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• Twin studies have proven effective in disentangling gene-environment effects. • Genes and environmental risk factors contribute to brain deficits in mood disorders. • Brain areas are differentially influenced by genes or environment in BD and MDD. • WM integrity emerges as a hallmark of bipolar disorder, under genetic influence. Magnetic resonance imaging (MRI) studies have identified neural structures implicated in the pathophysiology of mood disorders, especially bipolar disorder (BD) and major depressive disorder (MDD). However, the role of genetic and environmental influences on such brain deficits is still unclear. In this context, the present review summarizes the current evidence from structural MRI and Diffusion Tensor Imaging (DTI) studies on twin samples concordant or discordant for BD or MDD, with the aim of clarifying the role of genetic and environmental risk factors on brain alterations. Although the results showed a complex interplay between gene and environment in affective disorders, the evidence seem to underline that both genetic and environmental risk factors have an impact on brain areas and vulnerability to MDD and BD. However, the precise mechanism of action and the interaction between these factors still needs to be unveiled. Therefore, future larger studies on concordant or discordant twins should be encouraged, because this population provides a unique opportunity to probe separately genetic and environmental markers of disease vulnerability. [ABSTRACT FROM AUTHOR]

Background: Although it has been consistently reported the important role of genetic and environmental risk factors on structural and functional alterations in Major Depressive Disorder (MDD), the mechanism and the magnitude of the interactions between specific genetic and/or environmental risk factors on brain structures in this disabling disorder are still elusive. Therefore, in the last two decades an increased interest has been devoted to neuroimaging investigations on monozygotic and dizygotic twin samples mainly because their intrinsic characteristics may help to separate the effects of genetic and environmental risk factors on clinical phenotypes, including MDD.Methods: In this context, the present review summarizes results from structural and functional Magnetic Resonance Imaging studies that investigated twin samples in correlation with MDD.Results: Overall the results confirmed that a) MDD is characterized by significant alterations in selective brain areas presiding over emotion recognition and evaluation, including amygdala, insula and prefrontal cortices, and b) both genetic and environmental risk factors play a key role in the pathophysiology of this disorder.Limitations: Few MRI studies exploring MDD in twin samples.Conclusions: The specific contribution of both aspects is still not fully elucidated especially because genes and environment have an impact on the same brain areas, which are particularly vulnerable in MDD. Expansion of the current twin sample sizes would help to clearly establish the potential relationship between risk factors and the development of MDD. [ABSTRACT FROM AUTHOR]

Background: The function of the hypothalamo-pituitary-adrenal axis (HPA) has been widely investigated in mood disorders based on its role in regulating stress response. Particularly, Magnetic Resonance Imaging (MRI) reports have explored pituitary gland (PG) in both bipolar disorder (BD) and major depressive disorder (MDD). In this context, the present review summarizes the results from MRI studies with the final aim of commenting on the presence of common or distinct PG structural alterations between these two disabling illnesses.Methods: A bibliographic search on PUBMED of all MRI studies exploring PG volumes in BD and MDD as well as first-degree relatives (RELs) from 2000 up to October 2016 was performed.Results: Following the screening process of the available literature it can be said that a) PG enlargement has been found in both BD and MDD, therefore potentially representing a common neurobiological marker characterizing mood disorders, and b) PG volumes are moderated by age and sex in both illnesses, although the direction and the extent of this moderation are still not fully clear.Limitations: Few MRI studies with heterogeneous results.Conclusions: These hypotheses must be taken with caution especially because the heterogeneity of the results of the studies reviewed does not allow for a definite answer about the role of PG in affective disorders. Therefore, larger longitudinal studies investigating PG volumes in BD and MDD patients at the early phases of the illness, by considering females and males separately, are needed to further corroborate these findings. [ABSTRACT FROM AUTHOR]

Introduction: Recent resting-state electroencephalogram (EEG) studies have consistently reported an association between aberrant functional brain networks (FBNs) and treatment-resistant traits in patients with major depressive disorder (MDD). However, little is known about the changes in FBNs in response to external stimuli in these patients. This study investigates whether changes in the salience network (SN) could predict responsiveness to pharmacological treatment in resting-state and external stimuli conditions. Methods: Thirty-one drug-naïve patients with MDD (aged 46.61 ± 10.05, female 28) and twenty-one healthy controls (aged 43.86 ± 14.14, female 19) participated in the study. After 8 weeks of pharmacological treatment, the patients were divided into non-remitted MDD (nrMDD, n = 14) and remitted-MDD (rMDD, n = 17) groups. EEG data under three conditions (resting-state, standard, and deviant) were analyzed. The SN was constructed with three cortical regions as nodes and weighted phase-lag index as edges, across alpha, low-beta, high-beta, and gamma bands. A repeated measures analysis of the variance model was used to examine the group-by-condition interaction. Machine learning-based classification analyses were also conducted between the nrMDD and rMDD groups. Results: A notable group-by-condition interaction was observed in the highbeta band between nrMDD and rMDD. Specifically, patients with nrMDD exhibited hypoconnectivity between the dorsal anterior cingulate cortex and right insula (p = 0.030). The classification analysis yielded a maximum classification accuracy of 80.65%. Conclusion: Our study suggests that abnormal condition-dependent changes in the SN could serve as potential predictors of pharmacological treatment efficacy in patients with MDD. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to explore the association between bowel movement disorders and depression in adults. Method: A cross-sectional study was conducted using data from the National Health and Nutritional Examination Survey (NHANES), 2005–2010. Depression, constipation, diarrhea, and fecal incontinence were self-reported via questionnaires. Weighted logistic regression and subgroup analyses were performed to explore the association between bowel movement disorders and the risk of depression. Restricted cubic spline (RCS) was also conducted to investigate the association between bowel movements disorder and depression. Results: A total of 13,820 participants were collected. Compared to the participants with normal bowel movements, the full-adjusted depression model ORs for constipation and diarrhea were 2.28 (95%CI,1.78-2.92), 1.75 (95%CI,1.31-2.31), respectively. Any kind of bowel leakage were associated with depression. The RCS showed the possible nonlinear association between bowel movement frequency/stool shape and depression. Conclusions: Constipation, diarrhea, and bowel leakage are associated with an increased risk of depression. [ABSTRACT FROM AUTHOR]

Fluoxetine, the prototypical selective serotonin reuptake inhibitor (SSRI), is widely used to treat major depressive disorder (MDD) and a variety of other central nervous system conditions, primarily due to its established clinical safety profile. Although its efficacy in treating depression is well-recognized, the impact of fluoxetine on cognitive functions remains inconsistent and elusive. In this review, we first examine the well-substantiated biological mechanisms underlying fluoxetine's antidepressant effects, which include serotonin reuptake inhibition and activation of TrkB receptors--key to brain-derived neurotrophic factor (BDNF) signaling. Subsequently, we delve into the cognitive side effects observed in both preclinical and clinical studies, affecting domains such as memory, attention, and executive functions. While certain studies indicate cognitive improvements in patients with underlying disorders, there is also evidence of negative effects, influenced by variables like gender, duration of treatment, age, disease pathology, and the specifics of cognitive testing. Significantly, the negative cognitive outcomes reported in preclinical research often involve healthy, non-diseased animals. This review underscores the necessity for heightened caution in fluoxetine prescription and further investigation into its potentially detrimental cognitive effects, even when used prophylactically. [ABSTRACT FROM AUTHOR]

Background Epigenetic modifications, such as DNA methylation, contribute to the pathophysiology of major depressive disorder (MDD). This study aimed to identify novel MDD-associated epigenetic loci using DNA methylation profiles and explore the correlations between epigenetic loci and cortical thickness changes in patients with MDD. Methods A total of 350 patients with MDD and 161 healthy controls (HCs) were included in the epigenome-wide association studies (EWAS). We analyzed methylation, copy number alteration (CNA), and gene network profiles in the MDD group. A total of 234 patients with MDD and 135 HCs were included in neuroimaging methylation analysis. Pearson's partial correlation analysis was used to estimate the correlation between cortical thickness of brain regions and DNA methylation levels of the loci. Results In total, 2018 differentially methylated probes (DMPs) and 351 differentially methylated regions (DMRs) were identified. DMP-related genes were enriched in two networks involved in the central nervous system. In neuroimaging analysis, patients with MDD showed cortical thinning in the prefrontal regions and cortical thickening in several occipital regions. Cortical thickness of the left ventrolateral prefrontal cortex (VLPFC, i.e. pars triangularis) was negatively correlated with eight DMPs associated with six genes (EML6 , ZFP64 , CLSTN3 , KCNMA1 , TAOK2 , and NT5E). Conclusion Through combining DNA methylation and neuroimaging analyses, negative correlations were identified between the cortical thickness of the left VLPFC and DNA methylation levels of eight DMPs. Our findings could improve our understanding of the pathophysiology of MDD. [ABSTRACT FROM AUTHOR]

