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Previous pattern electroretinogram studies indicate reduced retinal contrast gain in patients with a major depressive disorder (MDD) which may contribute to alterations in visual perception. In line, psychophysical investigations reported elevated contrast thresholds in MDD. This study aims to gain insights into higher-level processing of visual information in MDD by evaluating contrast suppression. We examined contrast suppression of 21 MDD patients and 23 healthy controls (HC) using four different stimulus conditions (spatial frequencies 6.3 and 12.6 cpd at 30% and 60% background contrast) in a psychophysical test. Participants were instructed to adjust perceived contrasts between two vertical target patches, embedded in a horizontally or vertically oriented grid background. With finer stimulus gratings, MDD patients exhibited less contrast suppression compared to HC, particularly when the stimulus contrast was high (p = 0.006; MDD vs. HC =  - 45%). Contrast suppression in the HC group was significantly reduced for the coarse compared to the fine grating, while contrast suppression scores in MDD did not change with the spatial properties of the stimulus. The reduced contrast suppression in patients with MDD supports the hypothesis of altered dopaminergic neurotransmission and could be attributed to alterations in the retinal receptive fields or in dysfunctional adaptation mechanisms in depression., Competing Interests: Declarations Competing interests KN, SPH, MBa, DE, KR, SK, SM, MBe, EF: no conflict of interest. LTvE: Advisory boards, lectures, or travel grants within the last 3 years: Roche, Eli Lilly, Janssen-Cilag, Novartis, Shire, UCB, GSK, Servier, Janssen and Cyberonics. KD: Formerly: Steering Committee Neurosciences and speaker honoraria, Janssen-Cilag, within the last three years. Ethics approval and consent to participate The Ethics Committee of the University Medical Center Freiburg (Approval ID: 314/18) approved the study. All participants gave written informed consent to participate., (© 2024. The Author(s).)

Background: Psychomotor retardation (PMR) is a core feature of major depressive disorder (MDD), which is characterized by abnormalities in motor control and cognitive processes. PMR in MDD can predict a poor antidepressant response, suggesting that PMR may serve as a marker of the antidepressant response. However, the neuropathological relationship between treatment outcomes and PMR remains uncertain. Thus, this study examined electrophysiological biomarkers associated with poor antidepressant response in MDD., Methods: A total of 142 subjects were enrolled in this study, including 49 healthy controls (HCs) and 93 MDD patients. All participants performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. Patients who exhibited at least a 50 % reduction in disorder severity at the endpoint (>2 weeks) were considered to be responders. Motor-related beta desynchronization (MRBD) and inter- and intra-hemispheric functional connectivity were measured in the bilateral motor network., Results: An increased MRBD and decreased inter- and intra-hemispheric functional connectivity in the motor network during movement were observed in non-responders, relative to responders and HCs. This dysregulation predicted the potential antidepressant response., Conclusion: Abnormal local activity and functional connectivity in the motor network indicate poor psychomotor function, which might cause insensitivity to antidepressant treatment. This could be regarded as a potential neural mechanism for the prediction of a patient's treatment response., Competing Interests: Declaration of competing interest The authors have no conflict of interest to declare., (Copyright © 2024. Published by Elsevier B.V.)

Background: Childhood trauma is closely tied to adult depression, but the neurobiological mechanisms remain unclear. Previous studies suggested associations between depression and large-scale brain networks such as the Ventral Attention Network (VAN) and Somatosensory Motor Network (SMN). This study hypothesized that functional connectivity (FC) within and between these networks mediates the link between childhood trauma and adult depression., Methods: The Childhood Trauma Questionnaire (CTQ) assessed developmental experiences, and the Hamilton Rating Scale for Depression (HAMD-17) gauged depressive symptoms. Resting-state functional magnetic resonance imaging (fMRI) analyzed FC within and between the VAN and SMN., Results: Depression group exhibited significantly higher HAMD and CTQ scores, as well as elevated FC within the VAN and between the VAN and SMN (P < 0.05). Positive correlations were found between HAMD total score and FC within the VAN (P < 0.05, r = 0.35) and between the VAN and SMN (P < 0.05, r = 0.34), as well as with CTQ total score (P < 0.05, r = 0.27). Positive correlations were also observed between CTQ total score and FC within the VAN (P < 0.05, r = 0.31) and between the VAN and SMN (P < 0.05, r = 0.29). In the mediation model, FC within and between the VAN and SMN significantly mediated childhood trauma and depression., Limitations: The cross-sectional design limits causal inference. The sample size for different trauma types is relatively small, urging caution in generalizing findings., Conclusions: The study underscores the association between depression severity, VAN dysfunction, abnormal VAN-SMN FC, and childhood trauma. These findings contribute to understanding the neurobiological mechanisms underlying childhood trauma and depression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Major depressive disorder (MDD) is a widespread mental health issue, impacting spatial and temporal aspects of brain activity. The neural mechanisms behind MDD remain unclear. To address this gap, we introduce a novel measure, spatiotemporal topology (SPT), capturing both the hierarchy and dynamic attributes of brain activity in depressive disorder patients., Methods: We analyzed fMRI data from 285 MDD inpatients and 141 healthy controls (HC). SPT was assessed by coupling brain gradient measurement and time delay estimation. A nested machine learning process distinguished between MDD and HC using SPT. Person's correlation tested the link between SPT's and symptom severity, and another machine learning method predicted the gap between patients' chronological and brain age., Results: SPT demonstrated significant differences between patients and healthy controls (F = 2.944, p < 0.001). Machine learning approaches revealed SPT's ability to discriminate between patients and healthy controls (Accuracy = 0.65, Sensitivity = 0.67, Specificity = 0.64). Moreover, SPT correlated with the severity of depression symptom (r = 0.32. pFDR = 0.045) and predicted the gap between patients' chronological age and brain age (r = 0.756, p < 0.001)., Limitations: Evaluation of brain dynamics was constrained by MRI temporal resolution., Conclusions: Our study introduces SPT as a promising metric to characterize the spatiotemporal signature of brain function, providing insights into deviant brain activity associated with depressive disorders and advancing our understanding of their psychopathological mechanisms., Competing Interests: Declaration of competing interest The authors report no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS) during verbal fluency task (VFT) have the potential to be used as an objective indicator for assessing clinical symptoms. However, comprehensive quantitative and objective assessment instruments for individuals who exhibit symptoms suggestive of depression remain undeveloped. Drawing from a total of 467 samples in a large-scale dataset comprising 289 MDD patients and 178 healthy controls, fNIRS measurements were obtained throughout the VFT. To identify unique MDD biomarkers, this research introduced a data representation approach for extracting spatiotemporal features from fNIRS signals, which were subsequently utilized as potential predictors. Machine learning classifiers (e.g., Gradient Boosted Decision Trees (GBDT) and Multilayer Perceptron) were implemented to assess the ability to predict selected features. The mean and standard deviation of the cross-validation indicated that the GBDT model, when combined with the 180-feature pattern, distinguishes patients with MDD from healthy controls in the most effective manner. The accuracy of correct classification for the test set was 0.829 ± 0.053, with an AUC of 0.895 (95 % CI: 0.864-0.925) and a sensitivity of 0.914 ± 0.051. Channels that made the most important contribution to the identification of MDD were identified using Shapley Additive Explanations method, located in the frontopolar area and the dorsolateral prefrontal cortex, as well as pars triangularis Broca's area. Assessment of abnormal prefrontal activity during the VFT in MDD serves as an objectively measurable biomarker that could be utilized to evaluate cognitive deficits and facilitate early screening for MDD. The model suggested in this research could be applied to large-scale case-control fNIRS datasets to detect unique characteristics of MDD and offer clinicians an objective biomarker-based analytical instrument to assist in the evaluation of suspicious cases., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Major depressive disorder (MDD) affects multiple functional neural networks. Neuroimaging studies using resting-state functional connectivity (FC) have focused on the amygdala but did not assess changes in connectivity between the left and right amygdala. The current study aimed to examine the inter-hemispheric functional connectivity (homotopic FC, HoFC) between different amygdalar sub-regions in patients with MDD compared to healthy controls, and to examine whether amygdalar sub-regions' HoFC also predicts response to Serotonin Selective Reuptake Inhibitors (SSRIs)., Method: Sixty-seven patients with MDD and 64 matched healthy controls were recruited. An MRI scan focusing on resting state fMRI and clinical and cognitive evaluations were performed. An atlas seed-based approach was used to identify the lateral and medial sub-regions of the amygdala. HoFC of these sub-regions was compared between groups and correlated with severity of depression, and emotional processing performance. Baseline HoFC levels were used to predict response to SSRIs after 2 months of treatment., Results: Patients with MDD demonstrated decreased inter-hemispheric FC in the medial (F3,120 = 4.11, p = 0.008, η2 = 0.096) but not in the lateral (F3,119 = 0.29, p = 0.82, η2 = 0.008) amygdala compared with healthy controls. The inter-hemispheric FC of the medial sub-region correlated with symptoms severity (r = -0.33, p < 0.001) and emotional processing performance (r = 0.38, p < 0.001). Moreover, it predicted treatment response to SSRIs 65.4 % of the cases., Limitations: The current study did not address FC changes in MDD biotypes. In addition, structural connectivity was not examined., Conclusions: Using a unique perspective of the amygdalar distinct areas elucidated differential inter-hemispheric FC patterns in MDD patients, emphasizing the role of interhemispheric communication in depression., Competing Interests: Declaration of competing interest No disclosures were noted for this manuscript., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Major Depressive Disorder (MDD) may exhibit impairments in cognitive flexibility. This study investigated whether the cognitive flexibility deficits in MDD are evident across general stimuli or specific to emotional stimuli, while exploring the underlying neuropsychological mechanism., Methods: A total of 41 MDD patients and 42 healthy controls (HCs) were recruited. Event-related potentials (ERPs) were recorded when participants performed a non-emotional and an emotional task switching paradigm (N-ETSP and ETSP), both of which assessed cognitive flexibility. Microstate and source localization analysis were applied to reflect brain activity among different brain areas during task switching., Results: In the N-ETSP, MDD group showed larger P3 difference wave (Pd3) amplitudes and longer P2 difference wave (Pd2) latencies. In the ETSP, MDD group displayed smaller N2 difference wave (Nd2) amplitudes and larger Pd3 amplitudes. The comparison of sLORETA images of emotional switch task and emotional repeat task showed that MDD group had increased activation in the precentral gyrus in microstate2 of the P2 time window and had reduced activation in the middle occipital gyrus in microstate3 of the N2 time window., Limitations: The cross-sectional design failed to capture dynamic changes in cognitive flexibility in MDD., Conclusions: MDD demonstrated impaired cognitive flexibility respond to both non-emotional and emotional stimuli, with greater impairment for negative emotional stimuli. These deficits are evident in abnormal ERPs component during the early attention stage and the later task preparation stage. Furthermore, abnormal emotional switching cost in MDD appears to be related to early abnormal perceptual control in the parietal-occipital cortex., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Research in functional asymmetry of Major Depressive Disorder (MDD) under different tasks is crucial for clinical diagnose., Methods: Fifty individuals with MDD and twenty healthy controls (HCS) were recruited for hemodynamic data collection under four fNIRS tasks (Emotional picture, Verbal fluency, Fingering and Negative emotional picture description task). Integral values and functional connectivity strength were employed to probe neural activation and functional connectivity in frontal and temporal lobes in MDD. Following, asymmetry characteristic of the frontal cortex between MDD and HCS under four tasks were carefully analyzed and compared., Results: Individuals with MDD demonstrated heightened connectivity between the frontal and right temporal lobes and reduced connectivity between the frontal and left temporal lobes compared to HCS in all tasks. Additionally, MDD exhibited attenuated activation in the left frontal lobes and exaggerated activation in the right frontal lobes, diverging from HCS. Furthermore, the disparities in left-right asymmetry characteristic of frontal cortex activation between MDD and HCS were more pronounced during the combined task., Limitations: Further research is required to grasp the neurophysiological mechanisms governing left-right asymmetry across various tasks and the influence of task-induced brain fatigue on cerebral cortex hemodynamics in MDD., Conclusion: The left-right asymmetry feature provides valuable neurophysiological insights for diagnosing MDD clinically. Variations in activation patterns and functional connectivity features between MDD and HCS are closely tied to the task chosen. Thus, in clinical practice, carefully selecting appropriate fNIRS tasks and relevant features can significantly improve the diagnostic accuracy of MDD., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: The relationship between neurotransmitters and oxidative stress in Major Depressive Disorder (MDD) patients, considering HPA axis activity and psychological and cognitive states, is unclear. This study examines changes in neurotransmitters (GABA, Glx) and antioxidants (GSH) in the dorsal anterior cingulate cortex (dACC) of MDD patients under varying levels of ACTH, and their relationship with psychological and cognitive conditions., Methods: Forty-five MDD patients were divided into high-ACTH (>65 pg/mL; n = 16) and normal-ACTH (7-65 pg/mL; n = 29) groups based on blood ACTH levels, along with 12 healthy controls (HC). All participants underwent HAM-D, HAM-A assessments, and most completed MMSE and MoCA tests. GABA+, Glx, and GSH levels in the dACC were measured using the MEGA-PRESS sequence. Intergroup differences and correlations between clinical factors, HPA axis activity, and metabolites were analyzed., Results: Compared to HC, the normal ACTH group showed higher Glx and lower GSH levels. Glx and GSH were negatively correlated with MDD severity. In the high-ACTH MDD group, Glx positively correlated with delayed memory, and GSH positively correlated with abstraction. Factors influencing GABA included ACTH levels, depression duration, and negative events. Predictive factors for HAM-D scores were GSH and GABA., Limitations: The sample size is small., Conclusion: MDD patients exhibit neurochemical differences in the brain related to HPA axis levels, MDD severity, and cognitive function. Clinical factors, neurotransmitters, and neuroendocrine levels significantly influence depression severity., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Abdominal acupuncture has definite efficacy for major depressive disorder (MDD). Our study examined how abdominal acupuncture regulates the integration within and between brain networks of MDD patients by neuroimaging and whether this functional integration can predict the efficacy. Forty-six female MDD patients were randomly divided into a fluoxetine + real acupuncture group (n = 22) and a fluoxetine + sham acupuncture group (n = 24). The differences in functional magnetic resonance imaging data in the intra- and inter-network functional connectivity (FC) of the default mode network (DMN), affective network (AN), salience network (SN), and cognitive control network (CCN) between the two groups were analyzed. The FCs in brain regions with the inter-group differences and support vector regression were used to predict the efficacy of abdominal acupuncture. Our results showed: that the intra- and inter-network FCs of DMN, AN, SN, and CCN could be changed by abdominal acupuncture. Using the baseline FCs within AN and DMN or AN-DMN as characteristics, combined with support vector regression, could better predict the efficacy of acupuncture. Our study suggests that abdominal acupuncture could treat MDD by regulating the integration of the functional networks DMN, AN, SN, and CCN. The baseline FCs within the DMN and AN or between them could be used as neural markers for predicting the efficacy of abdominal acupuncture., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

