Decoding cognitive aging: how white matter tracts and demographics distinguish potential Super-Agers.
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.
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Research summary
The paper claims that the Optimal Cognitive Scoring (OptiCS) algorithm can accurately differentiate between "Positive-Agers" and "Cognitive Decliners" using diffusion MRI attributes. This research is relevant as it addresses cognitive aging and seeks to identify individuals who maintain superior cognitive function, potentially informing interventions that could mitigate age-related cognitive decline.
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