Background

Most studies of neurocognitive functioning in Clinical High Risk (CHR) cohorts have examined group averages, likely concealing heterogeneous subgroups. We aimed to identify neurocognitive subgroups and to explore associated outcomes.

Methods

Data were acquired from 324 participants (mean age 18.4) in the first phase of the North American Prodrome Longitudinal Study (NAPLS-1), a multi-site consortium following individuals for up to 2 1/2 years. We applied Ward's method for hierarchical clustering data to 8 baseline neurocognitive measures, in 166 CHR individuals, 49 non-CHR youth with a family history of psychosis, and 109 healthy controls. We tested whether cluster membership was associated with conversion to psychosis, social and role functioning, and follow-up diagnosis. Analyses were repeated after data were clustered based on independently developed clinical decision rules.

Results

Four neurocognitive clusters were identified: Significantly Impaired (n = 33); Mildly Impaired (n = 82); Normal (n = 145) and High (n = 64). The Significantly Impaired subgroup demonstrated the largest deviations on processing speed and memory tasks and had a conversion rate of 58%, a 40% chance of developing a schizophrenia spectrum diagnosis (compared to 24.4% in the Mildly Impaired, and 10.3% in the other two groups combined), and significantly worse functioning at baseline and 12-months. Data clustered using clinical decision rules yielded similar results, pointing to high convergent validity.

Conclusion

Neurocognitive profiles vary substantially in their severity and are associated with diagnostic and functional outcome, underscoring neurocognition as a predictor of illness outcomes. These findings, if replicated, are a first step toward personalized treatment for individuals at-risk for psychosis.

The MATRICS Consensus Cognitive Battery (MCCB) fills a significant need for a standardized battery of cognitive tests to use in clinical trials for schizophrenia in adults aged 20-59. A need remains, however, to develop norms for younger individuals, who also show elevated risks for schizophrenia. Toward this end, we assessed performance in healthy adolescents. Baseline MCCB, reading and IQ data were obtained from healthy controls (ages 12-19) participating in two concurrent NIMH-funded studies: North American Prodromal Longitudinal Study phase 2 (NAPLS-2; n=126) and Boston Center for Intervention Development and Applied Research (CIDAR; n=13). All MCCB tests were administered except the Managing Emotions subtest from the Mayer-Salovey-Caruso Emotional Intelligence Test. Data were collected from 8 sites across North America. MCCB scores were presented in four 2-year age cohorts as T-scores for each test and cognitive domain, and analyzed for effects of age and sex. Due to IQ differences between age-grouped subsamples, IQ served as a covariate in analyses. Overall and sex-based raw scores for individual MCCB tests are presented for each age-based cohort. Adolescents generally showed improvement with age in most MCCB cognitive domains, with the clearest linear trends in Attention/Vigilance and Working Memory. These control data show that healthy adolescence is a dynamic period for cognitive development that is marked by substantial improvement in MCCB performance through the 12-19 age range. They also provide healthy comparison raw scores to facilitate clinical evaluations of adolescents, including those at risk for developing psychiatric disorders such as schizophrenia-related conditions.