Psychosis Risk: Time to Look Empirically at a First-step Economical-pragmatic Way to Examine Anomalous Self-experience. Exploring the SQuEASE-11.

BACKGROUND: Since the late 1990s, there has been a worldwide surge of scientific interest in the pre-psychotic phase, resulting in the introduction of several clinical tools for early detection. The predictive accuracy of these tools has been limited, motivating the need for methodological and perspectival improvements. The EASE manual supports systematic assessment of anomalous self-experience, and proposes an overall model of understanding how most psychotic experiences may be initially generated on the basis of a unifying, fundamental, pre-reflective distortion of subjectivity. STUDY DESIGN: The EASE is time-consuming, so in order to spread the use of this essential perspective of psychosis risk we selected prototypical and frequent phenomena from the EASE, combining them into SQuEASE-11. To investigate this instrument for clinical relevance, basic psychometric properties, factor structure, and relationships with gold standard instruments and the full EASE, it was administered as an interview in the STEP intervention trial (Melbourne, Australia), with 328 clinical high-risk for psychosis (CHR-P) patients. STUDY RESULTS: The SQuEASE-11 had moderate internal consistency and revealed two correlated factors. Significant relationships were observed between the SQuEASE-11 and the widely used and validated instruments CAARMS, BPRS, SANS, MADRS, DACOBS, and SOFAS. The correlation with the full EASE was very strong. CONCLUSIONS: These 11 items do not necessarily relate specifically to ipseity disturbance, but the SQuEASE-11 seems to be a clinically relevant and brief supplementary first-line interview in CHR-P subjects. It may give a qualified indication of the need for a complete EASE interview, and it may also, importantly, inform treatment planning.

Are Psychiatric Nosologies Limiting the Success of Clinical Prediction Models?

This Viewpoint discusses the limitations of clinical prediction models in psychiatric research.

Development and temporal validation of a clinical prediction model of transition to psychosis in individuals at ultra-high risk in the UHR 1000+ cohort.

The concept of ultra-high risk for psychosis (UHR) has been at the forefront of psychiatric research for several decades, with the ultimate goal of preventing the onset of psychotic disorder in high-risk individuals. Orygen (Melbourne, Australia) has led a range of observational and intervention studies in this clinical population. These datasets have now been integrated into the UHR 1000+ cohort, consisting of a sample of 1,245 UHR individuals with a follow-up period ranging from 1 to 16.7 years. This paper describes the cohort, presents a clinical prediction model of transition to psychosis in this cohort, and examines how predictive performance is affected by changes in UHR samples over time. We analyzed transition to psychosis using a Cox proportional hazards model. Clinical predictors for transition to psychosis were investigated in the entire cohort using multiple imputation and Rubin's rule. To assess performance drift over time, data from 1995-2016 were used for initial model fitting, and models were subsequently validated on data from 2017-2020. Over the follow-up period, 220 cases (17.7%) developed a psychotic disorder. Pooled hazard ratio (HR) estimates showed that the Comprehensive Assessment of At-Risk Mental States (CAARMS) Disorganized Speech subscale severity score (HR=1.12, 95% CI: 1.02-1.24, p=0.024), the CAARMS Unusual Thought Content subscale severity score (HR=1.13, 95% CI: 1.03-1.24, p=0.009), the Scale for the Assessment of Negative Symptoms (SANS) total score (HR=1.02, 95% CI: 1.00-1.03, p=0.022), the Social and Occupational Functioning Assessment Scale (SOFAS) score (HR=0.98, 95% CI: 0.97-1.00, p=0.036), and time between onset of symptoms and entry to UHR service (log transformed) (HR=1.10, 95% CI: 1.02-1.19, p=0.013) were predictive of transition to psychosis. UHR individuals who met the brief limited intermittent psychotic symptoms (BLIPS) criteria had a higher probability of transitioning to psychosis than those who met the attenuated psychotic symptoms (APS) criteria (HR=0.48, 95% CI: 0.32-0.73, p=0.001) and those who met the Trait risk criteria (a first-degree relative with a psychotic disorder or a schizotypal personality disorder plus a significant decrease in functioning during the previous year) (HR=0.43, 95% CI: 0.22-0.83, p=0.013). Models based on data from 1995-2016 displayed good calibration at initial model fitting, but showed a drift of 20.2-35.4% in calibration when validated on data from 2017-2020. Large-scale longitudinal data such as those from the UHR 1000+ cohort are required to develop accurate psychosis prediction models. It is critical to assess existing and future risk calculators for temporal drift, that may reduce their utility in clinical practice over time.

