Alzheimer's disease (AD) is the most common neurodegenerative disease, afflicting over 4 million people over the age of 65 years, in the U.S. Current medications treat the symptoms but not the underlying causes of disease. There is therefore an urgent need to understand the pathogenic mechanisms of disease to enable rational drug design. During the last twenty years genetic studies of familial early onset AD have dramatically changed our understanding of the disease by demonstrating that mutations in three different genes cause disease via a common biochemical pathway involving B-amyloid (Ali) metabolism. Genetic epidemiology has demonstrated that late onset AD (LOAD) also has a strong genetic component. However, to date only the e4 allele of apolipoprotein E, present in only 50% of LOAD cases, has been convincingly demonstrated to influence risk for LOAD. There is therefore a clear need for new approaches to understanding the genetics of LOAD. We will use intermediate traits, or endophenotypes to identify novel genetic risk factors for LOAD. Endophenotypes may be continuous variables that are correlated with disease but measurable in many or all individuals, avoiding the heterogeneity associated with clinical diagnoses and allowing the use of quantitative statistical methods. Endophenotypes may also provide a biological model of disease and the possible effects of the associated genetic variation. Several promising endophenotypes are protein biomarkers found in cerebrospinal fluid (CSF) including amyloid-beta (A(3), tau, serpin peptidase inhibitor, clade C (antithrombin), member 1 (ATI11), serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 3 (ACT), carnosine dipeptidase 1 (CNDP1) andA-2- glycoprotein 1, zinc (ZAG). These proteins are present in all individuals, show variability amongnon- demented individuals and change with disease. The goal of this study is to identify cis-acting genetic variation that is associated with CSF levels of these AD biomarkers, and to test in independent datasets whether this variation also influences age at onset of AD or risk for AD. Functional studies will be employed to determine the biological effects of the associated genetic variation. These data will inform our models of age at onset of AD, AD diagnosis (project 2) and our studies of the interaction between preclinical AD and post-stroke dementia (project 1). As a proof of principle regarding this approach we have already identified genetic variants in A/MPTthat show significant association with both CSF tau and ptau181 levels. Further study shows that this association is limited to individuals with evidence of A(3deposition. Genetic variation in this region also appears to be associated with expression levels of tau mRNA in individuals with amyloid deposition and age at onset of LOAD.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Program Projects (P01)
Project #
5P01AG003991-28
Application #
8215307
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
2011-01-01
Budget End
2011-12-31
Support Year
28
Fiscal Year
2011
Total Cost
$101,168
Indirect Cost
Name
Washington University
Department
Type
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Sato, Chihiro; Barthélemy, Nicolas R; Mawuenyega, Kwasi G et al. (2018) Tau Kinetics in Neurons and the Human Central Nervous System. Neuron 97:1284-1298.e7
Day, Gregory S; Gordon, Brian A; Perrin, Richard J et al. (2018) In vivo [18F]-AV-1451 tau-PET imaging in sporadic Creutzfeldt-Jakob disease. Neurology 90:e896-e906
Vardarajan, Badri N; Barral, Sandra; Jaworski, James et al. (2018) Whole genome sequencing of Caribbean Hispanic families with late-onset Alzheimer's disease. Ann Clin Transl Neurol 5:406-417
Lewczuk, Piotr; Riederer, Peter; O'Bryant, Sid E et al. (2018) Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry. World J Biol Psychiatry 19:244-328
Pottier, Cyril; Zhou, Xiaolai; Perkerson 3rd, Ralph B et al. (2018) Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study. Lancet Neurol 17:548-558
Joseph-Mathurin, Nelly; Su, Yi; Blazey, Tyler M et al. (2018) Utility of perfusion PET measures to assess neuronal injury in Alzheimer's disease. Alzheimers Dement (Amst) 10:669-677
Del-Aguila, Jorge L; Fernández, Maria Victoria; Schindler, Suzanne et al. (2018) Assessment of the Genetic Architecture of Alzheimer's Disease Risk in Rate of Memory Decline. J Alzheimers Dis 62:745-756
Oxtoby, Neil P; Young, Alexandra L; Cash, David M et al. (2018) Data-driven models of dominantly-inherited Alzheimer's disease progression. Brain 141:1529-1544
Mishra, Shruti; Blazey, Tyler M; Holtzman, David M et al. (2018) Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ?4 genotype. Brain 141:1828-1839
Bonham, Luke W; Karch, Celeste M; Fan, Chun C et al. (2018) CXCR4 involvement in neurodegenerative diseases. Transl Psychiatry 8:73

Showing the most recent 10 out of 911 publications