Serological Analysis of New York City COVID19 Convalescent Plasma Donors

medRxiv(2020)

引用 68|浏览24
暂无评分
摘要
BACKGROUND: The development of neutralizing antibodies (NAbs) against SARS-CoV-2, following infection or vaccination, is likely to be critical for the development of sufficient population immunity to drive cessation of the COVID19 pandemic. A large number of serologic tests, platforms and methodologies are being employed to determine seroprevalence in populations to select convalescent plasmas for therapeutic trials, and to guide policies about reopening. However, these tests have substantially variable sensitivity and specificity, and their ability to quantitatively predict levels of NAbs is unknown. METHODS: We determined levels of antibodies in convalescent plasma using commercially available SARS-CoV-2 detection tests and in-house ELISA assays and correlated those measurements with neutralization activity measured using pseudotyped virus particles, which offer the most informative assessment of antiviral activity of patient sera against viral infection. FINDINGS: Our data show that a large proportion of convalescent plasma samples have modest antibody levels and that commercially available tests have varying degrees of accuracy in predicting neutralizing activity. Nevertheless, we found particular commercially available tests are capable of accurately measuring levels of antibodies that strongly correlate with neutralization assays. INTERPRETATION: Our findings imply that SARS-CoV-2 convalescent plasma donors have a wide range of antibody concentrations. At present it is unclear how antibody acquisition, particularly for low titer individuals, might afford future immunity to SARS-CoV-2. Further research will be required to determine the minimum threshold of antibody and neutralization activity necessary to accurately predict immunity. Correlation of clinical antibody tests with neutralization activity in this study could serve as a valuable roadmap to guide the choice and interpretation of serological tests for SARS-CoV-2.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要