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October 5, 2025Open Access

Prediction of Polygenic Risks by Screening Thousands of Polygenic Scores

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Method uses SNP data to enhance trait predictions in smaller studies, suggesting improvements over existing models.

SECRET methods maintained prediction power in smaller studies, enhancing polygenic trait predictions.
Using 2,100 samples, eight out of nine traits were correctly predicted using the top PGS from the SECRET method.
The algorithm showed that traditional PGS methods struggled in underpowered GWAS studies with limited sample sizes.
Systematic development of polygenic scores allows broad applicability in genomic studies with varying sample sizes.

Chen et al. (2025) studied this question.

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