Abstract
BackgroundWhether adiponectin (ADIPOQ) polymorphisms are associated with coronary artery disease (CAD) remain controversial. Therefore, we performed this meta-analysis to better explore potential roles of ADIPOQ polymorphisms in CAD.MethodsPubMed, Web of Science, Embase and CNKI were searched for eligible studies. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.ResultsTotally 45 studies were included for pooled analyses. A significant association with the susceptibility to CAD was detected for rs2241766 (dominant model: p = 0.0009, OR = 0.82, 95%CI 0.73–0.92; recessive model: p = 0.04, OR = 1.29, 95%CI 1.02–1.64; allele model: p < 0.0001, OR = 0.80, 95%CI 0.73–0.88) polymorphism in overall population. Further subgroup analyses by ethnicity showed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, whereas rs2241766 polymorphism was significantly associated with the susceptibility to CAD in Caucasians, East Asians and South Asians.ConclusionsOur findings indicated that rs1501299 and rs2241766 polymorphisms both affect the susceptibility to CAD in certain populations.
Highlights
Whether adiponectin (ADIPOQ) polymorphisms are associated with coronary artery disease (CAD) remain controversial
A significant association with the susceptibility to CAD was detected for rs2241766 polymorphism in overall analyses
Further subgroup analyses by ethnicity revealed that rs1501299 polymorphism was significantly associated with the susceptibility to CAD in East Asians, whereas rs2241766 polymorphism was significantly associated with the susceptibility to CAD in Caucasians, East Asians and South Asians
Summary
Whether adiponectin (ADIPOQ) polymorphisms are associated with coronary artery disease (CAD) remain controversial. We performed this meta-analysis to better explore potential roles of ADIPOQ polymorphisms in CAD. Numerous genetic variants were found to be associated with an increased susceptibility to CAD by previous genetic association studies, and screening of common causal variants was proved to be an efficient way to predict the individual risk of developing CAD [5, 6].
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