Psychosis Polyrisk Score (PPS) for the Detection of Individuals At-Risk and the Prediction of Their Outcomes

Polygenic and Polyenvironment Interplay in Schizophrenia-Spectrum Disorder and Affective Psychosis; the EUGEI First Episode Study

BACKGROUND

Multiple genetic and environmental risk factors play a role in the development of both schizophrenia-spectrum disorders and affective psychoses. How they act in combination is yet to be clarified.

METHODS

We analyzed 573 first episode psychosis cases and 1005 controls, of European ancestry. Firstly, we tested whether the association of polygenic risk scores for schizophrenia, bipolar disorder, and depression (PRS-SZ, PRS-BD, and PRS-D) with schizophrenia-spectrum disorder and affective psychosis differed when participants were stratified by exposure to specific environmental factors. Secondly, regression models including each PRS and polyenvironmental measures, including migration, paternal age, childhood adversity and frequent cannabis use, were run to test potential polygenic by polyenvironment interactions.

RESULTS

In schizophrenia-spectrum disorder vs controls comparison, PRS-SZ was the strongest genetic predictor, having a nominally larger effect in nonexposed to strong environmental factors such as frequent cannabis use (unexposed vs exposed OR 2.43 and 1.35, respectively) and childhood adversity (3.04 vs 1.74). In affective psychosis vs controls, the relative contribution of PRS-D appeared to be stronger in those exposed to environmental risk. No evidence of interaction was found between any PRS with polyenvironmental score.

CONCLUSIONS

Our study supports an independent role of genetic liability and polyenvironmental risk for psychosis, consistent with the liability threshold model. Whereas schizophrenia-spectrum disorders seem to be mostly associated with polygenic risk for schizophrenia, having an additive effect with well-replicated environmental factors, affective psychosis seems to be a product of cumulative environmental insults alongside a higher genetic liability for affective disorders.

Enriching ultra-high risk for psychosis cohorts based on accumulated exposure to environmental risk factors for psychotic disorders

BACKGROUND AND HYPOTHESIS

Transition to psychosis rates within ultra-high risk (UHR) services have been declining. It may be possible to 'enrich' UHR cohorts based on the environmental characteristics seen more commonly in first-episode psychosis cohorts. This study aimed to determine whether transition rates varied according to the accumulated exposure to environmental risk factors at the individual (migrant status, asylum seeker/refugee status, indigenous population, cannabis/methamphetamine use), family (family history or parental separation), and neighborhood (population density, social deprivation, and fragmentation) level.

METHODS

The study included UHR people aged 15-24 who attended the PACE clinic from 2012 to 2016. Cox proportional hazards models (frequentist and Bayesian) were used to assess the association between individual and accumulated factors and transition to psychosis. UHR status and transition was determined using the CAARMS. Benjamini-Hochberg was used to correct for multiple comparisons in frequentist analyses.

RESULTS

Of the 461 young people included, 55.5% were female and median follow-up was 307 days (IQR: 188-557) and 17.6% (n = 81) transitioned to a psychotic disorder. The proportion who transitioned increased incrementally according to the number of individual-level risk factors present (HR = 1.51, 95% CIs 1.19-1.93, p < 0.001, pcorr = 0.01). The number of family- and neighborhood-level exposures did not increase transition risk (p > 0.05). Cannabis use was the only specific risk factor significantly associated with transition (HR = 1.89, 95% CIs 1.22-2.93, pcorr = 0.03, BF = 6.74).

CONCLUSIONS

There is a dose-response relationship between exposure to individual-level psychosis-related environmental risk factors and transition risk in UHR patients. If replicated, this could be incorporated into a novel approach to identifying the highest-risk individuals within clinical services.

Individualized pretest risk estimates to guide treatment decisions in patients with clinical high risk for psychotic disorders

INTRODUCTION

Clinical high risk for psychosis (CHR) states are associated with an increased risk of transition to psychosis. However, the predictive value of CHR screening interviews is dependent on pretest risk enrichment in referred patients. This poses a major obstacle to CHR outreach campaigns since they invariably lead to risk dilution through enhanced awareness. A potential compensatory strategy is to use estimates of individual pretest risk as a 'gatekeeper' for specialized assessment. We aimed to test a risk stratification model previously developed in London, UK (OASIS) and to train a new predictive model for the Swiss population.

METHOD

The sample was composed of 513 individuals referred for CHR assessment from six Swiss early psychosis detection services. Sociodemographic variables available at referral were used as predictors whereas the outcome variable was transition to psychosis.

RESULTS

Replication of the risk stratification model developed in OASIS resulted in poor performance (Harrel's c=0.51). Retraining resulted in moderate discrimination (Harrel's c=0.67) which significantly differentiated between different risk groups. The lowest risk group had a cumulative transition incidence of 6.4% (CI: 0-23.1%) over two years.

CONCLUSION

Failure to replicate the OASIS risk stratification model might reflect differences in the public health care systems and referral structures between Switzerland and London. Retraining resulted in a model with adequate discrimination performance. The developed model in combination with CHR assessment result, might be useful for identifying individuals with high pretest risk, who might benefit most from specialized intervention.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

A systematic review of performance-based assessment studies on cognitive biases in schizophrenia spectrum psychoses and clinical high-risk states: A summary of 40 years of research

Cognitive models of psychosis have stimulated empirical studies on cognitive biases involved in schizophrenia spectrum psychoses and their symptoms. This systematic review aimed to summarize the studies on the role of cognitive biases as assessed in different performance-based tasks in schizophrenia spectrum psychoses and clinical high-risk states. We focused on five cognitive biases linked to psychosis, i.e., aberrant salience, attentional biases, source monitoring biases, jumping to conclusions, and bias against disconfirmatory evidence. We identified N = 324 studies published in N = 308 articles fulfilling inclusion criteria. Most studies have been cross-sectional and confirmed that the schizophrenia spectrum psychoses are related to exaggerated cognitive biases compared to healthy controls. On the contrary, less evidence suggests a higher tendency for cognitive biases in the UHR sample. The only exceptions were source monitoring and jumping to conclusions, which were confirmed to be exaggerated in both clinical groups. Hallucinations and delusions were the most frequent symptoms studied in the context of cognitive biases. Based on the findings, we presented a hypothetical model on the role of interactions between cognitive biases or additive effects of biases in shaping the risk of psychosis. Future research is warranted for further development of cognitive models for psychosis.

Modelling the effects of the exposome score within the extended psychosis phenotype

It has been reported that cumulative measures of risk factors for psychosis might help to predict its development. However, it remains unknown as to whether these measures are also associated with the extended psychosis phenotype that refers to a continuum of features bridging subclinical symptoms with clinically relevant outcomes. In this study, we aimed to investigate the association of the exposome score (ES) with psychosis risk in a non-clinical population. A total of 1100 non-clinical adults (aged 18-35 years, 51.4% females) with a negative history of psychiatric treatment were recruited. The Prodromal Questionnaire-16 (PQ-16) was used to screen for psychosis risk. Self-reports were used to record environmental exposures. The ES was significantly higher in participants with the positive PQ-16 screening. Specifically, the prevalence of obstetric complications, non-right handedness, all categories of childhood trauma, and problematic cannabis use was significantly higher in this group of participants. A network analysis demonstrated that the ES was directly connected not only to items representing psychotic experiences ("paranoid thoughts", "a lack of control over own ideas or thoughts", "thought echo", and "being distracted by distant sounds") but also those covering depressive or anxiety symptoms ("uninterested in things used to enjoy" and "feeling anxious when meeting people for the first time"). In conclusion, the ES is associated with the extended psychosis phenotype, suggesting its potential to identify individuals who may benefit from further psychosis risk assessment. The ES appears to contribute to non-specific psychopathology, which may, in some cases, progress to psychosis.

