Detailed investigation of the role of common and low-frequency WFS1 variants in type 2 diabetes risk.
Fawcett KA., Wheeler E., Morris AP., Ricketts SL., Hallmans G., Rolandsson O., Daly A., Wasson J., Permutt A., Hattersley AT., Glaser B., Franks PW., McCarthy MI., Wareham NJ., Sandhu MS., Barroso I.
OBJECTIVE: Wolfram syndrome 1 (WFS1) single nucleotide polymorphisms (SNPs) are associated with risk of type 2 diabetes. In this study we aimed to refine this association and investigate the role of low-frequency WFS1 variants in type 2 diabetes risk. RESEARCH DESIGN AND METHODS: For fine-mapping, we sequenced WFS1 exons, splice junctions, and conserved noncoding sequences in samples from 24 type 2 diabetic case and 68 control subjects, selected tagging SNPs, and genotyped these in 959 U.K. type 2 diabetic case and 1,386 control subjects. The same genomic regions were sequenced in samples from 1,235 type 2 diabetic case and 1,668 control subjects to compare the frequency of rarer variants between case and control subjects. RESULTS: Of 31 tagging SNPs, the strongest associated was the previously untested 3' untranslated region rs1046320 (P = 0.008); odds ratio 0.84 and P = 6.59 x 10(-7) on further replication in 3,753 case and 4,198 control subjects. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2 = 0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (minor allele frequency [MAF] <0.01) nonsynonymous variants between type 2 diabetic case and control subjects (P = 0.79). Two intermediate frequency (MAF 0.01-0.05) nonsynonymous changes also showed no statistical association with type 2 diabetes. CONCLUSIONS: We identified six highly correlated SNPs that show strong and comparable associations with risk of type 2 diabetes, but further refinement of these associations will require large sample sizes (>100,000) or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on type 2 diabetes risk in white U.K. populations, highlighting the complexities of undertaking association studies with low-frequency variants identified by resequencing.