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

Publication Type : Journal Article

Publisher : BMC Medical Genetics

Source : BMC Medical Genetics, Volume 11, Number 1 (2010)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-77955077171&partnerID=40&md5=38f83987881d7d6458d38fdac2cd0cd8

Keywords : adult, Age of Onset, allele, Alleles, article, Biochemistry, Blood, body mass, Body Mass Index, case control study, Case-Control Studies, cholesterol, controlled study, diabetes mellitus, ethnicity, exon, Exons, female, gastric inhibitory polypeptide, gene amplification, gene frequency, gene linkage disequilibrium, genetic association, genetic predisposition, Genetic Predisposition to Disease, genetic variability, Genetic Variation, genetics, genotype, human, Humans, India, intron, Introns, LDL, low density lipoprotein, low density lipoprotein cholesterol, major clinical study, male, middle aged, non insulin dependent diabetes mellitus, onset age, pathophysiology, polymerase chain reaction, Polymorphism, population genetics, Single Nucleotide, single nucleotide polymorphism, Tetra, Type 2

Campus : Amritapuri

School : School of Engineering

Department : Electronics and Communication

Year : 2010

Abstract : 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. © 2010 Sugunan et al; licensee BioMed Central Ltd.

Cite this Research Publication : Da Sugunan, Nair, A. Ka, Kumar, Hb, and Gopalakrishnapillai, Aa, “A case-control analysis of common variants in GIP with type 2 diabetes and related biochemical parameters in a South Indian population”, BMC Medical Genetics, vol. 11, 2010.

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