Aripiprazole 2-month ready-to-use 960 mg (Ari 2MRTU): review of its possible role in schizophrenia therapy

Most patients with schizophrenia need life-long treatment. There is therefore a continued need for effective and tolerable treatment options. A 2-monthly LAI formulation of aripiprazole, Aripiprazole 2-Month Ready-to-Use 960 mg (Ari 2MRTU 960) has recently been approved in the US. Here, the possible role in therapy for this new treatment option is discussed in a narrative review. PubMed was searched for literature on long-acting injectables with a focus on patient-reported outcomes and real-world evidence on extended injection intervals (2-3 months). Dopamine D2 partial agonists, one of which is aripiprazole, exhibit favorable tolerability and safety properties. Additionally, there are many advantages in using long-acting injectable formulations such as enhanced treatment persistence and stability of patients as well as reduced rates of relapses, hospitalizations, and death. Some of these advantages become more pronounced with longer injection intervals. Additional advantages of longer injection intervals are more room for non-medication-related communication between healthcare professionals and patients, patient and physician preferences, reduced caregiver burden, and easier transitioning from inpatient to outpatient treatment. Taken together, since aripiprazole may be a good treatment choice for many patients based on its favorable safety and tolerability profile, and given the advantages of LAI treatment over oral treatment and the advantages of reduced dosing frequency, Ari 2MRTU 960 may become an important treatment option for many clinically stable patients with schizophrenia.

The Translational Future of Stress Neurobiology and Psychosis Vulnerability: A Review of the Evidence

Psychosocial stress is a well-established risk factor for psychosis, yet the neurobiological mechanisms underlying this relationship have yet to be fully elucidated. Much of the research in this field has investigated hypothalamic-pituitary-adrenal (HPA) axis function and immuno-inflammatory processes among individuals with established psychotic disorders. However, as such studies are limited in their ability to provide knowledge that can be used to develop preventative interventions, it is important to shift the focus to individuals with increased vulnerability for psychosis (i.e., high-risk groups). In the present article, we provide an overview of the current methods for identifying individuals at high-risk for psychosis and review the psychosocial stressors that have been most consistently associated with psychosis risk. We then describe a network of interacting physiological systems that are hypothesised to mediate the relationship between psychosocial stress and the manifestation of psychotic illness and critically review evidence that abnormalities within these systems characterise highrisk populations. We found that studies of high-risk groups have yielded highly variable findings, likely due to (i) the heterogeneity both within and across high-risk samples, (ii) the diversity of psychosocial stressors implicated in psychosis, and (iii) that most studies examine single markers of isolated neurobiological systems. We propose that to move the field forward, we require well-designed, largescale translational studies that integrate multi-domain, putative stress-related biomarkers to determine their prognostic value in high-risk samples. We advocate that such investigations are highly warranted, given that psychosocial stress is undoubtedly a relevant risk factor for psychotic disorders.

Influence of cannabis use on incidence of psychosis in people at clinical high risk

AIMS

Evidence for case-control studies suggests that cannabis use is a risk factor for the development of psychosis. However, there have been limited prospective studies and the direction of this association remains controversial. The primary aim of the present study was to examine the association between cannabis use and the incidence of psychotic disorders in people at clinical high risk of psychosis. Secondary aims were to assess associations between cannabis use and the persistence of psychotic symptoms, and with functional outcome.

METHODS

Current and previous cannabis use were assessed in individuals at clinical high risk of psychosis (n = 334) and healthy controls (n = 67), using a modified version of the Cannabis Experience Questionnaire. Participants were assessed at baseline and followed up for 2 years. Transition to psychosis and persistence of psychotic symptoms were assessed using the Comprehensive Assessment of At-Risk Mental States criteria. Level of functioning at follow up was assessed using the Global Assessment of Functioning disability scale.

RESULTS

During follow up, 16.2% of the clinical high-risk sample developed psychosis. Of those who did not become psychotic, 51.4% had persistent symptoms and 48.6% were in remission. There was no significant association between any measure of cannabis use at baseline and either transition to psychosis, the persistence of symptoms, or functional outcome.

CONCLUSIONS

These findings contrast with epidemiological data that suggest that cannabis use increases the risk of psychotic disorder.

Symptoms of Attenuated Psychosis Syndrome in Relatives of Clinical High-Risk Youth: Preliminary Evidence

BACKGROUND AND HYPOTHESIS

Attenuated Psychosis Syndrome (APS) impacts functioning and predicts increased risk of psychosis. Risk for developing APS itself has received minimal attention. Knowledge of familial and environmental contributions to APS symptoms would advance understanding of APS and risk for psychosis. As an initial step, this report presents the first data on APS symptoms in family members of APS patients.

STUDY DESIGN

This study utilized a discordant sibling-pair family study design. The Structured Interview for Psychosis-risk Syndromes (SIPS) was administered to 17 APS probands and 26 non-APS biological siblings. Probands and siblings were compared on positive, negative, disorganized, and general SIPS symptom scales and factors derived from those scales.

STUDY RESULTS

There was significantly greater symptom severity in probands compared to siblings on nine of 19 SIPS scales. Negative/anxiety, functioning, and positive symptom factors were identified. Probands showed significantly greater severity than siblings on the negative/anxiety and positive factors. Elevated pathology on the negative/anxiety factor best differentiated between probands and siblings, over and above the contribution of the positive factor. No difference was found for the functioning factor.

CONCLUSIONS

Results support the importance of non-familial effects on risk for APS and suggest differences in familial contribution to APS symptoms. Understanding the relative contribution of familial and environmental effects on APS symptoms may reveal important differences among APS patients, with implications for risk characterization, symptom course, and treatment selection.

Differential effects of parental socioeconomic status on cortical thickness in patients with schizophrenia spectrum disorders and healthy controls

OBJECTIVES

Widespread changes in cortical thickness (CT) have been repeatedly reported in schizophrenia (SZ). The nature of the pathophysiologic process underlying such changes remains to be elucidated. The aims of the present study were to measure the CT; evaluate parent socioeconomic status (pSES), childhood trauma (ChT) and premorbid adjustment (PA) in patients with schizophrenia spectrum disorders (SSDs); and investigate group differences in CT (i.e., SSD vs. healthy controls (HCs)), pSES, PA, and/or ChT, as well as the interactions among these factors.

METHODS

164 patients with SSD and 245 age-, sex- and education-matched healthy controls have participated. The pSES, ChT and PA were evaluated using Korean version of Polyenvironmental Risk Score, Early Trauma Inventory Self Report-Short Form and Premorbid Adjustment Scale, respectively. Vertex-wise measure of CT was estimated using the FreeSurfer. To investigate the main effects and interactions, multilevel regression was employed.

RESULTS

We found widespread cortical thinning in patients with SSDs compared to HCs. The cortical thinning was associated with ChT, symptom severity and chlorpromazine equivalent dose and duration of illness in patients. In multilevel regression, main effects of group and pSES and interaction between group and pSES were found whereas a significant interaction between ChT and CPZ equivalent was found in patients.

CONCLUSION

Our findings indicate that compared to HCs, patients with SSDs have cortical structural abnormalities, and that group and pSES interaction determines CT. Further studies are needed to explore the effects of psychosocial factors on brain structural and functional abnormalities in SZ.

