
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.20.608703
preprint
1
Article
Three Open Questions in Polygenic Score Portability
Wang Joyce Y. http://orcid.org/0009-0003-0179-8333

Lin Neeka
Zietz Michael http://orcid.org/0000-0003-0539-630X

Mares Jason
Narasimhan Vagheesh M. http://orcid.org/0000-0001-8651-8844

Rathouz Paul J. http://orcid.org/0000-0001-8380-4300

Harpak Arbel http://orcid.org/0000-0002-3655-748X

21 8 2024
2024.08.20.608703https://creativecommons.org/licenses/by-nd/4.0/ This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
http://biorxiv.org/lookup/doi/10.1101/2024.08.20.608703
nihpp-2024.08.20.608703.pdf
Abstract

A major obstacle hindering the broad adoption of polygenic scores (PGS) is their lack of “portability” to people that differ—in genetic ancestry or other characteristics—from the GWAS samples in which genetic effects were estimated. Here, we use the UK Biobank to measure the change in PGS prediction accuracy as a continuous function of individuals’ genome-wide genetic dissimilarity to the GWAS sample (“genetic distance”). Our results highlight three gaps in our understanding of PGS portability. First, prediction accuracy is extremely noisy at the individual level and not well predicted by genetic distance. In fact, variance in prediction accuracy is explained comparably well by socioeconomic measures. Second, trends of portability vary across traits. For several immunity-related traits, prediction accuracy drops near zero quickly even at intermediate levels of genetic distance. This quick drop may reflect GWAS associations being more ancestry-specific in immunity-related traits than in other traits. Third, we show that even qualitative trends of portability can depend on the measure of prediction accuracy used. For instance, for white blood cell count, a measure of prediction accuracy at the individual level (reduction in mean squared error) increases with genetic distance. Together, our results show that portability cannot be understood through global ancestry groupings alone. There are other, understudied factors influencing portability, such as the specifics of the evolution of the trait and its genetic architecture, social context, and the construction of the polygenic score. Addressing these gaps can aid in the development and application of PGS and inform more equitable genomic research.
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pmc
