Search Results (224)

Background/Objectives: Juvenile idiopathic arthritis (JIA) and inflammatory bowel disease (IBD) are chronic autoimmune conditions that impact the physical and psychological well-being of pediatric patients. While previous studies have shown a high prevalence of mental health challenges among youth with chronic conditions, the prevalence of mental health issues in Canadian pediatric patients with JIA and IBD remains unclear. We aimed to estimate the prevalence of documented mental health disorders and related medication use of youth with JIA or IBD at a tertiary care centre. Methods: We conducted a retrospective chart review of youths aged 12–17 diagnosed with JIA or IBD at McMaster Children’s Hospital (MCH) to understand the prevalence of generalized anxiety disorder (GAD), separation anxiety disorder, social anxiety disorder (SAD), obsessive–compulsive disorders (OCD), eating disorders, major depressive disorder (MDD), adolescent adjustment disorder, suicide attempt/suicide ideation, self-harm behaviour, substance use disorder, and attention deficit disorders (ADD). Results: We reviewed 429 patient charts, including 303 patients with IBD and 126 with JIA. Our findings identified 90 IBD patients and 20 JIA patients who had one or more documented mental health conditions. Proportionately, there was a higher prevalence of mental health conditions among IBD patients (30%) compared to JIA patients (16%). The most frequently observed conditions in both IBD and JIA patients were GAD (63%, 50%), ADD (33%, 35%), and MDD (29%, 15%). Conclusions: These findings highlight the critical need for early mental health screening and integrated care approaches that address both medical and psychosocial needs in adolescents with chronic illnesses. Future research should incorporate prospective study designs, include diverse geographic and demographic populations, and explore targeted interventions to improve mental and physical health outcomes in this vulnerable group. Full article

Major depressive disorder is a mental illness characterized by persistent sadness or loss of interest that affects a person’s daily life. Early detection of this disorder is crucial for providing timely and effective treatment. Neuroimaging modalities, namely, functional magnetic resonance imaging, can be used to identify changes in brain regions related to major depressive disorder. In this study, regional homogeneity images, one of the derivative of functional magnetic resonance imaging is employed to detect major depressive disorder using the proposed feature/sample evolving voting ensemble approach. A total of 2380 subjects consisting of 1104 healthy controls and 1276 patients with major depressive disorder from Rest-meta-MDD consortium are studied. Regional homogeneity features from 90 regions are extracted using automated anatomical labeling template. These regional homogeneity features are then fed as an input to the proposed feature/sample selective evolving voting ensemble for classification. The proposed approach achieves an accuracy of 91.93%, and discriminative features obtained from the classifier are used to identify brain regions which may be responsible for major depressive disorder. A total of nine brain regions, namely, left superior temporal gyrus, left postcentral gyrus, left anterior cingulate gyrus, right inferior parietal lobule, right superior medial frontal gyrus, left lingual gyrus, right putamen, left fusiform gyrus, and left middle temporal gyrus, are identified. This study clearly indicates that these brain regions play a critical role in detecting major depressive disorder. Full article

Background/Objectives: Major depressive disorder (MDD) is a debilitating illness, and chronic stress is a contributing factor for depressive symptoms. However, despite intense research, the mechanisms of MDD remain substantially unidentified. Quercetin is a powerful flavonoid and could be used as a possible therapeutic strategy for depression. Acknowledging the potential benefits of quercetin, this study investigated its effect alone or in association with the standard drug tranylcypromine (TCP) in a rodent model of chronic restraint stress (CRS). Methods: Adult male rats were subjected to a CRS model consisting of an immobilization session of 4 h daily during 14 consecutive days. Quercetin (50 mg/kg, gavage) was administered for 45 days. TCP (10 mg/kg, gavage) was administered for 14 days. Behavioral tasks were conducted to assess locomotor functions, memory, anhedonia, depression-like behaviors, and anxiety-like behaviors. The activity, gene expression, and protein density of acetylcholinesterase (AChE) were investigated. Results: Behavioral tasks showed that the CRS model effectively induced stable behavioral changes. CRS did not alter locomotor function assessed by the open field test (OFT) or anhedonia behavior assessed by the sucrose preference test (SPT). CRS increased total fecal count, which was prevented by quercetin administration in rats. TCP and the association of quercetin and TCP increased the recognition index in comparison with the CRS group in the novel object recognition (NOR) test and improved the swimming and immobility times in comparison to stressed animals in the forced swim test (FST). All treatments were able to decrease the anxiety index assessed by the elevated plus maze (EPM) test. The activity, gene expression, and protein density of AChE were increased in the CRS model compared to control males. Overall, quercetin and TCP proved to reverse CRS-induced alterations in these parameters. Conclusions: Quercetin mitigated cognitive deficits, behavioral impairments, and neurochemical alterations induced by the CRS model, especially in association with TCP, supporting its potential as a promising therapeutic agent for depression. Full article

