Exploring causal relationships between COVID-19 and cardiometabolic disorders: A bi-directional Mendelian randomization study

BackgroundMore than 100 million cases of COVID-19 have been reported worldwide. A number of risk factors for infection or severe infection have been identified, however observational studies were subject to confounding bias. In addition, there is still limited knowledge about the complications or medical consequences of the disease. MethodsHere we performed bi-directional Mendelian randomization (MR) analysis to evaluate causal relationships between liability to COVID-19 (and severe/critical infection) and a wide range of around 30 cardiometabolic disorders (CMD) or traits. Genetic correlation (rg) was assessed by LD score regression(LDSC). The latest GWAS summary statistics from the COVID-19 Host Genetics Initiative was used, which comprised comparisons of general population controls with critically ill, hospitalized and any infected cases. ResultsOverall we observed evidence that liability to COVID-19 or severe infection may be causally associated with higher risks of type 2 diabetes mellitus(T2DM), chronic kidney disease(CKD), ischemic stroke (especially large artery stroke[LAS]) and heart failure(HF) when compared to the general population. On the other hand, our findings suggested that liability to atrial fibrillation (AF), stroke (especially LAS), obesity, diabetes (T1DM and T2DM), low insulin sensitivity and impaired renal function (low eGFR and diabetic kidney disease) may be causal risk factors for COVID-19 or severe disease. In genetic correlation analysis, T2DM, CAD, obesity, fasting insulin, CKD, gout, stroke and urate showed positive rg with critical or hospitalized infection. All above findings passed multiple testing correction at a false discovery rate (FDR)<0.05. ConclusionsIn summary, this study provides evidence for tentative bi-directional causal associations between liability to COVID-19 and severe disease and a number of CM disorders. Further replications and prospective studies are required to verify the findings.