| Literature DB >> 33040337 |
Qing Lei1, Yang Li2, Hong-Yan Hou3, Feng Wang3, Zhu-Qing Ouyang1, Yandi Zhang1, Dan-Yun Lai2, Jo-Lewis Banga Ndzouboukou1, Zhao-Wei Xu2, Bo Zhang3, Hong Chen2, Jun-Biao Xue2, Xiao-Song Lin1, Yun-Xiao Zheng2, Zong-Jie Yao1, Xue-Ning Wang2, Cai-Zheng Yu4, He-Wei Jiang2, Hai-Nan Zhang2, Huan Qi2, Shu-Juan Guo2, Sheng-Hai Huang5, Zi-Yong Sun3, Sheng-Ce Tao2, Xiong-Lin Fan1.
Abstract
BACKGROUND: The missing asymptomatic COVID-19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. MEASURE: Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty-three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS-CoV-2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset.Entities:
Keywords: COVID-19; SARS-CoV-2; antibody dynamics; asymptomatic; neutralizing antibody
Mesh:
Substances:
Year: 2020 PMID: 33040337 PMCID: PMC7675426 DOI: 10.1111/all.14622
Source DB: PubMed Journal: Allergy ISSN: 0105-4538 Impact factor: 14.710
FIGURE 1The workflow of screening participants
Characteristics of study population
| All | Healthy controls | Asymptomatic(n = 63) | Mild(n = 51) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Aa(NAT + IgG−IgM−) | Ab(NAT + IgG + IgM−) | Ac(NAT−IgG + IgM−) | Ad(NAT−IgG + IgM+) | Ma(NAT + IgG−IgM−) | Mb(NAT + IgG + IgM−) | Mc(NAT + IgG + IgM+) | Md(NAT−IgG + IgM−) | Me(NAT−IgG + IgM+) | |||
| N | 177 | 63 | 4 | 8 | 28 | 23 | 6 | 10 | 22 | 4 | 9 |
| Age, years | |||||||||||
| Mean(SD) | 44.6(19.25) | 43.2(19.85) | 42.8(8.62) | 40.6(10.85) | 46.5(18.05) | 44.7(17.89) | 39.7(25.02) | 39.7(23.77) | 47.6(22.46) | 45.0(31.12) | 54.0(7.40) |
| Median(IQR) | 46(30‐59) | 46(27‐60) | 41(36‐50) | 38(31‐52) | 50(29‐58) | 40(29‐55) | 38(29‐46) | 32(20‐58) | 51(30‐64) | 56(25‐66) | 55(48‐59) |
| Sex, n(%) | |||||||||||
| Male | 85(48.0) | 33(52.4) | 0(0.0) | 2(25.0) | 13(46.4) | 10(43.5) | 3(50.0) | 6(60.0) | 11(50.0) | 3(75.0) | 4(44.4) |
| Female | 92(52.0) | 30(47.6) | 4(100.0) | 6(75.0) | 15(53.6) | 13(56.5) | 3(50.0) | 4(40.0) | 11(50.0) | 1(25.0) | 5(55.6) |
Abbreviations: IQR, interquartile range; SD, standard deviation.
FIGURE 2Antibody responses to different proteins of SARS‐CoV‐2. Serum proteome microarray was used to probe IgM or IgG antibody against 20 proteins of SARS‐CoV‐2 in all samples collected from 63 healthy controls, 63 asymptomatic individuals, and 51 mild patients. The results were expressed as mean {log2 (Fluorescence intensity)} ± SD in different groups. A, Comparison of IgM responses to five proteins among three groups. B, Comparison of IgG responses to five proteins among three groups. Both analysis of variance (ANOVA) and post hoc test (SNK) were conducted to test difference in means among healthy controls, asymptomatics, and mild patients. ***P < .001, **P < .01, *P < .05, and ns indicating no significance
FIGURE 3Dynamic changes of S1‐ and N‐specific IgM and IgG responses. Serum proteome microarray was used to probe antibody responses in the samples collected from 48 healthy individuals, 36 asymptomatic individuals, and 51 mild patients. The result of each serum sample was expressed as log2 (fluorescence intensity). 48 healthy controls and 36 asymptomatic infections having clear exposure history were plotted in sections according to the exposure time. 51 mild COVID‐19 patients with serial sera samples (n = 87) were segmented according to days after symptoms onset. The yellow, green and blue line showed the mean level of antibody responses in healthy controls, asymptomatic infections and mild patients, respectively. A, Dynamic changes of S1‐ and N‐specific IgM responses. B, Dynamic changes of S1‐ and N‐specific IgG responses
FIGURE 4Neutralizing antibody responses and dynamics. The titer of neutralization antibody for each serum sample was expressed as the half‐maximal neutralizing titer (NT50), which was calculated by using nonlinear regression of SPSS. The results were shown as the medians of NT50 and interquartile ranges (IQRs) in different groups. A, Comparison of NT50 among healthy controls, asymptomatic infections and mild patients. B, Comparison of NT50 among different subgroups with that of healthy controls. C, Dynamic changes of NT50 for 48 healthy controls and 36 asymptomatic individuals over exposure time. D, Dynamic changes of NT50 for 51 mild COVID‐19 patients with the day after symptom onset. A loess 489 regression model was used to established the kinetics of neutralizing antibody by R. The lines show the mean value expected from a Loess 489 regression model, and the ribbons indicate the 95% confidence interval. Serum samples with NT50 below 1:10 are plotted at NT50 = 2