Association analysis of common variants in FOXO3 with type 2 diabetes in a South Indian Dravidian population.

Recent studies have identified common variants in forkhead box O3 gene (FOXO3) to be strongly associated with longevity in different populations. But studies have not been carried out to analyse the role of common variants in FOXO3 with type 2 diabetes. Since type 2 diabetes is an age related disorder and FOXO proteins play an important role in the regulation of metabolism, we studied the role of common variants in FOXO3 for association with type 2 diabetes. The study was carried out in 994 type 2 diabetic samples and 984 normoglycemic control samples from a South Indian Dravidian population. In our analysis, we found that there was no association between any of the selected SNPs in FOXO3 with type 2 diabetes. Analysis of these SNPs with diabetes related biochemical and clinical parameters also did not reveal any significant association. Haplotype association of SNPs in FOXO3 with type 2 diabetes was observed, but the frequency of the haplotypes was considerably lower and they do not remain significant after correction for multiple testing. In conclusion, we did not observe any association of SNPs in FOXO3 with type 2 diabetes and related parameters suggesting an entirely different mechanism by which these SNPs influence longevity. However additional studies in other populations are required to completely rule out the association of common variants in FOXO3 with type 2 diabetes.

A case-control analysis of common variants in GIP with type 2 diabetes and related biochemical parameters in a South Indian population.

BACKGROUND: Glucose-dependent insulinotropic polypeptide (GIP) is one of the incretins, which plays a crucial role in the secretion of insulin upon food stimulus and in the regulation of postprandial glucose level. It also exerts an effect on the synthesis and secretion of lipoprotein lipase, from adipocytes, important for lipid metabolism. The aim of our study was to do a case-control association analysis of common variants in GIP in association with type 2 diabetes and related biochemical parameters. METHOD: A total of 2000 subjects which includes 1000 (584M/416F) cases with type 2 diabetes and 1000 (470M/530F) normoglycemic control subjects belonging to Dravidian ethnicity from South India were recruited to assess the effect of single nucleotide polymorphisms (SNPs) in GIP (rs2291725, rs2291726, rs937301) on type 2 diabetes in a case-control manner. The SNPs were genotyped by using tetra primer amplification refractory mutation system-PCR (ARMS PCR). For statistical analysis, our study population was divided into sub-groups based on gender (male and female). Association analysis was carried out using chi-squared test and the comparison of biochemical parameters among the three genotypes were performed using analysis of covariance (ANCOVA). RESULT: Initial analysis revealed that, out of the total three SNPs selected for the present study, two SNPs namely rs2291726 and rs937301 were in complete linkage disequilibrium (LD) with each other. Therefore, only two SNPs, rs2291725 and rs2291726, were genotyped for the association studies. No significant difference in the allele frequency and genotype distribution of any of the SNPs in GIP were observed between cases and controls (P > 0.05). Analysis of biochemical parameters among the three genotypes showed a significant association of total cholesterol (P = 0.042) and low density lipoprotein (LDL) with the G allele of the SNP rs2291726 in GIP (P = 0.004), but this was observed only in the case of female subjects. However this association does not remain significant after correction for multiple testing by Bonferroni's inequality method. CONCLUSION: No statistically significant association was observed between any of the SNPs analysed and type 2 diabetes in our population. But the analysis of biochemical parameters indicates that the G allele in rs2291726 may be a putative risk allele for increased LDL cholesterol and further studies in other population needs to be carried out for ascertaining its role in cholesterol metabolism and subsequent cardiovascular risk.

Case-control analysis of SNPs in GLUT4, RBP4 and STRA6: association of SNPs in STRA6 with type 2 diabetes in a South Indian population.

BACKGROUND: The inverse relationship between GLUT4 and RBP4 expression is known to play a role in the pathogenesis of type 2 diabetes. Elevated levels of RBP4 were shown to cause insulin resistance in muscles and liver. Identification of STRA6 as a cell surface receptor for RBP4 provides further link in this axis and hence we analyzed SNPs in these three genes for association with type 2 diabetes in a South Indian population. METHODOLOGY/PRINCIPAL FINDINGS: Selected SNPs in the three genes were analyzed in a total of 2002 individuals belonging to Dravidian ethnicity, South India, by Tetra Primer ARMS PCR or RFLP PCR. Allele frequencies and genotype distribution were calculated in cases and controls and were analyzed for association by Chi-squared test and Logistic regression. Haplotype analysis was carried out for each gene by including all the markers in a single block. We observed a significant association of three SNPs, rs974456, rs736118, and rs4886578 in STRA6 with type 2 diabetes (P = 0.001, OR 0.79[0.69-0.91], P = 0.003, OR 0.81[0.71-0.93], and P = 0.001, OR 0.74[0.62-0.89] respectively). None of the SNPs in RBP4 and GLUT4 showed any association with type 2 diabetes. Haplotype analysis revealed that two common haplotypes H1 (111, P = 0.001, OR 1.23[1.08-1.40]) and H2 (222, P = 0.002 OR 0.73[0.59-0.89]) in STRA6, H6 (2121, P = 0.006, OR 1.69[1.51-2.48]) in RBP4 and H4 (2121, P = 0.01 OR 1.41[1.07-1.85]) in GLUT4 were associated with type 2 diabetes. CONCLUSION: SNPs in STRA6, gene coding the cell surface receptor for RBP4, were significantly associated with type 2 diabetes and further genetic and functional studies are required to understand and ascertain its role in the manifestation of type 2 diabetes.