Genotyping data on all of the variants were available for 2,309 type 2 diabetic case subjects and 2,598 control subjects. Characteristics of these participants are shown in . Supplementary Table 1, available in an online appendix at http://dx.doi.org/10.2337/db08-0504
, presents a comparison of clinical characteristics for these subjects against the 1,739 who were not successfully genotyped across all SNPs. Individually, the variants have similar effect sizes in this study compared with those reported in other large studies () (1
), and the range of ORs from 1.00 to 1.36 most likely reflects stochastic variation. Several variants are not associated at P
< 0.05 in the sample used here but are still included in the analyses because they are confirmed type 2 diabetes risk variants, and the lack of significance is the result of relatively low power in this number of subjects. Based on these and larger datasets, all of the variants appear to have an additive mode of inheritance (1
). The CDKAL1
locus was reported by Steinthorsdottir et al. (4
) to fit a recessive model, but other large studies do not support this. There is no evidence of interaction between any of the SNPs based on these data (supplementary Table 2) or on the larger analyses previously published. Therefore, we assumed an additive genetic model. We found no evidence of any interaction between the individual variants and BMI or age (lowest interaction P
values = 0.14 and 0.02, respectively). We performed the analysis with and without the FTO
variant, the one variant shown to predispose to type 2 diabetes through a primary effect on BMI (18
Summary of type 2 diabetes variants in 2,598 control subjects and 2,309 case subjects from the Dundee cohort
The proportion of case and control subjects grouped according to the number of risk alleles that they carry is shown in . The distribution of risk alleles follows a normal distribution in both case and control subjects, with a shift toward a higher number of risk alleles in the case subjects. There is an increase in ORs for type 2 diabetes with the increasing number of risk alleles against the baseline group of 1.8% of individuals carrying 10–12 risk alleles. Of individuals with ≥25 risk alleles, 1.2% have an OR of 4.2 (95% CI 2.11–8.56) against the baseline reference group. Similarly, 11.5% of this study population carrying ≥22 risk alleles had an OR of 2.3 (1.73–2.93) for type 2 diabetes compared with the 8.2% of individuals with ≤14 risk alleles.
Distribution of risk alleles in type 2 diabetic case subjects (black bars) and control subjects (gray bars).
plots the ORs relative to the median number of 18 risk alleles. Those with ≥25 risk alleles were more than twice as likely to have type 2 diabetes (OR 2.18 [95% CI 1.24–3.81]) compared with those with the median number of risk alleles. The TCF7L2 variant had a stronger effect than the other variants (OR 1.36 compared with 1.00–1.25 for the rest), so these results may be slight underestimates, because the additive model used for the allele counting assumes equal effects across all SNPs.
FIG. 2. A plot showing the increasing ORs with the increasing number of type 2 diabetes risk alleles versus the baseline of 10–11 risk alleles. The ORs are given relative to the median number of 18 risk alleles (•). The vertical bars represent (more ...)
We performed the same analyses for two subgroups of the cohort, one including only obese individuals (with BMI of ≥30 kg/m2, n = 1,803), the other nonobese individuals (BMI <30 kg/m2, n = 3,083). The results were similar across these subgroups. For example, the 1.4% of obese individuals with >24 risk alleles had an OR of 5.5 (95% CI 2.11–14.36) compared with the 1.9% of obese individuals with <13 risk alleles. The corresponding OR for the nonobese subjects was 3.31 (1.34–8.16), for the 1.8 and 1.1% of individuals with <13 and >24 risk alleles, respectively.
We evaluated the discriminatory power of a genetic test based on the 18 type 2 diabetes variants by calculating the area under the ROC curve. Using the general model (as opposed to the additive model, which assumes equal and additive effects), the ROC curve for the 18 type 2 diabetes variants studied here is 0.60 (). We performed the same analysis for the obese and nonobese subgroups of the cohort. The AUCs for the obese and nonobese groups were 0.58 and 0.60, respectively. A similar result was obtained when we removed the FTO variant (obese, 0.58; nonobese, 0.59). We also tested whether the risk variants would add to the discriminatory power of BMI, age, and sex alone (AUC 0.78 in our study). A model that includes BMI, age, sex, and the 18 variants has an AUC of 0.80 (); although marginal, the increase in the AUC was statistically significant (P = 2.88 × 10−12). The AUC remained virtually the same (AUC = 0.80) when the FTO variant was removed from the model.
ROC plot for a model containing all type 2 diabetes variants, BMI, age, and sex (gray line, AUC = 0.80) and for the 18 variants alone (black line, AUC = 0.60).
The effect of BMI and age.
Supplementary Table 3 presents the individual SNP type 2 diabetes associations adjusted for BMI. As expected, the FTO
association is weakened on adjusting for BMI (OR 1.00 [95% CI 0.92–1.10]), and the TCF7L2
association is strengthened (1.46 [1.32–1.61]). Testing the combined effect of the risk variants on clinical features of the type 2 diabetes patients, we found that the number of risk alleles was associated with an earlier age at diagnosis of 0.15 years per risk allele (95% CI −0.29 to −0.01, P
= 0.038). We also observed an overall modifying effect on BMI (−0.14 BMI units per risk allele [−0.23 to −0.05], P
= 3.41 × 10−3
), but this finding is mainly explained by the known association of the TCF7L2
variant alone with BMI in type 2 diabetic case subjects (30
). Here, each TCF7L2
risk allele was associated with a difference in BMI of −0.69 kg/m2
(−1.06 to −0.31, P
= 3.18 × 10−4
), whereas the combined effect of all other variants without TCF7L2
could just be detected (−0.10 kg/m2
per risk allele [−0.20 to 0.01], P
= 0.036). The difference in BMI and age at diagnosis was more noticeable when we compared individuals with low and high numbers of risk alleles. For example, carriers of ≥23 risk alleles (11.8%) were, on average, diagnosed 4.2 years earlier (−6.45 to −1.87, P
= 4.21 × 10−4
) and had 1.60 kg/m2
lower BMI (−3.35 to 0.08, P
= 0.062) than those carrying <15 (8.6%) risk alleles.