Introduction: Special Operations Forces service members (SOF) are regularly exposed to traumatic and concussive events, increasing the prevalence of symptoms of post-traumatic stress disorder (PTSD) and depression, shortening potential years of service. Methods: This retrospective chart review presents preliminary data on a Human Performance Optimization (HPO) program that provided an average of 30 sessions of individualized alpha frequency repetitive transcranial magnetic stimulation (α-rTMS) to active-duty SOF as to reduce symptoms of PTSD and depression following traumatic brain injury. Scores from the PTSD Checklist for DSM-5, PROMIS Depression short form and Perceived Deficits Questionnaire (PDQ) were reviewed. Results: Significant reductions were noted after the HPO program in all clinical scales with an average 37% decrease in PCL-5 (p<.01), 11.3% reduction in PROMIS depression T-scores (p<.01), and 45.5% reduction in PDQ scales by session 30 (p<.01), with side effects matching those commonly reported in rTMS. Importantly, the average PCL-5 score decreased from 42.9 to 27 by end of the treatment program, which is below the clinical threshold of 33 for presence of PTSD. For those with depression symptoms scores greater than cut off clinical thresholds at baseline, 46% resolved following treatment. Conclusion: This data provides preliminary support for safe application of α-rTMS for symptom reduction in active-duty special operations military personnel. [ABSTRACT FROM AUTHOR]

Objective: Manic and mixed episodes of bipolar disorder are important episodes of this disorder. The aim of the current study was to assess serum vitamin D (SVD) levels in patients with mania and mixed bipolar disorder, compared to healthy subjects. Method: The current cross-sectional study was conducted on 75 subjects, including healthy subjects (n = 25), patients with acute-phase mania (n = 25), and patients with mixed bipolar disorder (n = 25). The SVD levels were measured in all of the enrolled subjects. The Hamilton Depression Rating Scale (HDRS), Young Mania Rating Scale (YMRS), and Clinical Global Impression- Severity (CGI-S) were used to assess disease activity in patient groups. Data analysis was performed using SPSS version 18. For statistical analysis, analysis of variance (ANOVA), independent-sample t test, Pearson correlation, and Chi-square tests were utilized. P-values < 0.05 were considered statistically significant. Results: The results showed that the mean of SVD was significantly lower in mania and mixed bipolar patients compared to healthy subjects (P < 0.05). In addition, the number of subjects with SVD ≥ 20 ng/ml was higher in the healthy group compared to the patient groups (P < 0.05). Also, SVD was negatively correlated with the CGI-S (r = -0.311; P = 0.028), YMRS (r = -0.464; P = 0.001), and HDRS (r = -0.393; P = 0.005) in the total patient subjects. Conclusion: Prevalence of low SVD was considerably high in mania and mixed bipolar patients compared to healthy subjects. Additionally, meaningful negative correlations were found between SVD and disease activity-related variables including the HDRS, YMRS, and CGI-S. [ABSTRACT FROM AUTHOR]

Depression is the most common mental disorder worldwide. Both antidepressants and psychotherapy are effective in treating depression, but the response to these treatments is often incomplete. Yoga-based interventions (YBIs) have been advocated by some researchers as a promising form of alternative treatment for depression. Recent research has attempted to identify the biological mechanisms associated with the antidepressant actions of YBIs. In this scoping review, conducted according to the PRISMA-ScR guidelines, the PubMed and Scopus databases were searched to retrieve research on biomarkers of response to YBIs in patients with depression. These studies were also critically reviewed to evaluate their methodological quality and any sources of bias. Nineteen studies were included in the review. Based on these studies, there is preliminary evidence that YBIs may be associated with increased serum brain-derived neurotrophic factor (BDNF) and reduced serum cortisol and interleukin-6 (IL-6) in patients with depression. However, many of these changes were also observed in the control arms, and the overall quality of the research was low. At present, it cannot be concluded that there are reliable biomarkers of response to YBIs in depression, though there are some potential biological correlates. Further advances in this field will depend critically on improvements in study design, particularly the minimization of sources of bias and the selection of more specific and sensitive biomarkers based on existing evidence from other treatment modalities. [ABSTRACT FROM AUTHOR]

The prediction of depression is a crucial area of research which makes it one of the top priorities in mental health research as it enables early intervention and can lead to higher success rates in treatment. Self-reported feelings by patients represent a valuable biomarker for predicting depression as they can be expressed in a lower-dimensional network form, offering an advantage in visualizing the interactive characteristics of depression-related feelings. Furthermore, the network form of data expresses high-dimensional data in a compact form, making the data easy to use as input for the machine learning processes. In this study, we applied the graph convolutional network (GCN) algorithm, an effective machine learning tool for handling network data, to predict depression-prone patients using the network form of self-reported log data as the input. We took a data augmentation step to expand the initially small dataset and fed the resulting data into the GCN algorithm, which achieved a high level of accuracy from 86–97% and an F1 (harmonic mean of precision and recall) score of 0.83–0.94 through three experimental cases. In these cases, the ratio of depressive cases varied, and high accuracy and F1 scores were observed in all three cases. This study not only demonstrates the potential for predicting depression-prone patients using self-reported logs as a biomarker in advance, but also shows promise in handling small data sets in the prediction, which is critical given the challenge of obtaining large datasets for biomarker research. The combination of self-reported logs and the GCN algorithm is a promising approach for predicting depression and warrants further investigation. [ABSTRACT FROM AUTHOR]

Background: The usefulness of repetitious transcranial magnetic stimulation (rTMS) and its protocols in the treatment of major depressive disorder (MDD) remains controversial. This study aimed to evaluate the efficacy of rTMS in treating a sample of patients with MDD who did not respond to conventional treatment. Results: The Hamilton Depression Rating Scale (HDRS) scores for the active rTMS group were 19.66 ± 6.70 at baseline, 12.50 ± 6.69 at 2 weeks, and 11.23 ± 6.59 at 4 weeks. The average HDRS scores for the sham rTMS group were 20.03 ± 7.40 at baseline, 19.36 ± 6.86 at 2 weeks, and 18.53 ± 7.10 at 4 weeks (F = 5.98; p < 0.01). The Clinical Global Impression-Severity Scale (CGI-S) scores were significantly lower in the second and fourth weeks than the baseline due to the significant interaction between time effects and the groups (F = 9.95, p = 0.002). This condition was also similar to the CGI-Improvement Scale and Brief Illness Perception Questionnaire (Brief IPQ), and the intervention group showed a significantly lower score than the control group (p < 0.05). Conclusions: This study showed that rTMS using the employed protocol was promising for patients with MDD resistant to first-line drug therapy. Further studies are required to ensure our observation. Trial registration: Trial registration number: IRCT20190612043877N1 Trial registry Record URL: https://irct.behdasht.gov.ir/trial/63919 [ABSTRACT FROM AUTHOR]

Background: Anxiety and depression are prevalent mental disorders. As modern society continues to face mounting pressures, the incidence of anxiety and depression is on the rise. In recent years, there has been an increasing breadth of research exploring the relationship between anxiety, depression, and physical activity (PA). However, the current research progress and future development trends are unclear. The purpose of this study is to explore the research hotspots and development trends in this field, and to provide guidance for future studies and to provide some reference for clinicians. Methods: We searched the relevant literature of Web of Science Core Collection from the establishment of the database to August 15, 2023. CiteSpace, VOSviewer and Bibliometrix Packages based on the R language were used to analyze the number of publications, countries, institutions, journals, authors, references, and keywords. Results: A total of 1,591 studies were included in the analysis, and the research in the field of PA on anxiety or depression has consistently expanded. The USA (304 publications), Harvard University (93 publications), and the journal of affective disorders (97 publications) were the countries, institutions, and journals that published the highest number of articles, respectively. According to the keywords, students and pregnant women, adult neurogenesis, and Tai Chi were the groups of concern, physiological and pathological mechanisms, and the type of PA of interest, respectively. Conclusion: The study of PA on anxiety or depression is experiencing ongoing expansion. Clinicians can consider advising patients to take mind-body exercise to improve mood. In addition, future researchers can explore the mind-body exercise and its impact on anxiety or depression, PA and anxiety or depression in specific populations, and adult neurogenesis of various exercise in anxiety or depression. [ABSTRACT FROM AUTHOR]

