Lecture – Prediction and Prevention of Psychosis in At-Risk Youth

Available with English captions.

Presented by Tyrone D. Cannon, PhD, Yale University – Visiting Scholar Series

Currently, clinicians can use interventions that can target the symptoms and functional impairments associated with psychosis. Yet, many clinicians and researchers are working on ways to prevent psychosis or address worsening symptoms. Much of this work is focused on helping young people who are at high risk for psychosis.

In this lecture, Cannon asserts that identifying predictors and understanding the brain mechanisms underlying the onset of psychosis are critical for the development of targeted preemptive interventions. Cannon is the Clark L. Hull Professor and Chair of the Department of Psychology at Yale University.

He explains that multivariate models have achieved high levels of predictive accuracy when applied to clinical high-risk for psychosis samples. These models include risk factors from clinical, demographic, neurocognitive, and psychosocial assessments. Cannon reports that an individualized risk calculator is available to scale the risk for certain cases. This calculator could aid in clinical decision making and drug trial design.

To show the value of these models, Cannon shares findings from the North American Prodrome Longitudinal Study (NAPLS). The study uses the CHR-P paradigm for case determination.

Watch now to learn more about:

  • The clinical high-risk for psychosis research paradigm
  • How clinical high-risk for psychosis (CHR-P) syndrome is diagnosed
  • Risk prediction and the NAPLS psychosis risk calculator
  • Structural and functional brain changes that precede and predict onset of psychosis
  • Future areas of study into psychosis detection and prevention

Cannon explains that at-risk individuals who convert to psychosis show elevated levels of proinflammatory cytokines. They also show disrupted cerebello-thalamo-cortical functional connectivity at baseline, compared with those who do not convert. Also, converters show a steeper rate of gray matter reduction, most prominent in the prefrontal cortex. This, in turn, is predicted by higher levels of inflammatory markers at baseline.

According to Cannon, these findings encourage further work to identify novel targets for interventions related to neuroplasticity and neuroinflammation. Specifically, some of this work will focus on understanding whether changes in markers of inflammation or NMDA-dependent plasticity precede and predict changes in psychosis-relevant brain connectivity.

Future studies will examine whether biomarkers of this sort could be used to improve prediction of psychosis. Studies will also determine if these biomarkers could select interventions that target mechanisms that may be relevant to specific cases or subgroups of cases.