Longitudinal Association between Stressful Life Events and Suicidal Ideation in Adults with Major Depression Disorder: The Mediating Effects of Insomnia Symptoms.

Stressful life events (SLEs) and suicidal ideation (SI) are prevalent in persons with major depression disorder (MDD). Less is known about the underlying role of insomnia symptoms in the association between SLEs and SI. This three-wave prospective cohort study sought to investigate the longitudinal association among SLEs, insomnia symptoms, and SI in persons with MDD. The study population included 511 persons with MDD (mean [SD] age, 28.7 [6.7] years; 67.1% were females). Generalized estimated equations (GEEs) were utilized to explore prospective association among exposure of SLEs, insomnia symptoms, and SI. Additionally, a structural equation model (SEM) was employed to estimate the longitudinal mediating effect of insomnia symptoms in the relationship between SLEs and SI. Our study demonstrated that cumulative SLEs were determined to be longitudinally associated with SI in persons with MDD. We further observed that the association between SLEs and SI was significantly mediated by insomnia symptoms. Clinicians assessing persons with MDD, especially those with the history of SLE, could carefully evaluate and promptly treat insomnia symptoms as part of personalized assessment of their depressive illness, thereby achieving early prevention and intervention for suicidal behaviors in persons with MDD.

Technical Report: Efficacy and Safety of Low-Intensity Transcranial Magnetic Stimulation in the Remission of Depressive Symptoms in Patients With Treatment-Resistant Depression in Mexico.

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique that induces action potentials in the stimulated cortical area and has been approved by the Food and Drug Administration (FDA) for the treatment of major depressive disorder (MDD). The prevalence of MDD in Mexico almost tripled after the COVID-19 pandemic. In this study, we evaluated the safety and therapeutic effects of low-intensity TMS (Li-TMS) - characterized by inducing electric currents below the action potential threshold on the cerebral cortex - in 41 subjects diagnosed with treatment-resistant depression (TRD). A Li-TMS device dispensed repetitive magnetic pulses at 30 mT for 60 minutes during 20 sessions (once daily from Monday to Saturday) with the theta burst pattern. Our results suggest that Li-TMS is a safe therapy with antidepressant effects, demonstrated by the decrease in Beck Depression Inventory (BDI) scores and lessening of depressive symptoms.

TanhReLU -based convolutional neural networks for MDD classification.

Major Depression Disorder (MDD), a complex mental health disorder, poses significant challenges in accurate diagnosis. In addressing the issue of gradient vanishing in the classification of MDD using current data-driven electroencephalogram (EEG) data, this study introduces a TanhReLU-based Convolutional Neural Network (CNN). By integrating the TanhReLU activation function, which combines the characteristics of the hyperbolic tangent (Tanh) and rectified linear unit (ReLU) activations, the model aims to improve performance in identifying patterns associated with MDD while alleviating the issue of model overfitting and gradient vanishing. Experimental results demonstrate promising outcomes in the task of MDD classification upon the publicly available EEG data, suggesting potential clinical applications.

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia.

PURPOSE: Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia. METHODS: The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods. RESULTS: The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups. CONCLUSIONS: Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Unlocking new avenues for neuropsychiatric disease therapy: the emerging potential of Peroxisome proliferator-activated receptors as promising therapeutic targets.

RATIONALE: Peroxisome proliferator-activated receptors (PPARs) are transcription factors that regulate various physiological processes such as inflammation, lipid metabolism, and glucose homeostasis. Recent studies suggest that targeting PPARs could be beneficial in treating neuropsychiatric disorders by modulating neuronal function and signaling pathways in the brain. PPAR-α, PPAR-δ, and PPAR-γ have been found to play important roles in cognitive function, neuroinflammation, and neuroprotection. Dysregulation of PPARs has been associated with neuropsychiatric disorders like bipolar disorder, schizophrenia, major depression disorder, and autism spectrum disorder. The limitations and side effects of current treatments have prompted research to target PPARs as a promising novel therapeutic strategy. Preclinical and clinical studies have shown the potential of PPAR agonists and antagonists to improve symptoms associated with these disorders. OBJECTIVE: This review aims to provide an overview of the current understanding of PPARs in neuropsychiatric disorders, their potential as therapeutic targets, and the challenges and future directions for developing PPAR-based therapies. METHODS: An extensive literature review of various search engines like PubMed, Medline, Bentham, Scopus, and EMBASE (Elsevier) databases was carried out with the keywords "PPAR, Neuropsychiatric disorders, Oxidative stress, Inflammation, Bipolar Disorder, Schizophrenia, Major depression disorder, Autism spectrum disorder, molecular pathway". RESULT & CONCLUSION: Although PPARs present a hopeful direction for innovative therapeutic approaches in neuropsychiatric conditions, additional research is required to address obstacles and convert this potential into clinically viable and individualized treatments.

