Subclinical Psychotic Experiences Research Articles

The impact of affective and negative symptoms on the development of psychosis in a six-year follow-up of a community-based population.

The Clinical High Risk (CHR) concept has a limited transition risk to psychotic disorders (PD). This study investigates the association between affective and negative symptoms, currently not included in the CHR concept, and the risk of transition to PD in a community-based population of 2185 participants in Turkey. Participants were assessed twice over six years using a multistage sampling technique. Two separate linear regression analyses were conducted on data from both assessments, investigating the relationship between affective and negative symptoms, subclinical and clinical psychotic experiences (PE) and progression to PD. The overall transition rate to PD was 1.3%. The analysis showed no increased risk of developing PD for the 'subclinical PE only' group at follow-up, compared to the 'no PE' group. However, being classified as having 'clinical PE only' (OR: 6.23; p = 0.010) and 'clinical PE + affective/negative symptoms' (OR: 8.48; p = 0.001) at baseline was associated with an increased risk of developing PD at follow-up. The presence of 'affective/negative symptoms' at baseline was associated with an increased risk of incident subclinical PE (RR: 1.98; p = 0.001), incident clinical PE (RR: 3.14; p = 0.001), and incident PD (RR: 4.21; p = 0.030) at follow-up. The results confirm the significance of the baseline severity of positive symptoms in predicting the transition to PD and suggest that both positive and affective/negative symptoms impact the transition risk to PD and incident psychotic symptoms. This highlights the potential utility of defining CHR groups based on a combination of positive, affective, and negative symptoms.

Sex Differences in Subclinical Psychotic Experiences: The Role of Daily-Life Social Interactions.

Sex differences in psychosis are reported across the psychosis spectrum, including in subclinical stages. An important factor in understanding these variations is the subjective experience of everyday social interactions (SI). We investigated whether the presence of psychotic experiences (PEs), as well as associated distress, differs between men and women. We focused on the role of daily-life SI quality and whether its association with PEs varies by sex. We included adolescents from SIGMA, a general youth population study in Flanders, Belgium (n = 344; mean age = 18.7; 63.4% female). Psychotic experiences were measured using the PQ-16. We used Experience Sampling Methodology to assess daily-life SI. A multilevel model and multiple linear regressions were used to assess, respectively, the relationship between sex and SI quality and whether PEs and their association with SI quality differ between young men and women. The results of the multilevel linear regression model indicate that the prevalence of and distress associated with PEs were higher in women. No significant difference was observed in the subjective quality of daily SI. Social interaction quality was strongly related to PEs. This association did not seem to vary for the prevalence of PEs, though women's distress about PEs appeared to be more affected by SI quality. Present findings highlight the role of the subjective quality of SI in subclinical psychosis. More research is needed to investigate the mechanisms through which SI quality relates to PEs, and whether these differ between young men and women.

Individual differences in belief updating and phasic arousal are related to psychosis proneness

Many decisions entail the updating of beliefs about the state of the environment by accumulating noisy sensory evidence. This form of probabilistic reasoning may go awry in psychosis. Computational theory shows that optimal belief updating in environments subject to hidden changes in their state requires a dynamic modulation of the evidence accumulation process. Recent empirical findings implicate transient responses of pupil-linked central arousal systems to individual evidence samples in this modulation. Here, we analyzed behavior and pupil responses during evidence accumulation in a changing environment in a community sample of human participants. We also assessed their subclinical psychotic experiences (psychosis proneness). Participants most prone to psychosis showed overall less flexible belief updating profiles, with diminished behavioral impact of evidence samples occurring late during decision formation. These same individuals also exhibited overall smaller pupil responses and less reliable pupil encoding of computational variables governing the dynamic belief updating. Our findings provide insights into the cognitive and physiological bases of psychosis proneness and open paths to unraveling the pathophysiology of psychotic disorders.