Key Points: Question: Can multivariate machine learning approaches identify the neural signature of major depressive disorder in individual patients? Findings: In this case-control neuroimaging study that included 1801 patients with depression and healthy controls, the best machine learning algorithm only achieved a diagnostic classification accuracy of 62% across major neuroimaging modalities. Meaning: Although multivariate neuroimaging markers increase predictive power compared with univariate analyses, no depression biomarker could be uncovered that is able to identify individual patients. This case-control study evaluates whether machine learning can identify a multivariate biomarker for major depressive disorder. Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified. Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD. Design, Setting, and Participants: This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023. Exposure: Patients with MDD and healthy controls. Main Outcome and Measure: Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression. Results: Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups. Conclusion and Relevance: Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker—even under extensive ML optimization in a large sample of diagnosed patients—could be identified. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome. Methods: In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t 0), after ECT (t 1) and 2 years later (t 2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed. Results: Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t 0 to t 1 and decreases from t 1 to t 2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t 0 to t 1 correlate with immediate and delayed symptom increase, while volume decreases from t 1 to t 2 correlate with long-term depressive outcome (all p ⩽ 0.049). Conclusions: Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes. [ABSTRACT FROM AUTHOR]

Introduction: A large amount of studies demonstrated reduced serum Brain-Derived Neurotrophic Factor (BDNF) levels in stress-related and depressive disorders. However, it is still unclear if a similar deficit in BDNF concentrations might also characterize maternal perinatal depression.Methods: We performed a bibliographic search on PUBMED of all the studies investigating the association between maternal BDNF levels and perinatal depression. The inclusion criteria were met by thirteen studies.Results: Overall, the majority of the studies reported a significant reduction in serum BDNF levels among depressed mothers compared to healthy mothers either during pregnancy or in the postpartum period. Moreover, some studies also demonstrated that the BDNF reduction could be more evident in those depressed mothers with perinatal stressful life events and suicide risk.Limitations: BDNF were collected at different time points across the studies. Potential confounding factors, including the clinical characteristics of the samples employed by the original studies, might have influenced the results.Conclusions: So far, the evidences suggested the presence of decreased BDNF concentrations in perinatal depressive disorders. However, further studies are needed in order to confirm the role of BDNF in this disorder. [ABSTRACT FROM AUTHOR]

Major Depressive Disorder (MDD) is one of the most disabling diseases in the world. MDD is traditionally diagnosed based on a patient's symptoms, which can lead to misdiagnosis. Although the pathogenic mechanisms of MDD are unknown, several studies have identified mitochondrial dysfunction as a central factor in the onset and progression of MDD. In the context of MDD, alterations in mitochondrial metabolism can lead to imbalances in energy production and oxidative stress, contributing to the disorder´s underlying pathophysiological mechanisms. Consequently, the identification of mitochondrial dysfunction as a key biomarker for early and accurate diagnosis of MDD represents a significant challenge. Faced with the limits of traditional treatments with antidepressants, new pharmacological therapeutic targets are being investigated such as ketamine/esketamine, psychedelics, or anti-inflammatories. All of these drugs show potential antidepressant effects due to their speed of action and ability to modulate neuroplasticity and/or motor processing. In parallel, non-pharmacological therapeutic targets are studied, like Transcranial Magnetic Stimulation (TMS) and Deep Brain Stimulation (DBS), recognized for their ability to modulate neuronal activity and offer treatment alternatives. As cellular activity is directly related to mitochondrial respiration, the aim of this review is examining the link between mitochondrial dysfunction and MDD, assessing how mitochondrial biomarkers could provide a more objective and precise diagnostic tool, and exploring other treatments in addition to traditional antidepressants, with a specific focus on emerging therapeutic targets. Finally, a detailed analysis of the strengths, weaknesses, opportunities, and threats of these approaches was carried out, highlighting the key challenges that must be addressed. [ABSTRACT FROM AUTHOR]

Background. While the brain correlates of major depressive disorder (MDD) have been extensively studied, there is no consensus conclusion so far. Various meta-analyses tried to determine the most consistent findings, but the results are often discordant for grey matter volume (GMV) atrophy and hypertrophy. Applying rigorous and stringent inclusion criteria and controlling for confounding factors, such as the presence of anxiety comorbidity, we carried out two novel meta-analyses on the existing literature to unveil MDD signatures. Methods. A systematic literature search was performed up to January 2023. Seventy-three studies on MDD patients reporting GMV abnormalities were included in the first meta-analysis, for a total of 6167 patients and 6237 healthy controls (HC). To test the effects of anxiety comorbidity, we conducted a second meta-analysis, by adding to the original pure MDD sample a new cohort of MDD patients with comorbid anxiety disorders (308 patients and 342 HC). An activation likelihood estimation (ALE) analysis and a coordinate-based mapping approach separate for atrophy and hypertrophy were used to identify common brain structural alterations among patients. Results. The pure MDD sample exhibited atrophy in the left insula, as well as hypertrophy in the bilateral amygdala and parahippocampal gyri. When we added patients with comorbid anxiety to the original sample, bilateral insula atrophy emerged, whereas the hypertrophy results were not replicated. Conclusions. Our findings revealed important structural alterations in pure MDD patients, particularly in the insula and amygdala, which play key roles in sensory input integration and in emotional processing, respectively. Additionally, the amygdala and parahippocampal gyrus hypertrophy may be related to MDD functional overactivation to emotional stimuli, rumination, and overactive self-referential thinking. Conversely, the presence of anxiety comorbidity revealed separate effects which were not seen in the pure MDD sample, underscoring the importance of strict inclusion criteria for investigations of disorder-specific effects. [ABSTRACT FROM AUTHOR]

Introduction: The present study aimed to compare the Parietal Lobe (PL) volumes and Cancellation Test (CT) performances of euthymic patients with Bipolar Disorder-1 (BD) and Major Depressive Disorder (MDD), and healthy controls. Methods: The present study included 63 participants in three groups; two patient groups in remission involving patients with BD and MDD diagnosed according to DSM-5 and a control group with healthy individuals. Sociodemographic Data Form, CT, and Hand Preference Questionnaire were applied to all participants. Participant PL volumes were measured with the Cloud-Based Brain Magnetic Resonance Image Segmentation -- Parcellation System. Results: Both patient groups exhibited lower PL volume when compared to the control group, and there was no difference between the patient groups based on PL volume. It was determined that MDD and BB patients scored less in the CT when compared to the control group. There was a weak correlation between right and left PL volumes and CT performances. Conclusion: The present study findings demonstrated that BD and MDD patients in remission exhibited lower PL volume and CT performance when compared to healthy controls, emphasizing that PL could be structurally and functionally significant in the pathophysiology of mood disorders. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders. [ABSTRACT FROM AUTHOR]

Major Depressive Disorder (MDD) is a severe psychiatric disorder characterized by selective impairments in mood regulation, cognition and behavior. Although it is well-known that antidepressants can effectively treat moderate to severe depression, the biochemical effects of these medications on white matter (WM) integrity are still unclear. Therefore, the aim of the study is to review the main scientific evidence on the differences in WM integrity in responders and nonresponders to antidepressant medications. A record search was performed on three datasets (PubMed, Scopus and Web of Science) and ten records matched our inclusion criteria. Overall, the reviewed studies highlighted a good efficacy of antidepressants in MDD treatment. Furthermore, there were differences in WM integrity between responders and non-responders, mainly localized in cingulate cortices, hippocampus and corpus callosum, where the former group showed higher fractional anisotropy and lower axial diffusivity values. Modifications in WM integrity might be partially explained by branching and proliferation as well as neurogenesis of axonal fibers mediated by antidepressants, which in turn may have positively affected brain metabolism and increase the quantity of the serotonergic neurotransmitter within synaptic clefts. However, the reviewed studies suffer from some limitations, including the heterogeneity in treatment duration, antidepressant administration, medical posology, and psychiatric comorbidities. Therefore, future studies are needed to reduce confounding effects of antidepressant medications and to adopt longitudinal and multimodal approaches in order to better characterize the differences in WM integrity between responders and non-responders. [ABSTRACT FROM AUTHOR]

