ABSTRACT
Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac®) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC's potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning.
ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus-2.COVID-19 is highly pathogenic and infectious. COVID-19 epidemic is still spreading all over the world, and there is no sign of stopping at present. There is no specific cure for this disease, and the clinical management mainly depends on supportive treatment. Xiyanping is widely used in treating COVID-19 in China. However, there is no evidence that Xiyanping is effective and safe for COVID-19. METHODS: A comprehensive literature search will be conducted. Two methodological trained researchers will read the title, abstract, and full texts and independently select the qualified literature according to inclusion and exclusion criteria. After assessment of the risk of bias and data extraction, we will conduct meta-analysis for outcomes related to COVID-19. The heterogeneity of data will be investigated by Cochrane X and I tests. Then publication bias assessment will be conducted by funnel plot analysis and Egger test. RESULTS: The results of our research will be published in a peer-reviewed journal. CONCLUSION: Our study aims to systematically present the clinical evidence of Xiyanping in the treatment of COVID-19, which will be of guiding significance for further research and clinical practice. OPEN SCIENCE FRAMEWORK REGISTRATION NUMBER: 10.17605/OFS.IO/SW75F.