Evaluation of the causal effects of blood lipid levels on gout with summary level GWAS data: two-sample Mendelian randomization and mediation analysis


Observational studies have identified gout patients are often comorbid with dyslipidemia. However, the relationship between dyslipidemia and gout is still unclear. We first performed Mendelian randomization (MR) to evaluate the causal effect of four lipid traits on gout and serum urate based on publicly available GWAS summary statistics (n ~100,000 for lipid, 69,374 for gout and 110,347 for serum urate). MR showed each standard deviation (SD) (~12.26 mg/dL) increase in HDL resulted in about 25% (95% CI 9.0%–38%, p = 3.31E−3) reduction of gout risk, with 0.09 mg/dL (95% CI: −0.12 to −0.05, p = 7.00E−04) decrease in serum urate, and each SD (~112.33 mg/dL) increase of TG was associated with 0.10 mg/dL (95% CI: 0.06–0.14, p = 9.87E−05) increase in serum urate. Those results were robust against various sensitive analyses. Additionally, independent effects of HDL and TG on gout/serum urate were confirmed with multivariable MR. Finally, mediation analysis demonstrated HDL or TG could also indirectly affect gout via the pathway of serum urate. In conclusion, our study confirmed the causal associations between HDL (and TG) and gout, and further revealed the effect of HDL or TG on gout could also be mediated via serum urate.

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Data availability

The data sets generated during and/or analysed during the current study are available in the GLGC and Global Urate Genetics Consortium repository, [http://csg.sph.umich.edu/ and http://metabolomics.helmholtz-muenchen.de/].


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We are indebted to the GLGC and Global Urate Genetics Consortium studies for public availability in making the summary data and we are grateful to all the investigators and participants for their contributions to those studies. The data analyses in the present study were supported by the high-performance computing at Xuzhou Medical University. We are grateful to reviewer for the constructive comments, which substantially improved our manuscript.


The research of PZ was supported in part by the Youth Foundation of Humanity and Social Science funded by Ministry of Education of China (18YJC910002), the Natural Science Foundation of Jiangsu Province of China (BK20181472), the China Postdoctoral Science Foundation (2018M630607 and 2019T120465), the QingLan Research Project of Jiangsu Province for Outstanding Young Teachers, the Six-Talent Peaks Project in Jiangsu Province of China (WSN-087), the Training Project for Youth Teams of Science and Technology Innovation at Xuzhou Medical University (TD202008), the Postdoctoral Science Foundation of Xuzhou Medical University, the National Natural Science Foundation of China (81402765), and the Statistical Science Research Project from National Bureau of Statistics of China (2014LY112). The research of SH was supported in part by the Social Development Project of Xuzhou City (KC19017). The research of TW was supported in part by the Social Development Project of Xuzhou City. The research of TW was supported in part by the Social Development Project of Xuzhou City (KC20062).

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PZ, TW, and SH conceived the design of the study; PZ and XY obtained the data; PZ and XY cleared up the data sets; PZ, TW, and XY mainly performed the data analyses; PZ and XY helped clear and analyze the data; PZ, XY, and TW interpreted the results of the data analyses; PZ and XY drafted the paper, and all authors approved the paper and provided relevant suggestions.

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Correspondence to Shuiping Huang or Ping Zeng.

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Yu, X., Wang, T., Huang, S. et al. Evaluation of the causal effects of blood lipid levels on gout with summary level GWAS data: two-sample Mendelian randomization and mediation analysis. J Hum Genet (2020). https://doi.org/10.1038/s10038-020-00863-0

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