Unpacking Major Depressive Disorder: From Classification to Treatment Selection

Convolutional Neural Network for Depression and Schizophrenia Detection

Background/Objectives: This study presents a Convolutional Neural Network (CNN) approach for detecting depression and schizophrenia using motor activity patterns represented as images. Participants' motor activity data were captured and transformed into visual representations, enabling advanced computer vision techniques for the classification of these mental disorders. The model's performance was evaluated using a three-fold cross-validation, achieving an average accuracy of 95%, demonstrating the effectiveness of the proposed approach in accurately identifying mental health conditions. The objective of the study is to develop a model capable of identifying different mental disorders by processing motor data using CNN in order to provide a support tool to areas specialized in the diagnosis and efficient treatment of these psychological conditions. Methods: The methodology involved segmenting and transforming motor activity data into images, followed by a CNN training and testing phase on these visual representations. This innovative approach enables the identification of subtle motor behavior patterns, potentially indicative of specific mental states, without invasive interventions or self-reporting. Results: The results suggest that CNNs can capture discriminative features in motor activity to differentiate between individuals with depression, schizophrenia, and those without mental health diagnoses. Conclusions: These findings underscore the potential of computer vision and deep neural network techniques to contribute to early, non-invasive mental health disorder diagnosis, with significant implications for developing mental health support tools.

Methods for maintaining the effects of electroconvulsive therapy in depression treatment in various parts of the world

Introduction: Electroconvulsive therapy (ECT) is one of the most effective treatments in psychiatry. The aim of this study is to present innovative methods for preventing the recurrence of depression after ECT treatment using continuation ECT (c-ECT), maintenance ECT (m-ECT), and pharmacotherapy, as well as to compare different approaches to the use of these methods across different parts of the world. Materials and methods: A review of the available literature was performed by searching the PubMed and Google Scholar databases using the following keywords: “c-ECT”, “m-ECT”, “continuation electroconvulsive therapy”/”kontynuacja terapii elektrowstrząsowej”, “maintenance electroconvulsive therapy”/”podtrzymująca terapia elektrowstrząsowa”, “major depressive disorder”/”duże zaburzenia depresyjne”, “continuation pharmacotherapy”/”kontynuacja farmakoterapii” for original papers, meta-analyses, and review papers both in Polish and English, published from 1999 to 2023. The SANRA scale was used to maintain the quality of the narrative review. Results: In maintenance treatment, c-ECT and m-ECT achieve effects comparable to those of pharmacological treatment. The most effective method is a combination of pharmacological therapy and c-ECT. c-ECT and m-ECT can reduce the time and cost, and the number of hospitalisations. At the same time, one of the major trends in ECT practice over the past 20 years has been the shift from inpatient to outpatient treatment. Conclusions: c-ECT and m-ECT are underutilised and understudied despite positive clinical experience spanning over 70 years. Although they are used all over the world, there are no specific guidelines or standardised methods for conducting this therapy. Studies that are currently underway should provide recommendations regarding the selection, frequency, and duration of c-ECT and m-ECT.

Tissue-specific gene expression of genome-wide significant loci associated with major depressive disorder subtypes

Major depressive disorder (MDD) is a clinically and genetically heterogeneous disorder. To reduce heterogeneity, large-scale genome-wide association studies have recently identified genome-wide significant loci associated with seven MDD subtypes. However, it was unclear in which tissues the genes near those loci are specifically expressed. We investigated whether genes related to specific MDD subtypes would be preferably expressed in a specific tissue. At 14 novel subtype-specific loci related to seven MDD subtypes-(1) non-atypical-like features MDD, (2) early-onset MDD, (3) recurrent MDD, (4) MDD with suicidal thoughts, (5) MDD without suicidal thoughts, (6) MDD with moderate impairment, and (7) postpartum depression, we investigated whether 22 genome-wide significant genetic variant-mapped genes were tissue-specifically expressed in brain, female reproductive, male specific, cardiovascular, gastrointestinal, or urinary tissues in the Genotype-Tissue Expression (GTEx) subjects (n ≤ 948). To confirm the tissue-specific expression in the GTEx, we used independent Human Protein Atlas (HPA) RNA-seq subjects (n ≤ 95). Of 22 genes, nine and five genes were tissue-specifically expressed in brain and female reproductive tissues, respectively (p < 2.27 × 10-3). RTN1, ERBB4, and AMIGO1 related to early-onset MDD, recurrent MDD, or MDD with suicidal thoughts were highly expressed in brain tissues (d = 1.19-2.71), while OAS1, LRRC9, DHRS7, PSMA5, SYPL2, and GULP1 related to non-atypical-like features MDD, early-onset MDD, MDD with suicidal thoughts, or postpartum depression were expressed at low levels in brain tissues (d = -0.17--1.48). DFNA5, CTBP2, PCNX4, SDCCAG8, and GULP1, which are related to early-onset MDD, MDD with moderate impairment, or postpartum depression, were highly expressed in female reproductive tissues (d = 0.80-2.08). Brain and female reproductive tissue-specific expression was confirmed in the HPA RNA-seq subjects. Our findings suggest that brain and female reproductive tissue-specific expression might contribute to the pathogenesis of MDD subtypes.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Antidepressant effects of repeated s-ketamine administration as NMDAR Antagonist: Involvement of CaMKIIα and mTOR signaling in the hippocampus of CUMS mice

