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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 people with enduring illness, but few have explored inflammatory changes. We sought to identify an inflammatory signal and the associated brain function underlying anhedonia among young people with recent-onset psychosis and recent-onset depression. METHODS: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from 108 (mean [SD] age = 26.2 [6.2] years; female = 50) participants with recent-onset psychosis (n = 53) and recent-onset depression (n = 55) from the European Union/Seventh Framework Programme-funded PRONIA (Personalised Prognostic Tools for Early Psychosis Management) 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 a functional connectivity model were developed to classify participants into an anhedonic group or a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic recent-onset psychosis/recent-onset depression groups with a balanced accuracy of 63.9% and an area under the curve of 0.61. The functional connectivity model produced a balanced accuracy of 55.2% and an area under the curve 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. CONCLUSIONS: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications

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

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

BACKGROUND: Prolonged Exposure (PE), a trauma-focused therapy, is one of the most efficacious treatments available for PTSD. However, many people with PTSD do not lose their diagnosis following delivery of PE. The Unified Protocol (UP) for Transdiagnostic Treatment of Emotional Disorders is a non-trauma focused treatment that may offer an alternative treatment for PTSD. METHODS: This paper describes the study protocol for IMPACT, an assessor-blinded randomized controlled trial that examines the non-inferiority of UP relative to PE for participants who meet DSM-5 criteria for current PTSD. One hundred and twenty adult participants with PTSD will be randomized to receive either 10 × 90-min sessions of UP or PE with a trained provider. The primary outcome is severity of PTSD symptoms assessed by the Clinician Administered PTSD Scale for DSM-5 (CAPS-5) at post-treatment. DISCUSSION: While evidence-based treatments are available for PTSD, high levels of treatment dropout and non-response require new approaches to be tested. The UP is based on emotion regulation theory and is effective in treating anxiety and depressive disorders, however, there has been limited application to PTSD. This is the first rigorous study comparing UP to PE in a non-inferiority randomized controlled trial and may help improve clinical outcomes for those with PTSD. TRIAL REGISTRATION: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry, Trial ID (ACTRN12619000543189).

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 transdiagnost

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.

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.

INTRODUCTION: The terms 'precision medicine' and 'personalised medicine' have become key terms in health-related research and in science-related public communication. However, the application of these two concepts and their interpretation in various disciplines are heterogeneous, which also affects research translation and public awareness. This leads to confusion regarding the use and distinction of the two concepts. Our aim is to provide a snapshot of the current understanding of these concepts. METHODS AND ANALYSIS: Our study will use Rodgers' evolutionary concept analysis to systematically examine the current understanding of the concepts 'precision medicine' and 'personalised medicine' in clinical medicine, biomedicine (incorporating genomics and bioinformatics), health services research, physics, chemistry, engineering, machine learning and artificial intelligence, and to identify their respective attributes (clusters of characteristics) and surrogate and related terms. A systematic search of the literature will be conducted for 2016-2022 using databases relevant to each of these disciplines: ACM Digital Library, CINAHL, Cochrane Library, F1000Research, IEEE Xplore, PubMed/Medline, Science Direct, Scopus and Web of Science. These are among the most representative databases for the included disciplines. We will examine similarities and differences in definitions of 'precision medicine' and 'personalised medicine' in the respective disciplines and across (sub)disciplines, including attributes of each term. This will enable us to determine how these two concepts are distinguished. ETHICS AND DISSEMINATION: Following ethical and research standards, we will comprehensively report the methodology for a systematic analysis following Rodgers' concept analysis method. Our systematic concept analysis will contribute to the clarification of the two concepts and distinction in their application in given settings and circumstances. Such a broad concept analysis will contri

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.

Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models' ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40-64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.

