Clinically actionable pharmacogenomic landscape of antidepressants and antipsychotics in Qatar: A population-based cohort study

Author:

Velayutham Dinesh,Bastaki Kholoud,Ghuloum Suhaila,Azeem Muhammad Waqar,Pirmohamed Munir,Jithesh Puthen VeettilORCID,

Abstract

AbstractAntidepressants and antipsychotics, commonly prescribed worldwide, exhibit significant variability in patient responses. Genetic variations contribute substantially to this variability, offering the potential for predicting individual responses through pharmacogenetic testing. Clinical guidelines provided by organizations like the Clinical Pharmacogenetic Implementation Consortium (CPIC) and the Dutch Pharmacogenetic Working Group (DPWG) facilitate the application of pharmacogenomics in clinical settings. Understanding the prevalence of actionable genetic variants and their associated response phenotypes is vital for effective pharmacogenomic integration, especially in under-served populations.In this study, we analyzed the frequency distribution of actionable genetic variants in 6045 adult Qataris recruited by the Qatar Biobank, whose genomes were sequenced as part of the Qatar Genome Program, focusing on genes (CYP2C19, CYP2D6, CYP2B6, and CYP3A4) influencing psychotropic medication responses. Haplotypes and diplotypes were generated from 490 alleles, and metabolizer phenotypes were predicted based on established guidelines.Our findings revealed that over 52% of Qatari individuals may possess actionable metabolizer phenotypes associated with CYP2C19, CYP2B6, and CYP2D6, impacting their response to tricyclic antidepressants. The frequency of actionable genetic variants for serotonin reuptake inhibitors ranged from approximately 2% to 51%, and for antipsychotics, it ranged from 0.1% to 32%, based on genetic variations in CYP3A4 and CYP2D6.This study underscores the importance of assessing these genetic variants, particularly concerning commonly prescribed antidepressants like escitalopram and amitriptyline in Qatar. Implementing pharmacogenetic testing based on these findings can potentially enhance patient outcomes in psychiatric medication management.

Publisher

Cold Spring Harbor Laboratory

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