Avoiding collider bias in Mendelian randomization when performing stratified analyses.
Eur J Epidemiol
; 37(7): 671-682, 2022 Jul.
Article
em En
| MEDLINE
| ID: mdl-35639294
ABSTRACT
Mendelian randomization (MR) uses genetic variants as instrumental variables to investigate the causal effect of a risk factor on an outcome. A collider is a variable influenced by two or more other variables. Naive calculation of MR estimates in strata of the population defined by a collider, such as a variable affected by the risk factor, can result in collider bias. We propose an approach that allows MR estimation in strata of the population while avoiding collider bias. This approach constructs a new variable, the residual collider, as the residual from regression of the collider on the genetic instrument, and then calculates causal estimates in strata defined by quantiles of the residual collider. Estimates stratified on the residual collider will typically have an equivalent interpretation to estimates stratified on the collider, but they are not subject to collider bias. We apply the approach in several simulation scenarios considering different characteristics of the collider variable and strengths of the instrument. We then apply the proposed approach to investigate the causal effect of smoking on bladder cancer in strata of the population defined by bodyweight. The new approach generated unbiased estimates in all the simulation settings. In the applied example, we observed a trend in the stratum-specific MR estimates at different bodyweight levels that suggested stronger effects of smoking on bladder cancer among individuals with lower bodyweight. The proposed approach can be used to perform MR studying heterogeneity among subgroups of the population while avoiding collider bias.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Temas:
Geral
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Tipos_de_cancer
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Outros_tipos
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Bexiga Urinária
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Análise da Randomização Mendeliana
Tipo de estudo:
Clinical_trials
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Eur J Epidemiol
Assunto da revista:
EPIDEMIOLOGIA
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Espanha