The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP) is an intervention that targets common mechanisms that maintain symptoms across multiple disorders. The UP has been shown to be effective across many disorders, including generalized anxiety disorder, major depressive episode (MDE), and panic disorder, that commonly codevelop following trauma exposure. The present study represented the first randomized controlled trial of the UP in the treatment of trauma-related psychopathology, including posttraumatic stress disorder (PTSD), depression, and anxiety symptoms. Adults (N = 43) who developed posttraumatic psychopathology that included PTSD, MDE, or an anxiety disorder after sustaining a severe injury were randomly assigned to receive 10-14 weekly, 60-min sessions of UP (n = 22) or usual care (n = 21). The primary treatment outcome was PTSD symptom severity, with secondary outcomes of depression and anxiety symptom severity and loss of diagnosis for any trauma-related psychiatric disorder. Assessments were conducted at intake, posttreatment, and 6-month follow-up. Posttreatment, participants who received the UP showed significantly larger reductions in PTSD, Hedges' g = 1.27; anxiety, Hedges' g = 1.20; and depression symptom severity, Hedges' g = 1.40, compared to those receiving usual care. These treatment effects were maintained at 6-month follow-up for PTSD, anxiety, and depressive symptom severity. Statistically significant posttreatment loss of PTSD, MDE, and agoraphobia diagnoses was observed for participants who received the UP but not usual care. This study provides preliminary evidence that the UP may be an effective non-trauma-focused treatment for PTSD and other trauma-related psychopathology.

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.

IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear. OBJECTIVES: To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system. DESIGN, SETTING, AND PARTICIPANTS: This multisite, longitudinal prognostic study performed in 7 academic early recognition services in 5 European countries followed up patients with CHR syndromes or ROD and healthy volunteers. The referred sample of 167 patients with CHR syndromes and 167 with ROD was recruited from February 1, 2014, to May 31, 2017, of whom 26 (23 with CHR syndromes and 3 with ROD) developed psychosis. Patients with 18-month follow-up (n = 246) were used for model training and leave-one-site-out cross-validation. The remaining 88 patients with nontransition served as the validation of model specificity. Three hundred thirty-four healthy volunteers provided a normative sample for prognostic signature evaluation. Three independent Swiss projects contributed a further 45 cases with psychosis transition and 600 with nontransition for the external validation of clinical-neurocognitive, sMRI-based, and combined models. Data were analyzed from January 1, 2019, to March 31, 2020. MAIN OUTCOMES AND MEASURES: Accuracy and generalizability of prognostic systems. RESULTS: A total of 668 individuals (334 patients and 334 controls) were included in the analysis (mean [SD] age, 25.1 [5.

Background: Intermittent energy restriction (IER) has shown early success in adolescents with obesity, however efficacy trials are needed. This study aims to determine if IER results in lower body mass index (BMI) z-score after 52 weeks in metabolically unhealthy adolescents with obesity compared with continuous energy restriction (CER). Methods/design: This is a prospective, randomised, multi-centre trial conducted in tertiary care settings, with three phases: jumpstart (weeks 0-4); intensive intervention (weeks 5-16); continued intervention and/or maintenance (weeks 17-52). During the jumpstart phase, all participants follow a very low energy diet (~800 kcal/3350 kJ/day), then transition to their allocated intervention: IER or CER. IER involves three energy-restricted days/week, consuming one-third of daily energy requirements (~600-700 kcal/2500-2950 kJ/day), and four days/week of a healthy meal plan. The CER, which is current standard care, has individually tailored energy prescription based on age and sex (13-14 years, 1430-1670 kcal/6000-7000 kJ/day; 15-17 years, 1670-1900 kcal/7000-8000 kJ/day). The study will recruit 186 (93 per arm) treatment-seeking adolescents aged 13-17 years with obesity and at least one metabolic co-morbidity. The primary outcome is change in BMI z-score at 52 weeks. Secondary outcomes are changes at 4, 16 and 52 weeks in: body composition; diet quality, food choices and food patterns; cardio-metabolic risk factors; physical activity and sedentary behaviour; sleep and psycho-behavioural measures. Discussion(s): This study challenges existing clinical paradigms that CER is the only method for weight management in metabolically unhealthy adolescents. If successful, IER may offer an alternate medical nutrition therapy approach for those seeking treatment in tertiary settings. Clinical trial registration number: ACTRN12617001630303.Copyright © 2019

