The Role of Paraoxonase 1 (PON1) Gene Polymorphisms in Coronary Artery Disease: A Systematic Review and Meta-Analysis

Although many studies have investigated the association of paraoxonase 1 (PON1) polymorphisms with coronary artery disease (CAD). However, the outcomes were not consistent and remain uncertain. Therefore, it is the need of the hour to analyze the available literature and evaluate the association of PON1 polymorphisms with the CAD. All the relevant studies published in the English language from January 1, 2000, up to September 20, 2020, were identified by searching through various electronic databases. The two researchers independently extracted the information. The data were analyzed by using the MetaGenyo program. The pooled odds ratio was used to find the associations between CAD and PON1 polymorphisms. In the final analysis, we include 10 studies regarding the association of PON1 polymorphisms (rs662 and rs854560) with CAD. Overall, the Q192R polymorphism increased the risk of CAD in the tested genetic models including the homozygote model: OR 1.35, CI 1.02-1.79; allelic model: OR 1.16, CI 1.00-1.33; dominant model: OR 1.25, CI 1.03-1.52. The L55M polymorphism does not significantly associated with CAD in all the tested genetic models including the homozygote model: OR 1.00 CI, 0.64-1.56; allelic model: OR 1.02, 95% CI 0.84-1.23; dominant model: OR 1.08, CI 0.89-1.31. Further analysis showed no publication bias exists in meta-analysis. Our findings suggested that rs662 in the coding region was significantly associated with the CAD however, rs854560 has no significant association with the disease. Nevertheless, in future, there is a need for more studies with a larger sample size which may provide a more definite conclusion. Study Registration: PROSPERO registration number CRD42020202278

Automated summary

This study analyzed the association of PON1 gene polymorphisms with CAD and found that the Q192R polymorphism increased the risk of CAD while the L55M polymorphism showed no significant association. More studies with larger sample sizes are needed for a more definitive conclusion in the future.