期刊
NEUROLOGY
卷 87, 期 23, 页码 2443-2450出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1212/WNL.0000000000003397
关键词
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资金
- Vanderbilt Memory & Alzheimer's Center
- ADNI (NIH) [U01 AG024904]
- Department of Defense ADNI (Department of Defense) [W81XWH-12-2-0012]
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- Canadian Institutes of Health Research
- Northern California Institute for Research and Education
- [K01-AG049164]
- [K24-AG046373]
- [K23-AG045966]
- [R01-AG034962]
- [R01-HL111516]
- [K12-HD043483]
Objective: To define robust resilience metrics by leveraging CSF biomarkers of Alzheimer disease (AD) pathology within a latent variable framework and to demonstrate the ability of such metrics to predict slower rates of cognitive decline and protection against diagnostic conversion. Methods: Participants with normal cognition (n = 297) and mild cognitive impairment (n = 432) were drawn from the Alzheimer's Disease Neuroimaging Initiative. Resilience metrics were defined at baseline by examining the residuals when regressing brain aging outcomes (hippocampal volume and cognition) on CSF biomarkers. A positive residual reflected better outcomes than expected for a given level of pathology (high resilience). Residuals were integrated into a latent variable model of resilience and validated by testing their ability to independently predict diagnostic conversion, cognitive decline, and the rate of ventricular dilation. Results: Latent variables of resilience predicted a decreased risk of conversion (hazard ratio < 0.54, p < 0.0001), slower cognitive decline (beta > 0.02, p < 0.001), and slower rates of ventricular dilation (beta < -4.7, p < 2 x 10(-15)). These results were significant even when analyses were restricted to clinically normal individuals. Furthermore, resilience metrics interacted with biomarker status such that biomarker-positive individuals with low resilience showed the greatest risk of subsequent decline. Conclusions: Robust phenotypes of resilience calculated by leveraging AD biomarkers and baseline brain aging outcomes provide insight into which individuals are at greatest risk of short-term decline. Such comprehensive definitions of resilience are needed to further our understanding of the mechanisms that protect individuals from the clinical manifestation of AD dementia, especially among biomarker-positive individuals.
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