Severity of Antipsychotic-Induced Cervical Dystonia Assessed by the Algorithm-Based Rating System.

Background: The severity of antipsychotic-induced cervical dystonia has traditionally been evaluated visually. However, recent advances in information technology made quantification possible in this field through the introduction of engineering methodologies like machine learning.Methods: This study was conducted from June 2021 to March 2023. Psychiatrists rated the severity of cervical dystonia into 4 levels (0: none, 1: minimal, 2: mild, and 3: moderate) for 101 videoclips, recorded from 87 psychiatric patients receiving antipsychotics. The Face Mesh function of the open-source framework MediaPipe was employed to calculate the tilt angles of anterocollis or retrocollis, laterocollis, and torticollis. These were calculated to examine the range of tilt angles for the 4 levels of severity of the different types of cervical dystonia.Results: The tilt angles calculated using Face Mesh for each level of dystonia were 0° ≤ θ < 6° for none, 6° ≤ θ < 11° for minimal, 11° ≤ θ < 25° for mild, and 25° ≤ θ for moderate laterocollis; 0° ≤ θ < 11° for none, 11° ≤ θ < 18° for minimal, 18° ≤ θ <25° for mild, and 25° ≤ θ for moderate anterocollis or retrocollis; and 0° ≤ θ < 9° for none, 9° ≤ θ < 17° for minimal, 17° ≤ θ < 32° for mild, and 32° ≤ θ for moderate torticollis.Conclusion: While further validation with new cases is needed, the range of tilt angles in this study could provide a standard for future artificial intelligence devices for cervical dystonia.

Extremely Low Frequency, Extremely Low Magnetic Environment for depression: An open-label trial.

Mitochondrial dysfunction has been suggested to play a role in depression pathogenesis. This clinical trial (jRCTs042220011) was conducted to evaluate whether depression symptoms could be alleviated by an Extremely Low Frequency, Extremely Low Magnetic Environment (ELF-ELME), which has been found in basic research studies to enhance mitochondrial membrane potential. Participants were exposed to the ELF-ELME via a head-mounted magnetic field device (10 µTesla, 4 ms, 1-8 Hz/8 s) worn for 2 h per day for 8 consecutive weeks. Four male patients with treatment-resistant depression were enrolled. Significant reductions from baseline in the average total Montgomery-Åsberg Depression Rating Scale (MADRS) score were observed at 4, 6, and 8 weeks. ELF-ELME appears to ameliorate depressive symptoms in patients with major depressive disorder safely and effectively, suggesting that it could be used as an alternative treatment for depressive patients who do not prefer to take antidepressants and in combination with antidepressant therapy for patients who only partially respond to pharmacotherapy.

Association between copy number variations in parkin (PRKN) and schizophrenia and autism spectrum disorder: A case-control study.

AIM: The present study aimed to examine the association between copy number variations (CNVs) in parkin (PRKN) and schizophrenia (SCZ) and autism spectrum disorder (ASD) in a large case-control sample. METHOD: Array comparative genomic hybridization was performed on 3111 cases with SCZ, 1236 cases with ASD, and 2713 controls. We systematically prioritized likely pathogenic CNVs (LP-CNVs) in PRKN and examined their association with SCZ and ASD. RESULTS: In total, 3014 SCZ cases (96.9%), 1205 ASD cases (97.5%), and 2671 controls (98.5%) passed quality control. We found that monoallelic carriers of LP-CNVs in PRKN were common (70/6890, 1.02%) and were not at higher risk of SCZ (p = 0.29) or ASD (p = 0.72). We observed that the distribution pattern of LP-CNVs in the Japanese population was consistent with those in other populations. We also identified a patient diagnosed with SCZ and early-onset Parkinson's disease carrying biallelic pathogenic CNVs in PRKN. The absence of Parkinson's symptoms in 10 other monoallelic carriers of the same pathogenic CNV further reflects the lack of effect of monoallelic pathogenic variants in PRKN in the absence of a second hit. CONCLUSION: The present findings suggest that monoallelic CNVs in PRKN do not confer a significant risk for SCZ or ASD. However, further studies to investigate the association between biallelic CNVs in PRKN and SCZ and ASD are warranted.

Machine learning algorithm-based estimation model for the severity of depression assessed using Montgomery-Asberg depression rating scale.

