Journal article
Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics
Scientific reports, Vol.9(1), pp.2235-2235
02/19/2019
DOI: 10.1038/s41598-019-38793-3
PMCID: PMC6381141
PMID: 30783207
Abstract
In the Alzheimer’s disease (AD) continuum, the prodromal state of mild cognitive impairment (MCI) precedes AD dementia and identifying MCI individuals at risk of progression is important for clinical management. Our goal was to develop generalizable multivariate models that integrate high-dimensional data (multimodal neuroimaging and cerebrospinal fluid biomarkers, genetic factors, and measures of cognitive resilience) for identification of MCI individuals who progress to AD within 3 years. Our main findings were i) we were able to build generalizable models with clinically relevant accuracy (~93%) for identifying MCI individuals who progress to AD within 3 years; ii) markers of AD pathophysiology (amyloid, tau, neuronal injury) accounted for large shares of the variance in predicting progression; iii) our methodology allowed us to discover that expression of
CR1
(complement receptor 1), an AD susceptibility gene involved in immune pathways, uniquely added independent predictive value. This work highlights the value of optimized machine learning approaches for analyzing multimodal patient information for making predictive assessments.
Details
- Title: Subtitle
- Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics
- Creators
- Yogatheesan Varatharajah - University of Illinois Urbana-ChampaignVijay K. Ramanan - Mayo Clinic, Rochester, MN 55905 (USA)Ravishankar Iyer - University of Illinois Urbana-ChampaignPrashanthi Vemuri - Mayo Clinic, Rochester, MN, 55905, USA. Vemuri.Prashanthi@mayo.edu.Alzheimer’s Disease Neuroimaging Initiative
- Contributors
- Hristina Koleva (Contributor) - University of Iowa, Psychiatry
- Resource Type
- Journal article
- Publication Details
- Scientific reports, Vol.9(1), pp.2235-2235
- DOI
- 10.1038/s41598-019-38793-3
- PMID
- 30783207
- PMCID
- PMC6381141
- NLM abbreviation
- Sci Rep
- ISSN
- 2045-2322
- eISSN
- 2045-2322
- Publisher
- Nature Publishing Group UK
- Grant note
- R01 AG56366 / ; CNS-1337732; CNS-1624790 / ;
- Language
- English
- Date published
- 02/19/2019
- Academic Unit
- Psychiatry
- Record Identifier
- 9984293754902771
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