Models Of Major Depressive Disorder Research Articles

Deficient Autophagy in Microglia Aggravates Repeated Social Defeat Stress-Induced Social Avoidance.

Major depressive disorder (MDD) is associated with repeated exposure to environmental stress. Autophagy is activated under various stress conditions that are associated with several diseases in the brain. This study was aimed at elucidating the autophagy signaling changes in the prefrontal cortex (PFC) under repeated social defeat (RSD) to investigate the involvement of microglial autophagy in RSD-induced behavioral changes. We found that RSD stress, an animal model of MDD, significantly induced initial autophagic signals followed by increased transcription of autophagy-related genes (Atg6, Atg7, and Atg12) in the PFC. Similarly, significantly increased transcripts of ATGs (Atg6, Atg7, Atg12, and Atg5) were confirmed in the postmortem PFC of patients with MDD. The protein levels of the prefrontal cortical LC3B were significantly increased, whereas p62 was significantly decreased in the resilient but not in susceptible mice and patients with MDD. This indicates that enhanced autophagic flux may alleviate stress-induced depression. Furthermore, we identified that FKBP5, an early-stage autophagy regulator, was significantly increased in the PFC of resilient mice at the transcript and protein levels. In addition, the resilient mice exhibited enhanced autophagic flux in the prefrontal cortical microglia, and the autophagic deficiency in microglia aggravated RSD-induced social avoidance, indicating that microglial autophagy involves stress-induced behavioral changes.

Adaptation of Lipid Profiling in Depression Disease and Treatment: A Critical Review.

Major depressive disorder (MDD), also called depression, is a serious disease that impairs the quality of life of patients and has a high incidence, affecting approximately 3.8% of the world population. Its diagnosis is very subjective and is not supported by measurable biomarkers mainly due to the lack of biochemical markers. Recently, disturbance of lipid profiling has been recognized in MDD, in animal models of MDD or in depressed patients, which may contribute to unravel the etiology of the disease and find putative new biomarkers, for a diagnosis or for monitoring the disease and therapeutics outcomes. In this review, we provide an overview of current knowledge of lipidomics analysis, both in animal models of MDD (at the brain and plasma level) and in humans (in plasma and serum). Furthermore, studies of lipidomics analyses after antidepressant treatment in rodents (in brain, plasma, and serum), in primates (in the brain) and in humans (in plasma) were reviewed and give evidence that antidepressants seem to counteract the modification seen in lipids in MDD, giving some evidence that certain altered lipid profiles could be useful MDD biomarkers for future precision medicine.

Fluoxetine inhibited the activation of A1 reactive astrocyte in a mouse model of major depressive disorder through astrocytic 5-HT2BR/\u03b2-arrestin2 pathway

BackgroundFluoxetine, a selective serotonin reuptake inhibitor, has been reported to directly bind with 5-HT2B receptor (5-HT2BR), but the precise mechanisms, whereby fluoxetine confers the anti-depressive actions via 5-HT2BR is not fully understood. Although neuroinflammation-induced A1 astrocytes are involved in neurodegenerative diseases, the role of A1 astrocyte in the pathogenesis and treatment of major depressive disorder (MDD) remains unclear.MethodsMice were subjected to chronic mild stress (CMS) for 6 weeks and subsequently treated with fluoxetine for 4 weeks. The depressive-like and anxiety-like behaviors and the activation of A1 reactive astrocyte in hippocampus and cortex of mice were measured. Primary astrocytes were stimulated with A1 cocktail (tumor necrosis factor (TNF)-α, interleukin (IL)-1α and C1q), activated (LPS) microglia-conditioned medium (MCM) or IL-6 for 24 h and the expression of A1-special and A2-special markers were determined using RT-qPCR and western blot. The role of 5-HT2BR in the effects of fluoxetine on A1 reactive astrocyte was measured using 5-HT2BR inhibitor and siRNA in vitro and AAVs in vivo. The functions of downstream signaling Gq protein and β-arrestins in the effects of fluoxetine on the activation of A1 astrocyte were determined using pharmacological inhibitor and genetic knockout, respectively.ResultsIn this study, we found that fluoxetine inhibited the activation of A1 reactive astrocyte and reduced the abnormal behaviors in CMS mice, as well as ameliorated A1 astrocyte reactivity under three different stimulators in primary astrocytes. We also showed that astrocytic 5-HT2BR was required in the inhibitory effects of fluoxetine on A1 reactive astrocyte in MDD in vivo and in vitro. We further found that the functions of fluoxetine in the activation of A1 astrocyte were independent of either Gq protein or β-arrestin1 in vitro. β-arrestin2 pathway was the downstream signaling of astrocytic 5-HT2BR mediated the inhibitory effects of fluoxetine on A1 astrocyte reactivity in primary astrocytes and CMS mice, as well as the improved roles of fluoxetine in behavioral impairments of CMS mice.ConclusionsThese data demonstrate that fluoxetine restricts reactive A1 astrocyte via astrocytic 5-HT2BR/β-arrestin2 pathway in a mouse model of MDD and provide a novel therapeutic avenue for MDD.