Factors affecting major depression in Iran: a mixed-method study.

Depression is a major cause of disability and, if left untreated, can increase the risk of suicide. Evidence on the determinants of depression is incomplete, making it challenging to interpret results across studies. This study aims to identify the social, economic, environmental, political, and technological factors influencing the great recession in Iran. The study was conducted in two parts. The first step involved a literature review to identify the factors, using PubMed, Scopus, and Web of Science for the search. The reference lists of all identified articles were reviewed to find relevant studies, and the extracted information was summarized and reported descriptively. The second steps involved compiling and consulting 14 experts from different fields, using a framework analysis method. Twenty-four articles were used as primary sources of information, and a total of 28 factors were found to exist. After removing duplicates and related factors, 19 of these were subsequently declared as factors, resulting in a total of 36 determinants being identified. Most of these factors belong to the social category. The health policies implemented have a significant impact on disease risk factors and ultimately their occurrence. Political decisions and policy-making processes play a crucial role in all areas, particularly in addressing disease risk factors. Severe depression can disrupt all aspects of the healthcare system, underscoring the importance of access to care. Policies concerning physical education, transportation, nutrition, employment, green spaces, recreational facilities, and tobacco are vital in this context. The influence of health policies on disease risk factors and disease occurrence is profound. Severe depression can have far-reaching effects on the healthcare system, emphasizing the critical need for access to care. The formulation of policies to combat depression must be thoroughly evaluated in terms of economic, political, social, technological, and environmental factors. The findings suggest that addressing social inequalities and emphasizing the role of political action, as highlighted by the social determinants of health, should be top priorities in addressing depression. Efforts to prevent depression should incorporate ecological approaches that consider the impact of the socioeconomic environment on depressive symptoms.

Unraveling the molecular basis of cannabidiolic acid methyl Ester's anti-depressive effects in a rat model of treatment-resistant depression.

Major depressive disorder (MDD) stands as a significant cause of disability globally. Cannabidiolic Acid-Methyl Ester (CBDA-ME) (EPM-301, HU-580), a derivative of Cannabidiol, demonstrates immediate antidepressant-like effects, yet it has undergone only minimal evaluation in psychopharmacology. Our goal was to investigate the behavioral and potential molecular mechanisms associated with the chronic oral administration of this compound in the Wistar Kyoto (WKY) genetic model of treatment-resistant depression. Male WKY rats were subjected to behavioral assessments before and after receiving chronic (14-day) oral doses of CBDA-ME (0.5 mg/kg), 15 mg/kg of imipramine or vehicle. At the end of the study, plasma corticosterone levels and mRNA expression of various genes in the medial Prefrontal Cortex and Hippocampus were measured. Behavioral outcomes from CBDA-ME treatment indicated an antidepressant-like effect similar to imipramine, as oral ingestion reduced immobility and increased swimming duration in the Forced Swim Test. Neither treatment influenced locomotion in the Open Field Test nor preference in the Saccharin Preference Test. The behavioral impact in WKY rats coincided with reduced corticosterone serum levels, upregulated mRNA expression of Cannabinoid receptor 1, Fatty Acid Amide Hydrolase, and Corticotropin-Releasing Hormone Receptor 1, alongside downregulation of the Serotonin Transporter in the hippocampus. Additionally, there was an upregulation of CB1 mRNA expression and downregulation of Brain-Derived Neurotrophic Factor in the mPFC. These findings contribute to our limited understanding of the antidepressant effects of CBDA-ME and shed light on its potential psychopharmacological mechanisms. This discovery opens up possibilities for utilizing cannabinoids in the treatment of major depressive disorder and related conditions.

