In:
PLOS ONE, Public Library of Science (PLoS), Vol. 16, No. 8 ( 2021-8-11), p. e0255402-
Abstract:
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 = 1.9x10-7; rs5798227, p = 2.2x10-7). 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.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0255402
DOI:
10.1371/journal.pone.0255402.g001
DOI:
10.1371/journal.pone.0255402.g002
DOI:
10.1371/journal.pone.0255402.t001
DOI:
10.1371/journal.pone.0255402.s001
DOI:
10.1371/journal.pone.0255402.s002
DOI:
10.1371/journal.pone.0255402.s003
DOI:
10.1371/journal.pone.0255402.s004
DOI:
10.1371/journal.pone.0255402.s005
DOI:
10.1371/journal.pone.0255402.s006
DOI:
10.1371/journal.pone.0255402.s007
DOI:
10.1371/journal.pone.0255402.s008
DOI:
10.1371/journal.pone.0255402.s009
DOI:
10.1371/journal.pone.0255402.s010
DOI:
10.1371/journal.pone.0255402.s011
DOI:
10.1371/journal.pone.0255402.s012
DOI:
10.1371/journal.pone.0255402.s013
DOI:
10.1371/journal.pone.0255402.s014
DOI:
10.1371/journal.pone.0255402.r001
DOI:
10.1371/journal.pone.0255402.r002
DOI:
10.1371/journal.pone.0255402.r003
DOI:
10.1371/journal.pone.0255402.r004
DOI:
10.1371/journal.pone.0255402.r005
DOI:
10.1371/journal.pone.0255402.r006
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2267670-3
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