Antidepressant effects of Enterococcus faecalis 2001 through the regulation of prefrontal cortical myelination via the enhancement of CREB/BDNF and NF-κB p65/LIF/STAT3 pathways in olfactory bulbectomized mice

A therapeutic strategy through the gut–brain axis has been proven to be effective in treatment for depression. In our previous study, we demonstrated that Enterococcus faecalis 2001 (EF-2001) prevents colitis-induced depressive-like behavior through the gut–brain axis in mice. More recently, we found that demyelination in the prefrontal cortex (PFC) was associated with depressive-like behavior in an animal model of major depressive disorder, olfactory bulbectomized (OBX) mice. The present study investigated the effects of EF-2001 on depressive-like behaviors in OBX mice and the underlying molecular mechanisms from the perspective of myelination in the PFC. OBX mice exhibited depressive-like behaviors in the tail-suspension, splash, and sucrose preference tests, and decreased myelin and paranodal proteins along with mature oligodendrocytes in the PFC. These behavioral and biochemical changes were all prevented by treatment with EF-2001. Further, EF-2001 treatment increased brain-derived neurotrophic factor (BDNF) and leukemia inhibitory factor (LIF) in the PFC. Interestingly, an immunohistochemical analysis revealed enhanced phospho (p) -cAMP-responsive element binding protein (CREB) expression in neurons, p-nuclear factor-kappa B (NFκB) p65 (Ser536) expression in astrocytes, and p-signal transducer and activator of transcription 3 (STAT3) (Ty705) expression in mature oligodendrocytes in the PFC of OBX mice. From these results, we suggest that EF-2001 administration prevents depressive-like behaviors by regulating prefrontal cortical myelination via the enhancement of CREB/BDNF and NFκB p65/LIF/STAT3 pathways. Our findings strongly support the idea that a therapeutic strategy involving the gut microbiota may be a promising alternative treatment for alleviating symptoms of depression.

Death-associated protein kinase 1 is associated with cognitive dysfunction in major depressive disorder.

We previously showed that death-associated protein kinase 1 (DAPK1) expression is increased in hippocampal tissue in a mouse model of major depressive disorde and is related to cognitive dysfunction in Alzheimer's disease. In addition, depression is a risk factor for developing Alzheimer's disease, as well as an early clinical manifestation of Alzheimer's disease. Meanwhile, cognitive dysfunction is a distinctive feature of major depressive disorder. Therefore, DAPK1 may be related to cognitive dysfunction in major depressive disorder. In this study, we established a mouse model of major depressive disorder by housing mice individually and exposing them to chronic, mild, unpredictable stressors. We found that DAPK1 and tau protein levels were increased in the hippocampal CA3 area, and tau was hyperphosphorylated at Thr231, Ser262, and Ser396 in these mice. Furthermore, DAPK1 shifted from axonal expression to overexpression on the cell membrane. Exercise and treatment with the antidepressant drug citalopram decreased DAPK1 expression and tau protein phosphorylation in hippocampal tissue and improved both depressive symptoms and cognitive dysfunction. These results indicate that DAPK1 may be a potential reason and therapeutic target of cognitive dysfunction in major depressive disorder.

