Neutralizing Antibodies Against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants Induced by Natural Infection or Vaccination: A Systematic Review and Pooled Analysis

CLINICAL INFECTIOUS DISEASES(2022)

引用 81|浏览51
摘要
Recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants may pose a threat to immunity. A systematic landscape of neutralizing antibodies against emerging variants is needed. We systematically searched for studies that evaluated neutralizing antibody titers induced by previous infection or vaccination against SARS-CoV-2 variants and collected individual data. We identified 106 studies meeting the eligibility criteria. Lineage B.1.351 (beta), P.1 (gamma) and B.1.617.2 (delta) significantly escaped natural infection-mediated neutralization, with an average of 4.1-fold (95% confidence interval [CI]: 3.6-4.7-fold), 1.8-fold (1.4-2.4-fold), and 3.2-fold (2.4-4.1-fold) reduction in live virus neutralization assay, while neutralizing titers against B.1.1.7 (alpha) decreased slightly (1.4-fold [95% CI: 1.2-1.6-fold]). Serum from vaccinees also led to significant reductions in neutralization of B.1.351 across different platforms, with an average of 7.1-fold (95% CI: 5.5-9.0-fold) for nonreplicating vector platform, 4.1-fold (3.7-4.4-fold) for messenger RNA platform, and 2.5-fold (1.7-2.9-fold) for protein subunit platform. Neutralizing antibody levels induced by messenger RNA vaccines against SARS-CoV-2 variants were similar to, or higher, than that derived from naturally infected individuals. Antibody response established by infection or vaccination might enable effectively neutralize B.1.1.7 (alpha), but with large reductions in neutralizing titers against B.1.351 (beta), B.1.617.2 (delta) and P.1 (gamma). Standardized protocols for neutralization assays and updated prevention and treatment are needed.
更多
查看译文
关键词
natural infection, neutralizing antibodies, SARS-CoV-2 variants, vaccination
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn