Neuroimaging biomarkers as predictors of treatment outcome in Major Depressive Disorder

doi:10.1016/j.jad.2017.10.049

Journal of Affective Disorders

Volume 233, June 2018, Pages 21-35

https://doi.org/10.1016/j.jad.2017.10.049 Get rights and content

Highlights

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Neuroimaging response predictors for antidepressant therapies are proposed.
•
Frontolimbic structural and functional indices may have predictive potential.
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Frontolimbic regions are also involved in depression etiology.
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Inconsistency of findings may result from variation across depression ‘biotypes’.
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Data replication, validation, and integration are required for clinical translation.

Abstract

Background

Current practice for selecting pharmacological and non-pharmacological antidepressant treatments has yielded low response and remission rates in Major Depressive Disorder (MDD). Neuroimaging biomarkers of brain structure and function may be useful in guiding treatment selection by predicting response vs. non-response outcomes.

Methods

In this review, we summarize data from studies examining predictors of treatment response using structural and functional neuroimaging modalities, as they pertain to pharmacotherapy, psychotherapy, and stimulation treatment strategies. A literature search was conducted in OVID Medline, EMBASE, and PsycINFO databases with coverage from January 1990 to January 2017.

Results

Several imaging biomarkers of therapeutic response in MDD emerged: frontolimbic regions, including the prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, and insula were regions of interest. Since these sub-regions are implicated in the etiology of MDD, their association with response outcomes may be the result of treatments having a normalizing effect on structural or activation abnormalities.

Limitations

The direction of findings is inconsistent in studies examining these biomarkers, and variation across ‘biotypes’ within MDD may account for this. Limitations in sample size and differences in methodology likely also contribute.

Conclusions

The identification of accurate, reliable neuroimaging biomarkers of treatment response holds promise toward improving treatment outcomes and reducing burden of illness for patients with MDD. However, before these biomarkers can be translated into clinical practice, they will need to be replicated and validated in large, independent samples, and integrated with data from other biological systems.

Introduction

Current practice in selecting both pharmacological and non-pharmacological antidepressant treatments is influenced by evidence-based medicine and guideline-informed care. Nevertheless, response and remission rates in Major Depressive Disorder (MDD) remain low, even when best practice guidelines are applied. Considering that a treatment trial for MDD can require as long as 8–12 weeks, this consequently prolongs the functional burden associated with MDD, with negative consequences on occupation, social relationships, and physical health, among others (Lam et al., 2016).

There is growing interest in the development of precision medicine algorithms with the aim of tailoring treatment strategies to individual patients according to unique biological signatures. This biomarker-based approach to precision prescribing has the potential to improve therapeutic response, minimize adverse reactions, and reduce time to symptomatic relief. However, few validated biological targets for treatment response prediction in MDD have been identified to date. The National Institute of Mental Health (NIMH)’s Research Domain Criteria (RDoC) emphasize biomarker discovery as a clinical research priority by articulating an approach to the integration of biological and clinical data (Kozak and Cuthbert, 2016). For the purpose of this review, the term ‘predictor’ is generally used to describe baseline imaging markers that influence treatment outcome; where baseline markers differentially predict response to one treatment compared to another, the term ‘moderator’ is preferred.

Biomarkers derived from neuroimaging data are potentially important contributors to the goal of guiding treatment selection using clinical and biotyping data. Information on brain structure and function may be used to predict response vs. non-response to various treatments. Current studies, however, predominantly compare pre-treatment data between responders and non-responders retrospectively. Before such findings can be translated into psychiatric practice, prospective predictive accuracy of putative biomarkers needs to be established and replicated.

In this review, we summarize data from studies examining predictors of treatment response obtained from structural (magnetic resonance imaging [MRI], and diffusion tensor imaging [DTI]), and functional (functional MRI [fMRI], positron emission tomography [PET], single-photon emission computed tomography [SPECT], near-infrared spectroscopy [NIRS], and proton magnetic resonance spectroscopy [H¹MRS]) modalities, as they pertain to pharmacotherapy, psychotherapy, and stimulation treatment strategies.

Section snippets

Methodology

A literature search was conducted in OVID Medline, EMBASE, and PsycINFO databases with coverage from January 1990 to January 2017. Search terms included (‘major depression’ OR ‘depression’ OR ‘mood disorder’ OR ‘major depressive disorder’) AND (‘neuroimaging’ OR ‘magnetic resonance imaging (MRI)’ OR ‘fMRI’ OR ‘fMRI-BOLD’ OR ‘diffusion MRI’ OR ‘structural MRI’ OR ‘positron emission tomography (PET)’ OR ‘FDG-PET’ OR ‘diffusion tensor imaging (DTI)’ OR ‘computerized tomography’ OR ‘near-infrared

Predictors of pharmacotherapy outcomes

Structural imaging studies have identified neuroanatomical markers for pharmacotherapy treatment response by characterizing the size, shape, as well as gray and white matter patterns of whole brain and specific regions (see Table 1). Volumetric data suggest that pre-treatment brain volumes may have predictive potential in determining pharmacotherapy response outcomes, particularly where smaller brain volumes predict poor response, and comparatively larger volumes are associated with response

