Treatment resistant depression: A multi-scale, systems biology approach. (January 2018)

• Record Type: Journal Article
• Authors: Akil, Huda; Gordon, Joshua; Hen, Rene; Javitch, Jonathan; Mayberg, Helen; McEwen, Bruce; Meaney, Michael J.; Nestler, Eric J.
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 84(2018)
• Page Start: 272
• Page End: 288
• Publication Date: 2018-01
• Subjects: Major depressive disorder -- Prefrontal cortex -- Hippocampus -- Amygdala -- Nucleus accumbens -- GWAS -- Gene expression -- RNA-sequencing -- ChIP-sequencing -- Epigenetics -- Neural circuits; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2017.08.019
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: Treatment resistant depression (TRD) is a major public health concern. Yet little is known about how TRD differs from treatment-responsive depression. A multi-scale, systems biology approach is needed to better understand & treat TRD. This involves a coordinated study of depressed humans and improved animal models. And integrated use of genetic, epigenetic, cellular, and circuit analyses. The goal is a precision medicine approach to depression including TRD. Abstract: An estimated 50% of depressed patients are inadequately treated by available interventions. Even with an eventual recovery, many patients require a trial and error approach, as there are no reliable guidelines to match patients to optimal treatments and many patients develop treatment resistance over time. This situation derives from the heterogeneity of depression and the lack of biomarkers for stratification by distinct depression subtypes. There is thus a dire need for novel therapies. To address these known challenges, we propose a multi-scale framework for fundamental research on depression, aimed at identifying the brain circuits that are dysfunctional in several animal models of depression as well the changes in gene expression that are associated with these models. When combined with human genetic and imaging studies, our preclinical studies are starting to identify candidate circuits and molecules that are altered both in models of disease and in patient populations. Targeting these circuits and mechanisms can lead to novel generations of antidepressants tailored to specific patient populations with distinctive types of molecular and circuit dysfunction.