The non-specific nature of mental health and structural brain outcomes following childhood trauma.

BACKGROUND: Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure. METHODS: We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry. RESULTS: (i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains 'emotional neglect' and 'emotional abuse' were most predictive for CHR and ROP, while in ROD 'physical abuse' and 'sexual abuse' were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found. CONCLUSIONS: These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression.

BACKGROUND: Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression. METHODS: A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test. RESULTS: Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP. CONCLUSIONS: These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Psychosocial functioning in the balance between autism and psychosis: evidence from three populations.

Functional impairment is a core feature of both autism and schizophrenia spectrum disorders. While diagnostically independent, they can co-occur in the same individual at both the trait and diagnostic levels. The effect of such co-occurrence is hypothesized to worsen functional impairment. The diametric model, however, suggests that the disorders are etiologically and phenotypically diametrical, representing the extreme of a unidimensional continuum of cognition and behavior. A central prediction of this model is that functional impairment would be attenuated in individuals with mixed symptom expressions or genetic liability to both disorders. We tested this hypothesis in two clinical populations and one healthy population. In individuals with chronic schizophrenia and in individuals with first episode psychosis we evaluated the combined effect of autistic traits and positive psychotic symptoms on psychosocial functioning. In healthy carriers of alleles of copy number variants (CNVs) that confer risk for both autism and schizophrenia, we also evaluated whether variation in psychosocial functioning depended on the combined risk conferred by each CNV. Relative to individuals with biased symptom/CNV risk profiles, results show that functional impairments are attenuated in individuals with relatively equal levels of positive symptoms and autistic traits-and specifically stereotypic behaviors-, and in carriers of CNVs with relatively equal risks for either disorder. However, the pattern of effects along the "balance axis" varied across the groups, with this attenuation being generally less pronounced in individuals with high-high symptom/risk profile in the schizophrenia and CNV groups, and relatively similar for low-low and high-high individuals in the first episode psychosis group. Lower levels of functional impairments in individuals with "balanced" symptom profile or genetic risks would suggest compensation across mechanisms associated with autism and schizophrenia. CNVs that confer equal risks for both disorders may provide an entry point for investigations into such compensatory mechanisms. The co-assessment of autism and schizophrenia may contribute to personalized prognosis and stratification strategies.

Novel Gyrification Networks Reveal Links with Psychiatric Risk Factors in Early Illness.

Adult gyrification provides a window into coordinated early neurodevelopment when disruptions predispose individuals to psychiatric illness. We hypothesized that the echoes of such disruptions should be observed within structural gyrification networks in early psychiatric illness that would demonstrate associations with developmentally relevant variables rather than specific psychiatric symptoms. We employed a new data-driven method (Orthogonal Projective Non-Negative Matrix Factorization) to delineate novel gyrification-based networks of structural covariance in 308 healthy controls. Gyrification within the networks was then compared to 713 patients with recent onset psychosis or depression, and at clinical high-risk. Associations with diagnosis, symptoms, cognition, and functioning were investigated using linear models. Results demonstrated 18 novel gyrification networks in controls as verified by internal and external validation. Gyrification was reduced in patients in temporal-insular, lateral occipital, and lateral fronto-parietal networks (pFDR < 0.01) and was not moderated by illness group. Higher gyrification was associated with better cognitive performance and lifetime role functioning, but not with symptoms. The findings demonstrated that gyrification can be parsed into novel brain networks that highlight generalized illness effects linked to developmental vulnerability. When combined, our study widens the window into the etiology of psychiatric risk and its expression in adulthood.

Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression.

BACKGROUND: Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning. AIMS: We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample. METHOD: Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD). RESULTS: Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD. CONCLUSIONS: Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

The clinical relevance of formal thought disorder in the early stages of psychosis: results from the PRONIA study.