Background: In recent years, accelerated transcranial magnetic stimulation (aTMS) has been developed, which has a shortened treatment period. The aim of this study was to evaluate the efficacy and long-term maintenance effects of aTMS in patients with major depressive disorder (MDD). Methods: We systematically searched online databases for aTMS studies in patients with MDD published before February 2023 and performed a meta-analysis on the extracted data. Results: Four randomized controlled trials (RCTs) and 10 before-and-after controlled studies were included. The findings showed that depression scores significantly decreased following the intervention (SMD = 1.80, 95% CI (1.31, 2.30), p < 0.00001). There was no significant difference in antidepressant effectiveness between aTMS and standard TMS (SMD = -0.67, 95% CI (-1.62, 0.27), p = 0.16). Depression scores at follow-up were lower than those directly after the intervention based on the depression rating scale (SMD = 0.22, 95% CI (0.06, 0.37), p = 0.006), suggesting a potential long-term maintenance effect of aTMS. Subgroup meta-analysis results indicated that different modes of aTMS may have diverse long-term effects. At the end of treatment with the accelerated repetitive transcranial magnetic stimulation (arTMS) mode, depressive symptoms may continue to improve (SMD = 0.29, 95% CI (0.10, 0.49), I2 = 22%, p = 0.003), while the accelerated intermittent theta burst stimulation (aiTBS) mode only maintains posttreatment effects (SMD = 0.01, 95% CI (-0.45, 0.47), I2 = 66%, p = 0.98). Conclusions: Compared with standard TMS, aTMS can rapidly improve depressive symptoms, but there is no significant difference in efficacy. aTMS may also have long-term maintenance effects, but longer follow-up periods are needed to assess this possibility. Trial registration: This article is original and not under simultaneous consideration for publication. The study was registered on PROSPERO (https://www.crd.york.ac.uk/prospero/) (number: CRD42023406590). [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) therapy has few side effects and comparable therapeutic effects to antidepressant treatment, but few studies have introduced TMS therapy as an initial treatment for MDD. The objective of this study was to retrospectively compare the clinical outcomes between 50 MDD patients without antidepressants (i.e., TMS monotherapy) and 50 MDD patients with antidepressants plus TMS therapy, matched for age, sex, and depression severity. The presence or absence of antidepressant therapy in first-line treatment was determined via a detailed interview by psychiatrists. The study design was a retrospective observational case–control study using the TMS registry data. The key inclusion criteria were adult patients who met the diagnosis of MDD and received 20–30 sessions of intermittent theta-burst stimulation (iTBS) therapy to the left dorsolateral prefrontal cortex (DLPFC). In this study, the Montgomery–Åsberg Depression Rating Scale (MADRS) was used as the primary outcome measure. No significant group differences existed in the baseline MADRS total score between the unmedicated and medicated patient groups. Following TMS therapy, no significant group differences in response rate, remission rate, or relative total score change in the MADRS were observed. The main limitations were the retrospective design and the use of registry data as a source. Our findings suggest that TMS monotherapy may be as effective as TMS add-on therapy to antidepressants when used as the first-line therapy for MDD, but randomized controlled trials are needed. [ABSTRACT FROM AUTHOR]

Depression is a prevalent mental disorder and has a profound impact on an individual's psychological and physical well-being. It is characterized by a persistently depressed mood, loss of interest, energy loss, and cognitive dysfunction. In recent years, more and more people have changed to mental diseases, such as depression, anxiety, mania and so on. In the incidence of depression, covering all ages, but still mainly young and middle-aged women. Traditional treatments for depression mainly rely on medication and psychotherapy, but these methods are not effective for all patients and are often accompanied by certain side effects. Therefore, finding safe and effective alternative or adjuvant treatments has become a priority. Here we highlight the research progress of acupuncture in the treatment of depression and to explore the mechanism of acupuncture in the treatment of depression. Acupuncture treatment of depression is an ancient and effective method, the mechanism involves multiple biological pathways, for example, by regulating neurotransmitter levels, regulating the neuroendocrine axis, improving neuroplasticity, anti-inflammatory and other effects, improving emotional state and play an antidepressant role. To provide evidence to support the widespread use of acupuncture in clinical practice. We hope to provide new treatment ideas and methods for patients with depression, and even reduce the incidence of depression. [ABSTRACT FROM AUTHOR]

Background: Sexual dysfunction is commonly observed in individuals with Major Depressive Disorder (MDD), along with various psychological symptoms such as anxiety, somatic complaints, interpersonal sensitivity, and obsessive-compulsive tendencies. However, there is a research gap in understanding the impact of these psychological symptoms on sexual functioning in MDD. Furthermore, there is limited data on the incidence of sexual dysfunction among drug-naive MDD patients in West China. This study aims to determine the prevalence of sexual dysfunction in this patient population and explore its association with other psychological indicators. Methods: We conducted a retrospective analysis of patient data from October 2020 to September 2022 using propensity score matching. A focused group of 165 males and 490 females was selected from a total of 1941 MDD patients. This allowed for a comparative analysis of demographic data, as well as scores from the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), and Symptom Checklist-90 (SCL-90), the Arizona Sexual Experience Scale (ASEX). Results: Our findings reveal that 46.2% of drug-naive MDD patients experienced sexual dysfunction. Notably, there was a higher prevalence of sexual dysfunction among female patients (50.3%) compared to males (37.5%). MDD patients without sexual dysfunction consistently exhibited higher SDS scores than those with sexual dysfunction (p < 0.01), There were no statistically significant differences between male and female MDD patients with or without concomitant sexual dysfunction in terms of Somatic complaints, Obsessive-compulsive, Interpersonal sensitivity, Anxiety, Phobic anxiety, Paranoid ideation, Psychoticism and Diet/sleep difficulties (p > 0.05). In addition, male MDD patients with sexual dysfunction showed a emerging trend towards elevated Hostility scores on the SCL-90 (p = 0.058), male MDD patients with sexual dysfunction showed an increasing trend in hostility scores on the SCL-90, whereas female MDD patients with sexual dysfunction did not show such a trend. Conclusion: The study highlights a significant gender difference in the prevalence of sexual dysfunction among MDD patients, with females being more susceptible than males. There is a positive correlation between the severity of depression and sexual dysfunction in both genders. Interestingly, male MDD patients demonstrated a potential protective effect of hostility against sexual dysfunction, which was not observed in female patients. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a prevalent psychiatric condition with a complex and unknown pathological mechanism. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a valuable non-invasive technology for MDD diagnosis. By utilizing rs-fMRI data, a dynamic brain functional connection network (FCN) can be constructed to represent the complex interacting relationships of multiple brain sub-regions. Graph neural network (GNN) models have been widely employed to extract disease-associated information. The simple averaging or summation graph readout functions of GNNs may lead to a loss of critical information. This study introduces a two-channel graph neural network (DepressionGraph) that effectively aggregates more comprehensive graph information from the two channels based on the node feature number and node number. Our proposed DepressionGraph model leverages the transformer–encoder architecture to extract the relevant information from the time-series FCN. The rs-fMRI data were obtained from a cohort of 533 subjects, and the experimental data show that DepressionGraph outperforms both traditional GNNs and simple graph readout functions for the MDD diagnosis task. The introduced DepressionGraph framework demonstrates efficacy in extracting complex patterns from rs-fMRI data and exhibits promising capabilities for the precise diagnosis of complex neurological disorders. The current study acknowledges a potential gender bias due to an imbalanced gender distribution in the dataset. Future research should prioritize the development and utilization of gender-balanced datasets to mitigate this limitation and enhance the generalizability of the findings. [ABSTRACT FROM AUTHOR]

