Relationship between jumping to conclusions and clinical outcomes in people at clinical high-risk for psychosis.

BACKGROUND: Psychosis is associated with a reasoning bias, which manifests as a tendency to 'jump to conclusions'. We examined this bias in people at clinical high-risk for psychosis (CHR) and investigated its relationship with their clinical outcomes. METHODS: In total, 303 CHR subjects and 57 healthy controls (HC) were included. Both groups were assessed at baseline, and after 1 and 2 years. A 'beads' task was used to assess reasoning bias. Symptoms and level of functioning were assessed using the Comprehensive Assessment of At-Risk Mental States scale (CAARMS) and the Global Assessment of Functioning (GAF), respectively. During follow up, 58 (16.1%) of the CHR group developed psychosis (CHR-T), and 245 did not (CHR-NT). Logistic regressions, multilevel mixed models, and Cox regression were used to analyse the relationship between reasoning bias and transition to psychosis and level of functioning, at each time point. RESULTS: There was no association between reasoning bias at baseline and the subsequent onset of psychosis. However, when assessed after the transition to psychosis, CHR-T participants showed a greater tendency to jump to conclusions than CHR-NT and HC participants (55, 17, 17%; χ2 = 8.13, p = 0.012). There was a significant association between jumping to conclusions (JTC) at baseline and a reduced level of functioning at 2-year follow-up in the CHR group after adjusting for transition, gender, ethnicity, age, and IQ. CONCLUSIONS: In CHR participants, JTC at baseline was associated with adverse functioning at the follow-up. Interventions designed to improve JTC could be beneficial in the CHR population.

Urban Mind: Using Smartphone Technologies to Investigate the Impact of Nature on Mental Well-Being in Real Time.

Existing evidence on the beneficial effects of nature on mental health comes from studies using cross-sectional designs. We developed a smartphone-based tool (Urban Mind; www.urbanmind.info) to examine how exposure to natural features within the built environment affects mental well-being in real time. The tool was used to monitor 108 individuals who completed 3013 assessments over a 1-week period. Significant immediate and lagged associations with mental well-being were found for several natural features. These associations were stronger in people with higher trait impulsivity, a psychological measure of one's tendency to behave with little forethought or consideration of the consequences, which is indicative of a higher risk of developing mental-health issues. Our investigation suggests that the benefits of nature on mental well-being are time-lasting and interact with an individual's vulnerability to mental illness. These findings have potential implications from the perspectives of global mental health as well as urban planning and design.

Smartphone-based ecological momentary assessment reveals an incremental association between natural diversity and mental wellbeing.

Using smartphone-based ecological momentary assessment, this study investigated an association between natural diversity on mental wellbeing. A sample of 1,998 participants completed 41,448 assessments between April 2018 and September 2023. Environments which included a larger range of natural features, such as trees, plants and birdlife (high natural diversity) were associated with greater mental wellbeing than environments including a smaller range of natural features (low natural diversity). There was evidence of a mediating effect of natural diversity on the association between natural environments and mental wellbeing. These results highlight the importance of policies and practices that support richness of biodiversity for public mental health.

Individual placement and support focusing on employment and education for young people at clinical high risk of psychosis: A feasibility study.

