Cognitive and emotional biomarkers of melancholic depression: An iSPOT-D report

Interval Timing as a Computational Pathway From Early Life Adversity to Affective Disorders

Adverse early life experiences can have remarkably enduring negative consequences on mental health, with numerous, varied psychiatric conditions sharing this developmental origin. Yet, the mechanisms linking adverse experiences to these conditions remain poorly understood. Here, we draw on a principled model of interval timing to propose that statistically optimal adaptation of temporal representations to an unpredictable early life environment can produce key characteristics of anhedonia, a transdiagnostic symptom associated with affective disorders like depression and anxiety. The core observation is that early temporal unpredictability produces broader, more imprecise temporal expectations. As a result, reward anticipation is diminished, and associative learning is slowed. When agents with such representations are later introduced to more stable environments, they demonstrate a negativity bias, responding more to the omission of reward than its receipt. Increased encoding of negative events has been proposed to contribute to disorders with anhedonia as a symptom. We then examined how unpredictability interacts with another form of adversity, low reward availability. We found that unpredictability's effect was most strongly felt in richer environments, potentially leading to categorically different phenotypic expressions. In sum, our formalization suggests a single mechanism can help to link early life adversity to a range of behaviors associated with anhedonia, and offers novel insights into the interactive impacts of multiple adversities.

Uncovering the Neural Correlates of Anhedonia Subtypes in Major Depressive Disorder: Implications for Intervention Strategies

Major depressive disorder (MDD) represents a serious public health concern, negatively affecting individuals' quality of life and making a substantial contribution to the global burden of disease. Anhedonia is a core symptom of MDD and is associated with poor treatment outcomes. Variability in anhedonia components within MDD has been observed, suggesting heterogeneity in psychopathology across subgroups. However, little is known about anhedonia subgroups in MDD and their underlying neural correlates across subgroups. To address this question, we employed a hierarchical cluster analysis based on Temporal Experience of Pleasure Scale subscales in 60 first-episode, drug-naive MDD patients and 32 healthy controls. Then we conducted a connectome-wide association study and whole-brain voxel-wise functional analyses for identified subgroups. There were three main findings: (1) three subgroups with different anhedonia profiles were identified using a data mining approach; (2) several parts of the reward network (especially pallidum and dorsal striatum) were associated with anticipatory and consummatory pleasure; (3) different patterns of within- and between-network connectivity contributed to the disparities of anhedonia profiles across three MDD subgroups. Here, we show that anhedonia in MDD is not uniform and can be categorized into distinct subgroups, and our research contributes to the understanding of neural underpinnings, offering potential treatment directions. This work emphasizes the need for tailored approaches in the complex landscape of MDD. The identification of homogeneous, stable, and neurobiologically valid MDD subtypes could significantly enhance our comprehension and management of this multifaceted condition.

Abnormal dynamic functional connectivity of hippocampal subregions associated with working memory impairment in melancholic depression

BACKGROUND

Previous studies have demonstrated structural and functional changes of the hippocampus in patients with major depressive disorder (MDD). However, no studies have analyzed the dynamic functional connectivity (dFC) of hippocampal subregions in melancholic MDD. We aimed to reveal the patterns for dFC variability in hippocampus subregions - including the bilateral rostral and caudal areas and its associations with cognitive impairment in melancholic MDD.

METHODS

Forty-two treatment-naive MDD patients with melancholic features and 55 demographically matched healthy controls were included. The sliding-window analysis was used to evaluate whole-brain dFC for each hippocampal subregions seed. We assessed between-group differences in the dFC variability values of each hippocampal subregion in the whole brain and cognitive performance on the MATRICS Consensus Cognitive Battery (MCCB). Finally, association analysis was conducted to investigate their relationships.

RESULTS

Patients with melancholic MDD showed decreased dFC variability between the left rostral hippocampus and left anterior lobe of cerebellum compared with healthy controls (voxel p < 0.005, cluster p < 0.0125, GRF corrected), and poorer cognitive scores in working memory, verbal learning, visual learning, and social cognition (all p < 0.05). Association analysis showed that working memory was positively correlated with the dFC variability values of the left rostral hippocampus-left anterior lobe of the cerebellum (r = 0.338, p = 0.029) in melancholic MDD.

