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Prediction of Cognitive Progression Due to Alzheimer's Disease in Normal Participants Based on Individual Default Mode Network Metabolic Connectivity Strength.
Zhang, Qi; Li, Fangjie; Wei, Min; Wang, Min; Wang, Luyao; Han, Ying; Jiang, Jiehui.
Afiliação
  • Zhang Q; School of Communication & Information Engineering, Shanghai University, Shanghai, China; School of Life Sciences, Shanghai University, Shanghai, China.
  • Li F; Shanghai University of Traditional Chinese Medicine, Shanghai, China.
  • Wei M; Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China.
  • Wang M; School of Life Sciences, Shanghai University, Shanghai, China.
  • Wang L; School of Life Sciences, Shanghai University, Shanghai, China.
  • Han Y; Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China; School of Biomedical Engineering, Hainan University, Haikou, China; Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China; National Clinical Research Center for Geriatric Diseases,
  • Jiang J; School of Life Sciences, Shanghai University, Shanghai, China. Electronic address: jiangjiehui@shu.edu.cn.
Article em En | MEDLINE | ID: mdl-38631552
ABSTRACT

BACKGROUND:

Predicting cognitive decline among individuals in the aging population who are already amyloid-ß (Aß) positive or tau positive poses clinical challenges. In Alzheimer's disease research, intra-default mode network (DMN) connections play a pivotal role in diagnosis. In this article, we propose metabolic connectivity within the DMN as a supplementary biomarker to the Aß, pathological tau, and neurodegeneration framework.

METHODS:

Extracting data from 1292 participants in the Alzheimer's Disease Neuroimaging Initiative, we collected paired T1-weighted structural magnetic resonance imaging and 18F-labeled-fluorodeoxyglucose positron emission computed tomography scans. Individual metabolic DMN networks were constructed, and metabolic connectivity (MC) strength in the DMN was assessed. In the cognitively unimpaired group, the Cox model identified cognitively unimpaired (MC+), high-risk participants, with Kaplan-Meier survival analyses and hazard ratios revealing the strength of MC's predictive performance. Spearman correlation analyses explored relationships between MC strength, and Aß, pathological tau, neurodegeneration biomarkers, and clinical scales. DMN standard uptake value ratio (SUVR) provided comparative insights in the analyses.

RESULTS:

Both MC strength and SUVR exhibited gradual declines with cognitive deterioration, displaying significant intergroup differences. Survival analyses indicated enhanced Aß and tau prediction with both metrics, with MC strength outperforming SUVR. Combined MC strength and Aß yielded optimal predictive performance (hazard ratio = 9.29), followed by MC strength and tau (hazard ratio = 8.92). Generally, the strength of MC's correlations with Aß, pathological tau, and neurodegeneration biomarkers exceeded SUVR.

CONCLUSIONS:

Individuals with normal cognition and disrupted DMN metabolic connectivity face an elevated risk of cognitive decline linked to Aß that precedes metabolic issues.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Progressão da Doença / Tomografia por Emissão de Pósitrons / Doença de Alzheimer / Rede de Modo Padrão Limite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Biol Psychiatry Cogn Neurosci Neuroimaging Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Imageamento por Ressonância Magnética / Progressão da Doença / Tomografia por Emissão de Pósitrons / Doença de Alzheimer / Rede de Modo Padrão Limite: Aged / Aged80 / Female / Humans / Male Idioma: En Revista: Biol Psychiatry Cogn Neurosci Neuroimaging Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China