AIM: Depressive disorder is often evaluated using established rating scales. However, consistent data collection with these scales requires trained professionals. In the present study, the "rater & estimation-system" reliability was assessed between consensus evaluation by trained psychiatrists and the estimation by 2 models of the AI-MADRS (Montgomery-Asberg Depression Rating Scale) estimation system, a machine learning algorithm-based model developed to assess the severity of depression. METHODS: During interviews with trained psychiatrists and the AI-MADRS estimation system, patients responded orally to machine-generated voice prompts from the AI-MADRS structured interview questions. The severity scores estimated from two models of the AI-MADRS estimation system, the max estimation model and the average estimation model, were compared with those by trained psychiatrists. RESULTS: A total of 51 evaluation interviews conducted on 30 patients were analyzed. Pearson's correlation coefficient with the scores evaluated by trained psychiatrists was 0.76 (95% confidence interval 0.62-0.86) for the max estimation model, and 0.86 (0.76-0.92) for the average estimation model. The ANOVA ICC rater & estimation-system reliability with the evaluation scores by trained psychiatrists was 0.51 (-0.09 to 0.79) for the max estimation model, and 0.75 (0.55-0.86) for the average estimation model. CONCLUSION: The average estimation model of AI-MADRS demonstrated substantially acceptable rater & estimation-system reliability with trained psychiatrists. Accumulating a broader training dataset and the refinement of AI-MADRS interviews are expected to improve the performance of AI-MADRS. Our findings suggest that AI technologies can significantly modernize and potentially revolutionize the realm of depression assessments.

Slovenian Version of the Drug-Induced Extrapyramidal Symptoms Scale: Evaluation of Interrater and Test-Retest Reliability.

AIM: The Drug-Induced Extrapyramidal Symptom Scale (DIEPSS) is a multidimensional rating scale for the assessment of drug-induced extrapyramidal symptoms (EPS), developed in 1994. It is suitable for evaluating EPS considering the degree of influence EPS has on daily activities and the subjective distress that it causes. METHOD: This study to evaluate the interrater and test-retest reliability of the DIEPSS Slovenian version conducted at the University Medical Center Maribor in Slovenia in November 2018. RESULTS: Six raters performed the interrater assessment of 135 DIEPSS video clips with recordings of patients with EPS. A second assessment was then performed by 2 raters to evaluate the test-retest reliability, which was high (interclass correlation coefficients from 0.743 to 0.936). CONCLUSIONS: The results for the Slovenian language version of the DIEPSS show high interrater and test-retest reliability, with high concordance rates for all evaluated items (interclass correlation coefficient > 0.8).

Clinical characterization of patients with schizophrenia and 16p13.11 duplication: A case series.

BACKGROUND: Chromosome 16p13.11 duplication is a well-known genetic risk factor for schizophrenia (SCZ) (odds ratio = 1.84). However, no case reports focusing on patients with SCZ and 16p13.11 duplication have been published. Therefore, here, we report the detailed clinical cases of four patients with SCZ and 16p13.11 duplication who were identified in our previous whole-genome copy number variant (CNV) study. CASE PRESENTATION: In the four patients with SCZ and 16p13.11 duplication detected by array comparative genomic hybridization, one patient was found to have treatment-resistant SCZ and an additional pathogenic rare CNV. Two of the four patients in this study had environmental risk factors that may have been involved in the development of SCZ. CONCLUSIONS: The results of this case series suggest that a genetic cohort study would be useful for evaluating which genetic and environmental risk factors could better explain the variable expressivity of 16p13.11 duplication. Furthermore, this work could be useful for elucidating the pathophysiology of SCZ.

A case of schizophrenia with relapsed catatonia successfully treated with blonanserin transdermal patch.

BACKGROUND: Catatonia is a syndrome that may present with stupor, immobility, and postural retention, and appears in various primary disorders including schizophrenia, depressive disorders, and neurodevelopmental disorders. CASE PRESENTATION: In this report, we describe a 34-year-old female patient with schizophrenia, who had previously been treated with antipsychotic agents to improve psychotic symptoms with delusional symptoms and catatonia. However, she relapsed with catatonic symptoms around 1 year after she voluntarily discontinued the prescribed antipsychotic medications by herself. Her catatonia was successfully improved using the transdermal blonanserin patch, a drug formulation globally first approved in Japan in 2019. DISCUSSION: Although benzodiazepines or electroconvulsive therapy have been recommended as the first-line treatment of catatonic manifestation observed in psychiatric patients, this patient responded well to antipsychotic blonanserin. From the differential drug responses, catatonia may be the complex of heterogeneous conditions with different pathophysiologies.

The factor structure of extrapyramidal symptoms evaluated using the Drug-Induced Extrapyramidal Symptoms Scale in patients with schizophrenia: Results from the 2016 REAP AP-4 study.

INTRODUCTION: Drug-induced extrapyramidal syndrome (EPS) remains a major problem in clinical psychiatry. This study aimed to examine the factor structure of drug-induced extrapyramidal symptoms observed in patients with schizophrenia and assessed using the Drug-Induced Extrapyramidal Symptoms Scale (DIEPSS). METHODS: The participants were 1478 patients with a diagnosis of schizophrenia whose EPS was assessed using the DIEPSS in India, Indonesia, Japan, Malaysia, and Taiwan in the 2016 REAP AP-4 study. The records of the participants were randomly divided into two subgroups: the first for exploratory factor analysis of the eight DIEPSS items, and the second for confirmatory factor analysis. RESULTS: The factor analysis identified three factors: F1 (gait and bradykinesia), F2 (muscle rigidity and tremor), and F3 (sialorrhea, akathisia, dystonia, and dyskinesia). CONCLUSION: The results suggest that the eight individual items of the DIEPSS could be composed of three different mechanisms: acute parkinsonism observed during action (F1), acute parkinsonism observed at rest (F2), and central dopaminergic mechanisms with pathophysiology other than acute parkinsonism (F3).

Positron emission tomography studies in adult patients with attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention, motor hyperactivity, impulsivity, and psychosocial as well as cognitive dysfunction. Although characteristic clinical manifestations have been described, no definitive biomarkers to diagnose ADHD have been established. In this review article, we summarize positron emission tomography (PET) studies conducted in adult patients with ADHD. We found that, although, disturbances of dopamine, serotonin, and norepinephrine functions have been implicated in ADHD, no characteristic findings have been identified from PET studies in patients with ADHD. Several previous PET studies on the central dopaminergic transmission-related ligands in patients with ADHD have shown altered binding of dopamine markers in the basal ganglia. However, no consistent results were observed in the binding characteristics for dopamine transporters and receptors. Findings from PET studies with ligands related to serotonin and norepinephrine pathways showed either unclear clinical significance or low replicability. Therefore, whether alterations of monoamine function may be involved in the pathophysiological mechanism remains to be clarified. The limitations of previous PET studies include their small sample sizes, focus on several kinds of existing ligands, and a questionable validity of the diagnosis (lack of biological diagnostic criteria). To determine the characteristic findings for diagnosing ADHD, further research is needed, and particularly, studies that evaluate new active ligands with specific binding to monoamine pathways should be undertaken.

Poor prognostic impact of delirium: especially on mortality and institutionalisation.

The course of delirium is associated with increased hospital costs, healthcare complications, increased mortality, and long-term poor outcomes. Despite delirium being long recognised as one of the most important prognostic components of patients with illnesses, delirium remains poorly understood, effective management options are limited, and no effective treatment has yet been established. This review evaluated the effects of delirium on mortality, institutionalisation, and dementia in various situations to clarify its prognostic seriousness to elucidate important areas for clinical practice and future research. The effect of delirium on mortality in COVID-19 patients was similar to that in other diseases. The effect of delirium on mortality in patients with delirium between the ages of 18 and 65 may be higher than in those with delirium aged over 65, but studies are scarce. Promoting recognition of delirium at all ages is needed. With careful attention to the specific factors in younger patients that contribute to delirium, healthcare providers may be able to decrease the poor impact of delirium on clinical outcomes. Evaluation of the association between interventions for delirium such as sedation in present clinical practice and the prognosis of delirium is lacking, and further clinical studies are essential.

X chromosome aneuploidies and schizophrenia: association analysis and phenotypic characterization.

AIM: The aims of the present study were: (i) to examine the association between schizophrenia (SCZ) and 47, XXY or 47, XXX in a large case-control sample; and (ii) to characterize the clinical features of patients with SCZ with these X chromosome aneuploidies. METHODS: To identify 47, XXY and 47, XXX, array comparative genomic hybridization (aCGH) was performed in 3188 patients with SCZ and 3586 controls. We examined the association between 47, XXY and 47, XXX and SCZ in males and females separately using exact conditional tests to control for platform effects. Clinical data were retrospectively examined for patients with SCZ with X chromosome aneuploidies. RESULTS: Of the analyzed samples, 3117 patients (97.8%) and 3519 controls (98.1%) passed our quality control. X chromosome aneuploidies were exclusively identified in patients: 47, XXY in seven patients (0.56%), 47, XXX in six patients (0.42%). Statistical analysis revealed a significant association between SCZ and 47, XXY (P = 0.028) and 47, XXX (P = 0.011). Phenotypic data were available from 12 patients. Treatment-resistance to antipsychotics and manic symptoms were observed in six patients each (four with 47, XXY and two with 47, XXX for both), respectively. Statistical analysis revealed that treatment-resistance to antipsychotics, mood stabilizer use, and manic symptoms were significantly more common in patients with 47, XXY than in male patients without pathogenic copy number variations. CONCLUSION: These findings indicate that both 47, XXY and 47, XXX are significantly associated with risk for SCZ. Patients with SCZ with 47, XXY may be characterized by treatment-resistance and manic symptoms.