CONCLUSIONS

These findings confirmed the distinct dynamic functional pathway of hippocampal subregions in patients with melancholic MDD, and suggested that the dysfunction of hippocampus-cerebellum connectivity may be underlying the neural substrate of working memory impairment in melancholic MDD.

Apathy in melancholic depression and abnormal neural activity within the reward-related circuit

Major depressive disorder is a heterogeneous syndrome, of which the most common subtype is melancholic depression (MEL). Previous studies have indicated that anhedonia is frequently a cardinal feature in MEL. As a common syndrome of motivational deficit, anhedonia is closely associated with dysfunction in reward-related networks. However, little is currently known about apathy, another syndrome of motivational deficits, and the underlying neural mechanisms in MEL and non-melancholic depression (NMEL). Herein, the Apathy Evaluation Scale (AES) was used to compare apathy between MEL and NMEL. On the basis of resting-state functional magnetic resonance imaging, functional connectivity strength (FCS) and seed-based functional connectivity (FC) were calculated within reward-related networks and compared among 43 patients with MEL, 30 patients with NMEL, and 35 healthy controls. Patients with MEL had higher AES scores than those with NMEL (t = -2.20, P = 0.03). Relative to NMEL, MEL was associated with greater FCS (t = 4.27, P < 0.001) in the left ventral striatum (VS), and greater FC of the VS with the ventral medial prefrontal cortex (t = 5.03, P < 0.001) and dorsolateral prefrontal cortex (t = 3.18, P = 0.005). Taken together the results indicate that reward-related networks may play diverse pathophysiological roles in MEL and NMEL, thus providing potential directions for future interventions in the treatment of various depression subtypes.

Functional MRI study of feedback-based reinforcement learning in depression

Reinforcement learning depends upon the integrity of emotional circuitry to establish associations between environmental cues, decisions, and positive or negative outcomes in order to guide behavior through experience. The emotional dysregulation characteristic of major depressive disorder (MDD) may alter activity in frontal and limbic structures that are key to learning. Although reward and decision-making have been examined in MDD, the effects of depression on associative learning is less well studied. We investigated whether depressive symptoms would be related to abnormalities in learning-related brain activity as measured by functional magnetic resonance imaging (fMRI). Also, we explored whether melancholic and atypical features were associated with altered brain activity. We conducted MRI scans on a 4T Varian MRI system in 10 individuals with MDD and 10 healthy subjects. We examined event-related brain activation during feedback-based learning task using Analysis of Functional NeuroImages (AFNI) for image processing and statistical analysis. We observed that MDD patients exhibited reduced activation in visual cortex but increased activation in cingulate and insular regions compared to healthy participants. Also, in relation to features of depressive subtypes, we observed that levels of activation in striatal, thalamic, and precuneus regions were negatively correlated with atypical characteristics. These results suggest that the effects of MDD change the neural circuitry underlying associative learning, and these effects may depend upon subtype features of MDD.

Neurocognitive function of patients with melancholic and non-melancholic major depressive episodes: An exploratory study

OBJECTIVE

The aim of this exploratory study was to compare the neurocognitive performance of patients undergoing melancholic and non-melancholic major depressive episodes. Considering potential limitations of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) specifier, we employed an additional tool that has proven useful in identifying melancholia (the Sydney Melancholia Prototype Index).

METHODS

One hundred forty-one depressed inpatients were classified as melancholic or non-melancholic according to the Sydney Melancholia Prototype Index and the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) criteria and compared on a neurocognitive battery selected to assess attention and processing speed, verbal memory, working memory and executive functions. Results were controlled for several potential confounders.

RESULTS

Patients diagnosed as melancholic by the two diagnostic systems displayed lower scores in executive measures, semantic verbal fluency and phonological verbal fluency. On attention and processing speed, patients with melancholia underperformed those with non-melancholic depression only when diagnosed by the Sydney Melancholia Prototype Index. After controlling for confounders, associations between melancholic status and executive dysfunction remained significant for the Sydney Melancholia Prototype Index but not for the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) diagnosis.

CONCLUSION

In this study, melancholia diagnosed by the Sydney Melancholia Prototype Index (but not by the Diagnostic and Statistical Manual of Mental Disorders [5th ed.] criteria) was characterized by a greater compromise of tests assessing executive functions than non-melancholic depressions, even after controlling for depressive severity. These preliminary results might contribute to generating hypotheses about differences in the cognitive profile and pathophysiological substrate between melancholic and non-melancholic depressions. Likewise, the pattern of findings supports the hypothesis that the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) melancholia specifier might identify more severe forms of depressive episodes rather than a qualitatively different subtype.

