Medicine (Baltimore). 2024 Oct 18;103(42):e39591. doi: 10.1097/MD.0000000000039591.
ABSTRACT
Many previous observational studies have disputed whether there is a link between uric acid and stroke. And the causal relationship between uric acid and stroke is unclear. To determine whether there is a causal relationship between uric acid and stroke by using mendelian randomization (MR). Uric acid dataset was obtained from Anna Kottgen et al, with a sample size of 110,347 people, including 2450,548 single nucleotide polymorphisms (SNPs). Stroke pooled data from Malik R et al, publicly available in MEGASTROKE genome-wide association study, included meta-analysis data from 40,585 stroke patients and 406,111 control patients, totaling 8211,693 SNPs. The summary data of genome-wide association study of uric acid and stroke were collected from publicly available online databases. Inverse variance weighting was used to determine the causal relationship between uric acid and stroke. MR-Egger and weighted median model were used for supplementary analysis. Results were then analyzed for heterogeneity, pleiotropy, and sensitivity to ensure no statistical pleiotropy and to reduce bias. A total of 27 SNPs were included in this study after the disequilibrium instrumental variables were excluded. Check the PhenoScanner database for SNPs associated with confounders. In the end, a total of 8 SNPs were excluded. Two SNPs were excluded because the correction direction was the same. Since the F statistic is >10, rs10761587 and rs1825043 are excluded. Finally, 15 SNPs were selected as uric acid instrumental variables. Inverse variance weighting-fixed effect model suggested that there was no causal relationship between uric acid and stroke (odds ratio = 1.004, 95% confidence interval = 0.940, 1.072). MR-Egger and weighted median model also showed the same result. In addition, the results of this study were robust without heterogeneity and pleiotropy. This MR study suggests no support of a causal relationship between uric acid and stroke.
PMID:39432637 | DOI:10.1097/MD.0000000000039591