Brainwide Anatomical Connectivity and Prediction of Longitudinal Outcomes in Antipsychotic-Naïve First-Episode Psychosis.

BACKGROUND: Disruptions of axonal connectivity are thought to be a core pathophysiological feature of psychotic illness, but whether they are present early in the illness, prior to antipsychotic exposure, and whether they can predict clinical outcome remain unknown. METHODS: We acquired diffusion-weighted magnetic resonance images to map structural connectivity between each pair of 319 parcellated brain regions in 61 antipsychotic-naïve individuals with first-episode psychosis (15-25 years, 46% female) and a demographically matched sample of 27 control participants. Clinical follow-up data were also acquired in patients 3 and 12 months after the scan. We used connectome-wide analyses to map disruptions of inter-regional pairwise connectivity and connectome-based predictive modeling to predict longitudinal change in symptoms and functioning. RESULTS: Individuals with first-episode psychosis showed disrupted connectivity in a brainwide network linking all brain regions compared with controls (familywise error-corrected p = .03). Baseline structural connectivity significantly predicted change in functioning over 12 months (r = 0.44, familywise error-corrected p = .041), such that lower connectivity within fronto-striato-thalamic systems predicted worse functional outcomes. CONCLUSIONS: Brainwide reductions of structural connectivity exist during the early stages of psychotic illness and cannot be attributed to antipsychotic medication. Moreover, baseline measures of structural connectivity can predict change in patient functional outcomes up to 1 year after engagement with treatment services.

Do Cognitive Subtypes Exist in People at Clinical High Risk for Psychosis? Results From the EU-GEI Study.

BACKGROUND AND HYPOTHESIS: Cognition has been associated with socio-occupational functioning in individuals at Clinical High Risk for Psychosis (CHR-P). The present study hypothesized that clustering CHR-P participants based on cognitive data could reveal clinically meaningful subtypes. STUDY DESIGN: A cohort of 291 CHR-P subjects was recruited through the multicentre EU-GEI high-risk study. We explored whether an underlying cluster structure was present in the cognition data. Clustering of cognition data was performed using k-means clustering and density-based spatial clustering of applications with noise. Cognitive subtypes were validated by comparing differences in functioning, psychosis symptoms, transition outcome, and grey matter volume between clusters. Network analysis was used to further examine relationships between cognition scores and clinical symptoms. STUDY RESULTS: No underlying cluster structure was found in the cognitive data. K-means clustering produced "spared" and "impaired" cognition clusters similar to those reported in previous studies. However, these clusters were not associated with differences in functioning, symptomatology, outcome, or grey matter volume. Network analysis identified cognition and symptoms/functioning measures that formed separate subnetworks of associations. CONCLUSIONS: Stratifying patients according to cognitive performance has the potential to inform clinical care. However, we did not find evidence of cognitive clusters in this CHR-P sample. We suggest that care needs to be taken in inferring the existence of distinct cognitive subtypes from unsupervised learning studies. Future research in CHR-P samples could explore the existence of cognitive subtypes across a wider range of cognitive domains.

Harmonizing early intervention strategies: scoping review of clinical high risk for psychosis and borderline personality disorder.

