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

Gemma L Clayton; Ana   Goncalves Soares; Neil J Goulding; Maria C Borges; Michael V Holmes; George Davey Smith; Kate M Tilling; Debbie A Lawlor; Alice R Carter

doi:10.1136/bmj-2022-072148

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

Gemma L Clayton^*, Ana Goncalves Soares, Neil J Goulding, Maria C Borges, Michael V Holmes, George Davey Smith, Kate M Tilling, Debbie A Lawlor, Alice R Carter

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

15 Citations (Scopus)

Abstract

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.

Original language	English
Article number	e072148
Journal	BMJ
Volume	381
DOIs	https://doi.org/10.1136/bmj-2022-072148
Publication status	Published - 19 Jun 2023

Bibliographical note

Funding Information:
Funding: This work was supported by the Bristol British Heart Foundation (BHF) Accelerator Award (AA/18/7/34219, which supports ARC); the University of Bristol and Medical Research Council (MRC) Integrative Epidemiology Unit (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, which supports ARC, GLC, AGS, NG, GDS, DAL, KT, and MCB); the BHF-National Institute of Health Research (NIHR) COVIDITY flagship project; the European Union’s Horizon 2020 research and innovation programme (under grant agreement No 733206 LifeCycle, which supports GLC and DAL); the Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739, which supports AGS); the University of Bristol (Vice-Chancellor’s Fellowships, which supports MCB); the British Heart foundation (CH/F/20/90003, to DAL); and the NIHR (NF-0616-10102, to DAL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.

Research Groups and Themes

Bristol Population Health Science Institute

Keywords

Humans
Body Mass Index
COVID-19
Risk Factors
Bias
Mendelian Randomization Analysis

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10.1136/bmj-2022-072148Licence: CC BY

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Integrative Epidemiology Unit
Davey Smith, G. (Principal Investigator)
1/04/23 → 31/03/28
Project: Research
IEU: MRC Integrative Epidemiology Unit Quinquennial renewal
Gaunt, L. F. (Principal Investigator) & Davey Smith, G. (Principal Investigator)
1/04/18 → 31/03/23
Project: Research

Cite this

Clayton, G. L., Goncalves Soares, A., Goulding, N. J., Borges, M. C., Holmes, M. V., Davey Smith, G., Tilling, K. M., Lawlor, D. A., & Carter, A. R. (2023). A framework for assessing selection and misclassification bias in mendelian randomisation studies: an illustrative example between body mass index and covid-19. BMJ, 381, Article e072148. https://doi.org/10.1136/bmj-2022-072148

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abstract = "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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note = "Funding Information: Funding: This work was supported by the Bristol British Heart Foundation (BHF) Accelerator Award (AA/18/7/34219, which supports ARC); the University of Bristol and Medical Research Council (MRC) Integrative Epidemiology Unit (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, which supports ARC, GLC, AGS, NG, GDS, DAL, KT, and MCB); the BHF-National Institute of Health Research (NIHR) COVIDITY flagship project; the European Union{\textquoteright}s Horizon 2020 research and innovation programme (under grant agreement No 733206 LifeCycle, which supports GLC and DAL); the Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739, which supports AGS); the University of Bristol (Vice-Chancellor{\textquoteright}s Fellowships, which supports MCB); the British Heart foundation (CH/F/20/90003, to DAL); and the NIHR (NF-0616-10102, to DAL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.",

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AU - Clayton, Gemma L

AU - Goncalves Soares, Ana

AU - Goulding, Neil J

AU - Borges, Maria C

AU - Holmes, Michael V

AU - Davey Smith, George

AU - Tilling, Kate M

AU - Lawlor, Debbie A

AU - Carter, Alice R

N1 - Funding Information: Funding: This work was supported by the Bristol British Heart Foundation (BHF) Accelerator Award (AA/18/7/34219, which supports ARC); the University of Bristol and Medical Research Council (MRC) Integrative Epidemiology Unit (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, which supports ARC, GLC, AGS, NG, GDS, DAL, KT, and MCB); the BHF-National Institute of Health Research (NIHR) COVIDITY flagship project; the European Union’s Horizon 2020 research and innovation programme (under grant agreement No 733206 LifeCycle, which supports GLC and DAL); the Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases (H2020-SC1-2019-Single-Stage-RTD, project ID 874739, which supports AGS); the University of Bristol (Vice-Chancellor’s Fellowships, which supports MCB); the British Heart foundation (CH/F/20/90003, to DAL); and the NIHR (NF-0616-10102, to DAL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.

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N2 - 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.

AB - 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.

KW - Humans

KW - Body Mass Index

KW - COVID-19

KW - Risk Factors

KW - Bias

KW - Mendelian Randomization Analysis

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DO - 10.1136/bmj-2022-072148

M3 - Article (Academic Journal)

C2 - 37336561

SN - 0959-8138

VL - 381

JO - BMJ

JF - BMJ

M1 - e072148

ER -

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

Abstract

Bibliographical note

Research Groups and Themes

Keywords

Access to Document

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Projects

Integrative Epidemiology Unit

IEU: MRC Integrative Epidemiology Unit Quinquennial renewal

Cite this