OBJECTIVE: This study aimed to assess the feasibility of implementing Individual Placement and Support (IPS) with a focus on educational and employment goals, within a clinical service for the early detection of individuals at clinical high risk (CHR) of psychosis. METHOD: Between June 2019 and April 2021, participants were recruited and received up to 6 (± 2) months support. Primary outcome: Enrolled participants, attended sessions, and disengagement rates were analyzed to assess feasibility. SECONDARY OUTCOMES: Enrollment in mainstream education or/and employment, hours spent working or/and studying, salary, level of functioning, and self-efficacy at baseline and follow-up were compared. RESULTS: Thirty-one participants were recruited, 13 of whom were remotely recruited after the first COVID-19 lockdown. Dropout rates were relatively low (16.1%), and 26 participants (83.9%) completed the program. Each participant received on average nine sessions (M = 9.65; SD = 4.92). Secondary outcomes: At follow-up, 73.1% participants were employed, working on average more hours per week, t(25) = -2.725; p = .012, and were earning significantly more money, t(25) = -3.702; p = .001, compared to baseline. Gains in educational outcomes were less clear. Global Assessment of Functioning, t = 248.50; p = .001, and Social Occupational Functioning, t(25) = -3.273; p = .003, were significantly higher at 6-month follow-up compared to baseline. No differences were found in participants' self-efficacy. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Findings indicate that research procedures are appropriate and that IPS implementation within a CHR clinical team is feasible. Secondary outcomes also suggest that IPS may be a beneficial intervention for young people at CHR. A longer follow-up might be needed to assess its impact on educational outcomes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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.

Understanding the relationship between time spent outdoors, mental well-being and health-related behaviours in a Spanish sample: A real time smartphone-based study.

INTRODUCTION: COVID-19 pandemic has affected our lifestyle and physical and mental well-being. We aimed to study the effect of being outdoors and mental well-being after the COVID-19 pandemic. MATERIAL AND METHODS: We used smartphone based ecological momentary assessments (EMA) (Urban Mind app) to study the mental well-being of the Spanish general population. We collected socio-demographic data, past and current physical and mental health, and social and physical environment. Participants were recruited during 5 months (February to June 2021). Longitudinal associations between EMA and anxiety, depression, loneliness, tiredness, and happiness during the assessments were investigated using random intercept ordinal logistic regression models. RESULTS: 274 subjects downloaded the app and completed the baseline assessment. 66 participants completed at least 50 % of the assessments. Being outdoors was related to a lower likelihood of anxiety (OR: 0.48, 95 %CI 0.34-0.66), depression (OR: 0.40, 95 %CI 0.28-0.56), tiredness (OR: 0.47, 95 %CI 0.35-0.63), and loneliness (OR: 0.59, 95 %CI 0.42-0.84), and a higher likelihood of happiness (OR: 2.14, 95 %CI 1.57-2.93). CONCLUSIONS: Being outdoors is related to better mental health in the general population independently of other factors (baseline mental well-being or socio-demographic characteristics). Public policies should include measurements to promote outdoor spaces in urban settings.

Impact of adverse childhood experiences on educational achievements in young people at clinical high risk of developing psychosis.

BACKGROUND: Adverse childhood experiences (ACE) can affect educational attainments, but little is known about their impact on educational achievements in people at clinical high risk of psychosis (CHR). METHODS: In total, 344 CHR individuals and 67 healthy controls (HC) were recruited as part of the European Community's Seventh Framework Programme-funded multicenter study the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI). The brief version of the Child Trauma Questionnaire was used to measure ACE, while educational attainments were assessed using a semi-structured interview. RESULTS: At baseline, compared with HC, the CHR group spent less time in education and had higher rates of ACE, lower rates of employment, and lower estimated intelligence quotient (IQ). Across both groups, the total number of ACE was associated with fewer days in education and lower level of education. Emotional abuse was associated with fewer days in education in HC. Emotional neglect was associated with a lower level of education in CHR, while sexual abuse was associated with a lower level of education in HC. In the CHR group, the total number of ACE, physical abuse, and neglect was significantly associated with unemployment, while emotional neglect was associated with employment. CONCLUSIONS: ACE are strongly associated with developmental outcomes such as educational achievement. Early intervention for psychosis programs should aim at integrating specific interventions to support young CHR people in their educational and vocational recovery. More generally, public health and social interventions focused on the prevention of ACE (or reduce their impact if ACE occur) are recommended.

No rest for the weary: Prevalence, impact and nature of sleep problems among young people at risk of psychosis.