Aims: To map studies assessing both clinical high risk for psychosis (CHR-P) and borderline personality disorder (BPD) in clinical samples, focusing on clinical/research/preventive paradigms and proposing informed research recommendations. Methods: We conducted a PRISMA-ScR/JBI-compliant scoping review (protocol: https://osf.io/8mz7a) of primary research studies (cross-sectional/longitudinal designs) using valid measures/criteria to assess CHR-P and BPD (threshold/subthreshold) in clinical samples, reporting on CHR-P/psychotic symptoms and personality disorder(s) in the title/abstract/keywords, identified in Web of Science/PubMed/(EBSCO)PsycINFO until 23/08/2023. Results: 33 studies were included and categorized into four themes reflecting their respective clinical/research/preventive paradigm: (i) BPD as a comorbidity in CHR-P youth (k = 20), emphasizing early detection and intervention in psychosis; (ii) attenuated psychosis syndrome (APS) as a comorbidity among BPD inpatients (k = 2), with a focus on hospitalized adolescents/young adults admitted for non-psychotic mental disorders; (iii) mixed samples (k = 7), including descriptions of early intervention services and referral pathways; (iv) transdiagnostic approaches (k = 4) highlighting "clinical high at risk mental state" (CHARMS) criteria to identify a pluripotent risk state for severe mental disorders. Conclusion: The scoping review reveals diverse approaches to clinical care for CHR-P and BPD, with no unified treatment strategies. Recommendations for future research should focus on: (i) exploring referral pathways across early intervention clinics to promote timely intervention; (ii) enhancing early detection strategies in innovative settings such as emergency departments; (iii) improving mental health literacy to facilitate help-seeking behaviors; (iv) analysing comorbid disorders as complex systems to better understand and target early psychopathology; (v) investigating prospective risk for BPD; (vi) developing transdiagnostic interventions; (vii) engaging youth with lived experience of comorbidity to gain insight on their subjective experience; (viii) understanding caregiver burden to craft family-focused interventions; (ix) expanding research in underrepresented regions such as Africa and Asia, and; (x) evaluating the cost-effectiveness of early interventions to determine scalability across different countries. Systematic Review Registration: https://osf.io/8mz7a.

Erythrocyte membrane fatty acid concentrations and myelin integrity in young people at ultra-high risk of psychosis.

Decreased white matter (WM) integrity and disturbance in fatty acid composition have been reported in individuals at ultra-high risk of psychosis (UHR). The current study is the first to investigate both WM integrity and erythrocyte membrane polyunsaturated fatty acid (PUFA) levels as potential risk biomarkers for persistent UHR status, and global functioning in UHR individuals. Forty UHR individuals were analysed at baseline for erythrocyte membrane PUFA concentrates. Tract-based spatial statistics (TBSS) was used to analyse fractional anisotropy (FA) and diffusivity measures. Measures of global functioning and psychiatric symptoms were evaluated at baseline and at 12-months. Fatty acids and WM indices did not predict functional outcomes at baseline or 12-months. Significant differences were found in FA between UHR remitters and non-remitters (individuals who no longer met UHR criteria versus those who continued to meet criteria at 12-months). Docosahexaenoic acid (DHA) was found to be a significant predictor of UHR status at 12-months, as was the interaction between the sum of ώ-3 and whole brain FA, and the interaction between the right anterior limb of the internal capsule and the sum of ώ-3. The results confirm that certain fatty acids have a unique relationship with WM integrity in UHR individuals.

PsyCog: A computerised mini battery for assessing cognition in psychosis.

Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) (N = 135), Clinical High Risk (CHR) (N = 233), and First Episode Psychosis (FEP) (N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design.

An open label pilot trial of low-dose lithium for young people at ultra-high risk for psychosis.