Effect of NEUROG3 polymorphism rs144643855 on regional spontaneous brain activity in major depressive disorder

PURPOSE

Our previous study identified a significant association between a single nucleotide polymorphism (SNP) located in the neurogenin3 (NEUROG3) gene and post-stroke depression (PSD) in Chinese populations. The present work explores whether polymorphism rs144643855 affects regional brain activity and clinical phenotypes in major depressive disorder (MDD).

METHOD

A total of 182 participants were included: 116 MDD patients and 66 normal controls. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning at baseline. Spontaneous brain activity was assessed using amplitude of low-frequency fluctuation (ALFF). The Hamilton Depression Scale-24 (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess participants at baseline. Two-way analysis of covariance (ANCOVA) was used to explore the interaction between diagnostic groups and NEUROG3 rs144643855 on regional brain activity. We performed correlation analysis to further test the association between these interactive brain regions and clinical manifestations of MDD.

RESULTS

Genotype and disease significantly interacted in the left inferior frontal gyrus (IFG-L), right superior frontal gyrus (SFG-R), and left paracentral lobule (PCL-L) (P < 0.05). ALFF values of the IFG-L were found to be significantly associated with anhedonia in MDD patients.

CONCLUSION

These findings suggest a potential relationship between rs144643855 variations and altered frontal brain activity in MDD. NEUROG3 may play an important role in the neuropathophysiology of MDD.

Modeling Heterogeneous Brain Dynamics of Depression and Melancholia Using Energy Landscape Analysis

Our current understanding of melancholic depression is shaped by its position in the depression spectrum. The lack of consensus on how it should be treated-whether as a subtype of depression, or as a distinct disorder altogethe-interferes with the recovery of suffering patients. In this study, we analyzed brain state energy landscape models of melancholic depression, in contrast to healthy and non-melancholic energy landscapes. Our analyses showed significant group differences on basin energy, basin frequency, and transition dynamics in several functional brain networks such as basal ganglia, dorsal default mode, and left executive control networks. Furthermore, we found evidences suggesting the connection between energy landscape characteristics (basin characteristics) and depressive symptom scores (BDI-II and SHAPS). These results indicate that melancholic depression is distinguishable from its non-melancholic counterpart, not only in terms of depression severity, but also in brain dynamics.

Prediction of Antidepressant Treatment Outcome Using Event-Related Potential in Patients with Major Depressive Disorder

(1) Background: Prediction of treatment outcome has been one of the core objectives in clinical research of patients with major depressive disorder (MDD). This study explored the possibility of event-related potential (ERP) markers to predict antidepressant treatment outcomes among MDD patients; (2) Methods: Fifty-two patients with MDD were recruited and evaluated through Hamilton depression (HAM-D), Hamilton anxiety rating scale (HAM-A), and CORE. Patients underwent a battery of ERP measures including frontal alpha symmetry (FAA) in the low alpha band (8–10 Hz), mismatch negativity (MMN), and loudness-dependent auditory evoked potentials (LDAEP); (3) Results: During the eight weeks of study, 61% of patients achieved remission, and 77% showed successful treatment responsiveness. Patients with low FAA in F5/F6 demonstrated a significantly higher remission/response ratio and better treatment responsiveness (F (2.560, 117.755) = 3.84, p = 0.016) compared to patients with high FAA. In addition, greater FAA in F7/F8 EEG channels was significantly associated with greater melancholia scores (r = 0.34, p = 0.018). Other ERP markers lacked any significant effect; (4) Conclusions: Our results suggested low FAA (i.e., greater left frontal activity) could reflect a good treatment response in MDD patients. These findings support that FAA could be a promising index in understanding both MDD and melancholic subtype.

The biological face of melancholia: Are there any reliable biomarkers for this depression subtype?

BACKGROUND

Melancholic depression (MD) is a subtype of Major Depression associated with more clinical severity and poorer prognosis that non-melancholic depression (NMD). The differentiation between depression subtypes is still clinical, although the identification of specific biomarkers could be useful for diagnosis and the development of new treatments. Purpose of the present manuscript is to review the biomarkers that have been associated with MD.

