Investigating the causal role of smoking in gout

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.

Authors

Institutions

Publication Details

Journal
Medicine
Published
2026-08-28
DOI
https://doi.org/10.1097/md.0000000000050449
Primary Topic
Gout, Hyperuricemia, Uric Acid
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the causal role of smoking in gout

Fang Lv, 韦峭峰, Qing Du, Hongju Zhang et al.
Medicine
Gout, Hyperuricemia, Uric Acid
article

Investigating the causal role of smoking in gout

Fang Lv, 韦峭峰, Qing Du, Hongju Zhang, Lanlan Li
article en

Abstract

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.

MedicineVol. 105(35)
People’s Hospital of Rizhao (CN), Central Hospital of Zibo (CN)
Good health and well-being
Openalex Percentile: Top 10%
Gout, Hyperuricemia, Uric Acid
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.