Evidencing functional improvement in depression






Philippe FOSSATI,MD, PhD
GH Pitié Salpétrière
Service de Psychiatrie d’Adultes
ICM, AP-HP, IHU-A-ICM
Université Pierre & Marie Curie
Paris-VI, FRANCE

Evidencing functional improvement in depression


by P. Fossati, France



In this article we review functional and structural brain imaging studies in major depression, the brain effects of antidepressants, and their relationship with psychosocial functioning. Major depression is characterized by altered dynamics in neural networks involved in emotion and cognitive functions. Among these networks, the default mode network (DMN) has been extensively studied in major depressive disorder (MDD). The DMN is a network comprising anterior and posterior medial regions of the brain involved in self and other-processing, autobiographical memory, and allocation of attentional resources to the internal and external world. Several studies have showed that the anterior part of the DMN—the dorsomedial prefrontal cortex—and the posterior part of the DMN—the precuneus—are respectively associated with rumination and autobiographical memory impairment in MDD. Both rumination and autobiographical memory problems may contribute to functional impairment in depression and increase the duration of a depressive episode. By normalizing the cooperation between networks, antidepressants contribute to restoring the homeostatic balance between emotional and cognitive processes in depressed patients, thereby promoting functional recovery.

Medicographia. 2014;36:470-475 (see French abstract on page 475)



Major depressive disorder (MDD) is a leading cause of functional disability that represents a tremendous burden for patients, families, and health care systems. Sobocki et al estimated the total annual cost of depression in Europe at €118 billion.1 Direct costs alone totaled €42 billion, and indirect costs due to morbidity and mortality were estimated at €76 billion. Overall, this makes major depression one of the most costly brain disorders in Europe.2 Several factors may contribute to functional impairment in depressed patients, including symptom severity, acute and persistent cognitive-emotional problems, and medical comorbidities. Moreover, MDD is associated with a high rate of recurrence, and almost 30% of depressed patients develop treatment-resistant depression.

Based on its chronic and episodic course, MDD may be conceptualized as a neurodevelopmental disorder impacting the function and structure of multiple neural networks. In this short review we will discuss the structural and functional brain changes observed in MDD, the brain effects of antidepressant treatment, and the putative relationships between these brain changes and psychosocial functioning.



Figure 1. fMRI studies showing impaired activation in depressed patients compared with healthy controls during self-referential processing.

Activation was found in regions distributed in the ventral and dorsal parts of the medial prefrontal cortex.
After reference 8: Nejad et al. Front Hum Neurosci. 2013;7:666.© 2013 Nejad, Fossati and Lemogne.


Functional brain changes in major depressive disorder

Functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies of cerebral blood flow and glucose metabolism in major depression have consistently revealed that depression is a system-level disorder affecting discrete—but functionally integrated—cortical, subcortical, and limbic networks. Resting-state studies of depressed patients have identified alterations in the ventral and dorsal medial and lateral prefrontal cortex, ventral and dorsal anterior cingulate, posterior cingulate, parietal cortex, basal ganglia, insula, amygdala, and hippocampus prior to treatment.3,4

In a resting-state fMRI study of depressed patients the dorsomedial prefrontal cortex (DMPFC) was found to exhibit increased connectivity to seed regions representative of the cognitive (parietal and lateral prefrontal cortices), default mode (medial prefrontal and parietal cortices), and affective networks (amygdala), suggesting altered neural network dynamics in major depression.5

The dorsomedial prefrontal region and other regions involved in MDD are constitutive elements of the default mode network (DMN). The DMN is a network comprising ventral and dorsal medial prefrontal regions, the hippocampus, and the medial parietal (precuneus) and posterior cingulate regions. Although its specific function is not clearly defined, the DMN is involved in self- and other-processing, autobiographical memory, and allocation of attentional resources to the internal and external world. The DMPFC—the anterior part of the DMN—is activated during self-referential processing tasks, where subjects have to relate neutral or emotional stimuli to themselves.6 In keeping with the hypothesis of abnormal self-processing in MDD, impaired activation (usually increased activation) of the DMPFC has been described in depressed patients (Figure 1).7,8





