World Journal of Biological Psychiatry最新文献

Background: The evidence for repetitive transcranial magnetic stimulation (rTMS) to treat negative symptoms in schizophrenia (SCZ) is increasing, although variable response rates remain a challenge. Subject´s sex critically influences rTMS´ treatment outcomes. Females with major depressive disorder are more likely to respond to rTMS, while SCZ data is scarce.

Methods: Using data from the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial we assessed the impact of sex on rTMS´ clinical response rate from screening up to 105 days after intervention among SCZ patients. The impact of resting motor threshold (RMT) on response rates was also assessed.

Results: 157 patients received either active or sham rTMS treatment. No significant group differences were observed. Linear mixed model showed no effects on response rates (all p > 0.519). Apart from a significant sex*time interaction for the positive subscale of the positive and negative syndrome scale (PANSS) scores (p = 0.032), no other significant effects of sex on continuous PANSS scores were observed. RMT had no effect on response rate.

Conclusion: In the largest rTMS trial on the treatment of SCZ negative symptoms we did not observe any significant effect of sex on treatment outcomes. Better assessments of sex-related differences could improve treatment individualisation.

Objectives: Schizophrenia genetics is intricate, with common and rare variants' contributions not fully understood. Certain copy number variations (CNVs) elevate risk, pivotal for understanding mental disorder models. Despite CNVs' genome-wide distribution and variable gene and protein effects, we must explore beyond affected genes to interaction partners and molecular pathways.

Methods: In this study, we developed machine-readable interactive pathways to enable analysis of functional effects of genes within CNV loci and identify ten common pathways across CNVs with high schizophrenia risk using the WikiPathways database, schizophrenia risk gene collections from GWAS studies, and a gene-disease association database.

Results: For CNVs that are pathogenic for schizophrenia, we found overlapping pathways, including BDNF signalling, cytoskeleton, and inflammation. Common schizophrenia risk genes identified by different studies are found in all CNV pathways, but not enriched.

Conclusions: Our findings suggest that specific pathways - BDNF signalling - are critical contributors to schizophrenia risk conferred by rare CNVs. Our approach highlights the importance of not only investigating deleted or duplicated genes within pathogenic CNV loci, but also study their direct interaction partners, which may explain pleiotropic effects of CNVs on schizophrenia risk and offer a broader field for interventions.

Objectives: This study aims to explore the potential interconnections among gut microbiota, COVID-19 infection, depression and anxiety disorder. Additionally, it tries to assess potential therapeutic interventions that may improve the dysbiosis of gut microbiota.

Methods: To achieve these objectives, we reviewed existing literature, encompassing studies and critical reviews that intersect the domains of gut microbiota, COVID-19, depression and anxiety disorders.

Results: The findings highlight a notable correlation between the dysbiosis of gut microbiota and psychiatric symptoms in the context of COVID-19. Specifically, there is a marked reduction in the populations of bacteria that generate anti-inflammatory short-chain fatty acids (SCFAs), alongside a rise in the prevalence of gut bacterial clusters linked to inflammatory processes. Furthermore, several potential treatment strategies were summarised for improving the dysbiosis.

Conclusions: Gut microbiota plays a significant role in psychiatric symptoms during COVID-19, which has significant implications for the study and prevention of psychiatric symptoms in major epidemic diseases.

Objectives: This study compared machine learning models using unimodal imaging measures and combined multi-modal imaging measures for deep brain stimulation (DBS) outcome prediction in treatment resistant depression (TRD).

Methods: Regional brain glucose metabolism (CMRGlu), cerebral blood flow (CBF), and grey matter volume (GMV) were measured at baseline using 18F-fluorodeoxy glucose (18F-FDG) positron emission tomography (PET), arterial spin labelling (ASL) magnetic resonance imaging (MRI), and T1-weighted MRI, respectively, in 19 patients with TRD receiving subcallosal cingulate (SCC)-DBS. Responders (n = 9) were defined by a 50% reduction in HAMD-17 at 6 months from the baseline. Using an atlas-based approach, values of each measure were determined for pre-selected brain regions. OneR feature selection algorithm and the naïve Bayes model was used for classification. Leave-out-one cross validation was used for classifier evaluation.

