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Disease Progression Patterns of Brain Morphology in Schizophrenia: More Progressed Stages in Treatment Resistance

  • Daichi Sone
  • , Alexandra Young
  • , Shunichiro Shinagawa
  • , Sakiko Tsugawa
  • , Yusuke Iwata
  • , Ryosuke Tarumi
  • , Kamiyu Ogyu
  • , Shiori Honda
  • , Ryo Ochi
  • , Karin Matsushita
  • , Fumihiko Ueno
  • , Nobuaki Hondo
  • , Akihiro Koreki
  • , Edgardo Torres-Carmona
  • , Wanna Mar
  • , Nathan Chan
  • , Teruki Koizumi
  • , Hideo Kato
  • , Keisuke Kusudo
  • , Vincenzo de Luca
  • Philip Gerretsen, Gary Remington, Mitsumoto Onaya, Yoshihiro Noda, Hiroyuki Uchida, Masaru Mimura, Masahiro Shigeta, Ariel Graff-Guerrero, Shinichiro Nakajima

Research output: Contribution to journalArticlepeer-review

Abstract

Background and Hypothesis: Given the heterogeneity and possible disease progression in schizophrenia, identifying the neurobiological subtypes and progression patterns in each patient may lead to novel biomarkers. Here, we adopted data-driven machine-learning techniques to identify the progression patterns of brain morphological changes in schizophrenia and investigate the association with treatment resistance. Study Design: In this cross-sectional multicenter study, we included 177 patients with schizophrenia, characterized by treatment response or resistance, with 3D T1-weighted magnetic resonance imaging. Cortical thickness and subcortical volumes calculated by FreeSurfer were converted into z scores using 73 healthy controls data. The Subtype and Stage Inference (SuStaIn) algorithm was used for unsupervised machinelearning analysis. Study Results: SuStaIn identified 3 different subtypes: (1) subcortical volume reduction (SC) type (73 patients), in which volume reduction of subcortical structures occurs first and moderate cortical thinning follows, (2) globus pallidus hypertrophy and cortical thinning (GP-CX) type (42 patients), in which globus pallidus hypertrophy initially occurs followed by progressive cortical thinning, and (3) cortical thinning (pure CX) type (39 patients), in which thinning of the insular and lateral temporal lobe cortices primarily happens. The remaining 23 patients were assigned to baseline stage of progression (no change). SuStaIn also found 84 stages of progression, and treatment-resistant schizophrenia showed significantly more progressed stages than treatment-responsive cases (P = .001). The GP-CX type presented earlier stages than the pure CX type (P = .009). Conclusions: The brain morphological progressions in schizophrenia can be classified into 3 subtypes, and treatment resistance was associated with more progressed stages, which may suggest a novel biomarker.

Original languageEnglish
Pages (from-to)393-402
Number of pages10
JournalSchizophrenia Bulletin
Volume50
Issue number2
DOIs
Publication statusPublished - 2024 Mar 1

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • brain morphology
  • disease progression
  • machine learning
  • magnetic resonance imaging
  • schizophrenia

ASJC Scopus subject areas

  • Psychiatry and Mental health

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