Background Psychotic disorders are associated with serious deterioration in functioning even before the first psychotic episode. Also on clinical high risk (CHR) states of developing a first psychotic episode, several studies reported a decreased global functioning. In a considerable proportion of CHR individuals, functional deterioration remains even after (transient) remission of symptomatic risk indicators. Furthermore, deficits in functioning cause immense costs for the health care system and are often more debilitating for individuals than positive symptoms. However in the past, CHR research has mostly focused on clinical outcomes like transition. Prediction of functioning in CHR populations has received less attention. Therefore, the current study aims at predicting functioning in CHR individuals at a single subject level applying multi pattern recognition to clinical data. Patients with a first depressive episode who frequently have persistent functional deficits comparable to patients in the CHR state were investigated in addition. Methods PRONIA (‘Personalized Prognostic Tools for Early Psychosis Management’) is a prospective collaboration project funded by the European Union under the 7th Framework Programme (grant agreement n°602152). Considering a broad set of variables (MRI, clinical data, neurocognition, genomics and other blood derived parameters) as well as advanced statistical methods, PRONIA aims at developing an innovative multivariate prognostic tool enabling an individualized prediction of illness trajectories and outcome. 11 university centers in five European countries and in Australia (Munich, Basel, Birmingham, Cologne, Düsseldorf, Münster, Melbourne, Milan, Udine, Bari, Turku) participate in the evaluation of three clinical groups (subjects clinically at high risk of developing a psychosis [CHR], patients with a recent onset psychosis [ROP] and patients with a recent onset depression [ROD]) as well as healthy controls. In the curre

INTRODUCTION: There is a recognized increase in vulnerability to psychosis in autistic people (AP). However, the construct of psychosis (particularly schizophrenia) contains several distinct factors, making understanding the relationship between autism and psychosis complex. Previous research has suggested that affective lability may be particularly related to psychotic experiences for AP who have experienced psychosis (AP-P). There is also a suggestion that psychosis might be a state of extreme (over)empathizing, perhaps related to emotional processes. METHOD: We recruited three groups: AP-P (N = 23), a group of AP who had not experienced psychosis (AP-NP; N = 59) and a neurotypical control group (NC, N = 41). Participants completed measures of autistic traits, schizotypal traits (as a proxy for psychosis-proneness), emotional processes, and perspective taking (as a proxy for the type of empathizing most theoretically likely to be linked to psychosis). As well as comparisons between groups, regression analyses were used to understand the influence of dependent variables on schizotypal traits. RESULTS: We found that AP-P had significantly higher rates of schizotypy (positive and disorganized), as well as higher rates of emotional difficulties. Across all groups, affective lability had a positive and significant association with positive and disorganized schizotypal traits. Differences in perspective taking between groups were small and generally non-significant, particularly in adjusted comparisons; additionally, its impact on schizotypy was small and non-significant. DISCUSSION: Our findings suggest that positive and disorganized schizotypy, in particular, have a relationship with affective lability. This, in turn, supports the idea of emotional processes as related to the development of schizotypal traits and psychosis across all individuals, regardless of autism diagnostic status. We found no evidence of empathy relating to any subscale of schizotypy, or the tota

Background A multitude of clinical models to predict transition to psychosis in individuals at clinical high risk (CHR) have been proposed. However, only limited efforts have been made to systematically compare these models and to validate their performance in independent samples. Therefore, in this study we identified psychosis risk models based on information readily obtainable in general clinical settings, such as clinical and neuropsychological data, and compared their performance in the PRONIA study (Personalised Prognostic Tools for Early Psychosis Management, www.pronia.eu) as an independent sample. Methods Of the 278 CHR participants in the PRONIA sample, 150 had available data until month 18 and were included in the validation of eleven psychosis prediction models identified through systematic literature search. Discrimination performance was assessed with the area under the receiver operating characteristic curve (AUC), and compared to the performance of the prognosis of clinical raters. Psychosocial functioning was explored as an alternative outcome. Results Discrimination performance varied considerably across models (AUC ranging from 0.42 to 0.79). High model performance was associated with the inclusion of neurocognitive variables as predictors. Low model performance was associated with predictors based on dichotomized variables. Clinical raters performed comparable to the best data-driven models (AUC = 0.75). Combining raters’ prognosis and model-based predictions improved discrimination performance (AUC = 0.84), particularly for less experienced raters. One of the tested models predicted transition to psychosis and psychosocial outcomes comparably well. Discussion The present external validation study highlights the benefit of enriching clinical information with neuropsychological data in predicting transition to psychosis satisfactorily and with good generalizability across samples. Integration of data-driven risk models and clinical expert

