Psychiatry and Clinical Neurosciences最新文献

Aims: This study aims to assess the therapeutic effects of intermittent theta burst stimulation (iTBS) targeting the bilateral dorsomedial prefrontal cortex (DMPFC) on negative symptoms in patients with schizophrenia, utilizing functional near-infrared spectroscopy for evaluation.

Methods: Thirty-five schizophrenia patients with negative symptoms and moderate to severe cognitive impairment were randomly assigned to a treatment group (n = 18) or a control group (n = 17). The treatment group received iTBS via bilateral DMPFC. Negative symptoms, cognitive function, emotional state, and social function were assessed using Positive and Negative Syndrome Scale (PANSS), Scale for the Assessment of Negative Symptoms (SANS), Montreal Cognitive Assessment (MoCA), Calgary Depression Scale for Schizophrenia (CDSS), and Social Dysfunction Screening Questionnaire (SDSS) scales at pretreatment, posttreatment, and follow-up at 4, 8, and 12 weeks. Brain activation in regions of interest (ROIs) was evaluated through verbal fluency tasks.

Results: Prior to treatment there was no significant difference in the two groups. After 20 iTBS sessions, a significant difference was observed in SANS total score, its related subscales, PANSS total score, and PANSS-negative symptoms (all P < 0.05). The group-by-time interaction showed statistical significance, indicating improvements in negative symptoms and related dimensions over time, with therapeutic effects persisting for at least 8 weeks posttreatment. Prior to treatment, there were no significant differences in activation across all ROIs between the two groups. Posttreatment, the activation of right inferior frontal gyrus (t = 2.19, P = 0.036) and right frontal eye field (t = 2.14, P = 0.04) in the treatment group was significantly higher than in the control group.

Conclusions: iTBS stimulation of bilateral DMPFC demonstrates therapeutic effects in improving negative symptoms in schizophrenia patients, and this treatment approach has the potential to enhance activation within the prefrontal cortex.

Aim: Filicide-suicide represents a critical intersection of psychiatric and familial crises, yet the literature remains scant on differentiated risk profiles among family members. This study addresses a gap in understanding the specific mental health correlates of filicide-suicide, especially within a comprehensive family context, distinct from traditional parental or child-focused perspectives.

Method: This study used the Taiwan National Health Insurance Research Database to identify a nationally representative sample of families from 2004 to 2020, with continuous monitoring extending into 2021. Families were classified into those affected by filicide-suicide, parental suicide, and those without such incidents. Multinomial logistic regression was conducted to explore the association between family status and mental health. Analyses of effect modification were conducted to evaluate whether low-income status modified these relationships.

Results: The study encompassed 1,898,299 families, revealing that filicide-suicide is notably rare, with an incidence of 1.64 deaths per 100,000 newborn children from 2004 to 2020, with an increasing trend observed after 2014. Fathers and children in filicide-suicide families had the highest prevalence of mental disorders, followed by those in parental-suicide families and then other families (those where no child has been recorded as a homicide victim and no parent has committed suicide). There was a tendency for stronger associations between filicide-suicide families and paternal schizophrenia as well as autistic spectrum disorder in children among low-income families.

Conclusion: The findings underscore the profound impact of severe mental disorders within the familial framework, emphasizing the need for an integrated approach to mental health care that considers the familial context in order to better predict and prevent such devastating events.

Large language models (LLMs) have gained significant attention for their capabilities in natural language understanding and generation. However, their widespread adoption potentially raises public mental health concerns, including issues related to inequity, stigma, dependence, medical risks, and security threats. This review aims to offer a perspective within the actor-network framework, exploring the technical architectures, linguistic dynamics, and psychological effects underlying human-LLMs interactions. Based on this theoretical foundation, we propose four categories of risks, presenting increasing challenges in identification and mitigation: universal, context-specific, user-specific, and user-context-specific risks. Correspondingly, we introduce CORE: Chain of Risk Evaluation, a structured conceptual framework for assessing and mitigating the risks associated with LLMs in public mental health contexts. Our approach suggests viewing the development of responsible LLMs as a continuum from technical to public efforts. We summarize technical approaches and potential contributions from mental health practitioners that could help evaluate and regulate risks in human-LLMs interactions. We propose that mental health practitioners could play a crucial role in this emerging field by collaborating with LLMs developers, conducting empirical studies to better understand the psychological impacts on human-LLMs interactions, developing guidelines for LLMs use in mental health contexts, and engaging in public education.

Aim: Despite the clinical importance and significant social burden of neuropsychiatric symptoms (NPS) in dementia, the underlying neurobiological mechanism remains poorly understood. Recently, neuroimaging-derived brain-age estimation by machine-learning analysis has shown promise as an individual-level biomarker. We investigated the relationship between NPS and brain-age in amnestic mild cognitive impairment (MCI) and early dementia.

Methods: In this cross-sectional study, clinical data, including neuropsychiatric inventory (NPI), and structural brain MRI of 499 individuals with clinical diagnoses of amnestic MCI (n = 185), early Alzheimer's disease (AD) (n = 258) or dementia with Lewy bodies (DLB) (n = 56) were analyzed. We established a brain-age prediction model using 694 healthy brain MRIs and a support vector regression model and applied it to the participants' data. Finally, the brain-predicted age difference (brain-PAD: predicted age minus chronological age) was calculated.

Results: All groups showed significantly increased brain-PAD, and the median (IQR) brain-PAD was 4.3 (5.4) years in MCI, 6.3 (6.2) years in AD, and 5.0 (6.5) years in DLB. The NPI scores were subdivided into the following four categories: (i) Agitation and Irritability, (ii) Depression and Apathy, (iii) Delusions and Hallucinations, and (iv) Euphoria and Disinhibition. We found a significantly positive correlation between brain-PAD and the depression/apathy factor (Spearman's rs = 0.156, FDR-corrected P = 0.002), whereas no significance was shown for the other NPS factors.

Conclusion: Higher brain-age may be associated with depression and apathy symptoms presented in MCI to early dementia stages, and brain-age analysis may be useful as a novel biomarker for the assessment or monitoring of NPS.

Aims: Schizophrenia, a debilitating mental disorder, is characterized by persistent negative symptoms such as avolition and anhedonia. Currently, there are no effective treatments available for these symptoms. Thus, our study aims to assess the efficacy of online high-definition transcranial direct current stimulation (online HD-tDCS) in addressing the negative symptoms of schizophrenia, utilizing a double-blind, randomized, sham-controlled trial design.

Methods: Fifty-nine patients with schizophrenia were randomized to receive either active HD-tDCS or sham stimulation, targeting the left dorsolateral prefrontal cortex. Outcomes were measured by changes in the Positive and Negative Syndrome Scale Factor Score for Negative Symptom (PANSS-FSNS). Exact low-resolution electromagnetic tomography was used to assess the functional connectivity.

Results: All 59 participants, including 50.84% females with an average age of 43.36 years, completed the trial. In the intention-to-treat analysis, patients receiving active HD-tDCS showed greater improvement in PANSS-FSNS scores compared to those receiving the sham procedure. The differences were 2.34 (95% confidence interval [CI], 1.28-3.40), 4.28 (95% CI, 2.93-5.62), and 4.91 (95% CI, 3.29-6.52) after the intervention, as well as at 1-week and 1-month follow-ups, respectively. A tingling sensation on the scalp was more common in the active group (63.3%) compared to the sham group (10.3%). Additionally, HD-tDCS was associated with a decrease in delta-band connectivity within the default mode network.

Conclusions: High-definition transcranial direct current stimulation was effective and safe in ameliorating negative symptoms in patients with schizophrenia when combined with online functional targeting.

Aim: Whole-exome sequencing (WES) studies have revealed that germline de novo variants (gDNVs) contribute to the genetic etiology of schizophrenia. However, the contribution of mosaic DNVs (mDNVs) to the risk of schizophrenia remains to be elucidated. In the present study, we systematically investigated the gDNVs and mDMVs that contribute to the genetic etiology of schizophrenia in a Japanese population.