When discussing neurotransmitters whose signaling plays an important role in psychiatric illnesses, serotonin and dopamine may be the first that come to mind. Although serotonin and dopamine have significant roles, the impact of norepinephrine signaling is often overlooked. A growing body of evidence suggests that hyperactivity of norepinephrine signaling is an underlying issue in psychiatric disorders; conversely, there is evidence to suggest that deficits in the noradrenergic system are just as significant. Hence, alterations in noradrenergic activity are better characterized as dysregulation rather than a reductive, outdated formulation of "too much" or "too little" activity. Therefore, symptoms such as agitation, irritability, hyperarousal, and insomnia could be treated by targeting the underlying pathophysiology related to noradrenergic dysregulation with targeted treatments. In a recent consensus panel meeting, 5 experts reviewed the available evidence of altered noradrenergic activity and its potential role in some of the most common psychiatric disorders. This Academic Highlights article summarizes their discussion and presents the panel's conclusions., (© Copyright 2024 Physicians Postgraduate Press, Inc.)

Background: A subset of individuals with major depressive disorder (MDD) have a high burden of cardiovascular risk factors and cerebral small-vessel disease, implicating vascular disease in the development of depression. Cross-sectional studies demonstrate a link between endothelial dysfunction and MDD, but the prospective association between peripheral endothelial dysfunction (PED) and an incident diagnosis of MDD is unknown., Methods and Results: Patients undergoing a baseline assessment of cardiovascular risk were evaluated for PED using reactive hyperemia-peripheral arterial tonometry (≤1.8 consistent with PED). Patient medical records were reviewed to identify those who underwent a formal clinical evaluation of MDD after the index PED evaluation. The frequency of PED was compared in those with and without MDD. Logistic regression analyses were performed to assess the association between baseline PED and incident MDD. Between January 2006 and December 2020, 1614 patients underwent testing for PED. Four hundred eighty-four (30.1%) patients underwent a formal evaluation for MDD after (0-15 years) the index procedure (mean±SD age, 52.8±13.8 years; 65.2% women). Of these, 157 (32.4%) had PED and 108 (31.0%) were diagnosed with MDD. Individuals with MDD had a higher frequency of PED (40.2% versus 30.2%; P =0.034) compared with those without MDD. In multivariable analyses, PED was significantly associated with MDD (odds ratio, 2.3 [95% CI, 1.4-3.8]; P <0.001)., Conclusions: PED is significantly associated with incident MDD. Thus, PED may be a useful marker to identify individuals at increased risk of depression who may benefit from more frequent and earlier management strategies.

