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Rank concordance of polygenic indices
Dilnoza Muslimova1,2, Rita Dias Pereira3,4, Stephanie von Hinke4,5
1Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands. muslimova@ese.eur.nl.
Nature Human Behaviour
|March 14, 2023
Summary
Polygenic indices (PGIs) show unstable rankings across different construction methods for disease risk and educational attainment. Current PGIs lack the precision for routine personalized interventions.
Area of Science:
- Genetics
- Biostatistics
- Personalized Medicine
Background:
- Polygenic indices (PGIs) are emerging tools for disease risk prediction and personalized medicine.
- Their application in screening and education is gaining traction.
- However, the reliability of PGIs across different methodologies is not well-established.
Purpose of the Study:
- To empirically assess the rank concordance between PGIs constructed using various methods and discovery samples.
- To evaluate PGIs for cardiovascular disease and educational attainment.
- To understand the implications for personalized medicine and gene-environment interactions.
Main Methods:
- Spearman rank correlation analysis was used to compare PGI rankings.
- Data from the UK Biobank was utilized to illustrate potential consequences.
- Simulations were conducted to explore the drivers of rank discordance.
Main Results:
- Spearman rank correlations varied widely (0.17-0.93 for cardiovascular disease, 0.40-0.83 for educational attainment).
- Rankings were found to be unstable across different PGIs for the same trait.
- Rank discordance was linked to limited discovery sample size and PGI explained variance.
Conclusions:
- PGI-based individual ranking is highly dependent on the specific PGI chosen.
- Current PGIs do not possess the necessary precision for routine use in personalized interventions.
- Further research is needed to improve PGI stability and reliability.
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