Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-specific effects via GAUDI

Sun, Q.; Rowland, B. T.; Chen, J.; Mikhaylova, A. V.; Avery, C.; Peters, U.; Lundin, J.; Matise, T.; Buyske, S.; Tao, R.; Mathias, R. A.; Reiner, A. P.; Auer, P. L.; Cox, N. J.; Kooperberg, C.; Thornton, T.; Raffield, L. M.; Li, Y.

doi:10.1101/2022.10.06.511219

bioRxiv · 10.1101/2022.10.06.511219

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-specific effects via GAUDI

Sun, Q.·Rowland, B. T.·Chen, J.·Mikhaylova, A. V.·Avery, C.·Peters, U.·Lundin, J.·Matise, T.·Buyske, S.·Tao, R.·Mathias, R. A.·Reiner, A. P.·Auer, P. L.·Cox, N. J.·Kooperberg, C.·Thornton, T.·Raffield, L. M.·Li, Y.

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Abstract

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods have focused only on individuals with one primary continental ancestry, thus poorly accommodating recently-admixed individuals. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals by explicitly modeling ancestry-specific effects and jointly estimating ancestry-shared effects. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses.

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Sun, Q., Rowland, B. T., Chen, J., Mikhaylova, A. V., Avery, C., Peters, U., Lundin, J., Matise, T., Buyske, S., Tao, R., Mathias, R. A., Reiner, A. P., Auer, P. L., Cox, N. J., Kooperberg, C., Thornton, T., Raffield, L. M., Li, Y.. 2022-10-08. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-specific effects via GAUDI. https://doi.org/10.1101/2022.10.06.511219

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