The Pharmacogenomics of Selective Serotonin Reuptake Inhibitors

Abstract

Antidepressant medications are frequently used as the first line of treatment for depression. However, their effectiveness is highly variable and influenced by genetic factors. Recently, pharmacogenetic studies, including candidate-gene, genome-wide association studies or polygenic risk scores, have attempted to uncover the genetic architecture of antidepressant response. Genetic variants in at least 27 genes are linked to antidepressant treatment response in both coding and non-coding genomic regions, but evidence is largely inconclusive due to the high polygenicity of the trait and limited cohort sizes in published studies. Future studies should increase the number and diversity of participants to yield sufficient statistical power to characterize the genetic underpinnings and biological mechanisms of treatment response, improve results generalizability and reduce racial health-related inequities.

Keywords::

• antidepressants
• candidate gene studies
• depression
• genetics
• genome-wide association studies
• pharmacogenomics
• polygenic scores
• selective serotonin reuptake inhibitors
• treatment response

Financial & competing interests disclosure

LM García-Marín is supported by a UQ Research Training Scholarship from The University of Queensland (UQ). A Medina-Rivera was supported by CONACYT-FORDECYT-PRONACES (grant no. 11311), and Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica–Universidad Nacional Autónoma de México (PAPIIT-UNAM; grant no. IA203021). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

LM García-Marín is supported by a UQ Research Training Scholarship from The University of Queensland (UQ). A Medina-Rivera was supported by CONACYT-FORDECYT-PRONACES (grant no. 11311), and Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica–Universidad Nacional Autónoma de México (PAPIIT-UNAM; grant no. IA203021). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.