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising approach for the diagnosis and monitoring of psychosis, capturing symptoms like thought disorder and flattened affect. Recent advancements in Natural Language Processing (NLP) methodologies enable the automated extraction of informative speech features, which has been leveraged for early psychosis detection and assessment of symptomology. However, critical gaps persist, including the absence of standardized sample collection protocols, small sample sizes, and a lack of multi-illness classification, limiting clinical applicability. Our study aimed to (1) identify an optimal assessment approach for the online and remote collection of speech, in the context of assessing the psychosis spectrum and evaluate whether a fully automated, speech-based machine learning (ML) pipeline can discriminate among different conditions on the schizophrenia-bipolar spectrum (SSD-BD-SPE), help-seeking comparison subjects (MDD), and healthy controls (HC) at varying layers of analysis and diagnostic complexity. We adopted online data collection methods to collect 20 minutes of speech and demographic information from individuals. Participants were categorized as "healthy" help-seekers (HC), having a schizophrenia-spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), or being on the psychosis spectrum with sub-clinical psychotic experiences (SPE). SPE status was determined based on self-reported clinical diagnosis and responses to the PHQ-8 and PQ-16 screening questionnaires, while other diagnoses were determined based on self-report from participants. Linguistic and paralinguistic features were extracted and ensemble learning algorithms (e.g., XGBoost) were used to train models. A 70%-30% train-test split and 30-fold cross-validation was used to validate the model performance. The final analysis sample included 1140 individuals and 22,650 minutes of speech. Using 5-minutes of speech, our model could discriminate between HC and those with a serious mental illness (SSD or BD) with 86% accuracy (AUC = 0.91, Recall = 0.7, Precision = 0.98). Furthermore, our model could discern among HC, SPE, BD and SSD groups with 86% accuracy (F1 macro = 0.855, Recall Macro = 0.86, Precision Macro = 0.86). Finally, in a 5-class discrimination task including individuals with MDD, our model had 76% accuracy (F1 macro = 0.757, Recall Macro = 0.758, Precision Macro = 0.766). Our ML pipeline demonstrated disorder-specific learning, achieving excellent or good accuracy across several classification tasks. We demonstrated that the screening of mental disorders is possible via a fully automated, remote speech assessment pipeline. We tested our model on relatively high number conditions (5 classes) in the literature and in a stratified sample of psychosis spectrum, including HC, SPE, SSD and BD (4 classes). We tested our model on a large sample (N = 1150) and demonstrated best-in-class accuracy with remotely collected speech data in the psychosis spectrum, however, further clinical validation is needed to test the reliability of model performance.

Psychotic experiences in university students: prevalence, correlates and association with non-specific psychological distress

Introduction Subclinical psychotic experiences (PEs) are far more prevalent than psychotic disorders, with an estimated prevalence of 7.2% (Linscott & Van Os. Psychol Med 2013;43(6) 1133-1149). PEs are particularly prevalent in late adolescence and young adulthood, when obtaining academic education is one of the main developmental tasks. University students are at the peak age of onset of mental disorders, and often experience high levels of social and academic stress that may contribute to the onset of psychopathology. Hence, estimating the prevalence and correlates of PEs among university students is particularly important.ObjectivesTo estimate the prevalence of PEs in a sample of Israeli students; assess whether rates of PEs differ by selected sociodemographic characteristics; and examine the association between PEs and non-specific psychological distress.Methods150 students from universities and colleges in Israel participated in a cross-sectional online survey. All students were over the age of 18 and were not diagnosed with psychotic disorders. Participants completed self-report questionnaires, including the Prodromal Questionnaire - Brief Version (PQ-B), Kessler Psychological Distress Scale (K10) and sociodemographic details. The PQ-B yields a score for the total number of items endorsed (range 0–21), and a total distress score (range 0–105). A cutoff of ≥8 distressing symptoms was used to identify participants at high-risk for psychosis.Results 21 participants (14.0%) reported 8 or more distressing PEs. PEs were more common in males and among those with a psychiatric illness (Table 1). PEs were not associated with marital status, religiosity, or immigrant status. While a greater number of PEs was positively associated with non-specific psychological distress (r=0.589, p<.001), there was no association between distress caused by PEs and non-specific psychological distress (r=0.145, NS). Table 1.Sociodemographic characteristics by groupPEs-PEs+X2, pSexM29.5%52.4%4.32, .038F70.5%47.6%Marital StatusMarried17.1%23.8%0.56, NSUnmarried82.9%76.2%ImmigrantNo89.9%85.7%0.34, NSYes10.1%14.3%ReligiositySecular74.4%57.1%2.67, NSOther25.6%42.9% PsychiatricillnessNo87.6%61.9%8.87, .003Yes12.4%38.1%ConclusionsThe findings confirm that self-reported PEs are much more prevalent than clinically diagnosed psychotic disorders, particularly among young adults. As PEs were found to be associated with non-specific psychological distress, and as they are known forerunners for severe mental disorders, it is important to address mental health issues in school settings and promote prevention and early intervention programs.Disclosure of InterestNone Declared