Advances in biosensors for major depressive disorder diagnostic biomarkers.

Depression is one of the most common mental disorders and is mainly characterized by low mood or lack of interest and pleasure. It can be accompanied by varying degrees of cognitive and behavioral changes and may lead to suicide risk in severe cases. Due to the subjectivity of diagnostic methods and the complexity of patients' conditions, the diagnosis of major depressive disorder (MDD) has always been a difficult problem in psychiatry. With the discovery of more diagnostic biomarkers associated with MDD in recent years, especially emerging non-coding RNAs (ncRNAs), it is possible to quantify the condition of patients with mental illness based on biomarker levels. Point-of-care biosensors have emerged due to their advantages of convenient sampling, rapid detection, miniaturization, and portability. After summarizing the pathogenesis of MDD, representative biomarkers, including proteins, hormones, and RNAs, are discussed. Furthermore, we analyzed recent advances in biosensors for detecting various types of biomarkers of MDD, highlighting representative electrochemical sensors. Future trends in terms of new biomarkers, new sample processing methods, and new detection modalities are expected to provide a complete reference for psychiatrists and biomedical engineers.

The causal relationship between major depression disorder and thyroid diseases: A Mendelian randomization study and mediation analysis.

BACKGROUND: Studies have been conducted on the relationship between depression and thyroid diseases and function, its causal relationship remains unclear. METHODS: Using summary statistics of genome-wide association studies of European and East Asian ancestry, we conducted 2-sample bidirectional Mendelian randomization to estimate the association between MDD and thyroid function (European: normal range TSH, T4, T3, fT4, TPOAb levels and TPOAb-positives; East Asian: T4) and thyroid diseases (hypothyroidism, hyperthyroidism, and Hashimoto's thyroiditis), and used Mediation analysis to evaluate potential mediators (alcohol intake, antidepressant) of the association and calculate the mediated proportions. RESULTS: It was observed a significant causal association between MDD on hypothyroidism (P = 8.94 × 10-5), hyperthyroidism (P = 8.68 × 10-3), and hashimoto's thyroiditis (P = 3.97 × 10-5) among European ancestry, which was mediated by Alcohol intake (alcohol intake versus 10 years previously for hypothyroidism (P = 0.026), hashimoto's thyroiditis (P = 0.042), and alcohol intake frequency for hypothyroidism (P = 0.015)) and antidepressant (for hypothyroidism (P = 0.008), hashimoto's thyroiditis (P = 0.010)), but not among East Asian ancestry (PMDD-hypothyroidism = 0.016, but ß direction was different; PMDD-hyperthyroidism = 0.438; PMDD-hashimoto's thyroiditis = 0.496). There was no evidence for bidirectional causal association between thyroid function mentioned above and MDD among both ancestry (all P > 0.05). CONCLUSION: We importantly observed a significant causal association between MDD on risk of hypothyroidism, hyperthyroidism, and hashimoto's thyroiditis among European ancestry, and Alcohol intake and antidepressant as mediators for prevention of hypothyroidism, hashimoto's thyroiditis attributable to MDD.

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.

BACKGROUND: Major depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods for accurately predicting MDD in patients with NT1. OBJECTIVE: This study utilized machine learning (ML) algorithms to identify critical variables and developed the prediction model for predicting MDD in patients with NT1. METHODS: The study included 267 NT1 patients from four sleep centers. The diagnosis of comorbid MDD was based on Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5). ML models, including six full models and six compact models, were developed using a training set. The performance of these models was compared in the testing set, and the optimal model was evaluated in the testing set. Various evaluation metrics, such as Area under the receiver operating curve (AUC), precision-recall (PR) curve and calibration curve were employed to assess and compare the performance of the ML models. Model interpretability was demonstrated using SHAP. RESULT: In the testing set, the logistic regression (LG) model demonstrated superior performance compared to other ML models based on evaluation metrics such as AUC, PR curve, and calibration curve. The top eight features used in the LG model, ranked by feature importance, included social impact scale (SIS) score, narcolepsy severity scale (NSS) score, total sleep time, body mass index (BMI), education years, age of onset, sleep efficiency, sleep latency. CONCLUSION: The study yielded a straightforward and practical ML model for the early identification of MDD in patients with NT1. A web-based tool for clinical applications was developed, which deserves further verification in diverse clinical settings.