Borderline personality features among individuals at clinical high risk for psychosis (CHR-P): A brief report

AIM

This exploratory study reports on borderline symptomatology within a sample of individuals at clinical high risk for psychosis (CHR-P) through a validated, self-report instrument, the short version of the Borderline Symptom List (BSL-23).

METHODS

The sample consisted of 44 help-seeking CHR-P youth (ages 14-29 years) who completed an initial evaluation at a specialized clinic for psychosis-risk.

RESULTS

The mean BSL-23 score was 1.5 (SD = 1.0, range 0.1-4.0). Higher scores were strongly associated with greater reported depressive symptoms (r = 0.84, p < 0.001). Additionally, borderline symptoms associated with attenuated positive symptoms (r = 0.32, p = 0.034) and social anxiety (r = 0.34, p = 0.027). Borderline symptomatology was not associated with role or social functioning.

CONCLUSIONS

This study is one of the first examinations of borderline symptomatology within a CHR-P sample through a validated self-report measure. Future research replicating these results is required to determine their robustness.

Prevalence and risk factors of self-reported psychotic experiences among high school and college students: A systematic review, meta-analysis, and meta-regression

BACKGROUND

Adolescents are at high risk of incident psychopathology. Fleeting psychotic experiences (PEs) that emerge in young people in response to stress may be warning signs that are missed by research that fails to study stressed populations, such as late high school and college/university students. Our aim in this systematic review was to conduct a meta-analysis that estimates prevalence rates of PEs in students, and to assess whether these rates differ by gender, age, culture, and COVID-19 exposure.

METHOD

We searched nine electronic databases, from their inception until January 31, 2022 for relevant studies. We pooled the estimates using the DerSimonian-Laird technique and random-effects meta-analysis. Our main outcome was the prevalence of self-reported PEs in high school and college/university students. We subsequently analyzed our data by age, gender, population, country, culture, evaluation tool, and COVID-19 exposure.

RESULTS

Out of 486 studies retrieved, a total of 59 independent studies met inclusion criteria reporting 210' 024 students from 21 different countries. Nearly one in four students (23.31%; 95% CI 18.41%-29.05%), reported having experienced PEs (heterogeneity [Q = 22,698.23 (62), p = 0.001] τ²  = 1.4418 [1.0415-2.1391], τ = 1.2007 [1.0205-1.4626], I²  = 99.7%, H = 19.13 [18.59-19.69]). The 95% prediction intervals were 04.01%-68.85%. Subgroup analyses showed that the pooled prevalence differed significantly by population, culture, and COVID-19 exposure.

CONCLUSION

This meta-analysis revealed high prevalence rates of self-reported PEs among teen and young adult students, which may have significance for mental health screening in school settings. An important realization is that PEs may have very different mental health meaning in different cultures.

Combining MRI and clinical data to detect high relapse risk after the first episode of psychosis

Detecting patients at high relapse risk after the first episode of psychosis (HRR-FEP) could help the clinician adjust the preventive treatment. To develop a tool to detect patients at HRR using their baseline clinical and structural MRI, we followed 227 patients with FEP for 18–24 months and applied MRIPredict. We previously optimized the MRI-based machine-learning parameters (combining unmodulated and modulated gray and white matter and using voxel-based ensemble) in two independent datasets. Patients estimated to be at HRR-FEP showed a substantially increased risk of relapse (hazard ratio = 4.58, P < 0.05). Accuracy was poorer when we only used clinical or MRI data. We thus show the potential of combining clinical and MRI data to detect which individuals are more likely to relapse, who may benefit from increased frequency of visits, and which are unlikely, who may be currently receiving unnecessary prophylactic treatments. We also provide an updated version of the MRIPredict software.

Prognostic accuracy and clinical utility of psychometric instruments for individuals at clinical high-risk of psychosis: a systematic review and meta-analysis

Accurate prognostication of individuals at clinical high-risk for psychosis (CHR-P) is an essential initial step for effective primary indicated prevention. We aimed to summarise the prognostic accuracy and clinical utility of CHR-P assessments for primary indicated psychosis prevention. Web of Knowledge databases were searched until 1st January 2022 for longitudinal studies following-up individuals undergoing a psychometric or diagnostic CHR-P assessment, reporting transition to psychotic disorders in both those who meet CHR-P criteria (CHR-P + ) or not (CHR-P-). Prognostic accuracy meta-analysis was conducted following relevant guidelines. Primary outcome was prognostic accuracy, indexed by area-under-the-curve (AUC), sensitivity and specificity, estimated by the number of true positives, false positives, false negatives and true negatives at the longest available follow-up time. Clinical utility analyses included: likelihood ratios, Fagan's nomogram, and population-level preventive capacity (Population Attributable Fraction, PAF). A total of 22 studies (n = 4 966, 47.5% female, age range 12-40) were included. There were not enough meta-analysable studies on CHR-P diagnostic criteria (DSM-5 Attenuated Psychosis Syndrome) or non-clinical samples. Prognostic accuracy of CHR-P psychometric instruments in clinical samples (individuals referred to CHR-P services or diagnosed with 22q.11.2 deletion syndrome) was excellent: AUC = 0.85 (95% CI: 0.81-0.88) at a mean follow-up time of 34 months. This result was driven by outstanding sensitivity (0.93, 95% CI: 0.87-0.96) and poor specificity (0.58, 95% CI: 0.50-0.66). Being CHR-P + was associated with a small likelihood ratio LR + (2.17, 95% CI: 1.81-2.60) for developing psychosis. Being CHR-P- was associated with a large LR- (0.11, 95%CI: 0.06-0.21) for developing psychosis. Fagan's nomogram indicated a low positive (0.0017%) and negative (0.0001%) post-test risk in non-clinical general population samples. The PAF of the CHR-P state is 10.9% (95% CI: 4.1-25.5%). These findings consolidate the use of psychometric instruments for CHR-P in clinical samples for primary indicated prevention of psychosis. Future research should improve the ability to rule in psychosis risk.

The False Dawn of Polygenic Risk Scores for Human Disease Prediction

Polygenic risk scores (PRSs) are being constructed for many diseases and are presented today as a promising avenue in the field of human genetics. These scores aim at predicting the risk of developing a disease by leveraging the many genome-wide association studies (GWAS) conducted during the two last decades. Important investments are being made to improve score estimates by increasing GWAS sample sizes, by developing more sophisticated methods, and by proposing different corrections for potential biases. PRSs have entered the market with direct-to-consumer companies proposing to compute them from saliva samples and even recently to help parents select the healthiest embryos. In this paper, we recall how PRSs arose and question the credit they are given by revisiting underlying assumptions in light of the history of human genetics and by comparing them with estimated breeding values (EBVs) used for selection in livestock.

Development of the Korea-Polyenvironmental Risk Score for Psychosis

OBJECTIVE

Comprehensive understanding of polyenvironmental risk factors for the development of psychosis is important. Based on a review of related evidence, we developed the Korea Polyenvironmental Risk Score (K-PERS) for psychosis. We investigated whether the K-PERS can differentiate patients with schizophrenia spectrum disorders (SSDs) from healthy controls (HCs).

METHODS

We reviewed existing tools for measuring polyenvironmental risk factors for psychosis, including the Maudsley Environmental Risk Score (ERS), polyenviromic risk score (PERS), and Psychosis Polyrisk Score (PPS). Using odds ratios and relative risks for Western studies and the "population proportion" (PP) of risk factors for Korean data, we developed the K-PERS, and compared the scores thereon between patients with SSDs and HCs. In addition, correlation was performed between the K-PERS and Positive and Negative Syndrome Scale (PANSS).