AIM: Lithium, even at low doses, appears to offer neuroprotection against a wide variety of insults. In this controlled pilot, we examined the safety (i.e., side-effect profile) of lithium in a sample of young people identified at ultra-high risk (UHR) for psychosis. The secondary aim was to explore whether lithium provided a signal of clinical efficacy in reducing transition to psychosis compared with treatment as usual (TAU). METHODS: Young people attending the PACE clinic at Orygen, Melbourne, were prescribed a fixed dose (450 mg) of lithium (n = 25) or received TAU (n = 78). The primary outcome examined side-effects, with transition to psychosis, functioning and measures of psychopathology assessed as secondary outcomes. RESULTS: Participants in both groups were functionally compromised (lithium group GAF = 56.6; monitoring group GAF = 56.9). Side-effect assessment indicated that lithium was well-tolerated. 64% (n = 16) of participants in the lithium group were lithium-adherent to week 12. Few cases transitioned to psychosis across the study period; lithium group 4% (n = 1); monitoring group 7.7% (n = 6). There was no difference in time to transition to psychosis between the groups. No group differences were observed in other functioning and symptom domains, although all outcomes improved over time. CONCLUSIONS: With a side-effect profile either comparable to, or better than UHR antipsychotic trials, lithium might be explored for further research with UHR young people. A definitive larger trial is needed to determine the efficacy of lithium in this cohort.

Staging 2.0: refining transdiagnostic clinical staging frameworks to enhance reliability and utility for youth mental health.

Globally, 75% of depressive, bipolar, and psychotic disorders emerge by age 25 years. However, these disorders are often preceded by non-specific symptoms or attenuated clinical syndromes. Difficulties in determining optimal treatment interventions for these emerging mental disorders, and uncertainties about accounting for co-occurring psychopathology and illness trajectories, have led many youth mental health services to adopt transdiagnostic clinical staging frameworks. In this Health Policy paper, an international working group highlights ongoing challenges in applying transdiagnostic staging frameworks in clinical research and practice, and proposes refinements to the transdiagnostic model to enhance its reliability, consistent recording, and clinical utility. We introduce the concept of within-stage heterogeneity and describe the advantages of defining stage in terms of clinical psychopathology and stage modifiers. Using examples from medicine, we discuss the utility of categorising stage modifiers into factors associated with progression (ie, potential predictors of stage transition) and extension (ie, factors associated with the current presentation that add complexity to treatment selection). Lastly, we suggest how it is possible to revise the currently used transdiagnostic staging approach to incorporate these key concepts, and how the revised framework could be applied in clinical and research practice.

Nomenclature for psychosis risk in Japan: Survey results from high-risk individuals, caregivers, and mental health professionals.

BACKGROUND: Labeling terms for high-risk state for psychosis, such as 'ultra-high risk' (UHR), 'attenuated psychosis syndrome' (APS), and 'at-risk mental state' (ARMS), have been criticized for their potential to lead to stigma. Hence, mental health service users in Melbourne recently proposed new terms illustrating the at-risk concept ['pre-diagnosis stage' (PDS), 'potential of developing a mental illness' (PDMI), and 'disposition for developing a mental illness' (DDMI)]. We aimed at testing the suitability of these existing and new terms in the clinical settings of early psychiatric intervention in Japan. METHODS: At two centers of early intervention (Toyama and Tokyo), a questionnaire on the understanding and opinion of high-risk terminology was administered to 62 high-risk patients, 44 caregivers, and 64 clinicians. The questionnaire contained the existing and new terms, where the term ARMS was translated into two different Japanese terms ARMS-psychosis and ARMS-kokoro. Participants' opinion on the disclosure of high-risk status was also obtained. RESULTS: ARMS-kokoro was most preferred, least stigmatizing, and best explaining the patients' difficulties for all groups, while UHR and other terms including the Japanese word 'psychosis' (i.e., APS and ARMS-psychosis) were not preferred. New labeling terms were generally not well received. All groups preferred full disclosure of high-risk terms by the psychiatrist with or without the presence of family members. CONCLUSION: The term ARMS-kokoro was commonly accepted as a favorable labeling term for the high-risk state for psychosis in Japan. However, another translation ARMS-psychosis was considered stigmatizing, demonstrating the importance of appropriate translation of high-risk terminology into local languages.

A Dynamical Systems View of Psychiatric Disorders-Theory: A Review.

