Pharmacogenetic‐Guided Treatment of Depression: Real‐World Clinical Applications, Challenges, and Perspectives

• Published in: Clinical pharmacology and therapeutics 2021-09, Vol.110 (3), p.573-581
• Main Authors: Zanardi, Raffaella, Manfredi, Elena, Montrasio, Cristina, Colombo, Cristina, Serretti, Alessandro, Fabbri, Chiara
• Format: Article
• Language: English
• ISSN: 0009-9236; 1532-6535
• DOI: 10.1002/cpt.2315

Depression is a leading cause of disability worldwide and, despite the availability of numerous antidepressants, the lack of standardized criteria to apply personalized prescription is still a major issue. Pharmacogenetic (PGx) markers in cytochrome P450 (CYP450) genes are already usable to guide antidepressant choice/titration according to clinical guidelines; they are an important step toward personalized psychiatry as they can reduce the time to identify an effective and tolerated treatment. Clinical application is still limited due to the financial and organizational challenges, but the number of services providing genotyping of pharmacogenes is increasing, with encouraging projections of cost‐effectiveness. Critical aspects that emerged from the available studies are the importance of integration of genotyping results in electronic medical records, standardization, and regular updates of decision support systems, training and collaboration of different professionals, need of longer follow‐ups to estimate cost‐effectiveness, and importance of avoiding inequalities in access to genotyping. Diversities exist among the groups of patients to whom genotyping is offered (pre‐emptive or reactive testing) and the type of clinical services (e.g., hospitals and primary care), currently without a consensus on which is the best approach. Future studies should aim to clarify these issues, as well as consider and compare PGx applications among different countries and healthcare systems. Finally, the extension of genotyping outside pharmacokinetic genes should be considered as a key step to improve the clinical impact of PGx, as this could significantly increase the variance explained in treatment outcomes.