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Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance network analysis.
Han, Shaoqiang; Xue, Kangkang; Chen, Yuan; Xu, Yinhuan; Li, Shuying; Song, Xueqin; Guo, Hui-Rong; Fang, Keke; Zheng, Ruiping; Zhou, Bingqian; Chen, Jingli; Wei, Yarui; Zhang, Yong; Cheng, Jingliang.
Afiliação
  • Han S; Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Xue K; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.
  • Chen Y; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.
  • Xu Y; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.
  • Li S; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.
  • Song X; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.
  • Guo HR; Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China.
  • Fang K; Henan Engineering Research Center of Brain Function Development and Application, Zhengzhou, China.
  • Zheng R; Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Zhou B; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.
  • Chen J; Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.
  • Wei Y; Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.
  • Zhang Y; Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.
  • Cheng J; Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.
Psychol Med ; : 1-12, 2023 Mar 06.
Article em En | MEDLINE | ID: mdl-36876493
BACKGROUND: Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders. METHODS: Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed. RESULTS: Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network. CONCLUSIONS: These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Psychol Med Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Psychol Med Ano de publicação: 2023 Tipo de documento: Article