Automated analysis of speech as a marker of sub-clinical psychotic experiences.

Automated speech analysis techniques, when combined with artificial intelligence and machine learning, show potential in capturing and predicting a wide range of psychosis symptoms, garnering attention from researchers. These techniques hold promise in predicting the transition to clinical psychosis from at-risk states, as well as relapse or treatment response in individuals with clinical-level psychosis. However, challenges in scientific validation hinder the translation of these techniques into practical applications. Although sub-clinical research could aid to tackle most of these challenges, there have been only few studies conducted in speech and psychosis research in non-clinical populations. This work aims to facilitate this work by summarizing automated speech analytical concepts and the intersection of this field with psychosis research. We review psychosis continuum and sub-clinical psychotic experiences, and the benefits of researching them. Then, we discuss the connection between speech and psychotic symptoms. Thirdly, we overview current and state-of-the art approaches to the automated analysis of speech both in terms of language use (text-based analysis) and vocal features (audio-based analysis). Then, we review techniques applied in subclinical population and findings in these samples. Finally, we discuss research challenges in the field, recommend future research endeavors and outline how research in subclinical populations can tackle the listed challenges.

Longitudinal trajectories of anterior cingulate glutamate and subclinical psychotic experiences in early adolescence: the impact of bullying victimization

Previous studies reported decreased glutamate levels in the anterior cingulate cortex (ACC) in non-treatment-resistant schizophrenia and first-episode psychosis. However, ACC glutamatergic changes in subjects at high-risk for psychosis, and the effects of commonly experienced environmental emotional/social stressors on glutamatergic function in adolescents remain unclear. In this study, adolescents recruited from the general population underwent proton magnetic resonance spectroscopy (MRS) of the pregenual ACC using a 3-Tesla scanner. We explored longitudinal data on the association of combined glutamate-glutamine (Glx) levels, measured by MRS, with subclinical psychotic experiences. Moreover, we investigated associations of bullying victimization, a risk factor for subclinical psychotic experiences, and help-seeking intentions, a coping strategy against stressors including bullying victimization, with Glx levels. Finally, path analyses were conducted to explore multivariate associations. For a contrast analysis, gamma-aminobutyric acid plus macromolecule (GABA+) levels were also analyzed. Negative associations were found between Glx levels and subclinical psychotic experiences at both Times 1 (n = 219, mean age 11.5 y) and 2 (n = 211, mean age 13.6 y), as well as for over-time changes (n = 157, mean interval 2.0 y). Moreover, effects of bullying victimization and bullying victimization × help-seeking intention interaction effects on Glx levels were found (n = 156). Specifically, bullying victimization decreased Glx levels, whereas help-seeking intention increased Glx levels only in bullied adolescents. Finally, associations among bullying victimization, help-seeking intention, Glx levels, and subclinical psychotic experiences were revealed. GABA+ analysis revealed no significant results. This is the first adolescent study to reveal longitudinal trajectories of the association between glutamatergic function and subclinical psychotic experiences and to elucidate the effect of commonly experienced environmental emotional/social stressors on glutamatergic function. Our findings may deepen the understanding of how environmental emotional/social stressors induce impaired glutamatergic neurotransmission that could be the underpinning of liability for psychotic experiences in early adolescence.

