Molecular impact of single nucleotide polymorphisms in GIPR gene among type 2 diabetes mellitus patients in the Saudi population

沙特阿拉伯人群中GIPR基因单核苷酸多态性对2型糖尿病患者的分子影响

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Abstract

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a metabolic disorder that affects the human blood glucose levels. Previous studies have confirmed the role of the gastric inhibitory polypeptide receptor (GIPR) gene in T2DM, obesity, and other human diseases. This study aimed to identify the molecular role of 5 SNPs (rs1800436, rs1800437, rs2302382, rs10423928, and rs34125392) in the GIPR gene in patients with T2DM in the Saudi population. METHODS: This prospective case-control study enrolled 118 T2DM cases and 118 control participants based on the inclusion and exclusion criteria. Serum was collected from peripheral blood for biochemical tests, while EDTA blood was used for HbA1c and molecular analysis. RESULTS: In this study, T2DM cases were compared with control population to study the baseline characteristics along with molecular data. Genotyping and allelic association analysis showed that rs2302382, (OR-2.757 and OR-2.303) and rs10423928 (OR-3.859 and 2.206) are associated, while genotyping analysis alone showed rs34125392 (OR-1.776) is associated. The co-dominant model (OR-2.226) was associated with obese vs. non-obese participants among T2DM cases (p = 0.039). Females showed a positive association with rs2302382 (OR-3.701; p = 0.003) and rs10423928 (OR-2.343; p = 0.033) SNPs, while males showed a positive association with rs1800437 (OR-1.849; p = 0.040) rs2302382 (OR-2.418; p = 0.016), and rs10423928 (OR-3.641; p = 0.019) SNPs. ANOVA analysis and linkage disequilibrium exhibited a positive association along with gene-gene interaction in GMDR analysis. Linear regression, haplotype analysis and Frutcherman-Reingold, circle, and Kamada-Kawali models showed negative association. CONCLUSION: Our findings confirm a strong and significant association between rs2302382, rs10423928 and rs34125392 SNPs in T2DM. Additional analyses, such as ANOVA, haplotype analysis, gene-gene interaction, and graphical depiction models revealed genetic interactions among the studied SNPs.

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