Aims: Self-regulation (SR) dysfunction is a crucial risk factor for major depressive disorder (MDD). However, neural substrates of SR linking MDD remain unclear., Methods: Sixty-eight healthy controls and 75 MDD patients were recruited to complete regulatory orientation assessments with the Regulatory Focus Questionnaire (RFQ) and Regulatory Mode Questionnaire (RMQ). Nodal intra and inter-network functional connectivity (FC) was defined as FC sum within networks of 46 thalamic subnuclei (TS) or 88 AAL brain regions, and between the two networks separately. Group-level volumetric and functional difference were compared by two sample t-tests. Pearson's correlation analysis and mediation analysis were utilized to investigate the relationship among imaging parameters and the two behaviors. Canonical correlation analysis (CCA) was conducted to explore the inter-network FC mode of TS related to behavioral subscales. Network-based Statistics with machine learning combining powerful brain imaging features was applied to predict individual behavioral subscales., Results: MDD patients showed no group-level volumetric difference in 46 TS but represented significant correlation of TS volume and nodal FC with behavioral subscales. Specially, inter-network FC of the orbital part of the right superior frontal gyrus and the left supplementary motor area mediated the correlation between RFQ/RMQ subscales and depressive severity. Furthermore, CCA identified how the two behaviors are linked via the inter-network FC mode of TS. More crucially, thalamic functional subnetworks could predict RFQ/RMQ subscales and psychomotor retardation for MDD individuals., Conclusion: These findings provided neurological evidence for SR affecting depressive severity in the MDD patients and proposed potential biomarkers to identify the SR-based risk phenotype of MDD individuals., (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

This study aims to elucidate the neuroimaging changes associated with major depressive disorder (MDD) and their relationship with genetic characteristics. We conducted a global-brain functional connectivity (GFC) and genetic-neuroimaging correlation analysis on 42 MDD patients and 42 healthy controls (HCs), exploring the correlation between GFC abnormalities and clinical variables. Results showed that compared to HCs, MDD patients had significantly decreased GFC values in the bilateral posterior cingulate cortex/precuneus and increased GFC values in the left and right cerebellum Crus I/II. Additionally, a negative correlation was observed between the GFC values of the left cerebellum Crus I/II and subjective support scores, as well as social support revalued scale total scores. We identified genes associated with GFC changes in MDD, which are enriched in biological processes such as synaptic transmission and ion transport. Our findings indicate the presence of abnormal GFC values in severe depression, complementing the pathological research on the condition. Furthermore, this study provides preliminary evidence for the correlation between social support levels and brain functional connectivity, offering insights into the potential association between GFC changes and gene expression in MDD patients.

Background: Major depression disorder (MDD) exhibits a high global incidence; however, its pathogenesis remains elusive. In this prospective study, we employed diffusion kurtosis imaging (DKI) to investigate changes in brain function among patients with MDD both pre- and post-electroconvulsive therapy (ECT)., Methods: We divided a sample of 22 MDD patients into ECT group, which received six treatments over a span of two weeks, and control group (n = 12). DKI scanning was performed before and after treatment. The Hamilton Depression Rating Scale (HAMD) and Life Satisfaction Rating Scale (LSRS) were administered to assess depressive symptoms at baseline, on the 14th day, and at month three., Results: Significant differences were found between group, time and time × group in terms of HAMD score and LSRS score. In the ECT group compared to pre- ECT measurement, changes in mean diffusivity (MD), fractional Anisotropy (FA), mean kurtosis (MK), radial kurtosis (RK), FA of kurtosis (KA), and anxia kurtosis (AK) value were detected in specific regions such as the frontal, temporal lobe, and hippocampus. In the control group only MD and RK value increased in a limited number of area., Conclusions: ECT holds the potential to elicit neuroplasticity in the brain, facilitating rapid structural modifications and amelioration of depressive symptoms in patients with MDD., Competing Interests: Declaration of competing interest No potential conflict of interest was reported by the author(s)., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: Non-suicidal self-injury (NSSI) is an increasingly concerning issue that is linked to a range of mental health problems. However, little is known about the potential neurophysiological mechanisms underlying risk decision-making in Major depressive disorder (MDD) patients with NSSI-the present study aimed to fill this important literature gap., Methods: A total of 81 MDD patients (with NSSI: n = 40, without NSSI: n = 41) and 44 matched healthy controls (HC) underwent a modified version of the Iowa Gambling Task (IGT) while an electroencephalogram was recorded. Feedback-related negativity (FRN) and P300 were examined during the feedback stage of the risky decision-making process., Results: Behavioural findings revealed that individuals diagnosed with MDD displayed a greater tendency to make risky decisions compared to the control group. Furthermore, MDD patients with NSSI demonstrated a significantly more negative ΔFN (i.e., the difference in neural response to losses compared to gains) than those without NSSI. Further, NSSI patients showed a larger difference ΔFN (loss minus gain), which was associated with enhanced impulsivity., Conclusions: Collectively, the findings suggest that there is an altered processing of risky decision-making in the electrophysiology of patients with MDD who engage in NSSI. The ΔFN may serve as a psychophysiological marker indicating risk for NSSI., Competing Interests: Declaration of competing interest All authors disclosed no relevant relationships., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Importance: Antidepressant discontinuation substantially increases the risk of a depression relapse, but the neurobiological mechanisms through which this happens are not known. Amygdala reactivity to negative information is a marker of negative affective processes in depression that is reduced by antidepressant medication, but it is unknown whether amygdala reactivity is sensitive to antidepressant discontinuation or whether any change is related to the risk of relapse after antidepressant discontinuation., Objective: To investigate whether amygdala reactivity to negative facial emotions changes with antidepressant discontinuation and is associated with subsequent relapse., Design, Setting, and Participants: The Antidepressiva Absetzstudie (AIDA) study was a longitudinal, observational study in which adult patients with remitted major depressive disorder (MDD) and currently taking antidepressants underwent 2 task-based functional magnetic resonance imaging (fMRI) measurements of amygdala reactivity. Patients were randomized to discontinuing antidepressants either before or after the second fMRI measurement. Relapse was monitored over a 6-month follow-up period. Study recruitment took place from June 2015 to January 2018. Data were collected between July 1, 2015, and January 31, 2019, and statistical analyses were conducted between June 2021 and December 2023. The study took place in a university setting in Zurich, Switzerland, and Berlin, Germany. Of 123 recruited patients, 83 were included in analyses. Of 66 recruited healthy control individuals matched for age, sex, and education, 53 were included in analyses., Exposure: Discontinuation of antidepressant medication., Outcomes: Task-based fMRI measurement of amygdala reactivity and MDD relapse within 6 months after discontinuation., Results: Among patients with MDD, the mean (SD) age was 35.42 (11.41) years, and 62 (75%) were women. Among control individuals, the mean (SD) age was 33.57 (10.70) years, and 37 (70%) were women. Amygdala reactivity of patients with remitted MDD and taking medication did not initially differ from that of control individuals (t125.136 = 0.33; P = .74). An increase in amygdala reactivity after antidepressant discontinuation was associated with depression relapse (3-way interaction between group [12W (waited) vs 1W2 (discontinued)], time point [MA1 (first scan) vs MA2 (second scan)], and relapse: β, 18.9; 95% CI, 0.8-37.1; P = .04). Amygdala reactivity change was associated with shorter times to relapse (hazard ratio, 1.05; 95% CI, 1.01-1.09; P = .01) and predictive of relapse (leave-one-out cross-validation balanced accuracy, 67%; 95% posterior predictive interval, 53-80; P = .02)., Conclusions and Relevance: An increase in amygdala reactivity was associated with risk of relapse after antidepressant discontinuation and may represent a functional neuroimaging marker that could inform clinical decisions around antidepressant discontinuation.

Objective: To construct a predictive model for the improvement of cognitive function in patients with depressive disorder treated with SNRIs, based on emotional regulation abilities, and to provide personalized treatment for depressed patients., Methods: Clinical data from 170 patients with depressive disorder treated with SNRIs at Tongji Hospital, Shanghai, from December 2017 to May 2023 were collected. Based on whether the MoCA-B total score at 3-6 months post-treatment was at least 2 points higher than at baseline, patients were divided into the cognitive function improved group (n = 80) and the cognitive function not improved group (n = 90). Stepwise logistic regression and LASSO regression were used to select predictive factors, and logistic regression analysis was applied to construct predictive models solely based on emotional regulation abilities, combined with executive functions and HAMD scores. The models were further validated through Bootstrap internal validation, calibration curve plotting, and C-index calculation, and a comparison between the two models was performed., Results: An ER model with an area under the ROC curve of 0.817was established using four emotional regulation ability indicators: the valence of reappraised images, the arousal of negative images, the arousal of neutral images, and the success of reappraisal (arousal). Internal validation using Bootstrap showed a C index of 0.817, and clinical decision curves indicated that this model has a significant net benefit with a probability of improved cognitive function ranging from about 20 to 85%. Additionally, an EREH model including emotional regulation ability, executive function, and HAMD score as predictors was constructed using Lasso and logistic regression methods. This model reached an area under the ROC curve of 0.859and clinical decision curves showed high net benefits with probabilities of improved cognitive function ranging from 10 to 100%. The calibration curves of both models coincided well with the actual curves, with the latter having a higher AUC and significant statistical differences between the two models., Conclusion: This study suggests that emotional regulation ability may serve as a predictor for the improvement of cognitive functions in patients with depression depressive disorder treated with SNRIs. However, it is important to note that there may be other factors not covered or included in this study.The predictive model that includes executive functions and HAMD scores offers better differentiation and consistency and is more feasible in clinical practice., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024. Published by Elsevier Ltd.)

