An Updated Polygenic Index Repository: Expanded Phenotypes, New Cohorts, and Improved Causal Inference

Area of Science:

• Genetics and Genomics
• Biomedical Informatics

Background:

• Polygenic indexes (PGIs) are crucial DNA-based predictors for individual phenotypes in various scientific fields.
• The Polygenic Index Repository (PIR) provides a valuable resource for PGI development and application.

Purpose of the Study:

• To introduce Version 2 of the PIR, enhancing its scope and methodology.
• To improve the predictive power and interpretability of PGIs.

Main Methods:

• Expanded phenotype coverage to 61 and participating datasets to 20.
• Utilized updated Genome-Wide Association Study (GWAS) meta-analysis summary statistics for 16 phenotypes.
• Introduced imputed parental PGIs and a framework for controlling them in analyses.

Main Results:

• Enhanced PGI predictive performance through improved methodologies and larger datasets.
• Demonstrated the utility of parental PGIs in family-based analyses and for exploring PGI portability.
• Provided novel resources to reduce confounding bias and improve the interpretability of PGI associations.

Conclusions:

• Version 2 of the PIR offers a significantly improved resource for PGI research.
• The updates facilitate more robust and interpretable genetic association studies.
• The repository advancements support broader applications of PGIs in biomedical and social sciences.