Human blood metabolites and risk of severe COVID‐19: A Mendelian randomization study

Abstract

BackgroundEvidence 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.MethodsWe 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.ResultsFour 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.ConclusionThis 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.

Metabolic clues to aging: exploring the role of circulating metabolites in frailty, sarcopenia and vascular aging related traits and diseases

“…Firstly, we extracted SNPs with association thresholds at p < 1 × 10 −5 for each metabolite, which aligned with previous investigations ( Cai et al, 2022 ; Shang et al, 2023 ). Secondly, SNPs that did not exhibit linkage disequilibrium (LD) with other SNPs (with an r2 value less than 0.01 within a clustering window of 500 kb) were employed as genetic instruments for these metabolites.…”

“…The Frailty Index (FI) is used as a measure to assess this condition, taking into account various factors such as disability, diseases, physical and cognitive impairments, psychosocial risks, and geriatric syndromes (Mitnitski et al, 2001). The Rockwood FI, which is based on a deficit accumulation model, is an outcome measure for frailty, which assigns scores of 0 or 1 for each deficit, with the FI being the ratio of the number of deficits to a total of 49 and a higher FI score indicates a more severe level of frailty (Atkins et al, 2021;Chen Z. et al, 2023).…”