AIMS: Sleep problems are common in people with a psychosis-spectrum diagnosis and are associated with worse psychotic symptoms and lower quality of life. Sleep problems are also frequent in individuals at a clinical high risk for psychosis (CHR-P) however, less is known about the prevalence and association with symptoms in this population. This study investigates the prevalence of sleep problems within CHR-P individuals and the associations with attenuated positive symptoms, transition to psychosis, time to transition to psychosis and functioning. METHODS: The clinical records interactive search (CRIS) tool was used to carry out a retrospective study of 795 CHR-P individuals. Sleep problems, subsequent psychotic diagnoses, attenuated positive symptoms and Health of The Nation Outcome Scale scores were extracted. Regression models were used to examine the association between sleep problems and clinical outcomes. RESULTS: 59.5% of CHR-P individuals experienced sleep problems. Perceptual abnormality severity (OR = 1.24, 95% CI = 1.05-1.48) and frequency (OR = 1.31, 95% CI = 1.08-1.58) as measured by the Comprehensive Assessment of At-Risk Mental State interview, predicted sleep problems. Sleep problems were not associated with transition to psychosis; however, they were significantly associated with a shorter time to transition in individuals who developed psychosis (HR = 1.4, 95% CI = 1.05-1.88) and higher follow-up Health of the Nation Outcome Scale scores (MD = 2.26, 95% CI = 0.55-3.96). CONCLUSIONS: The high prevalence of sleep problems, along with the association with positive symptoms and worse functioning, highlights the need for effective sleep interventions in this population. Further research is needed to better understand the relationship between sleep problems and transition to psychosis.

The mental health benefits of visiting canals and rivers: An ecological momentary assessment study.

Existing evidence shows positive effects of being in nature on wellbeing, but we know little about the mental health benefits of spending time near canals and rivers specifically. This study investigates the association between visits to canals and rivers and mental wellbeing. We addressed the following questions: Are visits to canals and rivers associated with higher levels of mental wellbeing? Does this association depend on age and gender? Does this association vary between people with and without a diagnosis on mental illness? We used Urban Mind, a flexible smartphone application for examining the impact of different aspects of the built and social environment on mental wellbeing, a strong predictor of mental health. Participants were invited to complete an ecological momentary assessment three times a day for fourteen days. Each assessment included questions about their surrounding environment and mental wellbeing. A total of 7,975 assessments were completed by 299 participants including 87 with a diagnosis of mental illness. Multilevel regression models were used to analyse the data. We found positive associations between visits to canals and rivers and mental wellbeing (p < .05) when compared to being anywhere else and when compared to being in green spaces. Increases in mental wellbeing were still evident after the visit had taken place. These effects remained significant after adjusting for age, gender, ethnicity and education, and were consistent in people with and without a diagnosis of mental illness. Spending time near canals and rivers is associated with better mental wellbeing. These findings have potential implications for mental health as well as urban planning and policy. Visits to canals and rivers could become part of social prescribing schemes, playing a role in preventing mental health difficulties and complementing more traditional interventions.

Smartphone-based ecological momentary assessment reveals mental health benefits of birdlife.

The mental health benefits of everyday encounters with birdlife for mental health are poorly understood. Previous studies have typically relied on retrospective questionnaires or artificial set-ups with little ecological validity. In the present study, we used the Urban Mind smartphone application to examine the impact of seeing or hearing birds on self-reported mental wellbeing in real-life contexts. A sample of 1292 participants completed a total of 26,856 ecological momentary assessments between April 2018 and October 2021. Everyday encounters with birdlife were associated with time-lasting improvements in mental wellbeing. These improvements were evident not only in healthy people but also in those with a diagnosis of depression, the most common mental illness across the world. These findings have potential implications for both environmental and wildlife protection and mental healthcare policies. Specific measures, aimed at preserving and increasing everyday encounters with birdlife in urban areas, should be implemented.

Identifying Electroencephalography Biomarkers in Individuals at Clinical High Risk for Psychosis in an International Multi-Site Study.