METHODS

We performed a bibliographic research on the main databases (PubMed, Embase, PsycInfo, Isi Web of Knowledge, Medscape, The Cochrane Library), in order to find studies that proposed biological markers for melancholic depression. A total of 14 studies met our inclusion criteria.

RESULTS

Most of studies focused on immune dysregulation. Subjects with MD show biological abnormalities than healthy controls (HC). MD might be characterized by specific biological changes and it could be associated to more severe abnormalities with respect to NMD; however especially about this latter point the available data are preliminary.

LIMITATIONS

Most available data have not been replicated; the studies focused on different biomarkers. In addition, many articles report results on a limited sample size.

CONCLUSIONS

Melancholic depression is a subtype of major depression that seems to be associated with specific alterations of different biological systems. Future studies with larger sample can confirm the results and hypothesis presented in this review.

Connectivity of the Cognitive Control Network During Response Inhibition as a Predictive and Response Biomarker in Major Depression: Evidence From a Randomized Clinical Trial

BACKGROUND

In treating major depressive disorder, we lack tests anchored in neurobiology that predict antidepressant efficacy. Cognitive impairments are a particularly disabling feature of major depressive disorder. We tested whether functional connectivity during a response-inhibition task can predict response to antidepressants and whether its changes over time are correlated to symptom changes.

METHODS

We analyzed data from outpatients with major depressive disorder (n = 124) randomized to receive escitalopram, sertraline, or venlafaxine (8 weeks) and healthy control subjects (n = 59; age 18-65 years). Before and after treatment, participants were interviewed and scanned using functional magnetic resonance imaging, and functional connectivity was measured using generalized psychophysiological interaction during response inhibition (Go-NoGo task). We investigated the interaction between treatment type and response (≥50% reduction on self-reported symptoms), coupling differences between responders and nonresponders at baseline, their correlation with symptom improvement, and their changes in time.

RESULTS

During response inhibition, connectivity between the dorsolateral prefrontal cortex/supramarginal gyrus and supramarginal gyrus/middle temporal gyrus was associated with response to sertraline and venlafaxine, but not escitalopram. Sertraline responders had higher functional connectivity between these regions compared with nonresponders, whereas venlafaxine responders had lower functional connectivity. For sertraline, attenuation of connectivity in the precentral and superior temporal gyri correlated with posttreatment symptom improvement. For venlafaxine, enhancement of connectivity between the orbitofrontal cortex and subcortical regions correlated with symptom improvement.

CONCLUSIONS

Connectivity of the cognitive control circuit during response inhibition selectively and differentially predicts antidepressant treatment response and correlates with symptom improvement. These quantitative markers tied to the neurobiology of cognitive features of depression could be used translationally to predict and evaluate treatment response.

Empirical evidence for discrete neurocognitive subgroups in patients with non-psychotic major depressive disorder: clinical implications

BACKGROUND

Neuropsychological deficits are present across various cognitive domains in major depressive disorder (MDD). However, a consistent and specific profile of neuropsychological abnormalities has not yet been established.

METHODS

We assessed cognition in 170 patients with non-psychotic MDD using the Brief Assessment of Cognition in Schizophrenia and the scores were compared with those of 42 patients with schizophrenia as a reference for severity of cognitive impairment. Hierarchical cluster analysis was conducted to determine whether there are discrete neurocognitive subgroups in MDD. We then compared the subgroups in terms of several clinical factors and social functioning.

RESULTS

Three distinct neurocognitive subgroups were found: (1) a mild impairment subgroup with near-normative performance and mild dysfunction in motor speed; (2) a selective impairment subgroup, which exhibited preserved working memory and executive function, but moderate to severe deficits in verbal memory, motor speed, verbal fluency, and attention/information processing speed; and (3) a global impairment subgroup with moderate to severe deficits across all neurocognitive domains, comparable with deficits in schizophrenia. The global impairment subgroup was characterized by lower pre-morbid intelligence quotient (IQ). Moreover, a significant difference between groups was observed in premorbid IQ (p = 0.003), antidepressant dose (p = 0.043), antipsychotic dose (p = 0.013), or anxiolytic dose (p < 0.001).

CONCLUSIONS

These results suggest the presence of multiple neurocognitive subgroups in non-psychotic MDD with unique profiles, one of which exhibits deficits comparable to those of schizophrenia. The results of the present study may help guide future efforts to target these disabling symptoms using different treatments.