Global prevalence of major depressive disorder in LGBTQ+ samples: A systematic review and meta-analysis of epidemiological studies.

BACKGROUND: LGBTQ+ populations have been reported to have higher rates of depression compared with their heterosexual peers. Such data provided us the impetus to conduct a meta-analysis on the worldwide prevalence of major depressive disorder (MDD) in LGBTQ+ populations and moderating factors that contributed to differences in prevalence estimates between studies. METHODS: A systematic literature search was performed in major international (PubMed, PsycINFO, Web of Science, EMBASE) and Chinese (Chinese Nation Knowledge Infrastructure (CNKI) and WANFANG) databases from dates of inception to 10 December 2021. RESULTS: 48 articles comprising 4,616,903 individuals were included in the meta-analysis. The overall prevalence of MDD was 32.2 % (95%CI: 30.8-33.6 %, I2 = 99.6 %, τ2 = 0.284). MDD prevalence was higher in the LGBTQ+ samples from the United States than other countries, though the difference was not significant in moderator analyses. Moderator analyses indicated point and lifetime prevalence of MDD were significantly higher than estimates based on the past year (Q = 6.270, p = 0.043). Furthermore, studies that relied on convenience sampling had a higher prevalence of MDD than those based on other sampling methods (Q = 8.159, p = 0.017). In meta-regression analyses, mean age (B = 0.03, z = 9.54, p < 0.001) and study quality assessment score (B = 0.24, z = 67.64, p < 0.001) were positively associated with pooled prevalence of MDD while mediation data of year of study (B = -0.08, z = -72.55, p < 0.001) and sample size (B = -1.46, z = -37.83, p < 0.001) were negatively associated with pooled prevalence of MDD in LGBTQ+ samples. CONCLUSIONS: MDD is common among in LGBTQ+ individuals. Considering the negative consequences MDD has on daily life and well-being, appropriate prevention and treatment measures should be provided to vulnerable members of these populations. The findings of this meta-analysis could facilitate identifying at-risk subgroups, developing relevant health policy for LGBTQ+ individuals and allocating health resources from an intersectionality perspective.

Coding of Childhood Psychiatric and Neurodevelopmental Disorders in Electronic Health Records of a Large Integrated Health Care System: Validation Study.

Background: Mental, emotional, and behavioral disorders are chronic pediatric conditions, and their prevalence has been on the rise over recent decades. Affected children have long-term health sequelae and a decline in health-related quality of life. Due to the lack of a validated database for pharmacoepidemiological research on selected mental, emotional, and behavioral disorders, there is uncertainty in their reported prevalence in the literature. objectives: We aimed to evaluate the accuracy of coding related to pediatric mental, emotional, and behavioral disorders in a large integrated health care system's electronic health records (EHRs) and compare the coding quality before and after the implementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding as well as before and after the COVID-19 pandemic. Methods: Medical records of 1200 member children aged 2-17 years with at least 1 clinical visit before the COVID-19 pandemic (January 1, 2012, to December 31, 2014, the ICD-9-CM coding period; and January 1, 2017, to December 31, 2019, the ICD-10-CM coding period) and after the COVID-19 pandemic (January 1, 2021, to December 31, 2022) were selected with stratified random sampling from EHRs for chart review. Two trained research associates reviewed the EHRs for all potential cases of autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), major depression disorder (MDD), anxiety disorder (AD), and disruptive behavior disorders (DBD) in children during the study period. Children were considered cases only if there was a mention of any one of the conditions (yes for diagnosis) in the electronic chart during the corresponding time period. The validity of diagnosis codes was evaluated by directly comparing them with the gold standard of chart abstraction using sensitivity, specificity, positive predictive value, negative predictive value, the summary statistics of the F-score, and Youden J statistic. κ statistic for interrater reliability among the 2 abstractors was calculated. Results: The overall agreement between the identification of mental, behavioral, and emotional conditions using diagnosis codes compared to medical record abstraction was strong and similar across the ICD-9-CM and ICD-10-CM coding periods as well as during the prepandemic and pandemic time periods. The performance of AD coding, while strong, was relatively lower compared to the other conditions. The weighted sensitivity, specificity, positive predictive value, and negative predictive value for each of the 5 conditions were as follows: 100%, 100%, 99.2%, and 100%, respectively, for ASD; 100%, 99.9%, 99.2%, and 100%, respectively, for ADHD; 100%, 100%, 100%, and 100%, respectively for DBD; 87.7%, 100%, 100%, and 99.2%, respectively, for AD; and 100%, 100%, 99.2%, and 100%, respectively, for MDD. The F-score and Youden J statistic ranged between 87.7% and 100%. The overall agreement between abstractors was almost perfect (κ=95%). Conclusions: Diagnostic codes are quite reliable for identifying selected childhood mental, behavioral, and emotional conditions. The findings remained similar during the pandemic and after the implementation of the ICD-10-CM coding in the EHR system.

