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Preclinical models propose that increased hippocampal activity drives subcortical dopaminergic dysfunction and leads to psychosis-like symptoms and behaviors. Here, we used multimodal neuroimaging to examine the relationship between hippocampal regional cerebral blood flow (rCBF) and striatal dopamine synthesis capacity in people at clinical high risk (CHR) for psychosis and investigated its association with subsequent clinical and functional outcomes. Ninety-five participants (67 CHR and 28 healthy controls) underwent arterial spin labeling MRI and 18F-DOPA PET imaging at baseline. CHR participants were followed up for a median of 15 months to determine functional outcomes with the global assessment of function (GAF) scale and clinical outcomes using the comprehensive assessment of at-risk mental states (CAARMS). CHR participants with poor functional outcomes (follow-up GAF n = 25) showed higher rCBF in the right hippocampus compared to CHRs with good functional outcomes (GAF ≥ 65, n = 25) (pfwe = 0.026). The relationship between rCBF in this right hippocampal region and striatal dopamine synthesis capacity was also significantly different between groups (pfwe = 0.035); the association was negative in CHR with poor outcomes (pfwe = 0.012), but non-significant in CHR with good outcomes. Furthermore, the correlation between right hippocampal rCBF and striatal dopamine function predicted a longitudinal increase in the severity of positive psychotic symptoms within the total CHR group (p = 0.041). There were no differences in rCBF, dopamine, or their associations in the total CHR group relative to controls. These findings indicate that altered interactions between the hippocampus and the subcortical dopamine system are implicated in the pathophysiology of adverse outcomes in the CHR state.

Much is not known about the efficacy of interventions to prevent poor mental health outcomes in young people by targeting either the general population (universal prevention) or asymptomatic individuals with high risk of developing a mental disorder (selective prevention).We conducted a PRISMA/MOOSE-compliant systematic review and meta-analysis of Web of Science to identify studies comparing post-test efficacy (effect size [ES]; Hedges' g) of universal or selective interventions for poor mental health outcomes versus control groups, in samples with mean age35 years (PROSPERO: CRD42018102143). Measurements included random-effects models, I2 statistics, publication bias, meta-regression, sensitivity analyses, quality assessments, number needed to treat, and population impact number.295 articles (447,206 individuals; mean age = 15.4) appraising 17 poor mental health outcomes were included. Compared to control conditions, universal and selective interventions improved (in descending magnitude order) interpersonal violence, general psychological distress, alcohol use, anxiety features, affective symptoms, other emotional and behavioral problems, consequences of alcohol use, posttraumatic stress disorder features, conduct problems, tobacco use, externalizing behaviors, attention-deficit/hyperactivity disorder features, and cannabis use, but not eating-related problems, impaired functioning, internalizing behavior, or sleep-related problems. Psychoeducation had the highest effect size for ADHD features, affective symptoms, and interpersonal violence. Psychotherapy had the highest effect size for anxiety features.Universal and selective preventive interventions for young individuals are feasible and can improve poor mental health outcomes.

The ability to identify biomarkers of psychosis risk is essential in defining effective preventive measures to potentially circumvent the transition to psychosis. Using samples of people at clinical high risk for psychosis (CHR) and Healthy controls (HC) who were administered a task fMRI paradigm, we used a framework for labelling time windows of fMRI scans as ‘integrated’ FC networks to provide a granular representation of functional connectivity (FC). Periods of integration were defined using the ‘cartographic profile’ of time windows and k‐means clustering, and sub‐network discovery was carried out using Network Based Statistics (NBS). There were no network differences between CHR and HC groups. Within the CHR group, using integrated FC networks, we identified a sub‐network negatively associated with longitudinal changes in the severity of psychotic symptoms. This sub‐network comprised brain areas implicated in bottom‐up sensory processing and in integration with motor control, suggesting it may be related to the demands of the fMRI task. These data suggest that extracting integrated FC networks may be useful in the investigation of biomarkers of psychosis risk., A framework for extracting epochs of integrated functional connectivity was used to test network differences between healthy control and clinical high‐risk (CHR) groups, as well as associations with longitudinal changes in symptom and functioning scores in CHR participants. A sub‐network suggestive of bottom‐up sensory processing was found to be associated with changes in positive psychotic symptoms in the CHR group. We suggest this to be a useful approach in searching for network‐based biomarkers of psychosis risk.