Acceptance and Commitment Therapy and white matter plasticity in individuals with subclinical depression and psychotic experiences: A Randomised Controlled Trial

BackgroundResearch indicates that Acceptance and Commitment Therapy in Daily Life (ACT-DL) is effective in reducing symptoms of depression, anxiety and psychosis. During adolescence, vulnerability to psychopathology peaks, creating a window for early interventions, while white matter development is ongoing. This study aims to examine microstructural white matter after ACT-DL intervention in youngsters with mild psychopathology. MethodsForty-five individuals with mild psychopathology were randomly allocated to ACT-DL (n=20) or topic discussion control (TD, n=25). Symptomatology was assessed with the Community Assessment of Psychic Experiences (CAPE), Montgomery–Åsberg Depression Rating Scale (MADRS) and the Experience Sampling Method (ESM). Diffusion Weighted Imaging (DWI) and network-connectivity parameters were obtained and compared before and after the intervention/control condition. Interactions between microstructural white matter change and condition were examined in models of CAPE positive symptoms and ESM subclinical psychotic experiences (PE) and negative affect (NA) levels. ResultsACT-DL, compared to TD, was associated with changes on subclinical depressive and psychotic symptom levels. There was no significant change in DWI or network connectivity in either condition and no significant difference between both conditions. In the model of NA, several regional interactions between condition and network measures were significant, but stratification per condition provided no significant associations. There were no significant interactions between DWI or network connectivity parameters and condition in the models of the CAPE positive symptoms, MADRS and PE. ConclusionsThe findings suggest that behavioral (symptom) changes are more sensitive to a five-week psychological training than microstructural white matter changes which did not show significant changes over time.

Functioning, symptom expression and risk along the psychosis continuum

The psychosis continuum implies that subclinical psychotic experiences (PEs) can be differentiated from clinically relevant expressions since they are not accompanied by a 'need for care'. Using data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; N = 34 653), the current study examined variation in functioning, symptomology and aetiological risk across the psychosis phenotype [i.e. variation from (i) no PEs, 'No PEs' to (ii) non-distressing PEs, 'PE-Experienced Only' to (iii) distressing PEs, 'PE-Impaired' to (iv) clinically defined psychotic disorder, 'Diagnosed']. A graded trend was present such that, compared to those with no PEs, the Diagnosed group had the poorest functioning, followed by the PE-Impaired then PE-Experienced Only groups. In relation to symptom expression, the PE-Impaired group were more likely than the PE-Experienced Only and the Diagnosed groups to endorse most PEs. Predictors of group membership tended to vary quantitatively rather than qualitatively. Trauma, current mental health diagnoses (anxiety and depression) and drug use variables differentiated between all levels of the continuum, with the exception of the extreme end (PE-Impaired v. Diagnosed). Only a few variables distinguished groups at the upper end of the continuum: female sex, older age, unemployment, parental mental health hospitalisation and lower likelihood of having experienced physical assault. The findings highlight the importance of continuum-based interpretations of the psychosis phenotype and afford valuable opportunities to consider if and how impairment, symptom expression and risk change along the continuum.

Socioenvironmental Adversity and Adolescent Psychotic Experiences: Exploring Potential Mechanisms in a UK Longitudinal Cohort.

Children exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association. Data were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences. Higher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses. Cognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

A 6-year follow-up study in a community-based population: Is neighbourhood-level social capital associated with the risk of emergence and persistence of psychotic experiences and transition to psychotic disorder?

