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Updated: Aug 5, 2026
06:35
Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Exploring longitudinal relationships among Alzheimer's disease biomarkers
Benjamin Saef1, Kellen K Petersen1, Katherine Volluz1
1Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.
Summary
Baseline plasma biomarkers, particularly p-tau217, are more strongly linked to Alzheimer's disease (AD) progression than their rates of change. This finding aids in understanding AD biomarker dynamics.
Area of Science:
- Neuroscience
- Biomarker Research
- Alzheimer's Disease
Background:
- Longitudinal studies of Alzheimer's disease (AD) biomarkers are crucial for understanding disease progression.
- Most AD research focuses on cross-sectional biomarker relationships, limiting insights into dynamic changes.
Purpose of the Study:
- To investigate the longitudinal relationships between plasma biomarkers and key Alzheimer's disease (AD) outcomes.
- To determine whether baseline biomarker levels or their rates of change are more predictive of AD progression.
Main Methods:
- Utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n=373).
- Employed non-parametric Spearman correlations to analyze relationships.
- Examined baseline values and rates of change in plasma biomarkers against rates of change in AD outcomes (amyloid PET, cortical thickness, cognition).
Main Results:
- Baseline plasma biomarker values showed stronger associations with AD outcome changes than biomarker rates of change.
- Amyloid beta (Aβ)42/Aβ40 and phosphorylated tau (p-tau)217 baseline values were most associated with amyloid PET changes, particularly in amyloid PET-negative individuals.
- Baseline p-tau217 was most associated with cortical thickness and cognitive changes, especially in amyloid PET-positive individuals.
Conclusions:
- Baseline levels of p-tau217 are significantly associated with the progression of amyloid pathology and cognitive decline in Alzheimer's disease.
- Developed visualization tools to facilitate the exploration of complex AD biomarker interrelationships for researchers.
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