A leading hypothesis for schizophrenia and related psychotic disorders proposes that cortical brain disruption leads to subcortical dopaminergic dysfunction, which underlies psychosis in the majority of patients who respond to treatment. Although supported by preclinical findings that prefrontal cortical lesions lead to striatal dopamine dysregulation, the relationship between prefrontal structural volume and striatal dopamine function has not been tested in people with psychosis. We therefore investigated the in vivo relationship between striatal dopamine synthesis capacity and prefrontal grey matter volume in treatment-responsive patients with psychosis, and compared them to treatment non-responsive patients, where dopaminergic mechanisms are not thought to be central. Forty patients with psychosis across two independent cohorts underwent 18F-DOPA PET scans to measure dopamine synthesis capacity (indexed as the influx rate constant Kicer) and structural 3T MRI. The PET, but not MR, data have been reported previously. Structural images were processed using DARTEL-VBM. GLM analyses were performed in SPM12 to test the relationship between prefrontal grey matter volume and striatal Kicer. Treatment responders showed a negative correlation between prefrontal grey matter and striatal dopamine synthesis capacity, but this was not evident in treatment non-responders. Specifically, we found an interaction between treatment response, whole striatal dopamine synthesis capacity and grey matter volume in left (pFWE corr. = 0.017) and right (pFWE corr. = 0.042) prefrontal cortex. We replicated the finding in right prefrontal cortex in the independent sample (pFWE corr. = 0.031). The summary effect size was 0.82. Our findings are consistent with the long-standing hypothesis of dysregulation of the striatal dopaminergic system being related to prefrontal cortex pathology in schizophrenia, but critically also extend the hypothesis to indicate it can be applied to treatment-responsive schizophrenia only. This suggests that different mechanisms underlie the pathophysiology of treatment-responsive and treatment-resistant schizophrenia.

Dopaminergic dysregulation is one of the leading hypotheses for the pathoetiology underlying psychotic disorders such as schizophrenia. Molecular imaging studies have shown increased striatal dopamine synthesis capacity (DSC) in schizophrenia and people in the prodrome of psychosis. However, it is unclear if genetic risk for psychosis is associated with altered DSC. To investigate this, we recruited healthy controls and two antipsychotic naive groups of individuals with copy number variants, one with a genetic deletion at chromosome 22q11.2, and the other with a duplication at the same locus, who are at increased and decreased risk for psychosis, respectively. Fifty-nine individuals (21 with 22q11.2 deletion, 12 with the reciprocal duplication and 26 healthy controls) received clinical measures and [18F]-DOPA PET imaging to index striatal Kicer. There was an inverse linear effect of copy number variant number on striatal Kicer value (B = −1.2 × 10−3, SE = 2 × 10−4, p cer was significantly higher in the 22q11.2 deletion group compared to the healthy control (p d = 1.44) and 22q11.2 duplication (p d = 2) groups. Moreover, Kicer was positively correlated with the severity of psychosis-risk symptoms (B = 730.5, SE = 310.2, p

BackgroundPreclinical models propose that the onset of psychosis involves increased hippocampal activity which drives subcortical dopaminergic dysfunction. We used multi-modal neuroimaging to examine the relationship between hippocampal regional cerebral blood flow (rCBF) and striatal dopamine synthesis capacity in people at clinical high risk (CHR) for psychosis, and investigated its association with subsequent clinical outcomes.MethodsNinety-five participants (67 CHR and 28 healthy controls) underwent pseudo-continuous arterial spin labelling and 18F-DOPA PET imaging at baseline. Clinical outcomes in CHR participants were determined after a median of 15 months follow-up, using the Comprehensive Assessment of At Risk Mental States (CAARMS) and the Global Assessment of Function (GAF) scale.ResultsCHR participants with a poor functional outcome (follow-up GAFInterpretationThese findings indicate that altered interactions between the hippocampus and the subcortical dopamine system are implicated in the pathophysiology of psychosis-related outcomes.

Promotion of good mental health in young people is important. Our aim was to evaluate the consistency and magnitude of the efficacy of universal/selective interventions to promote good mental health. A systematic PRISMA/RIGHT-compliant meta-analysis (PROSPERO: CRD42018088708) search of Web of Science until 04/31/2019 identified original studies comparing the efficacy of universal/selective interventions for good mental health vs a control group, in samples with a mean age < 35 years. Meta-analytical random-effects model, heterogeneity statistics, assessment of publication bias, study quality and sensitivity analyses investigated the efficacy (Hedges' g = effect size, ES) of universal/selective interventions to promote 14 good mental health outcomes defined a-priori. 276 studies were included (total participants: 159,508, 79,142 interventions and 80,366 controls), mean age = 15.0 (SD = 7.4); female = 56.0%. There was a significant overall improvement in 10/13 good mental health outcome categories that could be meta-analysed: compared to controls, interventions significantly improved (in descending order of magnitude) mental health literacy (ES = 0.685, p < 0.001), emotions (ES = 0.541, p < 0.001), self-perceptions and values (ES = 0.49, p < 0.001), quality of life (ES = 0.457, p = 0.001), cognitive skills (ES = 0.428, p < 0.001), social skills (ES = 0.371, p < 0.001), physical health (ES = 0.285, p < 0.001), sexual health (ES = 0.257, p = 0.017), academic/occupational performance (ES = 0.211, p < 0.001) and attitude towards mental disorders (ES = 0.177, p = 0.006). Psychoeducation was the most effective intervention for promoting mental health literacy (ES = 0.774, p < 0.001) and cognitive skills (ES = 1.153, p = 0.03). Physical therapy, exercise and relaxation were more effective than psychoeducation and psychotherapy for promoting physical health (ES= 0.498, p

Preclinical models of psychosis propose that hippocampal glutamatergic neuron hyperactivity drives increased striatal dopaminergic activity, which underlies the development of psychotic symptoms. The aim of this study was to examine the relationship between hippocampal glutamate and subcortical dopaminergic function in people at clinical high risk for psychosis, and to assess the association with the development of psychotic symptoms. 1H-MRS was used to measure hippocampal glutamate concentrations, and 18F-DOPA PET was used to measure dopamine synthesis capacity in 70 subjects (51 people at clinical high risk for psychosis and 19 healthy controls). Clinical assessments were undertaken at baseline and follow-up (median 15 months). Striatal dopamine synthesis capacity predicted the worsening of psychotic symptoms at follow-up (r = 0.35; p p = 0.13). There were no differences in either glutamate (p = 0.5) or dopamine (p = 0.5) measures in the total patient group relative to controls. Striatal dopamine synthesis capacity at presentation predicts the subsequent worsening of sub-clinical total and psychotic symptoms, consistent with a role for dopamine in the development of psychotic symptoms, but is not strongly linked to hippocampal glutamate concentrations.

In children and adolescents, schizophrenia is one of the ten main causes of disability-adjusted life years. The identification of people at Clinical High Risk of developing Psychosis (CHR-P) is one of the most promising strategies to improve outcomes. However, in children and adolescents research on the CHR-P state is still in its infancy and the clinical validity of at-risk criteria appears understudied in this population. Furthermore, only few studies have evaluated the psychopathological, neuropsychological, neuroimaging characteristics and, especially, long-term outcomes of adolescents at high risk. We present here the protocol of an innovative longitudinal cohort study of adolescents aged 12-17. The sample will consist of patients admitted to a third level neuropsychiatric unit, belonging to one of the following three subgroups: 1) adolescents with established Diagnostic and Statistical Manual of Mental Disorder-Fifth Edition psychosis, 2) adolescents with CHR-P, and 3) adolescents with psychiatric symptoms other than established psychosis or CHR-P. The primary aim of our study is to evaluate the 2-year prognosis across the three groups. We will measure transition to psychosis (or the stability of the diagnosis of psychosis in the psychotic group), the risk of development of other psychiatric disorders, as well as socio-occupational functioning at outcome. The secondary aim will be to explore the effect of specific predictors (clinical, neuropsychological and neuroimaging factors) on the prognosis. At baseline, 1-year and 2-year follow-up participants will be assessed using standardized semi-structured interviews and instruments. Psychopathological and functioning variables, as well as neuropsychological domains will be compared across the three subgroups. Moreover, at baseline and 2-year follow-up all recruited patients will undergo a 3-Tesla magnetic resonance imaging examination and diffusion tensor imaging parameters will be analyzed. We believe that this study will advance our ability to predict outcomes in underage CHR-P samples. In particular, our data will enable a better understanding of the clinical significance of CHR-P in adolescents, and shed new light on prognostic factors that can be used to refine the prediction of clinical outcomes and the implementation of preventive interventions.

Introduction. With biomedical imaging research increasingly using large datasets, it becomes critical to find operator-free methods to quality control the data collected and the associated analysis. Attempts to use artificial intelligence (AI) to perform automated quality control (QC) for both single-site and multi-site datasets have been explored in some neuroimaging techniques (e.g. EEG or MRI), although these methods struggle to find replication in other domains. The aim of this study is to test the feasibility of an automated QC pipeline for brain [18F]-FDOPA PET imaging as a biomarker for the dopamine system. Methods. Two different Convolutional Neural Networks (CNNs) were used and combined to assess spatial misalignment to a standard template and the signal-to-noise ratio (SNR) relative to 200 static [18F]-FDOPA PET images that had been manually quality controlled from three different PET/CT scanners. The scans were combined with an additional 400 scans, in which misalignment (200 scans) and low SNR (200 scans) were simulated. A cross-validation was performed, where 80% of the data were used for training and 20% for validation. Two additional datasets of [18F]-FDOPA PET images (50 and 100 scans respectively with at least 80% of good quality images) were used for out-of-sample validation. Results. The CNN performance was excellent in the training dataset (accuracy for motion: 0.86 ± 0.01, accuracy for SNR: 0.69 ± 0.01), leading to 100% accurate QC classification when applied to the two out-of-sample datasets. Data dimensionality reduction affected the generalizability of the CNNs, especially when the classifiers were applied to the out-of-sample data from 3D to 1D datasets. Conclusions. This feasibility study shows that it is possible to perform automatic QC of [18F]-FDOPA PET imaging with CNNs. The approach has the potential to be extended to other PET tracers in both brain and non-brain applications, but it is dependent on the availability of large datasets necessary for the algorithm training.

