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BackgroundThe etiopathogenesis of major depressive disorder （MDD） is strongly associated with neuroinflammation. MDD is a highly heterogeneous psychiatric disorder， and the disease subtyping is an essential step for the identification of biological markers. The presence of psychomotor retardation seriously affects the prognosis of MDD， whereas the underlying mechanism is not yet completely clear. A potential involvement of granulocyte colony-stimulating factor （G-CSF） and macrophage colony-stimulating factor （M-CSF） in the pathogenesis of MDD with psychomotor retardation has been suggested in previous studies， but little detailed research has been completed.ObjectiveTo analyze the correlation of plasma G-CSF and M-CSF levels with psychomotor retardation in patients with MDD， and to explore the potential biological underpinnings of psychomotor retardation in MDD.MethodsA total of 50 MDD patients who met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） and attended the outpatient clinics of Shanghai Mental Health Center from April 2018 to April 2019 were included. The severity of symptoms was assessed using the Hamilton Depression Scale-17 item （HAMD-17）. According to the retardation factor in HAMD-17， patients with a score of ≥8 were included in retardation group （n=22）， and those with a score below 8 were included in non-retardation group （n=28）. Another 22 age- and sex-matched healthy controls were concurrently recruited. Plasma G-CSF and M-CSF levels were measured in all subjects using Luminex liquid suspension chip technology. Spearman correlation analysis was adopted to verify the correlation of retardation factor score in HAMD-17 with plasma G-CSF and M-CSF levels in MDD patients.ResultsPlasma G-CSF levels were decreased in MDD patients compared with healthy controls ［57.34（39.24， 83.15）pg/mL vs. 71.47（61.20， 79.99）pg/mL， Z=-2.098， P

People with an evening chronotype have an increased risk of experiencing a major depressive disorder (MDD). It is unclear if this effect is predominantly related to the initial development of MDD or also present in recurrent episodes. The current study aimed to investigate if the association between chronotype and depressive severity in MDD patients is comparable in MDD patients with first and recurrent episodes. 386 MDD patients, 70.7% females and aged between 16 and 64, participated in the study. The Morningness – Eveningness Questionnaire (MEQ), Pittsburgh Sleep Quality Index (PSQI), Multidimensional Fatigue Inventory (MFI20), and Quick Inventory of Depressive Symptomatology (QIDS-SR16) were administered to participants to determine chronotype, sleep quality, fatigue level, and depressive severity, respectively. Multivariate regression models were utilized to analyze how chronotype influences depressive severity. The study showed that chronotype, sleep quality, and fatigue level were all associated with depressive severity. Eveningness significantly predicted an increase in depressive severity independently of sleep quality and fatigue level only in patients with the first episode (−0.068, p = 0.010), but not in patients with recurrent episodes (0.013, p = 0.594). Circadian-focused treatment should be considered in first-episode depression only. [ABSTRACT FROM AUTHOR]

• Depressive-like symptoms were rapidly alleviated after ketamine treatment in a CRS model. • Neuroplasticity was improved after ketamine treatment in CRS rats. • Autophagy was activated after ketamine treatment in the HB nuclear complex of CRS rats. • Ferroptosis was inhibited after ketamine treatment in the HB nuclear complex of CRS rats. Major depressive disorder is a burdensome condition with few treatment options, and traditional antidepressants are characterized by slow onset. Sub-anesthetic ketamine has rapid-onset effects for the treatment of major depressive disorder (MDD), the mechanisms of which remain elusive. In this study, we explored whether neuroplasticity, autophagy, and ferroptosis in the habenular nucleus are involved in the rapid antidepressant process of ketamine. The results showed that Chronic Restraint Stress (CRS) treated rats exhibited decreased neuroplasticity, inhibition of autophagy, and enhanced ferroptosis. Depression-like symptoms were significantly improved after ketamine treatment in CRS rats, with changes in physiological parameters. Ketamine-treated CRS rats showed a significant improvement in habenular nuclear neuroplasticity. Electron microscopy observed that ketamine triggered autophagy, with increased levels of autophagy-related proteins. Ferroptosis was inhibited by ketamine by electron microscopy, with increased FTH1 and GPX4 levels and decreased Tfr1 levels. In conclusion, our findings demonstrate that ketamine may exert rapid antidepressant effects by improving neuroplasticity, activating autophagy, and inhibiting ferroptosis in the nuclear complex. [ABSTRACT FROM AUTHOR]