Major depressive disorder (MDD) is a complex mental disorder, potentially linked to the gut-microbiota-brain axis. Probiotics like Lactobacillus plantarum PS128 (PS128) may improve depressive symptoms by modulating the gut microbiota based on our previous open trial. We conducted an 8-week double-blind, placebo-controlled trial to investigate the impact of PS128 on depression severity, markers of inflammation and gut permeability, and the gut microbiota composition in 32 patients with MDD with stable antidepressant treatment but moderate symptom severity. Following the 8-week intervention, both the Hamilton Depression Rating Scale-17 score (HAMD), and Depression and Somatic Symptoms Scale (DSSS) showed a significant decrease in both groups (p<0.001). However, there was no significant difference in the change of depression severity between groups (p=0.203). Moreover, alterations in serum levels of high sensitivity C-reactive protein, interleukin-6, tumor necrosis factor-α, and intestinal fatty acid binding protein, as well as changes in the gut microbiota composition, did not exhibit significant differences before and after intervention or between the groups. In comparison to the placebo group, our study did not find significant effects of PS128 on depressive symptoms, biomarkers of inflammation and gut permeability, and the overall gut microbiota composition. Nonetheless, we observed a potential impact of PS128 on the symbiosis of specific taxa. To comprehensively understand the psychophysiological effects of PS128 in patients with MDD, further research with a larger sample size is imperative., Competing Interests: Declaration of Competing Interest The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Brain functional connectivity has been widely explored to reveal the functional interaction dynamics between the brain regions. However, conventional connectivity measures rely on deterministic models demanding application-specific empirical analysis, while deep learning approaches focus on finding discriminative features for state classification, having limited capability to capture the interpretable connectivity characteristics. To address the challenges, this study proposes a self-supervised triplet network with depth-wise attention (TripletNet-DA) to generate the functional connectivity: 1) TripletNet-DA firstly utilizes channel-wise transformations for temporal data augmentation, where the correlated & uncorrelated sample pairs are constructed for self-supervised training, 2) Channel encoder is designed with a convolution network to extract the deep features, while similarity estimator is employed to generate the similarity pairs and the functional connectivity representations, 3) TripletNet-DA applies Triplet loss with anchor-negative similarity penalty for model training, where the similarities of uncorrelated sample pairs are minimized to enhance model's learning capability. Experimental results on pathological EEG datasets (Autism Spectrum Disorder, Major Depressive Disorder) indicate that 1) TripletNet-DA demonstrates superiority in both ASD discrimination and MDD classification than the state-of-the-art counterparts, where the connectivity features in beta & gamma bands have respectively achieved the accuracy of 97.05%, 98.32% for ASD discrimination, 89.88%, 91.80% for MDD classification in the eyes-closed condition and 90.90%, 92.26% in the eyes-open condition, 2) TripletNet-DA enables to uncover significant differences of functional connectivity between ASD EEG and TD ones, and the prominent connectivity links are in accordance with the empirical findings, thus providing potential biomarkers for clinical ASD analysis.

Background: Major depressive disorder (MDD) is characterized by strong emotional dysregulation. Mechanisms driving the negative affect in depression may be fast processes existing on an unconscious level., Methods: A priming task was conducted using simultaneous electroencephalography-functional magnetic resonance imaging measurement involving presentation of facial expressions (happy, sad, and neutral) to examine the neurophysiological pathway of biased unconscious emotion processing in MDD. Priming prior to a target emotion created unconscious (16.7-ms primer) and conscious (150-ms primer) trials. A large sample (N = 126) was recruited, containing healthy control participants (n = 66; 37 women) and participants with MDD (n = 60; 31 women)., Results: The healthy control group showed a shorter reaction time in happy but not in sad or neutral trials compared with the MDD group. N170 amplitudes were lower in trials with unconscious than conscious primer presentation. N170 amplitudes correlated with cortical (right fusiform gyrus, right middle temporal gyrus, right inferior temporal gyrus, left supplementary motor area, right middle frontal gyrus) and subcortical brain regions (right amygdala). The strength of N170 and brain activity correlation increased when the stimulus was consciously presented. Presented emotions did not affect the correlation of N170 values and brain activity., Conclusions: Our findings show that MDD may exhibit biased emotion regulation abilities at a behavioral and neurophysiological level. Face-sensitive event-related potentials demonstrate a correlation with heightened brain activity in regions associated with both face recognition (fusiform gyrus) and emotion processing (amygdala). These findings are evident in both MDD and healthy control groups, with lower effect sizes in the MDD group indicating reduced emotion recognition and processing abilities., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Psychiatric disorders are a heterogeneous group of mental disorders with abnormal mental or behavioral patterns, which severely distress or disable affected individuals and can have a grave socioeconomic burden. Growing evidence indicates that mitochondrial function plays an important role in developing psychiatric disorders. This review discusses the neuropsychiatric consequences of mitochondrial abnormalities in both animal models and patients. We also discuss recent studies associated with compromised mitochondrial function in various psychiatric disorders, such as schizophrenia (SCZ), major depressive disorder (MD), and bipolar disorders (BD). These studies employ various approaches including postmortem studies, imaging studies, genetic studies, and induced pluripotent stem cells (iPSCs) studies. We also summarize the evidence from animal models and clinical trials to support mitochondrial function as a potential therapeutic target to treat various psychiatric disorders. This review will contribute to furthering our understanding of the metabolic etiology of various psychiatric disorders, and help guide the development of optimal therapies., (Copyright © 2022 Elsevier B.V. All rights reserved.)

While many studies have demonstrated a relationship between depression and cognitive deficits, most have neglected to include measurements of performance validity. This study examined the relationship between depression and cognition after accounting for noncredible performance. Participants were veterans referred for outpatient clinical evaluation. The first set of regression analyses ( N  = 187) included age, sex, and education in Model 1, Beck Depression Inventory-2 (BDI-2) added in Model 2, and pass/failure of Test of Memory Malingering (TOMM) added in Model 3 as predictors of 12 neuropsychological test indices. The second set of analyses ( N  = 559) mirrored the first but with Major Depressive Disorder (MDD) diagnosis in Models 2 and 3. In the first analyses, after including TOMM in the model, only the relationship between BDI-2 and verbal fluency remained significant, but this did not survive a Bonferroni correction. In the second analyses, after including TOMM and Bonferroni correction, MDD diagnosis was a significant predictor only for CVLT-II Short Delay Free Recall. Therefore, the relationship between depression and cognition may not be driven by frank cognitive impairment, but rather by psychological mechanisms, which has implications for addressing depressed individuals' concerns about their cognitive functioning and suggest the value of providing psychoeducation and reassurance.

Background: Functional connectivity has been shown to fluctuate over time. The present study aimed to identifying major depressive disorders (MDD) with dynamic functional connectivity (dFC) from resting-state fMRI data, which would be helpful to produce tools of early depression diagnosis and enhance our understanding of depressive etiology., Methods: The resting-state fMRI data of 178 subjects were collected, including 89 MDD and 89 healthy controls. We propose a spatio-temporal learning and explaining framework for dFC analysis. A yet effective spatio-temporal model is developed to classifying MDD from healthy controls with dFCs. The model is a stacking neural network model, which learns network structure information by a multi-layer perceptron based spatial encoder, and learns time-varying patterns by a Transformer based temporal encoder. We propose to explain the spatio-temporal model with a two-stage explanation method of importance feature extracting and disorder-relevant pattern exploring. The layer-wise relevance propagation (LRP) method is introduced to extract the most relevant input features in the model, and the attention mechanism with LRP is applied to extract the important time steps of dFCs. The disorder-relevant functional connections, brain regions, and brain states in the model are further explored and identified., Results: We achieved the best classification performance in identifying MDD from healthy controls with dFC data. The top important functional connectivity, brain regions, and dynamic states closely related to MDD have been identified., Limitations: The data preprocessing may affect the classification performance of the model, and this study needs further validation in a larger patient population., Conclusions: The experimental results demonstrate that the proposed spatio-temporal model could effectively classify MDD, and uncover structural and temporal patterns of dFCs in depression., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps., Methods: Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABA A (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography., Results: Results revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies., Conclusions: Acute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in μ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Deficient neural activities during emotion regulation have been reported in depression. We sought to conduct a meta-analysis to provide a comprehensive description of these neural alterations during use of emotion regulation strategies among patients with depression, including major depressive disorder (MDD) and bipolar disorder (BD)., Methods: We identified neuroimaging studies of abnormal neural activities during emotion regulation in depression. We extracted the peak coordinates and effect sizes of differences in brain activity between patients and healthy controls. Using seed-based d mapping, we conducted voxel-wise meta-analyses of the neural activation pattern differences between the 2 groups across conditions involving emotion regulation and those where emotion regulation was not needed., Results: We included 33 studies reporting 34 data sets, including 23 involving MDD (571 people with MDD and 578 matched controls) and 11 involving BD (358 people with BD and 369 matched controls). Overall, compared with controls, patients with depression showed hyperactivity in the insula and postcentral gyrus, and hypoactivity in the prefrontal part of the inferior, middle, and superior frontal gyrus, the middle temporal gyrus, and the supplementary motor area. In subgroup analyses, data from patients with MDD and studies focused on decreasing negative emotions or using the emotional strategy of reappraisal reported specific hypoactivity in the middle cerebellar peduncles., Limitations: Given limited studies involving patients with BD, we were unable to detect the common and distinct abnormalities in neural activation between MDD and BD. We did not conduct any meta-regression analyses because of limited information., Conclusion: In this meta-analysis, we identified hyperactivity in brain regions associated with emotional experience and hypoactivity in brain regions associated with cognitive control during emotion regulation among patients with depression, relative to healthy controls. These findings could help indicate a target for future interventions aimed at increasing emotion regulation capacity for patients with depression., Competing Interests: Competing interests:: None declared., (© 2024 CMA Impact Inc. or its licensors.)

The global prevalence of Major Depressive Disorder (MDD) is increasing at an alarming rate, underscoring the urgent need for timely and accurate diagnoses to facilitate effective interventions and treatments. Electroencephalography remains a widely used neuroimaging technique in psychiatry, due to its non-invasive nature and cost-effectiveness. With the rise of computational psychiatry, the integration of EEG with artificial intelligence has yielded remarkable results in diagnosing depression. This review offers a comparative analysis of two predominant methodologies in research: traditional machine learning and deep learning methods. Furthermore, this review addresses key challenges in current research and suggests potential solutions. These insights aim to enhance diagnostic accuracy for depression and also foster further development in the area of computational psychiatry.

Previous research has shown that blood flow abnormalities affect major depressive disorder (MDD) from multiple perspectives. Therefore, this study aims to investigate the relationship between middle cerebral artery (MCA) blood flow velocity parameters and clinical symptom scores (Hamilton Depression Rating Scale [HAMD] and Montgomery-Åsberg Depression Rating Scale [MADRS]) in patients with MDD. We compared the MCA blood flow velocity parameters, including peak systolic velocity (MCA-PSV), end-diastolic velocity (MCA-EDV), and mean velocity (MCA-MV), between 50 MDD patients and 50 control subjects. Additionally, we analyzed the correlation between these parameters and HAMD and MADRS scores. Hemodynamic parameters such as pulsatility index and resistance index were also compared between the 2 groups. MCA-PSV, MCA-EDV, and MCA-MV were significantly lower in MDD patients compared to the control group, while pulsatility index and resistance index were significantly higher. Correlation analysis revealed that MCA-PSV, MCA-EDV, and MCA-MV were significantly negatively correlated with HAMD and MADRS scores in MDD patients, indicating that cerebral blood flow velocity decreases as depressive symptoms worsen. Furthermore, regression analysis confirmed the negative relationship between blood flow velocity parameters and clinical symptom scores. The results of this study suggest that the reduction in cerebral blood flow velocity in MDD patients may be associated with the severity of depressive symptoms. This finding provides new insights into the pathophysiological mechanisms of MDD and offers a potential theoretical basis for developing depression treatment strategies based on cerebral blood flow velocity parameters., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: This study investigates the effects of accelerated high-frequency repetitive transcranial magnetic stimulation (aHF-rTMS), applied to the left dorsolateral prefrontal cortex (DLPFC), on locus coeruleus (LC) functional connectivity in the treatment of refractory medication-resistant major depression (MRD)., Methods: We studied 12 antidepressant-free refractory MRD patients, focusing on how aHF-rTMS affects the LC, a central component of the brain's noradrenergic system and key to mood regulation and stress response., Results: A stronger decrease in LC functional connectivity following aHF-rTMS treatment resulted in better clinical improvement. We observed such LC functional connectivity decreases with several brain regions, including the superior frontal gyrus, precentral gyrus, middle occipital gyrus, and cerebellum. Moreover, our exploratory analyses hint at a possible role for E-field modeling in forecasting clinical outcomes. Additional analyses suggest potential genetic and dopaminergic factors influencing changes in LC functional connectivity in relation to clinical response., Conclusions: The findings of this study underscore the pivotal role of the LC in orchestrating higher cognitive functions through its extensive connections with the prefrontal cortices, facilitating decision-making, influencing attention, and addressing depressive rumination. Additionally, the observed enhancement in LC-(posterior) cerebellar connectivity not only highlights the cerebellum's role in moderating clinical outcomes through noradrenergic system modulation but also suggests its potential as a predictive marker for aHF-rTMS efficacy. These results reveal new insights into the neural mechanisms of refractory depression and suggest therapeutic targets for enhancing noradrenergic activity, thereby addressing both cognitive and psychomotor symptoms associated with the disorder.

