Prediction and prevention of psychosis: current progress and future tasks

Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls

Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.

Attitudes towards Risk Prediction in a Help Seeking Population of Early Detection Centers for Mental Disorders-A Qualitative Approach

Big Data approaches raise hope for a paradigm shift towards illness prevention, while others are concerned about discrimination resulting from these approaches. This will become particularly important for people with mental disorders, as research on medical risk profiles and early detection progresses rapidly. This study aimed to explore views and attitudes towards risk prediction in people who, for the first time, sought help at one of three early detection centers for mental disorders in Germany (Cologne, Munich, Dresden). A total of 269 help-seekers answered an open-ended question on the potential use of risk prediction. Attitudes towards risk prediction and motives for its approval or rejection were categorized inductively and analyzed using qualitative content analysis. The anticipated impact on self-determination was a driving decision component, regardless of whether a person would decide for or against risk prediction. Results revealed diverse, sometimes contrasting, motives for both approval and rejection (e.g., the desire to control of one’s life as a reason for and against risk prediction). Knowledge about a higher risk as a potential psychological burden was one of the major reasons against risk prediction. The decision to make use of risk prediction is expected to have far-reaching effects on the quality of life and self-perception of potential users. Healthcare providers should empower those seeking help by carefully considering individual expectations and perceptions of risk prediction.

Development of Proteomic Prediction Models for Transition to Psychotic Disorder in the Clinical High-Risk State and Psychotic Experiences in Adolescence

IMPORTANCE

Biomarkers that are predictive of outcomes in individuals at risk of psychosis would facilitate individualized prognosis and stratification strategies.

OBJECTIVE

To investigate whether proteomic biomarkers may aid prediction of transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study comprised 2 case-control studies nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) and the Avon Longitudinal Study of Parents and Children (ALSPAC). EU-GEI is an international multisite prospective study of participants at CHR referred from local mental health services. ALSPAC is a United Kingdom-based general population birth cohort. Included were EU-GEI participants who met CHR criteria at baseline and ALSPAC participants who did not report PEs at age 12 years. Data were analyzed from September 2018 to April 2020.

MAIN OUTCOMES AND MEASURES

In EU-GEI, transition status was assessed by the Comprehensive Assessment of At-Risk Mental States or contact with clinical services. In ALSPAC, PEs at age 18 years were assessed using the Psychosis-Like Symptoms Interview. Proteomic data were obtained from mass spectrometry of baseline plasma samples in EU-GEI and plasma samples at age 12 years in ALSPAC. Support vector machine learning algorithms were used to develop predictive models.

RESULTS

The EU-GEI subsample (133 participants at CHR (mean [SD] age, 22.6 [4.5] years; 68 [51.1%] male) comprised 49 (36.8%) who developed psychosis and 84 (63.2%) who did not. A model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0%; and negative predictive value [NPV], 98.6%). Functional analysis of differentially expressed proteins implicated the complement and coagulation cascade. A model based on the 10 most predictive proteins accurately predicted transition status in training (AUC, 0.99; PPV, 76.9%; and NPV, 100%) and test (AUC, 0.92; PPV, 81.8%; and NPV, 96.8%) data. The ALSPAC subsample (121 participants from the general population with plasma samples available at age 12 years (61 [50.4%] male) comprised 55 participants (45.5%) with PEs at age 18 years and 61 (50.4%) without PEs at age 18 years. A model using proteomic data at age 12 years predicted PEs at age 18 years, with an AUC of 0.74 (PPV, 67.8%; and NPV, 75.8%).

CONCLUSIONS AND RELEVANCE

In individuals at risk of psychosis, proteomic biomarkers may contribute to individualized prognosis and stratification strategies. These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes.

Age effects on basic symptoms in the community: A route to gain new insight into the neurodevelopment of psychosis?

