1 Section of Medical and Molecular Genetics, Department of Pediatrics and Child Health, The Medical School, University of Birmingham, Edgbaston, U.K.
2 Department of Diabetes and Vascular Medicine, School of Postgraduate Medicine and Health Sciences, University of Exeter, Exeter, U.K.
3 Imperial College Genetics and Genomics Research Institute and Division of Medicine, Imperial College, London, U.K.
4 Department of Medicine, Medical School, University of Newcastle, Newcastle, U.K.
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() |
---|
The WFS1 gene maps to chromosome 4p16.3 (7) and consists of eight exons (8). WFS1 is widely expressed in tissues, including brain and pancreas, and has been localized to the endoplasmic reticulum (9). A wide spectrum of loss of function mutations have been reported in affected patients, with no obvious relation between mutation and phenotype (10). The function of WFS1 is unknown, but it is thought to be involved in the survival of islet ß-cells and neurons. A previous study of three Japanese cohorts of type 1 diabetic patients and control subjects identified three coding variants in strong linkage disequilibrium (LD), R456H, H611R, and I720V, in which the rare allele was present in more type 1 diabetic patients than control subjects (odds ratios [ORs] 1.802.04, P = 0.00050.0093) (11). Carriers of the H456 allele showed decreased frequencies of autoimmune characteristics (islet cell antibody or GAD autoantibody positivity and decreased frequencies of HLA-DRB susceptibility alleles) (11). This raised the suggestion that these variants (or further variants in LD with them) are associated with a nonautoimmune process of ß-cell dysfunction.
There have been no studies of the role of the WFS1 gene in type 2 diabetes. We hypothesized that variation in the WFS1 gene may contribute to ß-cell dysfunction and hence account for some of the genetic susceptibility of type 2 diabetes.
We screened the coding region of WFS1 for variants in 29 patients with type 2 diabetes. These subjects were randomly selected from the Diabetes U.K./Warren parent-offspring trios collection (Table 1). Sequencing of the coding region and intron/exon boundaries revealed 12 coding variants and 2 noncoding variants (Table 2). We selected five of these variants for association studies: F341F, R456H, R611H, K774K, and S855S. The I720V variant found in Japanese subjects was not observed. These five variants were chosen to ensure alleles associated with diabetes in previous studies were represented and to represent all common haplotypes across the genewe could distinguish all haplotypes with a frequency >0.05.
|
|
Using the transmission disequilibrium test (TDT) (13), both the R456 and H611 alleles and the R456-H611 haplotype showed borderline significant overtransmission to affected offspring from heterozygous parents (P = 0.04, P = 0.05, and P = 0.032, respectively) (Table 3). No significant deviations from the expected 50% transmission rates were observed for the three synonymous variants. However, the haplotype formed by the common alleles at all five positions showed borderline-significant overtransmission (P = 0.057) (Table 3). These observations were not independent, as we observed strong LD among the five variants investigated (P = 0.002 for LD between H611R and R456H and P < 0.000001 for LD among all five variants).
|
|
Our results show evidence for a possible association between WFS1 gene variants and type 2 diabetes in the U.K. This is the first evidence for a role of WFS1 in susceptibility to type 2 diabetes. Association studies of gene variants with complex diseases are fraught with difficulties, including potential population stratification, low a priori odds of finding a genuine association (15), and lack of replication. In this study, we tried to avoid these potential pitfalls in a number of ways, including use of family-based association tests to avoid population stratification, selection of variants previously associated with a similar disease process in a gene in which rare mutations are known to cause ß-cell dysfunction, and assessment of nominally significant results in secondary cohorts. Despite this, our results only reached significance (at P = 0.05) when all data were compared; therefore, further replication is required to confirm or refute our findings.
There are a number of differences between our study and a recent Japanese study (11). In the Japanese study, the R611 allele is associated with type 1 diabetes, and in our study, the H611 allele is associated with type 2 diabetes. In addition, the H611 allele frequency differs greatly between the two populations (88.7% in Japanese vs. 55% in white U.K. population). Given the borderline-significant TDT result with the 1-R-H-1-1 haplotype (Table 3), the H611 allele may only be a marker of a disease susceptibility haplotype.
Currently, there are no functional studies to support our findings because the function of WFS1 is unknown. To increase our knowledge of ß-cell metabolism, we need to establish the function of WFS1 and determine how variants alter ß-cell function. Our findings have to be tested in other populations and if replicated, we need to quantify the risk of diabetes conferred by these variants.
