The sequence of the Alzheimer amyloid peptide (beta-protein) is part of the sequence predicted from at least three distinct cDNA species which derive from the same gene by alternative splicing. Each of the two longer forms of the amyloid peptide precursors (APP) contains at least one additional sequence of 56 residues. The mechanism by which beta-protein derives from APPs is not known. However, evidence suggests that APP may be a cell surface and/or a secreted protein. We have hypothesized that amyloid peptide may derive as a result of abnormal post-translational processing of the APP including dysfunctional endocytosis, lysosomal degradation, recycling of cell-surface APP, or glycosylation. Recent work indicates that the three forms of APP may be differentially expressed both in different mammalian brains and within different regions of the human brain. Specifically, it seems that in both normal and AD brains the insert containing APPS are present only in the regions involved in plaque formation. We propose to use anti-APP antisera to (a) describe the topographical expression of the different APP forms in normal and AD brains, (b) since the insert containing APP seems to be absent from the rodent brain, we would like to study the expression of the APP 751 in transgenic mice and (c) determine the proteolytic modifications, phosphorylation, membrane interactions, endocytosis and lysosomal degradation of the APP. Production of beta-protein could be due to abnormalities involving any one of these pathways.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Specialized Center (P50)
Project #
5P50AG005138-07
Application #
3809198
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
1990
Total Cost
Indirect Cost
Name
Mount Sinai School of Medicine
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10029
Gallagher, Damien; Kiss, Alex; Lanctot, Krista et al. (2018) Depression and Risk of Alzheimer Dementia: A Longitudinal Analysis to Determine Predictors of Increased Risk among Older Adults with Depression. Am J Geriatr Psychiatry 26:819-827
Silverman, Jeremy M; Schmeidler, James (2018) Outcome age-based prediction of successful cognitive aging by total cholesterol. Alzheimers Dement 14:952-960
Haaksma, Miriam L; Calderón-Larrañaga, Amaia; Olde Rikkert, Marcel G M et al. (2018) Cognitive and functional progression in Alzheimer disease: A prediction model of latent classes. Int J Geriatr Psychiatry 33:1057-1064
Lin, Ming; Gong, Pinghua; Yang, Tao et al. (2018) Big Data Analytical Approaches to the NACC Dataset: Aiding Preclinical Trial Enrichment. Alzheimer Dis Assoc Disord 32:18-27
Ramsey, Christine M; Gnjidic, Danijela; Agogo, George O et al. (2018) Longitudinal patterns of potentially inappropriate medication use following incident dementia diagnosis. Alzheimers Dement (N Y) 4:1-10
Warren, Noel A; Voloudakis, Georgios; Yoon, Yonejung et al. (2018) The product of the ?-secretase processing of ephrinB2 regulates VE-cadherin complexes and angiogenesis. Cell Mol Life Sci 75:2813-2826
Tsartsalis, Stergios; Xekardaki, Aikaterini; Hof, Patrick R et al. (2018) Early Alzheimer-type lesions in cognitively normal subjects. Neurobiol Aging 62:34-44
Ridge, Perry G; Karch, Celeste M; Hsu, Simon et al. (2018) Correction to: Linkage, whole genome sequence, and biological data implicate variants in RAB10 in Alzheimer's disease resilience. Genome Med 10:4
Pimenova, Anna A; Raj, Towfique; Goate, Alison M (2018) Untangling Genetic Risk for Alzheimer's Disease. Biol Psychiatry 83:300-310
Kirson, Noam Y; Scott Andrews, J; Desai, Urvi et al. (2018) Patient Characteristics and Outcomes Associated with Receiving an Earlier Versus Later Diagnosis of Probable Alzheimer's Disease. J Alzheimers Dis 61:295-307

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