Background Brief Limited Intermittent Psychotic Symptoms (BLIPS) are key inclusion criteria to define individuals at ultra high risk for psychosis (UHR). Their diagnostic and prognostic significance is unclear. Objectives To address the baseline diagnostic relationship between BLIPS and the ICD-10 categories and examine the longitudinal prognostic impact of clinical and sociodemographic factors. Methods Prospective long-term study in UHR individuals meeting BLIPS criteria. Sociodemographic and clinical data, including ICD-10 diagnoses, were automatically drawn from electronic health records and analyzed using Kaplan–Meier failure function (1-survival), Cox regression models, bootstrapping methods, and Receiver Operating Characteristics (ROC) curve. Results Eighty BLIPS were included. At baseline, two-thirds (68%) of BLIPS met the diagnostic criteria for ICD-10 Acute and Transient Psychotic Disorder (ATPD), most featuring schizophrenic symptoms. The remaining individuals met ICD-10 diagnostic criteria for unspecified nonorganic psychosis (15%), mental and behavioral disorders due to use of cannabinoids (11%), and mania with psychotic symptoms (6%). The overall 5-year risk of psychosis was 0.54. Recurrent episodes of BLIPS were relatively rare (11%) but associated with a higher risk of psychosis (hazard ratio [HR] 3.98) than mono-episodic BLIPS at the univariate analysis. Multivariate analysis revealed that seriously disorganizing or dangerous features increased greatly (HR = 4.39) the risk of psychosis (0.89 at 5-year). Bootstrapping confirmed the robustness of this predictor (area under the ROC = 0.74). Conclusions BLIPS are most likely to fulfill the ATPD criteria, mainly acute schizophrenic subtypes. About half of BLIPS cases develops a psychotic disorder during follow-up. Recurrent BLIPS are relatively rare but tend to develop into psychosis. BLIPS with seriously disorganizing or dangerous features have an extreme high risk of psychosis.

Predicting the onset of psychosis in individuals at-risk is based on robust prognostic model building methods including a priori clinical knowledge (also termed clinical-learning) to preselect predictors or machine-learning methods to select predictors automatically. To date, there is no empirical research comparing the prognostic accuracy of these two methods for the prediction of psychosis onset. In a first experiment, no improved performance was observed when machine-learning methods (LASSO and RIDGE) were applied—using the same predictors—to an individualised, transdiagnostic, clinically based, risk calculator previously developed on the basis of clinical-learning (predictors: age, gender, age by gender, ethnicity, ICD-10 diagnostic spectrum), and externally validated twice. In a second experiment, two refined versions of the published model which expanded the granularity of the ICD-10 diagnosis were introduced: ICD-10 diagnostic categories and ICD-10 diagnostic subdivisions. Although these refined versions showed an increase in apparent performance, their external performance was similar to the original model. In a third experiment, the three refined models were analysed under machine-learning and clinical-learning with a variable event per variable ratio (EPV). The best performing model under low EPVs was obtained through machine-learning approaches. The development of prognostic models on the basis of a priori clinical knowledge, large samples and adequate events per variable is a robust clinical prediction method to forecast psychosis onset in patients at-risk, and is comparable to machine-learning methods, which are more difficult to interpret and implement. Machine-learning methods should be preferred for high dimensional data when no a priori knowledge is available.

