Structural and functional brain abnormalities in drug-naive, first-episode, and chronic patients with schizophrenia: A multimodal MRI study

Fengchun Wu, Yue Zhang, Yongzhe Yang, Xiaobing Lu, Ziyan Fang, Jianwei Huang, Lingyin Kong, Jun Chen, Yuping Ning, Xiaobo Li, Kai Wu

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Background: Structural and functional brain abnormalities in schizophrenia (SZ) have been widely reported. However, a few studies have investigated both structural and functional characteristics in SZ patients at different stages to understand the neuropathology of SZ. Methods: In this study, we recruited 44 first-episode drug-naive SZ (FESZ) patients, 44 medicated chronic SZ (CSZ) patients, and 56 normal controls (NCs) and acquired their structural and resting-state functional magnetic resonance imaging (MRI). We then made group comparisons on structural and functional characteristics, including regional gray matter volume (GMV), regional homogeneity, amplitude of low-frequency fluctuation, and degree centrality. A linear support vector machine (SVM) combined with a recursive feature elimination (RFE) algorithm was implemented to discriminate three groups. Results: Our results indicated that the regional GMV was significantly decreased in patients compared with that in NCs; CSZ patients have more diffused GMV decreases primarily involved in the frontal and temporal lobes when compared with FESZ patients. Both FESZ and CSZ patients showed significant functional alterations compared with NCs; when compared with FESZ patients, CSZ patients showed significant reductions in functional characteristics in several brain regions associated with auditory, visual processing, and sensorimotor functions. Moreover, a linear SVM combined with a RFE algorithm was implemented to discriminate three groups. The accuracies of the three classifiers were 79.80%, 83.16%, and 81.71%, respectively. The performance of classifiers in this study with multimodal MRI was better than that of previous discriminative analyses of SZ patients with single-modal MRI. Conclusion: Our findings bring new insights into the understanding of the neuropathology of SZ and contribute to stage-specific biomarkers in diagnosis and interventions of SZ.

Original languageEnglish (US)
Pages (from-to)2889-2904
Number of pages16
JournalNeuropsychiatric Disease and Treatment
Volume14
DOIs
StatePublished - 2018

All Science Journal Classification (ASJC) codes

  • Psychiatry and Mental health
  • Biological Psychiatry

Keywords

  • Classification
  • Multimodal MRI
  • SVM
  • Schizophrenia
  • Support vector machine

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