A framework for assessing selection and misclassification bias in mendelian randomisation studies: an illustrative example between body mass index and covid-19

Mendelian randomisation (MR) studies, which investigate causal effects of exposures on disease, might be biased by sample selection and misclassification if phenotypes are not measured universally with the same definition in all study populations or participants. For example, in MR analyses of effec...

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Published in:BMJ (Online) 2023-06, Vol.381, p.e072148
Main Authors: Clayton, Gemma L, Gonçalves, Ana, Soares, Goulding, Neil, Borges, Maria Carolina, Holmes, Michael V, Davey, George, Smith, Tilling, Kate, Lawlor, Deborah A, Carter, Alice R
Format: Article
Language:English
Subjects:
Bias
Body Mass Index
COVID-19
Genomes
Humans
Infections
Laboratories
Mendelian Randomization Analysis
Missing data
Phenotypes
Population studies
Questionnaires
Research Methods & Reporting
Risk Factors
Serology
Severe acute respiratory syndrome coronavirus 2
Ventilation
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creator Clayton, Gemma L
Gonçalves, Ana
Soares
Goulding, Neil
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Holmes, Michael V
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Smith
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Carter, Alice R
description Mendelian randomisation (MR) studies, which investigate causal effects of exposures on disease, might be biased by sample selection and misclassification if phenotypes are not measured universally with the same definition in all study populations or participants. For example, in MR analyses of effects of exposures on covid-19, studies might include individuals with specific characteristics (eg, high socioeconomic position) meaning they are more likely to be tested for SARS-CoV-2 infection or respond to study questionnaires collecting data on infection and disease (selection bias). Alternatively, studies might assume those who were not tested have not been infected by SARS-CoV-2 or had covid-19 and are included as control participants (misclassification bias). In this article, a set of analyses to investigate the presence of selection or misclassification bias in MR studies is proposed and the implications of these on results is considered. The effect of body mass index on covid-19 susceptibility and severity is used as an illustrative example.
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subjects Bias
Body Mass Index
COVID-19
Genomes
Humans
Infections
Laboratories
Mendelian Randomization Analysis
Missing data
Phenotypes
Population studies
Questionnaires
Research Methods & Reporting
Risk Factors
Serology
Severe acute respiratory syndrome coronavirus 2
Ventilation
title A framework for assessing selection and misclassification bias in mendelian randomisation studies: an illustrative example between body mass index and covid-19
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