TY - JOUR
AU - van Blokland, Irene V.
AU - Lanting, Pauline
AU - Ori, Anil P.S.
AU - Vonk, Judith M.
AU - Warmerdam, Robert C.A.
AU - Herkert, Johanna C.
AU - Boulogne, Floranne
AU - Claringbould, Annique
AU - Lopera-Maya, Esteban A.
AU - Bartels, Meike
AU - Hottenga, Jouke Jan
AU - Ganna, Andrea
AU - Karjalainen, Juha
AU - Hayward, Caroline
AU - Fawns-Ritchie, Chloe
AU - Campbell, Archie
AU - Porteous, David J.
AU - Cirulli, Elizabeth T.
AU - Barrett, Kelly M.Schiabor
AU - Riffle, Stephen
AU - Bolze, Alexandre
AU - White, Simon
AU - Tanudjaja, Francisco
AU - Wang, Xueqing
AU - Ramirez, Jimmy M.
AU - Lim, Yan Wei
AU - Lu, James T.
AU - Washington, Nicole L.
AU - de Geus, Eco J.C.
AU - Deelen, Patrick
AU - Boezen, H. Marike
AU - Franke, Lude H.
PY - 2021
DA - August
TI - Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility
JO - PLoS ONE
VL - 16
IS - 8
DO - https://doi.org/10.1371/journal.pone.0255402
AB - 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, largeeffect 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.
PB - Public Library of Science
UR - https://www.research.ed.ac.uk/en/publications/91be4a57-7f81-44ed-a4f0-fe5f44cbe522
KW - Coronavirus (COVID-19)
ER