BACKGROUND: Formal thought disorder (FTD) has been associated with more severe illness courses and functional deficits in patients with psychotic disorders. However, it remains unclear whether the presence of FTD characterises a specific subgroup of patients showing more prominent illness severity, neurocognitive and functional impairments. This study aimed to identify stable and generalizable FTD-subgroups of patients with recent-onset psychosis (ROP) by applying a comprehensive data-driven clustering approach and to test the validity of these subgroups by assessing associations between this FTD-related stratification, social and occupational functioning, and neurocognition. METHODS: 279 patients with ROP were recruited as part of the multi-site European PRONIA study (Personalised Prognostic Tools for Early Psychosis Management; www.pronia.eu). Five FTD-related symptoms (conceptual disorganization, poverty of content of speech, difficulty in abstract thinking, increased latency of response and poverty of speech) were assessed with Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS). RESULTS: The results with two patient subgroups showing different levels of FTD were the most stable and generalizable clustering solution (predicted clustering strength value = 0.86). FTD-High subgroup had lower scores in social (pfdr < 0.001) and role (pfdr < 0.001) functioning, as well as worse neurocognitive performance in semantic (pfdr < 0.001) and phonological verbal fluency (pfdr < 0.001), short-term verbal memory (pfdr = 0.002) and abstract thinking (pfdr = 0.010), in comparison to FTD-Low group. CONCLUSIONS: Clustering techniques allowed us to identify patients with more pronounced FTD showing more severe deficits in functioning and neurocognition, thus suggesting that FTD may be a relevant marker of illness severity in the early psychosis pathway.

Distinct multimodal biological and functional profiles of symptom-based subgroups in recent-onset psychosis.

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.

Anhedonia as a potential transdiagnostic phenotype with immune-related changes in recent onset mental health disorders.

BACKGROUND: Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes - reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in those with enduring illness, with few exploring inflammatory changes. We sought to identify an inflammatory signal and associated brain function underlying anhedonia among young people with recent onset psychosis (ROP) and recent onset depression (ROD). METHOD: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from N=108 (M age=26.2[SD 6.2]years; Female =50) participants with ROP (n=53) and ROD (n=55) from the EU-FP7-funded PRONIA study. Time-series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and functional connectivity model were developed to classify an anhedonic group, compared to a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic ROP/ROD groups with a balanced accuracy (BAC) of 63.9%, and an area under the curve (AUC) of 0.61. The functional connectivity model produced a BAC of 55.2% and an AUC of 0.57. Anhedonic group assignment was driven by higher levels of Interleukin-6, S100B, and Interleukin-1 receptor antagonist, and lower levels of Interferon gamma, in addition to connectivity within the precuneus and posterior cingulate. CONCLUSION: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

A Cross-sectional Conceptual Replication and Longitudinal Evaluation of the PANSS-Autism-Severity-Score Measure Suggests it Does Not Capture Autistic Traits in Individuals With Psychosis.

BACKGROUND: Autism and psychosis co-occur at elevated rates, with implications for clinical outcomes, functioning, and suicidality. The PANSS-Autism-Severity-Score (PAUSS) is a measure of autism trait severity which has not yet been validated externally or longitudinally. STUDY DESIGN: Participants were derived from the GROUP and SCOPE datasets. Participants included 1448 adults with schizophrenia spectrum disorder (SSD), 800 SSD-siblings, 103 adults diagnosed with an autistic spectrum condition (ASC), and 409 typically-developing controls (TC). Analyses from the original validation study were conducted with SSD participants, and extended into ASC, SSD-sibling, and TC participants. Test-retest reliability of the PAUSS at 2-weeks and long-term stability 3 and 6-years was also examined. STUDY RESULTS: Results differed in important ways from the original validation. SSD participants reported higher PAUSS scores than other groups, with only a fraction of ASC participants scoring as "PAUSS-Autistic." Cronbach's alpha was acceptable for the SSD cohort only. Two-week stability of the PAUSS was fair to good for all PAUSS scores. Long-term stability was poor for most PAUSS items but fair for total PAUSS score. CONCLUSIONS: Results suggest that the PAUSS does not appear appropriate for assessing autism, with the low rate of PAUSS-Autistic in the ASC population suggesting the PAUSS may not accurately reflect characteristics of autism. The relative lack of long-term stability is cause for concern and suggestive that the PAUSS is capturing features of psychosis rather than autism traits.