Background: The first rate-limiting step for primary indicated prevention of psychosis is the detection of young people who may be at risk. The ability of specialized clinics to detect individuals at risk for psychosis is limited. A clinically based, individualized, transdiagnostic risk calculator has been developed and externally validated to improve the detection of individuals at risk in secondary mental health care. This calculator employs core sociodemographic and clinical predictors, including age, which is defined in linear terms. Recent evidence has suggested a nonlinear impact of age on the probability of psychosis onset. Aim: To define at a meta-analytical level the function linking age and probability of psychosis onset. To incorporate this function in a refined version of the transdiagnostic risk calculator and to test its prognostic performance, compared to the original specification. Design: Secondary analyses on a previously published meta-analysis and clinical register-based cohort study based on 2008-2015 routine secondary mental health care in South London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust. Participants: All patients receiving a first index diagnosis of nonorganic/non-psychotic mental disorder within SLaM NHS Trust in the period 2008-2015. Main outcome measure: Prognostic accuracy (Harrell's C). Results: A total of 91,199 patients receiving a first index diagnosis of non-organic and non-psychotic mental disorder within SLaM NHS Trust were included in the derivation (33,820) or external validation (54,716) datasets. The mean follow-up was 1,588 days. The meta-analytical estimates showed that a second-degree fractional polynomial model with power (−2, −1: age1 = age−2 and age2 = age−1) was the best-fitting model (P < 0.001). The refined model that included this function showed an excellent prognostic accuracy in the external validation (Harrell's C = 0.805, 95% CI from 0.790 to 0.819), which was statistically higher than the original model, although of modest magnitude (Harrell's C change = 0.0136, 95% CIs from 0.006 to 0.021, P < 0.001). Conclusions: The use of a refined version of the clinically based, individualized, transdiagnostic risk calculator, which allows for nonlinearity in the association between age and risk of psychosis onset, may offer a modestly improved prognostic performance. This calculator may be particularly useful in young individuals at risk of developing psychosis who access secondary mental health care.

IMPORTANCE: Preclinical and human data suggest that hippocampal dysfunction plays a critical role in the onset of psychosis. Neural hyperactivity in the hippocampus is thought to drive an increase in subcortical dopamine function through glutamatergic projections to the striatum. OBJECTIVE: To examine the association between hippocampal glutamate levels in individuals at clinical high risk for psychosis and their subsequent clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study of 86 individuals at clinical high risk for psychosis and 30 healthy control individuals, with a mean follow-up of 18.5 months, was conducted between November 1, 2011, and November 1, 2017, at early detection services in London and Cambridge, United Kingdom. MAIN OUTCOMES AND MEASURES: Concentrations of glutamate and other metabolites were measured in the left hippocampus using 3-T proton magnetic resonance spectroscopy at the first clinical presentation. At follow-up, clinical outcomes were assessed in terms of transition or nontransition to psychosis using the Comprehensive Assessment of the At-Risk Mental State criteria and the level of overall functioning using the Global Assessment of Function scale. RESULTS: Of 116 total participants, 86 were at clinical high risk for psychosis (50 [58%] male; mean [SD] age, 22.4 [3.5] years) and 30 were healthy controls (14 [47%] male; mean [SD] age, 24.7 [3.8] years). At follow-up, 12 clinical high-risk individuals developed a first episode of psychosis whereas 74 clinical high-risk individuals did not; 19 clinical high-risk individuals showed good overall functioning (Global Assessment of Function ≥65), whereas 38 clinical high-risk individuals had a poor functional outcome (Global Assessment of Function

One of the most statistically significant loci to result from large-scale GWAS of schizophrenia is 10q24.32. However, it is still unclear how this locus is involved in the pathoaetiology of schizophrenia. The hypothesis that presynaptic dopamine dysfunction underlies schizophrenia is one of the leading theories of the pathophysiology of the disorder. Supporting this, molecular imaging studies show evidence for elevated dopamine synthesis and release capacity. Thus, altered dopamine function could be a potential mechanism by which this genetic variant acts to increase the risk of schizophrenia. We therefore tested the hypothesis that the 10q24.32 region confers genetic risk for schizophrenia through an effect on striatal dopamine function. To this aim we investigated the in vivo relationship between a GWAS schizophrenia-associated SNP within this locus and dopamine synthesis capacity measured using [18F]-DOPA PET in healthy controls. 92 healthy volunteers underwent [18F]-DOPA PET scans to measure striatal dopamine synthesis capacity (indexed as Ki cer) and were genotyped for the SNP rs7085104. We found a significant association between rs7085104 genotype and striatal Ki cer. Our findings indicate that the mechanism mediating the 10q24.32 risk locus for schizophrenia could involve altered dopaminergic function. Future studies are needed to clarify the neurobiological pathway implicated in this association.

