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- W4376609971 abstract "Abstract Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGS BMI ) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R 2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R 2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGS BMI -covariate interaction effects, modifying PGS BMI effects by nearly 20% per standard deviation change. We observed overlap with covariates that had significant R 2 differences between strata and interaction effects – across all covariates, their main effects on BMI were correlated with maximum R 2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGS-score individuals have highest R 2 and PGS effect increases. Given significant and replicable evidence for context-specific PGS BMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R 2 (mean 23%) across datasets. Finally, creating PGS BMI directly from GxAge GWAS effects increased relative R 2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGS BMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects." @default.
- W4376609971 created "2023-05-17" @default.
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- W4376609971 date "2023-05-14" @default.
- W4376609971 modified "2023-10-01" @default.
- W4376609971 title "Risk factors affecting polygenic score performance across diverse cohorts" @default.
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- W4376609971 doi "https://doi.org/10.1101/2023.05.10.23289777" @default.
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