Opioid modulation of cognitive impairment in depression

The failure of traditional antidepressant medications to adequately target cognitive impairment is associated with poor treatment response, increased risk of relapse, and greater lifetime disability. Opioid receptor antagonists are currently under development as novel therapeutics for major depressive disorder (MDD) and other stress-related illnesses. Although it is known that dysregulation of the endogenous opioid system is observed in patients diagnosed with MDD, the impact of opioidergic neurotransmission on cognitive impairment has not been systematically evaluated. Here we review the literature indicating that opioid manipulations can alter cognitive functions in humans. Furthermore, we detail the preclinical studies that demonstrate the ability of mu-opioid receptor and kappa-opioid receptor ligands to modulate several cognitive processes. Specifically, this review focuses on domains within higher order cognitive processing, including attention and executive functioning, which can differentiate cognitive processes influenced by motivational state.

Transdiagnostic Symptom Clusters and Associations With Brain, Behavior, and Daily Function in Mood, Anxiety, and Trauma Disorders

IMPORTANCE

The symptoms that define mood, anxiety, and trauma disorders are highly overlapping across disorders and heterogeneous within disorders. It is unknown whether coherent subtypes exist that span multiple diagnoses and are expressed functionally (in underlying cognition and brain function) and clinically (in daily function). The identification of cohesive subtypes would help disentangle the symptom overlap in our current diagnoses and serve as a tool for tailoring treatment choices.

OBJECTIVE

To propose and demonstrate 1 approach for identifying subtypes within a transdiagnostic sample.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study analyzed data from the Brain Research and Integrative Neuroscience Network Foundation Database that had been collected at the University of Sydney and University of Adelaide between 2006 and 2010 and replicated at Stanford University between 2013 and 2017. The study included 420 individuals with a primary diagnosis of major depressive disorder (n = 100), panic disorder (n = 53), posttraumatic stress disorder (n = 47), or no disorder (healthy control participants) (n = 220). Data were analyzed between October 2016 and October 2017.

MAIN OUTCOMES AND MEASURES

We followed a data-driven approach to achieve the primary study outcome of identifying transdiagnostic subtypes. First, machine learning with a hierarchical clustering algorithm was implemented to classify participants based on self-reported negative mood, anxiety, and stress symptoms. Second, the robustness and generalizability of the subtypes were tested in an independent sample. Third, we assessed whether symptom subtypes were expressed at behavioral and physiological levels of functioning. Fourth, we evaluated the clinically meaningful differences in functional capacity of the subtypes. Findings were interpreted relative to a complementary diagnostic frame of reference.

RESULTS

Four hundred twenty participants with a mean (SD) age of 39.8 (14.1) years were included in the final analysis; 256 (61.0%) were female. We identified 6 distinct subtypes characterized by tension (n=81; 19%), anxious arousal (n=55; 13%), general anxiety (n=38; 9%), anhedonia (n=29; 7%), melancholia (n=37; 9%), and normative mood (n=180; 43%), and these subtypes were replicated in an independent sample. Subtypes were expressed through differences in cognitive control (F5,383 = 5.13, P < .001, ηp2 = 0.063), working memory (F5,401 = 3.29, P = .006, ηp2 = 0.039), electroencephalography-recorded β power in a resting paradigm (F5,357 = 3.84, P = .002, ηp2 = 0.051), electroencephalography-recorded β power in an emotional paradigm (F5,365 = 3.56, P = .004, ηp2 = 0.047), social functional capacity (F5,414 = 21.33, P < .001, ηp2 = 0.205), and emotional resilience (F5,376 = 15.10, P < .001, ηp2 = 0.171).

CONCLUSIONS AND RELEVANCE

These findings offer a data-driven framework for identifying robust subtypes that signify specific, coherent, meaningful associations between symptoms, behavior, brain function, and observable real-world function, and that cut across DSM-IV-defined diagnoses of major depressive disorder, panic disorder, and posttraumatic stress disorder.

Latent variable analysis of positive and negative valence processing focused on symptom and behavioral units of analysis in mood and anxiety disorders

BACKGROUND

Mood and anxiety disorders are highly heterogeneous and their underlying pathology is complex. The Research Domain Criteria (RDoC) approach seeks to establish dimensionally and neuroscience-based descriptions of psychopathology that may inform better classification and treatment approaches. The current investigation sought to determine the latent variables underlying positive and negative valence processing in terms of symptoms and behavioral units of analysis.

