Assessing the causal relationships between gout and hypertension: a bidirectional Mendelian randomisation study with coarsened exposures

Abstract

Objectives: Observational studies have demonstrated associations between gout and hypertension, but whether they are causal remains unclear. Our work aims to assess the causal relationship between gout and hypertension.

Methods: We obtained genetic information from the Taiwan Biobank, including 88,347 participants and 686,439 single-nucleotide polymorphisms (SNPs). A novel model of Mendelian randomisation (MR) with coarsened exposures was used to examine the causality between the liability of gout on hypertension and vice versa, using 4 SNPs associated with gout and 10 SNPs associated with hypertension after removal of SNPs associated with measured confounders. The binary exposure (gout/hypertension) can be considered a coarsened approximation of a latent continuous trait. The inverse-variance weighted (IVW) and polygenic risk score (PRS) methods were used to estimate effect size. The MR analysis with coarsened exposures was performed with and without adjustments for covariates.

Results: Of the 88,347 participants, 3253 (3.68%) had gout and 11,948 (13.52%) had hypertension (men, 31.9%; mean age 51.1 [SD, 11.1] years). After adjusting to measured confounders, MR analysis with coarsened exposures showed a significant positive causal effect of the liability of gout on hypertension in both the IVW method (relative risk [RR], 1.10; 95% confidence interval [CI], 1.03-1.19; p = 0.0077) and the PRS method (RR, 1.10; 95% CI, 1.02-1.19; p = 0.0092). The result of causality was the same before and after involving measured confounders. However, there was no causal effect of the liability of hypertension on gout.

Conclusions: In this study, we showed that the liability of gout has a causal effect on hypertension, but the liability of hypertension does not have a causal effect on gout. Adequate management of gout may reduce the risk of developing hypertension.

Keywords: Gout; Hypertension; Mendelian randomisation.

Fig. 1

Flow chart of SNP and patient quality control. Parameters are listed in the chart. SNPs, single-nucleotide polymorphisms

Fig. 2

Directed acyclic graph for the MR with coarsened exposure framework under modified assumptions. Dotted circles represent unobserved variables and complete circles represent observed variables.$Z,$ multiple genetic IVs;$X,$ other genetic variables;$V,$ environmental share;$G,$ genetic share;$M,$ measured confounders;$L,$ latent exposure;$D,$ measured discrete exposure;$Y,$ continuous or binary outcome

Fig. 3

Plot of the relative risk of gout to hypertension. Relative risks calculated using the corresponding ${\theta }^2$ values estimated by our GWAS reports are marked in red. Abbreviations: IVW-FE, IVW fixed-effect method; PRS, polygenic risk score; CI, confidence interval

Fig. 4

Plot of the relative risk of hypertension to gout. Relative risks calculated using the corresponding ${\theta }^2$ values estimated by our GWAS reports are marked in red. Abbreviations: IVW-FE, IVW fixed-effect method; PRS, polygenic risk score; CI, confidence interval

Fig. 5

MR analysis with coarsened exposures from gout to hypertension with adjustment to measured confounders after removing SNPs associated with measured confounders. IVW-FE, IVW fixed-effects method; PRS, polygenic risk scores; CI, confidence interval