![]() |
RESEARCH DESIGN AND METHODS |
---|
![]() ![]() ![]() ![]() ![]() |
---|
PCR amplification of coding region of WFS1.
In the present study, exon 8 was divided into nine overlapping fragments, and the primers used were the same as those previously described (8), except for the following: 5'-TGGAGATGAAGGACAGGTAG-3', 5'-TTCGCCTTCTTCATCCCGCT-3', 5'-AGCAAGGACTGCATCCCCT-3', 5'AACTGCACGCCCACCA-3', 5'-TGGTGGGCGTGCTGCAGTT-3', 5'-AGCAAGGACTGCATCCCCT-3', 5-CTCCAGGATGGTGCTGAACT-3', 5'-CAG CGAGTTCAAAA-3', and 5'-GGGTGGAGATGGCATGCAAT-3'. PCRs were performed using Taq DNA polymerase (Gibco), and cycling conditions included an initial denaturation at 96°C for 5 min followed by 35 cycles at 95°C for 30 s. The annealing temperature was 60°C for exons 27, 54°C for exon 8 fragment 1, 51°C for exon 8 fragment 2, 58°C for exon 8 fragment 3, and 56°C for exon 8 fragments 49. Extension was at 72°C for 45 s and a final extension for 15 min at 72°C. MgCl2 was used in PCR amplification at a final concentration of 1.5 mmol/l.
Direct sequence analysis.
PCR products amplified as previously described from each exon were directly sequenced on both strands, if necessary, using a BigDye Terminator Cycle Sequencing Kit (PE Applied Biosystems).
Genotyping.
PCR amplification was performed as previously described. Ten microliters PCR product was digested with 10 units restriction endonuclease (F341F alters a BcgI restriction site, R456H alters a BstUI restriction site, R611H alters a HhaI restriction site, K774K alters a ApoI restriction site, and S855S alters a HpHI restriction site) (New England Biolabs U.K., Hitchin, U.K.) in a 20-µl reaction at optimal temperature for >2 h, followed by resolution of fragments on a 2% agarose gel in Tris-borate/EDTA (TBE) electrophoresis buffer and ethidium bromide staining. Results are shown in Table 3.
Statistics.
All P values quoted are two-tailed unless stated otherwise. The TDT in the parent-offspring trios for both individual WFS1 variants and haplotypes was performed using TRANSMIT (16). Transmisson rates were calculated using standard statistics for proportions. The significance of LD among variants was calculated using the maximum likelihood outputs from TRANSMIT.
For the follow-up case-control study, the significance of allele and genotype frequency differences was calculated using 2 analyses. Haplotype frequency differences were calculated using the maximum likelihood output from the Estimated Haplotype (EH) program (17,18).
For the pooled case-control study, the trios probands were used as case subjects, and the two untransmitted alleles in each trio were put together as a control, as with the haplotype-based haplotype relative risk statistic of Terwilliger and Ott (17). Allele and genotype frequency differences were then calculated using 2 analyses, with overall allele numbers used to calculate ORs and 95% CIs using 2 x 2 contingency tables. To assess the overall significance of the R456-H611 haplotype, estimated frequencies from the EH and TRANSMIT outputs were used to calculate actual numbers of haplotypes (R456-H611 versus the other three haplotypes formed by these two variants) in all case and control chromosomes. Although we tested five variants, we did not correct for multiple testing because alleles at two of the variants tested had previously been associated with diabetes and because strong LD existed across the gene (D values between 0.36 and 0.95 for H611R versus the other four variants in TDT analysis), meaning allele associations were not independent of each other.
To examine possible associations with ß-cell function in the control subjects, we used log-transformed percent of ß-cell function values, calculated by the HOMA 2.0 program. ANOVA and t tests using SPSS (version 9.0) were used to compare log-transformed percent of ß-cell function across genotypes while correcting for sex and age. The percentage of ß-cell function values quoted are back-transformed.
![]() |
ACKNOWLEDGMENTS |
---|
We are very grateful for the assistance of our colleagues Diane Jarvis (DNA extraction), Susan Ayres (collection of samples from type 2 diabetic subjects), Beatrice Knight, and Tina Turner (collection of samples from control subjects) as well as Penny Clark (Birmingham; measurement of insulin) and Sian Ellard (laboratory organization).
![]() |
FOOTNOTES |
---|
Received for publication 20 September 2001 and accepted in revised form 4 January 2002.
EH, Estimated Haplotype; LD, linkage disequilibrium; OR, odds ratio; TDT, transmission disequilibrium test.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() |
---|