Adding cognition to AT(N) models improves prediction of cognitive and functional decline

Abstract

Introduction: This study sought to determine whether adding cognition to a model with Alzheimer's disease biomarkers based on the amyloid, tau, and neurodegeneration/neuronal injury-AT(N)-biomarker framework predicts rates of cognitive and functional decline in older adults without dementia. Methods:The study included 465 participants who completed amyloid positron emission tomography, cerebrospinal fluid phosphorylated tau, structural magnetic resonance imaging, and serial neuropsychological testing. Using the AT(N) framework and a newly validated cognitive metric as the independent variables, we used linear mixed effects models to examine a 4-year rate of change in cognitive and functional measures. Results:The inclusion of baseline cognitive status improved model fit in predicting rate of decline in outcomes above and beyond biomarker variables. Specifically, those with worse cognitive functioning at baseline had faster rates of memory and functional decline over a 4-year period, even when accounting for AT(N).Discussion: Including a newly validated measure of baseline cognition may improve clinical prognosis in non-demented older adults beyond the use of AT(N) biomarkers alone.

Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum

“…A great similarity was observed between models explaining variance in concurrent cognitive impairment and decline in cognition. This might be due to the current level of cognition being a good predictor of cognitive decline, 49 , 50 reflecting the fact that people who are declining are likely to already show some impairment, and people with more severe impairments are more likely to be declining more rapidly.…”

Longitudinal change in serial position scores in older adults with entorhinal and hippocampal neuropathologies

“…In conjunction with routine neuropsychological scores, a process score approach that integrates primacy performance with existing approaches for defining subtle cognitive decline (Thomas et al, 2018) could help identify individuals at risk of progressing to Alzheimer's dementia much earlier and thereby widen the window of opportunity for pharmacologic and lifestyle intervention. Future studies should consider examining primacy effects in the context of the AT(N) biomarker framework, as recent work has proposed adding a measure of cognitive status could help improve prediction of cognitive decline in adults without dementia (O'Shea et al, 2021). More broadly, an exciting direction for this work will be to harness digital process scores from technologically advanced assessment tools that enable us to uncover novel cognitive parameters with enhanced sensitivity to preclinical AD (Au et al, 2017).…”

The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022

“…The prediction of functional decline by AT(N) biomarkers was enhanced by the addition of a baseline cognitive measure. 109 In preclinical AD and MCI participants, the previously validated Discrepancy-Based Evidence for the Loss of Thinking Abilities (DELTA) score improved the ability of Aβ PET SUVR, CSF p-tau181, and hippocampal volume to predict scores on the Functional Activities Questionnaire (FAQ) and CDR-SB. Different assessments also predicted different measures of atrophy, suggesting that measurements of decline are not interchangeable.…”