Subtypes of brain change in aging and their associations with cognition and Alzheimer’s disease biomarkers

Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.

Authors

Institutions

Publication Details

Journal
Neurobiology of Aging
Published
2024-12-26
DOI
https://doi.org/10.1016/j.neurobiolaging.2024.12.009
Citations
3
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
1.16
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Subtypes of brain change in aging and their associations with cognition and Alzheimer’s disease biomarkers

Didac Vidal‐Piñeiro, Marie Strømstad, James M. Roe, Anders M. Fjell et al.
3 citations
Neurobiology of Aging
Dementia and Cognitive Impairment Research
1.16
article

Subtypes of brain change in aging and their associations with cognition and Alzheimer’s disease biomarkers

Didac Vidal‐Piñeiro, Marie Strømstad, James M. Roe, Anders M. Fjell, Kaj Blennow, Elettra Capogna, Øystein Sørensen, Kristine B. Walhovd, Leiv Otto Watne, Nathalie Bodd Halaas, Ane Victoria Idland, Henrik Zetterberg
article en
3 citations

Abstract

Structural brain changes underlie cognitive changes and interindividual variability in cognition in older age. By using structural MRI data-driven clustering, we aimed to identify subgroups of cognitively unimpaired older adults based on brain change patterns and assess how changes in cortical thickness, surface area, and subcortical volume relate to cognitive change. We tested (1) which brain structural changes predict cognitive change (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease biomarkers, and (3) the degree of overlap between clusters derived from different structural modalities in 1899 cognitively healthy older adults followed up to 16 years. We identified four groups for each brain feature, based on the degree of a main longitudinal component of decline. The minimal overlap between features suggested that each contributed uniquely and independently to structural brain changes in aging. Cognitive change and baseline cognition were associated with cortical area change, whereas higher baseline levels of phosphorylated tau and amyloid-β related to changes in subcortical volume. These results may contribute to a better understanding of different aging trajectories.

Neurobiology of AgingVol. 147
Oslo University Hospital (NO), University of Oslo (NO), Akershus University Hospital (NO), Sahlgrenska University Hospital (SE), Sorbonne Université (FR), University College London (GB)
Openalex Percentile: Top 19%
Dementia and Cognitive Impairment Research
1.16
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.