Social capital is thought to represent an environmental factor associated with the risk of psychotic disorder (PD). This study aims to investigate the association between neighbourhood-level social capital and clinical transitions within the spectrum of psychosis. In total, 2175 participants, representative of a community-based population, were assessed twice (6 years apart) to determine their position within an extended psychosis spectrum: no symptoms, subclinical psychotic experiences (PE), clinical PE, PD. A variable representing change between baseline (T1) and follow-up (T2) assessment was constructed. Four dimensions of social capital (informal social control, social disorganisation, social cohesion and trust, cognitive social capital) were assessed at baseline in an independent sample, and the measures were aggregated to the neighbourhood level. Associations between the variable representing psychosis spectrum change from T1 to T2 and the social capital variables were investigated. Lower levels of neighbourhood-level social disorganisation, meaning higher levels of social capital, reduced the risk of clinical PE onset (OR 0.300; z = -2.75; p = 0.006), persistence of clinical PE (OR 0.314; z = -2.36; p = 0.018) and also the transition to PD (OR 0.136; z = -2.12; p = 0.034). The other social capital variables were not associated with changes from T1 to T2. Neighbourhood-level social disorganisation may be associated with the risk of psychosis expression. Whilst replication of this finding is required, it may point to level of social disorganisation as a public health target moderating population psychosis risk.

Neuroanatomical markers of psychotic experiences in adolescents: A machine-learning approach in a longitudinal population-based sample

It is important to identify accurate markers of psychiatric illness to aid early prediction of disease course. Subclinical psychotic experiences (PEs) are important risk factors for later mental ill-health and suicidal behaviour. This study used machine learning to investigate neuroanatomical markers of PEs in early and later stages of adolescence.Machine learning using logistic regression using Elastic Net regularization was applied to T1-weighted and diffusion MRI data to classify adolescents with subclinical psychotic experiences vs. controls across 3 timepoints (Time 1:11–13 years, n = 77; Time 2:14–16 years, n = 56; Time 3:18–20 years, n = 40). Neuroimaging data classified adolescents aged 11–13 years with current PEs vs. controls returning an AROC of 0.62, significantly better than a null model, p = 1.73e-29. Neuroimaging data also classified those with PEs at 18–20 years (AROC = 0.59;P = 7.19e-10) but performance was at chance level at 14–16 years (AROC = 0.50).Left hemisphere frontal regions were top discriminant classifiers for 11–13 years-old adolescents with PEs, particularly pars opercularis. Those with future PEs at 18–20 years-old were best distinguished from controls based on left frontal regions, right-hemisphere medial lemniscus, cingulum bundle, precuneus and genu of the corpus callosum (CC).Deviations from normal adolescent brain development in young people with PEs included an acceleration in the typical pattern of reduction in left frontal thickness and right parietal curvature, and accelerated progression of microstructural changes in right white matter and corpus callosum. These results emphasise the importance of multi-modal analysis for understanding adolescent PEs and provide important new insights into early phenotypes for psychotic experiences.

A systematic review and meta-analysis of the association between emotional stress reactivity and psychosis.

Emotional stress reactivity may be a mediating factor in the association between trauma and psychosis. This review aimed to (i) identify, summarise and critically evaluate the link between emotional stress reactivity and psychotic experiences (ii) examine evidence for a 'dose-response' relationship between stress reactivity and psychosis in the wider psychosis phenotype (i.e., sub-clinical symptoms). Electronic database searches (PsychINFO, MEDLINE, EMBASE) were conducted for studies which investigated the link between stress reactivity and psychosis, psychotic symptoms, or a vulnerability to developing psychosis (wider phenotype). Cross-sectional, experimental and experience sampling method study designs were eligible for inclusion. Fourty five eligible articles were identified (N participants=8830). Narrative synthesis showed that increased emotional stress reactivity was associated with psychosis and subclinical psychotic experiences across all study designs, however, findings were inconsistent across studies. The preliminary meta-analysis (k= 4, n= 383) showed increases in emotional stress reactivity was associated with higher negative affect in response to event-related stress, in those with psychosis compared to controls (mean difference in beta coefficients=0.05, 95% CI 0.02-0.08, p= .004). However, this difference was small with a considerable degree of heterogeneity (p= .001, I2 = 81%) so results should be interpreted with caution. Overall, the evidence suggests that there is a link between emotional stress reactivity and psychosis in those with psychosis, those at high risk of developing psychosis and in relation to subclinical psychotic-like experiences in the general population.

