Treatment resistant depression: A multi-scale, systems biology approach

Huda Akil, Joshua Gordon, Rene Hen, Jonathan Javitch, Helen Mayberg, Bruce McEwen, Michael J. Meaney, Eric J. Nestler

Research output: Contribution to journalReview articlepeer-review

261 Scopus citations


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.

Original languageEnglish
Pages (from-to)272-288
Number of pages17
JournalNeuroscience and Biobehavioral Reviews
StatePublished - Jan 2018


  • Amygdala
  • ChIP-sequencing
  • Epigenetics
  • GWAS
  • Gene expression
  • Hippocampus
  • Major depressive disorder
  • Neural circuits
  • Nucleus accumbens
  • Prefrontal cortex
  • RNA-sequencing


Dive into the research topics of 'Treatment resistant depression: A multi-scale, systems biology approach'. Together they form a unique fingerprint.

Cite this