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Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure.
Ye, Hua; Zalesky, Andrew; Lv, Jinglei; Loi, Samantha M; Cetin-Karayumak, Suheyla; Rathi, Yogesh; Tian, Ye; Pantelis, Christos; Di Biase, Maria A.
Affiliation
  • Ye H; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia.
  • Zalesky A; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia.
  • Lv J; Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia.
  • Loi SM; School of Biomedical Engineering & Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia.
  • Cetin-Karayumak S; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia.
  • Rathi Y; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
  • Tian Y; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
  • Pantelis C; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
  • Di Biase MA; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia.
Schizophr Bull ; 47(4): 1156-1167, 2021 07 08.
Article in En | MEDLINE | ID: mdl-33693887
ABSTRACT

INTRODUCTION:

Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia.

METHODS:

A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data.

RESULTS:

Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05).

CONCLUSION:

Symptom network structure varies over the course of schizophrenia symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Schizophrenia / Disease Progression / White Matter Type of study: Diagnostic_studies / Prognostic_studies Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Schizophr Bull Year: 2021 Document type: Article Affiliation country: Australia Publication country: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Schizophrenia / Disease Progression / White Matter Type of study: Diagnostic_studies / Prognostic_studies Limits: Adolescent / Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Schizophr Bull Year: 2021 Document type: Article Affiliation country: Australia Publication country: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA