TY - JOUR
T1 - Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility
AU - Illumina, Inc.
AU - Genomics England Research Consortium
AU - Lifelines COVID-19 cohort study
AU - The COVID-19 Host Genetics Initiative
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
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.
AU - Mierau, Jochen O.
AU - Dekens, Jackie
AU - Nolte, Ilja
AU - Dijkema, Marjolein X.L.
AU - Wiersma, Henry H.
AU - Jankipersadsing, Soesma A.
AU - Cho, Judy H.
AU - Loos, Ruth J.F.
AU - Moscati, Arden
AU - Chang, Yoosoo
AU - Choe, Pyoeng Gyun
AU - Haraldsson, Asgeir
AU - Ingvarsson, Ragnar F.
AU - Jonsdottir, Ingileif
AU - Palsson, Runolfur
AU - Stefansson, Kari
AU - Thorsteinsdottir, Unnur
AU - Melsted, Pall
N1 - Publisher Copyright:
© 2021 van Blokland et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2021/8
Y1 - 2021/8
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85112461727&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0255402
DO - 10.1371/journal.pone.0255402
M3 - Article
C2 - 34379666
AN - SCOPUS:85112461727
SN - 1932-6203
VL - 16
JO - PLoS ONE
JF - PLoS ONE
IS - 8
M1 - e0255402
ER -