Background Functional deficits associated with the Clinical High Risk (CHR) status very often lead to inability to attend school, unemployment, as well as social isolation, thus calling for predictors of individual functional outcomes which may facilitate the identification of people requiring care irrespective of transition to psychosis. Studies have revealed that a pattern of cortical and subcortical gray matter volumes (GMV) anomalies measured at baseline in CHR individuals could predict their functional abilities at follow up. Furthermore, literature is consistent in revealing the crucial role of several environmental adverse events in increasing the risk of developing either transition to psychosis, or a worse overall personal functioning. Therefore, the aim of this study is to employ machine learning to test the individual and combined ability of baseline GMV data and of history of environmental adverse events in predicting good vs. poor social and occupational outcome in CHR individuals at follow up. Methods 92 CHR individuals recruited from the 7 discovery PRONIA sites were included in this project. Social and occupational impairment at follow up (9–12 months) were respectively measured through the Global Functioning: Social (GF:S) and Role (GF:R) scale, and CHR with a follow up rating of 7 or below were labeled as having a poor functional outcome. This way, we could separate our cohort in 52 poor outcome CHR and 40 good outcome CHR. GMV data were preprocessed following published procedures which allowed also to correct for site effects. The environmental classifier was built based on Childhood Trauma Questionnaire, Bullying Scale, and Premorbid Adjustment Scale (childhood, early adolescence, late adolescence and adulthood) scores. Raw scores have been normalized according to the psychometric properties of the healthy samples used for validating these questionnaires and scale, in order to obtain individual scores of deviation from the normative occu

Background Formal thought disorder (FThD) has been associated with more severe illness courses and functional deficits in psychosis patients. Given these associations, it remains unclear whether the presence of FThD accounts for the heterogeneous presentation of psychoses, and whether it characterises a specific subgroup of patients showing prominent differential illness severity, neurocognitive and functional impairments already in the early stages of psychosis. Thus, our aim is 1) to evaluate whether there are stable subtypes of patients with Recent-Onset Psychosis (ROP) that are characterized by distinct FThD patterns, 2) to investigate whether this FThD-related stratification is associated with clinical, and neurocognitive phenotypes at an early stage of the disease, and 3) to explore correlation patterns among the FThD-related symptoms, functioning and neurocognition through network analysis. Methods 279 individuals experiencing ROP were recruited for this project as part of multi-site European PRONIA study. In the present study, FThD was assessed with conceptual disorganization, difficulty in abstract thinking, poverty of content of speech, increased latency of response and poverty of speech items from the Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS). We first applied a multi-step clustering protocol comparing three clustering algorithms: (i) k-means, (ii) hierarchical clustering, and (iii) partitioning around medoids with the number of clusters ranging from 2 to 10. Our protocol runs following four checkpoints; (i) validity [ClValid package], (ii) re-evaluation of validity results and unbiased determination of the winning algorithm [NbClust package], (iii) stability test [ClusterStability package] and (iv) generalizability [predict.strength package] testing for the most optimal clustering solution. Thereafter, we investigated whether the identified FThD subgrouping solution was associated wi

In community studies, both attenuated psychotic symptoms (APS) and basic symptoms (BS) were more frequent but less clinically relevant in children and adolescents compared to adults. In doing so, they displayed differential age thresholds that were around age 16 for APS, around age 18 for perceptive BS, and within the early twenties for cognitive BS. Only the age effect has previously been studied and replicated in clinical samples for APS. Thus, we examined the reported age effect on and age thresholds of 14 criteria-relevant BS in a patient sample at clinical-high risk of psychosis (N = 261, age 15-40 yrs.), recruited within the European multicenter PRONIA-study. BS and the BS criteria, "Cognitive Disturbances" (COGDIS) and "Cognitive-perceptive BS" (COPER), were assessed with the "Schizophrenia Proneness Instrument, Adult version" (SPI-A). Using logistic regressions, prevalence rates of perceptive and cognitive BS, and of COGDIS and COPER, as well as the impact of social and role functioning on the association between age and BS were studied in three age groups (15-18 years, 19-23 years, 24-40 years). Most patients (91.2%) reported any BS, 55.9% any perceptive and 87.4% any cognitive BS. Furthermore, 56.3% met COGDIS and 80.5% COPER. Not exhibiting the reported differential age thresholds, both perceptive and cognitive BS, and, at trend level only, COPER were less prevalent in the oldest age group (24-40 years); COGDIS was most frequent in the youngest group (15-18 years). Functional deficits did not better explain the association with age, particularly in perceptive BS and cognitive BS meeting the frequency requirement of BS criteria. Our findings broadly confirmed an age threshold in BS and, thus, the earlier assumed link between presence of BS and brain maturation processes. Yet, age thresholds of perceptive and cognitive BS did not differ. This lack of differential age thresholds might be due to more pronounced the brain abnormalities in this clinical sample

