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Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
The Impact of Different Intensities of Physical Activity on Serum Urate and Gout: A Mendelian Randomization Study
Tangxun Yang1, Shilin Bi2, Xing Zhang3
1School of Physical Education, Xihua University, Chengdu 610039, China.
Abstract:
Physical activity is a potential protective factor against gout, but the role of exercise intensity in this context remains unclear. To overcome the limitations of observational studies in causal inference, this study employed a two-sample Mendelian randomization approach to explore the impact of different genetically proxied/predicted intensities of physical activity on serum urate concentration and the incidence of gout. Our data related to physical activity, serum urate, and gout were obtained from the UK Biobank, the Global Urate Genetics Consortium (GUGC), and the FinnGen dataset, respectively. Walking was included as representative of typical low-intensity physical activity in the analysis, and the other two types were moderate and vigorous physical activities. The estimation methods we used included the inverse-variance-weighted (IVW) method, MR-Egger regression, weighted-median method, simple-mode method, and weighted-mode method. Sensitivity analyses involved Rucker's framework, Cochran's Q test, funnel plots, MR-PRESSO outlier correction, and leave-one-out analysis. We found suggestive evidence from the inverse-variance-weighted method that moderate physical activity was a potential factor in reducing the incidence of gout (OR = 0.628, p = 0.034), and this association became more substantial in our subsequent sensitivity analysis (OR = 0.555, p = 0.006). However, we observed no distinctive effects of physical activity on serum urate concentration. In conclusion, our study supports some findings from observational studies and emphasizes the preventive role of moderate physical activity against gout. Given the limitations of the existing datasets, we call for future reexamination and expansion of our findings using new GWAS data.
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