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Altered Regional Cerebral Blood Flow and Brain Function Across the Alzheimer's Disease Spectrum: A Potential Biomarker

Authors
  • Zhang, Qianqian1
  • Wang, Qing1
  • He, Cancan1
  • Fan, Dandan1
  • Zhu, Yao1
  • Zang, Feifei1
  • Tan, Chang1
  • Zhang, Shaoke1
  • Shu, Hao1
  • Zhang, Zhijun1, 2, 3
  • Feng, Haixia4
  • Wang, Zan1
  • Xie, Chunming1, 2, 3
  • 1 Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing , (China)
  • 2 Neuropsychiatric Institute, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing , (China)
  • 3 The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing , (China)
  • 4 Department of Nursing, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing , (China)
Type
Published Article
Journal
Frontiers in Aging Neuroscience
Publisher
Frontiers Media SA
Publication Date
Feb 22, 2021
Volume
13
Identifiers
DOI: 10.3389/fnagi.2021.630382
Source
Frontiers
Keywords
Disciplines
  • Neuroscience
  • Original Research
License
Green

Abstract

Objective: To investigate variation in the characteristics of regional cerebral blood flow (rCBF), brain activity, and intrinsic functional connectivity (FC) across the Alzheimer's disease spectrum (ADS). Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC). All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests. Additionally, the normalized CBF, regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) of individual subjects were compared in the ADS. Moreover, the changes in intrinsic FC were investigated across the ADS using the abnormal rCBF regions as seeds and behavioral correlations. Finally, a support-vector classifier model of machine learning was used to distinguish individuals with ADS from HC. Results: Compared to the HC subjects, patients with AD showed the poorest level of rCBF in the left precuneus (LPCUN) and right middle frontal gyrus (RMFG) among all participants. In addition, there was a significant decrease in the ALFF in the bilateral posterior cingulate cortex (PCC) and ReHo in the right PCC. Moreover, RMFG- and LPCUN-based FC analysis revealed that the altered FCs were primarily located in the posterior brain regions. Finally, a combination of altered rCBF, ALFF, and ReHo in posterior cingulate cortex/precuneus (PCC/PCUN) showed a better ability to differentiate ADS from HC, AD from SCD and MCI, but not MCI from SCD. Conclusions: The study demonstrated the significance of an altered rCBF and brain activity in the early stages of ADS. These findings, therefore, present a potential diagnostic neuroimaging-based biomarker in ADS. Additionally, the study provides a better understanding of the pathophysiology of AD.

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