Introduction: Major depressive disorder (MDD) is a prevalent mental illness, with severe symptoms that can significantly impair daily routines, social interactions, and professional pursuits. Recently, imaging genetics has received considerable attention for understanding the pathogenesis of human brain disorders. However, identifying and discovering the imaging genetic patterns between genetic variations, such as single nucleotide polymorphisms (SNPs), and brain imaging data still present an arduous challenge. Most of the existing MDD research focuses on single-modality brain imaging data and neglects the complex structure of brain imaging data. Methods: In this study, we present a novel association analysis model based on a self-expressive network to identify and discover imaging genetics patterns between SNPs and multi-modality imaging data. Specifically, we first build the multi-modality phenotype network, which comprises voxel node features and connectivity edge features from structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI), respectively. Then, we apply intra-class similarity information to construct self-expressive networks of multi-modality phenotype features via sparse representation. Subsequently, we design a fusion method guided by diagnosis information, which iteratively fuses the self-expressive networks of multi-modality phenotype features into a single new network. Finally, we propose an association analysis between MDD risk SNPs and the multi-modality phenotype network based on a fusion self expressive network. Results: Experimental results show that our method not only enhances the association between MDD risk SNP rs1799913 and the multi-modality phenotype network but also identifies some consistent and stable regions of interest (ROIs) multi-modality biological markers to guide the interpretation of MDD pathogenesis. Moreover, 15 new potential risk SNPs highly associated with MDD are discovered, which can further help interpret the MDD genetic mechanism. Discussion: In this study, we discussed the discriminant and convergence performance of the fusion self-expressive network, parameters, and atlas selection. [ABSTRACT FROM AUTHOR]

Background: Anhedonia is a core symptom in patients with unipolar and bipolar depression. However, sex-specific markers reflecting biological heterogeneity are lacking. Emerging evidence suggests that sex differences in immune-inflammatory markers and lipoprotein profiles are associated with anhedonia. Methods: The demographic and clinical data, immune-inflammatory markers (CD3, CD4, and CD8), and lipoprotein profiles [TC, TG, LDL-C, HDL-C, lipoprotein(a) Lp (a)] of 227 patients with unipolar and bipolar depression were collected. The Hamilton Depression Rating Scale (HAMD) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess depression and anhedonia symptoms. Data were analyzed using ANOVA, logistic regression, and receiver operating characteristic curves. Results: Male patients in the anhedonia group had higher levels of CD3, CD4, and CD8, and lower levels of Lp (a) than the non-anhedonia group, while no significant difference was identified in female patients with and without anhedonia. Logistic regression analysis showed that CD3, CD4, CD8, and Lp (a) levels were associated with anhedonia in male patients. Furthermore, the combination of CD3, CD4, CD8, and Lp (a) had the strongest predictive value for distinguishing anhedonia in male patients than individual parameters. Conclusions: We identified sex-specific associations between immune-inflammatory markers, lipoprotein profiles, and anhedonia in patients with unipolar and bipolar depression. The combination of CD3, CD4, CD8, and Lp (a) might be a possible biomarker for identifying anhedonia in male patients with unipolar and bipolar depression. [ABSTRACT FROM AUTHOR]

Background: Since diagnosis of mood disorder heavily depends on signs and symptoms, emerging researches have been studying biomarkers with the attempt to improve diagnostic accuracy, but none of the findings have been broadly accepted. The purpose of the present study was to construct a preliminary diagnostic model to distinguish major depressive disorder (MDD) and bipolar disorder (BD) using potential commonly tested blood biomarkers. Methods: Information of 721 inpatients with an ICD-10 diagnosis of MDD or BD were collected from the electronic medical record system. Variables in the nomogram were selected by best subset selection method after a prior univariable screening, and then constructed using logistic regression with inclusion of the psychotropic medication use. The discrimination, calibration and internal validation of the nomogram were evaluated by the receiver operating characteristic curve (ROC), the calibration curve, cross validation and subset validation method. Results: The nomogram consisted of five variables, including age, eosinophil count, plasma concentrations of prolactin, total cholesterol, and low-density lipoprotein cholesterol. The model could discriminate between MDD and BD with an area under the ROC curve (AUC) of 0.858, with a sensitivity of 0.716 and a specificity of 0.890. Conclusion: The comprehensive nomogram constructed by the present study can be convenient to distinguish MDD and BD since the incorporating variables were common indicators in clinical practice. It could help avoid misdiagnoses and improve prognosis of the patients. [ABSTRACT FROM AUTHOR]

Background: Brain-derived neurotrophic factor (BDNF) with neuronic development and function is a promising therapeutic agent for treating depressive disorder, according to the neurotrophin hypothesis. However, the delivery of BDNF into the brain is not easy as these large protein molecules cannot efficiently cross the blood-brain barrier (BBB) and easily suffer oxidative damage in vivo. Therefore, the quercetin-based alginate nanogels (quercetin nanogels) loaded with BDNF have been developed, which could efficiently bypass the BBB via the nose-to-brain pathway and protect BDNF from oxidative damage, providing an effective route for the therapy of depressive disorders by intranasal delivery. Results: Quercetin nanogels exhibited uniform size distribution, excellent biocompatibility, and potent antioxidant and anti-inflammatory activities. Quercetin nanogels in the thermosensitive gel achieved sustained and controlled release of BDNF with non-Fick's diffusion, exhibited rapid brain distribution, and achieved nearly 50-fold enhanced bioavailability compared to oral quercetin. Quercetin nanogels as a therapeutic drug delivery carrier exerted antidepressant effects on reserpine-induced rats, effectively delivered BDNF to reverse despair behavior in stress-induced mice, and exhibited antidepressant effects on chronic mild unpredictable stimulation (CUMS) rats. These antidepressant effects of BDNF-Quercetin nanogels for CUMS rats are associated with the regulation of the glutamatergic system, PI3K-Akt, and BDNF-TrkB signaling pathway. Conclusions: In this study, we provide a promising strategy for brain delivery of BDNF for treating depressive disorders, effectively achieved through combining quercetin nanogels and intranasal administration. Highlights: Natural antioxidant quercetin-based alginate nanogels protect BDNF from oxidative damage and have a quick brain distribution. Intranasal quercetin nanogels exhibit significantly higher bioavailability compared to oral quercetin. BDNF-Quercetin nanogels in thermosensitive gel release BDNF and quercetin in a sustained and controlled manner. BDNF-Quercetin nanogels in thermosensitive gel have significant antidepressant effects on stress-induced mice and rats. [ABSTRACT FROM AUTHOR]

The multifactorial etiology of major depressive disorder (MDD) includes biological, environmental, genetic, and psychological aspects. Recently, there has been an increasing interest in metallomic studies in psychiatry, aiming to evaluate the role of chosen trace elements in the MDD etiology as well as the progression of symptoms. This narrative review aims to summarize the available literature on the relationship between the concentration of chosen elements in the serum of patients with MDD and the onset and progression of this psychiatric condition. The authors reviewed PubMed, Web of Science, and Scopus databases searching for elements that had been investigated so far and further evaluated them in this paper. Ultimately, 15 elements were evaluated, namely, zinc, magnesium, selenium, iron, copper, aluminium, cadmium, lead, mercury, arsenic, calcium, manganese, chromium, nickel, and phosphorus. The association between metallomic studies and psychiatry has been developing dynamically recently. According to the results of current research, metallomics might act as a potential screening tool for patients with MDD while at the same time providing an assessment of the severity of symptoms. Either deficiencies or excessive amounts of chosen elements might be associated with the progression of depressive symptoms or even the onset of the disease among people predisposed to MDD. [ABSTRACT FROM AUTHOR]