Background: The clinical high-risk for psychosis (CHR-P) paradigm was introduced to detect individuals at risk of developing psychosis and to establish preventive strategies. While current prediction of outcomes in the CHR-P state is based mostly on the clinical assessment of presenting features, several emerging biomarkers have been investigated in an attempt to stratify CHR-P individuals according to their individual trajectories and refine the diagnostic process. However, heterogeneity across subgroups is a key challenge that has limited the impact of the CHR-P prediction strategies, as the clinical validity of the current research is limited by a lack of external validation across sites and modalities. Despite these challenges, electroencephalography (EEG) biomarkers have been studied in this field and evidence suggests that EEG used in combination with clinical assessments may be a key measure for improving diagnostic and prognostic accuracy in the CHR-P state. The PSYSCAN EEG study is an international, multi-site, multimodal longitudinal project that aims to advance knowledge in this field. Methods: Participants at 6 international sites take part in an EEG protocol including EEG recording, cognitive and clinical assessments. CHR-P participants will be followed up after 2 years and subcategorised depending on their illness progression regarding transition to psychosis. Differences will be sought between CHR-P individuals and healthy controls and between CHR-P individuals who transition and those who do not transition to psychosis using data driven computational analyses. Discussion: This protocol addresses the challenges faced by previous studies of this kind to enable valid identification of predictive EEG biomarkers which will be combined with other biomarkers across sites to develop a prognostic tool in CHR-P. The PSYSCAN EEG study aims to pave the way for incorporating EEG biomarkers in the assessment of CHR-P individuals, to refine the diagnostic process and help to stratify CHR-P subjects according to risk of transition. This may improve our understanding of the CHR-P state and therefore aid the development of more personalized treatment strategies.

The Relationship Between Grey Matter Volume and Clinical and Functional Outcomes in People at Clinical High Risk for Psychosis.

Objective: To examine the association between baseline alterations in grey matter volume (GMV) and clinical and functional outcomes in people at clinical high risk (CHR) for psychosis. Methods: 265 CHR individuals and 92 healthy controls were recruited as part of a prospective multi-center study. After a baseline assessment using magnetic resonance imaging (MRI), participants were followed for at least two years to determine clinical and functional outcomes, including transition to psychosis (according to the Comprehensive Assessment of an At Risk Mental State, CAARMS), level of functioning (according to the Global Assessment of Functioning), and symptomatic remission (according to the CAARMS). GMV was measured in selected cortical and subcortical regions of interest (ROI) based on previous studies (ie orbitofrontal gyrus, cingulate gyrus, gyrus rectus, inferior temporal gyrus, parahippocampal gyrus, striatum, and hippocampus). Using voxel-based morphometry, we analysed the relationship between GMV and clinical and functional outcomes. Results: Within the CHR sample, a poor functional outcome (GAF < 65) was associated with relatively lower GMV in the right striatum at baseline (P < .047 after Family Wise Error correction). There were no significant associations between baseline GMV and either subsequent remission or transition to psychosis. Conclusions: In CHR individuals, lower striatal GMV was associated with a poor level of overall functioning at follow-up. This finding was not related to effects of antipsychotic or antidepressant medication. The failure to replicate previous associations between GMV and later psychosis onset, despite studying a relatively large sample, is consistent with the findings of recent large-scale multi-center studies.

Verbal memory performance predicts remission and functional outcome in people at clinical high-risk for psychosis.

Robust deficits in cognitive functioning are present in people with psychosis and are evident in the early stages of the disorder. Impairments in verbal memory and verbal fluency are reliably seen in individuals at clinical high-risk for psychosis (CHR) compared to healthy populations. As previous studies have shown a relationship between cognition and longer-term outcomes in schizophrenia, the aim of this paper was to explore whether verbal memory and verbal fluency performance predicted outcomes in a large CHR sample recruited as part of the EU-GEI High Risk Study. Participants included 316 CHR individuals, 90.8% of whom were not currently on antipsychotic medication, and 60 healthy controls. Verbal memory and verbal fluency performance were measured at baseline. At two-year follow-up, CHR individuals were assessed by three different outcome measures, those who did and did not (1) transition to psychosis, (2) experience burdening impairment or disabilities, or (3) remit clinically from CHR status. Individuals with CHR displayed significant verbal memory and verbal fluency deficits at baseline compared to healthy controls (Hedges' g effect size = 0.24 to 0.66). There were no significant differences in cognitive performance of those who did and did not transition to psychosis. However, impaired immediate verbal recall predicted both functional disability and non-remission from the CHR state. Results remained significant when analyses were restricted to only include antipsychotic-free CHR participants. These findings may inform the development of early interventions designed to improve cognitive deficits in the early stages of psychosis.

