Elsevier

Neuropharmacology

Volume 61, Issue 3, September 2011, Pages 408-413
Neuropharmacology

Invited review
Modeling treatment-resistant depression

https://doi.org/10.1016/j.neuropharm.2011.02.017Get rights and content

Abstract

Depression is a polygenic and highly complex psychiatric disorder that is currently a major burden on society. Depression is highly heterogeneous in presentation and frequently exhibits high comorbidity with other psychiatric and somatic disorders. Commonly used treatments, such as selective serotonin reuptake inhibitors (SSRIs), are not ideal since only a subset of patients achieve remission. In addition, the reason why some individuals respond to SSRIs while others don’t are unknown. Here we begin to ask what the basis of treatment resistance is, and propose new strategies to model this phenomenon in animals. We focus specifically on animal models that offer the appropriate framework to study treatment resistance with face, construct and predictive validity.

Highlights

► We compare and contrast the currently used animal models of depression. ► We examine how chronic corticosterone can model SSRI-resistant depression. ► We compare behavior tests used to determine antidepressant non-responder populations. ► We discuss the role of Serotonin 1A (5-HT1A) autoreceptors in resilience to stress. ► We discuss the role of Serotonin 1A (5-HT1A) autoreceptors in response to SSRIs.

Introduction

Understanding the neurobiological basis of a highly complex disease like depression remains one of the foremost challenges for modern psychiatry. In patients, the essential feature of a major depressive episode is defined as a persistent period of at least 2 weeks in which there is either depressed mood or the loss of interest or pleasure in nearly all activities (DSM-IV). Approximately 32–35 million adults in the US population (16%) experience an episode of major depression in their lifetime (Kessler et al., 2003). Fortunately some approved classes of drugs with antidepressant activity have been developed, including selective serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants (TCAs), selective norepinephrine reuptake inhibitors (NRIs) and monoamine oxidase inhibitors (MAOIs) (Wong et al., 2010a). Unfortunately there are two major problems with these lines of treatment. First, there is a significant delay between the start of treatment and response. Second, many patients do not respond to antidepressant treatment with these drugs. As an example, only 47% of patients respond and only 33% of patients achieve remission in the first line of treatment with a widely used SSRI (Trivedi et al., 2006). Therefore, while currently available treatments are amongst the most widely prescribed drugs, they fail to have an effect on many patients and have incomplete effects for many others. The development of the next generation of novel antidepressants is therefore subjected to considerable challenges (Wong et al., 2010b), and understanding the basis of treatment-resistant depression should offer insights into new approaches.

When prescribing medication, there is increasing pressure on clinicians to follow decision-tree medical algorithms, such as the Texas Medication Algorithm project (TMAP), in attempts to combat depression in patients that are non-responsive to initial lines of treatment. These involve multiple levels of treatments, each with varying success. Recently, STAR*D, a large study designed to mirror clinical practice, was conducted at 25 different sites. The study enrolled over 4000 patients with a broad range of symptoms and involved 4 possible steps for treatment (Fava and Covino, 2007). If patients failed to achieve remission at any level, they would be randomized for the next step of treatment. As patients moved from levels 2–4 of treatment, remission rates dropped dramatically (from approximately 35% at level 2 to16% at level 4). Therefore, failure to achieve remission with 2 consecutive treatments is associated with very low remission rates in subsequent treatments. This suggests that the usefulness of current lines of treatment is limited and underscores the need for discovery of new treatments.

Section snippets

Animal models of depressive phenotypes and treatment resistance

Given the problems with current lines of antidepressant treatment in the clinic, it is incumbent upon basic research to yield novel methods of treatment. In order for basic research to provide potential advances, a critical first step is to create useful animal models with relevant phenotypic features to reveal treatment responsiveness. However, some of the original animal models designed to address this problem suffered from a flawed tautological approach in that they were based solely on

The serotonin-1A receptor

The most commonly used drugs to treat major depression today increase serotonergic signaling either directly or indirectly. The effects of altering brain serotonin levels by SSRI treatment are potentially mediated through more that 14 identified serotonin receptors (Barnes and Sharp, 1999, Wong et al., 2008). One receptor of particular interest is the serotonin-1A receptor (5-HT1A), an inhibitory G protein coupled receptor that is expressed on serotonergic neurons in the raphe where it

Future directions for treatment

In addition to new potential targets for treatment-resistant depression that will be uncovered via basic research, recent clinical trials have sparked interest in potentially faster acting antidepressants and treatment-resistant patients. The NMDA receptor antagonist ketamine, and the anti-cholinergic scopolamine, as well as deep brain stimulation, have been shown through multiple trials in the last decade to produce a rapid antidepressant response (Berman et al., 2000, Krystal, 2007, Mayberg

Conclusions

In summary, current antidepressant treatments are not sufficient, as many patients do not respond. Future basic and clinical research will need to take new approaches to advance the understanding and discover new methods for treatment-resistant depression. Since many animal models of depression have previously focused mainly on pharmacological validity, there has been an overemphasis on mechanisms underlying currently used drugs rather than the discovery of new targets that could benefit

Acknowledgments

R.H. is a consultant to Astra Zeneca and Brain Cells Inc. R.G., A.W., J.Z. and E.W. were all fulltime employees of Astra Zeneca when this review was prepared. B.A.S. is a Charles H. Revson Senior Fellow in Life Sciences.

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