Integrating individualized connectome with amyloid pathology improves predictive modeling of future cognitive decline.

ABSTRACT:

Background

The deposition of amyloid-β (Aβ) in the human brain is a hallmark of Alzheimer's disease and is associated with cognitive decline. Aβ pathology is traditionally assessed at the whole-brain level across neocortical regions using positron emission tomography (PET). However, these measures often show weak associations with future cognitive impairment. A more sensitive pathology metric is needed to quantify early Aβ burden and better predict cognitive decline. Here, we aim to develop a network-based metric of Aβ burden to improve early prediction of cognitive decline in aging populations.

Methods

We integrated subject-specific brain connectome information with Aβ-PET measures to construct a network-based metric of Aβ burden. Cross-validated predictive modeling was use

SUBMITTER: He H 

PROVIDER: S-EPMC12680778 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature