In young people at risk for psychosis, proteomic biomarkers may help to individualize prognosis, according to a study published online Aug. 26 in JAMA Psychiatry.
David Mongan, M.B., B.Ch., from the Royal College of Surgeons in Dublin, Ireland, and colleagues investigated whether proteomic biomarkers can predict transition to psychotic disorder in the clinical high-risk (CHR) state and adolescent psychotic experiences (PEs) in the general population. The analysis included data for patients participating in the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI; 133 participants at CHR [mean age, 22.6 years; 51.1 percent men]), of whom 36.8 percent developed psychosis and 63.2 percent did not. The analysis also included data from the general population participating in the Avon Longitudinal Study of Parents and Children (ALSPAC; 121 participants; 50.4 percent men), of whom 45.5 percent had PEs at age 18 years and 50.4 percent did not.
The researchers found that in the EU-GEI dataset, a model based on baseline clinical and proteomic data demonstrated excellent performance for prediction of transition outcome (area under the receiver operating characteristic curve [AUC], 0.95; positive predictive value [PPV], 75.0 percent; negative predictive value [NPV], 98.6 percent). Using the 10 most predictive proteins, a model accurately predicted transition status in training data (AUC, 0.99; PPV, 76.9 percent; NPV, 100 percent) and test data (AUC, 0.92; PPV, 81.8 percent; NPV, 96.8 percent). In the ALSPAC dataset, a model using proteomic data at age 12 years predicted PEs at age 18 years with an AUC of 0.74, a PPV of 67.8 percent, and an NPV of 75.8 percent.
“These findings implicate early dysregulation of the complement and coagulation cascade in the development of psychosis outcomes,” the authors write.
Two authors disclosed financial ties to the biopharmaceutical industry; several authors have patents related to a biomarker panel pending.