Background: Ketamine and its enantiomer have rapid and robust effects on depressive symptom and suicidal ideation. Little is known about their cognitive effects in adolescents. We aimed to evaluate the short-term effect of esketamine on cognition in adolescents with major depressive disorder (MDD) and suicidal ideation. Method: In this randomized-controlled trial, 51 participants aged 13–18 with MDD and suicidal ideation received three intravenous infusions of either esketamine (0.25 mg/kg) or midazolam (0.02 mg/kg). Four dimensions of the MATRICS Consensus Cognitive Battery (MCCB), including processing speed, working memory, verbal learning and visual learning, were assessed at Days 0, 6 and 12. Results: In the linear mixed model, a significant time main effect (F = 12.803, P < 0.001), drug main effect (F = 6.607, P = 0.013), and interaction effect (F = 3.315, P = 0.041) was found in processing speed. Other dimensions including working memory and verbal learning showed significant time main effect (all P < 0.05), but no significant drug or interaction effect (all P > 0.05). Esketamine group showed improvement in processing speed from baseline to Days 6 and 12, and working memory from baseline to Day 12 (all P < 0.05). The generalized estimation equation showed no significant association between baseline cognition and antidepressant or antisuicidal effect (both P > 0.05). Conclusions: The present study suggested that three-dose subanesthetic esketamine infusions did not harm cognition among adolescents with MDD and suicidal ideation. Instead, esketamine may be associated with improvement in processing speed. Trial registration: This trial was registered in the Chinese Clinical Trials Registry (http://www.chictr.org.cn, ChiCTR2000041232). [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to identify regions with altered degrees of centrality (DC) and changes in their functional connectivity (FC) in first-episode drug-naïve major depressive disorder (FEDN-MDD) patients using resting-state functional magnetic resonance imaging (fMRI). Methods: The study included 74 FEDN-MDD patients who met the study criteria and 41 healthy controls (HCs). All had undergone fMRI scanning in the resting condition. To evaluate differences between FEDN-MDD patients and HCs, we first compared the DC between the 2 groups. The DC regions with the most significant differences were then taken as seeds, and their FC was calculated. Results: Right posterior cingulum cortex (PCC.R), right precuneus (PCUN.R), and right putamen (PUT.R) all showed significantly different DC values (P < .001) between FEDNMDD patients and HC groups, which helped in distinguishing these groups. The PUT.R in FEDN-MDD patients showed increased FC (P < .001) with the right inferior temporal gyrus and right inferior occipital gyrus compared to HC. Moreover, the PCUN.R in FEDN-MDD patients showed decreased FC (P < .001) with bilateral cerebellum crus I, left cerebellum crus II, bilateral orbital medial frontal gyrus, right superior medial frontal gyrus, left precuneus, left posterior cingulum cortex, right superior frontal gyrus, and PCC.R compared with the HC group. The P-values for cluster testing were .050, while for voxel testing they were .001. Conclusion: These findings imply that PUT.R, PCUN.R, and PCC.R serve as the core brain net hub in FEDN-MDD patients, and their FC displays aberrant function. This may involve a specific psychiatric neuropathology associated with FEDN-MDD. [ABSTRACT FROM AUTHOR]

Nowadays, nervous tissue damage proteins in serum are considered promising drug targets and biomarkers of Mood Disorders. In a cross-sectional naturalistic study, the S100B, MBP and GFAP levels in the blood serum were compared between two diagnostic groups (patients with Depressive Episode (DE, n = 28) and patients with Recurrent Depressive Disorder (RDD, n = 21)), and healthy controls (n = 25). The diagnostic value of serum markers was assessed by ROC analysis. In the DE group, we did not find changed levels of S100B, MBP and GFAP compared with controls. In the RDD group, we found decreased S100B level (p = 0.011) and increased MBP level (p = 0.015) in comparison to those in healthy controls. Provided ROC analysis indicates that MBP contributes to the development of a DE (AUC = 0.676; 95%Cl 0.525–0.826; p = 0.028), and S100B and MBP have a significant effect on the development of RDD (AUC = 0.732; 95%Cl 0.560–0.903; p = 0.013 and AUC = 0.712; 95%Cl 0.557–0.867; p = 0.015, correspondingly). The study of serum markers of nervous tissue damage in patients with a current DE indicates signs of disintegration of structural and functional relationships, dysfunction of gliotransmission, and impaired secretion of neurospecific proteins. Modified functions of astrocytes and oligodendrocytes are implicated in the pathophysiology of RDD. [ABSTRACT FROM AUTHOR]

Treatment of bipolar disorder is prone to prolongation despite various treatments, including medication. The efficacy of exercise treatment (i.e., interventions involving physical exercise and sports intervention) for major depressive disorders has been reported for depressive symptoms, cognitive function, and sleep disturbances. However, its efficacy for bipolar disorder has yet to be established. We designed a randomized, controlled, double-blind clinical trial that includes 100 patients with bipolar disorder aged 20–65 years. This will be a cluster-randomized, two-group trial that will be conducted in ten psychiatric hospitals. The hospitals will be randomly assigned to an exercise intervention + treatment as usual (exercise) group or a placebo exercise intervention (stretching) + treatment as usual (control) group. Patients will be assessed using an extensive battery of clinical tests, physical parameters, sleep status, biological parameters (cytokines, neurotrophic factors), and genetic parameters (DNA and RNA) at baseline after a 6-week intervention period, at 10-week follow-up, and at 6-month follow-up. This innovative study may provide important evidence for the effectiveness of exercise in the treatment of bipolar depression based on clinical, biological, genetic, and physiological markers. [ABSTRACT FROM AUTHOR]

Introduction: Post-stroke depression (PSD) is a serious mental disorder after ischemic stroke. Early detection is important for clinical practice. This research aims to develop machine learning models to predict new-onset PSD using real-world data. Methods: We collected data for ischemic stroke patients from multiple medical institutions in Taiwan between 2001 and 2019. We developed models from 61,460 patients and used 15,366 independent patients to test the models' performance by evaluating their specificities and sensitivities. The predicted targets were whether PSD occurred at 30, 90, 180, and 365 days post-stroke. We ranked the important clinical features in these models. Results: In the study's database sample, 1.3% of patients were diagnosed with PSD. The average specificity and sensitivity of these four models were 0.83-0.91 and 0.30-0.48, respectively. Ten features were listed as important features related to PSD at different time points, namely old age, high height, low weight poststroke, higher diastolic blood pressure after stroke, no pre-stroke hypertension but post-stroke hypertension (new-onset hypertension), post-stroke sleep-wake disorders, post-stroke anxiety disorders, post-stroke hemiplegia, and lower blood urea nitrogen during stroke. Discussion: Machine learning models can provide as potential predictive tools for PSD and important factors are identified to alert clinicians for early detection of depression in high-risk stroke patients. [ABSTRACT FROM AUTHOR]

COVID-19's long-term effects, known as Long-COVID, present psychiatric and physical challenges in recovered patients. Similarly, rare long-term post-vaccination side effects, resembling Long-COVID, are emerging (called Post-Vaccine). However, effective treatments for both conditions are scarce. Our clinical experience suggests that transcranial magnetic stimulation (TMS) often aids recovery in Long-COVID and Post-Vaccine patients. However, its effectiveness is reduced in patients with severe fatigue. Therefore, we retrospectively analysed Tokyo TMS Clinic's outpatient records (60 in total; mean age, 38 years) to compare Long-COVID and post-vaccine patients' characteristics and symptoms, assess the impact of TMS on their symptoms, and investigate the role of fatigue in depression recovery with TMS. The primary outcome was the regression coefficient of the initial fatigue score on depression score improvement using TMS. Secondary outcomes included psychiatric/physical scores before and after TMS and their improvement rates. We found no differences in the initial symptoms and background factors between Long-COVID and Post-Vaccine patients. After ten TMS sessions, all psychiatric and physical symptom scores improved significantly. TMS improves depression, insomnia, anxiety, and related neuropsychiatric symptoms, which were the primary complaints in this study. Thus, we conclude that TMS improves depression and anxiety. The effectiveness of TMS in treating depression in Long-COVID and Post-Vaccine patients decreased as fatigue severity increased. In conclusion, TMS relieved depressive symptoms following COVID-19 and vaccination; however, fatigue may hinder its effectiveness. [ABSTRACT FROM AUTHOR]

Major psychiatric disorders create a significant public health burden, and mental disorders such as major depressive disorder, bipolar disorder, and schizophrenia are major contributors to the national disease burden. The search for biomarkers has been a leading endeavor in the field of biological psychiatry in recent decades. And the application of cross-scale and multi-omics approaches combining genes and imaging in major psychiatric studies has facilitated the elucidation of gene-related pathogenesis and the exploration of potential biomarkers. In this article, we summarize the results of using combined transcriptomics and magnetic resonance imaging to understand structural and functional brain changes associated with major psychiatric disorders in the last decade, demonstrating the neurobiological mechanisms of genetically related structural and functional brain alterations in multiple directions, and providing new avenues for the development of quantifiable objective biomarkers, as well as clinical diagnostic and prognostic indicators. [ABSTRACT FROM AUTHOR]

