Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Background: Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising approach for the diagnosis and monitoring of psychosis, capturing symptoms like thought disorder and flattened affect. Recent advancements in Natural Language Processing (NLP) methodologies enable the automated extraction of informative speech features, which has been leveraged for early psychosis detection and assessment of symptomology. However, critical gaps persist, including the absence of standardized sample collection protocols, small sample sizes, and a lack of multi-illness classification, limiting clinical applicability. Our study aimed to (1) identify an optimal assessment approach for the online and remote collection of speech, in the context of assessing the psychosis spectrum and evaluate whether a fully automated, speech-based machine learning (ML) pipeline can discriminate among different conditions on the schizophrenia-bipolar spectrum (SSD-BD-SPE), help-seeking comparison subjects (MDD), and healthy controls (HC) at varying layers of analysis and diagnostic complexity. Methods: We adopted online data collection methods to collect 20 minutes of speech and demographic information from individuals. Participants were categorized as "healthy" help-seekers (HC), having a schizophrenia-spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), or being on the psychosis spectrum with sub-clinical psychotic experiences (SPE). SPE status was determined based on self-reported clinical diagnosis and responses to the PHQ-8 and PQ-16 screening questionnaires, while other diagnoses were determined based on self-report from participants. Linguistic and paralinguistic features were extracted and ensemble learning algorithms (e.g., XGBoost) were used to train models. A 70%-30% train-test split and 30-fold cross-validation was used to validate the model performance. Results: The final analysis sample included 1140 individuals and 22,650 minutes of speech. Using 5-minutes of speech, our model could discriminate between HC and those with a serious mental illness (SSD or BD) with 86% accuracy (AUC = 0.91, Recall = 0.7, Precision = 0.98). Furthermore, our model could discern among HC, SPE, BD and SSD groups with 86% accuracy (F1 macro = 0.855, Recall Macro = 0.86, Precision Macro = 0.86). Finally, in a 5-class discrimination task including individuals with MDD, our model had 76% accuracy (F1 macro = 0.757, Recall Macro = 0.758, Precision Macro = 0.766). Conclusion: Our ML pipeline demonstrated disorder-specific learning, achieving excellent or good accuracy across several classification tasks. We demonstrated that the screening of mental disorders is possible via a fully automated, remote speech assessment pipeline. We tested our model on relatively high number conditions (5 classes) in the literature and in a stratified sample of psychosis spectrum, including HC, SPE, SSD and BD (4 classes). We tested our model on a large sample (N = 1150) and demonstrated best-in-class accuracy with remotely collected speech data in the psychosis spectrum, however, further clinical validation is needed to test the reliability of model performance.

Effect of BPC-157 on Symptoms in Patients with Interstitial Cystitis: A Pilot Study.

Context: Moderate to severe interstitial cystitis (also known as bladder pain syndrome) is a disabling disease with no effective treatment. Although pentosan polysulfate is an approved treatment for interstitial cystitis, some patients on this medication experience treatment failure after one year, and its long-term use has been linked to pigmentary maculopathy. The peptide Body Protective Compound 157 (BPC-157) is a possible treatment for interstitial cystitis but is currently not approved by the US Food and Drug Administration. Objective: To assess the safety and efficacy of BPC-157 manufactured by a 503A compounding pharmacy as a treatment for interstitial cystitis. Participants: Twelve women between the ages of 39 and 76 years with a mean age of 58.3 years participated in this trial at a private clinic. Of these, 10 were White, one was Asian, and one was Latina. None of the 12 women had responded to pentosan polysulfate. Methods: The women underwent cystoscopy and were treated with injections of the peptide BPC-157 (total of 10 mg) around the area of inflammation of the bladder during a single procedure. Global Response Assessment questionnaire was given to all the subjects to assess the efficacy of BPC-157. Results: Complete resolution of symptoms after one treatment was reported in 10 of 12 patients, who rated their success at 100%. The remaining 2 of 12 patients rated their success at 80%, with most symptoms resolved but about 20% of their symptoms lingering. No one dropped out of the study, and no adverse events were reported. This therapy was successful because all 12 patients scored a 5/5 on the Global Response Assessment. Conclusion: This is the first report of intravesical BPC-157 (10 mg) injection to help patients with moderate to severe interstitial cystitis who did not respond to pentosan polysulfate treatment.

The Effects of Fisetin on Reducing Biological Aging: A Pilot Study.

