Background: Measurement of antibody titers directed against mosquito salivary antigens in blood samples has been proposed as an outcome measure to assess human exposure to vector bites. However, only a handful of antigens have been identified and the specificity and longitudinal dynamics of antibody responses are not well known. We report the protocol of a clinical trial of controlled exposure to mosquito bites that aims to identify and validate biomarkers of exposure to bites of mosquito vector species that transmit malaria and dengue in Southeast Asia and some other parts of the world. Methods: This study is an exploratory factorial randomized control trial of controlled exposure to mosquito bites with 10 arms corresponding to different species (Aedes aegypt, Ae. albopictus, Anopheles dirus, An. maculatus and An. minimus) and numbers of bites (35 or 305 bites in total over 6 weeks). Blood samples will be collected from study participants before, during and after mosquito biting challenges. Candidate peptides will be identified from published literature with antigen prediction algorithms using mosquito DNA sequence data and with immunoblotting assays carried out using protein extracts of dissected mosquito salivary glands and participants samples. Antibody titers against candidate peptides will be determined in participants samples with high-throughput cutting-edge immuno-assays. Quantification of the antibody response profile over time (including an estimate of the decay rate) and the effect of the number of bites on the antibody response will be determined using linear and logistic mixed-effects models for the continuous and the binary response, respectively. Conclusion: This research is expected to generate important knowledge for vector sero-surveillance and evaluation of vector-control interventions against malaria and dengue in the Greater Mekong Subregion. Registration: This study is registered with clinicaltrials.gov (NCT04478370) on July 20th, 2020.
10.12688/wellcomeopenres.19049.1
Wellcome Open Research
F1000 Research Ltd
23/03/2023
8
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