Sensitive Detection of Total Anti-Spike Antibodies and Isotype Switching in Asymptomatic and Symptomatic COVID-19 Patients
Social Science Research Network(2020)
摘要
Early detection of infections is crucial to limit the spread of coronavirus 2019 disease (COVID-19). Here, we developed a flow cytometry-based assay to detect SARS-CoV-2 Spike protein (S protein) antibodies in COVID-19 patients. The assay detected specific IgM and IgG in COVID-19 patients and also the acquisition of all IgG subclasses, with IgG1 being the most dominant. The antibody response was significantly higher at a later stage of the infection. Furthermore, asymptomatic COVID-19 patients also developed specific IgM and IgG, with IgG1 as the most dominant subclass. Although the antibody levels were lower in asymptomatic infections, the assay was highly sensitive and detected 97% of asymptomatic infections. These findings demonstrated that the assay could be used for serological analysis of symptomatic patients, and also as a sensitive tool to detect asymptomatic infections, which may go undetected.
Funding: Biomedical Research Council (BMRC), the A*ccelerate GAP-funded project (ACCL/19-GAP064-R20H-H) from Agency of Science, Technology and Research (A*STAR), and National Medical Research Council (NMRC) COVID-19 Research fund (COVID19RF-001, COVID-19RF-007, COVID-19RF-60).
Conflict of Interest: The authors declare no competing interests.
Ethical Approval: The study design and protocols for COVID-19, recovered SARS and seasonal human CoV patient cohorts were approved by National Healthcare Group (NHG) Domain Specific Review Board (DSRB) and performed, following ethical guidelines in the approved studies 2012/00917, 2020/00091 and 2020/00076 respectively. Healthy donor samples were collected in accordance with approved studies 2017/2806 and NUS IRB 04-140. Written informed consent was obtained from participants in accordance with the Declaration of Helsinki for Human Research.
更多查看译文
关键词
antibodies,anti-spike
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要