Investigation of OLIG2 as a candidate gene for schizophrenia and autism spectrum disorder.

A number of genomic mutations that are thought to be strongly involved in the development of schizophrenia (SCZ) and autism spectrum disorder (ASD) have been identified. Abnormalities involving oligodendrocytes have been reported in SCZ, and as a related gene, oligodendrocyte lineage transcription factor 2 (OLIG2) has been reported to be strongly associated with SCZ. In this study, based on the common disease-rare variant hypothesis, target sequencing of candidate genes was performed to identify rare mutations with a high effect size and the possibility that the identified mutations may increase the risks of SCZ and ASD in the Japanese population. In this study, the exon region of OLIG2 was targeted; 370 patients with SCZ and 192 with ASD were subjected to next-generation sequencing. As a result, one rare missense mutation (A33T) was detected. We used the Sanger method to validate this missense mutation with a low frequency (<1%), and then carried out a genetic association analysis involving 3299 unrelated individuals (1447 with SCZ, 380 with ASD, and 1472 healthy controls) to clarify whether A33T was associated with SCZ or ASD. A33T was not found in either case group, and in only one control. We did not find evidence that p.A33T is involved in the onset of ASD or SCZ; however, associations with this variant need to be evaluated in larger samples to confirm our results.

Cross-Disorder Analysis of Genic and Regulatory Copy Number Variations in Bipolar Disorder, Schizophrenia, and Autism Spectrum Disorder.

BACKGROUND: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD). METHODS: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD. RESULTS: In genic CNVs, we found an increased burden of smaller (<100 kb) exonic deletions in BD, which contrasted with the highest burden of larger (>500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25-0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue. CONCLUSIONS: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD.

Machine Learning Algorithm-Based Prediction Model for the Augmented Use of Clozapine with Electroconvulsive Therapy in Patients with Schizophrenia.

The augmentation of clozapine with electroconvulsive therapy (ECT) has been an optimal treatment option for patients with treatment- or clozapine-resistant schizophrenia. Using data from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics survey, which was the largest international psychiatry research collaboration in Asia, our study aimed to develop a machine learning algorithm-based substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in terms of precision medicine. A random forest model and least absolute shrinkage and selection operator (LASSO) model were used to develop a substantial prediction model for the augmented use of clozapine with ECT. Among the 3744 Asian patients with schizophrenia, those treated with a combination of clozapine and ECT were characterized by significantly greater proportions of females and inpatients, a longer duration of illness, and a greater prevalence of negative symptoms and social or occupational dysfunction than those not treated. In the random forest model, the area under the curve (AUC), which was the most preferred indicator of the prediction model, was 0.774. The overall accuracy was 0.817 (95% confidence interval, 0.793−0.839). Inpatient status was the most important variable in the substantial prediction model, followed by BMI, age, social or occupational dysfunction, persistent symptoms, illness duration > 20 years, and others. Furthermore, the AUC and overall accuracy of the LASSO model were 0.831 and 0.644 (95% CI, 0.615−0.672), respectively. Despite the subtle differences in both AUC and overall accuracy of the random forest model and LASSO model, the important variables were commonly shared by the two models. Using the machine learning algorithm, our findings allow the development of a substantial prediction model for the augmented use of clozapine with ECT in Asian patients with schizophrenia. This substantial prediction model can support further studies to develop a substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in a strict epidemiological context.

Prevalence, clinical features, and risk factors of delusions in patients with delirium.

OBJECTIVES: Delirium may be divided into multiple subtypes with different pathological factors. This study aimed to focus on the delirium subtype in which delusions are conspicuous and explore its prevalence, clinical characteristics, and risk factors. METHODS: The subjects were 601 delirium cases referred to the department of psychiatry over 5 years at a general hospital. The Delirium Rating Scale-Revised-98 was used to assess the delusions in patients with delirium, and the features of delusions (delusional form, object, and content) were examined. Multiple regression analysis was applied to determine whether individual factors were associated with the delusions. RESULTS: A total of 78 patients with delirium experienced delusions (13.0%). Most were classified as delusion of reference, such as persecution or poisoning, and 84.3% of patients believed that the persecutors were medical staff members. Older age (p < 0.001), female gender (p < 0.001), and living alone (p < 0.001) were significantly associated with delusions in patients with delirium. CONCLUSIONS: The content of delusions was rooted in the distress caused by the patients' medical situation, and the features and risk factors of the delusions suggested a formal similarity with late paraphrenia and "lack-of-contact paranoia." Psychological interventions that consider the isolation, anxiety, and fear behind delusions may be necessary in the care and treatment of these patients.