RESULTS

We first constructed the "K-PERS-I," comprising five factors based on the PPS, and then the "K-PERS-II" comprising six factors based on the ERS. The instruments accurately predicted participants' status (case vs. control). In addition, the K-PERS-I and -II scores exhibited significant negative correlations with the negative symptom factor score of the PANSS.

CONCLUSION

The K-PERS is the first comprehensive tool developed based on PP data obtained from Korean studies that measures polyenvironmental risk factors for psychosis. Using pilot data, the K-PERS predicted patient status (SSD vs. HC). Further research is warranted to examine the relationship of K-PERS scores with clinical outcomes of psychosis and schizophrenia.

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

BACKGROUND

Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning.

AIMS

We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample.

METHOD

Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD).

RESULTS

Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD.

CONCLUSIONS

Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

Mapping the implementation and challenges of clinical services for psychosis prevention in England

INTRODUCTION

Indicated primary prevention of psychosis is recommended by NICE clinical guidelines, but implementation research on Clinical High Risk for Psychosis (CHR-P) services is limited.

METHODS

Electronic audit of CHR-P services in England, conducted between June and September 2021, addressing core implementation domains: service configuration, detection of at-risk individuals, prognostic assessment, clinical care, clinical research, and implementation challenges, complemented by comparative analyses across service model. Descriptive statistics, Fisher's exact test and Mann-Whitney U-tests were employed.

RESULTS

Twenty-four CHR-P clinical services (19 cities) were included. Most (83.3%) services were integrated within other mental health services; only 16.7% were standalone. Across 21 services, total yearly caseload of CHR-P individuals was 693 (average: 33; range: 4-115). Most services (56.5%) accepted individuals aged 14-35; the majority (95.7%) utilized the Comprehensive Assessment of At Risk Mental States (CAARMS). About 65% of services reported some provision of NICE-compliant interventions encompassing monitoring of mental state, cognitive-behavioral therapy (CBT), and family interventions. However, only 66.5 and 4.9% of CHR-P individuals actually received CBT and family interventions, respectively. Core implementation challenges included: recruitment of specialized professionals, lack of dedicated budget, and unmet training needs. Standalone services reported fewer implementation challenges, had larger caseloads (p = 0.047) and were more likely to engage with clinical research (p = 0.037) than integrated services.

DISCUSSION

While implementation of CHR-P services is observed in several parts of England, only standalone teams appear successful at detection of at-risk individuals. Compliance with NICE-prescribed interventions is limited across CHR-P services and unmet needs emerge for national training and investments.

Diagnosis, prognosis, and treatment of brief psychotic episodes: a review and research agenda

Brief psychotic episodes represent an intriguing paradox in clinical psychiatry because they elude the standard knowledge that applies to the persisting psychotic disorders such as schizophrenia. This Review describes key diagnostic considerations such as conceptual foundations, current psychiatric classification versus research-based operationalisations, epidemiology, and sociocultural variations; prognostic aspects including the risk of psychosis recurrence, types of psychotic recurrences, other clinical outcomes, prognostic factors; and therapeutic issues such as treatment guidelines and unmet need of care. The advances and challenges associated with the scientific evidence are used to set a research agenda in this area. We conclude that brief psychotic episodes can be reconceptualised within a clinical staging model to promote innovative translational research and improve our understanding and treatment of psychotic disorders.

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

BACKGROUND

The clinical high-risk for psychosis (CHR-P) paradigm was introduced to detect individuals at risk of developing psychosis and to establish preventive strategies. While current prediction of outcomes in the CHR-P state is based mostly on the clinical assessment of presenting features, several emerging biomarkers have been investigated in an attempt to stratify CHR-P individuals according to their individual trajectories and refine the diagnostic process. However, heterogeneity across subgroups is a key challenge that has limited the impact of the CHR-P prediction strategies, as the clinical validity of the current research is limited by a lack of external validation across sites and modalities. Despite these challenges, electroencephalography (EEG) biomarkers have been studied in this field and evidence suggests that EEG used in combination with clinical assessments may be a key measure for improving diagnostic and prognostic accuracy in the CHR-P state. The PSYSCAN EEG study is an international, multi-site, multimodal longitudinal project that aims to advance knowledge in this field.

METHODS

Participants at 6 international sites take part in an EEG protocol including EEG recording, cognitive and clinical assessments. CHR-P participants will be followed up after 2 years and subcategorised depending on their illness progression regarding transition to psychosis. Differences will be sought between CHR-P individuals and healthy controls and between CHR-P individuals who transition and those who do not transition to psychosis using data driven computational analyses.

DISCUSSION

This protocol addresses the challenges faced by previous studies of this kind to enable valid identification of predictive EEG biomarkers which will be combined with other biomarkers across sites to develop a prognostic tool in CHR-P. The PSYSCAN EEG study aims to pave the way for incorporating EEG biomarkers in the assessment of CHR-P individuals, to refine the diagnostic process and help to stratify CHR-P subjects according to risk of transition. This may improve our understanding of the CHR-P state and therefore aid the development of more personalized treatment strategies.

Polygenic risk scores across the extended psychosis spectrum

As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.

Risk and protective factors for mental disorders beyond genetics: an evidence-based atlas

Decades of research have revealed numerous risk factors for mental disorders beyond genetics, but their consistency and magnitude remain uncer-tain. We conducted a "meta-umbrella" systematic synthesis of umbrella reviews, which are systematic reviews of meta-analyses of individual studies, by searching international databases from inception to January 1, 2021. We included umbrella reviews on non-purely genetic risk or protective factors for any ICD/DSM mental disorders, applying an established classification of the credibility of the evidence: class I (convincing), class II (highly suggestive), class III (suggestive), class IV (weak). Sensitivity analyses were conducted on prospective studies to test for temporality (reverse causation), TRANSD criteria were applied to test transdiagnosticity of factors, and A Measurement Tool to Assess Systematic Reviews (AMSTAR) was employed to address the quality of meta-analyses. Fourteen eligible umbrella reviews were retrieved, summarizing 390 meta-analyses and 1,180 associations between putative risk or protective factors and mental disorders. We included 176 class I to III evidence associations, relating to 142 risk/protective factors. The most robust risk factors (class I or II, from prospective designs) were 21. For dementia, they included type 2 diabetes mellitus (risk ratio, RR from 1.54 to 2.28), depression (RR from 1.65 to 1.99) and low frequency of social contacts (RR=1.57). For opioid use disorders, the most robust risk factor was tobacco smoking (odds ratio, OR=3.07). For non-organic psychotic disorders, the most robust risk factors were clinical high risk state for psychosis (OR=9.32), cannabis use (OR=3.90), and childhood adversities (OR=2.80). For depressive disorders, they were widowhood (RR=5.59), sexual dysfunction (OR=2.71), three (OR=1.99) or four-five (OR=2.06) metabolic factors, childhood physical (OR=1.98) and sexual (OR=2.42) abuse, job strain (OR=1.77), obesity (OR=1.35), and sleep disturbances (RR=1.92). For autism spectrum disorder, the most robust risk factor was maternal overweight pre/during pregnancy (RR=1.28). For attention-deficit/hyperactivity disorder (ADHD), they were maternal pre-pregnancy obesity (OR=1.63), maternal smoking during pregnancy (OR=1.60), and maternal overweight pre/during pregnancy (OR=1.28). Only one robust protective factor was detected: high physical activity (hazard ratio, HR=0.62) for Alzheimer's disease. In all, 32.9% of the associations were of high quality, 48.9% of medium quality, and 18.2% of low quality. Transdiagnostic class I-III risk/protective factors were mostly involved in the early neurodevelopmental period. The evidence-based atlas of key risk and protective factors identified in this study represents a benchmark for advancing clinical characterization and research, and for expanding early intervention and preventive strategies for mental disorders.