The relationship between cognitive functioning and psychopathology in patients with psychiatric disorders: a transdiagnostic network analysis.

Patients with psychiatric disorders often experience cognitive dysfunction, but the precise relationship between cognitive deficits and psychopathology remains unclear. We investigated the relationships between domains of cognitive functioning and psychopathology in a transdiagnostic sample using a data-driven approach. Cross-sectional network analyses were conducted to investigate the relationships between domains of psychopathology and cognitive functioning and detect clusters in the network. This naturalistic transdiagnostic sample consists of 1016 psychiatric patients who have a variety of psychiatric diagnoses, such as depressive disorders, anxiety disorders, obsessive-compulsive and related disorders, and schizophrenia spectrum and other psychotic disorders. Psychopathology symptoms were assessed using various questionnaires. Core cognitive domains were assessed with a battery of automated tests. Network analysis detected three clusters that we labelled: general psychopathology, substance use, and cognition. Depressive and anxiety symptoms, verbal memory, and visual attention were the most central nodes in the network. Most associations between cognitive functioning and symptoms were negative, i.e. increased symptom severity was associated with worse cognitive functioning. Cannabis use, (subclinical) psychotic experiences, and anhedonia had the strongest total negative relationships with cognitive variables. Cognitive functioning and psychopathology are independent but related dimensions, which interact in a transdiagnostic manner. Depression, anxiety, verbal memory, and visual attention are especially relevant in this network and can be considered independent transdiagnostic targets for research and treatment in psychiatry. Moreover, future research on cognitive functioning in psychopathology should take a transdiagnostic approach, focusing on symptom-specific interactions with cognitive domains rather than investigating cognitive functioning within diagnostic categories.

Public health psychiatry: an idea whose time has come

Public health psychiatry: an idea whose time has come

Psychotic-Like Experiences: A Challenge in Definition and Assessment.

Assuming a continuum between psychotic experiences and psychotic symptoms aligned between healthy individuals and patients with non-psychotic and psychotic disorders, recent research has focused on subclinical psychotic experiences. The wide variety of definitions, assessment tools, and concepts of psychotic-like experiences (PLEs) might contribute to the mixed findings concerning prevalence and persistence rates and clinical impact. In this narrative review, we address the panoply of terminology, definitions, and assessment tools of PLEs and associated concerns with this multitude. Moreover, the ambiguous results of previous studies regarding the clinical relevance of PLEs are described. In conclusion, we address clinical implications and highly suggest conceptual clarity and consensus concerning the terminology and definition of PLEs. The development of an agreed upon use of a “gold standard” assessment tool seems essential for more comparable findings in future research.

Psychopathology among apprentice traditional health practitioners: A quantitative study from rural KwaZulu-Natal, South Africa.