Characterizing Major Depressive Disorder (MDD) using alpha-band activity in resting-state electroencephalogram (EEG) combined with MATRICS Consensus Cognitive Battery (MCCB).

BACKGROUND: The diagnosis of major depressive disorder (MDD) is commonly based on the subjective evaluation by experienced psychiatrists using clinical scales. Hence, it is particularly important to find more objective biomarkers to aid in diagnosis and further treatment. Alpha-band activity (7-13 Hz) is the most prominent component in resting electroencephalogram (EEG), which is also thought to be a potential biomarker. Recent studies have shown the existence of multiple sub-oscillations within the alpha band, with distinct neural underpinnings. However, the specific contribution of these alpha sub-oscillations to the diagnosis and treatment of MDD remains unclear. METHODS: In this study, we recorded the resting-state EEG from MDD and HC populations in both open and closed-eye state conditions. We also assessed cognitive processing using the MATRICS Consensus Cognitive Battery (MCCB). RESULTS: We found that the MDD group showed significantly higher power in the high alpha range (10.5-11.5 Hz) and lower power in the low alpha range (7-8.5 Hz) compared to the HC group. Notably, high alpha power in the MDD group is negatively correlated with working memory performance in MCCB, whereas no such correlation was found in the HC group. Furthermore, using five established classification algorithms, we discovered that combining alpha oscillations with MCCB scores as features yielded the highest classification accuracy compared to using EEG or MCCB scores alone. CONCLUSIONS: Our results demonstrate the potential of sub-oscillations within the alpha frequency band as a potential distinct biomarker. When combined with psychological scales, they may provide guidance relevant for the diagnosis and treatment of MDD.

Impact of Patient-Reported Allergies on Post-operative Complications and Healthcare Utilization Following Carpal Tunnel Release.

INTRODUCTION: Open carpal tunnel release (O-CTR) is associated with high patient satisfaction and low complication rates. Risk factors for complications are well-established. Recent studies have found that patient-reported allergies (PRAs) and psychiatric comorbidities may be associated with increased complication rates. The impact of these factors after elective hand surgery has not been evaluated. This study sought to identify whether PRAs and psychiatric comorbidities are associated with complications after O-CTR and to evaluate their association with prolonged follow-up and the need for post-operative occupational therapy (OT). METHODS: Patient demographics, PRAs, Patient Health Questionnaire-2 score, Charlson Comorbidity Index, Carpal Tunnel Symptoms-6 score, postoperative complications, OT utilization, and time to final follow-up were recorded for patients who underwent elective O-CTR between 2014 and 2022. Multivariable binomial logistic regression analysis was used to determine pre-operative variables associated with increased risk for complication. RESULTS: About 250 patients met the inclusion criteria. Fifty-one (20.4%) patients developed minor complications, including scar tenderness (N=34, 13.6%), superficial wound dehiscence (N=9, 3.6%), and superficial infection (N=8, 3.2%). There were no major complications. Independent risk factors for complications included PRAs (OR 1.80, p<0.01) and PHQ-2 score (OR 1.39, p=0.04). Five or more PRAs and PHQ-2 score ≥3 are significant independent risk factors for increased post-operative complications. Increased PRAs and PHQ-2 scores were associated with longer follow-up (p=0.01 and p<0.01, respectively) but not increased OT utilization. CONCLUSION: An increased number of PRAs and higher PHQ-2 scores are significant, independent risk factors for minor complications following O-CTR. Risk adjustment and peri-operative counseling should incorporate and account for these variables.