Fisetin, a natural flavonoid compound, is a senolytic agent that has shown promise in extending the lifespan of aging mice. Our goal was to determine whether Fisetin can reduce human biological aging, as verified by the TruAge test. This would be the first study in healthy human adults over the age of 50 years old to determine if Fisetin can reduce their biological age. Fisetin 500 mg daily was administered for one week per month for six months. The results showed that four out of ten healthy adults experienced a reduction in biological aging, five out of ten saw an increase, and one out of ten had no change. No adverse effects were noted among the ten subjects. Telomere lengths did not statistically change with the use of Fisetin. Because five of ten had an increase in biological age, taking Fisetin as an anti- aging agent is not recommended until more extensive studies are done.

Comparison of Negative Symptom Network Structures Between Patients With Early and Chronic Schizophrenia: A Network and Exploratory Graph Analysis.

BACKGROUND AND HYPOTHESIS: Despite the clinical relevance of negative symptoms in schizophrenia, our understanding of negative symptoms remains limited. Although various courses and stages of schizophrenia have been identified, variations in the negative symptom networks between distinct stages of schizophrenia remain unexplored. STUDY DESIGN: We examined 405 patients with early schizophrenia (ES) and 330 patients with chronic schizophrenia (CS) using the Scale for the Assessment of Negative Symptoms. Network analysis and exploratory graph analysis were used to identify and compare the network structures and community memberships of negative symptoms between the two groups. Further, associations between communities and social functioning were evaluated. The potential influences of other symptom domains and confounding factors were also examined. STUDY RESULTS: Multidimensional differences were found in the networks of negative symptoms between ES and CS. The global connectivity strength was higher in the network of ES than in the network of CS. In ES, central symptoms were mainly related to expressive deficits, whereas in CS they were distributed across negative symptom domains. A three-community structure was suggested across stages but with different memberships and associations with social functioning. Potential confounding factors and symptom domains, including mood, positive, disorganization, and excitement symptoms, did not affect the network structures. CONCLUSION: Our findings revealed the presence of stage-specific network structures of negative symptoms in schizophrenia, with negative symptom communities having differential significance for social functioning. These findings provide implications for the future development of tailored interventions to alleviate negative symptoms and improve functionality across stages.

Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

Mentalizing impairments and hypermentalizing bias in individuals with first-episode schizophrenia-spectrum disorder and at-risk mental state: the differential roles of neurocognition and social anxiety.

Mentalizing, or theory of mind (ToM), impairments and self-referential hypermentalizing bias are well-evident in schizophrenia. However, findings compared to individuals with at-risk mental states (ARMS) are inconsistent, and investigations into the relationship between social cognitive impairments and social anxiety in the two populations are scarce. This study aimed to examine and compare these deficits in first-episode schizophrenia-spectrum disorder (FES) and ARMS, and to explore potential specific associations with neurocognition and symptomatology. Forty patients with FES, 40 individuals with ARMS, and 40 healthy controls (HC) completed clinical assessments, a battery of neurocognitive tasks, and three social cognitive tasks. The comic strip and hinting tasks were used to measure non-verbal and verbal mentalizing abilities, and the gaze perception task was employed to assess self-referential hypermentalizing bias. FES and ARMS showed comparable mentalizing impairments and self-referential hypermentalizing bias compared to HC. However, only ambiguous self-referential gaze perception (SRGP) bias remained significantly different between three groups after controlling for covariates. Findings suggested that self-referential hypermentalizing bias could be a specific deficit and may be considered a potential behavioral indicator in early-stage and prodromal psychosis. Moreover, working memory and social anxiety were related to the social cognitive impairments in ARMS, whereas higher-order executive functions and positive symptoms were associated with the impairments in FES. The current study indicates the presence of stage-specific mechanisms of mentalizing impairments and self-referential hypermentalizing bias, providing insights into the importance of personalized interventions to improve specific neurocognitive domains, social cognition, and clinical outcomes for FES and ARMS.

Effects of long-term antipsychotic medication on brain instability in first-episode schizophrenia patients: a resting-state fMRI study.