BACKGROUND: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. METHODS: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. RESULTS: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. CONCLUSIONS: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

Recent life events have been implicated in the onset and progression of psychosis. However, psychological processes that account for the association are yet to be fully understood. Using a network approach, we aimed to identify pathways linking recent life events and symptoms observed in psychosis. Based on previous literature, we hypothesized that general symptoms would mediate between recent life events and psychotic symptoms. We analyzed baseline data of patients at clinical high risk for psychosis and with recent-onset psychosis (n = 547) from the Personalised Prognostic Tools for Early Psychosis Management (PRONIA) study. In a network analysis, we modeled links between the burden of recent life events and all individual symptoms of the Positive and Negative Syndrome Scale before and after controlling for childhood trauma. To investigate the longitudinal associations between burden of recent life events and symptoms, we analyzed multiwave panel data from seven timepoints up to month 18. Corroborating our hypothesis, burden of recent life events was connected to positive and negative symptoms through general psychopathology, specifically depression, guilt feelings, anxiety and tension, even after controlling for childhood trauma. Longitudinal modeling indicated that on average, burden of recent life events preceded general psychopathology in the individual. In line with the theory of an affective pathway to psychosis, recent life events may lead to psychotic symptoms via heightened emotional distress. Life events may be one driving force of unspecific, general psychopathology described as characteristic of early phases of the psychosis spectrum, offering promising avenues for interventions.

Background Childhood maltreatment (CM) is a major psychiatric risk factor and leads to long-lasting physical and mental health implications throughout the affected individual’s lifespan. Nonetheless, the neuroanatomical correlates of CM and their specific clinical impact remain elusive. This might be attributed to the complex, multidimensional nature of CM as well as to the restrictions of traditional analysis pipelines using nosological grouping, univariate analysis and region-of-interest approaches. To overcome these issues, we present a novel transdiagnostic and naturalistic machine learning approach towards a better and more comprehensive understanding of the clinical and neuroanatomical complexity of CM. Methods We acquired our dataset from the multi-center European PRONIA cohort (www.pronia.eu). Specifically, we selected 649 male and female individuals, comprising young, minimally medicated patients with clinical high-risk states for psychosis as well as recent-onset of depression or psychosis and healthy volunteers. As part of our analysis approach, we created a new Matlab Toolbox, which performs multivariate Sparse Partial Least Squares Analysis in a robust machine learning framework. We employed this algorithm to detect multi-layered associations between combinations of items from the Childhood Trauma Questionnaire (CTQ) and grey matter volume (GMV) and assessed their generalizability via nested cross-validation. The clinical relevance of these CM signatures was assessed by correlating them to a wide range of clinical measurements, including current functioning (GAF, GF), depressivity (BDI), quality of life (WHOQOL-BREF) and personality traits (NEO-FFI). Results Overall, we detected three distinct signatures of sexual, physical and emotional maltreatment. The first signature consisted of an age-dependent sexual abuse pattern and a corresponding GMV pattern along the prefronto-thalamo-cerebellar axis. The second signature yielded a sex-dependent phy

AIM: Resilience is rapidly gaining momentum in mental health literature. It provides a new understanding of the highly variable trajectories of mental illness, and has consistently been linked with improved mental health outcomes. The present review aims to clarify the definition of resilience and to discuss new directions for the field. METHODS: After discussing the definition of resilience, this narrative review synthesizes evidence that identifies the specific protective factors involved in this process. This review also addresses the mechanisms that underlie resilience. RESULTS: Recent literature has clarified the three core components of resilience, which are the presence of an adversity or specific risk for mental illness; the influence of protective factors that supersede this risk; and finally, a subsequently more positive outcome than expected. Now that these are largely agreed upon, the field should move on to addressing other topics. Resilience is a dynamic process by which individuals utilize protective factors and resources to their benefit. It can vary within one individual across time and circumstance. It can also refer to good functional outcomes in the context of diagnosable illness. While previous research has focused on psychological resilience, it is essential that resilience is conceptualized across modalities. CONCLUSIONS: The field should move towards the development of a multimodal model of resilience. Researchers should now focus on producing empirical research which clarifies the specific protective factors and mechanisms of the process, aligning with the core concepts of resilience. This growing, more homogeneous evidence base, can then inform new intervention strategies.