Effect of Vortioxetine in Comparison to Fluoxetine on Metabolic Parameters in Patients With Depressive Disorder: A Randomized Controlled Trial.

Background Major depressive disorder (MDD) is a debilitating mood disorder that increases the risk of metabolic syndrome (MS), emphasizing the need for mental and physical health treatments. Although many studies have linked atypical antipsychotics to metabolic disturbances, there is limited evidence linking selective serotonin reuptake inhibitor use to MS. This study aimed to assess the risk of MS among patients with MDD who were administered vortioxetine and fluoxetine. Methodology This was a prospective, open-label, randomized controlled trial conducted in the psychiatry department. Using computer-generated random numbers, the physician assigned fluoxetine 20 mg or vortioxetine 10 mg and recorded MS parameters at baseline and each visit (4, 8, 12, 16, 20, and 24 weeks). This study was registered with CTRI (CTRI/2021/07/034892). Results A total of 122 participants were allocated randomly to the following two groups: group A (n = 60) and group B (n = 62). An independent-sample t-test showed a significant improvement in fasting plasma glucose (FPG) at week eight (p = 0.005), triglycerides (TGs) at week 16 (p = 0.005), high-density lipoprotein (HDL) at week 20 (p = 0.005), and waist circumference at week 24 (p = 0.005) in group A compared to group B. However, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were not significantly associated with either group (p = 0.126 and p = 0.793, respectively). Overall depression remission (Hamilton Depression Rating Scale (HAM-D)) and medication adherence rating scale scores were similar between groups (p = 0.337 and 0.325, respectively). Furthermore, most adverse drug reactions were possibly associated with the study drugs. Conclusions In comparison to group B, group A showed significant improvements in FPG, HDL, and waist circumference more effectively; however, both groups led to higher TG levels, with non-significant numerical improvements observed in SBP and DBP in both groups. In addition, both treatment groups reduced the HAM-D score and had a similar MDD remission rate.

Upregulation of proBDNF/p75NTR signaling in immune cells and its correlation with inflammatory markers in patients with major depression.

ProBDNF is the precursor protein of brain-derived neurotrophic factor (BDNF) expressed in the central nervous system and peripheral tissues. Previous studies showed that the blood levels of both proBDNF and p75 neurotrophic receptors (p75NTR) in major depressive disorder (MDD) were increased, but which blood cell types express proBDNF and its receptors is not known. Furthermore, the relationship between proBDNF/p75NTR and inflammatory cytokines in peripheral blood of MDD is unclear. Peripheral blood mononuclear cells (PBMCs) and serum were obtained from depressive patients (n = 32) and normal donors (n = 20). We examined the expression of proBDNF and inflammatory markers and their correlative relationship in patients with major depression. Using flow cytometry analysis, we examined which blood cells express proBDNF and its receptors. Finally, the role of proBDNF/p75NTR signal in inflammatory immune activity of PBMCs was verified in vitro experiments. Inflammatory cytokines in PBMC from MDD patients were increased and correlated with the major depression scores. The levels of IL-1ß and IL-10 were also positively correlated with the major depression scores, while the levels of TNF-α and IL-6 were negatively correlated with the major depression scores. Intriguingly, the levels of sortilin were positively correlated with IL-1ß. Q-PCR and Western blots showed proBDNF, p75NTR, and sortilin levels were significantly increased in PBMCs from MDD patients compared with that from the normal donors. Flow cytometry studies showed that proBDNF and p75NTR were present mainly in CD4+ and CD8+ T cells. The number of proBDNF and p75NTR positive CD4+ and CD8+ T cells from MDD patients was increased and subsequently reversed after therapeutic management. Exogenous proBDNF protein or p75ECD-Fc treatment of cultured PBMC affected the release of inflammatory cytokines in vitro. ProBDNF promoted the expression of inflammatory cytokines, while p75ECD-Fc inhibited the expression of inflammatory cytokines. Given there was an inflammatory response of lymphocytes to proBDNF, it is suggested that proBDNF/p75NTR signaling may upstream inflammatory cytokines in MDD. Our data suggest that proBDNF/p75NTR signaling may not only serve as biomarkers but also may be a potential therapeutic target for MDD.

