Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers

Most adults experience age-related cognitive decline. However, "Positive-Agers" exhibit superior cognition compared to their age-matched peers. Distinguishing between those with superior cognitive performance and those with cognitive decline over time could better inform treatment therapies in older adults. We developed an algorithm called Optimal Cognitive Scoring (OptiCS) that accurately differentiates "Positive-Agers" from "Cognitive Decliners." This study draws on a cohort of 5797 participants longitudinally enrolled in the UK Biobank. Using a predictive pipeline, OptiCS could strongly differentiate Positive-Agers versus Cognitive Decliners (area under the curve, or AUC of 83%). The top diffusion MRI attributes highlighted tracts implicated in pathological aging, including the fornix from the hippocampus, the tapetum from the splenium of the corpus callosum, and other key tracts. This study provides three key insights: (I) The proposed algorithm offers a robust cognitive scoring system for subtle cognitive changes, (II) OptiCS can use diffusion MRI to accurately gauge cognitive performance, and (III) OptiCS provides a predictive framework for early detection of cognitive decline.

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Publication Details

Journal
GeroScience
Published
2025-02-26
DOI
https://doi.org/10.1007/s11357-025-01566-0
Citations
2
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.72

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article

Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers

Guiping Hu, Auriel A. Willette, Mohammad Fili, Parvin Mohammadiarvejeh
2 citations
GeroScience
Advanced Neuroimaging Techniques and Applications
2.72
article

Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers

Guiping Hu, Auriel A. Willette, Mohammad Fili, Parvin Mohammadiarvejeh
article en
2 citations

Abstract

Most adults experience age-related cognitive decline. However, "Positive-Agers" exhibit superior cognition compared to their age-matched peers. Distinguishing between those with superior cognitive performance and those with cognitive decline over time could better inform treatment therapies in older adults. We developed an algorithm called Optimal Cognitive Scoring (OptiCS) that accurately differentiates "Positive-Agers" from "Cognitive Decliners." This study draws on a cohort of 5797 participants longitudinally enrolled in the UK Biobank. Using a predictive pipeline, OptiCS could strongly differentiate Positive-Agers versus Cognitive Decliners (area under the curve, or AUC of 83%). The top diffusion MRI attributes highlighted tracts implicated in pathological aging, including the fornix from the hippocampus, the tapetum from the splenium of the corpus callosum, and other key tracts. This study provides three key insights: (I) The proposed algorithm offers a robust cognitive scoring system for subtle cognitive changes, (II) OptiCS can use diffusion MRI to accurately gauge cognitive performance, and (III) OptiCS provides a predictive framework for early detection of cognitive decline.

GeroScienceVol. 47(3)
Rutgers, The State University of New Jersey (US), Oklahoma State University (US), University of Maryland Medical System (US)
Alzheimer's Association, National Institutes of Health
Quality Education
Openalex Percentile: Top 12%
Advanced Neuroimaging Techniques and Applications
2.72
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Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers — Guiping Hu, Auriel A. Willette, et al. · GeroScience (2025) | TGRS Research Map | TGRS