Importance: Psychiatric disorders may come and go with symptoms changing over a lifetime. This suggests the need for a paradigm shift in diagnosis and treatment. Here we present a fresh look inspired by dynamical systems theory. This theory is used widely to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. Observations: In the dynamical systems view, we propose the healthy state has a basin of attraction representing its resilience, while disorders are alternative attractors in which the system can become trapped. Rather than an immutable trait, resilience in this approach is a dynamical property. Recent work has demonstrated the universality of generic dynamical indicators of resilience that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforests and tipping elements of the climate system. Other dynamical systems tools are used in ecology and climate science to infer causality from time series. Moreover, experiences in ecological restoration confirm the theoretical prediction that under some conditions, short interventions may invoke long-term success when they flip the system into an alternative basin of attraction. All this implies practical applications for psychiatry, as are discussed in part 2 of this article. Conclusions and Relevance: Work in the field of dynamical systems points to novel ways of inferring causality and quantifying resilience from time series. Those approaches have now been tried and tested in a range of complex systems. The same tools may help monitoring and managing resilience of the healthy state as well as psychiatric disorders.

A Dynamical Systems View of Psychiatric Disorders-Practical Implications: A Review.

Importance: Dynamical systems theory is widely used to explain tipping points, cycles, and chaos in complex systems ranging from the climate to ecosystems. It has been suggested that the same theory may be used to explain the nature and dynamics of psychiatric disorders, which may come and go with symptoms changing over a lifetime. Here we review evidence for the practical applicability of this theory and its quantitative tools in psychiatry. Observations: Emerging results suggest that time series of mood and behavior may be used to monitor the resilience of patients using the same generic dynamical indicators that are now employed globally to monitor the risks of collapse of complex systems, such as tropical rainforest and tipping elements of the climate system. Other dynamical systems tools used in ecology and climate science open ways to infer personalized webs of causality for patients that may be used to identify targets for intervention. Meanwhile, experiences in ecological restoration help make sense of the occasional long-term success of short interventions. Conclusions and Relevance: Those observations, while promising, evoke follow-up questions on how best to collect dynamic data, infer informative timescales, construct mechanistic models, and measure the effect of interventions on resilience. Done well, monitoring resilience to inform well-timed interventions may be integrated into approaches that give patients an active role in the lifelong challenge of managing their resilience and knowing when to seek professional help.

A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort.

BACKGROUND: We examined the course of illness over a 12-month period in a large, international multi-center cohort of people with a first-episode schizophrenia spectrum disorder (FES) in a naturalistic, prospective study (PSYSCAN). METHOD: Patients with a first episode of schizophrenia, schizoaffective disorder (depressive type) or schizophreniform disorder were recruited at 16 institutions in Europe, Israel and Australia. Participants (N = 304) received clinical treatment as usual throughout the study. RESULTS: The mean age of the cohort was 24.3 years (SD = 5.6), and 67 % were male. At baseline, participants presented with a range of intensities of psychotic symptoms, 80 % were taking antipsychotic medication, 68 % were receiving psychological treatment, with 46.5 % in symptomatic remission. The mean duration of untreated psychosis was 6.2 months (SD = 17.0). After one year, 67 % were in symptomatic remission and 61 % were in functional remission, but 31 % had been readmitted to hospital at some time after baseline. In the cohort as a whole, depressive symptoms remained stable over the follow-up period. In patients with a current depressive episode at baseline, depressive symptoms slightly improved. Alcohol, tobacco and cannabis were the most commonly used substances, with daily users of cannabis ranging between 9 and 11 % throughout the follow-up period. CONCLUSIONS: This study provides valuable insight into the early course of a broad range of clinical and functional aspects of illness in FES patients in routine clinical practice.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Non-psychotic Outcomes in Young People at Ultra-High Risk of Developing a Psychotic Disorder: A Long-Term Follow-up Study.

