ArticlebioRxiv : the preprint server for biology2025
Integrated analysis of COVID-19 multi-omics data for eQTLs reveals genetic mechanisms underlying disease severity.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The global pandemic caused by the SARS-CoV-2 virus provided an unprecedented opportunity to investigate genetic factors influencing the disease severity of the viral infection. Despite a plethora of recent research on both SARS-CoV-2 and COVID-19, few have taken a systems biology approach to address individual-level variation, especially based on non-European populations. Accordingly, we analyzed multi-omics data generated at three timepoints from 193 Korean COVID-19 patients with mild or severe symptoms, composed of whole genome sequencing, blood-based single-cell RNA-sequencing (2.15M cells), 195 cytokine profiles, and human leukocyte antigen (HLA) allele data. We identified expression quantitative trait loci (eQTLs), disease severity interacting eQTLs (
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