Department of Genetics, Harvard Medical School, Boston, MA, USA.
Howard Hughes Medical Institute, Division of Genetics, Brigham and Women's Hospital, Program in Virology, Harvard Medical School, Boston, MA, USA.
Science. 2020 Nov 27;370(6520). doi: 10.1126/science.abd4250. Epub 2020 Sep 29.
Understanding humoral responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for improving diagnostics, therapeutics, and vaccines. Deep serological profiling of 232 coronavirus disease 2019 (COVID-19) patients and 190 pre-COVID-19 era controls using VirScan revealed more than 800 epitopes in the SARS-CoV-2 proteome, including 10 epitopes likely recognized by neutralizing antibodies. Preexisting antibodies in controls recognized SARS-CoV-2 ORF1, whereas only COVID-19 patient antibodies primarily recognized spike protein and nucleoprotein. A machine learning model trained on VirScan data predicted SARS-CoV-2 exposure history with 99% sensitivity and 98% specificity; a rapid Luminex-based diagnostic was developed from the most discriminatory SARS-CoV-2 peptides. Individuals with more severe COVID-19 exhibited stronger and broader SARS-CoV-2 responses, weaker antibody responses to prior infections, and higher incidence of cytomegalovirus and herpes simplex virus 1, possibly influenced by demographic covariates. Among hospitalized patients, males produce stronger SARS-CoV-2 antibody responses than females.
了解严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)的体液反应对于改进诊断、治疗和疫苗至关重要。使用 VirScan 对 232 名新型冠状病毒肺炎(COVID-19)患者和 190 名 COVID-19 前时代对照者进行深度血清学分析,揭示了 SARS-CoV-2 蛋白组中的 800 多个表位,包括 10 个可能被中和抗体识别的表位。对照者中的预先存在的抗体识别 SARS-CoV-2 的 ORF1,而只有 COVID-19 患者的抗体主要识别刺突蛋白和核蛋白。基于 VirScan 数据训练的机器学习模型以 99%的敏感性和 98%的特异性预测 SARS-CoV-2 的暴露史;从最具区分力的 SARS-CoV-2 肽开发了一种快速的 Luminex 诊断方法。COVID-19 病情更严重的个体表现出更强和更广泛的 SARS-CoV-2 反应,对先前感染的抗体反应较弱,巨细胞病毒和单纯疱疹病毒 1 的发生率较高,这可能受到人口统计学协变量的影响。在住院患者中,男性比女性产生更强的 SARS-CoV-2 抗体反应。