Serology characteristics of SARS-CoV-2 infection after exposure and post-symptom onset

Abstract

Background: Timely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated.

Method: Serial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described.

Results: The seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0-7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays.

Conclusions: A typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.

FIGURE 1

Cumulative seroconversion rates and the dynamics of antibody levels since the onset of illness in 80 patients with COVID-19. a) The curves of the cumulative seroconversion rates for total antibody, IgM and IgG detected by ELISAs were plotted according to Kaplan-Meier methods. The serological status of patients was assigned to be negative before the time that the first sample was collected. b) The antibody levels were surrogated expressed using the relative binding signals compared to the cutoff value of each assay (S/CO). Four parameter logistic fitting curves were used to mimic the trends of antibody levels.

FIGURE 2

The total antibody dynamics of 45 patients with determined exposure time. The patients were listed according to their lasting time of incubation period, from shorter to longer. The clinical severity of each patient was described beside the patient ID. The red and blue symbols, “☻”, indicate the day of illness onset and hospital discharge respectively. “0” represents for total antibody undetectable at the time, and “1” for total antibody detectable. The gray bar indicates the incubation period. The serological status of each patient was presented only during the period of sample collection, without backward or forward extension. The green and orange bars represent for the periods with undetectable antibody (antibody negative period) and detectable antibody (antibody positive period) respectively, while the yellow bar showed the seroconversion period, during the period the seroconversion occurred.

FIGURE 3

Cumulative seroconversion rates and the dynamics of antibody levels since the onset of illness in 45 patients with COVID-19. a) The curves of the cumulative seroconversion rates for total antibody, IgM and IgG detected by ELISAs were plotted according to Kaplan-Meier methods. The serological status of patients was assigned to be negative before the time that the first sample was collected. For patients with a positive result of the first collected sample, the sero-status before the time that the first sample was collected is unknown and assigned as negative. The number of these patients at indicated days after exposure is shown in the brackets. b) The antibody levels were surrogated expressed using the relative binding signals compared to the cutoff value of each assay (S/CO). Four parameter logistic fitting curves were used to mimic the trends of antibody levels.