: Depression, commonly known as unipolar affective disorder, is one of the most prevalent mental illnesses in contemporary society, affecting individuals to varying degrees. Tea is one of the three major non-alcoholic beverages globally; it has a rich history of consumption and is associated with numerous health and nutritional benefits. This review systematically summarizes the antidepressant effects of various bioactive compounds found in tea, drawing upon research findings in the field of tea’s functional health. It elucidates the impact of tea’s bioactive components on the hypothalamic–pituitary–adrenal (HPA) axis, the nervous system, the immune system, intestinal microflora, and the monoaminergic system, among other physiological sites, to achieve antidepressant effects. These effects primarily involve enhancing neural signaling pathways, regulating neural signaling molecule levels, and reducing neuroinflammation. Tea may normalize the body’s nervous system by bolstering immune function, alleviating or eliminating cellular inflammation to maintain healthy homeostasis, or improving intestinal flora and mitigating stress to prevent or treat depressive disorders. Additionally, the potential social support derived from tea-drinking activities, such as cultural rituals and interpersonal communication, may contribute to its antidepressant effects. This review discusses and analyzes the current research status regarding the antidepressant effects of tea and highlights that tea and its active ingredients can be utilized to prevent and alleviate depression. Full article

Oligodendrocyte precursor cells (OPCs) are a dynamic and heterogeneous population of glial cells essential for brain development and myelination. Beyond their well-established role in oligodendrogenesis, emerging evidence suggests that OPCs contribute to synaptic regulation, neuronal communication, and brain plasticity. Recent studies have increasingly implicated OPC dysfunction in the pathophysiology of psychiatric disorders, particularly schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). This narrative review integrates clinical, genetic, transcriptomic, and histological findings to examine the role of OPC alterations in mental illnesses. In SCZ, OPC abnormalities predominantly affect myelination, but recent data also suggest deficits in non-canonical functions, including neuron–OPC communication. Findings in BD largely mirror those in SCZ, implying shared OPC-related mechanisms across these disorders. In contrast, OPC involvement in MDD appears more complex, with evidence supporting both myelination deficits and non-canonical dysfunctions, such as impaired neuro–glial interactions and perineuronal network alterations. The developmental timing of OPC dysfunction may represent a common denominator underlying psychiatric disorders, as early-life stress and neurodevelopmental disturbances have been linked to OPC impairments. Moreover, given the shared developmental origins of OPCs and parvalbumin-positive interneurons, disruptions in their mutual interactions may contribute to broader neural network dysregulation. Despite these insights, the field remains in its infancy. Future studies integrating independent human cohorts with robust preclinical models are needed to clarify the extent of OPC involvement in psychiatric pathophysiology. Understanding OPC dysfunction may reveal novel biomarkers and open new avenues for individualized therapeutic interventions and preventive strategies in mental health. Full article

