Article
A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.
Psychiatric genetics - 1 Apr 2025
Calabrò Marco, Fabbri Chiara, Serretti Alessandro, Kasper Siegfried, Zohar Joseph, Souery Daniel, Montgomery Stuart, Albani Diego, Forloni Gianluigi, Ferentinos Panagiotis, Rujescu Dan, Mendlewicz Julien, Colombo Cristina, Zanardi Raffaella, De Ronchi Diana, Crisafulli Concetta
Abstract excerpt
BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and treatment efficacy is variable across patients. Polymorphisms in cytochrome P450 2C19 (CYP2C19) play a role in response and side effects to medications; however, they interact with other factors. We aimed to predict treatment outcome in MDD using a machine learning model combining CYP2C19 activity and nongenetic...
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