Minocycline Treatment Improves Cognitive and Functional Plasticity in a Preclinical Mouse Model of Major Depressive Disorder

Minocycline Treatment Improves Cognitive and Functional Plasticity in a Preclinical Mouse Model of Major Depressive Disorder

Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study

Many patients with bipolar disorder (BD) are initially misdiagnosed with major depressive disorder (MDD) and are treated with antidepressants, whose potential iatrogenic effects are widely discussed. It is unknown whether MDD is a comorbidity of BD or its earlier stage, and no consensus exists on individual conversion predictors, delaying BD’s timely recognition and treatment. We aimed to build a predictive model of MDD to BD conversion and to validate it across a multi-national network of patient databases using the standardization afforded by the Observational Medical Outcomes Partnership (OMOP) common data model. Five “training” US databases were retrospectively analyzed: IBM MarketScan CCAE, MDCR, MDCD, Optum EHR, and Optum Claims. Cyclops regularized logistic regression models were developed on one-year MDD-BD conversion with all standard covariates from the HADES PatientLevelPrediction package. Time-to-conversion Kaplan-Meier analysis was performed up to a decade after MDD, stratified by model-estimated risk. External validation of the final prediction model was performed across 9 patient record databases within the Observational Health Data Sciences and Informatics (OHDSI) network internationally. The model’s area under the curve (AUC) varied 0.633–0.745 (µ = 0.689) across the five US training databases. Nine variables predicted one-year MDD-BD transition. Factors that increased risk were: younger age, severe depression, psychosis, anxiety, substance misuse, self-harm thoughts/actions, and prior mental disorder. AUCs of the validation datasets ranged 0.570–0.785 (µ = 0.664). An assessment algorithm was built for MDD to BD conversion that allows distinguishing as much as 100-fold risk differences among patients and validates well across multiple international data sources.

Functional Contribution of the Medial Prefrontal Circuitry in Major Depressive Disorder and Stress-Induced Depressive-Like Behaviors.

Despite decades of research on the neurobiology of major depressive disorder (MDD), the mechanisms underlying its expression remain unknown. The medial prefrontal cortex (mPFC), a hub region involved in emotional processing and stress response elaboration, is highly impacted in MDD patients and animal models of chronic stress. Recent advances showed alterations in the morphology and activity of mPFC neurons along with profound changes in their transcriptional programs. Studies at the circuitry level highlighted the relevance of deciphering the contributions of the distinct prefrontal circuits in the elaboration of adapted and maladapted behavioral responses in the context of chronic stress. Interestingly, MDD presents a sexual dimorphism, a feature recognized in the molecular field but understudied on the circuit level. This review examines the recent literature and summarizes the contribution of the mPFC circuitry in the expression of MDD in males and females along with the morphological and functional alterations that change the activity of these neuronal circuits in human MDD and animal models of depressive-like behaviors.

Vortioxetine Improves Mood and Cognitive Function in Animal Models of Psychiatric Disease: Relevance of 5-HT3 Receptor-Mediated Regulation of GABA and Glutamate Neurotransmission

Vortioxetine is a multimodal antidepressant that improves mood and some cognitive functions major depressive disorder (MDD). Vortioxetine has a complex pharmacological profile that includes 5-HT3 receptor antagonism, which is thought to induce regionally selective increases glutamatergic neurotransmission by suppressing activity in GABAergic interneurons. In the present work, the relevance of 5-HT3 receptor antagonism for improving mood and cognition will be evaluated in animal models of MDD and schizophrenia.

Urine proteome changes in a chronic unpredictable mild stress (CUMS) mouse model of major depressive disorder

Major depressive disorder (MDD) is a prevalent complex psychiatric disorder, and there are no effective biomarkers for clinical diagnosis. Urine is not subjected to homeostatic control, allowing it to reflect the sensitive changes that occur in various diseases. In this study, we examined the urine proteome changes in a chronic unpredictable mild stress mouse model of MDD. Male C57BL/6 mice were subjected to chronic unpredictable mild stress for 5 weeks. The tail suspension test and sucrose consumption test were then applied to evaluate depression-like behaviors. The urine proteomes on day 0 and day 36 in the CUMS group were profiled by liquid chromatography coupled with tandem mass spectrometry (LCMS/MS). A total of 36 differential proteins were identified, 19 of which have been associated with the pathogenic mechanisms of MDD. There was an average of two differential proteins that were identified through 1,048,574 random combination statistical analyses, indicating that at least 95 % of the differential proteins were reliable. The differential proteins were mainly associated with blood coagulation, inflammatory responses and central nervous system development. Our preliminary results indicated that the urine proteome can reflect changes associated with MDD in the CUMS model, which provides potential clues for the diagnosis of MDD.