BACKGROUND: The majority of individuals at ultra-high risk (UHR) for psychosis do not transition to a full threshold psychotic disorder. It is therefore important to understand their longer-term clinical and functional outcomes, particularly given the high prevalence of comorbid mental disorders in this population at baseline. AIMS: This study investigated the prevalence of non-psychotic disorders in the UHR population at entry and long-term follow-up and their association with functional outcomes. Persistence of UHR status was also investigated. STUDY DESIGN: The sample comprised 102 UHR young people from the Personal Assessment and Crisis Evaluation (PACE) Clinic who had not transitioned to psychosis by long-term follow-up (mean = 8.8 years, range = 6.8-12.1 years since baseline). RESULTS: Eighty-eight percent of participants at baseline were diagnosed with at least one mental disorder, the majority of which were mood disorders (78%), anxiety disorders (35%), and substance use disorders (SUDs) (18%). This pattern of disorder prevalence continued at follow-up, though prevalence was reduced, with 52% not meeting criteria for current non-psychotic mental disorder. However, 35% of participants developed a new non-psychotic mental disorder by follow-up. Presence of a continuous non-psychotic mental disorder was associated with poorer functional outcomes at follow-up. 28% of participants still met UHR criteria at follow-up. CONCLUSIONS: The study adds to the evidence base that a substantial proportion of UHR individuals who do not transition to psychosis experience persistent attenuated psychotic symptoms and persistent and incident non-psychotic disorders over the long term. Long-term treatment and re-entry into services is indicated.

Transdiagnostic risk identification: A validation study of the Clinical High At Risk Mental State (CHARMS) criteria.

A set of clinical criteria, the Clinical High At-Risk Mental State (CHARMS) criteria, have been developed to identify symptomatic young people who are at-risk of disorder progression. The current study aimed to validate the CHARMS criteria by testing whether they prospectively identify individuals at-risk of progressing from attenuated symptomatology to a first episode of serious mental disorder, namely first episode psychosis, first episode mania, severe major depression, and borderline personality disorder. 121 young people completed clinical evaluations at baseline, 6- and 12-month follow-up. The Kaplan-Meier method was used to assess transition rates. Cox regression and LASSO were used to examine baseline clinical predictors of transition. Linear mixed effects modelling was used to examine symptom severity. 28 % of CHARMS+ individuals transitioned to a Stage 2 disorder by 12-month follow-up. The CHARMS+ group had more severe symptoms at follow-up than the CHARMS- group. 96 % of Stage 2 transitions were initially to severe depression. Meeting criteria for multiple CHARMS subgroups was associated with higher transition risk: meeting one at-risk group = 24 %; meeting two at-risk groups = 17 %, meeting three at-risk groups = 55 %, meeting four at-risk groups = 50 %. The strongest baseline predictor of transition was severity of depressive symptoms. The CHARMS criteria identified a group of individuals at-risk of imminent onset of severe mental disorder, particularly severe depression. Larger scale studies and longer follow-up periods are required to validate and extend these findings.

Psychosis superspectrum I: Nosology, etiology, and lifespan development.

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

The temporal association between social isolation, distress, and psychotic experiences in individuals at clinical high-risk for psychosis.

BACKGROUND: Psychotic experiences (PEs) and social isolation (SI) seem related during early stages of psychosis, but the temporal dynamics between the two are not clear. Literature so far suggests a self-perpetuating cycle wherein momentary increases in PEs lead to social withdrawal, which, subsequently, triggers PEs at a next point in time, especially when SI is associated with increased distress. The current study investigated the daily-life temporal associations between SI and PEs, as well as the role of SI-related and general affective distress in individuals at clinical high risk (CHR) for psychosis. METHODS: We used experience sampling methodology in a sample of 137 CHR participants. We analyzed the association between SI, PEs, and distress using time-lagged linear mixed-effects models. RESULTS: SI did not predict next-moment fluctuations in PEs, or vice versa. Furthermore, although SI-related distress was not predictive of subsequent PEs, general affective distress during SI was a robust predictor of next-moment PEs. CONCLUSIONS: Our results suggest that SI and PEs are not directly related on a moment-to-moment level, but a negative emotional state when alone does contribute to the risk of PEs. These findings highlight the role of affective wellbeing during early-stage psychosis development.

Proteomic Biomarkers for the Prediction of Transition to Psychosis in Individuals at Clinical High Risk: A Multi-cohort Model Development Study.

Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD: 3.9; 51.9% male), 20.4% (n = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C-statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution.