Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer’s disease
Open/View files
Date
2017
Author(s)
Gamberger, Dragan
Lavrač, Nada
Srivatsa, Shantanu
Doraiswamy, P. Murali
Publisher
Nature Publishing Group UK
The Harvard community has made this article openly available. Please share how this access benefits you.
Citation
Gamberger, Dragan, Nada Lavrač, Shantanu Srivatsa, Rudolph E. Tanzi, and P. Murali Doraiswamy. 2017. “Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer’s disease.” Scientific Reports 7 (1): 6763. doi:10.1038/s41598-017-06624-y. http://dx.doi.org/10.1038/s41598-017-06624-y.
Abstract
The heterogeneity of Alzheimer’s disease contributes to the high failure rate of prior clinical trials. We analyzed 5-year longitudinal outcomes and biomarker data from 562 subjects with mild cognitive impairment (MCI) from two national studies (ADNI) using a novel multilayer clustering algorithm. The algorithm identified homogenous clusters of MCI subjects with markedly different prognostic cognitive trajectories. A cluster of 240 rapid decliners had 2-fold greater atrophy and progressed to dementia at almost 5 times the rate of a cluster of 184 slow decliners. A classifier for identifying rapid decliners in one study showed high sensitivity and specificity in the second study. Characterizing subgroups of at risk subjects, with diverse prognostic outcomes, may provide novel mechanistic insights and facilitate clinical trials of drugs to delay the onset of AD.
Other Available Sources
Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service
Collection