Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Functional annotation of genetic variants can improve polygenic risk score (PRS) prediction.
• Bayesian shrinkage methods are effective for sparse causal variant scenarios.
• Integrating annotation information and shrinkage simultaneously in PRS methods is limited.

Conclusions:

• PRSbils effectively incorporates overlapping and non-overlapping annotations into PRS construction using a bilevel shrinkage framework.
• The proposed method enhances genetic risk prediction performance.
• The PRSbils software is publicly available for use.