AIMS: Understanding how adolescents perceive mental illness is important for clinicians wishing to improve engagement, and for the development of educational programmes and health-behaviour directed policies. The current research aimed to develop a preliminary model of how adolescents perceive mental illness and construct their understanding of mental health. METHOD: Forty-six participants aged 11-18 from six schools in Birmingham, UK, took part in one of 12 group interviews. RESULTS: A thematic analysis highlighted a dual perception of mental illness. Adolescents discussed stereotypes and extreme examples of illness, but also displayed an insightful understanding of mental distress which had developed through participants' own experiences. Participants attempted to reconcile and negotiate these conflicting perceptions by creating distinctions between concepts of 'craziness' and 'normality', and reported experiencing negative emotions relating to both perceptions of illness. CONCLUSIONS: The findings suggest that once media stereotypes have been acknowledged, adolescents demonstrate a relatively sophisticated understanding of mental illness, although one which differed at times from the diagnostic medical model of mental illness. Focusing on individual symptoms, prevalence rates and prior contact adolescents have had with individuals with mental illnesses provides a framework to discuss mental health and ill-health with adolescents.

BACKGROUND/OBJECTIVES: Adolescents have unique nutrient requirements due to rapid growth and development. High rates of obesity in adolescents require a variety of diet interventions to achieve weight loss under clinical supervision. The aim of this study is to examine the nutritional adequacy of energy-restricted diets for adolescents. SUBJECTS/METHODS: Three popular diets were modelled for 7 days and assessed by comparing the nutrient profile to the Australian Nutrient Reference Values. Three diets were: (1) a standard energy restricted diet based on current dietary guidelines; (2) a modified carbohydrate diet; and (3) a modified alternate day fasting diet. RESULTS: Initial modelling revealed limiting nutrients (that is, not meeting the recommended intakes) across the diets. Subsequent modelling was required to achieve nutritional adequacy for all three diets. The dietary guidelines diet design met most nutrient targets except essential fatty acids before subsequent modelling, however this diet also provided the highest energy (8.8 vs 8.0 MJ and 6.8 MJ for the modified carbohydrate and modified alternate day fasting diet, respectively). CONCLUSIONS: Energy-restricted diets need careful consideration to meet nutritional requirements of adolescents. A variety of eating patterns can be adapted to achieve nutritional adequacy and energy restriction, however health practitioners need to consider adequacy when prescribing diet interventions for weight loss during adolescence.

OBJECTIVES: To investigate whether intergroup contact in addition to education is more effective than education alone in reducing stigma of mental illness in adolescents. DESIGN: A pragmatic cluster randomised controlled trial compared education alone with education plus contact. Blocking was used to randomly stratify classes within schools to condition. Random allocation was concealed, generated by a computer algorithm, and undertaken after pretest. Data was collected at pretest and 2-week follow-up. Analyses use an intention-to-treat basis. SETTING: Secondary schools in Birmingham, UK. PARTICIPANTS: The parents and guardians of all students in year 8 (age 12-13 years) were approached to take part. INTERVENTIONS: A 1-day educational programme in each school led by mental health professional staff. Students in the 'contact' condition received an interactive session with a young person with lived experience of mental illness. OUTCOMES: The primary outcome was students' attitudinal stigma of mental illness. Secondary outcomes included knowledge-based stigma, mental health literacy, emotional well-being and resilience, and help-seeking attitudes. RESULTS: Participants were recruited between 1 May 2011 and 30 April 2012. 769 participants completed the pretest and were randomised to condition. 657 (85%) provided follow-up data. At 2-week follow-up, attitudinal stigma improved in both conditions with no significant effect of condition (95% CI -0.40 to 0.22, p=0.5, d=0.01). Significant improvements were found in the education-alone condition compared with the contact and education condition for the secondary outcomes of knowledge-based stigma, mental health literacy, emotional well-being and resilience, and help-seeking attitudes. CONCLUSIONS: Contact was found to reduce the impact of the intervention for a number of outcomes. Caution is advised before employing intergroup contact with younger student age groups. The education intervention appeared to be successful in redu