Background. Sleep disturbances and benzodiazepine (BZD)/Z-drug use are common in patients with bipolar disorder (BD). Objective. To investigate the short- and long-term effects of BZD/Z-drug use during acute affective episode. Methods. Participants diagnosed with BD as well as sleep disturbance chose BZDs/Z-drugs or not at will. Manic and depressive symptoms were assessed by Mental Disorders Questionnaire (MDQ) and Quick Inventory of Depressive Symptoms (QIDS) as self-reporting surveys. The participants were assessed by trained evaluators at baseline and months 1, 3, 6, and 9. Results. 61 patients with BD combined sleep disturbances were studied. At baseline, patients who used BZDs/Z-drugs had more amount of mood stabilizers (p = 0.038), other psychotropic medications (p = 0.040), and more risk of suicide attempt (p = 0.019). The BZD/Z-drug group had a significantly higher QIDS reductive ratio as compared with the no BZD/Z-drug group at month 1; no significant differences in the variability of MDQ, QIDS reductive ratio, or recurrence rate were found between these two groups at baseline, month 1, month 3, month 6, or month 9. Conclusions. During acute affective episode, patients with BD combined sleep disturbance who took BZDs/Z-drugs tended to use more amount of mood stabilizers. Polytherapy of BZDs/Z-drugs or other psychiatric drugs could increase suicide attempt during an acute affective episode. BZD/Z-drug use, however, had a significant effect on helping depressive symptoms alleviate during affective period. [ABSTRACT FROM AUTHOR]

Objective and quantitative neuroimaging biomarkers are crucial for early diagnosis of major depressive disorder (MDD). However, previous studies using machine learning (ML) to distinguish MDD have often used small sample sizes and overlooked MDD's neural connectome and mechanism. To address these gaps, we applied Dynamic Graph Convolutional Nets (DGCNs) to a large multi-site dataset of 2317 resting state functional MRI (RS-fMRI) scans from 1081 MDD patients and 1236 healthy controls from 16 Rest-meta-MDD consortium sites. Our DGCN model combined with the personal whole brain functional connectivity (FC) network achieved an accuracy of 82.5 % (95 % CI:81.6-83.4 %, AUC:0.869), outperforming other universal ML classifiers. The most prominent domains for classification were mainly in the default mode network, fronto-parietal and cingulo-opercular network. Our study supports the stability and efficacy of using DGCN to characterize MDD and demonstrates its potential in enhancing neurobiological comprehension of MDD by detecting clinically related disorders in FC network topologies., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)

