Transcriptome-wide summary data-based Mendelian randomization analysis reveals 38 novel genes associated with severe...

Severe COVID-19 has a poor prognosis, while the genetic mechanism underlying severe COVID-19 remains largely unknown. We aimed to identify genes that are potentially causally associated with severe COVID-19. We conducted a summary data-based Mendelian randomization (SMR) analysis using expression quantitative trait loci (eQTL) data from 49 different tissues as the exposure and three COVID-19-phenotypes (very severe respiratory confirmed COVID-19 [severe COVID-19], hospitalized COVID-19, and SARS-CoV-2 infection) as the outcomes. SMR using multiple SNPs was used as a sensitivity analysis to reduce false positive rate. Multiple testing was corrected using the false discovery rate (FDR) q-value. We identified 309 significant gene-trait associations (FDR q value < 0.05) across 46 tissues for severe COVID-19, which mapped to 64 genes, of which 38 are novel. The top five most associated protein-coding genes were Interferon Alpha and Beta Receptor Subunit 2 (IFNAR2), 2'-5'-Oligoadenylate Synthetase 3 (OAS3), mucin 1 (MUC1), Interleukin 10 Receptor Subunit Beta (IL10RB), and Napsin A Aspartic Peptidase (NAPSA). The potential causal genes were enriched in biological processes related to type I interferons, interferon-gamma inducible protein 10 production, and chemokine (C-X-C motif) ligand 2 production. In addition, we further identified 23 genes and 5 biological processes which are unique to hospitalized COVID-19, as well as 13 genes that are unique to SARS-CoV-2 infection. We identified several genes that are potentially causally associated with severe COVID-19. These findings improve our limited understanding of the mechanism of COVID-19 and shed light on the development of therapeutic agents for treating severe COVID-19.