Reports of limited clinical significance of attenuated psychotic symptoms before age 15/16 indicate an important role of neurodevelopment in the early detection of psychoses. Therefore, we examined if age also exerts an influence on the prevalence and clinical significance of the 14 cognitive and perceptive basic symptoms (BS) used in psychosis-risk criteria and conceptualized as the most direct self-experienced expression of neurobiological aberrations. A random representative general population sample of the Swiss canton Bern (N = 689, age 8-40 years, 06/2011-05/2014) was interviewed for BS, psychosocial functioning, and current mental disorder. BS were reported by 18% of participants, mainly cognitive BS (15%). In regression analyses, age affected perceptive and cognitive BS differently, indicating an age threshold for perceptive BS in late adolescence (around age 18) and for cognitive BS in young adulthood (early twenties)-with higher prevalence, but a lesser association with functional deficits and the presence of mental disorder in the below-threshold groups. Thereby, interaction effects between age and BS on functioning and mental disorder were commonly stronger than individual effects of age and BS. Indicating support of the proposed "substrate-closeness" of BS, differential age effects of perceptual and cognitive BS seem to follow normal brain maturation processes, in which they might occur as infrequent and temporary non-pathological disturbances. Their persistence or occurrence after conclusion of main brain maturation processes, however, might signify aberrant maturation or neurodegenerative processes. Thus, BS might provide important insight into the pathogenesis of psychosis and into differential neuroprotective or anti-inflammatory targets.

Health literacy in clinical-high-risk individuals for psychosis: A systematic mixed-methods review

OBJECTIVE

Numerous studies suggest that health literacy (HL) plays a crucial role in maintaining and improving individual health. Empirical findings highlight the relation between levels of a person's HL and her/his clinical outcome. To date, the role of HL in persons at-risk for psychosis has not been systematically reviewed.

METHODS

We conducted a systematic review using a mixed-methods approach to analyse a variety of study types. Peer-reviewed publications were systematically searched in PUBMED, Cochrane Library, PsycINFO and Web of Science.

RESULTS

The search string returned 10587 publications. After screening, 15 quantitative, four qualitative studies and two reviews were included. Only one study assessed HL as primary outcome, assessing knowledge and beliefs about psychosis among the general population. In the other studies, sub-dimensions of HL were investigated. None of the publications operationalized HL or it's sub-dimensions with a validated measure.

CONCLUSIONS

A lack of understanding of their condition, and fear of stigmatization, were associated with a delay in help-seeking among people with clinical-high-risk state for psychosis. Family members, school personnel, general practitioners and the internet play a crucial role in the HL process. Considerable barriers in obtaining adequate specialist support emphasize the urgent need of a "HL environment" for persons at risk for psychosis.

Influence of demographic characteristics on attenuated positive psychotic symptoms in a young, help-seeking, at-risk population

AIM

Presentation of attenuated positive psychotic symptoms (APS) was reported to be modestly influenced by age, sex and education in a psychosis-risk sample. We re-examined the influence of demographic variables on APS in an independent psychosis-risk sample.

METHOD

In a clinical high-risk-sample (N = 188; 13-35 years; 60.1% men), bivariate correlations were examined with Spearman correlations. All other associations were computed with generalized linear models.

RESULTS

Inter-correlations between positive symptoms were statistically significant for all but the smallest coefficient (range: r = 0.12-0.49). Age was negatively related to APS (range: OR = 0.53-0.78, all P < .01). Male sex was uniquely related to disorganized communication (OR = 1.46) and a high education-level related negatively to suspiciousness/persecutory ideas (OR = 0.64), perceptual abnormalities/hallucinations (OR = 0.57) and disorganized communication (OR = 0.54). The variance explained by age ranged from R ² = 0.044 for unusual thought content to R ² = 0.144 for perceptual abnormalities.

CONCLUSION

Our results highlighted the role of age and, thereby, neurodevelopment in psychosis-risk assessment.

Course of clinical high-risk states for psychosis beyond conversion

BACKGROUND

The main focus of research on clinical high-risk states for psychosis (CHR) has been the development of algorithms to predict psychosis. Consequently, other outcomes have been neglected, and little is known about the long-term diagnostic and functional outcome among those not converting to psychosis.

