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
Brosch, Jared R; Farlow, Martin R; Risacher, Shannon L et al. (2017) Tau Imaging in Alzheimer's Disease Diagnosis and Clinical Trials. Neurotherapeutics 14:62-68
Blanken, Anna E; Hurtz, Sona; Zarow, Chris et al. (2017) Associations between hippocampal morphometry and neuropathologic markers of Alzheimer's disease using 7 T MRI. Neuroimage Clin 15:56-61
Du, Lei; Liu, Kefei; Yao, Xiaohui et al. (2017) Pattern Discovery in Brain Imaging Genetics via SCCA Modeling with a Generic Non-convex Penalty. Sci Rep 7:14052
Wilhalme, Holly; Goukasian, Naira; De Leon, Fransia et al. (2017) A comparison of theoretical and statistically derived indices for predicting cognitive decline. Alzheimers Dement (Amst) 6:171-181
Mustafa, Rafid; Brosch, Jared R; Rabinovici, Gil D et al. (2017) Patient and Caregiver Assessment of the Benefits From the Clinical Use of Amyloid PET Imaging. Alzheimer Dis Assoc Disord :
Deters, Kacie D; Nho, Kwangsik; Risacher, Shannon L et al. (2017) Genome-wide association study of language performance in Alzheimer's disease. Brain Lang 172:22-29
Du, Lei; Zhang, Tuo; Liu, Kefei et al. (2017) Identifying Associations Between Brain Imaging Phenotypes and Genetic Factors via A Novel Structured SCCA Approach. Inf Process Med Imaging 10265:543-555
Sokolow, Sophie; Li, Xiaohui; Chen, Lucia et al. (2017) Deleterious Effect of Butyrylcholinesterase K-Variant in Donepezil Treatment of Mild Cognitive Impairment. J Alzheimers Dis 56:229-237
Clark, David Glenn; McLaughlin, Paula M; Woo, Ellen et al. (2016) Novel verbal fluency scores and structural brain imaging for prediction of cognitive outcome in mild cognitive impairment. Alzheimers Dement (Amst) 2:113-22
Ramirez, Leslie M; Goukasian, Naira; Porat, Shai et al. (2016) Common variants in ABCA7 and MS4A6A are associated with cortical and hippocampal atrophy. Neurobiol Aging 39:82-9

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