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 #
5U01AG032984-05
Application #
8670681
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
2014-04-01
Budget End
2015-03-31
Support Year
5
Fiscal Year
2014
Total Cost
$3,247,012
Indirect Cost
$518,706
Name
University of Pennsylvania
Department
Pathology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Larsson, Susanna C; Markus, Hugh S (2017) Branched-chain amino acids and Alzheimer's disease: a Mendelian randomization analysis. Sci Rep 7:13604
Deming, Yuetiva; Li, Zeran; Kapoor, Manav et al. (2017) Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers. Acta Neuropathol 133:839-856
Monsell, Sarah E; Mock, Charles; Fardo, David W et al. (2017) Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology. Alzheimer Dis Assoc Disord 31:232-238
Mez, Jesse; Chung, Jaeyoon; Jun, Gyungah et al. (2017) Two novel loci, COBL and SLC10A2, for Alzheimer's disease in African Americans. Alzheimers Dement 13:119-129
Nordestgaard, Liv Tybjærg; Tybjærg-Hansen, Anne; Nordestgaard, Børge G et al. (2017) Body Mass Index and Risk of Alzheimer's Disease: A Mendelian Randomization Study of 399,536 Individuals. J Clin Endocrinol Metab 102:2310-2320
Sennik, Simrin; Schweizer, Tom A; Fischer, Corinne E et al. (2017) Risk Factors and Pathological Substrates Associated with Agitation/Aggression in Alzheimer's Disease: A Preliminary Study using NACC Data. J Alzheimers Dis 55:1519-1528
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
LoBue, Christian; Wadsworth, Hannah; Wilmoth, Kristin et al. (2017) Traumatic brain injury history is associated with earlier age of onset of Alzheimer disease. Clin Neuropsychol 31:85-98
Katsumata, Yuriko; Nelson, Peter T; Ellingson, Sally R et al. (2017) Gene-based association study of genes linked to hippocampal sclerosis of aging neuropathology: GRN, TMEM106B, ABCC9, and KCNMB2. Neurobiol Aging 53:193.e17-193.e25
Miller, Jeremy A; Guillozet-Bongaarts, Angela; Gibbons, Laura E et al. (2017) Neuropathological and transcriptomic characteristics of the aged brain. Elife 6:

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