Alzheimer’s Research & Therapy (Sep 2020)

Principal components of tau positron emission tomography and longitudinal tau accumulation in Alzheimer’s disease

  • Hanna Cho,
  • Min Seok Baek,
  • Hye Sun Lee,
  • Jae Hoon Lee,
  • Young Hoon Ryu,
  • Chul Hyoung Lyoo

DOI
https://doi.org/10.1186/s13195-020-00685-4
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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Abstract Background We aimed to investigate the clinical correlates of principal components (PCs) of tau positron emission tomography (PET) and their predictability for longitudinal changes in tau accumulation in Alzheimer’s disease (AD). Methods We enrolled 272 participants who underwent two PET scans [18F-flortaucipir for tau and 18F-florbetaben for amyloid-β (Aβ)], brain magnetic resonance imaging, and neuropsychological tests as baseline assessments. Among them, 187 participants underwent the same follow-up assessments after an average of 2 years. Using Aβ-positive AD dementia-specific PCs obtained from the baseline scans of 56 Aβ-positive patients with AD dementia, we determined the expression of the first two PCs (PC1 and PC2) in all participants. We assessed the correlation of PC expression with baseline clinical characteristics and tau accumulation rates. Moreover, we investigated the predictability of PCs for the longitudinal tau accumulation in training and test sets. Results PC1 corresponded to the tau distribution pattern in AD, while the two PC2 extremes reflected the parietal or temporal predominance of tau distribution. PC1 expression increased with tau burden and decreased with cognitive impairment, while PC2 expression decreased with advanced age and visuospatial and attention function deterioration. The tau accumulation rate was positively correlated with PC1 expression (greater tau burden) and negatively correlated with PC2 expression (temporal predominance). A regression model using both PCs could predict longitudinal changes in the tau burden (intraclass correlation coefficient = 0.775, R 2 = 0.456 in test set). Conclusions PC analysis of tau PET could be useful for evaluating disease progression, characterizing the tau distribution pattern, and predicting longitudinal tau accumulation.

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