The Pursuit of Pleasure

Abstract

Many component processes of reward require appropriate serotonin (5HT) and dopamine (DA) neurotransmission within key limbic brain regions. Evidence suggests that dysregulation of 5HT and DA transmission can precipitate reward dysfunction and major depressive disorder (MDD) symptoms in genetically predisposed individuals. Various neurobiological indicators (biomarkers) of MDD have been proposed, including changes in signal transduction pathways, protein phosphorylation, and gene expression in subcortical, reward-related structures. However, these insights have yielded limited clinically relevant benefits for diagnosis, treatment, or prognosis. In addition, clinical application of identified biomarkers is often hindered by multiple factors including disease heterogeneity and symptom variability between patients. Innovative approaches including big data analytics, methodical collaboration between research programs, and reverse-translational strategies are now required to understand if particular biomarkers can be used to predict disease onset and treatment response, to stratify treatments for patient subgroups, and develop novel pharmacotherapies. This review briefly summarizes the predictive value of big data analytics in parsing the neurobiological underpinnings of MDD, with a focus on potential clinically-viable biomarkers for predictive therapies.