Dynamic functional connectivity and its anatomical substrate reveal treatment outcome in first-episode drug-naïve schizophrenia

Abstract

Convergent evidence has suggested a significant effect of antipsychotic exposure on brain structure and function in patients with schizophrenia, yet the characteristics of favorable treatment outcome remains largely unknown. In this work, we aimed to examine how large-scale brain networks are modulated by antipsychotic treatment, and whether the longitudinal changes could track the improvements of psychopathologic scores. Thirty-four patients with first-episode drug-naïve schizophrenia and 28 matched healthy controls were recruited at baseline from Shanghai Mental Health Center. After 8 weeks of antipsychotic treatment, 24 patients were re-scanned. Through a systematical dynamic functional connectivity (dFC) analysis, we investigated the schizophrenia-related intrinsic alterations of dFC at baseline, followed by a longitudinal study to examine the influence of antipsychotic treatment on these abnormalities by comparing patients at baseline and follow-up. A structural connectivity (SC) association analysis was further carried out to investigate longitudinal anatomical changes that underpin the alterations of dFC. We found a significant symptomatic improvement-related increase in the occurrence of a dFC state characterized by stronger inter-network integration. Furthermore, symptom reduction was correlated with increased FC variability in a unique connectomic signature, particularly in the connections within the default mode network and between the auditory, cognitive control, and cerebellar network to other networks. Additionally, we observed that the SC between the superior frontal gyrus and medial prefrontal cortex was decreased after treatment, suggesting a relaxation of normal constraints on dFC. Taken together, these findings provide new evidence to extend the dysconnectivity hypothesis in schizophrenia from static to dynamic brain network. Moreover, our identified neuroimaging markers tied to the neurobiology of schizophrenia could be used as potential indicators in predicting the treatment outcome of antipsychotics.

Fig. 1. Dynamic functional connectivity patterns and association with psychosis symptoms.

A Five discrete dynamic functional connectivity patterns across all groups. The percentage of occurrences is listed above each cluster centroid. The color bar represents z values of functional connectivity (FC). B Differences in state occurrences between baseline schizophrenia patient (SZ_b) and healthy control (HC) groups. C Group differences in state occurrences between post-treatment (SZ_p) and paired baseline patients (SZ_bp). D Associations between changed occurrences of the State 3 and improved psychosis symptoms after treatment. **P < 0.01, FDR-corrected.

Fig. 2. The connectomic signature and association with psychosis symptoms.

A, B The functional connectomic signature was identified by using the NBS at baseline (SZ_b < HC). C Group differences in FC variability of this signature. D Associations between FC variability and psychosis symptoms. ***P < 0.001, ^★P = 0.058, FDR-corrected.

Fig. 3. Associations between altered FC variability of intra- and inter-RSNs and relief of psychosis symptoms.

Significance, P < 0.05, FDR-corrected.

Fig. 4. Structural connectivity association analyses.

A Spatial maps of two components (SFG and MPFC). B Differences in number of diffusion streamlines in patients between baseline (SZ_p) and follow-up (SZ_bp). C Decreased number of streamlines between the SFG and MPFC were marginally negatively correlated with decreased PANSS scores in patients after treatment. D Relationship between FC variability and number of streamlines in each groups. **P < 0.01. SFG = superior frontal gyrus; MPFC = medial prefrontal cortex.