A 17-year-old boy was referred from the general practitioner to the local psychosis early-detection clinic owing to a drop in functioning and social withdrawal during the previous 6 months. He began college 6 months prior but had found the workload difficult and failed his examinations. He had no family history of mental disorders, denied any current or past use of drugs, and reported no significant medical history. He was well kempt, was quiet during his interview, and provided short answers. He reported that he no longer enjoyed his former interests and could not relate to people at college or to friends, but there were no clear signs of depressive disorders. No formal thought disorders were elicited. He was 80% convinced that random people looked and talked about him when he was out in public but was able to question it. He stated that these people were probably commenting on the way he looked, but he did not believe these individuals meant him harm. He never acted on these thoughts. He also reported a vague feeling of perplexity and derealization. These experiences began when he started college and continued to occur every day for up to an hour at a time, causing significant distress. The Structured Clinical Interview for DSM did not reveal any mental disorder.

Background. Several psychometric instruments are available for the diagnostic interview of subjects at ultra high risk (UHR) of psychosis. Their diagnostic comparability is unknown.Methods. All referrals to the OASIS (London) or CAMEO (Cambridgeshire) UHR services from May 13 to Dec 14 were interviewed for a UHR state using both the CAARMS 12/2006 and the SIPS 5.0. Percent overall agreement, kappa, the McNemar-Bowkerχ2test, equipercentile methods, and residual analyses were used to investigate diagnostic outcomes and symptoms severity or frequency. A conversion algorithm (CONVERT) was validated in an independent UHR sample from the Seoul Youth Clinic (Seoul).Results. There was overall substantial CAARMS-versus-SIPS agreement in the identification of UHR subjects (n=212, percent overall agreement = 86%; kappa = 0.781, 95% CI from 0.684 to 0.878; McNemar-Bowker test = 0.069), with the exception of the brief limited intermittent psychotic symptoms (BLIPS) subgroup. Equipercentile-linking table linked symptoms severity and frequency across the CAARMS and SIPS. The conversion algorithm was validated in 93 UHR subjects, showing excellent diagnostic accuracy (CAARMS to SIPS: ROC area 0.929; SIPS to CAARMS: ROC area 0.903).Conclusions. This study provides initial comparability data between CAARMS and SIPS and will inform ongoing multicentre studies and clinical guidelines for the UHR psychometric diagnostic interview.

The external prognostic accuracy of Bipolar At Risk (BAR) criteria is undetermined and no psychometric tools are available to measure them. We present here three studies that overcome these limitations. Study 1 and 2 investigated the prognostic accuracy (Harrell's C) of the original BAR and revised Bipolar At Risk States (BARS) criteria respectively for the prediction of bipolar disorders, using a retrospective cohort of individuals at Clinical High Risk for Psychosis (CHR-P). Study 3 validated externally the prognostic accuracy of a newly developed Semistructured Interview of At Risk Bipolar States (SIBARS) in an independent prospective CHR-P cohort. In study 1 (n = 205), those meeting BAR criteria had an increased risk of developing bipolar disorders (HR = 5.30) relative to those not meeting them, but the prognostic accuracy was poor (Harrell's C = 0.659). In study 2 (n = 205), those meeting the refined BARS criteria had a higher risk of developing bipolar disorders than those not meeting them (HR = 12.364), with an adequate prognostic accuracy (Harrell's C = 0.777). Study 3 (n = 71) confirmed that SIBARS criteria had an adequate prognostic accuracy (Harrell's C = 0.742) and clinical utility. Overall, these findings suggest that the SIBARS could be used for the detection of individuals at risk of developing bipolar disorders in CHR-P services.

BackgroundThe diagnostic and prognostic significance of the DSM-5-defined Attenuated Psychosis Syndrome (DSM-5-APS) in individuals undergoing an ultra high risk (UHR) clinical assessment for suspicion of psychosis risk is unknown.MethodsProspective cohort study including all consecutive help-seeking individuals undergoing both a DSM-5-APS and a Comprehensive Assessment of At Risk Mental States (CAARMS 12/2006) assessment for psychosis risk at the Outreach and Support in South London (OASIS) UHR service (March 2013–April 2014). The diagnostic significance of DSM-5-APS was assessed with percent overall agreement, prevalence bias adjusted kappa, Bowker’s test, Stuart-Maxwell test, residual analysis; the prognostic significance with Cox regression, Kaplan–Meier failure function, time-dependent area under the curve (AUC) and net benefits analysis. The impact of specific revisions of the DSM-5-APS was further tested.ResultIn 203 help-seeking individuals undergoing UHR assessment, the agreement between the DSM-5-APS and the CAARMS 12/2006 was only moderate (kappa 0.59). Among 142 nonpsychotic cases, those meeting DSM-5-APS criteria had a 5-fold probability (HR = 5.379) of developing psychosis compared to those not meeting DSM-5-APS criteria, with a 21-month cumulative risk of psychosis of 28.17% vs 6.49%, respectively. The DSM-5-APS prognostic accuracy was acceptable (AUC 0.76 at 24 months) and similar to the CAARMS 12/2006. The DSM-5-APS designation may be clinically useful to guide the provision of indicated interventions within a 7%–35% (2-year) range of psychosis risk. The removal of the criterion E or C of the DSM-5-APS may improve its prognostic performance and transdiagnostic value.ConclusionsThe DSM-5-APS designation may be clinically useful in individuals accessing clinical services for psychosis prevention.

