In the past, the field of Alzheimer disease (AD) genetics has benefited from the development of innovative paradigms that incorporate the latest genomic technologies combined with pristine patient data to dissect its complex etiology. Our group has successfully used this paradigm in both the identification of the APOE risk effect and more recently the glutathione S-transferase Omega-1 (GSTO1) age at onset (AAO) effect in AD. There is a new appreciation of the power of incorporating clinical phenotypes and developing clinical subphenotypes in attacking complex disorders. In addition, molecular genetic methods have continued to advance rapidly. Whole genome association (WGA) is a new approach that allows the direct evaluation of 300,000- 1,000,000 SNPs from across the genome for association with AD and provides the opportunity to perform a much more detailed examination of the genome than linkage studies. However, while the information content of WGA is extraordinarily high, the initial false positive rate using standard analyses is also high. Investigating each of the thousands of markers that will reach nominal significance is an ominous and inefficient task. One solution to this problem is the genomic convergence approach, which integrates disparate data types to sift through the volumes of existing data to prioritize the best candidate genes for intensive analysis. We have already demonstrated the utility of this approach with the identification of the GSTO1 gene. Thus we are proposing a WGA study of AD and will filter the results using existing linkage, candidate gene, and our recently generated microarray and Serial Analysis of Gene Expression (SAGE) data. A small set of candidate genes identified in multiple of these studies will be the focus of intensive follow-up analysis. Of particular importance will be our ability to follow-up using detailed clinical data on movement and psychiatric symptoms in a newly collected case-control dataset. Our unique position will enable us to marry the most powerful of new genomic approaches, WGA, to existing information to elucidate additional genetic effects contributing to this important neurodegenerative disease. The knowledge derived from this study will further our understanding of AD and will be crucial for future studies to develop and evaluate interventions. The knowledge derived from this study will further our understanding of the genetic etiology of AD. This understanding will be crucial for future studies to develop early interventions and more focused treatments, which will help alleviate the suffering of those with the disease and their families.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG027944-04
Application #
8054243
Study Section
Neurological, Aging and Musculoskeletal Epidemiology (NAME)
Program Officer
Miller, Marilyn
Project Start
2008-04-01
Project End
2013-03-31
Budget Start
2011-04-01
Budget End
2012-03-31
Support Year
4
Fiscal Year
2011
Total Cost
$1,162,428
Indirect Cost
Name
University of Miami School of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
052780918
City
Coral Gables
State
FL
Country
United States
Zip Code
33146
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Jun, Gyungah R; Chung, Jaeyoon; Mez, Jesse et al. (2017) Transethnic genome-wide scan identifies novel Alzheimer's disease loci. Alzheimers Dement 13:727-738
Cukier, H N; Kunkle, B K; Hamilton, K L et al. (2017) Exome Sequencing of Extended Families with Alzheimer's Disease Identifies Novel Genes Implicated in Cell Immunity and Neuronal Function. J Alzheimers Dis Parkinsonism 7:
Sims, Rebecca (see original citation for additional authors) (2017) Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. Nat Genet 49:1373-1384
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Mez, Jesse; Mukherjee, Shubhabrata; Thornton, Timothy et al. (2016) The executive prominent/memory prominent spectrum in Alzheimer's disease is highly heritable. Neurobiol Aging 41:115-121
Ridge, Perry G; Hoyt, Kaitlyn B; Boehme, Kevin et al. (2016) Assessment of the genetic variance of late-onset Alzheimer's disease. Neurobiol Aging 41:200.e13-200.e20
Hohman, Timothy J; Bush, William S; Jiang, Lan et al. (2016) Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium. Neurobiol Aging 38:141-150
Kunkle, Brian W; Jaworski, James; Barral, Sandra et al. (2016) Genome-wide linkage analyses of non-Hispanic white families identify novel loci for familial late-onset Alzheimer's disease. Alzheimers Dement 12:2-10
Jun, G; Ibrahim-Verbaas, C A; Vronskaya, M et al. (2016) A novel Alzheimer disease locus located near the gene encoding tau protein. Mol Psychiatry 21:108-17

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