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

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

卷:84

Review

Akil, Huda^1,2  Gordon, Joshua^1,3,4  Hen, Rene^1,3,4  Javitch, Jonathan^1,3,4  Mayberg, Helen^1,5  McEwen, Bruce^1,6  Meaney, Michael J.^1,7,8  Nestler, Eric J.^1,9 

[1] Hope Depress Res Fdn, Depress Task Force, New York, NY 10019 USA

[2] Univ Michigan, Ann Arbor, MI 48109 USA

[3] Columbia Univ, New York, NY 10027 USA

[4] New York State Psychiat Inst & Hosp, New York, NY 10032 USA

[5] Emory Univ, Atlanta, GA 30322 USA

[6] Rockefeller Univ, 1230 York Ave, New York, NY 10021 USA

[7] McGill Univ, Montreal, PQ, Canada

[8] Singapore Inst Clin Sci, Singapore, Singapore

[9] Icahn Sch Med Mt Sinai, New York, NY 10029 USA

关键词: Major depressive disorder;    Prefrontal cortex;    Hippocampus;    Amygdala;    Nucleus accumbens;    GWAS;    Gene expression;    RNA-sequencing;    ChIP-sequencing;    Epigenetics;    Neural circuits;   

DOI  :  10.1016/j.neubiorev.2017.08.019

来源: Elsevier

【 摘 要 】

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 sub-types. 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.

【 授权许可】

Free