Document Type

Article

Publication Title

Journal of Unexplored Medical Data

Abstract

Aim:

Platelets provide substantial information about the proteolytic system profile in neurodegenerative diseases. Assessment of autophagy and proteasome target proteins in platelets may reflect the tissue proteolytic machinery profile in the central nervous system of patients with Alzheimer’s disease (AD). We aimed to demonstrate the optimum assay conditions and identify target proteins in platelet proteolytic machinery.

Methods:

Platelet samples were obtained from clinically verified AD patients and age-matched non-demented control subjects who were recruited by the University of Kansas Alzheimer’s disease Center. Autophagosome participating proteins in platelets were identified by Western blotting analysis. Standard gel electrophoresis and electro transfer apparatus were used for protein transfer onto the membrane. Several antibodies were tested to identify the best working antibodies, and their concentrations were optimized. An enzyme-linked immunosorbent assay kit was used for platelet proteasome protein determination. Infrared imaging technology was used for visualizing the proteins on the membrane.

Results:

Autophagosome participating proteins showed elevated levels in AD patient platelet cytosol. Only light chain 3-1 autophagosome protein levels were significantly elevated. The concentrations of platelet lysate proteasome were assessed. AD patient’s proteasome levels were elevated but they were statistically not different from controls.

Conclusion:

Platelets can be used for assessing whether the proteolytic system is functional. Blood-based sampling from human donors is less-invasive and analyzing the platelet proteolytic system profile may help to develop pharmaceutical intervention approaches for neurodegenerative diseases in general.

DOI

10.20517/2572-8180.2019.08

Publication Date

2-14-2020

Keywords

Autophagy, proteasome, platelets, Alzheimer’s disease, protein aggregation, TDP-43, neurodegeneration

ISSN

2572-8180

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