Computerized Assessment of Psychosis Risk

Early detection and intervention with young people at clinical high risk (CHR) for psychosis is critical for prevention efforts focused on altering the trajectory of psychosis. Early CHR research largely focused on validating clinical interviews for detecting at-risk individuals; however, this approach has limitations related to: (1) specificity (i.e., only 20% of CHR individuals convert to psychosis) and (2) the expertise and training needed to administer these interviews is limited. The purpose of our study is to develop the computerized assessment of psychosis risk (CAPR) battery, consisting of behavioral tasks that require minimal training to administer, can be administered online, and are tied to the neurobiological systems and computational mechanisms implicated in psychosis. The aims of our study are as follows: (1A) to develop a psychosis-risk calculator through the application of machine learning (ML) methods to the measures from the CAPR battery, (1B) evaluate group differences on the risk calculator score and test the hypothesis that the risk calculator score of the CHR group will differ from help-seeking and healthy controls, (1C) evaluate how baseline CAPR battery performance relates to symptomatic outcome two years later (i.e., conversion and symptomatic worsening). These aims will be explored in 500 CHR participants, 500 help-seeking individuals, and 500 healthy controls across the study sites. This project will provide a next-generation CHR battery, tied to illness mechanisms and powered by cutting-edge computational methods that can be used to facilitate the earliest possible detection of psychosis risk.

Preventive psychiatry: a blueprint for improving the mental health of young people

Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.

Prognostic Accuracy of DSM-5 Attenuated Psychosis Syndrome in Adolescents: Prospective Real-World 5-Year Cohort Study

There is limited research in adolescents at risk for psychosis. The new Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition attenuated psychosis syndrome (DSM-5 APS) criteria have not been validated in this group. We conducted a RECORD-compliant, real-world, prospective, 5-year cohort study addressing clinical profile, transition to psychosis, and prognostic accuracy of DSM-5 APS in help-seeking inpatient/outpatient adolescents accessing Children and Adolescent Neuropsychiatric services at IRCCS Mondino Foundation (Pavia, Lombardy, Italy) between 2012 and 2019. About 243 adolescents (31 early-onset psychosis [EOP]; 110 meeting DSM-5 APS criteria, DSM-5 APS; 102 not meeting psychotic or DSM-5 APS criteria, non-APS) were included. At baseline, DSM-5 APS adolescents (aged 15.4 ± 1.6) had on average 2.3 comorbid disorders (higher than EOP/non-APS, P < .001). DSM-5 APS adolescents had an intermediate psychopathological profile between non-APS/EOP (P < .001) and worsen Clinical Global Impression-Severity than non-APS (P < .001). DSM-5 APS functioning was intermediate between non-APS and EOP. 39.1% of DSM-5 APS were treated with psychotropic drugs (average = 64 days); 53.6% received psychotherapy. Follow-up of DSM-5 APS and non-APS groups lasted 33 and 26 months, respectively (median). The cumulative risk of transition at 1-5 years was 13%, 17%, 24.2%, 26.8%, and 26.8% in the DSM-5 APS group, 0%, 0%, 3.2%, 3.2%, and 3.2% in the non-APS group. The 5-year prognostic accuracy of the DSM-5 APS in adolescent was adequate (area under the curve = 0.77; Harrell's C = 0.736, 95%CI 0.697-0.775), with high sensitivity (91.3%) and suboptimal specificity (63.2%). The DSM-5 APS diagnosis can be used to detect help-seeking adolescents at risk of psychosis and predict their long-term outcomes. Future research should consolidate these findings.

Annual Research Review: Prevention of psychosis in adolescents - systematic review and meta-analysis of advances in detection, prognosis and intervention

BACKGROUND

The clinical high-risk state for psychosis (CHR-P) paradigm has facilitated the implementation of psychosis prevention into clinical practice; however, advancements in adolescent CHR-P populations are less established.

METHODS

We performed a PRISMA/MOOSE-compliant systematic review of the Web of Science database, from inception until 7 October 2019, to identify original studies conducted in CHR-P children and adolescents (mean age <18 years). Findings were systematically appraised around core themes: detection, prognosis and intervention. We performed meta-analyses (employing Q statistics and I ² test) regarding the proportion of CHR-P subgroups, the prevalence of baseline comorbid mental disorders, the risk of psychosis onset and the type of interventions received at baseline. Quality assessment and publication bias were also analysed.

RESULTS

Eighty-seven articles were included (n = 4,667 CHR-P individuals). Quality of studies ranged from 3.5 to 8 (median 5.5) on a modified Newcastle-Ottawa scale. Detection: Individuals were aged 15.6 ± 1.2 years (51.5% males), mostly (83%) presenting with attenuated positive psychotic symptoms. CHR-P psychometric accuracy improved when caregivers served as additional informants. Comorbid mood (46.4%) and anxiety (31.4%) disorders were highly prevalent. Functioning and cognition were impaired. Neurobiological studies were inconclusive.

PROGNOSIS

Risk for psychosis was 10.4% (95%CI: 5.8%-18.1%) at 6 months, 20% (95%CI: 15%-26%) at 12 months, 23% (95%CI: 18%-29%) at 24 months and 23.3% (95%CI: 17.3%-30.7%) at ≥36 months.

INTERVENTIONS

There was not enough evidence to recommend one specific treatment (including cognitive behavioural therapy) over the others (including control conditions) to prevent the transition to psychosis in this population. Randomised controlled trials suggested that family interventions, cognitive remediation and fish oil supplementation may improve cognition, symptoms and functioning. At baseline, 30% of CHR-P adolescents were prescribed antipsychotics and 60% received psychotherapy.

CONCLUSIONS

It is possible to detect and formulate a group-level prognosis in adolescents at risk for psychosis. Future interventional research is required.

Establishing a clinical service to prevent psychosis: What, how and when? Systematic review

The first rate-limiting step to successfully translate prevention of psychosis in to clinical practice is to establish specialised Clinical High Risk for Psychosis (CHR-P) services. This study systematises the knowledge regarding CHR-P services and provides guidelines for translational implementation. We conducted a PRISMA/MOOSE-compliant (PROSPERO-CRD42020163640) systematic review of Web of Science to identify studies until 4/05/2020 reporting on CHR-P service configuration, outreach strategy and referrals, service user characteristics, interventions, and outcomes. Fifty-six studies (1998-2020) were included, encompassing 51 distinct CHR-P services across 15 countries and a catchment area of 17,252,666 people. Most services (80.4%) consisted of integrated multidisciplinary teams taking care of CHR-P and other patients. Outreach encompassed active (up to 97.6%) or passive (up to 63.4%) approaches: referrals came mostly (90%) from healthcare agencies. CHR-P individuals were more frequently males (57.2%). Most (70.6%) services accepted individuals aged 12-35 years, typically assessed with the CAARMS/SIPS (83.7%). Baseline comorbid mental conditions were reported in two-third (69.5%) of cases, and unemployment in one third (36.6%). Most services provided up to 2-years (72.4%), of clinical monitoring (100%), psychoeducation (81.1%), psychosocial support (73%), family interventions (73%), individual (67.6%) and group (18.9%) psychotherapy, physical health interventions (37.8%), antipsychotics (87.1%), antidepressants (74.2%), anxiolytics (51.6%), and mood stabilisers (38.7%). Outcomes were more frequently ascertained clinically (93.0%) and included: persistence of symptoms/comorbidities (67.4%), transition to psychosis (53.5%), and functional status (48.8%). We provide ten practical recommendations for implementation of CHR-P services. Health service knowledge summarised by the current study will facilitate translational efforts for implementation of CHR-P services worldwide.