Early initiation of antipsychotic treatment plays a crucial role in the management of first-episode schizophrenia (FES) patients, significantly improving their prognosis. However, limited attention has been given to the long-term effects of antipsychotic drug therapy on FES patients. In this research, we examined the changes in abnormal brain regions among FES patients undergoing long-term treatment using a dynamic perspective. A total of 98 participants were included in the data analysis, comprising 48 FES patients, 50 healthy controls, 22 patients completed a follow-up period of more than 6 months with qualified data. We processed resting-state fMRI data to calculate coefficient of variation of fractional amplitude of low-frequency fluctuations (CVfALFF), which reflects the brain regional activity stability. Data analysis was performed at baseline and after long-term treatment. We observed that compared with HCs, patients at baseline showed an elevated CVfALFF in the supramarginal gyrus (SMG), parahippocampal gyrus (PHG), caudate, orbital part of inferior frontal gyrus (IOG), insula, and inferior frontal gyrus (IFG). After long-term treatment, the instability in SMG, PHG, caudate, IOG, insula and inferior IFG have ameliorated. Additionally, there was a positive correlation between the decrease in dfALFF in the SMG and the reduction in the SANS total score following long-term treatment. In conclusion, FES patients exhibit unstable regional activity in widespread brain regions at baseline, which can be ameliorated with long-term treatment. Moreover, the extent of amelioration in SMG instability is associated with the amelioration of negative symptoms.

Daratumumab, cyclophosphamide, bortezomib, and dexamethasone for transplant-ineligible myeloma: AMaRC 03-16.

ABSTRACT: In newly diagnosed transplant-ineligible patients with myeloma, daratumumab has improved outcomes when added to the standard-of-care regimens. In a randomized trial, we tested whether similar improvements would be observed when daratumumab was added to the bortezomib, cyclophosphamide, and dexamethasone (VCD) regimen. Transplant-ineligible patients with untreated myeloma were randomized to receive VCD or VCD plus daratumumab (VCDD). A total of 121 patients were randomized: 57 in the VCD arm and 64 in the VCDD arm. Baseline characteristics were balanced between the 2 arms. The median progression-free survival (PFS) was 16.8 months (95% confidence interval [CI], 15.3-21.7) and 25.8 months (95% CI, 19.9-33.5) in the VCD and VCDD arms, respectively (hazard ratio, 0.67; log-rank test P = .066). In a preplanned analysis, it was demonstrated that the daratumumab-containing arm showed a significant improvement in PFS from 18 months onward, based on estimates at fixed time points after randomization. The proportions of patients who were progression-free at the following time points were: 18 months, 48% vs 68% (P = .0002); 24 months, 36% vs 52% (P = .0001); and 30 months, 27% vs 41% (P < .0001) in the VCD and VCDD arms, respectively. The best overall response and very good partial response rate were significantly higher in the daratumumab arm compared with the VCD and VCDD arms, respectively (65% vs 86%, P = .007; and 28% vs 52%, P = .009). Seventy-two percent of the VCDD patients completed the 9 cycles of induction therapy with no grade 3 or 4 peripheral neuropathy adverse events. This study supports VCDD as an option for the initial treatment of transplant-ineligible patients with myeloma. This trial was registered at the Australian New Zealand Clinical Trials Registry (ACTRN12617000202369).

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping.

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

Modeling the effects of treatment resistance and anticholinergic burden on cognitive function domains in patients with schizophrenia.

The contribution of anticholinergic burden to cognitive function in patients with treatment resistant schizophrenia (TRS) is uncertain. This case-control study aims to comprehensively examine the association between treatment resistance and cognitive functions and the contribution of anticholinergic burden in patients with schizophrenia. Anticholinergic burden of all patients was calculated using the Anticholinergic Cognitive Burden scale. Exploratory Factor Analysis of 11 cognitive assessments identified four cognitive domains: verbal memory, attention and general cognitive functions, visual memory and processing speed, and executive function. Two structural equation models (SEM) examined the relationship of TRS and these cognitive functions with, and without considering anticholinergic burden. A total of 288 participants were included (TRS N=111, non-TRS N=177). Patients with TRS performed poorer than the non-TRS group only in the executive function domain. Anticholinergic burden contributed significantly to the attention and general cognitive functions, visual memory and processing speed, and executive function. The impact of TRS on executive function was no longer significant after adding anticholinergic burden to the SEM. Results suggested that anticholinergic burden contributes to a wide range of cognitive function impairment in patients with schizophrenia and is likely to be part of the apparent differences of cognitive function between TRS and non-TRS.

Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study.

