Affiliation:
1. The First Hospital of China Medical University
2. Cangzhou Medical College
3. The First Affiliated Hospital of Dalian Medical University
4. China Medical University
5. University of South Florida
Abstract
Abstract
Background
Evidence suggests that coronavirus disease 2019 (COVID-19) is associated with the risk of cardiovascular diseases (CVDs). However, the results are inconsistent, and the causality remains to be established. We aimed to investigate the potential causal relationship between COVID-19 and CVDs by using two-sample Mendelian randomization (MR) analysis.
Methods
Summary-level data for COVID-19 and CVDs including myocarditis, heart failure (HF), acute myocardial infarction (AMI), arrhythmia and venous thromboembolism (VTE) were obtained from the IEU OpenGWAS project, a public genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) were used as instrumental variables. Five complementary MR methods were performed, including inverse variance weighted (IVW), MR-Egger, weighted median, weighted mode and simple mode methods. IVW method was considered as the primary approach. Besides, sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis, were performed to evaluate the robustness of the results.
Results
According to the IVW results, our MR study indicated that genetically predicted COVID-19 was not causally connected with the risk of CVDs [myocarditis: odds ratio (OR) = 1.407, 95% confidence interval (CI) = 0.761–2.602, p-value = 0.277; HF: OR = 1.180, 95% CI = 0.980–1.420, p-value = 0.080; AMI: OR = 1.002, 95% CI = 0.998–1.005, p-value = 0.241; arrhythmia: OR = 0.865, 95% CI = 0.717–1.044, p-value = 0.132; VTE: OR = 1.013, 95% CI = 0.997–1.028, p-value = 0.115]. The supplementary MR methods showed similar results. Sensitivity analyses suggested that the causal estimates were robust.
Conclusion
This two-sample MR analysis did not provide sufficient evidence for a causal relationship between COVID-19 and the risk of acute CVDs, which may provide new insights into the prevention of acute CVDs in COVID-19 patients.
Publisher
Research Square Platform LLC
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