We recently reported that resting hippocampal, basal ganglia and midbrain perfusion is elevated in people at ultra high risk (UHR) for psychosis. The present study sought to replicate our previous finding in an independent UHR cohort, and examined the relationship between resting perfusion in these regions, psychosis and depression symptoms, and traumatic experiences in childhood. Pseudo-Continuous Arterial Spin Labelling (p-CASL) imaging was used to measure resting cerebral blood flow (rCBF) in 77 UHR for psychosis individuals and 25 healthy volunteers in a case-control design. UHR participants were recruited from clinical early detection services at 3 sites in the South of England. Symptoms levels were assessed using the Comprehensive Assessment of At Risk Mental States (CAARMS), the Hamilton Depression Scale (HAM-D), and childhood trauma was assessed retrospectively using the Childhood Trauma Questionnaire (CTQ). Right hippocampal and basal ganglia rCBF were significantly increased in UHR subjects compared to controls, partially replicating our previous finding in an independent cohort. In UHR participants, positive symptoms were positively correlated with rCBF in the right pallidum. CTQ scores were positively correlated with rCBF values in the bilateral hippocampus and negatively associated with rCBF in the left prefrontal cortex. Elevated resting hippocampal and basal ganglia activity appears to be a consistent finding in individuals at high risk for psychosis, consistent with data from preclinical models of the disorder. The association with childhood trauma suggests that its influence on the risk of psychosis may be mediated through an effect on hippocampal function.

Perinatal brain injuries, including hippocampal lesions, cause lasting changes in dopamine function in rodents, but it is not known if this occurs in humans. We compared adults who were born very preterm with perinatal brain injury to those born very preterm without perinatal brain injury, and age-matched controls born at full term using [18F]-DOPA PET and structural MRI. Dopamine synthesis capacity was reduced in the perinatal brain injury group relative to those without brain injury (Cohen’s d = 1.36, p=0.02) and the control group (Cohen’s d = 1.07, p=0.01). Hippocampal volume was reduced in the perinatal brain injury group relative to controls (Cohen’s d = 1.17, p=0.01) and was positively correlated with striatal dopamine synthesis capacity (r = 0.344, p=0.03). This is the first evidence in humans linking neonatal hippocampal injury to adult dopamine dysfunction, and provides a potential mechanism linking early life risk factors to adult mental illness., eLife digest Thirteen million infants are born too early every year. Improved care allows many to survive, but these “preterm infants” still face an increased risk of death and many other complications. Infants born very early, before 32 weeks, are at risk of brain injury because the brain is normally still developing in the later stages of pregnancy. They also have an increased risk of developing mental health problems later in life. Early-life brain injuries in rats cause changes in the production of a chemical called dopamine. Dopamine is a chemical messenger in the brain that reinforces rewarding behaviour. People with schizophrenia and attention deficit hyperactivity disorder (ADHD) have abnormal levels of dopamine. Changes in brain dopamine levels may explain why early-life brain injury is linked to later mental illness. But first scientists must study whether similar changes occur in humans with an early-life brain injury. Now, Froudist-Walsh et al. use brain imaging to show that people born very early who suffered a brain injury have lower dopamine levels than other adults. Imaging techniques were used to scan the brains of 13 adults who were born before 32 weeks and who had a brain injury around birth, 13 adults born before 32 weeks without a brain injury, and 13 adults born at “full term” (around 39 to 40 weeks). Individuals with low dopamine levels reported difficulty concentrating and a lack of motivation and enjoyment in their lives. Both can be warning signs of mental health problems. People born prematurely without a brain injury had normal dopamine levels and did not report such symptoms. More studies may help scientists understand how early brain injuries may cause brain chemical differences later in life, and how these brain changes affect individual’s mental health. They may also help scientists develop treatments to prevent or treat mental illness in people who experienced a brain injury after a very early birth.

Importance: The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined.Objective: To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care.Design, Setting, and Participants: Clinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016.Main Outcomes and Measures: Risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders.Results: A total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n = 33 820) or external validation (n = 54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88-3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses showed a lower risk of psychosis, with the exception of bipolar mood disorders (similar risk) and brief psychotic episodes (higher risk). The ARMS designation accounted only for a small proportion of transitions to psychosis (n = 52 of 1001; 5.19% in the derivation data set), indicating the need for transdiagnostic prediction of psychosis in secondary mental health care. A prognostic risk stratification model based on preselected variables, including index diagnosis, age, sex, age by sex, and race/ethnicity, was developed and externally validated, showing good performance and potential clinical usefulness.Conclusions and Relevance: This online individualized risk calculator can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.

