Longitudinal Clustering Identifies Different Rates of Cortical Aging in Healthy Older Adults
Benita Schmitz-Koep1,2, Fabian Bongratz3,4, Vivian Schultz1,2
1Department of Neuroradiology, School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Aging and Disease
|August 11, 2026
Summary
Healthy aging shows varied brain aging rates. Some individuals experience more pronounced cortical atrophy, particularly in the prefrontal cortex, linked to education levels.
Area of Science:
- Neuroscience
- Radiology
- Gerontology
Background:
- Global brain aging patterns are known, but individual differences in regional brain aging are less understood.
- Cortical thickness (CTh) is a key biomarker for brain aging and pathologies.
Purpose of the Study:
- To identify distinct brain aging patterns in healthy older adults using a clustering approach.
- To investigate predictors of cluster membership related to individual differences in brain aging.
Main Methods:
- Longitudinal study of 176 healthy individuals (aged 68-85) with two MRI scans (5-year interval).
- Assessed annualized percent change (APC) in cortical thickness (CTh) to identify regional atrophy.
- Used hierarchical cluster analysis to classify individuals into distinct aging groups based on APC values.
Main Results:
- Two distinct aging clusters were identified: minimal atrophy and pronounced atrophy.
- Pronounced atrophy was concentrated in left prefrontal and central regions.
- Higher education was associated with more pronounced atrophy (borderline significance in adjusted analysis); a trend towards cognitive decline was observed.
Conclusions:
- Healthy aging is characterized by heterogeneous rates of cortical aging.
- Individual differences in brain aging trajectories exist, with some showing accelerated atrophy in specific regions.
- Education may be a factor influencing these individual differences in brain aging.
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