Improvement of astrocytic gap junction involves the anti-depressive effect of celecoxib through inhibition of NF-κB.

CONTEXT: Celecoxib, a selective cyclooxygenase-2 (COX-2) inhibitor, has been shown to exhibit anti-depressive effects in clinical trials. However, the direct mechanism underlying its effect on neuroinflammation remains unclear. Neuroinflammatory reaction from astrocytes leads to depression, and our previous study found that gap junction disorder between astrocytes aggravated neuroinflammatory reaction in depressed mice. OBJECTIVE: To investigate the potential mechanism of celecoxib's effects on astrocytic gap junctions during the central nervous inflammation-induced depression. MATERIALS & METHODS: Stereotaxic injection of lipopolysaccharide (LPS) into the prefrontal cortex (PFC) to establish a model of major depressive disorder (MDD). Celecoxib was administrated into PFC 15 min after LPS injection. The depressive performance was tested by tail suspension test and forced swimming test, and the levels of proinflammation cytokines were determined at mRNA and protein levels. Resting-state functional connection (rsFC) was employed to assess changes in the default mode network (DMN). Additionally, astrocytic gap junctions were also determined by lucifer yellow (LY) diffusion and transmission electron microscope (TEM), and the expression of connexin 43 (Cx43) was measured by western blotting, quantitative polymerase chain reaction, and immunofluorescence. RESULTS: LPS injection induced significant depressive performance, which was ameliorated by celecoxib treatment. Celecoxib also improved rsFC in the DMN. Furthermore, celecoxib improved astrocytic gap junctions as evidenced by increased LY diffusion, shortened gap junction width, and normalized levels of phosphorylated Cx43. Celecoxib also blocked the phosphorylation of p65, and inhibition of p65 abolished the improvement of Cx43. DISCUSSION & CONCLUSION: Anti-depressive effects of celecoxib are mediated, at least in part, by the inhibition of nuclear factor- kappa B (NF-κB) and the subsequent improvement of astrocytic gap junction function.

Association between alopecia areata, anxiety, and depression: Insights from a bidirectional two-sample Mendelian randomization study.

BACKGROUND: As research progresses, there has been growing interest in the association between Alopecia areata (AA) and anxiety, as well as depression. However, there have been limited reports on the genetic variation level of AA in relation to mental disorders. METHOD: We performed large-scale Two sample Mendelian randomization (MR) analyses to examine whether there is a association between AA with anxiety and depression. The data utilized for AA analysis were sourced from the FinnGen release 9 databases, including 682 cases and 361,822 controls. Summary statistics for major depression disorder (MDD) were obtained from a genome-wide meta-analysis dataset, incorporating 170,756 cases and 329,443 controls. The anxiety disorder data was conducted by the Anxiety Neuro Genetics Study Consortium, including 5580 cases and 11,730 controls. We employed four distinct approaches, including MR-Egger, weighted median, random-effect inverse variance weighted (IVW), and weighted mode, to conduct the MR analysis. RESULTS: Genetic liability to AA was associated with an increased risk of Major depression disorder (MDD) and anxiety demonstrated an odds ratio (OR) of 1.01 (ßivw = 0.011, PIVW = 0.023) and OR of 1.16 (ßivw = 0.150, PIVW = 0.002). Upon conducting the Bonferroni correction, the P-values were 0.046 and 0.004, respectively. For reverse analysis, we observed no significant association between anxiety and MDD with the risk of AA. CONCLUSIONS: Our research unveil a unidirectional causal association whereby AA exerts a risk effect against MDD and anxiety, which serves as a valuable complement to prior meta-analyses, enriching the existing body of knowledge on the subject matter.