With the approval of s-ketamine nasal spray as a novel antidepressant, its robust antidepressant effects have been intensively examined in clinical trials. However, the therapeutic efficacy and mechanisms of repeated intermittent drug administration remain unclear. In the present study, we applied a classic chronic unpredictable mild stress (CUMS) model to induce depressive-like behaviors of mice and evaluated the role of repeated s-ketamine administration (10 mg/kg, 7 consecutive days) in ameliorating depressive-like behaviors and modulating related molecular pathways. A battery of behavioral tests were performed to assess CUMS-induced depression. The protein expressions of GluN1, GluN2A, GluN2B, GluR1, CaMKIIα, phosphorylated CaMKIIα (p-CaMKIIα), BDNF, TrkB, phosphorylated TrkB (p-TrkB), mTOR, and phosphorylated mTOR (p-mTOR) as well as modification of synaptic ultrastructure was identified in hippocampal tissues. It turned out that s-ketamine manifested evident antidepressant effects with improved synaptic plasticity. Meanwhile, the results suggested that s-ketamine could differentially modulate glutamate receptors with upregulated GluN1 and GluR1 levels and downregulated GluN2B levels. CUMS-induced elevation of CaMKIIα phosphorylation and decline of BDNF, TrkB phosphorylation and mTOR could also be reversed through s-ketamine treatment. Together, our study provided evidence that selectively modulated glutamate receptors as well as CaMKIIα and mTOR signaling were involved in repeated s-ketamine administration.

Zuranolone and its role in treating major depressive disorder: a narrative review

Major Depressive Disorder (MDD) is a mood disorder classified as a persistent depressive mood and loss of interest lasting for more than two weeks and accompanied by a list of symptoms outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) diagnostic criteria. MDD affects approximately 264 million people worldwide and is the most prevailing form of neuropsychiatric disorder. Owing to the probable hypothesized pathophysiology of MDD being an outcome of abnormalities in the amino acid neurotransmitter system, including glutamate (the primary excitatory neurotransmitter) and γ-aminobutyric acid (GABA), SAGE-217 (Zuranolone) is being evaluated as a possible therapeutic treatment for MDD. Zuranolone is a synthetic, neuroactive steroid (NAS) and positive allosteric modulator (PMA) of GABAA receptors, regulating both synaptic and extra-synaptic release of GABA. It is administered as a once-daily oral dose for 2 weeks due to its low-moderate clearance. A change in total HAM-D score from baseline was the primary end-point of all the trials. A phase II trial conducted to evaluate the efficacy and safety of Zuranolone (30 mg, once-daily dose), described a significant reduction in total HAM-D score at day 14 and reported the drug to be well tolerated with headache, dizziness, nausea, and somnolence as the most common adverse events (AE). Additional phase III trials were also conducted to evaluate similar outcomes, the interim topline results of which have been released. Consequently, this article attempts to briefly analyze the pharmacology of Zuranolone, review the available clinical data and outcomes regarding its use, and evaluate its place as a prospective novel therapy in the effective management of MDD.

The role of ghrelin peptide among a sample of Egyptian patients with first episode of major depressive disorder

Background

Major depressive disorder (MDD) is a prominent psychiatric disorder that significantly reduces living quality and increases the risk of suicide. Ghrelin influences the central nervous system (CNS) and impacts reward, inspiration, and signaling pathways in addition to acting as an appetite signal. This case-controlled comparative study focused on the association between serum ghrelin levels and MDD. The study was done during September 2021 and March 2022 on 25 people with MDD and 25 healthy controls. SCID-1 and the Ham-D 17 scales were used to evaluate the cases. The GHQ scale was used to evaluate the controls. The serum ghrelin levels of all samples were determined. The findings were presented, and statistically analyzed to perform an accurate assessment.

Results

There were 50 subjects: 25 cases of MDD and 25 healthy matched controls with non-statistically significant difference to cases as regard gender, marital status, residence, education, age, height, weight and body mass index (BMI). Total serum ghrelin levels among our cases showed a mean value of 4.152, while the controls showed markedly low values, with a mean value of 0.436, showing a statistically significant difference between both groups with p < 0.001. Furthermore, Post Hoc analysis by least significant difference showed a significant difference between mild-severe and moderate-severe groups, although there was no statistically significant difference between mild and moderate groups.

