Early indications of the likelihood of severe coronavirus disease 2019 COVID-19 can influence treatments and could improve clinical outcomes. However, knowledge on the prediction markers of COVID-19 fatality risks remains limited. Here, we analyzed and quantified the reactivity of serum samples from acute (non-fatal and fatal) and convalescent COVID-19 patients with the spike surface glycoprotein (S protein) and nucleocapsid phosphoprotein (N protein) SARS-CoV-2 peptide libraries. Cytokine activation was also analyzed. We demonstrated that IgM from fatal COVID-19 serum reacted with several N protein peptides. In contrast, IgM from non-fatal serum reacted more with S protein peptides. Further, higher levels of p... More
Early indications of the likelihood of severe coronavirus disease 2019 COVID-19 can influence treatments and could improve clinical outcomes. However, knowledge on the prediction markers of COVID-19 fatality risks remains limited. Here, we analyzed and quantified the reactivity of serum samples from acute (non-fatal and fatal) and convalescent COVID-19 patients with the spike surface glycoprotein (S protein) and nucleocapsid phosphoprotein (N protein) SARS-CoV-2 peptide libraries. Cytokine activation was also analyzed. We demonstrated that IgM from fatal COVID-19 serum reacted with several N protein peptides. In contrast, IgM from non-fatal serum reacted more with S protein peptides. Further, higher levels of pro-inflammatory cytokines were found in fatal COVID-19 serum compared to non-fatal. Many of these cytokines were pro-inflammatory and chemokines. Differences in IgG reactivity from fatal and non-fatal COVID-19 sera were also demonstrated. Additionally, the longitudinal analysis of IgG reactivity with SARS-CoV-2 S and N protein identified peptides with the highest longevity in humoral immune response. Finally, using IgM antibody reactivity with S and N SARS-CoV-2 peptides and selected cytokines, we have identified a panel of biomarkers specific to patients with a higher risk of fatal COVID-19 compared with that of patients who survive. This panel could be used for the early prediction of COVID-19 fatality risk.
