Collider bias undermines our understanding of COVID-19 disease risk and severity

Gareth J. Griffith; Tim T. Morris; Matthew J. Tudball; Annie Herbert; Giulia Mancano; Lindsey Pike; Gemma C. Sharp; Jonathan Sterne; Tom M. Palmer; George Davey Smith; Kate Tilling; Luisa Zuccolo; Neil M. Davies; Gibran Hemani

doi:10.1038/s41467-020-19478-2

Nature Communications (Nov 2020)

Collider bias undermines our understanding of COVID-19 disease risk and severity

Gareth J. Griffith,
Tim T. Morris,
Matthew J. Tudball,
Annie Herbert,
Giulia Mancano,
Lindsey Pike,
Gemma C. Sharp,
Jonathan Sterne,
Tom M. Palmer,
George Davey Smith,
Kate Tilling,
Luisa Zuccolo,
Neil M. Davies,
Gibran Hemani

Affiliations

Gareth J. Griffith: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Tim T. Morris: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Matthew J. Tudball: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Annie Herbert: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Giulia Mancano: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Lindsey Pike: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Gemma C. Sharp: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Jonathan Sterne: Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove
Tom M. Palmer: Medical Research Council Integrative Epidemiology Unit, University of Bristol
George Davey Smith: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Kate Tilling: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Luisa Zuccolo: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Neil M. Davies: Medical Research Council Integrative Epidemiology Unit, University of Bristol
Gibran Hemani: Medical Research Council Integrative Epidemiology Unit, University of Bristol

DOI: https://doi.org/10.1038/s41467-020-19478-2
Journal volume & issue: Vol. 11, no. 1
pp. 1 – 12

Abstract

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Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising study design to account for this.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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