Background and Objectives: Major depressive disorder (MDD) is a prevalent psychiatric illness increasingly recognized as a systemic condition with implications for cardiovascular diseases. Growing evidence indicates that individuals with MDD have an elevated risk of cardiovascular mortality, underscoring the need for reliable, non-invasive biomarkers to assess cardiac risk. While underlying mechanisms remain unclear, electrocardiogram (ECG)-based markers offer a promising, non-invasive means of evaluation. Among these, the electrical risk score (ERS), a composite derived from specific ECG parameters, has emerged as a predictor of adverse cardiac outcomes. This study aimed to investigate the association between ERS and MDD, and whether ERS correlates with depression severity and illness duration. Materials and Methods: In this retrospective cross-sectional study, 12-lead ECGs were evaluated to calculate the ERS based on six ECG parameters: heart rate, corrected QT interval, Tp-e interval, frontal QRS-T angle, QRS transition zone, and presence of left ventricular hypertrophy according to Sokolow–Lyon criteria. The Hamilton Depression Rating Scale (HAM-D) was utilized. Results: The study included 102 patients with MDD and 62 healthy controls. No significant differences were observed in baseline or laboratory parameters between the groups. However, heart rate, Tp-e interval, frontal QRS-T angle, and ERS were significantly higher in the depression group. ROC analysis identified ERS as the strongest predictor of depression. ERS was significantly higher in patients with severe depression compared to those with mild symptoms and showed a positive correlation with both disease duration and HAM-D score. Conclusions: Here, we show that the ECG-derived ERS is significantly elevated in patients with MDD and is associated with increased cardiac risk. ERS outperformed conventional ECG parameters in identifying individuals with depression and demonstrated positive associations with both illness duration and symptom severity. These findings suggest that ERS may serve as a practical, non-invasive biomarker for assessing cardiovascular vulnerability in this population. Full article

Background: Adjustment to stress requires the involvement of coping strategies. Using maladaptive coping strategies may precipitate the onset or recurrence of psychiatric disorders. On the other hand, the illness itself may alter the coping mechanisms of an individual. This study aims to identify the coping strategies in patients with bipolar disorder (BD) and major depressive disorder (MDD) and determine the correlation between coping strategies and clusters of psychiatric symptoms. Material and Methods: Socio-demographic and clinical data were analyzed for 30 inpatients with BD and 30 inpatients with MDD. The SCL-90 questionnaire and COPE inventory were filled in by the participants. Results: Compared to the general population, the patients with BD had lower scores for functional coping strategies and higher scores for one dysfunctional coping strategy. The patients with MDD had lower scores for all active functional and two passive functional coping strategies. By contrast, they presented higher scores on one passive functional and one dysfunctional coping strategy. Positive reinterpretation and growth were negatively correlated with somatization, depression, anxiety, interpersonal sensitivity, hostility, and psychoticism. Behavioral disengagement was positively correlated with depression, anxiety, somatization, interpersonal sensitivity, and psychoticism. Substance use was positively correlated with the number of episodes. Distinct coping mechanisms were associated with certain symptom clusters. Conclusions: Although dysfunctional coping strategies may predispose to psychiatric disorders, in our study, they appear to be state-dependent rather than trait-dependent. Full article

Psychiatric disorders are a major cause of illness in the world. Unfortunately, many patients are resistant to treatment and present serious complications. Schizophrenia is refractory to treatment in about one-third of patients. Antidepressants are effective in about half of patients. Suicidal ideation is an increasing issue in patients with mixed features in bipolar disorder (BD). Therefore, there is a need to develop and test new drugs or new indications of available medications for the treatment of psychiatric disorders through evidence-based investigations. This narrative review aims to present the molecules approved by the main drug agencies, the Food and Drug Administration (FDA) and the European Medicines Agency (EMA), from 2018 to date, along with new indications and new formulations of existing medications. We searched PubMed for new drugs approved for schizophrenia, BD, major depressive disorder (MDD), anxiety disorders, and obsessive-compulsive disorder (OCD). We evaluated their clinical benefits, safety, and tolerability profiles. Finally, we considered studies on the main molecules that have shown initial evidence of efficacy and are in the process of obtaining approval. Our search suggested that a new antipsychotic, lumateperone, and two drug combinations, olanzapine/samidorphan (OLZ/SAM) and xanomeline/trospium (KarXT), were approved for schizophrenia. In addition, some new methods of administration—monthly risperidone administration, subcutaneous risperidone administration, and transdermal asenapine administration—obtained approval from the main drug agencies. Lumateperone and OLZ/SAM were also approved in BD. Esketamine, a compound that modulates glutamatergic transmission, was approved to treat treatment-resistant depression and acute suicidal ideation. The dextromethorphan/bupropion combination was approved for MDD. Two new agents, brexanolone and zuranolone, were approved for treatment of postpartum depression. On the other hand, no new drugs received approval for anxiety disorders or OCD. In summary, some new psychotropic medications have been developed, in particular with the aim to improve the symptoms of resistant patients and to decrease the incidence of adverse effects. It is necessary to continue testing the effectiveness of new compounds in methodologically rigorous studies. Full article