Effects of DTNBP1 genotype on brain development in children.

BACKGROUND: Schizophrenia is a neurodevelopmental disorder, and risk genes are thought to act through disruption of brain development. Several genetic studies have identified dystrobrevin-binding protein 1 (DTNBP1, also known as dysbindin) as a potential susceptibility gene for schizophrenia, but its impact on brain development is poorly understood. The present investigation examined for the first time the effects of DTNBP1 on brain structure in children. Our hypothesis was that a genetic variation in DTNBP1 (i.e., the single nucleotide polymorphism rs2619538) would be associated with differences in both gray and white matter brain regions previously implicated in schizophrenia. METHODS: Magnetic resonance imaging and voxel-based morphometry were used to examine brain structure in 52 male children aged between 10 and 12 years. Statistical inferences on the effects of DTNBP1 genotype on gray and white matter volume (GMV and WMV) were made at p < .05 after family-wise error correction for multiple comparisons across the whole brain. RESULTS: Individuals homozygous for the schizophrenia high-risk allele (AA) compared with those homozygous for the low-risk allele (TT) expressed reduced GMV in the left anterior cingulate gyrus and reduced WMV in the left medial frontal area. CONCLUSIONS: Our results suggest that genetic variation in DTNBP1 is associated with differences in gray and white matter; and that these effects are already evident in children as young as 10-12 years. These findings are consistent with the notion that the DTNBP1 genotype influences brain development and may thereby modulate vulnerability to schizophrenia.

Lonely in a crowd: investigating the association between overcrowding and loneliness using smartphone technologies.

Loneliness is a major public health concern with links to social and environmental factors. Previous studies have typically investigated loneliness as a stable emotional state using retrospective cross-sectional designs. Yet people experience different levels of loneliness throughout the day depending on their surrounding environment. In the present study, we investigated the associations between loneliness and social and environmental factors (i.e. overcrowding, population density, social inclusivity and contact with nature) in real-time. Ecological momentary assessment data was collected from participants using the Urban Mind smartphone application. Data from 756 participants who completed 16,602 assessments between April 2018 and March 2020 were used in order to investigate associations between momentary feeling of loneliness, the social environment (i.e. overcrowding, social inclusivity, population density) and the built environment (i.e. contact with nature) using multilevel modelling. Increased overcrowding and population density were associated with higher levels of loneliness; in contrast, social inclusivity and contact with nature were associated with lower levels of loneliness. These associations remained significant after adjusting for age, gender, ethnicity, education and occupation. The positive association between social inclusivity and lower levels of loneliness was more pronounced when participants were in contact with nature, indicating an interaction between the social and built environment on loneliness. The feeling of loneliness changes in relation to both social and environmental factors. Our findings have potential implications for public health strategies and interventions aimed at reducing the burden of loneliness on society. Specific measures, which would increase social inclusion and contact with nature while reducing overcrowding, should be implemented, especially in densely populated cities.

Influence of neuregulin1 genotype on neural substrate of perceptual matching in children.

