RESUMEN
The COVID-19 pandemic has highlighted the urgent need for accurate, rapid, and cost-effective diagnostic methods to identify and track the disease. Traditional diagnostic methods, such as PCR and serological assays, have limitations in terms of sensitivity, specificity, and timeliness. To investigate the potential of using protein-peptide hybrid microarray (PPHM) technology to track the dynamic changes of antibodies in the serum of COVID-19 patients and evaluate the prognosis of patients over time. A discovery cohort of 20 patients with COVID-19 was assembled, and PPHM technology was used to track the dynamic changes of antibodies in the serum of these patients. The results were analyzed to classify the patients into different disease severity groups, and to predict the disease progression and prognosis of the patients. PPHM technology was found to be highly effective in detecting the dynamic changes of antibodies in the serum of COVID-19 patients. Four polypeptide antibodies were found to be particularly useful for reflecting the actual status of the patient's recovery process and for accurately predicting the disease progression and prognosis of the patients. The findings of this study emphasize the multi-dimensional space of peptides to analyze the high-volume signals in the serum samples of COVID-19 patients and monitor the prognosis of patients over time. PPHM technology has the potential to be a powerful tool for tracking the dynamic changes of antibodies in the serum of COVID-19 patients and for improving the diagnosis and prognosis of the disease.
RESUMEN
Characterizing the serologic features of asymptomatic SARS-CoV-2 infection is imperative to improve diagnostics and control of SARS-CoV-2 transmission. In this study, we evaluated the antibody profiles in 272 plasma samples collected from 59 COVID-19 patients, consisting of 18 asymptomatic patients, 33 mildly ill patients and 8 severely ill patients. We measured the IgG against five viral structural proteins, different isotypes of immunoglobulins against the Receptor Binding Domain (RBD) protein, and neutralizing antibodies. The results showed that the overall antibody response was lower in asymptomatic infections than in symptomatic infections throughout the disease course. In contrast to symptomatic patients, asymptomatic patients showed a dominant IgG-response towards the RBD protein, but not IgM and IgA. Neutralizing antibody titers had linear correlations with IgA/IgM/IgG levels against SARS-CoV-2-RBD, as well as with IgG levels against multiple SARS-CoV-2 structural proteins, especially with anti-RBD or anti-S2 IgG. In addition, the sensitivity of anti-S2-IgG is better in identifying asymptomatic infections at early time post infection compared to anti-RBD-IgG. These data suggest that asymptomatic infections elicit weaker antibody responses, and primarily induce IgG antibody responses rather than IgA or IgM antibody responses. Detection of IgG against the S2 protein could supplement nucleic acid testing to identify asymptomatic patients. This study provides an antibody detection scheme for asymptomatic infections, which may contribute to epidemic prevention and control.