Depression has become one of the most common mental illnesses, causing severe physical and mental harm. To clarify the impact of brain region segmentation on the detection accuracy of moderate-to-severe major depressive disorder (MDD) and identify the optimal brain region for detecting MDD using electroencephalography (EEG), this study compared eight traditional single-machine learning algorithms with a hybrid machine learning model based on a stacking ensemble technique. The hybrid model employed K-nearest neighbors (KNN), decision tree (DT), and Extreme Gradient Boosting (XGBoost) as base learners and used a DT as the meta-learner. Compared with traditional single methods, the hybrid approach significantly improved detection accuracy by leveraging the strengths of different algorithms. In addition, this study divided the brain regions into the left and right temporal lobes and extracted both linear and nonlinear features to comprehensively capture the complexity and dynamic behavior of EEG signals, enhancing the model’s ability to distinguish features across different brain regions. The experimental results showed that among the eight traditional machine learning methods, the KNN classifier achieved the highest detection accuracy of 96.97% in the left temporal lobe region. In contrast, the stacking hybrid learning model further increased the detection accuracy to 98.07%, significantly outperforming the single models. Moreover, the analysis of the brain region segmentation revealed that the left temporal lobe exhibited higher discriminative power in detecting MDD, highlighting its important role in the neurobiology of depression. This study provides a solid foundation for developing more efficient and portable methods for detecting depression, offering new perspectives and approaches for EEG-based MDD detection, and contributing to the improvement in objectivity and precision in depression diagnosis. Full article

Background: Young adulthood is a demanding developmental stage, in that individuals are often faced with making major and long-lasting decisions related to career and family. This is also a heightened time of mental health difficulties. There is recent evidence that cognitive disengagement syndrome (CDS; previously sluggish cognitive tempo) may also be more prevalent in young adults and associated with poorer functioning. However, the relation between CDS symptoms and anxiety, depression, stress, and insomnia remains insufficiently investigated among young adults. Given this, the aims of the present study were as follows: (1) to investigate the associations between CDS and symptoms of depression, anxiety, stress, and insomnia; (2) to investigate if and which dimensions of ill-being were more robustly related to higher CDS scores; (3) to explore if stress scores moderated the associations between CDS symptoms and insomnia; and (4) to explore if higher insomnia categories were associated with higher CDS scores. Methods: A total of 246 young adult students in Switzerland (mean age = 22.62; 56.3% females) completed a booklet of questionnaires covering socio-demographic information, cognitive disengagement syndrome (Adult Concentration Inventory; ACI), and symptoms of depression, anxiety, stress, and insomnia as part of this cross-sectional study. Results: Higher CDS scores on the ACI were associated with higher scores for depression, anxiety, stress, and insomnia. Depression, anxiety, stress, and insomnia were independently associated with higher scores for CDS. Higher categories of stress moderated the associations between higher CDS scores and higher insomnia. Higher insomnia categories were related to higher CDS scores. Conclusions: The present data showed that among a small sample of young adult students, higher CDS scores were associated with higher psychological ill-being (depression, anxiety, stress, and insomnia). If we consider CDS as a trait, specific performance-enhancing medication or psychotherapeutic interventions might favorably influence dimensions of psychological ill-being such as depression, anxiety, stress, and insomnia. Full article