Previous studies have found alterations in the local regional homogeneity of brain activity in individuals diagnosed with major depressive disorder. However, many studies have failed to consider that even during resting states, brain activity is dynamic and time-varying. The lack of investigation into the dynamic regional homogeneity has hindered the discovery of biomarkers for depression. This study aimed to assess the utility of the dynamic regional homogeneity by a machine learning model (support vector machine). Sixty-five individuals with dynamic regional homogeneity and 57 healthy controls participated in resting-state functional magnetic resonance rescanning and scale estimating. The dynamic regional homogeneity and receiver operating characteristic curve methods were used for analysis of the imaging data. Relative to healthy controls, major depressive disorder patients displayed increased dynamic regional homogeneity values in the left precuneus and right postcentral gyrus. Additionally, receiver operating characteristic curve results of the dynamic regional homogeneity values in the left precuneus and right postcentral gyrus could distinguish major depressive disorder patients from healthy controls; furthermore, changes in the dynamic regional homogeneity were correlated with depression severity., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Major depressive disorder (MDD) is progressively recognized as a stress-related disorder characterized by aberrant brain network dynamics, encompassing both structural and functional domains. Yet, the intricate interplay between these dynamic networks and their molecular underpinnings remains predominantly unexplored., Methods: Both structural and functional networks were constructed using multimodal neuroimaging data from 183 MDD patients and 300 age- and gender-matched healthy controls (HC). structural-functional connectivity (SC-FC) coupling was evaluated at both the connectome- and nodal-levels. Methylation data of five HPA axis key genes, including NR3C1, FKBP5, CRHBP, CRHR1, and CRHR2, were analyzed using Illumina Infinium Methylation EPIC BeadChip., Results: We observed a significant reduction in SC-FC coupling at the connectome-level in patients with MDD compared to HC. At the nodal level, we found an imbalance in SC-FC coupling, with reduced coupling in cortical regions and increased coupling in subcortical regions. Furthermore, we identified 23 differentially methylated CpG sites on the HPA axis, following adjustment for multiple comparisons and control of age, gender, and medication status. Notably, three CpG sites on NR3C1 (cg01294526, cg19457823, and cg23430507), one CpG site on FKBP5 (cg25563198), one CpG site on CRHR1 (cg26656751), and one CpG site on CRHR2 (cg18351440) exhibited significant associations with SC-FC coupling in MDD patients., Conclusions: These findings provide valuable insights into the connection between micro-scale epigenetic changes in the HPA axis and SC-FC coupling at macro-scale connectomes. They unveil the mechanisms underlying increased susceptibility to MDD resulting from chronic stress and may suggest potential pharmacological targets within the HPA-axis for MDD treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background and Objective: Repetitive transcranial magnetic stimulation (rTMS) is a safe and effective treatment for major depressive disorder (MDD); however, this treatment currently lacks reliable biomarkers of treatment response. TMS-evoked potentials (TEPs), measured using TMS-electroencephalography (TMS-EEG), have been suggested as potential biomarker candidates, with the N100 peak being one of the most promising. This study investigated the association between baseline N100 amplitude and 1 Hz right dorsolateral prefrontal cortex (R-DLPFC) accelerated rTMS (arTMS) treatment in MDD., Methods: Baseline TMS-EEG sessions were performed for 23 MDD patients. All patients then underwent 40 sessions of 1 Hz R-DLPFC (F4) arTMS over 5 days and a follow-up TMS-EEG session one week after the end of theses arTMS sessions., Results: Baseline N100 amplitude at F4 showed a strong positive association (p < .001) with treatment outcome. The association between the change in N100 amplitude (baseline to follow-up) and treatment outcome did not remain significant after Bonferroni correction (p = .06, corrected; p = .03, uncorrected). Furthermore, treatment responders had a significantly larger mean baseline F4 TEP amplitude during the N100 time frame compared to non-responders (p < .001). Topographically, after Bonferroni correction, F4 is the only electrode at which its baseline N100 amplitude showed a significant positive association (p < .001) with treatment outcome., Limitations: Lack of control group and auditory masking., Conclusion: Baseline N100 amplitude showed a strong association with treatment outcome and thus demonstrated great potential to be utilized as a cost-effective and widely adoptable biomarker of rTMS treatment in MDD., Competing Interests: Declaration of competing interest JZS, FMazza, DM, FMansouri, TR, RZ, MH, LF, HV, EBA do not report any conflict of interest. DMB receives research support from CIHR, NIH, Brain Canada and the Temerty Family through the CAMH Foundation and the Campbell Research Institute. He received research support and in-kind equipment support for an investigator-initiated study from Brainsway Ltd. and he has been the site principal investigator for sponsor-initiated studies for Brainsway Ltd. He also receives in-kind equipment support from Magventure for investigator-initiated studies. He received medication supplies for an investigator-initiated trial from Indivior. ZJD has received research and equipment in-kind support for an investigator-initiated study through Brainsway Inc. and Magventure Inc. His work has been supported by the Canadian Institutes of Health Research (CIHR), the National Institute of Mental Health (NIMH), Brain Canada and the Temerty Family and Grant Family and through the Centre for Addiction and Mental Health (CAMH) Foundation and the Campbell Institute. JD has received research support from the Arrell Family Foundation, the Buchan Family Foundation, Brain Canada, the Canadian Biomarker Integration Network in Depression, the Canadian Institutes of Health Research (CIHR), the Klarman Family Foundation, NIH, the Ontario Brain Institute, the Toronto General and Western Hospital Foundation, and the Weston Family Foundation; he has received travel stipends from Lundbeck and ANT Neuro; he has served as an advisor for BrainCheck, Restorative Brain Clinics, and TMS Neuro Solutions, holds equity in Arc Health Partners, and is a co-founder of Ampa. JPM reports research support from the Brain & Behavior Research Foundation (BBRF), the Réseau Québécois sur le Suicide, les troubles de l'Humeur et les troubles Associés (RQSHA), the Canadian Research Initiative in Substance Misuse (CRISM), the Fonds de Recherche du Québec - Santé (FRQS), the Branch Out Neurological Foundation, and the Canadian Institutes of Health Research (CIHR). JDG has received research support from the Labatt Family Network, the CAMH Discovery Fund, the University of Toronto EMHSeed program, and the Tri-Council Canada-UK AI Initiative., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Anhedonia is a core symptom of depression that is closely related to prognosis and treatment outcomes. However, accurate and efficient treatments for anhedonia are lacking, mandating a deeper understanding of the underlying mechanisms., Methods: A total of 303 patients diagnosed with depression and anhedonia were assessed by the Snaith-Hamilton Pleasure Scale (SHAPS) and magnetic resonance imaging (MRI). The patients were categorized into a low-anhedonia group and a high-anhedonia group using the K-means algorithm. A data-driven approach was used to explore the differences in brain structure and function with different degrees of anhedonia based on MATLAB. A random forest model was used exploratorily to test the predictive ability of differences in brain structure and function on anhedonia in depression., Results: Structural and functional differences were apparent in several brain regions of patients with depression and high-level anhedonia, including in the temporal lobe, paracingulate gyrus, superior frontal gyrus, inferior occipital gyrus, right insular gyrus, and superior parietal lobule. And changes in these brain regions were significantly correlated with scores of SHAPS., Conclusions: These brain regions may be useful as biomarkers that provide a more objective assessment of anhedonia in depression, laying the foundation for precision medicine in this treatment-resistant, relatively poor prognosis group., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Previous studies have shown a lower hemodynamic response in patients with major depressive disorder (MDD) during cognitive tasks. However, the mechanism underlying impaired hemodynamic and neural responses to cognitive tasks in MDD patients remains unclear. Succinate dehydrogenase (SDH) is a key biomarker of mitochondrial energy generation, and it can affect the hemodynamic response via the neurovascular coupling effect. In the current study, cerebral hemodynamic responses were detected during verbal fluency tasks (VFTs) via functional near-infrared spectroscopy (fNIRS) and SDH protein levels were examined in serum from MDD patients to quickly identify whether these hemodynamic alterations were related to mitochondrial energy metabolism., Methods: Fifty patients with first-episode drug-naïve MDD and 42 healthy controls (HCs) were recruited according to inclusion and exclusion criteria. The 17-item Hamilton Depression Rating Scale (17-HDRS), Hamilton Anxiety Rating Scale (HAMA) and Inventory of Depressive Symptomatology-Self Report (IDS-SR) were used to assess the clinical symptoms of the patients. All participants underwent fNIRS measurements to evaluate cerebral hemodynamic responses in the frontal and temporal cortex during VFTs; moreover, SDH protein levels were measured using an enzyme-linked immunosorbent assay., Results: Activation in the frontal-temporal brain region during the VFTs was lower in patients with MDD than in HCs. The SDH level in the serum of MDD patients was also significantly lower than that in HCs (p = 0.003), which significantly affected right lateral frontal (p = 0.025) and right temporal (p = 0.022) lobe activation. Both attenuated frontal-temporal activation during the VFTs (OR = 1.531) and lower SDH levels (OR = 1.038) were risk factors for MDD., Conclusions: MDD patients had lower cerebral hemodynamic responses to VFTs; this was associated with mitochondrial dysfunction, as indicated by SDH protein levels. Furthermore, attenuated hemodynamic responses in frontotemporal regions and lower SDH levels increased the risk for MDD., Limitations: The sample size is relatively small. SDH protein levels in peripheral blood may not necessarily reflect mitochondrial energy generation in the central nervous system., Competing Interests: Declaration of competing interest The authors have no conflicts of interest in connection with this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Major depressive disorder (MDD) is a form of glial cell-based synaptic dysfunction disease in which glial cells interact closely with neuronal synapses and perform synaptic information processing. Glial cells, particularly astrocytes, are active components of the brain and are responsible for synaptic activity through the release gliotransmitters. A reduced density of astrocytes and astrocyte dysfunction have both been identified the brains of patients with MDD. Furthermore, gliotransmission, i.e., active information transfer mediated by gliotransmitters between astrocytes and neurons, is thought to be involved in the pathogenesis of MDD. However, the mechanism by which astrocyte-mediated gliotransmission contributes to depression remains unknown. This review therefore summarizes the alterations in astrocytes in MDD, including astrocyte marker, connexin 43 (Cx43) expression, Cx43 gap junctions, and Cx43 hemichannels, and describes the regulatory mechanisms of astrocytes involved in synaptic plasticity. Additionally, we investigate the mechanisms acting of the glutamatergic, gamma-aminobutyric acidergic, and purinergic systems that modulate synaptic function and the antidepressant mechanisms of the related receptor antagonists. Further, we summarize the roles of glutamate, gamma-aminobutyric acid, d-serine, and adenosine triphosphate in depression, providing a basis for the identification of diagnostic and therapeutic targets for MDD., Competing Interests: Declaration of competing interest The authors have no conflict of interest to declare., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Changes in sleep and circadian function are leading candidate markers for the detection of relapse in Major Depressive Disorder (MDD). Consumer-grade wearable devices may enable remote and real-time examination of dynamic changes in sleep. Fitbit data from individuals with recurrent MDD were used to describe the longitudinal effects of sleep duration, quality, and regularity on subsequent depression relapse and severity., Methods: Data were collected as part of a longitudinal observational mobile Health (mHealth) cohort study in people with recurrent MDD. Participants wore a Fitbit device and completed regular outcome assessments via email for a median follow-up of 541 days. We used multivariable regression models to test the effects of sleep features on depression outcomes. We considered respondents with at least one assessment of relapse (n = 218) or at least one assessment of depression severity (n = 393)., Results: Increased intra-individual variability in total sleep time, greater sleep fragmentation, lower sleep efficiency, and more variable sleep midpoints were associated with worse depression outcomes. Adjusted Population Attributable Fractions suggested that an intervention to increase sleep consistency in adults with MDD could reduce the population risk for depression relapse by up to 22 %., Limitations: Limitations include a potentially underpowered primary outcome due to the smaller number of relapses identified than expected., Conclusion: Our study demonstrates a role for consumer-grade activity trackers in estimating relapse risk and depression severity in people with recurrent MDD. Variability in sleep duration and midpoint may be useful targets for stratified interventions., Competing Interests: Declaration of competing interest HE was a full-time employee of H. Lundbeck A/S and held stock and stock options in H. Lundbeck A/S at the time of study conduct. QL, SV and VN were employees of Janssen Research & Development, LLC and held company stocks/stock options at the time of study conduct. JMH has received economic compensation for participating in advisory boards or giving educational lectures from Eli Lilly & Co, Sanofi, Lundbeck, and Otsuka. No other authors have competing interests to declare., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Current pharmacological agents for depression have limited efficacy in achieving remission. Developing and validating new medications is challenging due to limited biological targets. This study aimed to link electrophysiological data and symptom improvement to better understand mechanisms underlying treatment response. Longitudinal changes in neural oscillations were assessed using resting-state electroencephalography (EEG) data from two Canadian Biomarker Integration Network in Depression studies, involving pharmacological and cognitive behavioral therapy (CBT) trials. Patients in the pharmacological trial received eight weeks of escitalopram, with treatment response defined as ≥ 50% decrease in Montgomery-Åsberg Depression Rating Scale (MADRS). Early (baseline to week 2) and late (baseline to week 8) changes in neural oscillation were investigated using relative power spectral measures. An association was found between an initial increase in theta and symptom improvement after 2 weeks. Additionally, late increases in delta and theta, along with a decrease in alpha, were linked to a reduction in MADRS after 8 weeks. These late changes were specifically observed in responders. To assess specificity, we extended our analysis to the independent CBT cohort. Responders exhibited an increase in delta and a decrease in alpha after 2 weeks. Furthermore, a late (baseline to week 16) decrease in alpha was associated with symptom improvement following CBT. Results suggest a common late decrease in alpha across both treatments, while modulatory effects in theta may be specific to escitalopram treatment. This study offers insights into electrophysiological markers indicating a favorable response to antidepressants, enhancing our comprehension of treatment response mechanisms in depression., (© 2024. The Author(s).)