Rumination, a process characterized by increased and repetitive self-focus on negative content, is a clinical hallmark of impaired self-processing in MDD. There is evidence that rumination is associated with increased connectivity in the DMN, both in healthy subjects and indepressed patients.8-21 In a study involving treatment-naïve patients with first-episode depression, Zhu et al observed increased connectivity of the DMN in patients compared with controls, and found that the activity of the anterior part of the DMN (ie, DMPFC) was positively correlated to rumination scores.20 There is a large body of observational and experimental evidence suggesting a reciprocally reinforcing relationship between rumination and negative affect.22 Moreover, levels of rumination have been associated with the severity of depressive episodes in depressed patients.23 Moreover, increased levels of rumination have been found to increase social withdrawal, dampen executive resources, and contribute to psychosocial functioning impairment in MDD.23

The precuneus—the posterior medial part of the parietal cortex— is also a core element of the DMN. At rest, the precuneus is highly connected with other regions of the DMN, but it is also connected with the lateral prefrontal cortex (cognitive network) when subjects are engaged in cognitive tasks. Thus, the precuneus is a hub that regulates cognition, emotion, and behavior.24

Several studies have shown that the precuneus is involved in the physiopathology of depression. In the study with treatment- naïve patients with first-episode depression discussed above,20 the posterior part of the DMN (ie, the precuneus) was hypo-connected in depressed patients and was correlated with overgeneralization (OGM) during autobiographical memory retrieval. OGM emphasizes the difficulty of depressed patients to retrieve specific (ie, spatio-temporal, factual, and emotional details) personal memories in response to retrieval cues. We demonstrated elsewhere that patients with acute depression show impaired autobiographical memory.25 Nixon et al described hyperconnectivity in the DMN and hypogyrification of the precuneus in remitted depressed patients.26 Although Nixon et al26 did not assess autobiographical memory performance, their results may confirm the findings of Bergouignan et al,27 which showed impaired autobiographical memory retrieval in remitted depressed patients. Likewise, the abnormal structure and function of the precuneus in depression may be related to Freton et al’s28 findings in healthy volunteers, which showed that the gray matter volume of the precuneus is positively correlated with the ability of subjects to retrieve specific autobiographical events with a field perspective. Overall, in relation with other regions (especially the hippocampus; see below), the precuneus may subserve some aspects of autobiographical memory impairment in major depression. Autobiographical memory retrieval is a self-related process that contributes to the regulation of emotion. Impairment of such a process in acute and remitted major depression decreases the ability of depressed patients to adapt to the emotional and cognitive demands of their environment.


Figure 2
Figure 2. Structural changes in the posterior part of the hippocampus
in depressed patient.

After reference 37: Bergouignan et al. Neuroimage. 2009;45:29-37. © 2008,
Elsevier Inc.



Greicius et al found increased resting-state functional connectivity of the precuneus and the thalamus compared with the rest of the DMN in depressed patients, and this increase was correlated with the duration of the depressive episode.29 Although Greicius et al29 did not assess self-related processes such as rumination and autobiographical memory retrieval in their population of depressed patients, several studies have highlighted the role of rumination and OGM in increasing the duration and risk of recurrence of depression.30,31

Beyond impaired self-processing, neuropsychological studies have consistently reported that depression interferes with effortful processing and that cognitive impairment may mediate psychosocial impairment in depressed patients.32 In healthy subjects, fMRI experiments indicate that increasing cognitive demand engages a pattern of brain activation that is characterized by a balance between increasing activity in cortical cognitive areas and decreasing activity in the DMN network.33 Patients with depression fail to modulate the activity of the medial prefrontal regions and the DMN in response to cognitive demand, suggesting that abnormal DMN and cognitive network interactions subserve performance decrements in effortful cognitive tasks in depression.34

Structural brain changes in major depressive disorder

Functional changes in major depressive disorder are associated with structural changes in areas involved in cognition and emotion processing, including the prefrontal cortex, orbito- frontal cortex, and subcortical regions.35 The hippocampus is a major region where structural changes occur in MDD. There is now a lot of evidence showing that MDD is marked by a reduction in hippocampal volume.36 Several factors contribute to this reduction in hippocampal volume: genetics, life-stress exposure (ie, physical or sexual abuse), the number of depressive episodes, inflammation, and hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis.

The volume of the hippocampus is usually reduced by 8% to 20%, with more pronounced changes in the posterior part of the hippocampus (head and tail; Figure 2).37 The exact molecular and cellular mechanisms involved in hippocampal damage and their histopathological signatures in depression are not clearly understood. Chronic stress exposure, glutamatergic toxicity, reduction in the density of glial cells and dendritic arborization, impairment in neurogenesis-related processes have all been proposed to contribute to impaired neuroplasticity in MDD.38 Studies in animal models combining MRI imaging and histopathological assessment are clearly needed to throw light upon the respective contributions of these mechanisms to hippocampal atrophy in MDD.