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

BackgroundExperiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies tested the MDD factor structure in Chinese natural disaster survivors. Therefore, the aim of the current study was to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors.MethodParticipants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different domains of health-related quality of life (HRQoL), respectively.ResultsIn the current sample, the model consisted of somatic and cognitive/affective (non-somatic) factors demonstrated significantly better fit than the other competing MDD models (χ2 = 173.89, df = 26, CFI = 0.986, TLI = 0.981, RMSEA = 0.073, BIC = 18,091.13). Further SEM analyses indicated that the non-somatic factor was significantly related to both physical (β = − 0.362, p < .01) and psychosocial HRQoL (β = − 0.773, p < .01), while the somatic factor was a uniquely predictor of physical HRQoL (β = − 0.336, p < .01). Furthermore, we found the somatic factor partially mediated the relationship between the cognitive/affective factor and physical HRQoL (all ps < .05).ConclusionsThe MDD symptoms was best captured by a two-factor model comprised of somatic and cognitive/affective factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial HRQoL, and the cognitive/affective factor associated physical HRQoL partially through the somatic factor. The current findings increase our understanding of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.

Brain-derived neurotrophic factor enhances the therapeutic effect of oleuropein in the lipopolysaccharide-induced models of depression.

Major depressive disorder (MDD) is a heterogeneous disease, involving multiple mechanisms and factors, which commonly result in injury to the psychosocial function of the central nervous system, and even suicidality of patients. However, effective treatment for MDD is still lacking. Oleuropein is a newly discovered natural compound extracted from olive leaves, which has a strong antioxidative effect by reducing the production of reactive oxygen species (ROS). Oleuropein also reduces blood pressure in humans and experimental animals, and protects blood vessels. Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophin family, which supports the function of the central nervous system. BDNF plays an important role in the development of the nervous system via the regulation of cellular differentiation, survival neurogenesis and synaptic plasticity; therefore, we hypothesized that overexpression of BDNF might contribute to the therapeutic effect of oleuropein. Here, we first demonstrated that oleuropein reverses depressive-like behaviour and restores the inflammatory response in a mouse lipopolysaccharide (LPS) model of MDD. We further established a cell model of BDNF overexpression and inhibition in SH-SY5Y cells, and found that the concentration of intercellular calcium was increased after treatment with oleuropein combined with BDNF overexpression, which may be mediated by the BDNF-TrkB-CaMKII signalling pathway. In addition, we observed that the expression of neurotrophic factors, including epidermal growth factor (EGF), neurotrophin-3 (NT-3), and neurotrophin-4 (NT-4), was increased, which may be mediated by inhibition of the RhoA-ROCK signalling pathway.

Subgenual activation and the finger of blame: individual differences and depression vulnerability.

Subgenual cingulate cortex (SCC) responses to self-blaming emotion-evoking stimuli were previously found in individuals prone to self-blame with and without a history of major depressive disorder (MDD). This suggested SCC activation reflects self-blaming emotions such as guilt, which are central to models of MDD vulnerability. Here, we re-examined these hypotheses in an independent larger sample. A total of 109 medication-free participants (70 with remitted MDD and 39 healthy controls) underwent fMRI whilst judging self- and other-blaming emotion-evoking statements. They also completed validated questionnaires of proneness to self-blaming emotions including those related to internal (autonomy) and external (sociotropy) evaluation, which were subjected to factor analysis. An interaction between group (remitted MDD v. Control) and condition (self- v. other-blame) was observed in the right SCC (BA24). This was due to higher SCC signal for self-blame in remitted MDD and higher other-blame-selective activation in Control participants. Across the whole sample, extracted SCC activation cluster averages for self- v. other-blame were predicted by a regression model which included the reliable components derived from our factor analysis of measures of proneness to self-blaming emotions. Interestingly, this prediction was solely driven by autonomy/self-criticism, and adaptive guilt factors, with no effect of sociotropy/dependency. Despite confirming the prediction of SCC activation in self-blame-prone individuals and those vulnerable to MDD, our results suggest that SCC activation reflects blame irrespective of where it is directed rather than selective for self. We speculate that self-critical individuals have more extended SCC representations for blame in the context of self-agency.

Solid lipid nanoparticles loading with curcumin and dexanabinol to treat major depressive disorder.

