Integrating Nutrient Biomarkers, Cognitive Function, and Structural MRI Data to Build Multivariate Phenotypes of
Tanveer Talukdar1, Christopher E Zwilling1, Aron K Barbey2
1Decision Neuroscience Laboratory, Beckman Institute, University of Illinois, Urbana, IL, USA(†).
The Journal of Nutrition
|March 25, 2023
Summary
Nutrition, cognition, and brain health are interconnected. This study used data fusion to reveal how nutrient profiles, cognitive abilities, and brain volumes are linked in healthy older adults.
Area of Science:
- Nutritional cognitive neuroscience
- Neuroimaging
- Biomarker analysis
Background:
- Nutrition significantly impacts cognitive performance and brain health.
- Previous research often examined nutrition and cognition or brain health separately.
Purpose of the Study:
- Investigate the joint relationship between nutrition, cognition, and brain health.
- Utilize advanced data fusion to analyze these interconnected health domains.
Main Methods:
- Applied coupled matrix tensor factorization to 111 healthy older adults.
- Analyzed 52 nutrient biomarkers, cognitive tests (e.g., Wechsler scales), and MRI brain volumes.
- Employed hierarchical cluster analysis to identify distinct health phenotypes.
Main Results:
- Data fusion identified latent factors linking nutrient profiles, cognitive measures, and cortical volumes.
- Hierarchical clustering revealed distinct phenotypes based on fatty acid biomarkers, memory function, and brain volumes (frontal, temporal, parietal).
Conclusions:
- Nutrition, cognition, and brain health are integrated, influenced by lifestyle choices.
- This interdisciplinary approach synthesizes methods to understand healthy aging.
- Identified specific nutrient biomarkers, cognitive functions, and brain regions associated with integrated health phenotypes.
Keywords:
data fusionhealthy agingnutrient biomarker analysisnutritional cognitive neurosciencephenotypes
