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ABSTRACT. This meta-analysis investigated the correlation between the PPARγ2 Pro12Ala polymorphism and cardiovascular disease (CVD). Electronic database and manual searches were conducted to retrieve studies published relevant to the PPARγ2 Pro12Ala polymorphism and CVD. Rigorous inclusion and exclusion criteria were employed for selection of high-quality patients-control studies. Statistical data analyses on allelic, dominant, homozygous, heterozygous, and recessive inheritance models were performed using the R 3.1.0 and Stata 12.0 software. We enrolled 12 case-control studies consisting of 10,189 patients with CVD [1070 with myocardial infarction (MI), 7849 with coronary artery disease (CAD), and 1270 with acute coronary syndromes (ACS)] and 17,899 controls. The results of meta-analyses revealed that the PPARγ2 Pro12Ala (rs1801282) polymorphism was correlated with a higher risk of CVD under both allelic and dominant models, while no statistical significance was found under (2015) homozygous, heterozygous, or recessive models. Subgroup analysis based on disease showed that the PPARγ2 Pro12Ala (rs1801282) polymorphism was correlated with a higher risk of MI under both allelic and dominant models, while no statistical significance was found for association with CAD or ACS under allele or dominant models. Furthermore, under homozygous, heterozygous, and recessive models, the PPARγ2 Pro12Ala (rs1801282) polymorphism had no statistically significant association with MI, CAD, or ACS. The results of this meta-analysis suggest that the PPARγ2 Pro12Ala (rs1801282) polymorphism might be correlated with a higher risk of CVD, particularly MI, and could serve as an important early indicator for CVD.

ABSTRACT. We aimed to confirm the correlations between rs2359612 and rs9923231 single nucleotide polymorphisms (SNPs) in the vitamin K epoxide reductase complex subunit 1 (VKORC1) gene and the risk of cardiovascular and cerebrovascular diseases (CCVDs) using metaanalysis. Electronic databases were exhaustively searched for relevant case-control studies by employing stringent inclusion and exclusion criteria. Manual retrieval was also conducted to obtain additional pertinent literature. The STATA statistical software was employed for the process of evidence synthesis. The initial literature search broadly identified 225 studies relevant to our topic of interest, and after multiple rounds of screening, 10 clinical case-control studies met the final inclusion criteria and were selected for this meta-analysis. The selected studies represented a combined total of 7329 patients with CCVD and 7951 healthy controls. Our meta-analysis demonstrated that the VKORC1 rs2359612 and rs9923231 SNPs were closely associated with high risk for CCVD (rs2359612: allelic: OR = 1.23, 95%CI = 1.00-1.50, P = 0.047; dominant: OR = 1.32, 95%CI = 1.19-1.46, P < 0.001; rs9923231: allelic: OR = 0.74, 95%CI = 0.63-0.87, P < 0.001; dominant: OR = 0.67, 95%CI = 0.55-0.82, P < 0.001). Our meta-analysis provides strong evidence that two SNPs in the VKORC1 gene, rs2359612 and rs9923231, contribute to the risk of CCVD.