Development of an Immunoassay for the Detection of Amyloid Beta 1-42 and Its Application in Urine Samples

Amyloid beta peptides (Aβ1-42) have been found to be associated with the cause of Alzheimer’s disease (AD) and dementia. Currently, methods for detecting Aβ1-42 are complicated and expensive. The present study is aimed at developing an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA...

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Published inJournal of Immunology Research Vol. 2020; no. 2020; pp. 1 - 9
Main Authors Wang, Hong, Sringarm, Korawan, Sapbamrer, Ratana, Pattarawarapan, Mookda, Chantara, Somporn, Hongsibsong, Surat, Wongta, Anurak, Xu, Zhen-Lin
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
John Wiley & Sons, Inc
Hindawi Limited
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Summary:Amyloid beta peptides (Aβ1-42) have been found to be associated with the cause of Alzheimer’s disease (AD) and dementia. Currently, methods for detecting Aβ1-42 are complicated and expensive. The present study is aimed at developing an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) to detect Aβ1-42 by using a polyclonal antibody from alpaca, an application used in urine samples. The serum was collected from the alpaca after immunizing it with Aβ1-42 at 500 μg/injection 5 times. The ic-ELISA was developed and showed a half-maximal inhibitory concentration (IC50) of 103.20 ng/ml. The limit of detection (LOD) was 0.39 ng/100 μl. The cross-reactivity was tested with Aβ1-40 and 8 synthesized peptides that had sequence similarities to parts of Aβ1-42. The cross-reactivity of Aβ1-40 and peptide 1 (DAEFRHDSGYE) was 55% and 69.4%, respectively. The ic-ELISA was applied to analyze Aβ1-42 in the urine and precipitated protein urine samples. This method can be used for detecting a normal level of total soluble Aβ (approximately 1 ng in 5 mg of precipitated urine protein) and can be used for detecting the early stages of AD. It is considered to be an easy and inexpensive method for monitoring and diagnosing AD.
Bibliography:Academic Editor: Xiao Feng Yang
ISSN:2314-8861
2314-7156
DOI:10.1155/2020/8821181