Literature DB >> 29422002

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

Antonio Martinez-Torteya1, Hugo Gomez-Rueda2, Victor Trevino2, Joshua Farber3, Jose Tamez-Pena2.   

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. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Entities:  

Keywords:  ADNI; Alzheimer’s disease; early conversion; longitudinal analysis; mild cognitive impairment; temporal characterization.

Mesh:

Year:  2018        PMID: 29422002     DOI: 10.2174/1567205015666180202095616

Source DB:  PubMed          Journal:  Curr Alzheimer Res        ISSN: 1567-2050            Impact factor:   3.498


  2 in total

1.  Benchmarking machine learning models for late-onset alzheimer's disease prediction from genomic data.

Authors:  Javier De Velasco Oriol; Edgar E Vallejo; Karol Estrada; José Gerardo Taméz Peña; The Alzheimer's Disease Neuroimaging Initiative
Journal:  BMC Bioinformatics       Date:  2019-12-16       Impact factor: 3.169

2.  Plasma Transthyretin as a Predictor of Amnestic Mild Cognitive Impairment Conversion to Dementia.

Authors:  Yi-Ting Tien; Wei-Ju Lee; Yi-Chu Liao; Wen-Fu Wang; Kai-Ming Jhang; Shuu-Jiun Wang; Jong-Ling Fuh
Journal:  Sci Rep       Date:  2019-12-10       Impact factor: 4.379

  2 in total

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