Exploring functional connectivity patterns and their associations with amyloid and tau biomarkers across alzheimer's disease stages: a resting-state fmri study

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and hallmark biomarkers: amyloid-beta (Aβ) plaques and neurofibrillary tau tangles. Functional connectivity, assessed via resting-state functional Magnetic Resonance Imaging (fMRI), has shown associations with Aβ and tau. However, its adoption is hindered by high data dimensionality, noise, and artefact susceptibility. This study explored functional connectivity differences across clinically relevant AD groups, aiming to enhance our understanding of the link between brain function and AD neuropathology. Methods and Data Analysis: Two datasets were used for cross-sectional analyses: dataset 1 was comprised of cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia of the Alzheimer’s Disease type (DAT) participants. Dataset 2 included CU only. Whole-brain region-of-interest (ROI)-to-ROI analysis was followed by a dual-approach of Multivariate Pattern Analysis and seed-based connectivity to identify regions and measure group differences in functional connectivity patterns. We then investigated whether AD biomarkers moderate functional connectivity and cognition relationships. Lastly, network-level functional connectivity differences within and between the Default Mode network and medial temporal lobe (MTL) were measured between CU Aβ+ and Aβ- participants. Results: Multivariate Pattern Analysis revealed functional connectivity differences between two out of three group comparisons. The left thalamus, precuneus, and frontal gyri sub-regions were identified as key ROIs. Tau (more than Aβ) moderated more relationships between functional connectivity and cognition, particularly among MCI participants. In dataset 2, CU Aβ+ participants showed more relationships between MTL functional connectivity and regional tau burden. Specifically, among Aβ+, lower functional connectivity was associated with higher tau pathology, pointing towards early neurodegeneration. Conclusions: These findings enhance our understanding of the interplay between brain function and AD pathology, reinforce tau as a biomarker closely linked to functional connectivity, and identify specific brain regions and networks with potential clinical applications in early AD diagnosis and therapeutic interventions.

Institutions

Publication Details

Journal
Spiral (Imperial College London)
Published
2024-12-03
DOI
https://doi.org/10.25560/119625
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring functional connectivity patterns and their associations with amyloid and tau biomarkers across alzheimer's disease stages: a resting-state fmri study

Spiral (Imperial College London)
Functional Brain Connectivity Studies
article

Exploring functional connectivity patterns and their associations with amyloid and tau biomarkers across alzheimer's disease stages: a resting-state fmri study

article en

Abstract

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disorder marked by cognitive decline and hallmark biomarkers: amyloid-beta (Aβ) plaques and neurofibrillary tau tangles. Functional connectivity, assessed via resting-state functional Magnetic Resonance Imaging (fMRI), has shown associations with Aβ and tau. However, its adoption is hindered by high data dimensionality, noise, and artefact susceptibility. This study explored functional connectivity differences across clinically relevant AD groups, aiming to enhance our understanding of the link between brain function and AD neuropathology. Methods and Data Analysis: Two datasets were used for cross-sectional analyses: dataset 1 was comprised of cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia of the Alzheimer’s Disease type (DAT) participants. Dataset 2 included CU only. Whole-brain region-of-interest (ROI)-to-ROI analysis was followed by a dual-approach of Multivariate Pattern Analysis and seed-based connectivity to identify regions and measure group differences in functional connectivity patterns. We then investigated whether AD biomarkers moderate functional connectivity and cognition relationships. Lastly, network-level functional connectivity differences within and between the Default Mode network and medial temporal lobe (MTL) were measured between CU Aβ+ and Aβ- participants. Results: Multivariate Pattern Analysis revealed functional connectivity differences between two out of three group comparisons. The left thalamus, precuneus, and frontal gyri sub-regions were identified as key ROIs. Tau (more than Aβ) moderated more relationships between functional connectivity and cognition, particularly among MCI participants. In dataset 2, CU Aβ+ participants showed more relationships between MTL functional connectivity and regional tau burden. Specifically, among Aβ+, lower functional connectivity was associated with higher tau pathology, pointing towards early neurodegeneration. Conclusions: These findings enhance our understanding of the interplay between brain function and AD pathology, reinforce tau as a biomarker closely linked to functional connectivity, and identify specific brain regions and networks with potential clinical applications in early AD diagnosis and therapeutic interventions.

Spiral (Imperial College London)
Imperial College London (GB)
Openalex Percentile: Top 55%
Functional Brain Connectivity Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.