Depression increasingly affects a wide range and a large number of people worldwide, both physically and psychologically, which makes it a social problem requiring prompt attention and management. Accumulating clinical and animal studies have provided us with substantial insights of disease pathogenesis, especially central monoamine deficiency, which considerably promotes antidepressant research and clinical treatment. The first-line antidepressants mainly target the monoamine system, whose drawbacks mainly include slow action and treatment resistant. The novel antidepressant esketamine, targeting on central glutamatergic system, rapidly and robustly alleviates depression (including treatment-resistant depression), whose efficiency is shadowed by potential addictive and psychotomimetic side effects. Thus, exploring novel depression pathogenesis is necessary, for seeking more safe and effective therapeutic methods. Emerging evidence has revealed vital involvement of oxidative stress (OS) in depression, which inspires us to pursue antioxidant pathway for depression prevention and treatment. Fully uncovering the underlying mechanisms of OS-induced depression is the first step towards the avenue, thus we summarize and expound possible downstream pathways of OS, including mitochondrial impairment and related ATP deficiency, neuroinflammation, central glutamate excitotoxicity, brain-derived neurotrophic factor/tyrosine receptor kinase B dysfunction and serotonin deficiency, the microbiota-gut-brain axis disturbance and hypothalamic-pituitary-adrenocortical axis dysregulation. We also elaborate on the intricate interactions between the multiple aspects, and molecular mechanisms mediating the interplay. Through reviewing the related research progress in the field, we hope to depict an integral overview of how OS induces depression, in order to provide fresh ideas and novel targets for the final goal of efficient treatment of the disease. [ABSTRACT FROM AUTHOR]

Background: This study aimed to explore possible differences of the whole-brain functional connectivity of the anterior cingulate cortex (ACC) and anterior insula (AI), in a sample of depressed patients with major depressive disorder (MDD), bipolar disorder (BD) and healthy controls (HC). Methods: A hundred and three subjects (nMDD = 35, nBD = 25, and nHC = 43) between the ages of eighteen and sixty-five years old underwent functional magnetic resonance imaging. The CONN Toolbox was used to process and analyze the functional connectivity of the ACC and AI. Results: The comparison between the patients (MDD/BD) and HC yielded increased resting-state functional connectivity (rsFC) between the ACC and the motor and somatosensory cortices (SSC), superior parietal lobule (SPL), precuneus, and lateral occipital cortex, which was driven by the BD group. In addition, hyperconnectivity between the right AI and the motor and SSC was found in BD, as compared to HC. In MDD, as compared to HC, hyperconnectivity between ACC and SPL and the lateral occipital cortex was found, with no statistical rsFC differences for the AI seed. Compared to BD, the MDD group showed ACC–cerebellum hyperconnectivity and a trend for increased rsFC between the right AI and the bilateral superior frontal cortex. Conclusions: Considering the observed hyperconnectivity between the ACC/somatosensory cortex in the patient group, we suggest depression may be related to an impairment of the sensory-discriminative function of the SSC, which results in the phenomenological signature of mental pain in both MDD and BD. These findings suggest that future research should investigate this particular network with respect to motor functions and executive control, as a potential differential diagnostic biomarker for MDD and BD. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) refers to a widespread psychiatric disorder. Astrocytes play a pivotal role in regulating inflammation which is a well-acknowledged key component in depression pathogenesis. However, the effects of the neuroinflammation-inducing A1-like astrocytes on MDD are still unknown. TWIK-related K+ channel 1 (TREK-1) has been demonstrated to regulate the action of antidepressants. Nevertheless, its mechanisms and effects on A1-like astrocyte stimulation in MDD are not clear. Therefore, we conducted in vivo and in vitro experiments using TREK-1 specific inhibitor spadin. In vivo, rats were subjected to a 6-week chronic unpredictable mild stress (CUMS) followed by spadin treatment. Behavioral tests were employed to surveil depressive-like behaviors. Hippocampal proteomic analysis was carried out with the purpose of identifying differentially expressed proteins after CUMS and spadin treatments. In vitro, astrocyte-conditioned medium and spadin were used to treat rat astrocyte cell line. The activated microglia, inflammatory factors, A1 astrocyte markers, and activated nuclear factor kappa B (NF-κB) pathway were later analyzed using immunofluorescence, western blot, and RT-qPCR. Our findings indicated that blockage of TREK-1 reduced CUMS-induced depressive-like behavior in rats, inhibited the microglial stimulation, reduced inflammatory factor levels, and suppressed the activation of A1-like reactive astrocytes in the hippocampus. We also verified that the suppression of A1-like astrocytes by spadin necessitated the NF-κB pathway. According to the findings, blocking TREK-1 inhibited the activation of A1-like reactive astrocytes via the NF-κB signaling pathway in MDD. Our study preliminarily identifies a novel antidepressant mechanism of TREK-1 action and provides a therapeutic path for MDD. [ABSTRACT FROM AUTHOR]

Purpose: Repetitive transcranial magnetic stimulation (rTMS) is an eective therapy in improving depressive symptoms in MDD patients, but the intrinsic mechanism is still unclear. In this study, we investigated the influence of rTMS on brain gray matter volume for alleviating depressive symptoms in MDD patients using structural magnetic resonance imaging (sMRI) data. Methods: Patients with first episode, unmedicated patients with MDD (n = 26), and healthy controls (n = 31) were selected for this study. Depressive symptoms were assessed before and after treatment by using the HAMD-17 score. Highfrequency rTMS treatment was conducted in patients with MDD over 15 days. The rTMS treatment target is located at the F3 point of the left dorsolateral prefrontal cortex. Structural magnetic resonance imaging (sMRI) data were collected before and after treatment to compare the changes in brain gray matter volume. Results: Before treatment, patients with MDD had significantly reduced gray matter volumes in the right fusiform gyrus, left and right inferior frontal gyrus (triangular part), left inferior frontal gyrus (orbital part), left parahippocampal gyrus, left thalamus, right precuneus, right calcarine fissure, and right median cingulate gyrus compared with healthy controls (P < 0.05). After rTMS treatment, significant growth in gray matter volume of the bilateral thalamus was observed in depressed patients (P < 0.05). Conclusion: Bilateral thalamic gray matter volumes were enlarged in the thalamus of MDD patients after rTMS treatment and may be the underlying neural mechanism for the treatment of rTMS on depression [ABSTRACT FROM AUTHOR]

The effects of celecoxib on a broad spectrum of mood disorders and on inflammatory parameters have not yet been comprehensively evaluated. The aim of this study was to systematically summarize the available knowledge on this topic. Data from both preclinical and clinical studies were analyzed, considering the efficacy and safety of celecoxib in the treatment of mood disorders, as well as the correlation of inflammatory parameters with the effect of celecoxib treatment. Forty-four studies were included. We found evidence supporting the antidepressant efficacy of celecoxib in a dose of 400 mg/day used for 6 weeks as an add-on treatment in major depression (SMD = −1.12 [95%Cl: −1.71,−0.52], p = 0.0002) and mania (SMD = −0.82 [95% CI:−1.62,−0.01], p = 0.05). The antidepressant efficacy of celecoxib in the above dosage used as sole treatment was also confirmed in depressed patients with somatic comorbidity (SMD = −1.35 [95% CI:−1.95,−0.75], p < 0.0001). We found no conclusive evidence for the effectiveness of celecoxib in bipolar depression. Celecoxib at a dose of 400 mg/d used for up to 12 weeks appeared to be a safe treatment in patients with mood disorders. Although an association between celecoxib response and inflammatory parameters has been found in preclinical studies, this has not been confirmed in clinical trials. Further studies are needed to evaluate the efficacy of celecoxib in bipolar depression, as well as long-term studies evaluating the safety and efficacy of celecoxib in recurrent mood disorders, studies involving treatment-resistant populations, and assessing the association of celecoxib treatment with inflammatory markers. [ABSTRACT FROM AUTHOR]