Background: Metabolic syndrome (MetS) is common following first-episode psychosis (FEP), contributing to substantial morbidity and mortality. The Psychosis Metabolic Risk Calculator (PsyMetRiC), a risk prediction algorithm for MetS following a FEP diagnosis, was developed in the United Kingdom and has been validated in other European populations. However, the predictive accuracy of PsyMetRiC in Chinese populations is unknown. Methods: FEP patients aged 15-35 y, first presented to the Early Assessment Service for Young People with Early Psychosis (EASY) Programme in Hong Kong (HK) between 2012 and 2021 were included. A binary MetS outcome was determined based on the latest available follow-up clinical information between 1 and 12 years after baseline assessment. The PsyMetRiC Full and Partial algorithms were assessed for discrimination, calibration and clinical utility in the HK sample, and logistic calibration was conducted to account for population differences. Sensitivity analysis was performed in patients aged >35 years and using Chinese MetS criteria. Findings: The main analysis included 416 FEP patients (mean age = 23.8 y, male sex = 40.4%, 22.4% MetS prevalence at follow-up). PsyMetRiC showed adequate discriminative performance (full-model C = 0.76, 95% C.I. = 0.69-0.81; partial-model: C = 0.73, 95% C.I. = 0.65-0.8). Systematic risk underestimation in both models was corrected using logistic calibration to refine PsyMetRiC for HK Chinese FEP population (PsyMetRiC-HK). PsyMetRiC-HK provided a greater net benefit than competing strategies. Results remained robust with a Chinese MetS definition, but worse for the older age group. Interpretation: With good predictive performance for incident MetS, PsyMetRiC-HK presents a step forward for personalized preventative strategies of cardiometabolic morbidity and mortality in young Hong Kong Chinese FEP patients. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Age-related differences in the impact of resilience on mental health outcomes during the COVID-19 pandemic in Hong Kong.

OBJECTIVE: This study investigated changes in mental health in Hong Kong over two years and examined the role of resilience and age in mitigating the negative effects of public health emergencies, particularly the COVID-19 pandemic. METHODS: Complete data of interest from two telephone surveys conducted in 2020 (n = 1182) and 2021 (n = 1108) were analysed. Participants self-reported depressive and anxiety symptoms using the Patient Health Questionnaire 4-item version (PHQ), psychotic-like experiences (PLEs) using three items from the Prodromal Questionnaire Brief (PQB), and resilience using the Connor-Davidson Resilience Scale 2-item version (CD-RISC-2). RESULTS: We observed an increase in the percentage of participants with high depressive and anxiety symptoms and PLEs from 1.6% to 6.5% between 2020 and 2021. The likelihood of having high depressive and anxiety symptoms or PLEs depended on resilience and age, with no significant between-year differences. Resilience and age interaction effects were significant when comparing the high PHQ-high PQB group to the low PHQ-low PQB group only in 2021 but not in 2020. CONCLUSIONS: This study provides valuable insights into the impact of the COVID-19 pandemic on mental health in Hong Kong, emphasising the age-dependent nature of resilience in mitigating negative effects. Future research should explore the mechanisms by which resilience promotes mental health and well-being and identify ways to enhance resilience among older individuals during public health crises.

The duration of lithium use and biological ageing: telomere length, frailty, metabolomic age and all-cause mortality.

Lithium is an established first-line treatment for bipolar disorder. Beyond its therapeutic effect as a mood stabiliser, lithium exhibits potential anti-ageing effects. This study aimed to examine the relationship between the duration of lithium use, biological ageing and mortality. The UK Biobank is an observational study of middle-aged and older adults. We tested associations between the duration of lithium use (number of prescriptions, total duration of use and duration of the first prescription period) and telomere length, frailty, metabolomic age (MileAge) delta, pulse rate and all-cause mortality. Five hundred ninety-one individuals (mean age = 57.49 years; 55% females) had been prescribed lithium. There was no evidence that the number of prescriptions (ß = - 0.022, 95% CI - 0.081 to 0.037, p = 0.47), the total duration of use (ß = - 0.005, 95% CI - 0.023 to 0.013, p = 0.57) or the duration of the first prescription period (ß = - 0.018, 95% CI - 0.051 to 0.015, p = 0.29) correlated with telomere length. There was also no evidence that the duration of lithium use correlated with frailty or MileAge delta. However, a higher prescription count and a longer duration of use was associated with a lower pulse rate. The duration of lithium use did not predict all-cause mortality. We observed no evidence of associations between the duration of lithium use and biological ageing markers, including telomere length. Our findings suggest that the potential anti-ageing effects of lithium do not differ by the duration of use.

