key: cord-0942028-2tmnhl00
authors: Ma, Huan; Zeng, Weihong; He, Hongliang; Zhao, Dan; Jiang, Dehua; Zhou, Peigen; Cheng, Linzhao; Li, Yajuan; Ma, Xiaoling; Jin, Tengchuan
title: Serum IgA, IgM, and IgG responses in COVID-19
date: 2020-05-28
journal: Cell Mol Immunol
DOI: 10.1038/s41423-020-0474-z
sha: 4e56e013678d44b9e5788bf317a23a42e151825a
doc_id: 942028
cord_uid: 2tmnhl00

nan

99.7%, respectively. This is better than those when IgM and IgG kits are combined using our data or the previous data shown by others. [1] [2] [3] [4] In order to investigate the seroconversion during COVID-19 pathogenesis, all the data from 216 sera samples were divided into six groups according to the time windows of collection after illness onset (Fig. 1d) . At 4-10 days after symptom onset, the IgA kit exhibited the highest positive diagnostic rate as 88.2% (15/17), while IgM and IgG kit showed detection rates of 76.4% (13/17) and 64.7% (11/17), respectively. The 2 sera diagnosed as negative in the 4-10 days group by IgA kit were collected at the 4th day after illness onset, all other sera includes 2 at the 6th day, 3 at the 7th day, 1 at the 8th day, 6 at the 9th day, and 3 at 10th day after illness onset were tested as positive. In the group of 11-41 days after symptom onset, both RBD IgA and IgG kit showed the same positive diagnostic rate of 99.5% (198/199) . In contrast, IgM kit somehow showed a relatively lower positive diagnostic rate as 98.5% (196/199) . These results suggest that including IgA in a test provides better diagnostic outcome in early stages. Overall, the medium seroconversion time for IgA, IgM, and IgG are 4-6, 4-6, and 5-10 days post symptom onset, respectively, if tested with the RBD-kits described in this study. While it generally follows a typical seroconversion and immunoglobulin class switching time course, our kits provides an early diagnosis solution due to high sensitivities.

To better understand the trends of antibody levels in all of the 87 COVID-19 patients (some of them contributed multiple samples), we plotted the median RLU reading according the time windows when sera were collected (Fig. 1e ). IgA detection shows the highest sensitivity during about 4-25 days after illness onset. The median RLU of RBD-specific IgA reached the peak during 16-20 days after illness onset, and then began to decline but remained at relatively high reading until 31-41 days. The median RLU of RBD-specific IgG was the lowest in early disease stages but raised at 15 days post illness onset, the IgG reached its peak during 21-25 days after illness onset, and stayed at a relatively high reading until 31-41 days, suggesting that IgG is powerful for diagnostics at later stages. Although IgM reached its peak at early stages, the RLU reading was lower than that of IgA or IgG. We further divided the 87 patients into three severity groups based on established clinical classifications. Consistent with a previous report, 7 we found that COVID-19 severity is correlated positively with age in our cohort (Supplementary Fig. 3) . Patients with severe symptoms were significantly older (median age of 62.5) than those patients with moderate (median age of 46) and mild symptoms (median age of 30), as expected. We used the data of antibody levels at the period of 16-25 days after illness onset, when all of the three isotypes reached or were near their peaks (Fig. 1e) . If there were more than one data points, the average value was taken. Serum IgM and IgG levels in moderate and severe COVID-19 patients were significantly higher than mild cases, while no significant difference was observed between severe and moderate patients (Fig. 1g, h) . However, we found that IgA levels in severe cases were significantly higher than those mild or moderate cases (Fig. 1f) . The molecular mechanism of this observation warrants future studies.

There are some limitations in this study at the current form. We used 216 serum samples from 87 confirmed COVID-19 patients in this study, and serum samples were not available every day for each patient. The earliest serum was collected at the 4th day, and last one was at the 41th day after self-reported illness onset. There are only 17 cases of serum samples collected within the first 10 days after illness onset; which consequently influenced the accuracy. Similarly, there were only 23 cases of serum samples taken after 30 days post illness onset, hampering an analysis of long-term antibody levels in recovered patients. We are currently following up some of the 87 convalescent COVID-19 patients who are willing to participate in further study. Nevertheless, this study provide valuable information regarding COVID-19 serological testing and seroconversion responses, especially for IgA antibodies.

Molecular and serological investigation of 2019-nCoV infected patients: implication of multiple shedding routes

Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study

Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019

Development and clinical application of a rapid IgM-IgG combined antibody test for SARS-CoV-2 infection diagnosis

Profiling early humoral response to diagnose novel coronavirus disease (COVID-19)

IgA-Ab response to spike glycoprotein of SARS-CoV-2 in patients with COVID-19: a longitudinal study

Virological assessment of hospitalized patients with COVID-2019

The online version of this article (https://doi.org/10.1038/s41423-020-0474-z) contains supplementary material.Competing interests: Dehua Jiang is an employee of Kangrun Biotech LTD (Guangzhou, China). Tengchuan Jin, Huan Ma, Weihong Zeng in USTC and Dehua Jiang have applied a joining patent related to the antibody detecting kits. Other authors declare that they have no conflicts of interest.Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/.