Background: One of the most prevailing hypotheses of schizophrenia implicates the dopaminergic system. Positron Emission Tomography (PET) studies have consistently reported increased presynaptic dopamine synthesis capacity (DSC) in individuals with schizophrenia. Interestingly, striatal hyperdopaminergia has also been shown to precede the onset of psychosis and to be associated with symptom severity. Although current evidence suggests that dopaminergic dysregulation has at least a state component, the evidence for the trait component is still ambiguous. This highlights the need for studies in a homogenous population of individuals with shared etiological genetic risk factors. Over the last fifteen years, it has been well established that 22q11 deletion is one of the most important genetic risk factors for the development of schizophrenia. Individuals with 22q11 deletion are at increased genetic risk for psychosis, reaching a prevalence for schizophrenia spectrum disorders of 23.53% in adults between 18 and 26 years old and 41% in individuals above 26 years old 30% for psychotic disorder. This mutation accounts for 1% -2% of sporadic cases of schizophrenia. The aim of our study was to investigate dopamine (DA) function in individuals with 22q11 deletion.

Background: Some animal models propose that the onset of psychosis involves dysfunction in GABAergic interneurons, leading to excessive cortical glutamatergic activity, which then drives subcortical dopamine activity. Recent neuroimaging studies in people at ultra high risk (UHR) for psychosis have revealed the extent to which GABA, glutamate, and dopamine function are altered in this population and the relationship between these changes and the later onset of psychosis.

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Background The dopamine hypothesis of psychosis suggests that dopamine abnormalities are present in psychotic illness, irrespective of diagnostic class. Meta-analyses of Positron Emission Tomography (PET) studies of the dopamine system have shown elevated dopamine synthesis capacity in schizophrenia, though there is a dearth of studies examining this in other psychotic disorders. We therefore sought to answer the question of whether abnormalities of the presynaptic dopamine system are seen in bipolar psychosis, how this compared to schizophrenia, and whether positive psychotic symptoms were associated with dopamine synthesis capacity, irrespective of diagnostic class. Methods Cross-sectional, case-control 18F-DOPA Positron Emission Tomography (PET) study in people with first episode bipolar psychosis, schizophrenia and control subjects. Clinical measures included the Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale and Global Assessment of Functioning (GAF). Results Mean (SD) ages were 23.6 (3.6) years in 22 people with bipolar psychosis (13 male), 26.3 (4.4) years in 16 people with schizophrenia (14 male), and 24.5 (4.5) years in controls (14 male). There was a significant group difference in striatal dopamine synthesis capacity (Kicer) (F2,57=6.80, P=.002), post-hoc tests indicating Kicer was significantly elevated in both the bipolar group (mean [SD], 13.18 [1.08]×10–3 min-1; P=.002) and the schizophrenia group (mean [SD], 12.94 [0.79]×10–3 min-1; P=.04) compared with controls (mean [SD], 12.16 [0.92]×10–3 min-1). Kicer was positively correlated with positive psychotic symptom severity in the combined bipolar and schizophrenia sample currently experiencing psychosis, explaining 27% of the variance in symptom severity (n=32, r=0.52, P=.003). Discussion This is the first study to examine the presynaptic dopamine system in bipolar psychosis, finding an elevation compared to controls, equivalent to schizophrenia, from first onset of illness. A relationship was found between dopamine synthesis capacity and positive psychotic symptoms, across diagnostic classes, indicating a transdiagnostic role for dopamine synthesis capacity and positive psychotic symptoms.

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR-). The reference index was psychosis onset over time in both CHR+ and CHR- subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR-: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.

Background: Antipsychotic medication remains the primary treatment for symptoms of psychosis. The dopamine system, in particular, the presynaptic system, has been linked to treatment response, leading to the suggestion that dopaminergic and nondopaminergic forms of schizophrenia exist. This has been examined in vivo, using PET to index presynaptic dopamine (linking elevated dopamine to good treatment response), and Magnetic Resonance Spectroscopy (MRS) to measure glutamatergic function, linking elevated anterior cingulate glutamate to poor antipsychotic response. To date, no study has utilised these measures to examine antipsychotic response prospectively, in first episode patients. We sought to examine both neuroimaging methods in antipsychotic-naïve, first-episode psychosis patients, before and after treatment.