Principal Component Analysis Reduces Collider Bias in Polygenic Score Effect Size Estimation.
- Authors
- Thomas, Nathaniel S; Barr, Peter; Aliev, Fazil; Stephenson, Mallory; Kuo, Sally I-Chun; Chan, Grace; Dick, Danielle M; Edenberg, Howard J; Hesselbrock, Victor; Kamarajan, Chella; Kuperman, Samuel; Salvatore, Jessica E
- Year
- 2022
- Journal
- Behavior genetics
- PMID
- 35674916
- DOI
- 10.1007/s10519-022-10104-z
- PMCID
- PMC10103419
In this study, we test principal component analysis (PCA) of measured confounders as a method to reduce collider bias in polygenic association models. We present results from simulations and application of the method in the Collaborative Study of the Genetics of Alcoholism (COGA) sample with a polygenic score for alcohol problems, DSM-5 alcohol use disorder as the target phenotype, and two collider variables: tobacco use and educational attainment. Simulation results suggest that assumptions regarding the correlation structure and availability of measured confounders are complementary, such that meeting one assumption relaxes the other. Application of the method in COGA shows that PC covariates reduce collider bias when tobacco use is used as the collider variable. Application of this method may improve PRS effect size estimation in some cases by reducing the effect of collider bias, making efficient use of data resources that are available in many studies.
Diagram of the simulation modelThe effect of PRS on the heritable covariate is varied between 0.0 to 0.5 at intervals of 0.1. The effect of PRS on the target phenotype is set to 0.1. The effect of the first PC of all confounders on the heritable covariate and the target phenotype is set to 0.5. The effect of the heritable covariate on the target phenotype is also set to 0.5.
Simulation results for rGE = 0.1 and rGE = 0.5 with confounder correlations ranging between 0.05 and 0.1PRS = polygenic risk score; Env = heritable covariate; PCs = principal components; rGE = gene-environment correlationThe magnitude of collider bias is larger when rGE is higher. The PRS beta estimate that is corrected by the incomplete PC approaches the true value of 0.1 as the proportion of confounders included in the PC increases.
Simulation results for rGE = 0.1 and rGE = 0.5 with confounder correlations ranging between 0.8 and 0.9.PRS = polygenic risk score; Env = heritable covariate; PCs = principal components; rGE = gene-environment correlationThe magnitude of collider bias is larger when rGE is higher. The PRS beta estimate that is corrected by the incomplete PC approaches the true value of 0.1 as the proportion of confounders included in the PC increases. Relative to Figure 2 where confounder correlations are lower, the corrected beta is closer to the true value of 0.1 with a lower proportion of the confounding data.
Change in Alcohol Problems PRS Beta across models with TOB/EDU environment.PRS = polygenic risk score; TOB = tobacco use; EDU = educational attainment; PCs = principal componentsThe PRS beta is lower when TOB is included in the model. The beta increases when phenotypic PCs are added to the model. The PRS beta does not decrease substantially in the presence of EDU.
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|---|---|---|---|---|
| Alcohol use polygenic risk score, social support, and alcohol use among European American and African American adults. | Su J et al. | — | 2023 | → |
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