The heterogeneity of attenuated and brief limited psychotic symptoms: association of contents with age, sex, country, religion, comorbidities, and functioning.

Introduction: The Attenuated Psychosis Symptoms (APS) syndrome mostly represents the ultra-high-risk state of psychosis but, as does the Brief Intermittent Psychotic Symptoms (BIPS) syndrome, shows a large variance in conversion rates. This may be due to the heterogeneity of APS/BIPS that may be related to the effects of culture, sex, age, and other psychiatric morbidities. Thus, we investigated the different thematic contents of APS and their association with sex, age, country, religion, comorbidity, and functioning to gain a better understanding of the psychosis-risk syndrome. Method: A sample of 232 clinical high-risk subjects according to the ultra-high risk and basic symptom criteria was recruited as part of a European study conducted in Germany, Italy, Switzerland, and Finland. Case vignettes, originally used for supervision of inclusion criteria, were investigated for APS/BIPS contents, which were compared for sex, age, country, religion, functioning, and comorbidities using chi-squared tests and regression analyses. Result: We extracted 109 different contents, mainly of APS (96.8%): 63 delusional, 29 hallucinatory, and 17 speech-disorganized contents. Only 20 contents (18.3%) were present in at least 5% of the sample, with paranoid and referential ideas being the most frequent. Thirty-one (28.5%) contents, in particular, bizarre ideas and perceptual abnormalities, demonstrated an association with age, country, comorbidity, or functioning, with regression models of country and obsessive-compulsive disorders explaining most of the variance: 55.8 and 38.3%, respectively. Contents did not differ between religious groups. Conclusion: Psychosis-risk patients report a wide range of different contents of APS/BIPS, underlining the psychopathological heterogeneity of this group but also revealing a potential core set of contents. Compared to earlier reports on North-American samples, our maximum prevalence rates of contents were considerably lower; this likely being related to a stricter rating of APS/BIPS and cultural influences, in particular, higher schizotypy reported in North-America. The various associations of some APS/BIPS contents with country, age, comorbidities, and functioning might moderate their clinical severity and, consequently, the related risk for psychosis and/or persistent functional disability.

Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study.

BACKGROUND: Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. METHODS: Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. RESULTS: Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%. CONCLUSIONS: We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.

A randomised controlled feasibility trial for an educational school-based mental health intervention: study protocol.

BACKGROUND: With the burden of mental illness estimated to be costing the English economy alone around £22.5 billion a year 1, coupled with growing evidence that many mental disorders have their origins in adolescence, there is increasing pressure for schools to address the emotional well-being of their students, alongside the stigma and discrimination of mental illness. A number of prior educational interventions have been developed and evaluated for this purpose, but inconsistency of findings, reporting standards, and methodologies have led the majority of reviewers to conclude that the evidence for the efficacy of these programmes remains inconclusive. METHODS/DESIGN: A cluster randomised controlled trial design has been employed to enable a feasibility study of 'SchoolSpace', an intervention in 7 UK secondary schools addressing stigma of mental illness, mental health literacy, and promotion of mental health. A central aspect of the intervention involves students in the experimental condition interacting with a young person with lived experience of mental illness, a stigma reducing technique designed to facilitate students' engagement in the project. The primary outcome is the level of stigma related to mental illness. Secondary outcomes include mental health literacy, resilience to mental illness, and emotional well-being. Outcomes will be measured pre and post intervention, as well as at 6 month follow-up. DISCUSSION: The proposed intervention presents the potential for increased engagement due to its combination of education and contact with a young person with lived experience of mental illness. Contact as a technique to reduce discrimination has been evaluated previously in research with adults, but has been employed in only a minority of research trials investigating the impact on youth. Prior to this study, the effect of contact on mental health literacy, resilience, and emotional well-being has not been evaluated to the authors' knowledge. If efficacious the intervention could provide a reliable and cost-effective method to reduce stigma in young people, whilst increasing mental health literacy, and emotional well-being. TRIAL REGISTRATION: ISRCTN: ISRCTN07406026.

