Coronavirus disease 2019 (COVID-19) is a current pandemic, and studies reported that older people have higher rates of infection and more severe cases. Recently, studies have revealed the involvement of both genetic and exposure factors in the susceptibility of COVID-19. However, the correlation between them is still unclear. Thus, we aimed to investigate the correlation between genetic and exposure factors associated with COVID-19. We retrieved the information of 7362 participants with COVID-19 testing results from the UK Biobank. We identified genetic factors for COVID-19 by genome-wide association studies (GWAS) summary analysis. In this study, 21 single-nucleotide polymorphisms (SNPs) and 15 exposure factors [smoking, alcohol intake, daytime dozing, body mass index (BMI), triglyceride, High Density Lipoprotein (HDL), diabetes, chronic kidney disease, chronic liver disease, dementia, atmosphere NO2 concentration, socioeconomic status, education qualification, ethnicity, and income] were found to be potential risk factors of COVID-19. Then, a gene-exposure (G × E) association network was built based on the correlation among and between these genetic factors and exposure factors. rs140092351, a SNP on microRNA miR1202, not only had the most significant association with COVID-19, but also interacted with multiple exposure factors. Dementia, alcohol consumption, daytime dozing, BMI, HDL, and atmosphere NO2 concentration were among most significant G × E interactions with COVID-19 infection (P = 0.001).
Keywords: Association analysis; COVID-19; Exposure risks; Genetic risks.
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