Real-world implementation of precision psychiatry: Transdiagnostic risk calculator for the automatic detection of individuals at-risk of psychosis

BACKGROUND

Risk estimation models integrated into Electronic Health Records (EHRs) can deliver innovative approaches in psychiatry, but clinicians' endorsement and their real-world usability are unknown. This study aimed to investigate the real-world feasibility of implementing an individualised, transdiagnostic risk calculator to automatically screen EHRs and detect individuals at-risk for psychosis.

METHODS

Feasibility implementation study encompassing an in-vitro phase (March 2018 to May 2018) and in-vivo phase (May 2018 to April 2019). The in-vitro phase addressed implementation barriers and embedded the risk calculator (predictors: age, gender, ethnicity, index cluster diagnosis, age*gender) into the local EHR. The in-vivo phase investigated the real-world feasibility of screening individuals accessing secondary mental healthcare at the South London and Maudsley NHS Trust. The primary outcome was adherence of clinicians to automatic EHR screening, defined by the proportion of clinicians who responded to alerts from the risk calculator, over those contacted.

RESULTS

In-vitro phase: implementation barriers were identified/overcome with clinician and service user engagement, and the calculator was successfully integrated into the local EHR through the CogStack platform. In-vivo phase: 3722 individuals were automatically screened and 115 were detected. Clinician adherence was 74% without outreach and 85% with outreach. One-third of clinicians responded to the first email (37.1%) or phone calls (33.7%). Among those detected, cumulative risk of developing psychosis was 12% at six-month follow-up.

CONCLUSION

This is the first implementation study suggesting that combining precision psychiatry and EHR methods to improve detection of individuals with emerging psychosis is feasible. Future psychiatric implementation research is urgently needed.

Real-world digital implementation of the Psychosis Polyrisk Score (PPS): A pilot feasibility study

BACKGROUND

The Psychosis Polyrisk Score (PPS) is a potential biomarker integrating non-purely genetic risk/protective factors for psychosis that may improve identification of individuals at risk and prediction of their outcomes at the individual subject level. Biomarkers that are easy to administer are direly needed in early psychosis to facilitate clinical implementation. This study digitally implements the PPS and pilots its feasibility of use in the real world.

METHODS

The PPS was implemented digitally and prospectively piloted across individuals referred for a CHR-P assessment (n = 16) and healthy controls (n = 66). Distribution of PPS scores was further simulated in the general population.

RESULTS

98.8% of individuals referred for a CHR-P assessment and healthy controls completed the PPS assessment with only one drop-out. 96.3% of participants completed the assessment in under 15 min. Individuals referred for a CHR-P assessment had high PPS scores (mean = 6.2, SD = 7.23) than healthy controls (mean = -1.79, SD = 6.78, p < 0.001). In simulated general population data, scores were normally distributed ranging from -15 (lowest risk, RR = 0.03) to 39.5 (highest risk, RR = 8912.51).

DISCUSSION

The PPS is a promising biomarker which has been implemented digitally. The PPS can be easily administered to both healthy controls and individuals at potential risk for psychosis on a range of devices. It is feasible to use the PPS in real world settings to assess individuals with emerging mental disorders. The next phase of research should be to include the PPS in large-scale international cohort studies to evaluate its ability to refine the prognostication of outcomes.

Transdiagnostic individualized clinically-based risk calculator for the automatic detection of individuals at-risk and the prediction of psychosis: external replication in 2,430,333 US patients

The real-world impact of psychosis prevention is reliant on effective strategies for identifying individuals at risk. A transdiagnostic, individualized, clinically-based risk calculator to improve this has been developed and externally validated twice in two different UK healthcare trusts with convincing results. The prognostic performance of this risk calculator outside the UK is unknown. All individuals who accessed primary or secondary health care services belonging to the IBM® MarketScan® Commercial Database between January 2015 and December 2017, and received a first ICD-10 index diagnosis of nonorganic/nonpsychotic mental disorder, were included. According to the risk calculator, age, gender, ethnicity, age-by-gender, and ICD-10 cluster diagnosis at index date were used to predict development of any ICD-10 nonorganic psychotic disorder. Because patient-level ethnicity data were not available city-level ethnicity proportions were used as proxy. The study included 2,430,333 patients with a mean follow-up of 15.36 months and cumulative incidence of psychosis at two years of 1.43%. There were profound differences compared to the original development UK database in terms of case-mix, psychosis incidence, distribution of baseline predictors (ICD-10 cluster diagnoses), availability of patient-level ethnicity data, follow-up time and availability of specialized clinical services for at-risk individuals. Despite these important differences, the model retained accuracy significantly above chance (Harrell's C = 0.676, 95% CI: 0.672-0.679). To date, this is the largest international external replication of an individualized prognostic model in the field of psychiatry. This risk calculator is transportable on an international scale to improve the automatic detection of individuals at risk of psychosis.

Progression from being at-risk to psychosis: next steps

Over the past 20 years there has been a great deal of research into those considered to be at risk for developing psychosis. Much has been learned and studies have been encouraging. The aim of this paper is to offer an update of the current status of research on risk for psychosis, and what the next steps might be in examining the progression from CHR to psychosis. Advances have been made in accurate prediction, yet there are some methodological issues in ascertainment, diagnosis, the use of data-driven selection methods and lack of external validation. Although there have been several high-quality treatment trials the heterogeneity of this clinical high-risk population has to be addressed so that their treatment needs can be properly met. Recommendations for the future include more collaborative research programmes, and ensuring they are accessible and harmonized with respect to criteria and outcomes so that the field can continue to move forward with the development of large collaborative consortiums as well as increased funding for multisite projects.

Proportion of young people in the general population consulting general practitioners: Potential for mental health screening and prevention

AIM

One of the main obstacles with prevention in psychiatry is low detection of young subjects at risk for psychosis. The aim of the present work is to test whether general practitioners' (GP) offices are a possible setting for prevention of mental illness.

METHODS

We used an Electronic Health Record database (Datanet) representing South-London (Lambeth), where frequency of GP visits were available for each registered subject.

RESULTS

We show that in 2018 out of almost 175 000 subjects aged 12 to 35, almost six out of ten people were seen by their General practitioner at least once in 2018, and considering those subjects with at least one medical condition, around nine subjects out of ten did the same.

CONCLUSIONS

A high proportion of adolescents and young adults are seen by GPs at least once per year. GP offices should be tested as possible setting for detection of subjects at risk for mental illness, in particular in subjects with risk factors for mental illness.

