GWA methods have now been successfully used to detect disease-related susceptibility genes for a growing 1st of genetically complex disorders. In these studies, a critical element for success is that the sample size be large enough so that there is adequately power to detect genes with modest effect sizes at genome-wide significance. The sample needed to detect a given effect size depends on genetic heterogeneity, which is difficult to predict for AD. However, for other diseases such as type 2 diabetes, susceptibility genes with odds ratios of ~1.3 have been detected with initial discovery cohorts of 4,549 cases and 5,579 controls (phase 1, 3 studies combined) followed by a replication dataset of 10,053 cases and 12,289 controls (phase 2). Current genotyping platforms permit coverage of ~92% of the linkage disequilibrium landscape of the human genome using ~550,000 SNP's. Typically, ~1% of the top SNP's nominally detected in the discovery phase are then tested in the replication dataset. It is not unusual that validated loci not in the top tier of SNP's from the initial discovery experiment. Thus a large replication samples is critical to the success of these studies. The quality of the replication samples in terms of accurate diagnosis is critical to the success of GWA studies because incorrect diagnoses can result in reduced power to confirm true loci. The ADGC is being formed to collaboratively use the collective resources of AD research community to identify AD genes. The clinical, neuropathologic, molecular and statistical expertise exists within the AD research community. Also, much of the needed phenotype data and DNA samples also exist, gathered by the ADCs. The primary goal of the ADGC will be to identify variability in genes that influences susceptibility to AD. Susceptibility genes potentially influence onset-age, rate of progression through the prodromal and mild cognitive impairment (MCI) phase of the disease. Secondary goals are to identify genes that influence specific AD- related endophenotypes such as neuropathology features (e.g. amyloid load, tangle load, etc), biomarker measures [e.g. cerebral spinal fluid (CSF) A? and tau levels, MRI measures], rate-of-disease progression, responses to environmental factors (e.g. drugs, non-pharmaceutical environmental factors).

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01AG032984-04S1
Application #
8733885
Study Section
Special Emphasis Panel (ZAG1-ZIJ-7 (O4))
Program Officer
Anderson, Dallas
Project Start
2009-04-01
Project End
2015-03-31
Budget Start
2013-09-30
Budget End
2014-03-31
Support Year
4
Fiscal Year
2013
Total Cost
$263,120
Indirect Cost
$33,083
Name
University of Pennsylvania
Department
Pathology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Nelson, Peter T; Estus, Steven; Abner, Erin L et al. (2014) ABCC9 gene polymorphism is associated with hippocampal sclerosis of aging pathology. Acta Neuropathol 127:825-43
Sherva, Richard; Tripodis, Yorghos; Bennett, David A et al. (2014) Genome-wide association study of the rate of cognitive decline in Alzheimer's disease. Alzheimers Dement 10:45-52
Logue, Mark W; Schu, Matthew; Vardarajan, Badri N et al. (2014) Two rare AKAP9 variants are associated with Alzheimer's disease in African Americans. Alzheimers Dement 10:609-618.e11
Benitez, Bruno A; Jin, Sheng Chih; Guerreiro, Rita et al. (2014) Missense variant in TREML2 protects against Alzheimer's disease. Neurobiol Aging 35:1510.e19-26
Barral, Sandra; Reitz, Christiane; Small, Scott A et al. (2014) Genetic variants in a 'cAMP element binding protein' (CREB)-dependent histone acetylation pathway influence memory performance in cognitively healthy elderly individuals. Neurobiol Aging 35:2881.e7-2881.e10
Carney, Regina M; Kohli, Martin A; Kunkle, Brian W et al. (2014) Parkinsonism and distinct dementia patterns in a family with the MAPT R406W mutation. Alzheimers Dement 10:360-5
Ryvkin, Paul; Leung, Yuk Yee; Ungar, Lyle H et al. (2014) Using machine learning and high-throughput RNA sequencing to classify the precursors of small non-coding RNAs. Methods 67:28-35
Kauwe, John S K; Bailey, Matthew H; Ridge, Perry G et al. (2014) Genome-wide association study of CSF levels of 59 alzheimer's disease candidate proteins: significant associations with proteins involved in amyloid processing and inflammation. PLoS Genet 10:e1004758
Swaminathan, Shanker; Risacher, Shannon L; Yoder, Karmen K et al. (2014) Association of plasma and cortical amyloid beta is modulated by APOE ?4 status. Alzheimers Dement 10:e9-e18
Logue, Mark W; Schu, Matthew; Vardarajan, Badri N et al. (2014) Search for age-related macular degeneration risk variants in Alzheimer disease genes and pathways. Neurobiol Aging 35:1510.e7-18

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