Alzheimer's disease (AD) is the most common neurodegenerative disease with no effective means of prevention or treatment. Most of the recent published genetic studies for AD have focused on the identification of genetic variants associated with risk for disease. Other aspects of AD, such as age at onset, disease duration or rate of disease progression are less well studied. It is very likely that different genetic variants and genes will influence these different aspects of disease. The goal of this study is to identify novel genetic variants and genes associated with rate of disease progression and other informative endophenotypes for AD, such as amyloid imaging (Pittsburgh compound B or florbetapir) and hippocampal volume. We will use innovative genomic and statistical methods, to analyze not only the effect of common variants but also rare coding variants on endophenotype levels by incorporating genome-wide association data, whole-genome sequencing and exome-chip data into our analyses. We will also test whether the variants associated with rate of progression, amyloid imaging and hippocampal volume are also associated with risk for disease, cerebrospinal fluid tau and A? levels and other AD phenotypes. The broad, long-term goal of this research is to dissect the complex genetic architecture of Alzheimer's disease, which will lead to better prediction and treatment of this devastating disease. By studying several AD endophenotypes we expect to identify genetic variants, genes and pathways affecting different aspects of the disease. These findings will help to identify novel and key proteins involved in disease pathogenesis and potential therapeutic targets.

Public Health Relevance

As instructed by the funding opportunity announcement for this application (PAR-13-329), only the Overall component contains a project narrative. Cores and projects were instructed not to include this section.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
5P01AG003991-35
Application #
9477565
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2018-05-01
Budget End
2019-04-30
Support Year
35
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Sutphen, Courtney L; McCue, Lena; Herries, Elizabeth M et al. (2018) Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer's disease. Alzheimers Dement 14:869-879
Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872
Lancour, Daniel; Naj, Adam; Mayeux, Richard et al. (2018) One for all and all for One: Improving replication of genetic studies through network diffusion. PLoS Genet 14:e1007306
Li, Zeran; Del-Aguila, Jorge L; Dube, Umber et al. (2018) Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure. Genome Med 10:43
Blaiotta, Claudia; Freund, Patrick; Cardoso, M Jorge et al. (2018) Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction. Neuroimage 166:117-134
Schindler, Suzanne E; Sutphen, Courtney L; Teunissen, Charlotte et al. (2018) Upward drift in cerebrospinal fluid amyloid ? 42 assay values for more than 10 years. Alzheimers Dement 14:62-70
Gabel, Matthew; Gooblar, Jonathan; Roe, Catherine M et al. (2018) Political Ideology, Confidence in Science, and Participation in Alzheimer Disease Research Studies. Alzheimer Dis Assoc Disord 32:179-184
Blue, Elizabeth E; Bis, Joshua C; Dorschner, Michael O et al. (2018) Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer's Disease Sequencing Project. Dement Geriatr Cogn Disord 45:1-17
Rao, Shuquan; Ghani, Mahdi; Guo, Zhiyun et al. (2018) An APOE-independent cis-eSNP on chromosome 19q13.32 influences tau levels and late-onset Alzheimer's disease risk. Neurobiol Aging 66:178.e1-178.e8
Roe, Catherine M; Babulal, Ganesh M; Mishra, Shruti et al. (2018) Tau and Amyloid Positron Emission Tomography Imaging Predict Driving Performance Among Older Adults with and without Preclinical Alzheimer's Disease. J Alzheimers Dis 61:509-513

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