Clustering of antipsychotic-naïve patients with schizophrenia based on functional connectivity from resting-state electroencephalography

Eur Arch Psychiatry Clin Neurosci. 2023 Dec;273(8):1785-1796. doi: 10.1007/s00406-023-01550-9. Epub 2023 Feb 2.

Abstract

Schizophrenia is associated with aberrations in the Default Mode Network (DMN), but the clinical implications remain unclear. We applied data-driven, unsupervised machine learning based on resting-state electroencephalography (rsEEG) functional connectivity within the DMN to cluster antipsychotic-naïve patients with first-episode schizophrenia. The identified clusters were investigated with respect to psychopathological profile and cognitive deficits. Thirty-seven antipsychotic-naïve, first-episode patients with schizophrenia (mean age 24.4 (5.4); 59.5% males) and 97 matched healthy controls (mean age 24.0 (5.1); 52.6% males) underwent assessments of rsEEG, psychopathology, and cognition. Source-localized, frequency-dependent functional connectivity was estimated using Phase Lag Index (PLI). The DMN-PLI was factorized for each frequency band using principal component analysis. Clusters of patients were identified using a Gaussian mixture model and neurocognitive and psychopathological profiles of identified clusters were explored. We identified two clusters of patients based on the theta band (4-8 Hz), and two clusters based on the beta band (12-30 Hz). Baseline psychopathology could predict theta clusters with an accuracy of 69.4% (p = 0.003), primarily driven by negative symptoms. Five a priori selected cognitive functions conjointly predicted the beta clusters with an accuracy of 63.6% (p = 0.034). The two beta clusters displayed higher and lower DMN connectivity, respectively, compared to healthy controls. In conclusion, the functional connectivity within the DMN provides a novel, data-driven means to stratify patients into clinically relevant clusters. The results support the notion of biological subgroups in schizophrenia and endorse the application of data-driven methods to recognize pathophysiological patterns at earliest stage of this syndrome.

Keywords: Antipsychotic-naïve first-episode schizophrenia; Clustering; Cognition; Functional connectivity; Psychopathology; Resting-state electroencephalography.

MeSH terms

  • Adult
  • Antipsychotic Agents* / pharmacology
  • Antipsychotic Agents* / therapeutic use
  • Brain / diagnostic imaging
  • Brain Mapping
  • Cluster Analysis
  • Cognition Disorders* / psychology
  • Electroencephalography
  • Female
  • Humans
  • Magnetic Resonance Imaging
  • Male
  • Schizophrenia* / diagnostic imaging
  • Schizophrenia* / drug therapy
  • Young Adult

Substances

  • Antipsychotic Agents