An opportunity for primary prevention research in psychotic disorders

Elliot S. Gershon, S. Hong Lee, Xuan Zhou, John A. Sweeney, Carol Tamminga, Godfrey A. Pearlson, Brett A. Clementz, Matcheri S. Keshavan, Ney Alliey-Rodriguez, Matthew Hudgens-Haney, Sarah K. Keedy, David C. Glahn, Huma Asif, Rebekka Lencer, S. Kristian Hill

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


An opportunity has opened for research into primary prevention of psychotic disorders, based on progress in endophenotypes, genetics, and genomics. Primary prevention requires reliable prediction of susceptibility before any symptoms are present. We studied a battery of measures where published data supports abnormalities of these measurements prior to appearance of initial psychosis symptoms. These neurobiological and behavioral measurements included cognition, eye movement tracking, Event Related Potentials, and polygenic risk scores. They generated an acceptably precise separation of healthy controls from outpatients with a psychotic disorder. Methods: The Bipolar and Schizophrenia Network on Intermediate Phenotypes (B-SNIP) measured this battery in an ancestry-diverse series of consecutively recruited adult outpatients with a psychotic disorder and healthy controls. Participants include all genders, 16 to 50 years of age, 261 with psychotic disorders (Schizophrenia (SZ) 109, Bipolar with psychosis (BPP) 92, Schizoaffective disorder (SAD) 60), 110 healthy controls. Logistic Regression, and an extension of the Linear Mixed Model to include analysis of pairwise interactions between measures (Environmental kernel Relationship Matrices (ERM)) with multiple iterations, were performed to predict case-control status. Each regression analysis was validated with four-fold cross-validation. Results and conclusions: Sensitivity, specificity, and Area Under the Curve of Receiver Operating Characteristic of 85%, 62%, and 86%, respectively, were obtained for both analytic methods. These prediction metrics demonstrate a promising diagnostic distinction based on premorbid risk variables. There were also statistically significant pairwise interactions between measures in the ERM model. The strong prediction metrics of both types of analytic model provide proof-of-principle for biologically-based laboratory tests as a first step toward primary prevention studies. Prospective studies of adolescents at elevated risk, vs. healthy adolescent controls, would be a next step toward development of primary prevention strategies.

Original languageEnglish
Pages (from-to)433-439
Number of pages7
JournalSchizophrenia Research
StatePublished - May 2022
Externally publishedYes


  • Cognition
  • Diagnostic tests
  • Event-related potentials
  • Eye movements
  • Polygenic risk score
  • Prediction metrics
  • Prevention
  • Psychosis


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