Objective: To identify DNA methylation and clinical features, and to construct machine learning classifiers to assign the patients with major depressive disorder (MDD) into responders and non-responders after a 2-week treatment into responders and non-responders. Method: Han Chinese patients (291 in total) with MDD comprised the study population. Datasets contained demographic information, environment stress factors, and the methylation levels of 38 methylated sites of tryptophan hydroxylase 2 (TPH2) genes in peripheral blood samples. Recursive Feature Elimination (RFE) was employed to select features. Five classification algorithms (logistic regression, classification and regression trees, support vector machine, logitboost and random forests) were used to establish the models. Performance metrics (AUC, F-Measure, G-Mean, accuracy, sensitivity, specificity, positive predictive value and negative predictive value) were computed with 5-fold-cross-validation. Variable importance was evaluated by random forest algorithm. Result: RF with RFE outperformed the other models in our samples based on the demographic information and clinical features (AUC = 61.2%, 95%CI: 60.1-62.4%) / TPH2 CpGs features (AUC = 66.6%, 95%CI: 65.4-67.8%) / both clinical and TPH2 CpGs features (AUC = 72.9%, 95%CI: 71.8-74.0%). Conclusion: The effects of TPH2 on the early-stage antidepressant response were explored by machine learning algorithms. On the basis of the baseline depression severity and TPH2 CpG sites, machine learning approaches can enhance our ability to predict the early-stage antidepressant response. Some potentially important predictors (e.g., TPH2-10-60 (rs2129575), TPH2-2-163 (rs11178998), age of first onset, age) in early-stage treatment response could be utilized in future fundamental research, drug development and clinical practice. [ABSTRACT FROM AUTHOR]

Depression is a common mental disorder that seriously affects the quality of life and leads to an increasing global suicide rate. Macro, micro, and trace elements are the main components that maintain normal physiological functions of the brain. Depression is manifested in abnormal brain functions, which are considered to be tightly related to the imbalance of elements. Elements associated with depression include glucose, fatty acids, amino acids, and mineral elements such as lithium, zinc, magnesium, copper, iron, and selenium. To explore the relationship between these elements and depression, the main literature in the last decade was mainly searched and summarized on PubMed, Google Scholar, Scopus, Web of Science, and other electronic databases with the keywords "depression, sugar, fat, protein, lithium, zinc, magnesium, copper, iron, and selenium". These elements aggravate or alleviate depression by regulating a series of physiological processes, including the transmission of neural signals, inflammation, oxidative stress, neurogenesis, and synaptic plasticity, which thus affect the expression or activity of physiological components such as neurotransmitters, neurotrophic factors, receptors, cytokines, and ion-binding proteins in the body. For example, excessive fat intake can lead to depression, with possible mechanisms including inflammation, increased oxidative stress, reduced synaptic plasticity, and decreased expression of 5-Hydroxytryptamine (5-HT), Brain Derived Neurotrophic Factor (BDNF), Postsynaptic density protein 95(PSD-95), etc. Supplementing mineral elements, such as selenium, zinc, magnesium, or lithium as a psychotropic medication is mostly used as an auxiliary method to improve depression with other antidepressants. In general, appropriate nutritional elements are essential to treat depression and prevent the risk of depression. [ABSTRACT FROM AUTHOR]

Major depression is one of the most prevalent mental disorders, causing significant human suffering and socioeconomic loss. Since conventional antidepressants are not sufficiently effective, there is an urgent need to develop new antidepressant medications. Despite marked advances in the neurobiology of depression, the etiology and pathophysiology of this disease remain poorly understood. Classical and newer hypotheses of depression suggest that an imbalance of brain monoamines, dysregulation of the hypothalamic-pituitary-adrenal axis (HPAA) and immune system, or impaired hippocampal neurogenesis and neurotrophic factors pathways are cause of depression. It is assumed that conventional antidepressants improve these closely related disturbances. The purpose of this review was to discuss the possibility of affecting these disturbances by targeting the melanocortin system, which includes adrenocorticotropic hormone-activated receptors and their peptide ligands (melanocortins). The melanocortin system is involved in the regulation of various processes in the brain and periphery. Melanocortins, including peripherally administered non-corticotropic agonists, regulate HPAA activity, exhibit anti-inflammatory effects, stimulate the levels of neurotrophic factors, and enhance hippocampal neurogenesis and neurotransmission. Therefore, endogenous melanocortins and their analogs are able to complexly affect the functioning of those body's systems that are closely related to depression and the effects of antidepressants, thereby demonstrating a promising antidepressant potential. [ABSTRACT FROM AUTHOR]

Recently, vitamin D is considered a pleiotropic hormone, and as such, it has also become a topic of renewed interest in neuropsychiatry for its proposed role in the aetiology and pathophysiology of different psychiatric conditions, including mood disorders (MDs). This seems particularly crucial while considering the relatively high and often neglected prevalence of hypovitaminosis D in the general population and in specific groups, such as patients suffering from the most common type of MDs, which are major depression (MDD) and bipolar disorders (BDs). Therefore, in view of the controversial literature and findings on this topic and its potential therapeutic implications, the present study aimed at evaluating vitamin D levels in the plasma of a sample of inpatients fulfilling the DSM-5 criteria for mood episodes within BDs. The clinical picture was assessed by means of specific rating scales. The results showed that the vitamin D levels (mean ± SD, nM/L) of the bipolar patients of our sample were significantly lower (14.58 ± 11.27 nmol/L) than the normative values (>30 nmol/L). Eleven patients had sufficient values and only 4 had optimal, while 19 showed insufficient, 18 critical, and 17 severely critical levels. No differences emerged according to different socio-demographic or clinical features. In our opinion, the present findings strengthen previous research highlighting decreased vitamin D levels in bipolar patients and support the role of this pleiotropic hormone in BDs. Nevertheless, further studies should follow to corroborate the data of this preliminary study and to address the potential benefits of vitamin D supplementation in the treatment of MDs. [ABSTRACT FROM AUTHOR]

Depression is a highly prevalent emotional disorder characterized by persistent low mood, diminished interest, and loss of pleasure. The pathological causes of depression are associated with neuronal atrophy, synaptic loss, and neurotransmitter activity decline in the central nervous system (CNS) resulting from injuries, such as inflammatory responses. In Traditional Chinese Medicine (TCM) theory, patients with depression often exhibit the liver qi stagnation syndrome type. Sini Powder (SNP) is a classic prescription for treating such depression-related syndrome types in China. This study systematically summarized clinical applications and experimental studies of SNP for treatments of depression. We scrutinized the active components of SNP with blood–brain barrier (BBB) permeability and speculated about the corresponding pharmacodynamic pathways relevant to depression treatment through intervening in the CNS. Therefore, this article can enhance our understanding of SNP's pharmacological mechanisms and formula construction for depression treatment. Moreover, a re-demonstration of this classic TCM prescription in the modern-science language is of great significance for future drug development and research. [ABSTRACT FROM AUTHOR]

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The aim of the current study was to compare the unified protocol for transdiagnostic treatment of emotional disorders (UP) with and without transcranial direct current stimulation (tDCS) for the treatment of emotion regulation and executive control dysfunction in individuals diagnosed with generalized anxiety disorder (GAD) and comorbid major depressive disorder (MDD). A total of 43 individuals with GAD and co‐morbid MDD were randomly assigned to three groups including UP with tDCS (UP+tDCS; n = 15), UP alone (UP; n = 13) or wait‐list control (n = 15). Difficulties in emotion regulation, reappraisal, suppression, inhibition and working memory were assessed at baseline, post‐treatment and 3‐month follow‐up. Treatment with both UP+tDCS and UP alone resulted in significant improvements in difficulties in emotion regulation, cognitive reappraisal, and working memory, and significant reductions in suppression and inhibition relative to wait‐list controls at post‐treatment and 3‐month follow‐up. Relative to UP alone, UP+tDCS showed significantly greater improvements in difficulties in emotion regulation, cognitive reappraisal, inhibition, and working memory at post‐treatment and 3‐month follow‐up. These results suggest combination of UP treatment with tDCS may be an efficacious intervention to improve emotion regulation and executive function in GAD with co‐morbid MDD. Trial registration reference is IRCT20140929019334N1 (see https://irct.ir/trial/27988). [ABSTRACT FROM AUTHOR]