Occurrence of psychosis and bipolar disorder in adults with autism: A systematic review and meta-analysis.

OBJECTIVE: Evidence suggests that individuals with autism spectrum disorder have increased rates of co-occurring psychosis and/or bipolar disorder. Considering the peak age of onset for psychosis and bipolar disorder occurs in adulthood, we investigated the co-occurrence of these disorders in adults with autism. METHODS: We conducted a systematic review and meta-analysis (PROSPERO Registration Number: CRD42018104600) to (1) examine the prevalence of psychosis and bipolar disorder in adults with autism, and (2) review potential risk factors associated with their co-occurrence. RESULTS: Fifty-three studies were included. The pooled prevalence for the co-occurrence of psychosis in adults with autism was 9.4 % (N = 63,657, 95 %CI = 7.52, 11.72). The pooled prevalence for the co-occurrence of bipolar disorders in adults with autism was 7.5 % (N = 31,739, 95 %CI = 5.79, 9.53). CONCLUSIONS: Psychosis and bipolar disorder occur at a substantially higher prevalence in adults with autism compared to general population estimates. While there is an overall dearth of research examining risk factors for these disorders in autism, males had increased likelihood of co-occurring psychosis, and females of co-occurring bipolar disorder. These results highlight the need for ongoing assessment and monitoring of these disorders in adults with autism.

Relationships between global functioning and neuropsychological predictors in subjects at high risk of psychosis or with a recent onset of depression.

OBJECTIVE: Psychotic disorders are frequently associated with decline in functioning and cognitive difficulties are observed in subjects at clinical high risk (CHR) for psychosis. In this work, we applied automatic approaches to neurocognitive and functioning measures, with the aim of investigating the link between global, social and occupational functioning, and cognition. METHODS: 102 CHR subjects and 110 patients with recent onset depression (ROD) were recruited. Global assessment of functioning (GAF) related to symptoms (GAF-S) and disability (GAF-D). and global functioning social (GF-S) and role (GF-R), at baseline and of the previous month and year, and a set of neurocognitive measures, were used for classification and regression. RESULTS: Neurocognitive measures related to GF-R at baseline (r = 0.20, p = 0.004), GF-S at present (r = 0.14, p = 0.042) and of the past year (r = 0.19, p = 0.005), for GAF-F of the past month (r = 0.24, p < 0.001) and GAF-D of the past year (r = 0.28, p = 0.002). Classification reached values of balanced accuracy of 61% for GF-R and GAF-D. CONCLUSION: We found that neurocognition was related to psychosocial functioning. More specifically, a deficit in executive functions was associated to poor social and occupational functioning.

Neurobiologically Based Stratification of Recent-Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes.

BACKGROUND: Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. METHODS: HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). RESULTS: The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. CONCLUSIONS: We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages.

Importance: Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures. Objective: To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages. Design, Setting, and Participants: A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022. Main Outcomes and Measures: A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample. Results: There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample. Conclusions and Relevance: The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

Gender differences in the experience of psychotic-like experiences and their associated factors: A study of adolescents from the general population.