Orbitofrontal and striatal metabolism, volume, thickness and structural connectivity in relation to social anhedonia in depression: A multimodal study.

BACKGROUND: Social anhedonia is common within major depressive disorder (MDD) and associated with worse treatment outcomes. The orbitofrontal cortex (OFC) is implicated in both reward (medial OFC) and punishment (lateral OFC) in social decision making. Therefore, to understand the biology of social anhedonia in MDD, medial/lateral OFC metabolism, volume, and thickness, as well as structural connectivity to the striatum, amygdala, and ventral tegmental area/nucleus accumbens were examined. A positive relationship between social anhedonia and these neurobiological outcomes in the lateral OFC was hypothesized, whereas an inverse relationship was hypothesized for the medial OFC. The association between treatment-induced changes in OFC neurobiology and depression improvement were also examined. METHODS: 85 medication-free participants diagnosed with MDD were assessed with Wisconsin Schizotypy Scales to assess social anhedonia and received pretreatment simultaneous fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI), including structural and diffusion. Participants were then treated in an 8-week randomized placebo-controlled double-blind course of escitalopram. PET/MRI were repeated following treatment. Metabolic rate of glucose uptake was quantified from dynamic FDG-PET frames using Patlak graphical analysis. Structure (volume and cortical thickness) was quantified from structural MRI using Freesurfer. To assess structural connectivity, probabilistic tractography was performed on diffusion MRI and average FA was calculated within the derived tracts. Linear mixed models with Bonferroni correction were used to examine the relationships between variables. RESULTS: A significantly negative linear relationship between pretreatment social anhedonia score and structural connectivity between the medial OFC and the amygdala (estimated coefficient: -0.006, 95 % CI: -0.0108 - -0.0012, p-value = 0.0154) was observed. However, this finding would not survive multiple comparisons correction. No strong evidence existed to show a significant linear relationship between pretreatment social anhedonia score and metabolism, volume, thickness, or structural connectivity to any of the regions examined. There was also no strong evidence to suggest significant linear relationships between improvement in depression and percent change in these variables. CONCLUSIONS: Based on these multimodal findings, the OFC likely does not underlie social anhedonia in isolation and therefore should not be the sole target of treatment for social anhedonia. This is consistent with previous reports that other areas of the brain such as the amygdala and the striatum are highly involved in this behavior. Relatedly, amygdala-medial OFC structural connectivity could be a future target. The results of this study are crucial as, to our knowledge, they are the first to relate structure/function of the OFC with social anhedonia severity in MDD. Future work may need to involve a whole brain approach in order to develop therapeutics for social anhedonia.

Impulsivity, decision-making, and risk behavior in bipolar disorder and major depression from bipolar multiplex families.

OBJECTIVES: Bipolar disorder (BD) and major depressive disorder (MDD) are characterized by specific alterations of mood. In both disorders, alterations in cognitive domains such as impulsivity, decision-making, and risk-taking have been reported. Identification of similarities and differences of these domains in BD and MDD could give further insight into their etiology. The present study assessed impulsivity, decision-making, and risk-taking behavior in BD and MDD patients from bipolar multiplex families. METHODS: Eighty-two participants (BD type I, n = 25; MDD, n = 26; healthy relatives (HR), n = 17; and healthy controls (HC), n = 14) underwent diagnostic interviews and selected tests of a cognitive battery assessing neurocognitive performance across multiple subdomains including impulsivity (response inhibition and delay aversion), decision-making, and risk behavior. Generalized estimating equations (GEEs) were used to analyze whether the groups differed in the respective cognitive domains. RESULTS: Participants with BD and MDD showed higher impulsivity levels compared to HC; this difference was more pronounced in BD participants. BD participants also showed lower inhibitory control than MDD participants. Overall, suboptimal decision-making was associated with both mood disorders (BD and MDD). In risk-taking behavior, no significant impairment was found in any group. LIMITATIONS: As sample size was limited, it is possible that differences between BD and MDD may have escaped detection due to lack of statistical power. CONCLUSIONS: Our findings show that alterations of cognitive domains-while present in both disorders-are differently associated with BD and MDD. This underscores the importance of assessing such domains in addition to mere diagnosis of mood disorders.