Major depressive disorder (MDD) is a complex psychiatric illness, with synaptic plasticity playing a key role in its pathology. Our study aims to investigate the molecular basis of MDD by analyzing synaptic plasticity-related gene expression at the single-cell level. Utilizing a published snRNA-seq dataset (GSE144136), we identified Excitatory.neurons_1 as the cell cluster most associated with MDD and synaptic plasticity through cell clustering, gene set enrichment analysis (GSEA), and pseudotime analysis. Integrating the bulk RNA-seq data (GSE38206), we identified CASKIN1 and CSTB as hub genes via differential expression analysis and machine learning methods. Further exploration of the relevant mechanisms was performed via cell–cell communication and ligand-receptor interaction analysis, functional enrichment analysis, and the construction of molecular regulatory networks, highlighting miR-21-5p as a key biomarker. We propose that elevated miR-21-5p in MDD downregulates CASKIN1 in Excitatory.neurons_1 cells, resulting in decreased neural connectivity and altered synaptic plasticity. As our analyzed snRNA-seq dataset consists solely of male samples, these findings may be male-specific. Our findings shed light on potential mechanisms underlying synaptic plasticity in MDD, offering novel insights into the disorder’s cellular and molecular dynamics. Full article

Background/Objectives: Severe mental illnesses such as schizophrenia, major depressive disorder, and bipolar disorder are often accompanied by metabolic comorbidities. While the role of vitamins in physical health is well-established, their involvement in psychiatric disorders has garnered increasing attention in recent years. Methods: We conducted a cross-sectional analysis of 1003 patients diagnosed with severe mental illnesses. Vitamin D, B9, and B12 serum levels were measured, and deficiencies were defined using established clinical cutoffs. Multivariate regression analyses were performed to identify associations between vitamin deficiencies and clinical outcomes. Results: Our findings revealed that vitamin deficiencies were prevalent across all diagnostic groups, with particularly high rates in patients with schizophrenia and major depressive disorder. Vitamin D deficiency was significantly associated with worse psychiatric outcomes, including increased depressive symptoms (adjusted OR = 1.89, p = 0.018), lower Global Assessment of Functioning scores (adjusted OR = −0.18, p < 0.001), and higher rates of metabolic syndrome (adjusted OR = 1.97, p = 0.007). Folate and B12 deficiencies were also linked to greater psychiatric symptom severity and metabolic disturbances, including increased risks of obesity and dyslipidemia. Conclusions: Our study highlights the critical role of vitamins deficiencies in both psychiatric and metabolic health of patients with severe mental illnesses. These findings underscore the importance of routine screening and correction of these deficiencies as part of comprehensive care in psychiatric populations. The integration of nutritional interventions may offer a novel and holistic approach to improving both mental and physical health outcomes. Full article

In recent decades, substantial evidence has highlighted the integral roles of neuroglia, particularly astrocytes, microglia, oligodendrocytes, and ependymal cells, in the regulation of synaptic transmission, metabolic support, and immune mechanisms within the central nervous system. In addition to their structural role, these cells actively modulate neurotransmitter homeostasis and influence neuronal plasticity, thereby affecting cognition, mood, and behavior. This review discusses how neuroglial alterations contribute to the pathophysiology of five common psychiatric disorders: major depression, bipolar disorder, anxiety disorders, attention-deficit/hyperactivity disorder (ADHD), and schizophrenia. We synthesized preclinical and clinical findings illustrating that glial dysfunction, including impaired myelination and aberrant neuroinflammatory responses, often parallels disease onset and severity. Moreover, we outline how disruptions in astrocytic glutamate uptake, microglia-mediated synaptic pruning, and blood–brain barrier integrity may underlie the neurobiological heterogeneity observed in these disorders. The therapeutic implications range from anti-inflammatory agents to investigational compounds that aim to stabilize glial function or promote remyelination. However, challenges due to interindividual variability, insufficient biomarkers, and the multifactorial nature of psychiatric illnesses remain. Advances in neuroimaging, liquid biopsy, and more precise molecular techniques may facilitate targeted interventions by stratifying patient subgroups with distinct glial phenotypes. Continued research is essential to translate these insights into clinically efficacious and safe treatments. Full article

