Statistical power in COVID-19 case-control host genomic study design
Open Access
- 28 December 2020
- journal article
- letter
- Published by Springer Science and Business Media LLC in Genome Medicine
- Vol. 12 (1), 1-8
- https://doi.org/10.1186/s13073-020-00818-2
Abstract
The identification of genetic variation that directly impacts infection susceptibility to SARS-CoV-2 and disease severity of COVID-19 is an important step towards risk stratification, personalized treatment plans, therapeutic, and vaccine development and deployment. Given the importance of study design in infectious disease genetic epidemiology, we use simulation and draw on current estimates of exposure, infectivity, and test accuracy of COVID-19 to demonstrate the feasibility of detecting host genetic factors associated with susceptibility and severity in published COVID-19 study designs. We demonstrate that limited phenotypic data and exposure/infection information in the early stages of the pandemic significantly impact the ability to detect most genetic variants with moderate effect sizes, especially when studying susceptibility to SARS-CoV-2 infection. Our insights can aid in the interpretation of genetic findings emerging in the literature and guide the design of future host genetic studies.Keywords
Funding Information
- CANSSI Ontario STAGE
This publication has 25 references indexed in Scilit:
- Universal Screening for SARS-CoV-2 in Women Admitted for DeliveryThe New England Journal of Medicine, 2020
- CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, ChinaJournal of Infection, 2020
- Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populationsCell Discovery, 2020
- The UK Biobank resource with deep phenotyping and genomic dataNature, 2018
- Genetic susceptibility to infectious diseases: Current status and future perspectives from genome-wide approachesInfection, Genetics and Evolution, 2017
- Case-Control StudiesPublished by Cambridge University Press (CUP) ,2014
- Estimation of significance thresholds for genomewide association scansGenetic Epidemiology, 2008
- Genetic susceptibility to infectious diseases: big is beautiful, but will bigger be even better?The Lancet Infectious Diseases, 2006
- Infectogenomics: Insights from the Host Genome into Infectious DiseasesCell, 2006
- The impact of diagnostic error on testing genetic association in case–control studiesStatistics in Medicine, 2004