk at HLA-DRB1 was seen in the DRB1*0301/DRB1*0401 heterozygotes, though this was not significantly greater than the estimate for either homozygote group (data not shown).
Table 3.
Association of HLA-DRB1 and -DQB1 genotypes (frequencies >5% in either cases or controls) with LADA
| LADAa | Control subjectsa | OR (95% CI) | p value | |
|---|---|---|---|---|
| DRB1 genotype | ||||
| *0301/*0401 | 62 (0.164) | 12 (0.037) | 5.14 (2.68–10.69) | 1.3×10−8 |
| *0301/*0301 | 34 (0.090) | 7 (0.021) | 4.51 (1.93–12.23) | 7.6×10−5 |
| *0301/*0701 | 29 (0.077) | 11 (0.034) | 2.38 (1.13–5.38) | 0.014 |
| *0401/*0701 | 22 (0.058) | 14 (0.043) | 1.38 (0.66–2.97) | 0.39 |
| *0701/*1501-06 | 1 (0.003) | 17 (0.052) | 0.05 (0.001–0.31) | 2.9×10−5 |
| DQB1 genotype | ||||
| *0201/*0302 | 73 (0.194) | 11 (0.034) | 6.88 (3.54–14.68) | 1.2×10−11 |
| *0201/*0201 | 38 (0.101) | 7 (0.021) | 5.11 (2.21–13.77) | 9.4×10−6 |
| *0201/*0202 | 22 (0.058) | 8 (0.024) | 2.47 (1.04–6.51) | 0.038 |
| *0201/*0501 | 19 (0.050) | 6 (0.018) | 2.84 (1.07–8.79) | 0.024 |
| *0302/*0302 | 19 (0.050) | 6 (0.018) | 2.84 (1.07–8.79) | 0.024 |
| *0201/*0301 | 17 (0.045) | 17 (0.052) | 0.86 (0.41–1.83) | 0.73 |
| *0301/*0602 | 3 (0.008) | 22 (0.067) | 0.11 (0.02–0.38) | 1.7×10−5 |
All OR were calculated as presence of the genotype in question vs all other genotypes and are presented as LADA compared with control subjects.
Data are given as number of individuals (frequency).
DRB1_DQB1 haplotype distribution was different between LADA and control subjects (p<0.0001; ESM Table 3). Haplotypes DRB1*0301_DQB1*0201 and DRB1*0401_DQB1*0302 were predisposing (OR=3.08, 95% CI 2.32–4.12; and OR=2.57, 95% CI 1.80–3.73, respectively) whereas DRB1*1101(04)_DQB1*0301 and DRB1*1501-06_DQB1*0602 (OR=0.25, 95% CI 0.12–0.48; and OR=0.21, 95% CI 0.13–0.34, respectively) conferred protection against LADA (Table 4).
Table 4.
Association of HLA-DRB1_DQB1 haplotypes (frequencies >5% in either cases or controls) with LADA
| Haplotype | LADAa | Control subjectsa | OR (95% CI) | p value |
|---|---|---|---|---|
| *0301_*0201 | 234 (0.310) | 83 (0.127) | 3.08 (2.32–4.12) | 1.2×10−16 |
| *0401_*0302 | 128 (0.169) | 48 (0.073) | 2.57 (1.80–3.73) | 4.5×10−8 |
| *0701_*0202 | 81 (0.107) | 64 (0.098) | 1.11 (0.77–1.59) | 0.60 |
| *0101_*0501 | 52 (0.069) | 64 (0.098) | 0.68 (0.46–1.02) | 0.052 |
| *0401_*0301 | 49 (0.065) | 47 (0.072) | 0.90 (0.58–1.39) | 0.60 |
| *1501-06_*0602 | 25 (0.033) | 90 (0.138) | 0.21 (0.13–0.34) | 4.2×10−13 |
| *1101(04)_*0301 | 13 (0.017) | 43 (0.066) | 0.25 (0.12–0.48) | 3.4×10−6 |
All OR are calculated under the multiplicative model and are presented as LADA vs control subjects
Data are given as number of chromosomes (frequency)
Similarly, DRB1_DQB1 diplotype frequencies differed significantly between LADA and control subjects (p<0.0001; ESM Table 4), with DRB1*0301_DQB1*0201-DRB1*0401_DQB1*0302 and DRB1*0301_DQB1*0201-DRB1*0301_DQB1*0201 occurring more frequently in LADA compared with control subjects (OR=8.70, 95% CI 3.67–25.13, p=8.1×10−10 and OR=4.51, 95% CI 1.93–12.23, p=7.6×10−5, respectively). A nominally significant predisposing effect of DRB1*0301_DQB1*0201-DRB1*0701_DQB1*0202 was also observed (OR=2.46, 95% CI 1.04–6.49, p=0.048).
Diagnostic criteria for LADA have been proposed, including age at diagnosis >30 years and no clinical requirement for insulin within 6 months after diagnosis [14]. Using these criteria, we repeated the analyses, excluding 50 non-compliant cases. The effect sizes (odd ratios) were comparable (data not shown) with those described above.
