Abstract
Evidence supports the observational associations of human blood metabolites with the risk of severe COVID-19. However, little is known about the potential pathological mechanisms and the analysis of blood metabolites may offer a better understanding of the underlying biological processes. We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 486 blood metabolites and the risk of severe COVID-19. The inverse-variance weighted (IVW) model was used as the primary two-sample MR analysis method to estimate the causal relationship of the exposure on the outcome. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot. Four hunderd and eighty six metabolites were included for MR analysis following rigorous genetic variants selection. After MR analyses and sensitivity analysis filtration, we found weak evidence of an association between 3-hydroxybutyrate (odds ratio [OR] = 1.21, 95% CI, 1.07-1.38, p = .0036) and the risk of severe COVID-19. A series of sensitivity analyses have been carried out to confirm the rigidity of the above results. This study suggested a causal relationship between 3-hydroxybutyrate and the severity of COVID-19, thus providing novel insights into biomarkers and pathways for COVID-19 prevention and clinical interventions.
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