Pharmacogenetics of Antidepressants: from Genetic Findings to Predictive Strategies

Abstract

The constantly growing contribution of depressive disorders to the global disease statistics calls for a growth of treatment effectiveness and optimization. Antidepressants are the most frequently prescribed medicines for depressive disorders. However, development of a standardized pharmacotherapeutic approach is burdened by the genomic heterogeneity, lack of reliable predictive biomarkers and variability of the medicines metabolism aggravated by multiple side effects of antidepressants. According to modern assessments up to 20 % of the genes expressed in our brain are involved in the pathogenesis of depression. Large-scale genetic and genomic research has found a number of potentially prognostic genes. It has also been proven that the effectiveness and tolerability of antidepressants directly depend on the variable activity of the enzymes that metabolize medicines. Almost all modern antidepressants are metabolized by the cytochrome P450 family enzymes. The most promising direction of research today is the GWAS (Genome-Wide Association Study) method that is aimed to link genomic variations with phenotypical manifestations. In this type of research genomes of depressive patients with different phenotypes are compared to the genomes of the control group containing same age, sex and other parameters healthy people. Notably, regardless of the large cohorts of patients analyzed, none of the GWA studies conducted so far can reliably reproduce the results of other analogous studies. The explicit heterogeneity of the genes associated with the depression pathogenesis and their pleiotropic effects are strongly influenced by environmental factors. This may explain the difficulty of obtaining clear and reproducible results. However, despite any negative circumstances, the active multidirectional research conducted today, raises the hope of clinicians and their patients to get a whole number of schedules how to achieve remission faster and with guaranteed results

Keywords

• depression
• antidepressants
• pharmacogenetics
• personalized medicine