Functional Coupling and Longitudinal Outcome Prediction in First-Episode Psychosis

Abstract

Background

Clinical outcomes following the first episode of psychosis (FEP) are highly heterogeneous across patients. The identification of prognostic biomarkers would greatly facilitate personalized treatments. Patients with psychosis often display brainwide disruptions of interregional functional coupling (FC), with some being linked to symptom severity and remission. Thus, FC may have prognostic potential for people experiencing psychosis.

Methods

Fifty-five antipsychotic-naïve patients with FEP (51% female, ages 15–25 years) were randomized to receive either antipsychotic or placebo tablets for 6 months alongside psychosocial interventions. Functional magnetic resonance imaging was conducted at baseline and after 3 months to evaluate whether baseline FC or 3-month change in FC could predict 6- and 12-month changes in symptoms and functioning, quantified using the Brief Psychiatric Rating Scale and the Social and Occupational Functioning Assessment Scale, respectively. We considered 3 different cross-validated prediction algorithms: 1) connectome-based predictive modeling, 2) kernel ridge regression, and 3) multilayer meta-matching. Each prediction model comprised 35 to 49 individuals.

Results

All models showed poor performance in predicting patients’ 6- and 12-month changes in symptoms and functioning (all r_mean < 0.3), and no model achieved significance via permutation testing (all p > .05).

Conclusions

Our findings suggest that brainwide measures of FC may not be suitable for predicting extended clinical outcomes over a 6- to 12-month period in patients with FEP.