Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9×10-7; rs5798227, p = 2.2×10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
【초록키워드】 COVID-19, cross-sectional, SARS-COV-2 infection, susceptibility, COVID-19 pandemic, variant, Symptoms, Cohort, Viral, severity of COVID-19, phenotype, SNP, genetic susceptibility, genetic variants, Genetic variant, GWAS, predict, COVID-19 susceptibility, genetic associations, genetic association, COVID-19 cases, overlap, COVID-19 case, scenario, effort, viral infectious diseases, pursuit, viral outbreak, viral infectious disease, genome-wide significance, Genetic studies, genetic architecture, genetic study, while, Inclusion, controls, independent, observé, IMPROVE, shown, predicted, the disease, conducted, analysis, reached, with COVID-19, 【제목키워드】 Genetic, Factor, Host, identify, contribute,