Sociocultural context seems to influence the epidemiology, phenotype, treatment, and course of psychosis. However, data from low- and middle-income countries is sparse. This research is part of a multidisciplinary and multimethod study on possible mental disturbances, including hallucinations, among (apprentice) traditional health practitioners (THPs) who have experienced the "ancestral calling to become a THP" in rural KwaZulu-Natal, South Africa. The aim of the current article is to examine whether the calling-related experiences can be assessed according to a psychiatric taxonomy. We included individuals who were identified with the calling and who were undergoing training to become a THP (ukuthwasa). IsiZulu-speaking formal mental health practitioners conducted thorough psychiatric interviews that measured psychological experiences with and without distress using the Community Assessment of Psychic Experiences, and psychiatric symptoms and disorders using the Schedule for Clinical Assessment in Neuropsychiatry. Of the 48 individuals who participated, 92% had psychotic experiences (PE), causing distress in 75%; and 23% met DSM-5 criteria for an unspecified psychotic disorder (15%) or mood disorder (8%). In conclusion, in rural KwaZulu-Natal, the ancestral calling may resemble phenomena that psychiatry would understand in the context of psychosis, ranging from subclinical PE to clinical psychotic disorder. Ukuthwasa might have a beneficial influence on the course of psychotic symptoms in some individuals, potentially because it reduces stigma and promotes recovery. Further multidisciplinary research is needed to investigate the psychopathology of the apprentice THPs and the underlying processes of ukuthwasa.

Lifetime and Momentary Psychotic Experiences in Adult Males and Females With an Autism Spectrum Disorder.

BackgroundExisting research shows that adults with an autism spectrum disorder (ASD) are more vulnerable to develop overt psychosis. However, studies investigating (subclinical) psychotic experiences (PE) in ASD are scarce, and it is unknown if PE are accompanied with more distress in adults with ASD compared to the general population. This study examined lifetime PE and accompanying distress, momentary PE levels, and the impact of daily life stress and negative affect (NA) on momentary PE in males and females with ASD compared to controls.MethodsIn 50 adults with ASD (males N= 26, females N= 24) and 51 adults without ASD (males N= 26, females N= 25), the Community Assessment of Psychic Experiences (CAPE) was used to analyze group differences in frequency and distress of lifetime subclinical positive, negative, and depressive symptoms. The Experience Sampling Method (ESM) was used to measure momentary PE, NA, and stress (activity-related, event-related, and social stress) for 10 days. Multilevel analyses were conducted to test whether stress and NA were associated with momentary PE and whether these associations were modified by group or sex.ResultsAdults with ASD reported more lifetime CAPE negative and depressive symptoms, but similar levels of PE, than controls. Higher levels of accompanying distress were found in participants with ASD for each subscale. With respect to ESM momentary PE, higher levels were reported by adults with ASD and a stronger association between event-related stress and momentary PE was found compared to controls. This was not the case for NA, activity-related, and social stress. Overall, no significant differences between male and female outcomes were found.ConclusionAdults with ASD are more prone to encounter lifetime subclinical negative and depressive symptoms and accompanying distress compared to adults without ASD. Similar levels of lifetime PE in both groups were still accompanied with more distress in the ASD group. Furthermore, higher levels of ESM momentary PE were found in participants with ASD. Additionally, event-related stress may act as a risk factor for PE in both females and males with ASD, with a stronger risk-increasing effect than in their control counterparts.

Childhood adversity and psychosis: a systematic review of bio-psycho-social mediators and moderators.

The association between childhood adversity (CA) and psychosis has been extensively investigated in recent years. An increasing body of research has also focused on the mediating or moderating role of biological and psychological mechanisms, as well as other risk factors that might account for the link between CA and psychosis. We conducted a systematic search of the PsychINFO, Embase, Ovid, and Web of Science databases for original articles investigating the role of genetic vulnerabilities, environmental factors, psychological and psychopathological mechanisms in the association between CA and psychosis up to August 2019. We included studies with individuals at different stages of the psychosis continuum, from subclinical psychotic experiences to diagnosed disorders. From the 28 944 records identified, a total of 121 studies were included in this review. Only 26% of the studies identified met the criteria for methodological robustness. Overall, the current evidence suggests that CA may be associated with psychosis largely independently of genetic vulnerabilities. More consistent and robust evidence supports interaction between early and recent adversities, as well as the mediating role of attachment and mood symptoms, which is suggestive of an affective pathway between CA and psychosis across the continuum from subclinical experiences to diagnosable disorder. This review highlighted numerous methodological issues with the existing literature, including selection bias, heterogeneity of measurement instruments utilised, and lack of control for potential confounders. Future research should address these limitations to more accurately estimate mediation and moderation effects on the CA-psychosis association to inform the development of preventive interventions.