Dexanabinol (HU-211) is an artificially synthesized cannabinoid derivative that exerts neuroprotective effects through anti-inflammatory and antioxidant effects. Curcumin exhibits antidepressant effects in the treatment of major depressive disorder. To investigate the antidepressant effects of solid lipid nanoparticles loaded with both curcumin and dexanabinol, and the underlying mechanisms associated with this combination, we established wild-type (CBR1+/+) and cannabinoid receptor 1 (CBR1) knockout (CBR1-/-) mouse models of major depressive disorder, through the intraperitoneal injection of corticosterone, for 3 successive days, followed by treatment with intraperitoneal injections of solid lipid nanoparticles loading with curcumin (20 mg/kg) and dexanabinol (0.85 mg/kg), for 2 successive days. Our results revealed that solid lipid nanoparticle loading with curcumin and dexanabinol increased the mRNA and protein expression levels of the mature neuronal markers neuronal nuclei, mitogen-activated protein 2, and neuron-specific beta-tubulin III, promoted the release of dopamine and norepinephrine, and increased the mRNA expression of CBR1 and the downstream genes Rasgef1c and Egr1, and simultaneously improved rat locomotor function. However, solid lipid nanoparticles loaded with curcumin and dexanabinol had no antidepressant effects on the CBR1-/- mouse models of major depressive disorder. This study was approved by the Institutional Ethics Committee of Tongji Hospital of Tongji University, China (approval No. 2017-DW-020) on May 24, 2017.

Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation of both structural and functional connections of the brain and the effects in the diagnosis and treatment of neurodegenerative diseases. Currently, there is no clinically specific diagnostic biomarker capable of confirming the diagnosis of major depressive disorder (MDD). Therefore, exploring translational biomarkers of mood disorders based on deep learning (DL) has valuable potential with its recently underlined promising outcomes. In this article, an electroencephalography (EEG)-based diagnosis model for MDD is built through advanced computational neuroscience methodology coupled with a deep convolutional neural network (CNN) approach. EEG recordings are analyzed by modeling 3 different deep CNN structure, namely, ResNet-50, MobileNet, Inception-v3, in order to dichotomize MDD patients and healthy controls. EEG data are collected for 4 main frequency bands (Δ, θ, α, and β, accompanying spatial resolution with location information by collecting data from 19 electrodes. Following the pre-processing step, different DL architectures were employed to underline discrimination performance by comparing classification accuracies. The classification performance of models based on location data, MobileNet architecture generated 89.33% and 92.66% classification accuracy. As to the frequency bands, delta frequency band outperformed compared to other bands with 90.22% predictive accuracy and area under curve (AUC) value of 0.9 for ResNet-50 architecture. The main contribution of the study is the delineation of distinctive spatial and temporal features using various DL architectures to dichotomize 46 MDD subjects from 46 healthy subjects. Exploring translational biomarkers of mood disorders based on DL perspective is the main focus of this study and, though it is challenging, with its promising potential to improve our understanding of the psychiatric disorders, computational methods are highly worthy for the diagnosis process and valuable in terms of both speed and accuracy compared with classical approaches.

Machine-learning models for depression and anxiety in individuals with immune-mediated inflammatory disease

ObjectiveIndividuals with immune-mediated inflammatory disease (IMID) have a higher prevalence of psychiatric disorders than the general population. We utilized machine-learning to identify patient-reported outcome measures (PROMs) that accurately predict major depressive disorder (MDD) and anxiety disorder in an IMID population. MethodsParticipants with IMID were enrolled in a cohort study and completed a Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID), and multiple PROMs. PROM items were ranked separately for MDD and anxiety disorder by the standardized mean difference between individuals with and without psychiatric disorders. Items were added sequentially to logistic regression (LR), neural network (NN), and random forest (RF) models. Discriminative performance was assessed with area under the receiver operator curve (AUC) and calibration was assessed with Brier scores. Ten-fold cross-validation was used. ResultsOf 637 participants, 75% were female and average age was 51 years. AUC and Brier scores respectively ranged from 0.87–0.91 and 0.07 (i.e., no variation) for MDD models, and from 0.79–0.83 and 0.09–0.11 for anxiety disorder models. In LR and NN, few PROM items were required to obtain optimal discriminatory performance. RF did not perform as well as LR and NN when few PROM items were included. ConclusionsPredictive model performance was respectable and revealed insight into PROM items that are predictive of MDD and anxiety disorder. Models that included only the items ‘I felt depressed’ and ‘I felt like I needed help for my anxiety’ performed similarly to models that included all items from multiple PROMs.

Chronic Royal Jelly Administration Induced Antidepressant-Like Effects Through Increased Sirtuin1 and Oxidative Phosphorylation Protein Expression in the Amygdala of Mice.