Adult psychopathology is often rooted early in life and first emerges during childhood and adolescence. However, as most imaging genetic research to date has involved adult participants, little is known about how risk genes affect brain function to influence biological vulnerability in childhood. We examined the impact of neuregulin1 (NRG1), a probable susceptibility gene for schizophrenia and bipolar disorder, on brain function in a sample of 102 healthy 10-12 year old boys including 18 pairs of monozygotic twins, 24 pairs of dizygotic twins and 18 singletons. Each participant performed a perceptual matching task, while brain responses were measured using functional magnetic resonance imaging. Response accuracy and reaction times did not differ as a function of NRG1 genotype; however, individuals with two high-risk alleles showed relatively increased brain activation in a distributed network comprising the precuneus bilaterally, and the left cuneus, middle occipital gyrus, angular gyrus and caudate nucleus. These results indicate that genetic variation in NRG1 significantly affects cortical function during perceptual and monitoring processes in healthy children as young as 10-12 years of age.

Using Machine Learning and Structural Neuroimaging to Detect First Episode Psychosis: Reconsidering the Evidence.

Despite the high level of interest in the use of machine learning (ML) and neuroimaging to detect psychosis at the individual level, the reliability of the findings is unclear due to potential methodological issues that may have inflated the existing literature. This study aimed to elucidate the extent to which the application of ML to neuroanatomical data allows detection of first episode psychosis (FEP), while putting in place methodological precautions to avoid overoptimistic results. We tested both traditional ML and an emerging approach known as deep learning (DL) using 3 feature sets of interest: (1) surface-based regional volumes and cortical thickness, (2) voxel-based gray matter volume (GMV) and (3) voxel-based cortical thickness (VBCT). To assess the reliability of the findings, we repeated all analyses in 5 independent datasets, totaling 956 participants (514 FEP and 444 within-site matched controls). The performance was assessed via nested cross-validation (CV) and cross-site CV. Accuracies ranged from 50% to 70% for surfaced-based features; from 50% to 63% for GMV; and from 51% to 68% for VBCT. The best accuracies (70%) were achieved when DL was applied to surface-based features; however, these models generalized poorly to other sites. Findings from this study suggest that, when methodological precautions are adopted to avoid overoptimistic results, detection of individuals in the early stages of psychosis is more challenging than originally thought. In light of this, we argue that the current evidence for the diagnostic value of ML and structural neuroimaging should be reconsidered toward a more cautious interpretation.

Emotion Recognition and Adverse Childhood Experiences in Individuals at Clinical High Risk of Psychosis.

OBJECTIVE: To investigate the association between facial affect recognition (FAR) and type of adverse childhood experiences (ACEs) in a sample of clinical high risk (CHR) individuals and a matched sample of healthy controls (HCs). METHODS: In total, 309 CHR individuals and 51 HC were recruited as part of an European Union-funded multicenter study (EU-GEI) and included in this work. During a 2-year follow-up period, 65 CHR participants made a transition to psychosis (CHR-T) and 279 did not (CHR-NT). FAR ability was measured using a computerized version of the Degraded Facial Affect Recognition (DFAR) task. ACEs were measured using the Childhood Experience of Care and Abuse Questionnaire, the Childhood Trauma Questionnaire, and the Bullying Questionnaire. Generalized regression models were used to investigate the relationship between ACE and FAR. Logistic regressions were used to investigate the relationship between FAR and psychotic transition. RESULTS: In CHR individuals, having experienced emotional abuse was associated with decreased total and neutral DFAR scores. CHR individuals who had experienced bullying performed better in the total DFAR and in the frightened condition. In HC and CHR, having experienced the death of a parent during childhood was associated with lower DFAR total score and lower neutral DFAR score, respectively. Analyses revealed a modest increase of transition risk with increasing mistakes from happy to angry faces. CONCLUSIONS: Adverse experiences in childhood seem to have a significant impact on emotional processing in adult life. This information could be helpful in a therapeutic setting where both difficulties in social interactions and adverse experiences are often addressed.

Towards Precision Medicine in Psychosis: Benefits and Challenges of Multimodal Multicenter Studies-PSYSCAN: Translating Neuroimaging Findings From Research into Clinical Practice.