Copy number variants in siblings of Mexican origin concordant for schizophrenia or bipolar disorder

Schizophrenia (SCZ) and bipolar disorder (BD) cause similar symptomatology. A correlation between these disorders has been found. We aimed to explore shared CNVs between SCZ and BD, in 35 sibpairs diagnosed with SCZ and 21 sibpairs diagnosed with BD. CNV calling was performed using data derived of Psycharray, by PennCNV. We did not find any shared CNVs between individuals diagnosed with BD and SCZ, neither with psychotic symptoms in individuals with BD. Nevertheless, we found a significant higher CNV burden in early-onset SCZ. This is one of the first's studies analyzing shared CNVs between SCZ and BD in Mexican population.

Enhancing Psychosis Risk Prediction Through Computational Cognitive Neuroscience

Research suggests that early identification and intervention with individuals at clinical high risk (CHR) for psychosis may be able to improve the course of illness. The first generation of studies suggested that the identification of CHR through the use of specialized interviews evaluating attenuated psychosis symptoms is a promising strategy for exploring mechanisms associated with illness progression, etiology, and identifying new treatment targets. The next generation of research on psychosis risk must address two major limitations: (1) interview methods have limited specificity, as recent estimates indicate that only 15%-30% of individuals identified as CHR convert to psychosis and (2) the expertise needed to make CHR diagnosis is only accessible in a handful of academic centers. Here, we introduce a new approach to CHR assessment that has the potential to increase accessibility and positive predictive value. Recent advances in clinical and computational cognitive neuroscience have generated new behavioral measures that assay the cognitive mechanisms and neural systems that underlie the positive, negative, and disorganization symptoms that are characteristic of psychotic disorders. We hypothesize that measures tied to symptom generation will lead to enhanced sensitivity and specificity relative to interview methods and the cognitive intermediate phenotype measures that have been studied to date that are typically indicators of trait vulnerability and, therefore, have a high false positive rate for conversion to psychosis. These new behavioral measures have the potential to be implemented on the internet and at minimal expense, thereby increasing accessibility of assessments.

Prevention of Psychosis: Advances in Detection, Prognosis, and Intervention

IMPORTANCE

Detection, prognosis, and indicated interventions in individuals at clinical high risk for psychosis (CHR-P) are key components of preventive psychiatry.

OBJECTIVE

To provide a comprehensive, evidence-based systematic appraisal of the advancements and limitations of detection, prognosis, and interventions for CHR-P individuals and to formulate updated recommendations.

EVIDENCE REVIEW

Web of Science, Cochrane Central Register of Reviews, and Ovid/PsychINFO were searched for articles published from January 1, 2013, to June 30, 2019, to identify meta-analyses conducted in CHR-P individuals. MEDLINE was used to search the reference lists of retrieved articles. Data obtained from each article included first author, year of publication, topic investigated, type of publication, study design and number, sample size of CHR-P population and comparison group, type of comparison group, age and sex of CHR-P individuals, type of prognostic assessment, interventions, quality assessment (using AMSTAR [Assessing the Methodological Quality of Systematic Reviews]), and key findings with their effect sizes.

FINDINGS

In total, 42 meta-analyses published in the past 6 years and encompassing 81 outcomes were included. For the detection component, CHR-P individuals were young (mean [SD] age, 20.6 [3.2] years), were more frequently male (58%), and predominantly presented with attenuated psychotic symptoms lasting for more than 1 year before their presentation at specialized services. CHR-P individuals accumulated several sociodemographic risk factors compared with control participants. Substance use (33% tobacco use and 27% cannabis use), comorbid mental disorders (41% with depressive disorders and 15% with anxiety disorders), suicidal ideation (66%), and self-harm (49%) were also frequently seen in CHR-P individuals. CHR-P individuals showed impairments in work (Cohen d = 0.57) or educational functioning (Cohen d = 0.21), social functioning (Cohen d = 1.25), and quality of life (Cohen d = 1.75). Several neurobiological and neurocognitive alterations were confirmed in this study. For the prognosis component, the prognostic accuracy of CHR-P instruments was good, provided they were used in clinical samples. Overall, risk of psychosis was 22% at 3 years, and the risk was the highest in the brief and limited intermittent psychotic symptoms subgroup (38%). Baseline severity of attenuated psychotic (Cohen d = 0.35) and negative symptoms (Cohen d = 0.39) as well as low functioning (Cohen d = 0.29) were associated with an increased risk of psychosis. Controlling risk enrichment and implementing sequential risk assessments can optimize prognostic accuracy. For the intervention component, no robust evidence yet exists to favor any indicated intervention over another (including needs-based interventions and control conditions) for preventing psychosis or ameliorating any other outcome in CHR-P individuals. However, because the uncertainty of this evidence is high, needs-based and psychological interventions should still be offered.

CONCLUSIONS AND RELEVANCE

This review confirmed recent substantial advancements in the detection and prognosis of CHR-P individuals while suggesting that effective indicated interventions need to be identified. This evidence suggests a need for specialized services to detect CHR-P individuals in primary and secondary care settings, to formulate a prognosis with validated psychometric instruments, and to offer needs-based and psychological interventions.

Prenatal and perinatal risk and protective factors for psychosis: a systematic review and meta-analysis

BACKGROUND

Prenatal and perinatal insults are implicated in the aetiopathogenesis of psychotic disorders but the consistency and magnitude of their associations with psychosis have not been updated for nearly two decades. The aim of this systematic review and meta-analysis was to provide a comprehensive and up-to-date synthesis of the evidence on the association between prenatal or perinatal risk and protective factors and psychotic disorders.

METHODS

In this systematic review and meta-analysis, we searched the Web of Science database for articles published up to July 20, 2019. We identified cohort and case-control studies examining the association (odds ratio [OR]) between prenatal and perinatal factors and any International Classification of Diseases (ICD) or Diagnostic and Statistical Manual of Mental Disorders (DSM) non-organic psychotic disorder with a healthy comparison group. Other inclusion criteria were enough data available to do the analyses, and non-overlapping datasets. We excluded reviews, meta-analyses, abstracts or conference proceedings, and articles with overlapping datasets. Data were extracted according to EQUATOR and PRISMA guidelines. Extracted variables included first author, publication year, study type, sample size, type of psychotic diagnosis (non-affective psychoses or schizophrenia-spectrum disorders, affective psychoses) and diagnostic instrument (DSM or ICD and version), the risk or protective factor, and measure of association (primary outcome). We did random-effects pairwise meta-analyses, Q statistics, I² index, sensitivity analyses, meta-regressions, and assessed study quality and publication bias. The study protocol was registered at PROSPERO, CRD42017079261.

FINDINGS

152 studies relating to 98 risk or protective factors were eligible for analysis. Significant risk factors were: maternal age younger than 20 years (OR 1·17) and 30-34 years (OR 1·05); paternal age younger than 20 years (OR 1·31) and older than 35 years (OR 1·28); any maternal (OR 4·60) or paternal (OR 2·73) psychopathology; maternal psychosis (OR 7·61) and affective disorder (OR 2·26); three or more pregnancies (OR 1·30); herpes simplex 2 (OR 1·35); maternal infections not otherwise specified (NOS; OR 1·27); suboptimal number of antenatal visits (OR 1·83); winter (OR 1·05) and winter to spring (OR 1·05) season of birth in the northern hemisphere; maternal stress NOS (OR 2·40); famine (OR 1·61); any famine or nutritional deficits in pregnancy (OR 1·40); maternal hypertension (OR 1·40); hypoxia (OR 1·63); ruptured (OR 1·86) and premature rupture (OR 2·29) of membranes; polyhydramnios (OR 3·05); definite obstetric complications NOS (OR 1·83); birthweights of less than 2000 g (OR 1·84), less than 2500 g (OR 1·53), or 2500-2999 g (OR 1·23); birth length less than 49 cm (OR 1·17); small for gestational age (OR 1·40); premature birth (OR 1·35), and congenital malformations (OR 2·35). Significant protective factors were maternal ages 20-24 years (OR 0·93) and 25-29 years (OR 0·92), nulliparity (OR 0·91), and birthweights 3500-3999 g (OR 0·90) or more than 4000 g (OR 0·86). The results were corrected for publication biases; sensitivity and meta-regression analyses confirmed the robustness of these findings for most factors.

