Predicting Alzheimer’s Disease Using Combined Imaging-Whole Genome SNP Data
Open accessAbstract
The growing public threat of Alzheimer's disease (AD) has raised the urgency to discover and validate prognostic biomarkers in order to predicting time to onset of AD. It is anticipated that both whole genome single nucleotide polymorphism (SNP) data and high dimensional whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. The aim of this paper is to test whether both whole genome SNP data and whole brain imaging data offer predictive values to identify subjects at risk for progressing to AD. In 343 subjects with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI-1), we extracted high dimensional MR imaging (volumetric data on 93 brain regions plus a surface fluid registration based hippocampal subregion and surface data), and whole genome data (504,095 SNPs from GWAS), as well as routine neurocognitive and clinical data at baseline. MCI patients were then followed over 48 months, with 150 participants progressing to AD. Combining information from whole brain MR imaging and whole genome data was substantially superior to the standard model for predicting time to onset of AD in a 48-month national study of subjects at risk. Our findings demonstrate the promise of combined imaging-whole genome prognostic markers in people with mild memory impairment.
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Prior work has modeled time-to-AD-progression in a survival framework and obtained encouraging results.
“Several studies [11, 12, 16] have focused on the prediction of time of progression to AD under a time-to-event analysis setting, and promising performance have been obtained.”
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- Authors
- Kong, D., Initiative, A. F. T. A. D. N., Giovanello, K. S., Wang, Y., Lin, W., Lee, E., Fan, Y., Murali Doraiswamy, P., & Zhu, H.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Departments of Psychiatry and Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- Venue
- Journal of Alzheimer's Disease
- Publisher
- SAGE Publications
- Published
- 2015-06-25
- Volume
- 46
- Issue
- 3
- Pages
- 695-702
- ISSN
- 1387-2877 (ISSN-L)
- 1875-8908
- PMC
- PMC4583331
- OpenAlex
- W1740214078
- Cited by
- 26
- References
- 48
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 4 · 2021: 2 · 2020: 3 · 2019: 3 · 2018: 3 · 2017: 2 · 2016: 4
- FWCI
- 2.43
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Alzheimer s Disease (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- U.S. Department of Defense
- National Institutes of Health (UL1TR001111, 5u01ag024904-10, UL1TR002489, RR025747)
- National Institute on Aging (R21AG043760, U01-AG-024904, AG033387, R21AG033387)
- National Institute of Mental Health (T32MH106440, MH086633, R01MH086633)
- National Cancer Institute (P01CA142538)
- National Center for Research Resources (UL1RR025747)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
- Keywords
- Alzheimer's disease, mild cognitive impairment
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Psychiatric Status Rating Scales, Genome, Polymorphism, Single Nucleotide, Principal Component Analysis, Apolipoprotein E4, Genetic Association Studies, Cognitive Dysfunction
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