METHOD

As part of an ongoing study, individuals with mood and anxiety problems were recruited largely from primary care clinics at UCLA (n=62) and UCSD (n=58). These participants underwent a comprehensive symptomatic and behavioral assessment. An implicit approach avoidance task and a modified dot probe detection task were used to measure positive and negative valence processing.

RESULTS

Principal components analysis with varimax rotation identified four symptom components, three behavioral components for the dot probe task, and two behavioral components for the implicit approach avoidance task. These components yielded two meta-components consisting of: negative valence symptoms, negative approach bias, and high sustained, selective attention; and positive valence symptoms, positive approach bias, and slow selective or sustained attention. The components did not differ between males and females, nor by age or medication status.

LIMITATIONS

The limitations are: (1) relatively small sample, (2) exploratory analysis strategy, (3) no test/re-test data, (4) no neural circuit analysis, and (5) limited reliability of behavioral data.

CONCLUSIONS

These preliminary data show that positive and negative valence processing domains load on independent dimensions. Taken together, multi-level assessment approaches combined with advanced statistical analyses may help to identify distinct positive and negative valence processes within a clinical population that cut across traditional diagnostic categories.

Neuropsychological changes in melancholic and atypical depression: A systematic review

There is not a consensus as to whether neuropsychological profiling can distinguish depressive subtypes. We aimed to systematically review and critically analyse the literature on cognitive function in patients with melancholic and atypical depression. We searched in databases PubMed, SCOPUS, Web of Knowledge and PsycInfo for papers comparing the neuropsychological performance of melancholic patients (MEL) to non-melancholic depressive patients (NMEL), including atypical depressives, and healthy controls (HC). All studies were scrutinised to determine the main methodological characteristics and particularly possible sources of bias influencing the results reported, using the STROBE statement checklist. We also provide effect size of the results reported for contrasts between MEL; patients and NMEL patients. Seventeen studies were included; most of them demonstrated higher neuropsychological impairments of MEL patients compared to both NMEL patients and HC on tasks requiring memory, executive function, attention and reaction time. Detailed analysis of the methodologies used in the studies revealed significant variability especially regarding the participants' sociodemographic characteristics, clinical characteristics of patients and differences in neuropsychological assessment. These findings suggest that MEL may have a distinct and impaired cognitive performance compared to NMEL depressive patients on tasks involving verbal and visual memory, executive function, sustained attention and span, as well as psychomotor speed, this last especially when cognitive load is increased. Additional studies with adequate control of potentially confounding variables will help to clarify further differences in the neuropsychological functioning of depressive subtypes.

The properties and utility of the CORE measure of melancholia

BACKGROUND

The CORE measure was designed to assess a central feature of melancholia - signs of psychomotor disturbance (PMD) - and so provide an alternate non-symptom based measure of melancholia or of its probability. This review evaluates development and application studies undertaken over the last 25 years to consider how well it has met its original objectives.

METHODS

All studies published using the CORE measure as either the only or an adjunctive measure of melancholia were obtained and are considered in this review.

RESULTS

Findings suggest high reliability in quantifying CORE scores can be achieved and that it has construct validity as a measure of PMD. A number of application studies assessing socio-demographic factors, cognitive and motor impairment, dexamethasone suppression and thyrotropin-releasing hormone, response to psychotherapy and to electroconvulsive therapy support its validity as a measure of melancholia, while functional brain imaging studies suggest that the measure identifies regions of decreased connectivity.

LIMITATIONS

Use of the CORE benefits from rater training and for subjects to be assessed at or near nadir of their depressive episode. There have been insufficient studies evaluating genetic factors, and the treatment response of CORE-defined melancholic patients to antidepressant drugs of differing classes.

CONCLUSIONS

The CORE, either as a proxy or direct measure of melancholia, provides a strategy for assigning depressed subjects a diagnosis or melancholic or non-melancholic depression or for estimating the probability of melancholia.

A meta-analysis of cognitive performance in melancholic versus non-melancholic unipolar depression

BACKGROUND

Recently there is increasing recognition of cognitive dysfunction as a core feature of Major Depressive Disorder (MDD). The goal of the current meta-analysis was to review and examine in detail the specific features of cognitive dysfunction in Melancholic (MEL) versus Non-Melancholic (NMEL) MDD.

