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.
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.
|Teng, Edmond; Chow, Nicole; Hwang, Kristy S et al. (2015) Low plasma ApoE levels are associated with smaller hippocampal size in the Alzheimer's disease neuroimaging initiative cohort. Dement Geriatr Cogn Disord 39:154-66|
|Apostolova, Liana G; Hwang, Kristy S; Kohannim, Omid et al. (2014) ApoE4 effects on automated diagnostic classifiers for mild cognitive impairment and Alzheimer's disease. Neuroimage Clin 4:461-72|
|(2014) The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav 8:153-82|
|Apostolova, Liana G; Di, Li Jie; Duffy, Erin L et al. (2014) Risk factors for behavioral abnormalities in mild cognitive impairment and mild Alzheimer's disease. Dement Geriatr Cogn Disord 37:315-26|
|Kilroy, Emily; Apostolova, Liana; Liu, Collin et al. (2014) Reliability of two-dimensional and three-dimensional pseudo-continuous arterial spin labeling perfusion MRI in elderly populations: comparison with 15O-water positron emission tomography. J Magn Reson Imaging 39:931-9|
|McLaughlin, Paula M; Wright, Matthew J; Larocca, Michael et al. (2014) The "Alzheimer's type" profile of semantic clustering in amnestic mild cognitive impairment. J Int Neuropsychol Soc 20:402-12|