Major depressive disorder (MDD) is a common psychological disorder worldwide. However, one-third of patients with MDD are resistant to the present anti-depressant medicine, which regulates monoamine contents in the brain. Thus, another drug target is strongly required. Much evidence strongly suggests that sirtuin1, which is the key factor in regulating the mitochondrial activity, may be implicated in MDD. Since it is suggested that royal jelly (RJ) ameliorated depressive-like behavior and affected mitochondrial activity in mice, we hypothesized that RJ could be an alternative medicine against MDD, which acts via sirtuin1 signaling to improve mitochondrial activity. In the present study, we applied a mouse model of MDD to investigate the effect of RJ on the depressive-like behavior and the sirtuin1 signaling on mitochondrial activity. Our results indicated that either the oral administration of RJ for 12 days or single intracerebroventricular (i.c.v.) injection decreased the duration of immobility in the tail suspension test, which suggested that RJ had an antidepressant-like effect. Moreover, sirtuin1 protein expression increased in mice following RJ treatment in the amygdala region, but not in the other brain regions. Similarly, the expressions of oxidative phosphorylation (OXPHOS) related proteins increased in the amygdala regions, but not in the hippocampal regions. The increase of sirtuin1 and OXPHOS protein expression may at least in part contribute to the antidepressant-like effect of the RJ pathway, and RJ may have the potential to be a novel anti-depressant drug.

Depressing effects of microglia

Immunopsychiatry Microglia act as the brain's resident cleanup squad by phagocytosing apoptotic cells, plaques, and pathogens. Because they can prune and reshape synapses, microglia may also be influential in the pathogenesis of psychiatric illnesses. Lago et al. report that CD300f, a receptor found on microglia that recognizes the “eat me” signal phosphatidylserine, may be involved in major depressive disorder (MDD). A polymorphism of CD300f affects signaling and is associated with protection against MDD in women but not men. A lack of CD300f impairs microglial metabolic fitness, and Cd300f −/− female mice exhibited depressive-like behavior in models of MDD. Caveats about murine MDD models aside, this suggests that microglia and CD300f may be suitable future therapeutic targets for this disorder. Proc. Natl. Acad. Sci. U.S.A. 117 , 6651 (2020).

Major Depressive Disorder Among HIV Infected Youth in Uganda: Incidence, Persistence and Their Predictors.

Incidence and persistence of major depressive disorder (MDD) in children and adolescents with HIV (CA-HIV) in Uganda is described. 1339 CA-HIV attending care were enrolled and followed up for 12months. MDD was assessed using the DSM-5 referenced Child and Adolescent Symptom Inventory-5 (CASI-5), with a prevalence for MDD at baseline of 5% (95% CI 3.3-7.3). Kaplan-Meir method was used to estimate incidence of MDD and Cox models were fitted to investigate predictors of incident MDD. Cumulative incidence of MDD over 12months was 7.6 per 100 person-years 95% CI (6.2-9.4) and a rate of persistent MDD of 10/105 (9.5% CI 3.9-15.1). Significant independent predictors of incident MDD were: highest educational level of CA-HIV (protective), increasing depressive scores and decreasing CD4 Nadir. These finding have implications for what should constitute components of a mental health integration model in HIV youth services and for the future development of individualised mental health care.

Shared Transcriptional Signatures in Major Depressive Disorder and Mouse Chronic Stress Models

BackgroundMost of our knowledge of the biological basis of major depressive disorder (MDD) is derived from studies of chronic stress models in rodents. While these models capture certain aspects of the behavioral and neuroendocrine features of MDD, the extent to which they reproduce the molecular pathology of the human syndrome remains unknown. MethodsWe systematically compared transcriptional signatures in two brain regions implicated in depression—medial prefrontal cortex and nucleus accumbens—of humans with MDD and of 3 chronic stress models in mice: chronic variable stress, adult social isolation, and chronic social defeat stress. We used differential expression analysis combined with weighted gene coexpression network analysis to create interspecies gene networks and assess the capacity of each stress paradigm to recapitulate the transcriptional organization of gene networks in human MDD. ResultsOur results show significant overlap between transcriptional alterations in medial prefrontal cortex and nucleus accumbens in human MDD and the 3 mouse chronic stress models, with each of the chronic stress paradigms capturing distinct aspects of MDD abnormalities. Chronic variable stress and adult social isolation better reproduce differentially expressed genes, while chronic social defeat stress and adult social isolation better reproduce gene networks characteristic of human MDD. We also identified several gene networks and their constituent genes that are most significantly associated with human MDD and mouse stress models. ConclusionsThis study demonstrates the ability of 3 chronic stress models in mice to recapitulate distinct aspects of the broad molecular pathology of human MDD, with no one mouse model apparently better than another.