Development of high sensitivity nanobody for determining biomarker of Alzheimer’s disease and chlorpyrifos exposure

Abstract

The objectives of this study composed of 3 parts as follows; Part one was to develop a method for immunoassay for the determination of amyloid-beta 1-42 by using produced nanobodies and their application in urine samples. Part two was to analyze the biomarkers of exposure to chlorpyrifos in the urine samples of farmers and consumers. Part three involved exploring the relationship between a biomarker of AD and CPS among farmers and consumers who lived in the study area. In part one, sandwich ELISA was developed for the detection of Aβ1-42. After alpaca was immunized with antigen, a specific nanobody to Aβ1-42 was produced from PBLs of immunized alpaca using the phage biopanning technique. The obtained EC50 was 1.69 µg/mL. Another ic-ELISA was developed based on pAb of alpaca, which showed IC50 was 164.2 ng/mL and cross-reaction to Aβ1-40 and Aβ1-8 at 59.4 and 41.6%, respectively. The average recovery of Aβ1-42 was 105.6%, intra-assay CV and interassay CV were 3.6 - 6.9% and 2.8 - 8.2%, respectively. LoD and LoQ of ic-ELISA were 0.03 and 0.1 µg/mL, respectively. In part two, metabolites of CPS and OPs in urine samples of 84 farmers and 44 consumers in an agricultural area, San Pa Thong, Ching Mai, were determined using GCFPD. The results of OPs metabolites detection that including DMP, DMTP, DMDTP, DEP, DETP, and DEDTP showed that at least one metabolite was found in any urine samples and no significant difference of each metabolite between farmers and consumers. In part three, characteristics data and pesticides used the behavior of 128 participants were collected by interview. Cognitive decline test was performed using MMSE Thai 2002, detection of Aβ1-42 in urine samples was performed using developed ic-ELISA and used as a biomarker of AD. The results showed that all characteristics, including sex, age, education level, years in pesticide usage, and farming occupational, had been associated with cognitive decline in this study. The relationship between the biomarkers of exposure and cognitive decline showed that the high DEP concentration was significantly correlated with the low MMSE score. At the same time, the relationship between biomarkers of exposure and biomarker of AD could not be analyzed because of the undetectable results of Aβ1-42 in urine samples by ic-ELISA.