ABSTRACT
Background Many COVID-19-infected patients have been observed to develop unexplained valvular heart disease (VHD), and the association between COVID-19 and VHD remains inconclusive. Therefore, we conducted a two-sample Mendelian randomization study to infer causality between COVID-19 and VHD from a genetic perspective using COVID-19 genetic tools.Methods This study used genetic variables and summary statistics from COVID-19 and VHD genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) were selected based on the assumption of instrumental variables (IVs). The inverse-variance weighted (IVW) method was used as the main analysis method to summarize the causal effects between exposure and outcome, while the weighted median and weighted mode methods were used as secondary methods. MR-Egger was used to test for horizontal pleiotropy, and the Q-test was used to test for heterogeneity. Sensitivity analysis was conducted using leave-one-out method. Scatterplots, forest plots, and funnel plots were used to visualize the results of MR analysis.Results In this study, seven COVID-19-related SNPs were selected as IVs, and the IVW [odds ratio (OR) = 1.16, 95% confidence interval (CI) = 1.04 − 1.28, P = 0.008], weighted median (OR = 1.21, 95% CI = 1.06 − 1.39, P = 0.006), and weighted mode (OR = 1.27, 95% CI = 1.05 − 1.54, P = 0.047) analysis methods suggested a causal effect of COVID-19 on CHD. MR-Egger indicated no evidence of horizontal pleiotropy (P = 0.589), and the Q-test suggested no heterogeneity (IVW, P = 0.349). Sensitivity analysis indicated robustness of the MR analysis results.Conclusions MR analysis revealed a causal effect of COVID-19 infection on the occurrence of VHD, indicating that patients with COVID-19 had a higher risk of VHD.