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Do anti-amyloid beta protein antibody cross reactivities confound Alzheimer disease research?

Overview of attention for article published in Journal of Negative Results in BioMedicine, January 2017
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Title
Do anti-amyloid beta protein antibody cross reactivities confound Alzheimer disease research?
Published in
Journal of Negative Results in BioMedicine, January 2017
DOI 10.1186/s12952-017-0066-3
Pubmed ID
Authors

Sally Hunter, Carol Brayne

Abstract

Alzheimer disease (AD) research has focussed mainly on the amyloid beta protein (Aβ). However, many Aβ-and P3-type peptides derived from the amyloid precursor protein (APP) and peptides thought to derive from Aβ catabolism share sequence homology. Additionally, conformations can change dependent on aggregation state and solubility leading to significant uncertainty relating to interpretations of immunoreactivity with antibodies raised against Aβ. We review evidence relating to the reactivities of commonly used antibodies including 6F3D, 6E10 and 4G8 and evaluate their reactivity profiles with respect to AD diagnosis and research. Antibody cross-reactivities between Aβ-type, P3-type and Aβ-catabolic peptides confound interpretations of immunoreactivity. More than one antibody is required to adequately characterise Aβ. The relationships between anti-Aβ immunoreactivity, neuropathology and proposed APP cleavages are unclear. We find that the concept of Aβ lacks clarity as a specific entity. Anti-Aβ antibody cross-reactivities lead to significant uncertainty in our understanding of the APP proteolytic system and its role in AD with profound implications for current research and therapeutic strategies.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 98 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 23%
Researcher 20 20%
Student > Master 10 10%
Student > Bachelor 8 8%
Professor 4 4%
Other 11 11%
Unknown 23 23%
Readers by discipline Count As %
Neuroscience 28 28%
Agricultural and Biological Sciences 12 12%
Biochemistry, Genetics and Molecular Biology 9 9%
Medicine and Dentistry 6 6%
Chemistry 5 5%
Other 11 11%
Unknown 28 28%