Association Between Trp64Arg Polymorphism of Beta-3 Adrenergic Receptor Gene and Susceptibility to Overactive Bladder: A Meta-Analysis

Objective: Some studies have been carried out to investigate the association between Trp64Arg polymorphism in beta-3 adrenergic receptor gene (ADRB3) and susceptibility to overactive bladder (OAB), but the results remain inconsistent. We carried out a meta-analysis to acquire a more accurate estimation. Methods: All eligible studies were searched in PubMed, Web of Science, Embase, and Cochrane Library. Pooled odds ratios, with 95% confidence intervals, were assessed for the association using fixed and random effects models. Results: The overall results of this meta-analysis demonstrated that there might be an association between Trp64Arg polymorphism and susceptibility to OAB in allele model, dominant model, and heterozygote comparison with a relative risk of 2.00 (95% CI 1.36-2.93), 2.13 (95% CI 1.20-3.76), and 2.07 (95% CI: 1.13-3.79), respectively. However, in the recessive model and homozygote comparison, no significant association between ESR1 Trp64Arg polymorphism and susceptibility to OAB was observed, with a relative risk of 2.47 (95% CI 0.63-9.73) and 3.12 (95% CI: 0.79-12.35), respectively. Based on trail sequential analysis, the results turned out to be true positive in the allele model, false positive in the dominant model and heterozygote comparison, and negative in the recessive model and homozygote comparison, respectively. Conclusion: Our analysis indicated that Trp64Arg polymorphisms in ADRB3 might increase the risk of OAB twice in the allele model, but further well-designed studies with large sample sizes are required to confirm the present findings in other modes and comparisons.

Automated summary

This meta-analysis investigated the association between Trp64Arg polymorphism in ADRB3 gene and susceptibility to OAB. The results suggest that Trp64Arg polymorphism might be associated with increased risk of OAB in different models and comparisons. However, further well-designed studies with large sample sizes are needed to confirm these findings.