Topographical Overlapping of the Amyloid-β and Tau Pathologies in the Default Mode Network Predicts Alzheimer's Disease with Higher Specificity. Academic Article uri icon

Overview

abstract

  • BACKGROUND: While amyloid-β (Aβ) plaques and tau tangles are the well-recognized pathologies of Alzheimer's disease (AD), they are more often observed in healthy individuals than in AD patients. This discrepancy makes it extremely challenging to utilize these two proteinopathies as reliable biomarkers for the early detection as well as later diagnosis of AD. OBJECTIVE: We hypothesize and provide preliminary evidence that topographically overlapping Aβ and tau within the default mode network (DMN) play more critical roles in the underlying pathophysiology of AD than each of the tau and/or Aβ pathologies alone. METHODS: We used our newly developed quantification methods and publicly available neuroimaging data from 303 individuals to provide preliminary evidence of our hypothesis. RESULTS: We first showed that the probability of observing overlapping Aβ and tau is significantly higher within than outside the DMN. We then showed evidence that using Aβ and tau overlap can increase the reliability of the prediction of healthy individuals converting to mild cognitive impairment (MCI) and to a lesser degree converting from MCI to AD. Finally, we provided evidence that while the initial accumulations of Aβ and tau seems to be started independently in the healthy participants, the accumulations of the two pathologies interact in the MCI and AD groups. CONCLUSION: These findings shed some light on the complex pathophysiology of AD and suggest that overlapping Aβ and tau pathologies within the DMN might be a more reliable biomarker of AD for early detection and later diagnosis of the disease.

publication date

  • January 1, 2021

Research

keywords

  • Alzheimer Disease
  • Amyloid beta-Peptides
  • Default Mode Network
  • tau Proteins

Identity

Scopus Document Identifier

  • 85114403449

Digital Object Identifier (DOI)

  • 10.3233/JAD-210419

PubMed ID

  • 34219729

Additional Document Info

volume

  • 83

issue

  • 1