METHODS

In a naturalistic study, incidence, persistence, and remission rates of CHR states according to symptomatic ultra-high risk or cognitive disturbances criteria were investigated in 160 of 246 outpatients of an early detection of psychoses service (21.1% CHR negative and 78.9% CHR positive at baseline) who had not converted to psychosis within follow-up (median 53.7 months, range 13.9-123.7 months).

RESULTS

Remission rate of CHR status was 43.3% of all 194 CHR-positive cases, including converters, or 72.4% if only the 116 non-converters were considered, persistence rate was 27.6%, and new occurrence rate in initially CHR-negative patients was 9.1%. At follow-up, 54.5% of the non-converters met criteria of at least one Axis-I diagnosis, mainly affective and anxiety disorders, and had functional problems. The severity of risk at baseline was not associated with a higher presence of Axis-I diagnosis at follow-up.

CONCLUSIONS

During follow-up, CHR symptoms remitted in one-third of initially CHR-positive patients, while almost 10% met CHR criteria newly in CHR-negative adults presenting at early detection services. The presence of CHR criteria seems to maintain the risk for lower functioning and mental disorders, particularly for affective disorders. Thus, therapeutic efforts targeting CHR patients should also focus on the current mental disorders as well as social and role functions to improve the long-term outcome.

Aberrant Temporal Connectivity in Persons at Clinical High Risk for Psychosis

Background

Schizophrenia, a neurodevelopmental disorder, involves abnormalities in functional connectivity (FC) across distributed neural networks, which are thought to antedate the emergence of psychosis. In a cohort of adolescents and young adults at clinical high risk (CHR) for psychosis, we applied data-driven approaches to resting-state fMRI data so as to systematically characterize FC abnormalities during this period and determine whether these abnormalities are associated with psychosis risk and severity of psychotic symptoms.

Methods

Fifty-one CHR participants and 47 matched healthy controls (HCs) were included in our analyses. Twelve of these CHR participants developed psychosis within 3.9 years. We estimated one multivariate measure of FC and studied its relationship to CHR status, conversion to psychosis and positive symptom severity.

Results

Multivariate analyses revealed between-group differences in whole-brain connectivity patterns of bilateral temporal areas, mostly affecting their functional connections to the thalamus. Further, more severe positive symptoms were associated with greater connectivity abnormalities in the anterior cingulate and frontal cortex.

Conclusions

Our study demonstrates that the well-established FC abnormalities of the thalamus and temporal areas observed in schizophrenia are also present in the CHR period, with aberrant connectivity of the temporal cortex most associated with psychosis risk.

Restricted attention to social cues in schizophrenia patients

Deficits of psychosocial functioning are a robust finding in schizophrenia. Research on social cognition may open a new avenue for the development of effective interventions. As a correlate of social perceptive information processing deficits, schizophrenia patients (SZP) show deviant gaze behavior (GB) while viewing emotional faces. As understanding of a social environment requires gathering complex social information, our study aimed at investigating the gaze behavior of SZP related to social interactions and its impact on the level of social and role functioning. GB of 32 SZP and 37 healthy control individuals (HCI) was investigated with a high-resolution eye tracker during an unguided viewing of 12 complex pictures of social interaction scenes. Regarding whole pictures, SZP showed a shorter scanpath length, fewer fixations and a shorter mean distance between fixations. Furthermore, SZP exhibited fewer and shorter fixations on faces, but not on the socially informative bodies nor on the background, suggesting a cue-specific abnormality. Logistic regression with bootstrapping yielded a model including two GB parameters; a subsequent ROC curve analysis indicated an excellent ability of group discrimination (AUC .85). Face-related GB aberrations correlated with lower social and role functioning and with delusional thinking, but not with negative symptoms. Training of spontaneous integration of face-related social information seems promising to enable a holistic perception of social information, which may in turn improve social and role functioning. The observed ability to discriminate SZP from HCI warrants further research on the predictive validity of GB in psychosis risk prediction.

Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients

OBJECTIVES

This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients.

METHODS

We assessed the individualised prediction of psychosis by detecting specific patterns of beta and gamma oscillations using machine-learning algorithms. Prediction models were trained and tested on 53 neuroleptic-naïve patients with a clinical high-risk for psychosis. Of these, 18 later transitioned to psychosis. All patients were followed up for at least 3 years. For an honest estimation of the generalisation capacity, the predictive performance of the models was assessed in unseen test cases using repeated nested cross-validation.

RESULTS

Transition to psychosis could be predicted from current-source density (CSD; area under the curve [AUC] = 0.77), but not from lagged phase synchronicity data (LPS; AUC = 0.56). Combining both modalities did not improve the predictive accuracy (AUC = 0.78). The left superior temporal gyrus, the left inferior parietal lobule and the precuneus most strongly contributed to the prediction of psychosis.

CONCLUSIONS

Our results suggest that CSD measurements extracted from clinical resting state EEG can help to improve the prediction of psychosis on a single-subject level.

Progress and Future Directions in Research on the Psychosis Prodrome: A Review for Clinicians

LEARNING OBJECTIVES

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ABSTRACT

The psychosis prodrome, or period of clinical and functional decline leading up to acute psychosis, offers a unique opportunity for identifying mechanisms of psychosis onset and for testing early-intervention strategies. We summarize major findings and emerging directions in prodromal research and provide recommendations for clinicians working with individuals suspected to be at high risk for psychosis. The past two decades of research have led to three major advances. First, tools and criteria have been developed that can reliably identify imminent risk for a psychotic disorder. Second, longitudinal clinical and psychobiological data from large multisite studies are strengthening individual risk assessment and offering insights into potential mechanisms of illness onset. Third, psychosocial and pharmacological interventions are demonstrating promise for delaying or preventing the onset of psychosis in help-seeking, high-risk individuals. The dynamic psychobiological processes implicated in both risk and onset of psychosis, including altered gene expression, cognitive dysfunction, inflammation, gray and white matter brain changes, and vulnerability-stress interactions suggest a wide range of potential treatment targets and strategies. The expansion of resources devoted to early intervention and prodromal research worldwide raises hope for investigating them. Future directions include identifying psychosis-specific risk and resilience factors in children, adolescents, and non-help-seeking community samples, improving study designs to test hypothesized mechanisms of change, and intervening with strategies that, in order to improve functional outcomes, better engage youth, address their environmental contexts, and focus on evidence-based neurodevelopmental targets. Prospective research on putatively prodromal samples has the potential to substantially reshape our understanding of mental illness and our efforts to combat it.

Detection and treatment of at-risk mental state for developing a first psychosis: making up the balance

The at-risk mental state (ARMS) has been substantially researched and used as the basis for new clinical settings and strategies over the past two decades. However, it has also caused controversy and intense debate. In this Review, we assess available evidence and propose future directions. Accumulating research suggests that a blend of clinical staging and profiling, which naturally incorporates ARMS, might be a better guide for treatment of patients in different stages of psychiatric illness than the categorical DSM and ICD systems. Furthermore, clinical staging, with its emphasis on balancing risks and benefits, could help to prevent premature treatment or overtreatment with psychotropic drugs. Meta-analyses and reviews show that treatment of ARMS leads to a significant reduction in transition rate to a first psychosis. The debate about stigma associated with ARMS is based on scarce published work. The few studies that have been done suggest that stigma (including self-stigma) arises largely from negative societal views on psychiatric disorders and, depending on the setting and approach, not from engagement in treatment for ARMS per se. The evidence base suggests that definition of ARMS is an important step in implementation of clinical staging and profiling in psychiatry. However, more research across traditional diagnostic boundaries is needed to refine these clinical phenotypes and link them to biomarkers with the goal of personalised stepwise care. Health-system reform is overdue and a parallel process to support this approach is needed, which is similar to how physical forms of non-communicable disease are treated.