Risk factors and long-term consequences of COVID-19 infection are unclear but can be investigated with large-scale genomic data. To distinguish correlation from causation, we performed in-silico analyses of three COVID-19 outcomes (N > 1,000,000). We show genetic correlation and putative causality with depressive symptoms, metformin use (genetic causality proportion (gĉp) with severe respiratory COVID-19 = 0.576, p = 1.07 × 10 −5 and hospitalized COVID-19 = 0.713, p = 0.003), and alcohol drinking status (gĉp with severe respiratory COVID-19 = 0.633, p = 7.04 × 10 −5 and hospitalized COVID-19 = 0.848, p = 4.13 × 10 −13 ). COVID-19 risk loci associated with several hematologic biomarkers. Comprehensive findings inform genetic contributions to COVID-19 epidemiology, molecular mechanisms, and risk factors and potential long-term health effects of severe response to infection.
【저자키워드】 COVID-19, SARS-CoV-2, diabetes, alcohol, Causal inference, genetic overlap, 【초록키워드】 Biomarkers, Epidemiology, Genetic, Infection, outcome, risk factor, Depressive symptoms, Health, COVID-19 infection, correlation, in-silico, Analysis, Factor, genomic data, molecular mechanisms, hematologic, hospitalized COVID-19, risk loci, Effect, consequence, Comprehensive, performed, proportion, investigated, 【제목키워드】 Behavior, Drinking, participant, descent, European, Associate,