METHODS

An electronic literature search was performed to find studies comparing cognitive performance in MEL versus NMEL. A meta-analysis of broad cognitive domains (processing speed, reasoning/problem solving, verbal learning, visual learning, attention/working memory) was conducted on all included studies (n=9). Sensitivity and meta-regression analyses were also conducted to detect possible effects of moderator variables (age, gender, education, symptom severity and presence of treatments).

RESULTS

MEL patients were older and more severly depressed than NMEL subjects. The MEL group was characterized by a worse cognitive performance in attention/working memory (ES=-0.31), visual learning (ES=-0.35) and reasoning/problem solving (ES=-0.46). No difference was detected in drug-free patients by sensitivity analyses. No effect was found for any of our moderators on the cognitive performance in MEL vs NMEL.

CONCLUSION

Our findings seem to support a moderate but specific effect of melancholic features in affecting the cognitive performance of MDD, in particular as regards visual learning and executive functions.

Anticipatory reward deficits in melancholia

Dysfunctional reward processing has long been considered an important feature of major depressive disorder (MDD). However, depression is a heterogeneous construct and the nature of this heterogeneity may contribute to some of the inconsistent empirical findings on reward dysfunction in MDD. The current study examined 1 source of heterogeneity, melancholic symptoms, and its association with reward processing. In individuals with MDD (N = 141) and MDD-free controls (N = 113), electroencephalogram (EEG) alpha asymmetry was measured during a behavioral reward task that probed reward anticipation. Melancholic depression was measured both categorically (Diagnostic and Statistical Manual of Mental Disorders [DSM] diagnosis) and dimensionally (Hamilton Endogenomorphy Scale [HES]). Results showed that a dimensional (and not categorical) definition of melancholia predicted reward processing, with higher melancholic symptoms predicting reduced reward anticipation. Importantly, the effects of melancholic symptoms on reduced reward anticipation remained above and beyond overall depression severity. These results suggest that dysfunctional reward processing may only be associated with melancholic symptoms, not depression in general. (PsycINFO Database Record

Cognitive Dysfunction in Major Depressive Disorder. A Translational Review in Animal Models of the Disease

Major Depressive Disorder (MDD) is the most common psychiatric disease, affecting millions of people worldwide. In addition to the well-defined depressive symptoms, patients suffering from MDD consistently complain about cognitive disturbances, significantly exacerbating the burden of this illness. Among cognitive symptoms, impairments in attention, working memory, learning and memory or executive functions are often reported. However, available data about the heterogeneity of MDD patients and magnitude of cognitive symptoms through the different phases of MDD remain difficult to summarize. Thus, the first part of this review briefly overviewed clinical studies, focusing on the cognitive dysfunctions depending on the MDD type. As animal models are essential translational tools for underpinning the mechanisms of cognitive deficits in MDD, the second part of this review synthetized preclinical studies observing cognitive deficits in different rodent models of anxiety/depression. For each cognitive domain, we determined whether deficits could be shared across models. Particularly, we established whether specific stress-related procedures or unspecific criteria (such as species, sex or age) could segregate common cognitive alteration across models. Finally, the role of adult hippocampal neurogenesis in rodents in cognitive dysfunctions during MDD state was also discussed.

Theory of mind in major depressive disorder: A meta-analysis

OBJECTIVE

Social cognitive deficits can contribute to risk for depression and to psychosocial impairment during depression. However, available evidence suggests that emotion recognition is only marginally impaired in major depressive disorder (MDD). Recent studies have investigated theory of mind (ToM) abilities, a cognitively more demanding aspect of social cognition.

METHODS

We conducted a meta-analysis of studies comparing ToM abilities in MDD and healthy controls. 18 studies comparing 613 patients with MDD and 529 healthy controls were included.

RESULTS

MDD patients significantly underperformed healthy controls in ToM (d=0.51-0.58). ToM impairment in MDD was evident in response to different types of ToM tasks (verbal/visual and cognitive/affective and reasoning/decoding). ToM impairment was significantly related to severity of depressive symptoms.

CONCLUSION

Theory of mind abilities are impaired during depression and can potentially contribute to psychosocial difficulties during depression. There is a need to investigate ToM abilities in different subtypes and stages of depression, especially in remitted patients.