️ Episode 180: Leveraging Global Genetics Resources for Equitable Polygenic Prediction

In this episode of PaperCast Base by Base, we explore how multi-ancestry genome-wide association study resources and modern polygenic score methodologies can improve prediction accuracy across African, East Asian, and European populations, with a focus on practical, computationally efficient strategies that work even when individual-level data are unavailable.

Study Highlights:
This article systematically benchmarks leading single-source and multi-source polygenic score methods across 10 complex traits using GWAS summary statistics from Ugandan Genome Resource, Biobank Japan, UK Biobank, and the Million Veteran Program. The authors show that combining ancestry-aligned and European GWAS improves prediction in non-European targets and that independently optimized multi-source approaches often outperform jointly optimized methods while being far more computationally efficient. They introduce a generalizable use of the LEOPARD framework to estimate optimal linear combinations of population-specific scores using only summary statistics, achieving performance comparable to individual-level tuning in many settings. All methods are implemented in the GenoPred pipeline, providing an accessible, reference-standardized workflow for equitable polygenic prediction across diverse populations.

Conclusion:
Multi-source, summary-statistics–friendly approaches implemented in GenoPred offer a practical path to more accurate and equitable polygenic prediction, particularly when leveraging diverse GWAS resources and efficient tuning frameworks like LEOPARD.

Reference:
Pain O. Leveraging global genetics resources to enhance polygenic prediction across ancestrally diverse populations. Human Genetics and Genomics Advances. 2025;6:100482. https://doi.org/10.1016/j.xhgg.2025.100482

License:
This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/

Support:
If you'd like to support Base by Base, you can make a one-time or monthly donation here: https://basebybase.castos.com/