Mental disorders present challenges in diagnosis and treatment due to their complex and heterogeneous nature. Electroencephalogram (EEG) has shown promise as a source of potential biomarkers for these disorders. However, existing methods for analyzing EEG signals have limitations in addressing heterogeneity and capturing complex brain activity patterns between regions. This paper proposes a novel random effects state-space model (RESSM) for analyzing large-scale multi-channel resting-state EEG signals, accounting for the heterogeneity of brain connectivities between groups and individual subjects. We incorporate multi-level random effects for temporal dynamical and spatial mapping matrices and address non-stationarity so that the brain connectivity patterns can vary over time. The model is fitted under a Bayesian hierarchical model framework coupled with a Gibbs sampler. Compared to previous mixed-effects state-space models, we directly model high-dimensional random effects matrices of interest without structural constraints and tackle the challenge of identifiability. Through extensive simulation studies, we demonstrate that our approach yields valid estimation and inference. We apply RESSM to a multi-site clinical trial of major depressive disorder (MDD). Our analysis uncovers significant differences in resting-state brain temporal dynamics among MDD patients compared to healthy individuals. In addition, we show the subject-level EEG features derived from RESSM exhibit a superior predictive value for the heterogeneous treatment effect compared to the EEG frequency band power, suggesting the potential of EEG as a valuable biomarker for MDD., (© The Author(s) 2024. Published by Oxford University Press on behalf of The International Biometric Society.)

Alterations in structural-functional (SC-FC) coupling have been linked to major depressive disorder (MDD). A newly developed algorithm for regional-specific SC-FC coupling analysis shows potential in advancing psychiatric research. In this study, we calculated the gray matter regional-specific SC-FC coupling of 114 MDD patients and 131 healthy controls (HCs). The delayed matching to sample (DMS) and Pattern Recognition Memory (PRM) subtests of the computerized Cambridge Neurocognitive Test Automated Battery (CANTAB) were used to evaluate visual memory. We found that the Xgboost model exhibited robust discriminative performance (Area under the ROC curve [95% CI]: 0.75 [0.65 to 0.85], Accuracy [95% CI]: 0.73 [0.63 to 0.84], Sensitivity [95% CI]: 0.65 [0.53 to 0.76], Specificity [95% CI]: 0.82 [0.77 to 0.87]). MDD patients showed lower SC-FC coupling in the left inferior frontal orbital gyrus (IFGorb&#95;L) and the right inferior occipital gyrus (IOG&#95;R) and higher SC-FC coupling in the left superior temporal pole (TPOsup&#95;L) and the right middle temporal pole (TPOmid&#95;R) than HCs. SC-FC coupling of IFGorb&#95;L negatively correlated with current duration of illness (r = -0.26, P = 0.007), IOG&#95;R negatively correlated with HAMD-17 cognitive factor score (r = -0.24, P = 0.011), while TPOsup&#95;L positively correlated with percent correct in PRM delayed task among MDD patients (r = 0.31, P = 0.003). In conclusion, the study suggested that altered regional SC-FC coupling may be involved in MDD pathophysiology and associated with visual memory impairment., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Cognitive impairment is prevalent across neuropsychiatric disorders but there is a lack of treatment strategies with robust, enduring effects. Emerging evidence indicates that altitude-like hypoxia cognition training may induce long-lasting neuroplasticity and improve cognition. We will investigate whether repeated cognition training under normobaric hypoxia can improve cognitive functions in healthy individuals and patients with affective disorders and the neurobiological underpinnings of such effects., Methods: In sub-study 1, 120 healthy participants are randomized to one of four treatment arms in a double-blind manner, allowing for examination of separate and combined effects of three-week repeated moderate hypoxia and cognitive training, respectively. In sub-study 2, 60 remitted patients with major depressive disorder or bipolar disorder are randomized to hypoxia with cognition training or treatment as usual. Assessments of cognition, psychosocial functioning, and quality of life are performed at baseline, end-of-treatment, and at 1-month follow-up. Functional magnetic resonance imaging (fMRI) scans are conducted at baseline and 1-month follow-up, and [ 11 C]UCB-J positron emission tomography (PET) scans are performed at end-of-treatment to quantify the synaptic vesicle glycoprotein 2A (SV2A). The primary outcome is a cognitive composite score of attention, verbal memory, and executive functions. Statistical power of ≥ 80% is reached to detect a clinically relevant between-group difference with minimum n = 26 per treatment arm. Behavioral data are analyzed with an intention-to-treat approach using mixed models. fMRI data is analyzed with the FMRIB Software Library, while PET data is quantified using the simplified reference tissue model (SRTM) with centrum semiovale as reference region., Discussion: The results will provide novel insights into whether repeated hypoxia cognition training increases cognition and brain plasticity, which can aid future treatment development strategies., Trial Registration: ClinicalTrials.gov, NCT06121206 . Registered on 31 October 2023., (© 2024. The Author(s).)

Introduction: Poor quality sleep has often been cited as a cause of lowered quality of life in patients with affective disorders such as major depressive disorder (MDD) and generalized anxiety disorder (GAD). As sleep and affective disorders are affected by multi-network interactions, we hypothesize that the modulation of the central executive network (CEN), salience, and default mode networks (DMNs) through individualized repetitive transcranial magnetic stimulation (rTMS) may improve sleep and quality of life., Methods: A retrospective analysis from 2020 to 2023 was conducted in patients with affective disorders at Cingulum Health. Multiple targets were selected based on anomalies detected from individual, functional connectivity networks from a machine-learning connectivity software. rTMS was conducted with accelerated continuous or intermittent theta burst stimulation (TBS) based on the anomaly detected. Pittsburgh Sleep Quality Index (PSQI), EuroQol (EQ5D), Beck's Depression Inventory (BDI), and the General Anxiety Disorder-7 (GAD-7) questionnaires were administered prior to, after, and at follow-up of rTMS., Results: Twenty-seven patients were identified, and the most common diagnoses were MDD (41%) or MDD with GAD (41%). All patients had at least one rTMS target in the CEN. The most common target (19 patients) was L8Av in the dorsolateral prefrontal cortex (dlPFC). Patients experienced significant improvements in sleep, quality of life, depressive, and anxiety symptoms after rTMS and during follow-up. Improvements in sleep correlated with quality of life at follow-up., Conclusion: This study suggests that personalized, parcel-guided rTMS is safe and may provide sustained improvements in sleep, quality of life, and affective symptoms for patients with affective disorders., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Aim: This cross-sectional study aims to identify the characteristic changes of prefrontal and motor areas during a tai chi chuan task in patients with Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) using wearable functional near-infrared spectroscopy (fNIRS)., Methods: Three parallel groups (T2DM with DD group, T2DM group, and healthy group) were recruited from December 10, 2022, to May 31, 2023. Participants in three groups conducted a motor task of tai chi chuan designed by Eprime 3.0, and fNIRS was used to monitor the brain activation, functional connectivity (FC), and lateralization of prefrontal and motor areas. Correlation analyses were performed to examine the relationship between depressive symptoms and the function of prefrontal and motor areas., Results: Ninety elder adults (aged ≥ 60), including 30 patients with T2DM and MDD, 30 patients with T2DM, and 30 healthy subjects, were enrolled. In contrast with the patients with T2DM and healthy subjects, the patients with T2DM and MDD had decreased activation and abnormal lateralization in prefrontal and motor areas and decreased FC among supplementary motor area, motor area, and dorsolateral prefrontal cortex (DLPFC). Furthermore, the oxyhemoglobin (HbO 2 ) concentration value of DLPFC in patients with T2DM and MDD was negatively associated with scores of Hamilton Depression Scale-24 (HAMD-24)., Conclusions: Patients with T2DM and MDD had characteristic functional changes in prefrontal and motor areas. DLPFC may be a potential target of diagnosis and intervention for patients with T2DM and MDD., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

Introduction: Although major depression is the disorder most frequently associated with suicidal behavior, it is unclear that major depressive disorder patients may develop suicidal ideation. Basic affective system theory may provide a novel and beneficial viewpoint in this field. The goal of this study was to investigate the basic affective system in relation to suicidal ideation in individuals with depression., Method: The study population comprised 160 participants who had been formally diagnosed with major depressive disorder. Participants were divided into two groups according to whether they had suicide ideation (depression with suicide [DS]) (N = 93) or not (depression with no suicidal ideation [DNS]) (N = 67). The Beck Depression Inventory (BDI), the Suicide Probability Scale (SPS), the Beck Hopelessness Scale (BHS), and the Affective Neuroscience Personality Scale (ANPS) were applied. Statistical Product and Service Solutions (SPSS) 24 and the SPSS macroprocess, which were specifically developed for assessing complex models including serial mediators, were used to analyze the data., Results: The mean age of all participants was 31.1 ± 11 years, and most of them were female (65%). The DS group had a higher family history of psychiatric medication use and suicidal attempts. In addition, BDI, BHS, and SPS total scores were higher, as well as ANGER subscale scores were higher in the DS group. In mediation analysis, the ANGER subscale significantly predicted the presence of suicide ideation. We observed a direct effect of the ANGER subscale score on suicide ideation as well as an indirect effect of the ANGER subscale score on suicidal ideation via depression severity., Conclusion: Higher scores on ANGER are associated with suicidal ideation. Neurobiological correlates, including the ANGER system, may be promising in understanding suicidal behaviors., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)

This study investigated how resting-state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC) predicts antidepressant response in patients with major depressive disorder (MDD). Eighty-seven medication-free MDD patients underwent baseline resting-state functional MRI scans. After 12 weeks of escitalopram treatment, patients were classified into remission depression (RD, n = 42) and nonremission depression (NRD, n = 45) groups. We conducted two analyses: a voxel-wise rsFC analysis using sgACC as a seed to identify group differences, and a prediction model based on the sgACC rsFC map to predict treatment efficacy. Haufe transformation was used to interpret the predictive rsFC features. The RD group showed significantly higher rsFC between the sgACC and regions in the fronto-parietal network (FPN), including the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral inferior parietal lobule (IPL), compared to the NRD group. These sgACC rsFC measures correlated positively with symptom improvement. Baseline sgACC rsFC also significantly predicted treatment response after 12 weeks, with a mean accuracy of 72.64% (p < 0.001), mean area under the curve of 0.74 (p < 0.001), mean specificity of 0.82, and mean sensitivity of 0.70 in 10-fold cross-validation. The predictive voxels were mainly within the FPN. The rsFC between the sgACC and FPN is a valuable predictor of antidepressant response in MDD patients. These findings enhance our understanding of the neurobiological mechanisms underlying treatment response and could help inform personalized treatment strategies for MDD., (© 2024. The Author(s).)

