Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients.

BACKGROUND: Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients. METHODS: The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands. RESULTS: Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups. CONCLUSIONS: Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

Relationship between cognitive function and functional outcomes in remitted major depression.

BACKGROUND: Few studies have focused on functional impairment in depressed patients during symptomatic remission. The exact relationship between cognitive performance and functional outcomes of patients with Major depressive disorder (MDD) remains unclear. METHODS: Participants diagnosed with MDD were included and interviewed at both baseline and follow-up. Cognitive function was assessed during acute episodes using the Cambridge Neuropsychological Test Automated Battery (CANTAB), which targeted attention (Rapid Visual Processing - RVP), visual memory (Pattern Recognition Memory - PRM), and executive function (Intra-Extra Dimensional Set Shift - IED). The 17-item Hamilton Depression Scale (HAMD) was used for symptom assessment. Participants were divided into two groups based on their SDSS (Social Disability Screening Schedule) scores, and the differences between their demographic information, HAMD scores, and baseline CANTAB test results were compared. Logistic regression analysis was used to identify cognitive predictors of social function during symptomatic remission. RESULTS: According to the SDSS score at follow-up, 103 patients were divided into the normal social function group (n = 81,78.6%) and the poor social function group (n = 22, 21.4%) during clinical remission. Participants with poorer social function performed worse in the visual memory (PRM) and executive function tests (IED) at the baseline. Logistic regression analysis suggested that performance on the PRM (95%CI = 0.31-0.93, p = 0.030) and IED (95%CI = 1.01-1.13, p = 0.014) tests, instead of less severe symptoms, significantly contributed to functional outcomes. CONCLUSION: Better performance in visual memory and executive function during acute episodes may predict better social functional outcomes in individuals with MDD. A potential early intervention to improve social function in individuals with MDD could include the treatments for executive function and visual memory.

Functional connectivity of the amygdala subregions and the antidepressant effects of repeated ketamine infusions in major depressive disorder.

BACKGROUND: Amygdala subregion-based network dysfunction has been determined to be centrally implicated in major depressive disorder (MDD). Little is known about whether ketamine modulates amygdala subarea-related networks. We aimed to investigate the relationships between changes in the resting-state functional connectivity (RSFC) of amygdala subregions and ketamine treatment and to identify important neuroimaging predictors of treatment outcomes. METHODS: Thirty-nine MDD patients received six doses of ketamine (0.5 mg/kg). Depressive symptoms were assessed, and magnetic resonance imaging (MRI) scans were performed before and after treatment. Forty-five healthy controls underwent one MRI scan. Seed-to-voxel RSFC analyses were performed on the amygdala subregions, including the centromedial amygdala (CMA), laterobasal amygdala (LBA), and superficial amygdala subregions. RESULTS: Abnormal RSFC between the left LBA and the left precuneus in MDD patients is related to the therapeutic efficacy of ketamine. There were significant differences in changes in bilateral CMA RSFC with the left orbital part superior frontal gyrus and in changes in the left LBA with the right middle frontal gyrus between responders and nonresponders following ketamine treatment. Moreover, there was a difference in the RSFC of left LBA and the right superior temporal gyrus/middle temporal gyrus (STG/MTG) between responders and nonresponders at baseline, which could predict the antidepressant effect of ketamine on Day 13. CONCLUSIONS: The mechanism by which ketamine improves depressive symptoms may be related to its regulation of RSFC in the amygdala subregion. The RSFC between the left LBA and right STG/MTG may predict the response to the antidepressant effect of ketamine.

Towards precision in the diagnostic profiling of patients: leveraging symptom dynamics as a clinical characterisation dimension in the assessment of major depressive disorder.