Emerging evidence suggests that glucagon-like peptide-1 receptor (GLP1R) agonists may have potential benefits for mental illnesses. However, their exact effects remain unclear. This study investigated the causal relationship between glucagon-like peptide-1 receptor agonist (GLP1RA) and the risk of 10 common mental illnesses, including attention deficit and hyperactivity disorder, anorexia nervosa, anxiety disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, post-traumatic stress disorder, schizophrenia, cannabis use disorder, and alcohol use disorder. We selected GLP1RA as the exposure and conducted a Mendelian randomization (MR) analysis. The cis-eQTLs of the drug target gene GLP1R, provided by eQTLGen, were used to simulate the pharmacological effects of GLP1RA. Type 2 diabetes and BMI were included as positive controls. Using data from both the Psychiatric Genomic Consortium and FinnGen, we conducted separate MR analyses for the same disease across these two independent databases. Meta-analysis was used to pool the results. We found genetic evidence suggesting a causal relationship between GLP1RA and a reduced risk of schizophrenia [OR (95% CI) = 0.84 (0.71–0.98), I² = 0.0%, common effects model]. Further mediation analysis indicated that this effect might be unrelated to improvements in glycemic control but rather mediated by BMI. However, the findings of this study provide insufficient evidence to support a causal relationship between GLP1RA and other mental illnesses. Sensitivity analyses did not reveal any potential bias due to horizontal pleiotropy or heterogeneity in the above results (p > 0.05). This study suggests that genetically proxied activation of glucagon-like peptide-1 receptor is associated with a lower risk of schizophrenia. GLP1R is implicated in schizophrenia pathogenesis, and its agonists may exert potential benefits through weight management. Our study provides useful information for understanding the neuropsychiatric effects of GLP1RA, which may contribute to refining future research designs and guiding clinical management. Moreover, our findings could have significant implications for overweight individuals at high risk of schizophrenia when selecting weight-loss medications. Future research should further investigate the potential mechanisms underlying the relationship between GLP1RA and schizophrenia. Full article

Background/Objectives: Globally, there has been an increase in the prevalence of anxiety and depression among university students, and medical students are no exception. Medical students are especially susceptible to these mental health challenges, primarily due to multifaceted stressors, which can significantly impact their academic achievements and future career. There is a pressing need for comprehensive research that not only investigates the prevalence of anxiety and depression among medical students but also explores strategies for developing effective mental health interventions and support systems that can enhance the well-being of medical students. Therefore, this study aimed to identify the prevalence and severity of anxiety and depression among medical students at a university in South Africa, evaluating the association of socio-demographic, student, and clinical variables with total general anxiety disorder (GAD-7) and patient health questionnaire (PHQ-9) scores. Methods: A survey-based quantitative cross-sectional study was conducted with 208 medical undergraduate students at a South African university. Participants who provided written consent completed GAD-7 and PHQ-9 questionnaires together with socio-demographic, student, and clinical variable information. The relationship between socio-demographic, student, and clinical variables and total GAD-7 and PHQ-9 scores was determined using the Mann–Whitney U test and Kruskal–Wallis H test. Correlation analysis was used to establish the relationship between total anxiety and depression scores. The threshold for statistical significance was set at p ≤ 0.05. Results: More than half of the participants were female (n = 130; 62.5%), single (n = 123; 59.1%), and belonged to the Pedi ethnic group. A majority of the students were Christian (n = 183; 88.0%), received a bursary (n = 183; 88.0%), and had a rural background (n = 155; 74.5%). However, a small percentage of students reported a history of psychiatric and chronic illnesses (n = 26; 12.5%) and previously received professional psychological support (n = 38; 18.3%). In this study, 38% (n = 79) of the participants reported GAD and 67.8% (n = 141) reported symptoms of depression. Significant associations (p <0.05) were observed between variables such as year of study, repeating a module, and history of psychiatric illness with total GAD-7 and PHQ-9 scores. Correlation analysis revealed a moderate positive correlation (r_s = 0.400, df = 206, p < 0.001) between total GAD-7 and PHQ-9 scores. Conclusions: This study identified a high level of depression and anxiety among medical students and found a positive correlation between anxiety and depression scores. Addressing these mental health challenges is crucial not only for the well-being of the students but also for the future of healthcare, as the mental health of medical professionals directly impacts patient care. Full article