What are the functional consequences of structural hippocampal changes in depression? Longitudinal studies have shown that a reduction in hippocampal volume is associated with the persistence of depressive symptoms after 3 years of follow up and that it is a predictor of poor clinical outcome.39,40 On the other hand, patients with residual symptoms showed a higher decrease in hippocampal volume during clinical follow up.41

Young et al found that the autobiographical memory problems experienced by depressed patients was related to abnormal functional activation of the hippocampus.42 Likewise, episodic and working memory deficits have been found to be associated with hippocampal volume reduction in MDD.43

The links between structural and functional brain changes in depression have not been extensively investigated. One study showed that hyperconnectivity in the DMN was associated with hypo-gyrification of the precuneus in remitted depressed patients with recurrent depression.26 Such studies on the relationships between structural and functional changes are essential to understand the chronic and episodic course of MDD more precisely and to disentangle the contribution of acute and chronic brain factors involved in psychosocial impairment in depressed patients.


Figure 3
Figure 3. Functional changes induced by antidepressant
on neural activity related to the processing
of emotional stimuli.

In blue, increased activation; in red: decreased activation.


Brain effects of antidepressant treatment

Does antidepressant treatment correct the brain activity pattern identified in major depression and restore normal dynamic interactions in neural networks? To answer this question, we used a meta-analytical approach to examine the patterns associated with clinical improvement in depression in emotional activation studies using fMRI.44 Nine emotional activation fMRI studies involving a total of 126 patients were included in the meta-analysis using the activation likelihood estimation technique. Following treatment with antidepressant drugs, the activation of several brain regions involved in response to emotional stimuli in major depression was normalized. In addition, decreased activation in the anterior (BA 32) and posterior cingulate cortices, as well as in the precuneus, was found to reflect restored deactivation of the DMN (Figure 3).

Several studies have assessed the differences between treatment responders and nonresponders to identify the specific brain changes necessary to obtain a clinical response. Mayberg and colleagues examined the time course of the regional metabolic changes associated with fluoxetine treatment in depressed inpatients.45 The patients were divided into responders (reduction ≥50% on the Hamilton Depression Rating Scale [HAM-D]) and nonresponders after 6 weeks of treatment. Clinical response was associated with limbic-paralimbic and striatal metabolic decreases and brainstem and prefrontal, dorsal anterior cingulate, posterior cingulate, and parietal metabolic increases. The identical pattern of the brain changes seen in depressed patients responding to placebo46 or cognitive-behavioral therapy47 suggests a final common pathway for clinical response in depression.

However, the presence of unique specific changes in the brainstem and hippocampus in fluoxetine-treated patients, which were not observed with other treatments, supports the hypothesis that both treatment-specific and response- specific effects can be identified.45

Brain imaging at baseline can be used to predict short-term and long-term clinical outcomes and functional recovery. Several studies have found that pretreatment metabolic activity in the rostral (pregenual) cingulate uniquely distinguishes medication responders from nonresponders.48 It is now generally accepted that clinical remission—defined as a HAM-D score of 7 or less1—is the primary goal for the treatment of depression. Using remission as the end point of their study, McGrath et al found that anterior insula activity predicted clinical remission to antidepressant treatment or cognitive-behavior therapy.49 In a recent study in depressed outpatients treated with agomelatine, we were able to demonstrate that reduced activation of the DMPFC and precuneus at baseline during self-referential processing was a good predictor of clinical remission at 6 months.50

Conclusion
Antidepressant treatments exert their therapeutic effect through modulation of the reactivity of the limbic, DMN, and cortical networks to cognitive and emotional stimuli as well as during the resting state. This is in agreement with the concept of major depression as a brain disorder of multiple connected neural networks and with the effects of conventional or atypical antidepressant treatments such as ketamine on these connected networks in healthy subjects.51,52 The mechanism of action of antidepressant treatment likely contributes to restoring the homeostatic balance between emotional and cognitive processes in depressed patients, thereby promoting functional recovery.


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Keywords: cognitive function; depression; functional magnetic resonance imaging; functional recovery; neural networks