Alzheimer's disease (AD) presently affects over 5 million Americans and is projected to affect 15 million by 2050. Biomarkers are presently the only feasible approach for diagnosing and quantifying disease-associated changes in the latent AD stage during which a successful disease-modifying therapeutic intervention would realize the greatest impact. High-throughput neuroimaging and genetics have a proven track record for critically advancing our understanding of disease mechanisms and promoting therapeutic development. Our goals are to develop a multimodal biomarker AD risk assessment tool using the prospectively collected imaging, genetic and gene expression ImaGene data set. We propose to apply advanced imaging genetics statistical approaches to achieve the following three aims: 1) identify a discovery set of AD-relevant candidate imaging and genetic biomarkers;2) select gene expression variables with strong evidence for biological relevance to AD;and 3) develop and validate a multimodal classifier capable of accurately assessing one's risk for future conversion to AD. The discovery of critical disease-related pathways will fundamentally advance our understanding of the molecular and genetic triggers of AD and bring us closer to genomic-based interventions and personalized risk assessment.

Public Health Relevance

The proposed research is relevant to public health as there is an urgent need for biomarkers capable of early and presymptomatic diagnosis and for discovery of critical disease-associated pathways. The proposed research is highly relevant to the mission of NIA because it will 1) identify and test key imaging and peripheral blood genetic biomarkers that when combined will help diagnose early AD and 2) critically inform AD drug development.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
3R01AG040770-01A1S1
Application #
8634179
Study Section
Clinical Neuroscience and Neurodegeneration Study Section (CNN)
Program Officer
Hsiao, John
Project Start
2013-03-20
Project End
2017-03-31
Budget Start
2013-03-20
Budget End
2013-03-31
Support Year
1
Fiscal Year
2013
Total Cost
$30,510
Indirect Cost
$6,296
Name
University of California Los Angeles
Department
Neurology
Type
Schools of Medicine
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
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