Comparing predictors of conversion and decline in mild cognitive impairment
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Abstract
Objective: A variety of measurements have been individually linked to decline in mild cognitive impairment (MCI), but the identification of optimal markers for predicting disease progression remains unresolved. The goal of this study was to evaluate the prognostic ability of genetic, CSF, neuroimaging, and cognitive measurements obtained in the same participants.
Methods: APOE ε4 allele frequency, CSF proteins (Aβ1-42, total tau, hyperphosphorylated tau [p-tau181p]), glucose metabolism (FDG-PET), hippocampal volume, and episodic memory performance were evaluated at baseline in patients with amnestic MCI (n = 85), using data from a large multisite study (Alzheimer's Disease Neuroimaging Initiative). Patients were classified as normal or abnormal on each predictor variable based on externally derived cutoffs, and then variables were evaluated as predictors of subsequent conversion to Alzheimer disease (AD) and cognitive decline (Alzheimer's Disease Assessment Scale–Cognitive Subscale) during a variable follow-up period (1.9 ± 0.4 years).
Results: Patients with MCI converted to AD at an annual rate of 17.2%. Subjects with MCI who had abnormal results on both FDG-PET and episodic memory were 11.7 times more likely to convert to AD than subjects who had normal results on both measures (p ≤ 0.02). In addition, the CSF ratio p-tau181p/Aβ1-42 (β = 1.10 ± 0.53; p = 0.04) and, marginally, FDG-PET predicted cognitive decline.
Conclusions: Baseline FDG-PET and episodic memory predict conversion to AD, whereas p-tau181p/Aβ1-42 and, marginally, FDG-PET predict longitudinal cognitive decline. Complementary information provided by these biomarkers may aid in future selection of patients for clinical trials or identification of patients likely to benefit from a therapeutic intervention.
Footnotes
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Editorial, page 204
Supplemental data at www.neurology.org
e–Pub ahead of print on June 30, 2010, at www.neurology.org.
Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators is available in appendix e–2 at www.neurology.org.
Study funding: Funding information is provided at the end of the article.
Disclosure: Author disclosures are provided at the end of the article.
Received December 7, 2009. Accepted in final form March 9, 2010.
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Letters: Rapid online correspondence
- PET has no clothes
- Mikko P. Laakso, Department of Psychiatry, Kuopio University Hospital, P.O. Box 1627, FI-70211 Kuopio, Finlandmikko.laakso@uef.fi
- None
Submitted September 08, 2010 - Reply from the authors
- Susan M. Landau, University of California, Berkeley, 118 Barker Hall, MC #3190, Berkeley, CA 94720slandau@berkeley.edu
- William J. Jagust (Berkeley, CA; jagust@berkeley.edu)
Submitted September 08, 2010
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