Comprehensive Review of the Safety and Efficacy of Thymosin Alpha 1 in Human Clinical Trials.

Objective: This study aims to assess the safety and efficacy of Thymosin Alpha 1 (Tα1) through a comprehensive narrative review of clinical studies involving over 11 000 human subjects in more than 30 trials. The focus was on Tα1's application in COVID-19, autoimmune conditions, and cancer treatment, with implications for future considerations. Methods: We systematically searched articles relevant to critical studies on COVID-19, infectious diseases, cancer, and autoimmune diseases indexed on Pubmed, Google Scholar, and Cochrane Library. Our focus was on evaluating the safety and efficacy of Tα1 in human subjects. Clinical trials conducted worldwide involving diverse populations were analyzed to assess the safety and effectiveness of Tα1. The review examines explicit outcomes in over 11 000 human subjects, emphasizing its role in addressing COVID-19, autoimmune conditions, and cancer treatment. Results: Contrary to the FDA's restriction on Tα1 and 21 additional peptides in 2023, our analysis reveals consistent evidence of Tα1's safety and efficacy. The peptide has demonstrated significant effectiveness in treating various conditions, including COVID-19, autoimmune disorders, and cancer. This review summarizes conclusions drawn from a comprehensive examination of clinical trials worldwide. Conclusions: Based on substantial evidence from clinical trials, Tα1 emerges as a well-tolerated and effective immune modulator. The FDA>s restriction appears unfounded, as Tα1 has shown safety and efficacy beyond the initially specified conditions. Urgent attention and intervention are warranted to ensure the continued availability of this life-saving peptide through prescription. Therefore, it is recommended that the FDA permits 503A compounding pharmacies to compound Tα1, considering its potential to treat a variety of conditions effectively.

Exploring the effects of Dasatinib, Quercetin, and Fisetin on DNA methylation clocks: a longitudinal study on senolytic interventions.

Senolytics, small molecules targeting cellular senescence, have emerged as potential therapeutics to enhance health span. However, their impact on epigenetic age remains unstudied. This study aimed to assess the effects of Dasatinib and Quercetin (DQ) senolytic treatment on DNA methylation (DNAm), epigenetic age, and immune cell subsets. In a Phase I pilot study, 19 participants received DQ for 6 months, with DNAm measured at baseline, 3 months, and 6 months. Significant increases in epigenetic age acceleration were observed in first-generation epigenetic clocks and mitotic clocks at 3 and 6 months, along with a notable decrease in telomere length. However, no significant differences were observed in second and third-generation clocks. Building upon these findings, a subsequent investigation evaluated the combination of DQ with Fisetin (DQF), a well-known antioxidant and antiaging senolytic molecule. After one year, 19 participants (including 10 from the initial study) received DQF for 6 months, with DNAm assessed at baseline and 6 months. Remarkably, the addition of Fisetin to the treatment resulted in non-significant increases in epigenetic age acceleration, suggesting a potential mitigating effect of Fisetin on the impact of DQ on epigenetic aging. Furthermore, our analyses unveiled notable differences in immune cell proportions between the DQ and DQF treatment groups, providing a biological basis for the divergent patterns observed in the evolution of epigenetic clocks. These findings warrant further research to validate and comprehensively understand the implications of these combined interventions.

Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator.

About 15-40% of patients with schizophrenia are treatment resistance (TR) and require clozapine. Identifying individuals who have higher risk of development of TR early in the course of illness is important to provide personalized intervention. A total of 1400 patients with FEP enrolled in the early intervention for psychosis service or receiving the standard psychiatric service between July 1, 1998, and June 30, 2003, for the first time were included. Clozapine prescriptions until June 2015, as a proxy of TR, were obtained. Premorbid information, baseline characteristics, and monthly clinical information were retrieved systematically from the electronic clinical management system (CMS). Training and testing samples were established with random subsampling. An automated machine learning (autoML) approach was used to optimize the ML algorithm and hyperparameters selection to establish four probabilistic classification models (baseline, 12-month, 24-month, and 36-month information) of TR development. This study found 191 FEP patients (13.7%) who had ever been prescribed clozapine over the follow-up periods. The ML pipelines identified with autoML had an area under the receiver operating characteristic curve ranging from 0.676 (baseline information) to 0.774 (36-month information) in predicting future TR. Features of baseline information, including schizophrenia diagnosis and age of onset, and longitudinal clinical information including symptoms variability, relapse, and use of antipsychotics and anticholinergic medications were important predictors and were included in the risk calculator. The risk calculator for future TR development in FEP patients (TRipCal) developed in this study could support the continuous development of data-driven clinical tools to assist personalized interventions to prevent or postpone TR development in the early course of illness and reduce delay in clozapine initiation.

