Characterising cognitive heterogeneity in individuals at clinical high-risk for psychosis: a cluster analysis with clinical and functional outcome prediction.

Schizophrenia is characterised by cognitive impairments that are already present during early stages, including in the clinical high-risk for psychosis (CHR-P) state and first-episode psychosis (FEP). Moreover, data suggest the presence of distinct cognitive subtypes during early-stage psychosis, with evidence for spared vs. impaired cognitive profiles that may be differentially associated with symptomatic and functional outcomes. Using cluster analysis, we sought to determine whether cognitive subgroups were associated with clinical and functional outcomes in CHR-P individuals. Data were available for 146 CHR-P participants of whom 122 completed a 6- and/or 12-month follow-up; 15 FEP participants; 47 participants not fulfilling CHR-P criteria (CHR-Ns); and 53 healthy controls (HCs). We performed hierarchical cluster analysis on principal components derived from neurocognitive and social cognitive measures. Within the CHR-P group, clusters were compared on clinical and functional variables and examined for associations with global functioning, persistent attenuated psychotic symptoms and transition to psychosis. Two discrete cognitive subgroups emerged across all participants: 45.9% of CHR-P individuals were cognitively impaired compared to 93.3% of FEP, 29.8% of CHR-N and 30.2% of HC participants. Cognitively impaired CHR-P participants also had significantly poorer functioning at baseline and follow-up than their cognitively spared counterparts. Specifically, cluster membership predicted functional but not clinical outcome. Our findings support the existence of distinct cognitive subgroups in CHR-P individuals that are associated with functional outcomes, with implications for early intervention and the understanding of underlying developmental processes.

Neuropsychological deficits in participants at clinical high risk for psychosis recruited from the community: relationships to functioning and clinical symptoms.

BACKGROUND: The current study examined the pattern of neurocognitive impairments in a community-recruited sample of clinical high-risk (CHR) participants and established relationships with psychosocial functioning. METHODS: CHR-participants (n = 108), participants who did not fulfil CHR-criteria (CHR-negatives) (n = 42) as well as a group of healthy controls (HCs) (n = 55) were recruited. CHR-status was assessed using the Comprehensive Assessment of At-Risk Mental States (CAARMS) and the Schizophrenia Proneness Instrument, Adult Version (SPI-A). The Brief Assessment of Cognition in Schizophrenia Battery (BACS) as well as tests for emotion recognition, working memory and attention were administered. In addition, role and social functioning as well as premorbid adjustment were assessed. RESULTS: CHR-participants were significantly impaired on the Symbol-Coding and Token-Motor task and showed a reduction in total BACS-scores. Moreover, CHR-participants were characterised by prolonged response times (RTs) in emotion recognition as well as by reductions in both social and role functioning, GAF and premorbid adjustments compared with HCs. Neurocognitive impairments in emotion recognition accuracy, emotion recognition RT, processing speed and motor speed were associated with several aspects of functioning explaining between 4% and 12% of the variance. CONCLUSION: The current data obtained from a community sample of CHR-participants highlight the importance of dysfunctions in motor and processing speed and emotion recognition RT. Moreover, these deficits were found to be related to global, social and role functioning, suggesting that neurocognitive impairments are an important aspect of sub-threshold psychotic experiences and a possible target for therapeutic interventions.

Prevalence and predictors of suicidality and non-suicidal self-harm among individuals at clinical high-risk for psychosis: Results from a community-recruited sample.

AIM: Suicidal thoughts and behaviours are prevalent in individuals with schizophrenia. However, research examining the prevalence and predictors of suicidality and self-harm in participants at clinical high-risk for psychosis (CHR-P) is limited and mostly focuses on help-seeking participants recruited through clinical pathways. The current study sought to assess the prevalence of suicidality and self-harm and identify predictors of current suicidal ideation in community-recruited CHR-P participants. METHODS: Data were available for 130 CHR-P participants, 15 participants with first-episode psychosis (FEP), 47 participants not fulfilling CHR-P criteria (CHR-Ns) and 53 healthy controls. Current and lifetime suicidality and self-harm were assessed using the Mini-International Neuropsychiatric Interview and the Comprehensive Assessment of At-Risk Mental States (CAARMS). Multivariable logistic regression analysis was used to determine predictors of current suicidal ideation in the CHR-P group. RESULTS: A considerable proportion of CHR-P participants disclosed current suicidal ideation (34.6%). Overall, FEP individuals were at greatest risk, with considerably high prevalence rates for current suicidal ideation (73.3%), lifetime self-harm behaviour (60.0%) and lifetime suicide attempt (60.0%). In the CHR-P sample, current suicidal ideation was predicted by lifetime suicide attempts, lower CAARMS severity, impaired social functioning and greater comorbidity. CONCLUSIONS: Our findings suggest that suicidality and self-harm are highly prevalent in community-recruited CHR-P and FEP individuals. Accordingly, these results highlight the importance of further research into the determinants of suicidality and self-harm during at-risk and early stages of psychosis, and the implementation of intervention strategies to reduce adverse outcomes in these populations.

The relationship between cognitive deficits and impaired short-term functional outcome in clinical high-risk for psychosis participants: A machine learning and modelling approach.

Poor functional outcomes are common in individuals at clinical high-risk for psychosis (CHR-P), but the contribution of cognitive deficits remains unclear. We examined the potential utility of cognitive variables in predictive models of functioning at baseline and follow-up with machine learning methods. Additional models fitted on baseline functioning variables were used as a benchmark to evaluate model performance. Data were available for 1) 146 CHR-P individuals of whom 118 completed a 6- and/or 12-month follow-up, 2) 47 participants not fulfilling CHR criteria (CHR-Ns) but displaying affective and substance use disorders and 3) 55 healthy controls (HCs). Predictors of baseline global assessment of functioning (GAF) scores were selected by L1-regularised least angle regression and then used to train classifiers to predict functional outcome in CHR-P individuals. In CHR-P participants, cognitive deficits together with clinical and functioning variables explained 41% of the variance in baseline GAF scores while cognitive variables alone explained 12%. These variables allowed classification of functional outcome with an average balanced accuracy (BAC) of 63% in both mixed- and cross-site models. However, higher accuracies (68%-70%) were achieved using classifiers fitted only on baseline functioning variables. Our findings suggest that cognitive deficits, alongside clinical and functioning variables, displayed robust relationships with impaired functioning in CHR-P participants at baseline and follow-up. Moreover, these variables allow for prediction of functional outcome. However, models based on baseline functioning variables showed a similar performance, highlighting the need to develop more accurate algorithms for predicting functional outcome in CHR-P participants.