"Psychotic-Like Experiences" (PLEs) are common in the general population. While they are usually transient and resolve spontaneously, they can be distressing and signify increased risk for later psychosis or other psychopathology. It is important to investigate factors associated with PLEs which could be targeted to reduce their prevalence and impact. Males and females are known to experience PLEs differently, but any gender differences in the relationships between PLEs and other, potentially targetable, factors are currently unknown. 302 adolescents (175 females, mean age = 16.03, SD = 0.75; 127 males, mean age = 16.09, SD = 0.74) from secondary schools in the West Midlands region of the UK completed baseline self-report measures of positive PLEs, measured by the Community Assessment of Psychic Experiences (CAPE-P), and several potentially related factors including: cannabis use, perceived stress, anxiety, depression, and daily hassles. PLEs were common in this sample, with 67.5% of individuals experiencing at least one CAPE-P item 'often' or 'almost always'. Females reported significantly higher levels of PLEs, and associated distress, than males. Anxiety, depressive, and stress symptoms were similarly associated with PLEs in both genders. However, there was a significant interaction of gender and daily hassles in the association with PLEs. In summary, there were significant gender differences in the experience of PLEs in this sample. Although daily hassles were more common in females, they had a significantly stronger association with PLEs in males. Thus, addressing "daily life stress" in adolescents may require tailoring towards the more emotional perception of stress in females, and towards everyday life hassles in males.

Sleep disturbances and the At Risk Mental State: A systematic review and meta-analysis.

AIMS: To synthesise and investigate how sleep disturbances relate to psychotic symptoms, functioning and Quality of Life (QoL) in At Risk Mental State (ARMS) youth. METHOD: A comprehensive search of six databases (MEDLINE, PsycINFO, Embase, CINAHL, Web of Science and CENTRAL) was conducted. Eligible studies provided data on sleep disturbances or disorders in ARMS patients. RESULTS: Sixteen studies met the inclusion criteria (n = 1962 ARMS patients) including 7 cross-sectional studies, 2 RCT's and 7 cohort studies. Narrative synthesis revealed that self-reported sleep (e.g., general disturbances, fragmented night time sleep and nightmares) was poorer among ARMS patients compared to healthy controls. In the limited studies (n = 4) including objective measurements of sleep disturbances, ARMS patients experienced higher levels of movement during sleep, more daytime naps and increased sleep latency compared to controls. Furthermore, sleep disturbances were associated with attenuated psychotic symptoms and functional outcomes cross-sectionally and longitudinally. Only one study investigated the relationship between sleep and QoL. The exploratory meta-analysis revealed a significant difference in self-reported sleep disturbances measured by the PSQI (mean difference in score: 3.30 (95% CI 1.87, 4.74), p < 0.00001) and SIPS (mean difference in score: 1.58 (95% CI 0.80, 2.35), p < 0.00001) of ARMS patients compared to control groups. CONCLUSIONS: ARMS individuals report impaired sleep quality and reduced sleep quantity compared to healthy controls. However, further research is needed to explore the longitudinal relationship between sleep disruptions and QoL in early psychosis. Significant variations in how sleep is measured across studies highlight a need to assess disturbances to sleep using robust and consistent approaches in this patient group.

Towards clinical application of prediction models for transition to psychosis: A systematic review and external validation study in the PRONIA sample.

A multitude of prediction models for a first psychotic episode in individuals at clinical high-risk (CHR) for psychosis have been proposed, but only rarely validated. We identified transition models based on clinical and neuropsychological data through a registered systematic literature search and evaluated their external validity in 173 CHRs from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC), and compared to the prediction of clinical raters. External discrimination performance varied considerably across the 22 identified models (AUC 0.40-0.76), with two models showing good discrimination performance. None of the tested models significantly outperformed clinical raters (AUC = 0.75). Combining predictions of clinical raters and the best model descriptively improved discrimination performance (AUC = 0.84). Results show that personalized prediction of transition in CHR is potentially feasible on a global scale. For implementation in clinical practice, further rounds of external validation, impact studies, and development of an ethical framework is necessary.

Heterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning Approach.

Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.