Conclusions

There was a significant indirect correlation between serum ghrelin level and severity of the illness. Further investigations via longitudinal studies and on larger samples are recommended to settle specific causal paths between the two variables.

Abnormal habenula functional connectivity characterizes treatment-resistant depression

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Habenular hyper connectivity characterizes treatment-resistant depression.

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An interplay between reward and default mode networks is linked to suicidality.

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Abnormal habenula connectivity is a possible mechanism for anhedonia.

Background

A significant proportion of patients with major depressive disorder are resistant to antidepressant medication and psychological treatments. A core symptom of treatment-resistant depression (TRD) is anhedonia, or the inability to feel pleasure, which has been attributed to disrupted habenula function – a component of the reward network. This study aimed to map detailed neural circuitry architecture related to the habenula to identify neural mechanisms of TRD.

Methods

35 TRD patients, 35 patients with treatment-sensitive depression (TSD), and 38 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Functional connectivity analyses were performed using the left and right habenula as seed regions of interest, and the three groups were compared using whole-brain voxel-wise comparisons.

Results

The TRD group demonstrated hyperconnectivity of the left habenula to the left precuneus cortex and the right precentral gyrus, compared to the TSD group, and to the right precuneus cortex, compared to the TSD and HC groups. In contrast, TSD demonstrated hypoconnectivity than HC for both connectivity measures. These connectivity values were significantly higher in patients with a history of suicidal ideation.

Conclusions

This study provides evidence that, unlike TSD, TRD is characterized by hyperconnectivity of the left habenula particularly with regions of the default mode network. An increased interplay between reward and default mode networks is linked to suicidality and could be a possible mechanism for anhedonia in hard to treat depression.

A clinical approach to treatment resistance in depressed patients: What to do when the usual treatments don't work well enough?

BACKGROUND

Major depressive disorder is a common, recurrent, disabling and costly disorder that is often severe and/or chronic, and for which non-remission on guideline concordant first-line antidepressant treatment is the norm. A sizeable percentage of patients diagnosed with MDD do not achieve full remission after receiving antidepressant treatment. How to understand or approach these 'refractory', 'TRD' or 'difficult to treat' patients need to be revisited. Treatment resistant depression (TRD) has been described elsewhere as failure to respond to adequate treatment by two different antidepressants. This definition is problematic as it suggests that TRD is a subtype of major depressive disorder (MDD), inferring a boundary between TRD and depression that is not treatment resistant. However, there is scant evidence to suggest that a discrete TRD entity exists as a distinct subtype of MDD, which itself is not a discrete or homogeneous entity. Similarly, the boundary between TRD and other forms of depression is predicated at least in part on regulatory and research requirements rather than biological evidence or clinical utility.

AIM

This paper aims to investigate the notion of treatment failure in order to understand (i) what is TRD in the context of a broader formulation based on the understanding of depression, (ii) what factors make an individual patient difficult to treat, and (iii) what is the appropriate and individualised treatment strategy, predicated on an individual with refractory forms of depression?

METHOD

Expert contributors to this paper were sought internationally by contacting representatives of key professional societies in the treatment of MDD - World Federation of Societies for Biological Psychiatry, Australasian Society for Bipolar and Depressive Disorders, International Society for Affective Disorders, Collegium Internationale Neuro-Psychopharmacologium and the Canadian Network for Mood and Anxiety Treatments. The manuscript was prepared through iterative editing.

OUTCOMES

The concept of TRD as a discrete subtype of MDD, defined by failure to respond to pharmacotherapy, is not supported by evidence. Between 15 and 30% of depressive episodes fail to respond to adequate trials of 2 antidepressants, and 68% of individuals do not achieve remission from depression after a first-line course of antidepressant treatment. Failure to respond to antidepressant treatment, somatic therapies or psychotherapies may often reflect other factors including; biological resistance, diagnostic error, limitations of current therapies, psychosocial variables, a past history of exposure to childhood maltreatment or abuse, job satisfaction, personality disorders, co-morbid mental and physical disorders, substance use or non-adherence to treatment. Only a subset of patients not responding to antidepressant treatment can be explained through pharmacokinetic or pharmacodynamics mechanisms. We propose that non remitting MDD should be personalised, and propose a strategy of 'deconstructing depression'. By this approach, the clinician considers which factors contribute to making this individual both depressed and 'resistant' to previous therapeutic approaches. Clinical formulation is required to understand the nature of the depression. Many predictors of response are not biological, and reflect a confluence of biological, psychological, and sociocultural factors, which may influence the illness in a particular individual. After deconstructing depression at a personalised level, a personalised treatment plan can be constructed. The treatment plan needs to address the factors that have contributed to the individual's hard to treat depression. In addition, an individual with a history of illness may have a lot of accumulated life issues due to consequences of their illness, and these should be addressed in a recovery plan.