T21. DEVELOPMENT OF PROTEOMIC PREDICTION MODELS FOR OUTCOMES IN THE CLINICAL HIGH RISK STATE AND PSYCHOTIC EXPERIENCES IN ADOLESCENCE: MACHINE LEARNING ANALYSES IN TWO NESTED CASE-CONTROL STUDIES

BackgroundIndividuals at clinical high risk (CHR) of psychosis have an approximately 20% probability of developing psychosis within 2 years, as well as an associated risk of non-psychotic disorders and functional impairment. People with subclinical psychotic experiences (PEs) are also at risk of future psychotic and non-psychotic disorders and decreased functioning. It is difficult to accurately predict outcomes in individuals at risk of psychosis on the basis of symptoms alone. Biomarkers for accurate prediction of outcomes could inform the clinical management of this group.MethodsWe conducted two nested case-control studies.Study 1, a clinical high-risk (CHR) sample, was nested within the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) cohort study. The sample comprised 133 CHR participants who were followed clinically for up to 6 years, of whom 49 transitioned to psychosis and 84 did not.Study 2, a general population sample, was nested within the Avon Longitudinal Study of Parents and Children (ALSPAC). The sample comprised 121 participants who did not report psychotic experiences (PEs) at age 12, of whom 55 later reported PEs at age 18 and 66 did not.We employed discovery-based proteomic methods to analyse protein expression in baseline plasma samples in EU-GEI and age 12 plasma samples in ALSPAC using liquid chromatography mass spectrometry.Differential expression of quantified proteomic markers was determined by analyses of covariance (with false discovery rate of 5%) comparing expression levels for each marker between those who did not and did not develop psychosis in Study 1 (adjusting for age, gender, body mass index and years in education), and between those who did and did not develop PEs in Study 2 (adjusting for gender, body mass index and maternal social class).Support vector machine algorithms were used to develop models for prediction of transition vs. non-transition (as determined by the Comprehensive Assessment of At Risk Mental States) and poor vs. good functional outcome at 2 years in Study 1 (General Assessment of Functioning: Disability subscale score </=60 vs. >60). Similar algorithms were used to develop a model for prediction of PEs vs. no PEs at age 18 in Study 2 (as determined by the Psychosis Like Symptoms Interview).ResultsIn Study 1, 35 of 166 quantified proteins were significantly differentially expressed between CHR participants who did and did not develop psychosis. Functional enrichment analysis provided evidence for particular implication of the complement and coagulation cascade (false discovery rate-adjusted Fisher’s exact test p=2.23E-21). Using 65 clinical and 166 proteomic features a model demonstrated excellent performance for prediction of transition status (area under the receiver-operating curve [AUC] 0.96, positive predictive value [PPV] 83.0%, negative predictive value [NPV] 93.8%). A model based on the ten most predictive proteins accurately predicted transition status in training (AUC 0.96, PPV 87.5%, NPV 95.8%) and withheld data (AUC 0.92, PPV 88.9%, NPV 91.4%). A model using the same 65 clinical and 166 proteomic features predicted 2-year functional outcome with AUC 0.72 (PPV 67.6%, NPV 47.6%).In Study 2, 5 of 265 quantified proteins were significantly differentially expressed between participants who did and did not report PEs at age 18. A model using 265 proteomic features predicted PEs at age 18 with AUC 0.76 (PPV 69.1%, NPV 74.2%).DiscussionWith external validation, models incorporating proteomic data may contribute to improved prediction of clinical outcomes in individuals at risk of psychosis.