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

Chiara Fabbri, Stuart Montgomery, Cathryn M. Lewis, Alessandro Serretti

2020International Clinical Psychopharmacology34 citationsDOIOpen Access PDF

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.

Topics & Concepts

Major depressive disorderAntidepressantDrug repositioningPharmacogenomicsGenetic architecturePrecision medicineDiseaseBipolar disorderPsychiatryGenome-wide association studyMedicineBioinformaticsGeneComputational biologyGeneticsBiologyDrugPhenotypeInternal medicineSingle-nucleotide polymorphismCognitionAnxietyGenotypeGenetic Associations and EpidemiologyGenetics and Neurodevelopmental DisordersBioinformatics and Genomic Networks