INTERPRETATION

Several prenatal and perinatal factors are associated with the later onset of psychosis. The updated knowledge emerging from this study could refine understanding of psychosis pathogenesis, enhance multivariable risk prediction, and inform preventive strategies.

FUNDING

None.

Zebrafish as a tool to study schizophrenia-associated copy number variants

Schizophrenia remains one of the most debilitating human neurodevelopmental disorders, with few effective treatments and striking consequences felt by individuals, communities and society as a whole. As such, there remains a critical need for further investigation into the mechanistic underpinnings of schizophrenia so that novel therapeutic targets can be identified. Because schizophrenia is a highly heritable disorder, genetic risk factors remain an attractive avenue for this research. Given their clear molecular genetic consequences, recurrent microdeletions and duplications, or copy number variants (CNVs), represent one of the most tractable genetic entry points to elucidating these mechanisms. To date, eight CNVs have been shown to significantly increase the risk of schizophrenia. Although rodent models of these CNVs that exhibit behavioral phenotypes have been generated, the underlying molecular mechanisms remain largely elusive. Over the past decades, the zebrafish has emerged as a powerful vertebrate model that has led to fundamental discoveries in developmental neurobiology and behavioral genetics. Here, we review the attributes that make zebrafish exceptionally well suited to investigating individual and combinatorial gene contributions to CNV-mediated brain dysfunction in schizophrenia. With highly conserved genetics and neural substrates, an ever-expanding molecular genetic and imaging toolkit, and ability to perform high-throughput and high-content genetic and pharmacologic screens, zebrafish is poised to generate deep insights into the molecular genetic mechanisms of schizophrenia-associated neurodevelopmental and behavioral deficits, and to facilitate the identification of therapeutic targets.

Challenges and Future Prospects of Precision Medicine in Psychiatry

Precision medicine is increasingly recognized as a promising approach to improve disease treatment, taking into consideration the individual clinical and biological characteristics shared by specific subgroups of patients. In specific fields such as oncology and hematology, precision medicine has already started to be implemented in the clinical setting and molecular testing is routinely used to select treatments with higher efficacy and reduced adverse effects. The application of precision medicine in psychiatry is still in its early phases. However, there are already examples of predictive models based on clinical data or combinations of clinical, neuroimaging and biological data. While the power of single clinical predictors would remain inadequate if analyzed only with traditional statistical approaches, these predictors are now increasingly used to impute machine learning models that can have adequate accuracy even in the presence of relatively small sample size. These models have started to be applied to disentangle relevant clinical questions that could lead to a more effective management of psychiatric disorders, such as prediction of response to the mood stabilizer lithium, resistance to antidepressants in major depressive disorder or stratification of the risk and outcome prediction in schizophrenia. In this narrative review, we summarized the most important findings in precision medicine in psychiatry based on studies that constructed machine learning models using clinical, neuroimaging and/or biological data. Limitations and barriers to the implementation of precision psychiatry in the clinical setting, as well as possible solutions and future perspectives, will be presented.

Preventive Treatments for Psychosis: Umbrella Review (Just the Evidence)

Background: Indicated primary prevention in young people at Clinical High Risk for Psychosis (CHR-P) is a promising avenue for improving outcomes of one of the most severe mental disorders but their effectiveness has recently been questioned. Methods: Umbrella review. A multi-step independent literature search of Web of Science until January 11, 2019, identified interventional meta-analyses in CHR-P individuals. The individual randomised controlled trials that were analysed by the meta-analyses were extracted. A review of ongoing trials and a simulation of living meta-analysis complemented the analysis. Results: Seven meta-analyses investigating preventive treatments in CHR-P individuals were included. None of them produced pooled effect sizes across psychological, pharmacological, or other types of interventions. The outcomes analysed encompassed risk of psychosis onset, the acceptability of treatments, the severity of attenuated positive/negative psychotic symptoms, depression, symptom-related distress, social functioning, general functioning, and quality of life. These meta-analyses were based on 20 randomised controlled trials: the vast majority defined the prevention of psychosis onset as their primary outcome of interest and only powered to large effect sizes. There was no evidence to favour any preventive intervention over any other (or control condition) for improving any of these clinical outcomes. Caution is required when making clinical recommendations for the prevention of psychosis in individuals at risk. Discussion: Prevention of psychosis from a CHR-P state has been, and should remain, the primary outcome of interventional research, refined and complemented by other clinically meaningful outcomes. Stagnation of knowledge should promote innovative and collaborative research efforts, in line with the progressive and incremental nature of medical knowledge. Advancements will most likely be associated with the development of new experimental therapeutics that are ongoing along with the ability to deconstruct the high heterogeneity within CHR-P populations. This would require the estimation of treatment-specific effect sizes through living individual participant data meta-analyses, controlling risk enrichment during recruitment, statistical power, and embedding precision medicine within youth mental health services that can accommodate sequential prognosis and advanced trial designs. Conclusions: The evidence-based challenges and proposed solutions addressed by this umbrella review can inform the next generation of research into preventive treatments for psychosis.

Transdiagnostic Individualized Clinically Based Risk Calculator for the Detection of Individuals at Risk and the Prediction of Psychosis: Model Refinement Including Nonlinear Effects of Age

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 non-organic/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.

Improving the Detection of Individuals at Clinical Risk for Psychosis in the Community, Primary and Secondary Care: An Integrated Evidence-Based Approach

Background: The first rate-limiting step for improving outcomes of psychosis through preventive interventions in people at clinical high risk for psychosis (CHR-P) is the ability to accurately detect individuals who are at risk for the development of this disorder. Currently, this detection power is sub-optimal. Methods: This is a conceptual and nonsystematic review of the literature, focusing on the work conducted by leading research teams in the field. The results will be structured in the following sections: understanding the CHR-P assessment, validity of the CHR-P as a universal risk state for psychosis, and improving the detection of at-risk individuals in secondary mental health care, in primary care, and in the community. Results: CHR-P instruments can provide adequate prognostic accuracy for the prediction of psychosis provided that they are employed in samples who have undergone risk enrichment during recruitment. This substantially limits their detection power in real-world settings. Furthermore, there is initial evidence that not all cases of psychosis onset are preceded by a CHR-P stage. A transdiagnostic individualized risk calculator could be used to automatically screen secondary mental health care medical notes to detect those at risk of psychosis and refer them to standard CHR-P assessment. Similar risk estimation tools for use in primary care are under development and promise to boost the detection of patients at risk in this setting. To improve the detection of young people who may be at risk of psychosis in the community, it is necessary to adopt digital and/or sequential screening approaches. These solutions are based on recent scientific evidence and have potential for implementation internationally. Conclusions: The best strategy to improve the detection of patients at risk for psychosis is to implement a clinical research program that integrates different but complementary detection approaches across community, primary, and secondary care. These solutions are based on recent scientific advancements in the development of risk estimation tools and e-health approaches and have the potential to be applied across different clinical settings.