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Author:

Zhang, Baiwen (Zhang, Baiwen.) | Lin, Lan (Lin, Lan.) | Wu, Shuicai (Wu, Shuicai.) (Scholars:吴水才) | Al-Masqari, Zakarea H. M. A. (Al-Masqari, Zakarea H. M. A..)

Indexed by:

Scopus SCIE PubMed

Abstract:

Alzheimer's disease (AD) is a disease of a heterogeneous nature, which can be disentangled by exploring the characteristics of each AD subtype in the brain structure, neuropathology, and cognition. In this study, a total of 192 AD and 228 cognitively normal (CN) subjects were obtained from the Alzheimer's disease Neuroimaging Initiative database. Based on the cortical thickness patterns, the mixture of experts method (MOE) was applied to the implicit model spectrum of transforms lined with each AD subtype, then their neuropsychological and neuropathological characteristics were analyzed. Furthermore, the piecewise linear classifiers composed of each AD subtype and CN were resolved, and each subtype was comprehensively explained. The following four distinct AD subtypes were discovered: bilateral parietal, frontal, and temporal atrophy AD subtype (occipital sparing AD subtype (OSAD), 29.2%), left temporal dominant atrophy AD subtype (LTAD, 22.4%), minimal atrophy AD subtype (MAD, 16.1%), and diffuse atrophy AD subtype (DAD, 32.3%). These four subtypes display their own characteristics in atrophy pattern, cognition, and neuropathology. Compared with the previous studies, our study found that some AD subjects showed obvious asymmetrical atrophy in left lateral temporal-parietal cortex, OSAD presented the worst cerebrospinal fluid levels, and MAD had the highest proportions of APOE E4 and APOE E2. The subtype characteristics were further revealed from the aspect of the model, making it easier for clinicians to understand. The results offer an effective support for individual diagnosis and prognosis.

Keyword:

neuropathology atrophy subtypes cortical thickness mixture of experts structural magnetic resonance imaging Alzheimer's disease neuropsychology

Author Community:

  • [ 1 ] [Zhang, Baiwen]Beijing Univ Technol, Fac Environm & Life Sci, Dept Biomed Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Lin, Lan]Beijing Univ Technol, Fac Environm & Life Sci, Dept Biomed Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Wu, Shuicai]Beijing Univ Technol, Fac Environm & Life Sci, Dept Biomed Engn, Beijing 100124, Peoples R China
  • [ 4 ] [Al-Masqari, Zakarea H. M. A.]Beijing Univ Technol, Fac Environm & Life Sci, Dept Biomed Engn, Beijing 100124, Peoples R China
  • [ 5 ] [Zhang, Baiwen]Beijing Univ Technol, Beijing Int Base Sci & Technol Cooperat, Intelligent Physiol Measurement & Clin Translat, Beijing 100124, Peoples R China
  • [ 6 ] [Lin, Lan]Beijing Univ Technol, Beijing Int Base Sci & Technol Cooperat, Intelligent Physiol Measurement & Clin Translat, Beijing 100124, Peoples R China
  • [ 7 ] [Wu, Shuicai]Beijing Univ Technol, Beijing Int Base Sci & Technol Cooperat, Intelligent Physiol Measurement & Clin Translat, Beijing 100124, Peoples R China
  • [ 8 ] [Al-Masqari, Zakarea H. M. A.]Beijing Univ Technol, Beijing Int Base Sci & Technol Cooperat, Intelligent Physiol Measurement & Clin Translat, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Lin, Lan]Beijing Univ Technol, Fac Environm & Life Sci, Dept Biomed Engn, Beijing 100124, Peoples R China;;[Lin, Lan]Beijing Univ Technol, Beijing Int Base Sci & Technol Cooperat, Intelligent Physiol Measurement & Clin Translat, Beijing 100124, Peoples R China

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Source :

BRAIN SCIENCES

Year: 2021

Issue: 2

Volume: 11

3 . 3 0 0

JCR@2022

ESI Discipline: NEUROSCIENCE & BEHAVIOR;

ESI HC Threshold:71

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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