Schizophrenia-like topological changes in the structural connectome of individuals with subclinical psychotic experiences

Mark Drakesmith*, Karen Caeyenberghs, Anirban Dutt, Stanley Zammit, Christopher John Evans, Abraham Reichenberg, Glyn Lewis, Anthony S. David, Derek K. Jones

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

38 Citations (Scopus)
207 Downloads (Pure)

Abstract

Schizophrenia is often regarded as a "dysconnectivity" disorder and recent work using graph theory has been used to better characterize dysconnectivity of the structural connectome in schizophrenia. However, there are still little data on the topology of connectomes in less severe forms of the condition. Such analysis will identify topological markers of less severe disease states and provide potential predictors of further disease development. Individuals with psychotic experiences (PEs) were identified from a population-based cohort without relying on participants presenting to clinical services. Such individuals have an increased risk of developing clinically significant psychosis. 123 individuals with PEs and 125 controls were scanned with diffusion-weighted MRI. Whole-brain structural connectomes were derived and a range of global and local GT-metrics were computed. Global efficiency and density were significantly reduced in individuals with PEs. Local efficiency was reduced in a number of regions, including critical network hubs. Further analysis of functional subnetworks showed differential impairment of the default mode network. An additional analysis of pair-wise connections showed no evidence of differences in individuals with PEs. These results are consistent with previous findings in schizophrenia. Reduced efficiency in critical core hubs suggests the brains of individuals with PEs may be particularly predisposed to dysfunction. The absence of any detectable effects in pair-wise connections illustrates that, at less severe stages of psychosis, white-matter alterations are subtle and only manifest when examining network topology. This study indicates that topology could be a sensitive biomarker for early stages of psychotic illness.

Original languageEnglish
Pages (from-to)2629-2643
Number of pages15
JournalHuman Brain Mapping
Volume36
Issue number7
Early online date2 Apr 2015
DOIs
Publication statusPublished - 1 Jul 2015

Keywords

  • ALSPAC
  • Birth cohort
  • Connectomics
  • Diffusion MRI
  • Epidemiology
  • Graph theory
  • Network efficiency
  • Neuropsychiatry
  • Psychosis
  • Psychosis risk
  • Psychotic experiences
  • Schizophrenia
  • Structural connectivity
  • Tractography

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