A whole-brain functional connectivity model of Alzheimer's disease pathology.

ABSTRACT:

Introduction

Alzheimer's disease (AD) is characterized by the presence of two proteinopathies, amyloid and tau, which have a cascading effect on the functional and structural organization of the brain.

Methods

In this study, we used a supervised machine learning technique to build a model of functional connections that predicts cerebrospinal fluid (CSF) p-tau/Aβ₄₂ (the PATH-fc model). Resting-state functional magnetic resonance imaging (fMRI) data from 289 older adults in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were utilized for this model.

Results

We successfully derived the PATH-fc model to predict the ratio of p-tau/Aβ₄₂ as well as cognitive functioning in older adults across the spectrum of healthy and pathological aging. Howev

SUBMITTER: Prakash RS 

PROVIDER: S-EPMC11781256 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature