Evaluation of the Association of Omentin 1 rs2274907 A>T and rs2274908 G>A Gene Polymorphisms with Coronary Artery Disease in Indian Population: A Case Control Study

Abstract

Coronary artery disease (CAD) is a major cause of death all over the world. CAD is caused by atherosclerosis which is induced by the interaction of genetic factors and environmental factors. Traditional environmental risk factors include hyperlipidemia, diabetes mellitus, lack of exercise, obesity, poor diet and others. Genome-wide association studies have revealed the association of certain gene polymorphisms with susceptibility to CAD. Omentin 1 is an adipokine secreted by the visceral adipose tissues and has been reported to have anti-inflammatory, cardioprotective, and enhances insulin sensitivity. In this study, we examined the role of omentin-1 common single nucleotide polymorphisms (SNPs) (rs2274907 A>T and rs2274908 G>A) in CAD. We genotyped 100 CAD patients and 100 matched healthy controls from the south Indian population using an amplification refractory mutation system (ARMS-PCR) and allele-specific PCR (AS-PCR). Our result indicated the rs2274908 G>A is not associated with CAD. Results showed that there was a significant difference in rs2274907 A>T genotype distribution between controls and CAD cases (P-value < 0.05). Results indicated that the AT genotype of the rs2274907 is associated with CAD with OR = 3.0 (95% confidence interval (CI), 1.64 to 5.49), 1.65 (1.27 to 2.163), P = 0.002. The T allele of the rs2274907 was also associated with CAD with OR = 1.82 (95% CI, 1.193 to 2.80), 1.37 (1.08 to 1.74), P = 0.005. Rs2274907 genotype distribution was also correlated with serum total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), hypertension and diabetes. We conclude that the AT genotype and the T allele of the rs2274907 A>T is associated with Cad in the south Indian population. Further studies on the effect of the rs2274907 A>T on omentin-1 function are recommended, and future well-designed studies with larger sample sizes and in different populations are required to validate our findings.