Cai, Siyang and Hartley, April and Mahmoud, Osama and Tilling, Kate and Dudbridge, Frank (2022) Adjusting for collider bias in genetic association studies using instrumental variable methods. Genetic Epidemiology, 46 (5-6). pp. 303-316. DOI https://doi.org/10.1002/gepi.22455
Cai, Siyang and Hartley, April and Mahmoud, Osama and Tilling, Kate and Dudbridge, Frank (2022) Adjusting for collider bias in genetic association studies using instrumental variable methods. Genetic Epidemiology, 46 (5-6). pp. 303-316. DOI https://doi.org/10.1002/gepi.22455
Cai, Siyang and Hartley, April and Mahmoud, Osama and Tilling, Kate and Dudbridge, Frank (2022) Adjusting for collider bias in genetic association studies using instrumental variable methods. Genetic Epidemiology, 46 (5-6). pp. 303-316. DOI https://doi.org/10.1002/gepi.22455
Abstract
Genome-wide association studies have provided many genetic markers that can be used as instrumental variables to adjust for confounding in epidemiological studies. Recently the principle has been applied to other forms of bias in observational studies, especially collider bias that arises when conditioning or stratifying on a variable that is associated with the outcome of interest. An important case is in studies of disease progression and survival. Here we clarify the links between the genetic instrumental variable methods proposed for this problem and with the established methods of Mendelian randomisation developed to account for confounding. We highlight the critical importance of weak instrument bias in this context and describe a corrected weighted least squares procedure as a simple approach to reduce this bias. We illustrate the range of available methods on two data examples. The first, waist-hip ratio adjusted for body-mass index, entails statistical adjustment for a quantitative trait. The second, smoking cessation, is a stratified analysis conditional on having initiated smoking. In both cases we find little effect of collider bias on the primary association results, but this may propagate into more substantial effects on further analyses such as polygenic risk scoring and Mendelian randomisation.
Item Type: | Article |
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Uncontrolled Keywords: | Selection bias; index event bias; ascertainment bias; Mendelian randomisation |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 30 May 2022 08:36 |
Last Modified: | 30 Oct 2024 16:36 |
URI: | http://repository.essex.ac.uk/id/eprint/32743 |
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