Genetics and major depressive disorder: clinical implications for disease risk, prognosis and treatment

Abstract

In the post-genomic era, genetics has led to limited clinical applications in the diagnosis and treatment of major depressive disorder (MDD). Variants in genes coding for cytochrome enzymes are included in guidelines for assisting in antidepressant choice and dosing, but there are no recommendations involving genes responsible for antidepressant pharmacodynamics and no consensus applications for guiding diagnosis or prognosis. However, genetics has contributed to a better understanding of MDD pathogenesis and the mechanisms of antidepressant action, also thanks to recent methodological innovations that overcome the challenges posed by the polygenic architecture of these traits. Polygenic risk scores can be used to estimate the risk of disease at the individual level, which may have clinical relevance in cases with extremely high scores (e.g. top 1%). Genetic studies have also shed light on a wide genetic overlap between MDD and other psychiatric disorders. The relationships between genes/pathways associated with MDD and known drug targets are a promising tool for drug repurposing and identification of new pharmacological targets. Increase in power thanks to larger samples and methods integrating genetic data with gene expression, the integration of common variants and rare variants, are expected to advance our knowledge and assist in personalized psychiatry.

Pharmacogenetics in Psychiatry: An Update on Clinical Usability

“…As indicated, this concerns genotyping itself (SNP analysis/arrays/NGS), structural variant detection (haplotypes/CNVs/hybrids), genotype-to-phenotype translation, cost-effectiveness, and actionability (FDA/CPIC/PharmGKB lists). Notably, this paper did not discuss pharmacodynamic gene variants, since the clinical relevance is still under investigation (Fabbri et al, 2020b). Despite the challenges described, there is an increase in uptake for clinical care, making harmonization and clinical guidelines important to bring this field further in facilitating effective and safe treatment of patients.…”

Can polygenic-informed EEG biomarkers predict differential antidepressant treatment response? An EEG stratification marker for rTMS and sertraline

“…18 Consequently, a polygenic instead of single gene or locus approach, by calculation of the individual's polygenic risk score (PRS) seems valuable to associate genetic risk with treatment (non)response. 19 However, despite recent evidence showing the power of PRS of MDD for a range of MDD-related phenotypes, 20 at present evidence for the out-of-sample value of polygenic risk approaches in the prediction of treatment outcome is limited. 18,[21][22][23][24] A proposed strategy to effectively predict therapeutic outcomes for clinically prognostic purposes, is to integrate PRS with other predictors, such as neuroimaging and clinical characteristics.…”

A polygenic-informed approach to a predictive EEG signature empowers stratified antidepressant treatment

“…Thus, antidepressant treatment outcome is likely a complex trait and explained by several loci of small effect (16), with recent evidence indeed suggesting that antidepressant response is polygenic (6). Consequently, a polygenic instead of single gene or locus approach, by calculation of the individual's polygenic risk score (PRS) seems valuable to associate genetic risk with treatment (non)response (17). However, despite recent evidence showing the power of PRS of MDD for a range of MDD-related phenotypes (18), at present evidence for the out-of-sample value of polygenic risk approaches in the prediction of treatment outcome is limited (6, [19][20][21][22].…”