In the last 2 decades, several neuroimaging studies investigated brain abnormalities associated with the early stages of psychosis in the hope that these could aid the prediction of onset and clinical outcome. Despite advancements in the field, neuroimaging has yet to deliver. This is in part explained by the use of univariate analytical techniques, small samples and lack of statistical power, lack of external validation of potential biomarkers, and lack of integration of nonimaging measures (eg, genetic, clinical, cognitive data). PSYSCAN is an international, longitudinal, multicenter study on the early stages of psychosis which uses machine learning techniques to analyze imaging, clinical, cognitive, and biological data with the aim of facilitating the prediction of psychosis onset and outcome. In this article, we provide an overview of the PSYSCAN protocol and we discuss benefits and methodological challenges of large multicenter studies that employ neuroimaging measures.

Association of Adverse Outcomes With Emotion Processing and Its Neural Substrate in Individuals at Clinical High Risk for Psychosis.

Importance: The development of adverse clinical outcomes in patients with psychosis has been associated with behavioral and neuroanatomical deficits related to emotion processing. However, the association between alterations in brain regions subserving emotion processing and clinical outcomes remains unclear. Objective: To examine the association between alterations in emotion processing and regional gray matter volumes in individuals at clinical high risk (CHR) for psychosis, and the association with subsequent clinical outcomes. Design, Setting, and Participants: This naturalistic case-control study with clinical follow-up at 12 months was conducted from July 1, 2010, to August 31, 2016, and collected data from 9 psychosis early detection centers (Amsterdam, Basel, Cologne, Copenhagen, London, Melbourne, Paris, The Hague, and Vienna). Participants (213 individuals at CHR and 52 healthy controls) were enrolled in the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) project. Data were analyzed from October 1, 2018, to April 24, 2019. Main Measures and Outcomes: Emotion recognition was assessed with the Degraded Facial Affect Recognition Task. Three-Tesla magnetic resonance imaging scans were acquired from all participants, and gray matter volume was measured in regions of interest (medial prefrontal cortex, amygdala, hippocampus, and insula). Clinical outcomes at 12 months were evaluated for transition to psychosis using the Comprehensive Assessment of At-Risk Mental States criteria, and the level of overall functioning was measured through the Global Assessment of Functioning [GAF] scale. Results: A total of 213 individuals at CHR (105 women [49.3%]; mean [SD] age, 22.9 [4.7] years) and 52 healthy controls (25 women [48.1%]; mean [SD] age, 23.3 [4.0] years) were included in the study at baseline. At the follow-up within 2 years of baseline, 44 individuals at CHR (20.7%) had developed psychosis and 169 (79.3%) had not. Of the individuals at CHR reinterviewed with the GAF, 39 (30.0%) showed good overall functioning (GAF score, ≥65), whereas 91 (70.0%) had poor overall functioning (GAF score, <65). Within the CHR sample, better anger recognition at baseline was associated with worse functional outcome (odds ratio [OR], 0.88; 95% CI, 0.78-0.99; P = .03). In individuals at CHR with a good functional outcome, positive associations were found between anger recognition and hippocampal volume (ze = 3.91; familywise error [FWE] P = .02) and between fear recognition and medial prefrontal cortex volume (z = 3.60; FWE P = .02), compared with participants with a poor outcome. The onset of psychosis was not associated with baseline emotion recognition performance (neutral OR, 0.93; 95% CI, 0.79-1.09; P = .37; happy OR, 1.03; 95% CI, 0.84-1.25; P = .81; fear OR, 0.98; 95% CI, 0.85-1.13; P = .77; anger OR, 1.00; 95% CI, 0.89-1.12; P = .96). No difference was observed in the association between performance and regional gray matter volumes in individuals at CHR who developed or did not develop psychosis (FWE P < .05). Conclusions and Relevance: In this study, poor functional outcome in individuals at CHR was found to be associated with baseline abnormalities in recognizing negative emotion. This finding has potential implications for the stratification of individuals at CHR and suggests that interventions that target socioemotional processing may improve functional outcomes.