BACKGROUND: International guidelines present overall symptom severity as the key dimension for clinical characterisation of major depressive disorder (MDD). However, differences may reside within severity levels related to how symptoms interact in an individual patient, called symptom dynamics. AIMS: To investigate these individual differences by estimating the proportion of patients that display differences in their symptom dynamics while sharing the same overall symptom severity. METHOD: Participants with MDD (n = 73; mean age 34.6 years, s.d. = 13.1; 56.2% female) rated their baseline symptom severity using the Inventory for Depressive Symptomatology Self-Report (IDS-SR). Momentary indicators for depressive symptoms were then collected through ecological momentary assessments five times per day for 28 days; 8395 observations were conducted (average per person: 115; s.d. = 16.8). Each participant's symptom dynamics were estimated using person-specific dynamic network models. Individual differences in these symptom relationship patterns in groups of participants sharing the same symptom severity levels were estimated using individual network invariance tests. Subsequently, the overall proportion of participants that displayed differential symptom dynamics while sharing the same symptom severity was calculated. A supplementary simulation study was conducted to investigate the accuracy of our methodology against false-positive results. RESULTS: Differential symptom dynamics were identified across 63.0% (95% bootstrapped CI 41.0-82.1) of participants within the same severity group. The average false detection of individual differences was 2.2%. CONCLUSIONS: The majority of participants within the same depressive symptom severity group displayed differential symptom dynamics. Examining symptom dynamics provides information about person-specific psychopathological expression beyond severity levels by revealing how symptoms aggravate each other over time. These results suggest that symptom dynamics may be a promising new dimension for clinical characterisation, warranting replication in independent samples. To inform personalised treatment planning, a next step concerns linking different symptom relationship patterns to treatment response and clinical course, including patterns related to spontaneous recovery and forms of disorder progression.

Impaired topology and connectivity of grey matter structural networks in major depressive disorder: evidence from a multi-site neuroimaging data-set.

BACKGROUND: Major depressive disorder (MDD) has been increasingly understood as a disruption of brain connectome. Investigating grey matter structural networks with a large sample size can provide valuable insights into the structural basis of network-level neuropathological underpinnings of MDD. AIMS: Using a multisite MRI data-set including nearly 2000 individuals, this study aimed to identify robust topology and connectivity abnormalities of grey matter structural network linked to MDD and relevant clinical phenotypes. METHOD: A total of 955 MDD patients and 1009 healthy controls were included from 23 sites. Individualised structural covariance networks (SCN) were established based on grey matter volume maps. Following data harmonisation, network topological metrics and focal connectivity were examined for group-level comparisons, individual-level classification performance and association with clinical ratings. Various validation strategies were applied to confirm the reliability of findings. RESULTS: Compared with healthy controls, MDD individuals exhibited increased global efficiency, abnormal regional centralities (i.e. thalamus, precentral gyrus, middle cingulate cortex and default mode network) and altered circuit connectivity (i.e. ventral attention network and frontoparietal network). First-episode drug-naive and recurrent patients exhibited different patterns of deficits in network topology and connectivity. In addition, the individual-level classification of topological metrics outperforms that of structural connectivity. The thalamus-insula connectivity was positively associated with the severity of depressive symptoms. CONCLUSIONS: Based on this high-powered data-set, we identified reliable patterns of impaired topology and connectivity of individualised SCN in MDD and relevant subtypes, which adds to the current understanding of neuropathology of MDD and might guide future development of diagnostic and therapeutic markers.

Cingulate dynamics track depression recovery with deep brain stimulation.

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient's current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Peripheral Interleukin-18 is negatively correlated with abnormal brain activity in patients with depression: a resting-state fMRI study.

BACKGROUND: Interleukin-18 (IL-18) may participate in the development of major depressive disorder, but the specific mechanism remains unclear. This study aimed to explore whether IL-18 correlates with areas of the brain associated with depression. METHODS: Using a case-control design, 68 subjects (34 patients and 34 healthy controls) underwent clinical assessment, blood sampling, and resting-state functional Magnetic Resonance Imaging (fMRI). The total Hamilton depression-17 (HAMD-17) score was used to assess depression severity. Enzyme-linked immunosorbent assay (ELISA) was used to detect IL-18 levels. Rest-state fMRI was conducted to explore spontaneous brain activity. RESULTS: The level of IL-18 was higher in patients with depression in comparison with healthy controls. IL-18 was negatively correlated with degree centrality of the left posterior cingulate gyrus in the depression patient group, but no correlation was found in the healthy control group. CONCLUSION: This study suggests the involvement of IL-18 in the pathophysiological mechanism for depression and interference with brain activity.

Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities.

Importance: Identifying neurobiological differences between patients with major depressive disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for decades. However, recent meta-analyses have raised concerns regarding the replicability and clinical relevance of brain alterations in depression. Objective: To quantify the upper bounds of univariate effect sizes, estimated predictive utility, and distributional dissimilarity of healthy individuals and those with depression across structural magnetic resonance imaging (MRI), diffusion-tensor imaging, and functional task-based as well as resting-state MRI, and to compare results with an MDD polygenic risk score (PRS) and environmental variables. Design, Setting, and Participants: This was a cross-sectional, case-control clinical neuroimaging study. Data were part of the Marburg-Münster Affective Disorders Cohort Study. Patients with depression and healthy controls were recruited from primary care and the general population in Münster and Marburg, Germany. Study recruitment was performed from September 11, 2014, to September 26, 2018. The sample comprised patients with acute and chronic MDD as well as healthy controls in the age range of 18 to 65 years. Data were analyzed from October 29, 2020, to April 7, 2022. Main Outcomes and Measures: Primary analyses included univariate partial effect size (η2), classification accuracy, and distributional overlapping coefficient for healthy individuals and those with depression across neuroimaging modalities, controlling for age, sex, and additional modality-specific confounding variables. Secondary analyses included patient subgroups for acute or chronic depressive status. Results: A total of 1809 individuals (861 patients [47.6%] and 948 controls [52.4%]) were included in the analysis (mean [SD] age, 35.6 [13.2] years; 1165 female patients [64.4%]). The upper bound of the effect sizes of the single univariate measures displaying the largest group difference ranged from partial η2 of 0.004 to 0.017, and distributions overlapped between 87% and 95%, with classification accuracies ranging between 54% and 56% across neuroimaging modalities. This pattern remained virtually unchanged when considering either only patients with acute or chronic depression. Differences were comparable with those found for PRS but substantially smaller than for environmental variables. Conclusions and Relevance: Results of this case-control study suggest that even for maximum univariate biological differences, deviations between patients with MDD and healthy controls were remarkably small, single-participant prediction was not possible, and similarity between study groups dominated. Biological psychiatry should facilitate meaningful outcome measures or predictive approaches to increase the potential for a personalization of the clinical practice.

Psychomotor semiology in depression: a standardized clinical psychomotor approach.

BACKGROUND: Although psychomotor symptoms are associated with the clinical symptomatology of depression, they are rarely assessed and standardized clinical evaluation tools are lacking. Psychomotor retardation is sometimes assessed through direct patient observations by clinicians or through a clinical observation grid, in the absence of a standardized psychomotor assessment. In this pilot study, we evaluated the feasibility of standardized psychomotor examination of patients with major depressive disorder (MDD) and detailed a psychomotor semiology in these patients. METHODS: We used a standardized psychomotor assessment to examine 25 patients with MDD and 25 age- and sex-matched healthy controls (HC) and compared their psychomotor profiles. Using standardized tests, we assessed muscle tone and posture, gross motor skills, perceptual-motor skills, and body image/organization. Clinical assessments of depressive symptoms (levels of psychomotor retardation, anxiety, and self-esteem) comprised this detailed psychomotor examination. RESULTS: All participants were examined using the standardized psychomotor assessment. The main results of the psychomotor examination highlighted low body image of MDD participants (p < 0.001). Significant differences between groups were found in passive muscle tone, posture, emotional control, jumping, manual dexterity, walking, and praxis. Among these psychomotor variables, body image, passivity, jumping and rhythm scores predicted an MDD diagnosis. CONCLUSIONS: Beyond the psychomotor retardation known to be present in MDD patients, this examination revealed an entire psychomotor symptomatology characterized by elevated muscle tone, poor body image associated with poor self-esteem, slowness in global motor skills and manual praxis, and poor rhythmic adaptation. In light of these results, we encourage clinicians to consider using a standardized tool to conduct detailed psychomotor examination of patients with depressive disorders. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04031937 , 24/07/2019.

Resting-State Functional Magnetic Resonance Image to Analyze Electrical Biological Characteristics of Major Depressive Disorder Patients with Suicide Ideation.

The study was aimed to explore the brain imaging characteristics of major depressive disorder (MDD) patients with suicide ideation (SI) through resting-state functional magnetic resonance imaging (rs-fMRI) and to investigate the potential neurobiological role in the occurrence of SI. 50 MDD patients were selected as the experimental group and 50 healthy people as the control group. The brain images of the patients were obtained by MRI. Extraction of EEG biological features was from rs-fMRI images. Since MRI images were disturbed by noise, the initial clustering center of FCM was determined by particle swarm optimization algorithm so that the noise of the collected images was cleared by adaptive median filtering. Then, the image images were processed by the optimized model. The correlation between brain mALFF and clinical characteristics was analyzed. It was found that the segmentation model based on the FCM algorithm could effectively eliminate the noise points in the image; that the zALFF values of the right superior temporal gyrus (R-STG), left middle occipital gyrus (L-MOG), and left middle temporal gyrus (L-MTG) in the observation group were significantly higher than those in the control group (P < 0.05); and that the average zALFF values of left thalamus (L-THA) and left middle frontal gyrus (L-MFG) decreased. The mean zALFF values of L-MFG and L-SFG demonstrated good identification value for SI in MDD patients. In summary, MRI images based on FCM had a good convergence rate, and electrical biological characteristics of brain regions were abnormal in MDD patients with SI, which can be applied to the diagnosis and treatment of patients with depression in clinical practice.

Multiscale neural signatures of major depressive, anxiety, and stress-related disorders.

The extent of shared and distinct neural mechanisms underlying major depressive disorder (MDD), anxiety, and stress-related disorders is still unclear. We compared the neural signatures of these disorders in 5,405 UK Biobank patients and 21,727 healthy controls. We found the greatest case­control differences in resting-state functional connectivity and cortical thickness in MDD, followed by anxiety and stress-related disorders. Neural signatures for MDD and anxiety disorders were highly concordant, whereas stress-related disorders showed a distinct pattern. Controlling for cross-disorder genetic risk somewhat decreased the similarity between functional neural signatures of stress-related disorders and both MDD and anxiety disorders. Among cases and healthy controls, reduced within-network and increased between-network frontoparietal and default mode connectivity were associated with poorer cognitive performance (processing speed, attention, associative learning, and fluid intelligence). These results provide evidence for distinct neural circuit function impairments in MDD and anxiety disorders compared to stress disorders, yet cognitive impairment appears unrelated to diagnosis and varies with circuit function.

Using language in social media posts to study the network dynamics of depression longitudinally.

Network theory of mental illness posits that causal interactions between symptoms give rise to mental health disorders. Increasing evidence suggests that depression network connectivity may be a risk factor for transitioning and sustaining a depressive state. Here we analysed social media (Twitter) data from 946 participants who retrospectively self-reported the dates of any depressive episodes in the past 12 months and current depressive symptom severity. We construct personalised, within-subject, networks based on depression-related linguistic features. We show an association existed between current depression severity and 8 out of 9 text features examined. Individuals with greater depression severity had higher overall network connectivity between depression-relevant linguistic features than those with lesser severity. We observed within-subject changes in overall network connectivity associated with the dates of a self-reported depressive episode. The connectivity within personalized networks of depression-associated linguistic features may change dynamically with changes in current depression symptoms.

Efficacy and safety of psilocybin-assisted treatment for major depressive disorder: Prospective 12-month follow-up.

BACKGROUND: Preliminary data suggest that psilocybin-assisted treatment produces substantial and rapid antidepressant effects in patients with major depressive disorder (MDD), but little is known about long-term outcomes. AIMS: This study sought to examine the efficacy and safety of psilocybin through 12 months in participants with moderate to severe MDD who received psilocybin. METHODS: This randomized, waiting-list controlled study enrolled 27 patients aged 21-75 with moderate to severe unipolar depression (GRID-Hamilton Depression Rating Scale (GRID-HAMD) ⩾ 17). Participants were randomized to an immediate or delayed (8 weeks) treatment condition in which they received two doses of psilocybin with supportive psychotherapy. Twenty-four participants completed both psilocybin sessions and were followed through 12 months following their second dose. RESULTS: All 24 participants attended all follow-up visits through the 12-month timepoint. Large decreases from baseline in GRID-HAMD scores were observed at 1-, 3-, 6-, and 12-month follow-up (Cohen d = 2.3, 2.0, 2.6, and 2.4, respectively). Treatment response (⩾50% reduction in GRID-HAMD score from baseline) and remission were 75% and 58%, respectively, at 12 months. There were no serious adverse events judged to be related to psilocybin in the long-term follow-up period, and no participants reported psilocybin use outside of the context of the study. Participant ratings of personal meaning, spiritual experience, and mystical experience after sessions predicted increased well-being at 12 months, but did not predict improvement in depression. CONCLUSIONS: These findings demonstrate that the substantial antidepressant effects of psilocybin-assisted therapy may be durable at least through 12 months following acute intervention in some patients.

Targeting neuroinflammation by polyphenols: A promising therapeutic approach against inflammation-associated depression.

Depression is the most prevalent and debilitating mental disorder that affects a substantial number of people globally, hindering all aspects of their lives and leading to a high number of suicides each year. Despite the availability of an array of antidepressant medications, taking these medications does not relieve depressive symptoms in a considerable number of patients, implying that an incomplete understanding of the pathomechanisms involved in the development of depression. Besides that, a subset of those non-responsive patients exhibits an increased systemic and central inflammatory response, which has collectively led to the evolvement of the inflammatory theory of depression. Indeed, peripherally generated inflammatory mediators, as well as insults within the brain, can activate the brain's resident immune cells, resulting in a neuroinflammatory response that interferes with the multitude of neurobiological domains implicated in the pathogenesis of depression. Polyphenols, a group of plant-derived bioactive molecules, have been shown to exert neuroprotective functions on the brain by influencing an array of neuropathological mechanisms, including neuroinflammation. From these perspectives, this review mechanistically provides an overview of the neuropathological roles of sustained neuroinflammatory response in the development of depression and elucidates the therapeutic potential of flavonoid and nonflavonoid polyphenols in modulating inflammatory mediators and signaling cascades as well as promoting other neurophysiological and neuroprotective functions underlying inflammation-associated depressive symptoms. Therefore, given their significant anti-neuroinflammatory effects, polyphenols could be a promising and effective adjunctive therapy for the treatment of neuropsychiatric symptoms associated with inflammation-related depression.

Reduced inhibition in depression impairs stimulus processing in human cortical microcircuits.

Cortical processing depends on finely tuned excitatory and inhibitory connections in neuronal microcircuits. Reduced inhibition by somatostatin-expressing interneurons is a key component of altered inhibition associated with treatment-resistant major depressive disorder (depression), which is implicated in cognitive deficits and rumination, but the link remains to be better established mechanistically in humans. Here we test the effect of reduced somatostatin interneuron-mediated inhibition on cortical processing in human neuronal microcircuits using a data-driven computational approach. We integrate human cellular, circuit, and gene expression data to generate detailed models of human cortical microcircuits in health and depression. We simulate microcircuit baseline and response activity and find a reduced signal-to-noise ratio and increased false/failed detection of stimuli due to a higher baseline activity in depression. We thus apply models of human cortical microcircuits to demonstrate mechanistically how reduced inhibition impairs cortical processing in depression, providing quantitative links between altered inhibition and cognitive deficits.

Lifetime use of MDMA/ecstasy and psilocybin is associated with reduced odds of major depressive episodes.

BACKGROUND: Depression is a major mental health issue worldwide, with high rates of chronicity and non-recovery associated with the condition. Existing treatments such as antidepressant medication and psychological treatments have modest effectiveness, suggesting the need for alternative interventions. AIM: The aim of this study was to examine the relationships between MDMA (3,4-methylenedioxymethamphetamine)/ecstasy and psilocybin use and major depressive episodes (MDEs). METHODS: This observational study used data from a large (N = 213,437) nationally representative sample of US adults to test the association of lifetime use of MDMA/ecstasy, psilocybin and other classic psychedelics (lysergic acid diethylamide (LSD), peyote, mescaline), other illegal substances (e.g. cocaine, phencyclidine (PCP)), and legal/medicinal substances of misuse (e.g. pain relievers, tranquilizers) with lifetime, past year, and past year severe MDEs. RESULTS: Results revealed that lifetime MDMA/ecstasy use was associated with significantly lowered odds of a lifetime MDE (adjusted odds ratio (aOR) = 0.84; p < 0.001), past year MDE (aOR = 0.84; p < 0.001), and past year severe MDE (aOR = 0.82; p < 0.001). Psilocybin was associated with significantly lowered odds of a past year MDE (aOR = 0.90; p < 0.05) and past year severe MDE (aOR = 0.87; p < 0.05). All other substances either shared no relationship with a MDE or conferred increased odds of an MDE. CONCLUSIONS: These results suggest that MDMA/ecstasy and psilocybin use is associated with lower risk of depression. Experimental studies are needed to test whether there is a causal association between use of these compounds and the alleviation of depressive symptoms.

Extracellular vesicle-mediated delivery of circDYM alleviates CUS-induced depressive-like behaviours.

Major depressive disorder (MDD) is the most prevalent psychiatric disorder worldwide and severely limits psychosocial function and quality of life, but no effective medication is currently available. Circular RNAs (circRNAs) have been revealed to participate in the MDD pathological process. Targeted delivery of circRNAs without blood-brain barrier (BBB) restriction for remission of MDD represents a promising approach for antidepressant therapy. In this study, RVG-circDYM-extracellular vesicles (RVG-circDYM-EVs) were engineered to target and preferentially transfer circDYM to the brain, and the effect on the pathological process in a chronic unpredictable stress (CUS) mouse model of depression was investigated. The results showed that RVG-circDYM-EVs were successfully purified by ultracentrifugation from overexpressed circDYM HEK 293T cells, and the characterization of RVG-circDYM-EVs was successfully demonstrated in terms of size, morphology and specific markers. Beyond demonstrating proof-of-concept for an RNA drug delivery technology, we observed that systemic administration of RVG-circDYM-EVs efficiently delivered circDYM to the brain, and alleviated CUS-induced depressive-like behaviours, and we discovered that RVG-circDYM-EVs notably inhibited microglial activation, BBB leakiness and peripheral immune cells infiltration, and attenuated astrocyte disfunction induced by CUS. CircDYM can bind mechanistically to the transcription factor TAF1 (TATA-box binding protein associated factor 1), resulting in the decreased expression of its downstream target genes with consequently suppressed neuroinflammation. Taken together, our findings suggest that extracellular vesicle-mediated delivery of circDYM is effective for MDD treatment and promising for clinical applications.

Negative bias effects during audiovisual emotional processing in major depression disorder.

Aberrant affective neural processing and negative emotional bias are trait-marks of major depression disorders (MDDs). However, most research on biased emotional perception in depression has only focused on unimodal experimental stimuli, the neural basis of potentially biased emotional processing of multimodal inputs remains unclear. Here, we addressed this issue by implementing an audiovisual emotional task during functional MRI scanning sessions with 37 patients with MDD and 37 gender-, age- and education-matched healthy controls. Participants were asked to distinguish laughing and crying sounds while being exposed to faces with different emotional valences as background. We combined general linear model and psychophysiological interaction analyses to identify abnormal local functional activity and integrative processes during audiovisual emotional processing in MDD patients. At the local neural level, MDD patients showed increased bias activity in the ventromedial prefrontal cortex (vmPFC) while listening to negative auditory stimuli and concurrently processing visual facial expressions, along with decreased dorsolateral prefrontal cortex (dlPFC) activity in both the positive and negative visual facial conditions. At the network level, MDD exhibited significantly decreased connectivity in areas involved in automatic emotional processes and voluntary control systems during perception of negative stimuli, including the vmPFC, dlPFC, insula, as well as the subcortical regions of posterior cingulate cortex and striatum. These findings support a multimodal emotion dysregulation hypothesis for MDD by demonstrating that negative bias effects may be facilitated by the excessive ventral bottom-up negative emotional influences along with incapability in dorsal prefrontal top-down control system.

Altered temporal reachability highlights the role of sensory perception systems in major depressive disorder.

BACKGROUND: The latest studies have considered the time-dependent structures in dynamic brain networks. However, the effect of periphery structures on the temporal flow of information remains unexplored in patients with major depressive disorder (MDD). In this work, we aimed to explore the pattern of interactions between brain regions in MDD across space and time. METHODS: We concentrated on the temporal reachability of nodes in temporal brain networks derived from the resting-state functional magnetic resonance imaging (rs-fMRI) of 55 MDD patients and 62 sex-, age-matched healthy controls. Specifically, temporal connectedness and temporal efficiency (TEF) were estimated based on the length of temporal paths between node pairs. Subsequently, the temporal clustering coefficient (TCC) and temporal distance were jointly employed to explore the patterns in which a node's periphery structure affects its reachability. RESULTS: Significantly higher TEF and lower TCC were found in temporal brain networks in MDD. Besides, significant between-group differences of nodal TCC were detected in regions of sensory perception systems. Considering the temporal paths that begin or end at these regions, MDD patients showed several altered temporal distances. CONCLUSION: Our results showed that the temporal reachability of specific brain regions in MDD could be affected as their periphery structures evolve, which may explain the dysfunction of sensory perception systems in the spatiotemporal domain.

Plasma Levels of the Cytokines B Cell-Activating Factor (BAFF) and A Proliferation-Inducing Ligand (APRIL) in Schizophrenia, Bipolar, and Major Depressive Disorder: A Cross Sectional, Multisite Study.

BACKGROUND: Immune dysfunction has been implicated in the pathogenesis of schizophrenia and other nonaffective psychosis (SCZ), bipolar spectrum disorder (BIP) and major depressive disorder (MDD). The cytokines B cell-activating factor (BAFF) and A proliferation-inducing ligand (APRIL) belong to the tumor necrosis factor (TNF) super family and are essential in orchestrating immune responses. Abnormal levels of BAFF and APRIL have been found in autoimmune diseases with CNS affection. METHODS: We investigated if plasma levels of BAFF and APRIL differed between patients with SCZ, BIP, and MDD with psychotic symptoms (n = 2009) and healthy control subjects (HC, n = 1212), and tested for associations with psychotic symptom load, controlling for sociodemographic status, antipsychotic and other psychotropic medication, smoking, body-mass-index, and high sensitivity CRP. RESULTS: Plasma APRIL level was significantly lower across all patient groups compared to HC (P < .001; Cohen's d = 0.33), and in SCZ compared to HC (P < .001; d = 0.28) and in BIP compared to HC (P < .001; d = 0.37). Lower plasma APRIL was associated with higher psychotic symptom load with nominal significance (P = .017), but not with any other clinical characteristics. Plasma BAFF was not significantly different across patient groups vs HC, but significantly higher in BIP compared to HC (P = .040; d = 0.12) and SCZ (P = .027; d = 0.10). CONCLUSIONS: These results show aberrant levels of BAFF and APRIL and association with psychotic symptoms in patients with SCZ and BIP. This suggest that dysregulation of the TNF system, mediated by BAFF and APRIL, is involved in the pathophysiology of psychotic disorders.