Principal Component Analysis Reduces Collider Bias in Polygenic Score Effect Size Estimation

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 polyg...

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Veröffentlicht in:	Behavior genetics 2022-09, Vol.52 (4-5), p.268-280
Hauptverfasser:	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.
Format:	Artikel
Sprache:	eng
Schlagworte:	Alcohol Drinking - genetics Alcohol related disorders Alcohol use Alcoholism Alcoholism - genetics Application Behavior Behavioral Science and Psychology Bias Clinical Psychology Cohort analysis Educational attainment Genetics Genome-Wide Association Study Genotype & phenotype Health Psychology Humans Liability Medicine Multifactorial Inheritance - genetics Original Research Phenotypes Principal Component Analysis Principal components analysis Psychiatry Psychology Public Health Simulation Tobacco Variables
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