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Pharmacogenomics polygenic risk score for drug response prediction using PRS-PGx methods.
Zhai, Song; Zhang, Hong; Mehrotra, Devan V; Shen, Judong.
Afiliação
  • Zhai S; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.
  • Zhang H; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA.
  • Mehrotra DV; Biostatistics and Research Decision Sciences, Merck & Co., Inc., North Wales, PA, 19454, USA.
  • Shen J; Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, 07065, USA. judong.shen@merck.com.
Nat Commun ; 13(1): 5278, 2022 09 08.
Article em En | MEDLINE | ID: mdl-36075892
Polygenic risk scores (PRS) have been successfully developed for the prediction of human diseases and complex traits in the past years. For drug response prediction in randomized clinical trials, a common practice is to apply PRS built from a disease genome-wide association study (GWAS) directly to a corresponding pharmacogenomics (PGx) setting. Here, we show that such an approach relies on stringent assumptions about the prognostic and predictive effects of the selected genetic variants. We propose a shift from disease PRS to PGx PRS approaches by simultaneously modeling both the prognostic and predictive effects and further make this shift possible by developing a series of PRS-PGx methods, including a novel Bayesian regression approach (PRS-PGx-Bayes). Simulation studies show that PRS-PGx methods generally outperform the disease PRS methods and PRS-PGx-Bayes is superior to all other PRS-PGx methods. We further apply the PRS-PGx methods to PGx GWAS data from a large cardiovascular randomized clinical trial (IMPROVE-IT) to predict treatment related LDL cholesterol reduction. The results demonstrate substantial improvement of PRS-PGx-Bayes in both prediction accuracy and the capability of capturing the treatment-specific predictive effects while compared with the disease PRS approaches.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacogenética / Estudo de Associação Genômica Ampla Tipo de estudo: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacogenética / Estudo de Associação Genômica Ampla Tipo de estudo: Clinical_trials / Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article