Widespread accumulation of β-amyloid plaques and tau neurofibrillary tangles are neuropathologic hallmarks of MCI and AD.
Early hypotheses focused on β-amyloid deposition as a trigger of AD, while associated tau pathology with later events leading to neuronal loss.
Recent studies support an alternate hypothesis that accumulation of β-amyloid and tau are coordinated and parallel events over the course of disease progression.
Pattern of β-amyloid (top) and tau (bottom) pathology progression.
To explore the complex spatiotemporal relationship between β-amyloid, tau, and cognition, we introduce a new method called Canonical Distance Correlation Analysis (CDCA).
The CDCA employs the concepts of distance-correlations and distance-induced kernels, and produces statistically independent components to explore the nonlinear associations between β-amyloid and tau using PET imaging data.
Our understanding of the complex relationship between β-amyloid and tau in MCI and Alzheimer's disease has evolved over the past several years thanks to the advent of PET imaging radiotracers for in vivo detection of these misfolded proteins. Leveraging Amyloid and Tau PET images, several studies have explored the spatiotemporal relationship, but have typically focused on a linear, local relationship.
We hypothesize that the patterns of association between β-amyloid and tau may be more thoroughly interrogated using alternative association metrics that account for linear and more complex, including nonlinear, dependencies.
In the presentation, we describe a new method, called Canonical Distance Correlation Analysis (CDCA). The CDCA approach produces statistically independent components in the spatiallly distributed-to-distributed organization of the nonlinear association between the β-amyloid and tau PET images.