Venous thromboembolism (VTE) is known to be intricately linked to severe COVID-19 (sCOVID-19) occurrence. Herein, we employed univariable Mendelian randomization (MR) and transcriptome analysis to predict the causal association and associated signaling networks between VTE and sCOVID-19.
Potential VTE and sCOVID-19 association was assessed using MR-Egger, weighted median, simple mode, weighted mode, and inverse variance weighted (IVW) regression. We conducted independent univariable analyses involving VTE and sCOVID-19. Using heterogeneity, pleiotropy, and the Leave-One-Out examinations, we performed sensitivity analyses. Thereafter, we performed transcriptome analysis of the GSE164805 dataset to identify differentially expressed genes (DEGs) linked to single nucleotide polymorphisms (SNPs). Lastly, we conducted immune analyses.
Based on our univariable analysis, VTE was a strong indicator of sCOVID-19 development, and it was intricately linked to sCOVID-19. We further conducted sensitivity analysis to demonstrate the reliability of our results. Using differential analysis, we identified 15 major genes, namely,
Herein, we demonstrated we strong association between VTE and enhanced sCOVID-19 risk. We also identified 15 DEGs which potentially contribute to the shared immunologic pathogenesis between VTE and sCOVID-19.