Methods: We performed deep WES (depth: 460×) of 73 affected offspring and WES (depth: 116×) of 134 parents from 67 families with schizophrenia. Prioritized rare nonsynonymous gDNV and mDNV candidates were validated using Sanger sequencing and ultra-deep targeted amplicon sequencing (depth: 71,375×), respectively. Subsequently, we performed a Gene Ontology analysis of the gDNVs and mDNVs to obtain biological insights. Lastly, we selected DNVs in known risk genes for psychiatric and neurodevelopmental disorders.

Results: We identified 62 gDNVs and 98 mDNVs. The Gene Ontology analysis of mDNVs implicated actin filament and actin cytoskeleton as candidate biological pathways. There were eight DNVs in known risk genes: splice region gDNVs in AKAP11 and CUL1; a frameshift gDNV in SHANK1; a missense gDNV in SRCAP; missense mDNVs in CTNNB1, GRIN2A, and TSC2; and a nonsense mDNV in ZFHX4.

Conclusion: Our results suggest the potential contributions of rare nonsynonymous gDNVs and mDNVs to the genetic etiology of schizophrenia. This is the first report of the mDNVs in schizophrenia trios, demonstrating their potential relevance to schizophrenia pathology.

Aim: Bipolar disorder (BD) is a common psychiatric disorder characterized by alterations between manic/hypomanic and depressive states. Rare pathogenic copy number variations (CNVs) that overlap with exons of synaptic genes have been associated with BD. However, no study has comprehensively explored CNVs in synaptic genes associated with BD. Here, we evaluated the relationship between BD and rare CNVs that overlap with synaptic genes, not limited to exons, in the Japanese population.

Methods: Using array comparative genome hybridization, we detected CNVs in 1839 patients with BD and 2760 controls. We used the Synaptic Gene Ontology database to identify rare CNVs that overlap with synaptic genes. Using gene-based analysis, we compared their frequencies between the BD and control groups. We also searched for synaptic gene sets related to BD. The significance level was set to a false discovery rate of 10%.

Results: The RNF216 gene was significantly associated with BD (odds ratio, 4.51 [95% confidence interval, 1.66-14.89], false discovery rate < 10%). The BD-associated CNV that corresponded with RNF216 also partially overlapped with the minimal critical region of the 7p22.1 microduplication syndrome. The integral component of the postsynaptic membrane (Gene Ontology:0099055) was significantly associated with BD. The CNV overlapping with the intron region of GRM5 in this gene set showed a nominal significant association between cases and controls (P < 0.05).

Conclusion: We provide evidence that CNVs in RNF216 and postsynaptic membrane-related genes confer a risk of BD, contributing to a better understanding of the pathogenesis of BD.

Aim: This study examined the efficacy of AST-001 for the core symptoms of autism spectrum disorder (ASD) in children.

Methods: This phase 2 clinical trial consisted of a 12-week placebo-controlled main study, a 12-week extension, and a 12-week follow-up in children aged 2 to 11 years with ASD. The participants were randomized in a 1:1:1 ratio to a high-dose, low-dose, or placebo-to-high-dose control group during the main study. The placebo-to-high-dose control group received placebo during the main study and high-dose AST-001 during the extension. The a priori primary outcome was the mean change in the Adaptive Behavior Composite (ABC) score of the Korean Vineland Adaptive Behavior Scales II (K-VABS-II) from baseline to week 12.

Results: Among 151 enrolled participants, 144 completed the main study, 140 completed the extension, and 135 completed the follow-up. The mean K-VABS-II ABC score at the 12th week compared with baseline was significantly increased in the high-dose group (P = 0.042) compared with the placebo-to-high-dose control group. The mean CGI-S scores were significantly decreased at the 12th week in the high-dose (P = 0.046) and low-dose (P = 0.017) groups compared with the placebo-to-high-dose control group. During the extension, the K-VABS-II ABC and CGI-S scores of the placebo-to-high-dose control group changed rapidly after administration of high-dose AST-001 and caught up with those of the high-dose group at the 24th week. AST-001 was well tolerated with no safety concern. The most common adverse drug reaction was diarrhea.

Conclusions: Our results provide preliminary evidence for the efficacy of AST-001 for the core symptoms of ASD.