Within the LADA group, the DRB1*0301/*0401 genotype associated with a younger age of diagnosis (mean age±SD in carriers vs non-carriers, 42.1±10.3 vs 46.6±10.2 years, p=0.0016), as did possession of the DRB1*0401 allele (43.8±9.8 vs 47.4±10.5 years, p=0.00075). Similarly, an earlier age of diagnosis was associated with the DQB1*0201/DQB1*0302 genotype (42.8±9.8 vs 46.5± 10.3 years, p=0.0051) and with possession of the DQB1*0302 allele (44.3±9.8 vs 46.9± 10.5 years, p=0.018). Conversely, patients carrying DRB1*1501-06 were older at diagnosis than those not carrying this allele (50.3±10.7 vs 45.6±10.2 years, p=0.030), as were carriers of DQB1*0602 (50.3±10.7 vs 45.5±10.2 years, p=0.029).
Discussion
The major LADA susceptibility determinants at the two loci were DRB1*0301, DRB1*0401, DQB1*0201 and DQB1*0302. This confirms previously reported genotype associations of DRB1*0301/DRB1*0401, DRB1*0301/DRB1*0301, DQB1*0201/DQB1*0201, DQB1*0201/DQB1*0302 and DQB1*0302/DQB1*0302 in LADA [7, 8]. This is the first report to demonstrate that DR4 antigen specificity subtypes confer differential risk of LADA: DRB1*0401 conferred susceptibility to LADA, whereas DRB1*0403(06/07) had a protective effect. The synergistic effects of the DRB1*0301 and DRB1*0401 alleles reported in type 1 diabetes [3] were not statistically significant in LADA, although the greatest point estimate for genotypic risk at HLA-DRB1 was observed for DRB1*0301/DRB1*0401 heterozygotes, which conferred an approximately 5-fold risk of disease (OR=5.14, 95% CI 2.68–10.69, p=1.3×10−8).
The major protective alleles in our LADA cohort were DRB1*1501-06 and DQB1*0602, as seen in Swedish patients [10] though not in Finns [8]. DRB1*1101(04), DQB1*0301 and DQB1*0303 were also protective, as seen in type 1 diabetes [2]. However, we found that DRB1_DQB1 haplotypes/diplotypes were very strongly associated with LADA and, in some cases, could account for the genotype/allele effects, e.g. protection conferred by DRB1*1101(04)_DQB1*0301. The age-related associations observed in this study are similar to those reported in type 1 diabetes and LADA [4, 6, 7].
We conclude that the architecture of HLA-conferred susceptibility to LADA is similar to that observed in type 1 diabetes, although individual effect sizes may differ. Susceptibility conferred by the insulin gene region is indistinguishable from that observed in type 1 diabetes [15]. Thus, similarities in genetic predisposition conferred by the two major type 1 diabetes susceptibility loci suggest that adult-onset autoimmune diabetes is an age-related extension of the pathophysiological process presenting as type 1 diabetes in children.
Supplementary Material
Acknowledgements
We thank J. Ayers and M. Barnardo at the Tissue Typing Laboratories (Churchill Hospital, Oxford, UK) for use of genotyping facilities and their expert advice, and A. Malloy for genotyping assistance. We acknowledge the laboratory of G. F. Bottazzo (Royal London Hospital, UK) for performing antibody testing of study subjects. E. Zeggini is a Wellcome Trust Research Career Development Fellow. This work was funded by Diabetes UK (V. A. Horton, M. Desai) and the Wellcome Trust (A. Clark.).
Abbreviations
- DIF
Diabetes in Families study
- HLA
human leucocyte antigen
- OR
odds ratio
- UKPDS
UK Prospective Diabetes Study
- W2
Warren 2 Repository
- YT2D
Exeter Young-Onset Type 2 Diabetes Study
Footnotes
Duality of interest None of the authors have any conflicts of interest.
Electronic supplementary material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s00125-006-0480-4 and is accessible to authorised users.
Contributor Information
M. Desai, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK
E. Zeggini, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
V. A. Horton, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK
K. R. Owen, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK
A. T. Hattersley, Institute of Biomedical and Clinical Sciences, Peninsula Medical School, Exeter, UK
J. C. Levy, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK
M. Walker, School of Clinical Medical Sciences, University of Newcastle, Newcastle, UK
K. M. Gillespie, Diabetes and Metabolism Unit, University of Bristol, Bristol, UK
P. J. Bingley, Diabetes and Metabolism Unit, University of Bristol, Bristol, UK
G. A. Hitman, Centre for Diabetes and Metabolic Medicine, Barts and The London, Queen Mary’s School of Medicine and Dentistry, London, UK
R. R. Holman, Diabetes Trials Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
M. I. McCarthy, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
A. Clark, Diabetes Research Laboratories, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford OX3 7LJ, UK, anne.clark@drl.ox.ac.uk
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