Data used in preparation of this article were obtained from the ADNI database (http://www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Authorship_List.pdf
Disease progression model in subjects with mild cognitive impairment from the Alzheimer's disease neuroimaging initiative: CSF biomarkers predict population subtypes
Version of Record online: 14 DEC 2012
© 2012 Janssen Pharmaceuticals, Inc. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society
British Journal of Clinical Pharmacology
Volume 75, Issue 1, pages 146–161, January 2013
How to Cite
Samtani, M. N., Raghavan, N., Shi, Y., Novak, G., Farnum, M., Lobanov, V., Schultz, T., Yang, E., DiBernardo, A., Narayan, V. A. and the Alzheimer' s Disease Neuroimaging Initiative (2013), Disease progression model in subjects with mild cognitive impairment from the Alzheimer's disease neuroimaging initiative: CSF biomarkers predict population subtypes. British Journal of Clinical Pharmacology, 75: 146–161. doi: 10.1111/j.1365-2125.2012.04308.x
- Issue online: 14 DEC 2012
- Version of Record online: 14 DEC 2012
- Accepted manuscript online: 25 APR 2012 11:11PM EST
- Received; 21 June 2011; Accepted; 18 April 2012; Accepted Article Published Online; 25 April 2012
- CSF biomarkers;
- disease progression;
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT
• Amnestic mild cognitive impairment MCI) represents the prodromal stage of Alzheimer's dementia and this disease progresses in a non-linear fashion.
• Disease progression depends on a variety of demographic, biochemical, genetic and cognitive factors.
WHAT THIS STUDY ADDS
• Baseline CSF biomarkers carry information about disease pathology and critical thresholds for these markers (Aβ and p-tau181P) have been identified that allow segregation of the population into MCI progressers and non-progressers.
AIM The objective is to develop a semi-mechanistic disease progression model for mild cognitive impairment (MCI) subjects. The model aims to describe the longitudinal progression of ADAS-cog scores from the Alzheimer's disease neuroimaging initiative trial that had data from 198 MCI subjects with cerebrospinal fluid (CSF) information who were followed for 3 years.
METHOD Various covariates were tested on disease progression parameters and these variables fell into six categories: imaging volumetrics, biochemical, genetic, demographic, cognitive tests and CSF biomarkers.
RESULTS CSF biomarkers were associated with both baseline disease score and disease progression rate in subjects with MCI. Baseline disease score was also correlated with atrophy measured using hippocampal volume. Progression rate was also predicted by executive functioning as measured by the Trail B-test.
CONCLUSION CSF biomarkers have the ability to discriminate MCI subjects into sub-populations that exhibit markedly different rates of disease progression on the ADAS-cog scale. These biomarkers can therefore be utilized for designing clinical trials enriched with subjects that carry the underlying disease pathology.