Comorbidity of autism spectrum and attention deficit/hyperactivity disorder symptoms and their associations with 1-year mental health outcomes in adolescents and young adults.

Autism spectrum (ASD) and attention deficit/hyperactivity disorders (ADHD) share genetic, neurological, and behavioural features. However, related research in Asia is limited. We collected self-reported ASD and ADHD symptoms from 2186 Hong Kong adolescents and young adults aged 15-24 years, among whom, 1200 provided 1-year data on mental health-related outcomes. Comparative and network analyses were performed. Rating scale cutoff scores were used to divide participants into ASD, ADHD, comorbid, and control groups. The prevalence rates of ASD, ADHD, and comorbidities in Hong Kong were 13.3 %, 10.6 %, and 2.7 %, respectively. Compared with the control group, the comorbid group experienced more psychotic-like experiences (PLEs), the ASD group had poorer functioning, and the ADHD group had higher depression and anxiety symptoms and a lower quality of life after 1 year. The ability to switch attention, preference for routines and difficulty with change, and problems with organisation and planning were positively associated with depressive symptoms, forgetfulness and working memory issues with anxiety symptoms, and heightened sensory input and difficulties in sustaining attention and task completion with PLEs after 1 year. Our findings provide insight into support strategies to address the needs of young Asians to improving their well-being and long-term outcomes.

Evaluation of a Low-Intensity Online Intervention (LiON) for Reducing Distress and Mental Health Symptoms in Young People.

PURPOSE: Enhancing young people's mental health is crucial given that most adult mental disorders develop before age 24 years. However, it is unclear whether low-intensity interventions delivered online can be effective. This study aimed to provide preliminary evidence on whether a low-intensity online intervention (LiON) can effectively lower young people's distress levels and mental health symptoms. METHODS: We compared the preintervention and postintervention changes in distress level and severity of depression and anxiety symptoms in 137 young people aged 15-24 years who used the LiON service with the three-month changes in a 1:1 propensity score-matched control group of community young people who did not use the service. They participated in one of the following modules for the first time: (1) sleep and relaxation, (2) stress-coping, and (3) problem-solving. RESULTS: Participants who received LiON intervention (mean age 22.88 [standard deviation 3.67] years, 65.7% female) showed significantly greater reductions in distress level (Cohen's f2: 0.079), as well as the severity of depressive symptoms (Cohen's f2: 0.056) and anxiety symptoms (Cohen's f2: 0.044) compared to the control group. DISCUSSION: The findings suggest that the LiON intervention has the potential to effectively reduce distress and mental health symptoms in young people. Future research should aim to confirm these findings through randomized controlled trials and explore the cost-effectiveness of the intervention.

Investigating the role of the relaxin-3/RXFP3 system in neuropsychiatric disorders and metabolic phenotypes: A candidate gene approach.

The relaxin-3/RXFP3 system has been implicated in the modulation of depressive- and anxiety-like behaviour in the animal literature; however, there is a lack of human studies investigating this signalling system. We seek to bridge this gap by leveraging the large UK Biobank study to retrospectively assess genetic risk variants linked with this neuropeptidergic system. Specifically, we conducted a candidate gene study in the UK Biobank to test for potential associations between a set of functional, candidate single nucleotide polymorphisms (SNPs) pertinent to relaxin-3 signalling, determined using in silico tools, and several outcomes, including depression, atypical depression, anxiety and metabolic syndrome. For each outcome, we used several rigorously defined phenotypes, culminating in subsample sizes ranging from 85,881 to 386,769 participants. Across all outcomes, there were no associations between any candidate SNP and any outcome phenotype, following corrections for multiple testing burden. Regression models comprising several SNPs per relevant candidate gene as exploratory variables further exhibited no prediction of outcome. Our findings corroborate conclusions from previous literature about the limitations of candidate gene approaches, even when based on firm biological hypotheses, in the domain of genetic research for neuropsychiatric disorders.