Results: The performance accuracy of the CMRGlu classification model (84%) was greater than CBF (74%) or GMV (74%) models. The classification model using the three image modalities together led to a similar accuracy (84%0 compared to the CMRGlu classification model.

Conclusions: CMRGlu imaging measures may be useful for the development of multivariate prediction models for SCC-DBS studies for TRD. The future of multivariate methods for multimodal imaging may rest on the selection of complementing features and the developing better models.Clinical Trial Registration: ClinicalTrials.gov (#NCT01983904).

Objectives: This study sought to identify pathways affected by rat cortical RNA that were changed after treatment with fluoxetine or imipramine.

Methods: We measured levels of cortical RNA in male rats using GeneChip^® Rat Exon 1.0 ST Array after treatment with vehicle (0.9% NaCl), fluoxetine (10 mg/kg/day) or imipramine (20 mg/kg/day) for 28 days. Levels of coding and non-coding RNA in vehicle treated rats were compared to those in treated rats using ANOVA in JMP Genomics 13 and the Panther Gene Ontology Classification System was used to identify pathways involving the changed RNAs.

Results: 18,876 transcripts were detected; there were highly correlated changes in 1010 levels of RNA after both drug treatments that would principally affect the metabolism of polyamines, mRNA splicing, regulation of RAS by GAPs, neddylation and GPCR ligand binding. Using our previously published data, we compared changes in transcripts after treatment with antipsychotic and mood stabilising drugs.

Conclusions: Our study shows there are common, correlated, changes in coding and non-coding RNA in the rat cortex after treatment with fluoxetine or imipramine; we propose the pathways affected by these changes are involved in the therapeutic mechanisms of action of antidepressant drugs.

Objectives: The prevalence of generalised anxiety disorder (GAD) is high. However, the underlying mechanisms remain elusive. Proteomics techniques can be employed to assess the pathological mechanisms involved in GAD.

Methods: Twenty-two drug-naive GAD patients were recruited, their serum samples were used for protein quantification and identified using Tandem Mass Tag and Multiple Reaction Monitoring (MRM). Machine learning models were employed to construct predictive models for disease occurrence by using clinical scores and target proteins as input variables.

Results: A total of 991 proteins were differentially expressed between GAD and healthy participants. Gene Ontology analysis revealed that these proteins were significantly associated with stress response and biological regulation, suggesting a significant implication in anxiety disorders. MRM validation revealed evident disparities in 12 specific proteins. The machine learning model found a set of five proteins accurately predicting the occurrence of the disease at a rate of 87.5%, such as alpha 1B-glycoprotein, complement component 4 A, transferrin, V3-3, and defensin alpha 1. These proteins had a functional association with immune inflammation.

Conclusions: The development of generalised anxiety disorder might be closely linked to the immune inflammatory stress response.

Objectives: Corticosteroids are widely prescribed for a variety of medical conditions. Accumulating evidence suggests that their use may be associated with adverse psychiatric effects, including mania. In this systematic review, we aim to critically evaluate the existing literature on the association between corticosteroid use and the emergence of mania.

Methods: We conducted a comprehensive search of major electronic databases (PubMed, Embase, Cochrane Library) for relevant studies published up to the date of the search (12th January 2023). Inclusion criteria involve studies that investigate the association between corticosteroid use and the emergence of mania in adult patients. The primary outcome is the prevalence of (hypo)mania following corticosteroid administration. Secondary outcomes include potential risk factors, dose-response relationships, and differences among various corticosteroid formulations.

Results: The identified studies were subjected to a systematic selection process and data extraction by an independent reviewer. A total of 47 articles met the inclusion criteria for our systematic review.

Conclusion: Our findings suggest that mania is a common side-effect of corticosteroid use, particularly in prednisone equivalent doses above 40 mg. These findings hold practical significance for clinicians and provide insights into potential interventions, including careful monitoring, dose adjustments, and consideration of psychotropic medications when managing corticosteroid-induced mania.

Background: Gender plays a role in the mechanisms of depression, but fewer studies have focused on gender differences in the abnormal activation of brain regions when patients perform specific cognitive tasks.

Methods: A total of 110 major depressive disorder (MDD) patients and 106 healthy controls were recruited. The relative change in oxygen-haemoglobin (oxy-Hb) concentration during the verbal fluency task were measured by a 52-channel near-infra-red spectroscopy (NIRS) system. Differences in brain region activation between patients and healthy controls and between genders of depression patients were compared.

Results: MDD patients demonstrated significantly decreased [oxy-Hb] changes in the right inferior frontal gyrus (p = 0.043) compared to healthy controls. A marked increase in leftward functional language lateralisation in the inferior frontal gyrus was observed in the MDD group in contrast to the HC group (p = 0.039). Furthermore, female patients in the MDD group exhibited significant reductions in [oxy-Hb] changes in the right frontal region (specifically, the superior and middle frontal gyrus; p = 0.037) compared with male patients.

Conclusions: Gender impacts depression-related brain activation during cognitive tasks, potentially influencing depression's pathogenesis.

Objectives: Repetitive transcranial magnetic stimulation (rTMS) has been considered as an effective antidepressant treatment; however, the mechanism of its antidepressant effect is still unclear. Fluoxetine, a selective serotonin reuptake inhibitor antidepressant, may be neuroprotective. The objective of the present study was to evaluate the effect and underlying possible neuroprotective mechanism of rTMS and fluoxetine on abnormal behaviours in a depressive mouse model induced by chronic unpredictable mild stress (CUMS).Methods: After 28 days of CUMS exposure, mice were chronically treated with rTMS (10 Hz for 5 s per train, total 20 trains per day) and (or) fluoxetine (5 mg/kg/day, intraperitoneally) for 28 days targeting on the frontal cortex. After the behavioural tests, the protein expressions of glial fibrillary acidic protein (GFAP), brain-derived neurotrophic factor (BDNF) and tyrosine kinase B (TrkB) were measured by immunohistochemistry and (or) Western Blot.Results: The results showed rTMS and (or) fluoxetine attenuated the locomotion decrease, anxiety and depressive like behaviours in the CUMS-exposed mice.Conclusion: Our results suggest that both rTMS and fluoxetine could benefit the CUMS-induced abnormal behaviours including depressive-like behaviours, and the beneficial effects of rTMS as well as fluoxetine on depression might be partly related to their neuroprotective effect on attenuating astroglial activation and BDNF decrease.

Background: Sleep problems are commonly observed in patients with tic disorders. Nevertheless, studies have demonstrated a wide variation in the prevalence of sleep disturbances among this population. Consequently, it remains ambiguous whether sleep issues are inherently characteristic of tic disorders or are influenced by external factors.

Methods: We conducted a comprehensive search across various databases and performed a meta-analysis to determine the prevalence of sleep problems in tic disorders. Additionally, we assessed pre-existing comorbidities and associated characteristics using meta-regression analysis.

Results: After including 33 studies in the final meta-analysis, we found that the pooled prevalence of sleep problems in tic disorders was 34% (95%CI: 26% to 43%). Meta-regression analysis revealed that the presence of co-occurring symptoms of ADHD (p < 0.05), obsession compulsive disorder/behaviours (p < 0.05), anxiety (p < 0.001), and mood disorders (p < 0.001) was associated with an increased likelihood of experiencing sleep problems.

Conclusions: Our findings consistently indicate that individuals with tic disorders frequently encounter significant sleep problems. This underscores the importance of routinely screening for sleep problems during clinical assessments. Effectively managing sleep problems in patients with tic disorders is crucial not only for the well-being of the patients themselves but also for their families.