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Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer's Disease.
Zhang, Jingwen; Liu, Qing; Zhang, Haorui; Dai, Michelle; Song, Qianqian; Yang, Defu; Wu, Guorong; Chen, Minghan.
Afiliação
  • Zhang J; Department of Computer Science, Wake Forest University, Winston-Salem, NC, USA.
  • Liu Q; Department of Mathematics, University of North Georgia, Oakwood, GA, USA.
  • Zhang H; Department of Mathematics, University of North Georgia, Oakwood, GA, USA.
  • Dai M; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Song Q; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
  • Yang D; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Wu G; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Chen M; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
J Alzheimers Dis ; 95(3): 1201-1219, 2023.
Article em En | MEDLINE | ID: mdl-37661878
BACKGROUND: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-ß (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive. OBJECTIVE: To disentangle the massive heterogeneities in Alzheimer's disease (AD) progressions and identify vulnerable/critical brain regions to AD pathology. METHODS: In this work, we characterized the interaction of AT[N] biomarkers and their propagation across brain networks using a novel bistable reaction-diffusion model, which allows us to establish a new systems biology underpinning of AD progression. We applied our model to large-scale longitudinal neuroimages from the ADNI database and studied the systematic vulnerability and criticality of brains. RESULTS: Our model yields long term prediction that is statistically significant linear correlated with temporal imaging data, produces clinically consistent risk prediction, and captures the Braak-like spreading pattern of AT[N] biomarkers in AD development. CONCLUSIONS: Our major findings include (i) tau is a stronger indicator of regional risk compared to amyloid, (ii) temporal lobe exhibits higher vulnerability to AD-related pathologies, (iii) proposed critical brain regions outperform hub nodes in transmitting disease factors across the brain, and (iv) comparing the spread of neuropathological burdens caused by amyloid-ß and tau diffusions, disruption of metabolic balance is the most determinant factor contributing to the initiation and progression of AD.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article