Investigating the causal role of smoking in gout: A triangulation approach combining NHANES data, genetic correlation, and Mendelian randomization.

The relationship between smoking and the development of gout is not well understood. To address this, we adopted a triangulation framework that integrates observational analysis, genetic correlation estimation, and two-sample Mendelian randomization (MR) to examine whether smoking confers a causal risk for gout. We first performed a cross-sectional analysis using information for 13,626 participants from the National Health and Nutrition Examination Survey between 2013 and 2018. The association of smoking with gout was subsequently assessed through logistic regression models. We next investigated the extent of shared genetic factors between smoking phenotypes and gout. We were able to demonstrate this using the linkage disequilibrium score regression applied to genome-wide association study data of European ancestry. Finally, to verify the causality of our relationship, we carried out a two-sample MR analysis. We selected the inverse-variance weighted (IVW) method and confirmed the consistency of using the IVW method with other statistical methods, including weighted median, weighted mode, and simple mode, as well as MR-Egger regression. We performed sensitivity analyses to investigate the heterogeneity of the hypothesis and stability of the data. Our findings based on National Health and Nutrition Examination Survey data reveal that there is a strong positive association between smoking and the risk of gout (odds ratio [OR] = 1.94, 95% confidence interval [CI] = 1.48-2.55, P < .001). This association persisted after confounding adjustments (OR = 1.41, 95% CI = 1.04-1.91, P = .027). In the subgroup analyses, former smokers and current smokers of 10 to 20 cigarettes per day had a substantially increased risk. Post-linkage disequilibrium score regression analysis revealed that the significantly positive genetic correlations of smoking initiation and lifetime smoking index with gout risk were both significantly positive. Additional evidence for causality is presented by MR. Genetic prediction of smoking initiation statistically increases gout risk (IVW OR = 1.55, 95% CI = 1.26-1.90, P = 3.17 × 10-5). A much stronger association is evident for lifetime smoking index (IVW OR = 1.99, 95% CI = 1.44-2.76, P = 3.24 × 10-5). These findings are the same with or without heterogeneity by sensitivity analysis. In light of our integrated analysis, smoking is a causative factor for gout. This suggests that public health interventions like anti-smoking campaigns might reduce gout incidence.