Title: Analysis of COVID-19 genetic risk susceptibility using UK Biobank SNP genotype data

Authors: Taewan Goo; Kyulhee Han; Catherine Apio; Taesung Park

Addresses: Interdisciplinary Program in Bioinformatics, Seoul National University, Gwanak-gu, Seoul, South Korea ' Interdisciplinary Program in Bioinformatics, Seoul National University, Gwanak-gu, Seoul, South Korea ' Interdisciplinary Program in Bioinformatics, Seoul National University, Gwanak-gu, Seoul, South Korea ' Department of Statistics, Seoul National University, Gwanak-gu, Seoul, South Korea

Abstract: The coronavirus disease 2019 (COVID-19) has become a global pandemic. Here, we performed a study on host susceptibility to COVID-19 infection using COVID-19 test results and genomic data released by UK Biobank until early October of 2020. The data consisted of 27,713 samples including 2740 positive cases. We employed genome-wide association study, gene-level association and pathway analyses using common and rare variants. Among these analyses, only pathway analysis based on rare variants found seven significant pathways. Among them, the JAK-STAT pathway and glycolipid biosynthesis pathway have been reported to be associated with a viral infection, especially COVID-19 infection. Further, we found new pathways that were not previously reported, including pathways related to cellular signalling like NLR signalling pathway. Additional experiments and studies of these pathways may unveil the pathophysiological of COVID-19 and identify highly susceptible groups.

Keywords: COVID-19; GWAS; host genetics; infection susceptibility; pathway analysis.

DOI: 10.1504/IJDMB.2021.116879

International Journal of Data Mining and Bioinformatics, 2021 Vol.25 No.1/2, pp.1 - 16

Received: 23 Mar 2021
Accepted: 05 Apr 2021
Published online: 05 Aug 2021 *

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