Network Analysis-Based Disentanglement of the Symptom Heterogeneity in Asian Patients with Schizophrenia: Findings from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics.

The symptom heterogeneity of schizophrenia is consistent with Wittgenstein's analogy of a language game. From the perspective of precision medicine, this study aimed to estimate the symptom presentation and identify the psychonectome in Asian patients, using data obtained from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics. We constructed a network structure of the Brief Psychiatric Rating Scale (BPRS) items in 1438 Asian patients with schizophrenia. Furthermore, all the BPRS items were considered to be an ordered categorical variable ranging in value from 1-7. Motor retardation was situated most centrally within the BPRS network structure, followed by depressive mood and unusual thought content. Contrastingly, hallucinatory behavior was situated least centrally within the network structure. Using a community detection algorithm, the BPRS items were organized into positive, negative, and general symptom clusters. Overall, DSM symptoms were not more central than non-DSM symptoms within the symptom network of Asian patients with schizophrenia. Thus, motor retardation, which results from the unmet needs associated with current antipsychotic medications for schizophrenia, may be a tailored treatment target for Asian patients with schizophrenia. Based on these findings, targeting non-dopamine systems (glutamate, γ-aminobutyric acid) may represent an effective strategy with respect to precision medicine for psychosis.

Autistic traits as predictors of persistent depression.

Persistent depression has been suggested to be associated with autistic traits in people of working age. This study aimed to clarify which autistic characteristics at the initial visit were associated with persistent depression at the 12 week follow-up in a primary care setting. Newly depressed outpatients aged 24-59 years with no history of autism were asked to complete the 50-item autism spectrum quotient (AQ) and the Beck depression inventory (BDI) at baseline and 12 week follow-up (N = 123, males: 48%, age: 37.7 ± 9.15 years). Nearly 40% of participants had an AQ score ≥ 26. Significant differences were observed between the group with remitted depression (N = 43) and those with persistent depression (N = 80) in educational years and AQ "attention switching" and "attention to detail" subscale scores. In addition, a statistically significant decrease in the total AQ and the "communication" and "imagination" scores were observed in the remitted group, while no such change was observed in the group with persistent depression. It remains unclear whether the self-perceived severity of communication and imagination traits in persistent depression was due to the state of persistent depression or a kind of premorbid autistic trait. The results suggest that high levels of autistic traits are frequently present in adults with depression. High "attention switching" and "attention to detail" scores in AQ screening at the first visit might predict the persistence of depressive symptoms after 12 weeks in adults with depression, while total AQ scores, especially for "communication" and "imagination" items, might be state-dependent.

Severe and long-lasting neuropsychiatric symptoms after mild respiratory symptoms caused by COVID-19: A case report.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is known to cause not only respiratory but also neuropsychiatric symptoms, which are assumed to be derived from a cytokine storm and its effects on the central nervous systems. Patients with COVID-19 who develop severe respiratory symptoms are known to show severe neuropsychiatric symptoms such as cerebrovascular disease and encephalopathy. However, the detailed clinical courses of patients with neuropsychiatric symptoms caused by mild or asymptomatic COVID-19 remain poorly understood. Here, we present a case of COVID-19 who presented with severe and prolonged neuropsychiatric symptoms subsequent to mild respiratory symptoms. CASE PRESENTATION: A 55-year-old female with COVID-19 accompanied by mild respiratory symptoms showed delusion, psychomotor excitement, and poor communication ability during quarantine outside the hospital. Considering her diminished respiratory symptoms, her neuropsychiatric symptoms were initially regarded as psychogenic reactions. However, as she showed progressive disturbance of consciousness accompanied by an abnormal electroencephalogram, she was diagnosed with post-COVID-19 encephalopathy. Although her impaired consciousness and elevated cytokine level improved after steroid pulse therapy, several neuropsychiatric symptoms, including a loss of concentration, unsteadiness while walking, and fatigue, remained. CONCLUSIONS: This case suggests the importance of both recognizing that even apparently mild COVID-19-related respiratory symptoms can lead to severe and persistent neuropsychiatric symptoms, and elucidating the mechanisms, treatment, and long-term course of COVID-19-related neuropsychiatric symptoms in the future.