Tracking Positive and Negative Symptom Improvement in First-Episode Schizophrenia Treated with Risperidone Using Individual-Level Functional Connectivity.

Background: To improve treatment outcomes of patients with schizophrenia, research efforts have focused on identifying brain-based markers of treatment response. Personal characteristics regarding disease-related behaviors likely stem from interindividual variability in the organization of brain functional systems. This study aimed to track dimension-specific changes in psychotic symptoms following risperidone treatment using individual-level functional connectivity (FC). Methods: A reliable cortical parcellation approach that accounts for individual heterogeneity in cortical functional anatomy was used to localize functional regions in a longitudinal cohort consisting of 42, drug-naive, first-episode schizophrenia (FES) patients at baseline and after 8 weeks of risperidone treatment. FC was calculated in individually specified brain regions and used to predict the baseline severity and improvement of positive and negative symptoms in FES. Results: Distinct sets of individual-specific FC were separately associated with the positive and negative symptom burden at baseline, which could be used to track the corresponding symptom resolution in FES patients following risperidone treatment. Between-network connections of the fronto-parietal network (FPN) contributed the most to predicting the positive symptom domain. A combination of between-network connections of the default mode network, FPN, and within-network connections of the FPN contributed markedly to the prediction model of negative symptoms. Conclusion: This novel study, which accounts for individual brain variation, takes a step toward establishing individual-specific theranostic biomarkers in schizophrenia. Impact statement This study revealed a theranostic marker for personalized medicine in schizophrenia and may aid in circuit-specific therapies for this disorder.