Surrogate markers of treatment outcome in major depressive disorder

Abstract

Major depressive disorder (MDD) is a common medical illness affecting millions worldwide. Despite their widespread use since the 1950s and 1960s, the 'downstream' mechanism by which antidepressants ultimately exert their therapeutic effects remains elusive. In addition, except for a few exceptions such as episode severity and the presence of comorbid Axis-I or Axis-III disorders, biological or clinical characteristics which can accurately quantify the risk of poor treatment outcome are lacking, as are factors which could help patients and clinicians select treatment options that would result in superior outcome. The identification of such markers, termed 'surrogate' markers, could help shed further insights into what constitutes illness and recovery, help identify molecular targets for the development of future antidepressants, and lead the way to the design and refinement of a personalized medicine treatment model for MDD. In the following text, several major areas ('leads') where evidence exists regarding the presence of surrogate markers of efficacy outcome in MDD will be briefly reviewed. Leads include evidence from the role of demographic and clinical factors as surrogate markers, to the role of various biological markers including genotype, brain functional imaging, electroencephalography, dichotic listening, and molecular biology and immunology. The purpose of this work is to focus selectively on areas where there have been findings, as opposed to conducting an exhaustive literature review of studies which have failed to yield any significant breakthrough in our knowledge.

Prediction of SSRI treatment response in major depression based on serotonin transporter interplay between median raphe nucleus and projection areas

“…The results of this study strongly indicate a pivotal role of the balance between baseline SERT binding in the MRN and baseline SERT binding in key areas within the depression circuits to serve as a strong predictor of treatment response (for a distinction between predictors, moderators and mediators, see Papakostas et al (Papakostas, 2011)). Among those key areas, the habenulae, the sgACC and the OFC, and the amygdala-hippocampus complex have been consistently linked to major depression and antidepressant treatment response (Mayberg, 2009;Sartorius et al, 2010).…”

“…The mechanism of selective serotonin reuptake inhibitors' (SSRIs) antidepressant effects and research approaches to develop predictors for treatment response are matters of vivid debate (Holsboer, 2008;Papakostas, 2011). SSRIs are defined by their selective blockage of the serotonin transporter (SERT) and a substantial body of research has been conducted to investigate the SERT in unmedicated patients and under the influence of SSRIs (Cannon et al, 2007;Catafau et al, 2006;Cavanagh et al, 2006;Herold et al, 2006;Meyer et al, 2001Meyer et al, , 2004Miller et al, 2008).…”

A Review of Antidepressant Therapy in Primary Care

“…Other advances have come from the field of molecular psychiatry, wherein a combination of biomarkers reflecting monoamine neurotransmitters, neurotrophic factors, and inflammatory markers is able to distinguish patients with MDD from healthy controls 82. Although it is unlikely that any one of these putative biomarkers will identify unique subpopulations or predict treatment response, integrated biomarkers involving neuroimaging, proteomic, and genomic data, as well as clinical profiles, may help to individualize treatment strategies 83…”

Biomarkers Predicting Antidepressant Treatment Response: How Can We Advance the Field?

“…The purpose of this work will be to selectively focus on areas where there have been promising findings, as opposed to conducting an exhaustive literature review of studies which have failed to yield any significant breakthrough in our knowledge. There are excellent reviews providing a detailed summary on what has been published during the last years in the field of depression biomarkers [4, 5]. Finally, we will present an outlook on future approaches and discuss and submit an optimized translational strategy to improve the biomarker discovery process in depression research.…”