岩田 仲生

Dendritic spine abnormalities are believed to be one of the critical etiologies of autism spectrum disorder (ASD). Over the past decade, the importance of microglia in brain development, particularly in synaptic elimination, has become evident. Thus, microglial abnormalities may lead to synaptic dysfunction, which may underlie the pathogenesis of ASD. Several human studies have demonstrated aberrant microglial activation in the brains of individuals with ASD, and studies in animal models of ASD have also shown a relationship between microglial dysfunction and synaptic abnormalities. However, there are very few methods available to directly assess whether phagocytosis by human microglia is abnormal. Microglia are tissue-resident macrophages with phenotypic similarities to monocyte-derived macrophages, both of which consistently exhibit pathological phenotypes in individuals with ASD. Therefore, in this study, we examined the phagocytosis capacity of human macrophages derived from peripheral blood monocytes. These macrophages were polarized into two types: those induced by granulocyte-macrophage colony-stimulating factor (GM-CSF MΦ, traditionally referred to as "M1 MΦ") and those induced by macrophage colony-stimulating factor (M-CSF MΦ, traditionally referred to as "M2 MΦ"). Synaptosomes purified from human induced pluripotent stem cell-derived neuron were used to assess phagocytosis capacity. Our results revealed that M-CSF MΦ exhibited higher phagocytosis capacity compared to GM-CSF MΦ, whereas ASD-M-CSF MΦ showed a marked impairment in phagocytosis. Additionally, we found a positive correlation between phagocytosis capacity and cluster of differentiation 209 expression. This research contributes to a deeper understanding of the pathobiology of ASD and offers new insights into potential therapeutic targets for the disorder.

BACKGROUND: With 30%-50% of people with bipolar depression (BDep) not responding to multiple pharmacological treatments, alternative therapies are needed. Accelerated intermittent theta burst stimulation (aiTBS) over the left dorsolateral prefrontal cortex (L-DLPFC) has been employed for individuals with pharmacological treatment-resistant major depressive disorder (TR-MDD). Imaging studies have revealed reduced regional activity of the L-DLPFC for both TR-MDD and pharmacological treatment-resistant BDep (TR-BDep), suggesting that aiTBS over the L-DLPFC may be beneficial for people with TR-BDep. METHODS: A 6-week, double-blind, sham-controlled, randomized trial will be conducted to compare the efficacy and safety of aiTBS to the L-DLPFC in people with TR-BDep (jRCTs042240019). Fifty iTBS sessions (1800 pulses/session) will be delivered in 10 daily sessions over 5 consecutive days at 90% resting motor threshold. This aiTBS protocol is termed as Fujita Neuromodulation Therapy for Bipolar Depression (FNT-BD). Twenty-two participants (both sexes, aged 18-64 years) with TR-BDep (DSM-5-TR, Type I) will be recruited. The response rate at any given week of follow-up will be the primary efficacy outcome, defined as a reduction of ≥50% in the Montgomery Åsberg Depression Rating Scale (MADRS) score. Other outcomes will include MADRS score changes, remission rate (10 ≥ MADRS score), Clinical Global Impression-Improvement score, Clinical Global Impression-Severity score, discontinuation rate, and incidence of individual adverse events. RESULTS: We anticipate that individuals who receive the aiTBS treatment show significant improvement in depressing symptoms compared to those receiving sham treatment. CONCLUSIONS: This study will provide valuable evidence for both patients with TR-BDep and clinicians.

Suicidal ideation (SI) and behavior (SB) are major public health concerns, but risk factors for their development and progression are poorly understood. We used ICD codes and a natural language processing algorithm to identify individuals in a hospital biobank with SI-only, SB, and controls without either. We compared the profiles of SB and SI-only patients to controls, and each other, using phenome-wide association studies (PheWAS) and polygenic risk scores (PRS). PheWAS identified many risk factors for SB and SI-only, plus specific psychiatric disorders which may be involved in progression from SI-only to SB. PRS for suicide attempt were only associated with SB, and even after accounting for psychiatric disorder PRS. SI PRS were only associated with SI-only, although not after accounting for psychiatric disorder PRS. These findings advance understanding of distinct genetic and clinical risk factors for SB and SI-only, which will aid in early detection and intervention efforts.

The United States Food and Drug Administration approved the xanomeline-trospium combination in September 2024 for treating schizophrenia, based in part on three double-blind, randomized placebo-controlled trials in adults with schizophrenia experiencing acute psychosis. This random-effects model pairwise meta-analysis of those three trials found that xanomeline-trospium was comparable to placebo in terms of all-cause discontinuation, discontinuation rate due to adverse events, Simpson-Angus Scale score change, Barnes Akathisia Rating Scale score change, body weight change, body mass index change, blood pressure change, serum total cholesterol change, blood glucose change, QTc interval changes, and the incidence of headache, somnolence, insomnia, dizziness, akathisia, agitation, tachycardia, gastroesophageal reflux disease, diarrhea, increased weight, and decreased appetite. However, xanomeline-trospium was associated with a higher incidence of at least one adverse event, dry mouth, hypertension, nausea, vomiting, dyspepsia, and constipation, and increased serum triglyceride compared with placebo. Notably, xanomeline-trospium demonstrated superior efficacy than placebo in improving the Positive and Negative Syndrome Scale (PANSS) total score, PANSS positive subscale score, and PANSS negative subscale score.

BACKGROUND: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from hospitals and self-reported physician diagnoses or typical schizophrenia symptoms. These approaches are likely to underestimate the true prevalence owing to stigma, poor insight, or lack of access to health care among respondents. To address these issues, we previously developed an artificial neural network (ANN)-based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. In addition, we also plan to introduce a population-based survey to collect general information and sample participants matching the population's demographic structure, thereby achieving a precise estimate of the prevalence of schizophrenia in Japan. OBJECTIVE: This study aimed to estimate the prevalence of schizophrenia by applying the SZ classifier to random samples from the Japanese population. METHODS: We randomly selected a sample of 750 participants where the age, sex, and regional distributions were similar to Japan's demographic structure from a large-scale Japanese web-based survey. Demographic data, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities were collected and applied to the SZ classifier, as this information was also used for developing the SZ classifier. The crude prevalence of schizophrenia was calculated through the proportion of positive cases detected by the SZ classifier. The crude estimate was further refined by excluding false-positive cases and including false-negative cases to determine the actual prevalence of schizophrenia. RESULTS: Out of 750 participants, 62 were classified as schizophrenia cases by the SZ classifier, resulting in a crude prevalence of schizophrenia in the general population of Japan of 8.3% (95% CI 6.6%-10.1%). Among these 62 cases, 53 were presumed to be false positives, and 3 were presumed to be false negatives. After adjustment, the actual prevalence of schizophrenia in the general population was estimated to be 1.6% (95% CI 0.7%-2.5%). CONCLUSIONS: This estimated prevalence was slightly higher than that reported in previous studies, possibly due to a more comprehensive disease classification methodology or, conversely, model limitations. This study demonstrates the capability of an ANN-based model to improve the estimation of schizophrenia prevalence in the general population, offering a novel approach to public health analysis.