LIMITATIONS

A 'deconstructing depression' qualitative rubric does not easily provide clear inclusion and exclusion criteria for researchers wanting to investigate TRD.

CONCLUSIONS

MDD is a polymorphic disorder and many individuals who fail to respond to standard pharmacotherapy and are considered hard to treat. These patients are best served by personalised approaches that deconstruct the factors that have contributed to the patient's depression and implementing a treatment plan that adequately addresses these factors. The existence of TRD as a discrete and distinct subtype of MDD, defined by two treatment failures, is not supported by evidence.

Association between Depression, Antidepression Medications, and the Risk of Developing Type 2 Diabetes Mellitus: A Nationwide Population-Based Retrospective Cohort Study in Taiwan

The relationship between depression, antidepressant medications (ADMs), and the risk of subsequent type 2 diabetes mellitus (T2DM) development remains controversial. Thus, we investigated this aspect by a population-based retrospective cohort study using the Longitudinal Health Insurance Database 2000 available in Taiwan. This large, observational study included 46,201 patients with depression and a 1 : 1 age- and sex-matched nondepression cohort enrolled between January 1, 2000, and December 31, 2013, and the newly diagnosed T2DM incidence rates were determined. We estimated the effects of depression on T2DM and the cumulative incidence curves by Cox proportional regression hazard models and Kaplan-Meier methods, respectively. We found that 47.97% of the patients with depression did not receive ADM. Among patients with depression who received ADM, 29.71%, 6.29%, 0.05%, 9.65%, and 6.32% received selective serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants (TCAs), monoamine oxidase inhibitors (MAOIs), heterocyclic antidepressants, and other medications, respectively. Patients without ADM treatment had a 39% higher risk of developing T2DM. However, those who received ADM treatment had a significantly lower risk of T2DM development in every treatment category. Depressive disorder treated with ADMs, especially with long-term use, was associated with an 11–48% decrease in the risk of T2DM in all ADM groups; however, heterocyclic antidepressant treatment for shorter periods (<80 days) was not significantly associated with a decreased risk of T2DM. The incidence of T2DM in Taiwan was found to be associated with an a priori history of depression and was inversely correlated with ADM treatment.

Reverse translation of major depressive disorder symptoms: A framework for the behavioural phenotyping of putative biomarkers

BACKGROUND

Reverse translating putative biomarkers of depression from patients to animals is complex because Major Depressive Disorder (MDD) is a highly heterogenous condition. This review proposes an approach to reverse translation based on relating relevant bio-behavioural functions in laboratory rodents to MDD symptoms.

METHODS

This systematic review outlines symptom clusters assessed by psychometric tests of MDD and antidepressant treatment response including the Montgomery-Åsberg Depression Rating Scale, the Hamilton Depression Rating Scale, and the Beck Depression Inventory. Symptoms were related to relevant behavioural assays in laboratory rodents.

RESULTS

The resulting battery of tests includes passive coping, anxiety-like behaviours, sleep, caloric intake, cognition, psychomotor functions, hedonic reactivity and aversive learning. These assays are discussed alongside relevant clinical symptoms of MDD, providing a framework through which reverse translation of a biomarker can be interpreted.

LIMITATIONS

Certain aspects of MDD may not be quantified by tests in laboratory rodents, and their biological significance may not always be of clinical relevance.

CONCLUSIONS

Using this reverse translation approach, it is possible to clarify the functional significance of a putative biomarker in rodents and hence translate its contribution to specific clinical symptoms, or clusters of symptoms.

An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report

Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment. 181 MDD and 95 healthy comparison (HC) participants were studied. After 8 weeks of escitalopram treatment (10-20 mg/d, flexible dosage), responders (>50% decrease in Montgomery-Åsberg Depression Scale score) were continued on escitalopram; non-responders received adjunctive aripiprazole (2-10 mg/d, flexible dosage). MDD participants were classified into subgroups according to their response profiles at weeks 8 and 16. Baseline group differences in cortical thickness were analyzed with FreeSurfer between HC and MDD groups as well as between response groups. Two-stage longitudinal processing was used to investigate 8-week escitalopram treatment-related changes in cortical thickness. Compared to HC, the MDD group exhibited thinner cortex in the left rostral middle frontal cortex [MNI(X,Y,Z=-29,9,54.5,-7.7); CWP=0.0002]. No baseline differences in cortical thickness were observed between responders and non-responders based on week-8 or week-16 response profile. No changes in cortical thickness was observed after 8 weeks of escitalopram monotherapy. In a two-step 16-week sequential clinical trial we found that baseline cortical thickness does not appear to be associated to clinical response to pharmacotherapy at 8 or 16 weeks.