Identification and Temporal Characterization of Features Associated with the Conversion from Mild Cognitive Impairment to Alzheimer’s Disease

Author:

Martinez-Torteya Antonio1,Gomez-Rueda Hugo2,Trevino Victor2,Farber Joshua3,Tamez-Pena Jose4,For the Alzheimer’s Disease Neuroimaging Initiative

Affiliation:

1. Departamento de Ingenieria, Division de Ingenieria y Tecnologias, Universidad de Monterrey, Morones Prieto 4500 Pte., 66238 San Pedro Garza Garcia, NL, Mexico

2. Escuela de Medicina, Tecnologico de Monterrey, Morones Prieto 2916 Pte., Del Carmen, 64710 Monterrey, NL, Mexico

3. Qmetrics Technology, Rochester, NY 14618, United States

4. Escuela de Medicina, Tecnológico de Monterrey, Morones Prieto 2916 Pte., Del Carmen, 64710 Monterrey, NL, Mexico

Abstract

Background: Diagnosing Alzheimer’s disease (AD) in its earliest stages is important for therapeutic and support planning. Similarly, being able to predict who will convert from mild cognitive impairment (MCI) to AD would have clinical implications. Objectives: The goals of this study were to identify features from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database associated with the conversion from MCI to AD, and to characterize the temporal evolution of that conversion. Methods: We screened the publically available ADNI longitudinal database for subjects with MCI who have developed AD (cases: n=305), and subjects with MCI who have remained stable (controls: n=250). Analyses included 1,827 features from laboratory assays (n=12), quantitative MRI scans (n=1,423), PET studies (n=136), medical histories (n=72), and neuropsychological tests (n=184). Statistical longitudinal models identified features with significant differences in longitudinal behavior between cases and matched controls. A multiple-comparison adjusted log-rank test identified the capacity of the significant predictive features to predict early conversion. Results: 411 features (22.5%) were found to be statistically different between cases and controls at the time of AD diagnosis; 385 features were statistically different at least 6 months prior to diagnosis, and 28 features distinguished early from late conversion, 20 of which were obtained from neuropsychological tests. In addition, 69 features (3.7%) had statistically significant changes prior to AD diagnosis. Conclusion: Our results characterized features associated with disease progression from MCI to AD, and, in addition, the log-rank test identified features which are associated with the risk of early conversion.

Publisher

Bentham Science Publishers Ltd.

Subject

Neurology (clinical),Neurology

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