ArticleGenetics2025
A Bayesian approach to correcting the attenuation bias of regression using polygenic risk score.
Article in Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Incorporating additive genetic effects and linkage disequilibrium information to discover gene-environment interactions using BV-LDER-GE.Genome biology · 2025Article
- Biobanks in GENETICS and G3: tackling the statistical challenges.G3 (Bethesda, Md.) · 2025Article
- Article
- A review of methods and software for polygenic risk score analysis.PeerJ. Computer science · 2025Article
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3 authors.
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Abstract
Polygenic risk score has become increasingly popular for predicting the value of complex traits. In many settings, polygenic risk score is used as a covariate in regression analysis to study the association between different phenotypes. However, measurement error in polygenic risk score causes attenuation bias in the estimation of regression coefficients. In this paper, we employ a Bayesian approach to accounting for the measurement error of polygenic risk score and correcting the attenuation bias in linear and logistic regression. Through simulation, we show that our approach is able to obtain approximately unbiased estimation of coefficients and credible intervals with correct coverage probability. We also empirically compare our Bayesian measurement error model with the conventional regression model by analyzing real traits in the UK Biobank. The results demonstrate the effectiveness of our approach as it significantly reduces the error in coefficient estimates.
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