Functional magnetic resonance imaging (fMRI) is currently one of the most popular technologies for measuring brain activity in both research and clinical contexts. However, clinical constraints often result in short fMRI scan durations, limiting the diagnostic performance for brain disorders. To address this limitation, we developed an end-to-end frequency-specific dual-attention-based adversarial network (FDAA-Net) to extend the time series of existing blood oxygen level-dependent (BOLD) data, enhancing their diagnostic utility. Our approach leverages the frequency-dependent nature of fMRI signals using variational mode decomposition (VMD), which adaptively tracks brain activity across different frequency bands. We integrated the generative adversarial network (GAN) with a spatial-temporal attention mechanism to fully capture relationships among spatially distributed brain regions and temporally continuous time windows. We also introduced a novel loss function to estimate the upward and downward trends of each frequency component. We validated FDAA-Net on the Human Connectome Project (HCP) database by comparing the original and predicted time series of brain regions in the default mode network (DMN), a key network activated during rest. FDAA-Net effectively overcame linear frequency-specific challenges and outperformed other popular prediction models. Test-retest reliability experiments demonstrated high consistency between the functional connectivity of predicted outcomes and targets. Furthermore, we examined the clinical applicability of FDAA-Net using short-term fMRI data from individuals with autism spectrum disorder (ASD) and major depressive disorder (MDD). The model achieved a maximum predicted sequence length of 40% of the original scan durations. The prolonged time series improved diagnostic performance by 8.0% for ASD and 11.3% for MDD compared with the original sequences. These findings highlight the potential of fMRI time series prediction to enhance diagnostic power of brain disorders in short fMRI scans., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Background: Inhibitory control function and proinflammatory cytokines play a role in the pathomechanisms underlying major affective disorders and suicidal behavior. However, the distinct or interactive effects of major affective disorders and suicidal symptom severity on inhibitory control function and proinflammatory cytokines remain unclear., Methods: This study included 287 patients with bipolar disorder, 344 with major depressive disorder, and 169 healthy controls. We categorized the participants into 3 groups based on Montgomery-Åsberg Depression Rating Scale (MADRS) item 10 (suicidal symptoms) score: 0, 2 or 3, and ≥4. The participants completed the go/no-go task and the measurements for C-reactive protein (CRP) and tumor necrosis factor-α (TNF-α) levels., Results: Errors in the go/no-go task were associated with suicidality (P = .040), regardless of the severity of suicidal symptoms and diagnosis. An elevated CRP level was especially associated with a Montgomery-Åsberg Depression Rating Scale item 10 score ≥4 (P = .001). An increased TNF-α level could distinguish bipolar disorder from major depressive disorder (P < .001)., Discussion: Our study indicated the distinct effects of major affective disorder diagnosis and suicide symptom severity on inhibitory control function and CRP and TNF-α levels. Importantly, individuals with the poorest inhibitory control function and highest CRP levels had more severe suicidal symptoms., (© The Author(s) 2024. Published by Oxford University Press on behalf of CINP.)

Major depressive disorder (MDD) is characterized by psychomotor retardation whose underlying neural source remains unclear. Psychomotor retardation may either be related to a motor source like the motor cortex or, alternatively, to a psychomotor source with neural changes outside motor regions, like input regions such as visual cortex. These two alternative hypotheses in main (n = 41) and replication (n = 18) MDD samples using 7 Tesla MRI are investigated. Analyzing both global and local connectivity in primary motor cortex (BA4), motor network and middle temporal visual cortex complex (MT+), the main findings in MDD are: 1) Reduced local and global synchronization and increased local-to-global output in motor regions, which do not correlate with psychomotor retardation, though. 2) Reduced local-to-local BA4 - MT+ functional connectivity (FC) which correlates with psychomotor retardation. 3) Reduced global synchronization and increased local-to-global output in MT+ which relate to psychomotor retardation. 4) Reduced variability in the psychophysical measures of MT+ based motion perception which relates to psychomotor retardation. Together, it is shown that visual cortex MT+ and its relation to motor cortex play a key role in mediating psychomotor retardation. This supports psychomotor over motor hypothesis about the neural source of psychomotor retardation in MDD., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background: Major Depressive Disorder (MDD), as a chronic mental disorder, causes changes in mood, thoughts, and behavior. The pathophysiology of the disorder and its treatment are still unknown. One of the most notable changes observed in patients with MDD through fMRI is abnormal functional brain connectivity., Methods: Preprocessed data from 60 MDD patients and 60 normal controls (NCs) were selected, which has been performed using the DPARSF toolbox. The whole-brain functional networks and topologies were extracted using graph theory-based methods. A two-sample, two-tailed t-test was used to compare the topological features of functional brain networks between the MDD and NCs groups using the DPABI-Net/Statistical Analysis toolbox., Results: The obtained results showed a decrease in both global and local efficiency in MDD patients compared to NCs, and specifically, MDD patients showed significantly higher path length values. Acceptable p-values were obtained with a small sample size and less computational volume compared to the other studies on large datasets. At the node level, MDD patients showed decreased and relatively decreased node degrees in the sensorimotor network (SMN) and the dorsal attention network (DAN), respectively, as well as decreased node efficiency in the SMN, default mode network (DMN), and DAN. Also, MDD patients showed slightly decreased node efficiency in the visual networks (VN) and the ventral attention network (VAN), which were reported after FDR correction with Q < 0.05., Limitations: All participants were Chinese., Conclusions: Collectively, increased path length, decreased global and local efficiency, and also decreased nodal degree and efficiency in the SMN, DAN, DAN, VN, and VAN were found in patients compared to NCs., Competing Interests: Declaration of competing interest The authors have no competing interests to declare that are relevant to the content of this article., (Copyright © 2024. Published by Elsevier B.V.)

Whether proinflammatory cytokine dysregulation and cognitive dysfunction are associated with suicidal symptoms in adolescents and young adults with major depressive disorder (MDD) remains uncertain. We assessed the cognitive function and proinflammatory cytokine levels of 43 and 51 patients aged 15-29 years with MDD and severe and mild suicidal symptoms, respectively, as well as those of 85 age- and sex-matched healthy controls. Specifically, we measured serum levels of C-reactive protein, tumor necrosis factor-α (TNF-α), interleukin-2, and interleukin-6 and assessed cognitive function by using working memory and go/no-go tasks. The severity of the patients' suicidal symptoms was based on Item 10 of the Montgomery-Åsberg Depression Rating Scale; scores of ≤ 2 and ≥ 4 indicated mild and severe symptoms, respectively. The patients with MDD and severe suicidal symptoms had higher levels of C-reactive protein (p = .019) and TNF-α (p = .002) than did the patients with mild symptoms or the healthy controls. The number of errors committed on the go/no-go by patients with MDD and severe suicidal symptoms (p = .001) was significantly higher than those by patients with MDD and mild symptoms or by controls. After adjusting for nonsuicidal depressive symptoms, we observed suicidal symptoms to be positively associated with TNF-α levels (p = .050) and errors on the go/no-go task (p = .021). Compared with mild suicidal symptoms, severe symptoms are associated with greater serum levels of proinflammatory cytokines and inferior cognitive function in adolescents and young adults with MDD., (© 2024. The Author(s).)

Depression is a complex mood disorder with multifactorial etiology and is also the most frequent non-motor symptom of Parkinson's disease. Emerging research suggests a potential link between mitochondrial dysfunction and the pathophysiology of major depressive disorder. By synthesizing current knowledge and research findings, this review sheds light on the intricate relationship between Parkin, a protein classically associated with Parkinson's disease, and mitochondrial quality control mechanisms (e.g., mitophagy, mitochondrial biogenesis, and mitochondrial dynamic), specifically focusing on their relevance in the context of depression. Additionally, the present review discusses therapeutic strategies targeting Parkin-medicated mitophagy and calls for further research in this field. These findings suggest promise for the development of novel depression treatments through modulating Parkin-mediated mitophagy., Competing Interests: Declaration of competing interest The authors have no conflict of interest to declare., (Copyright © 2024 Elsevier Ltd. All rights reserved.)