Predictors of psychotherapy outcomes

The majority of imaging studies focused on psychotherapy have addressed response biomarkers for cognitive behavioural therapy (CBT) using functional imaging (see Table 2). The four most consistently identified regions are the ACC, PFC, amygdala/temporal lobe, and insula as predictive regions for response, although the direction of findings is inconsistent. In the only identified resting-state study, greater functional connectivity of the amygdala to the left DLPFC and left anterior insula was

Predictors of stimulation therapy outcomes

Stimulation therapies – electroconvulsive therapy (ECT), deep brain stimulation, (DBS), repetitive transcranial magnetic stimulation (rTMS), and vagus nerve stimulation (VNS) – have attracted considerable attention in terms of imaging predictors of response or non-response (see Table 3).

ECT has been the main therapy investigated within structural imaging studies, with the amygdala/temporal lobe region as a biomarker of interest. Large baseline amygdala volume predicts a reduction in depressive

Predictors of combined treatment outcomes

Several imaging investigations have used combined MDD therapies or compared therapies within a single protocol (see Table 4). In general, increased brain volumes are associated with antidepressant response, while proxies of brain atrophy, such as white matter lesions and enlarged CSF spaces, are associated with poor outcomes. In a study combining pharmacotherapy and ECT to treat LLD, subcortical hyperintensities in the frontal lobes, basal ganglia, and pons predicted poor response (Simpson et

Integrating imaging modalities for the prediction of response outcomes

The studies discussed so far have independently used structural and functional imaging modalities to identify biomarkers of treatment response. This section will focus on studies that have examined the cross-talk between indices of neuroanatomy and functional activity. Most integrated analyses address prediction of response to pharmacotherapy, and have implicated the hippocampus.

One study using both resting-state functional activation and structural imaging identified increased hippocampal

Conclusions and future directions

Structural and functional imaging studies have identified several neural biomarkers of antidepressant treatment response, some of which are consistent across treatments (see Table 5A, Table 5B, Table 5C). Frontolimbic regions, particularly the PFC, ACC, hippocampus, amygdala, and insula, most frequently influence therapeutic outcome, although the directions of association may vary for different treatments.

Each of these regions is important in the etiology of MDD, suggesting that their

Acknowledgements

None.

Role of funding source

This research was conducted as part of the Canadian Biomarker Integration Network in Depression (CAN-BIND) program. CAN-BIND is an Integrated Discovery Program carried out in partnership with, and financial support from, the Ontario Brain Institute, an independent non-profit corporation, funded partially by the Ontario Government. The opinions, results and conclusions are those of the authors and no endorsement by the Ontario Brain Institute is intended or should be inferred.

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Review articleNeuroimaging biomarkers as predictors of treatment outcome in Major Depressive Disorder

Highlights

Abstract

Background

Methods

Results

Limitations

Conclusions

Introduction

Section snippets

Methodology

Predictors of pharmacotherapy outcomes

Predictors of psychotherapy outcomes

Predictors of stimulation therapy outcomes

Predictors of combined treatment outcomes

Integrating imaging modalities for the prediction of response outcomes

Conclusions and future directions

Acknowledgements

Role of funding source

J. Affect. Disord.

J. Affect. Disord.

Psychiatry Res.

Brain Stimul.

Biol. Psychiatry

Brain Stimul.

Brain Stimul.

Psychiatry Res.

Prog. Neuro-Psychopharmacol. Biol. Psychiatry

Psychiatry Res.

Neurobiol. Dis.

Biol. Psychiatry

J. Physiol.

Psychiatry Res.

Brain Stimul.

Biol. Psychiatry

J. Affect. Disord.

J. Psychiatr. Res.

Prog. Neuro-Psychopharmacol. Biol. Psychiatry

Biol. Psychiatry

J. Psychiatr. Res.

Psychiatry Res.

J. Affect. Disord.

Asian J. Psychiatry

J. Affect. Disord.

J. Psychiatr. Res.

J. Affect. Disord.

Brain Stimul.

Biol. Psychiatry

NeuroImage

J. Affect. Disord.

Biol. Psychiatry

J. Psychiatr. Res.

Biol. Psychiatry

Biol. Psychiatry

Biol. Psychiatry

Psychiatry Res.

Psychiatry Res.

NeuroImage

Psychiatry Res.

J. Affect. Disord.

NeuroImage

J. Psychiatr. Res.

J. Affect. Disord.

J. Affect. Disord.

Psychiatry Res.

Hippocampal structural and functional changes associated with electroconvulsive therapy response

Transl. Psychiatry

Change over time in brain serotonin transporter binding in major depression: effects of therapy measured with [(123)I]-ADAM SPECT

J. Neuroimaging: Off. J. Am. Soc. Neuroimaging

HF-rTMS treatment in medication-resistant melancholic depression: results from 18FDG-PET brain imaging

CNS Spectr.

Treatment response in late-onset depression: relationship to neuropsychological, neuroradiological and vascular risk factors

Psychol. Med.

Review article
Neuroimaging biomarkers as predictors of treatment outcome in Major Depressive Disorder