Background: Depression, anxiety and schizophrenia among older persons have become global public health challenges. However, the burden of these disorders in ageing and aged countries has not been analysed., Aims: To investigate the burden of depression, anxiety and schizophrenia among older adults in ageing and aged countries., Methods: Using data from the Global Burden of Disease Study 2019, we calculated the estimated annual percentage change (EAPC) in the age-standardised incidence rates (ASIR) and age-standardised disability-adjusted life years (DALYs) rates (ASDR) for depression, anxiety and schizophrenia of older people in ageing countries (China, India, Indonesia) and aged countries (Japan, Italy, Portugal) between 1990 and 2019. Trends in incidence and DALYs were analysed by gender and age., Results: In 2019, the highest incidence of depression, anxiety and schizophrenia in the older population in aged countries was in Japan (927 271.3 (752 552.3-1 125 796.5), 51 498.2 (37 625.7-70 487.3) and 126.0 (61.0-223.2), respectively), while the highest incidence in ageing countries was in China (5 797 556.9 (4 599 403.4-7 133 006.5), 330 256.1 (246 448.9-445 987.4) and 1067.7 (556.2-1775.9), respectively). DALYs for these disorders were similar, with the highest in Japan and China. From 1990 to 2019, the ASIR for depressive disorders decreased in aged countries but increased in ageing countries; the ASIR for anxiety disorders and schizophrenia declined in both ageing and aged countries. The ASDR for depressive disorders was consistent with the ASIR but not for anxiety disorders and schizophrenia. The ASIR for depressive disorders was higher in older women, while the opposite was observed in anxiety disorders and schizophrenia. Notably, the conditions of burden of depressive disorders, anxiety disorders and schizophrenia in the 65-70-year-old age group were the most burdensome., Conclusions: The incidence and DALYs of these three mental disorders increased while exhibiting differences between ageing and aged countries. Raising awareness about formulating health policies for preventing and treating mental disorders in the older population is necessary to reduce the future burden posed by the ageing challenge., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Inflammatory cytokines disturbance is the main result of immune dysregulation, which is widely described in major depressive disorder (MDD). However, the potential causal relationship between these two factors has not been discovered. Therefore, the purpose of this study was to investigate the causal relationship between inflammatory cytokines and MDD risk by using the two-sample Mendelian randomization (MR) analysis. Method: Two genetic instruments obtained from publicly available gene profile data were utilized for the analysis. We obtained the genetic variation data of 41 inflammatory cytokines from genome-wide association studies (GWAS) meta-analysis of 8293 individuals of Finnish descent. The MDD data, including 135,458 MDD cases and 344,901 controls, were obtained from the Psychiatric Genomics Consortium Database. For the Mendelian randomization (MR) estimation, several methods were employed, namely, MR-Egger regression, inverse-variance weighted (IVW), weighted median, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods. Result: A causal relationship was identified between the genetically proxied levels of Interleukin (IL) -18, IL-1β, and Regulated upon activation normal T cell expressed and secreted (RANTES) and the risk of MDD (OR = 0.968, 95%CI = 0.938, 0.998, p = 0.036; OR = 0.875, 95%CI = 0.787, 0.971, p = 0.012; OR = 0.947, 95%CI = 0.902, 0.995, p = 0.03; respectively). However, our Mendelian randomization (MR) estimates provided no causality of MDD on inflammatory cytokines. Conclusion: Our study elucidates the connection between inflammatory cytokines and MDD by using MR analysis, thereby enhancing our comprehension of the potential mechanisms. By identifying these associations, our findings hold substantial implications for the development of more effective treatments aimed at improving patient outcomes. However, further investigation is required to fully comprehend the exact biological mechanisms involved., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Jin, Cheng, Guan, Zheng and Zhang.)

Atypical antipsychotics are highly effective antischizophrenic medications but their clinical utility is limited by adverse metabolic sequelae. We investigated whether upregulation of macrophage migration inhibitory factor (MIF) underlies the insulin resistance that develops during treatment with the most commonly prescribed atypical antipsychotic, olanzapine. Olanzapine monotherapy increased BMI and circulating insulin, triglyceride, and MIF concentrations in drug-naive schizophrenic patients with normal MIF expression, but not in genotypic low MIF expressers. Olanzapine administration to mice increased their food intake and hypothalamic MIF expression, which led to activation of the appetite-related AMP-activated protein kinase and Agouti-related protein pathway. Olanzapine also upregulated MIF expression in adipose tissue, which reduced lipolysis and increased lipogenic pathways. Increased plasma lipid concentrations were associated with abnormal fat deposition in liver and skeletal muscle, which are important determinants of insulin resistance. Global MIF-gene deletion protected mice from olanzapine-induced insulin resistance, as did intracerebroventricular injection of neutralizing anti-MIF antibody, supporting the role of increased hypothalamic MIF expression in metabolic dysfunction. These findings uphold the potential pharmacogenomic value of MIF genotype determination and suggest that MIF may be a tractable target for reducing the metabolic side effects of atypical antipsychotic therapy.

Cross-disorder studies are identifying shared genetic variations among common mental illnesses - including schizophrenia, bipolar disorder, and major depression - which are classified as independent disorders in the current diagnostic system. These cross-disorder studies are challenging the traditional system of diagnosing mental disorders based on clinical symptoms, but it remains to be seen whether or not they will lead to an improved method of classifying psychiatric disorders that can, in turn, lead to better outcomes for individuals suffering from these conditions.