Association between serum inflammatory parameters and the disease severity in COVID-19 patients.

OBJECTIVE: Most patients infected with the novel coronavirus (SARS-CoV-2), as the causative agent of COVID-19 disease, show mild symptoms, but some of them develop severe illness. The purpose of this study was to analyze the blood markers of COVID-19 patients and to investigate the correlation between serum inflammatory cytokines and the disease severity. METHODS: In this prospective cross-sectional study, 50 patients with COVID-19 and 20 patients without COVID-19 were enrolled. According to ICU admission criteria, patients were divided into two groups of non-severe and severe. Differences in the serum levels of C-reactive protein (CRP), IL-6, and TNF-α, as well as erythrocyte sedimentation rate (ESR), lymphocytes (LYM) count, and neutrophils (NEU) count between the two groups were determined and analyzed. RESULTS: Out of the 50 patients with COVID-19, 14 were diagnosed as severe cases. There was no significant difference between the two groups of COVID-19 patients in terms of gender and age. Blood tests of COVID-19 patients showed a significant decrease and increase in NEU and LYM counts, respectively. There were significant differences in the serum levels of IL-6, TNF-α, and CRP between the severe and non-severe groups, which were higher in the severe group. Also, there was a significant correlation between the disease severity and CRP with ESR (r = 0.79), CRP with IL-6 (r = 0.74), LYM with NEU (r = -0.97), and ESR with TNF-α (r = 0.7). CONCLUSION: The findings of this study, as the first study in Iran, suggest that the levels of IL-6, TNF-α, ESR, and CRP could be used to predict the severity of COVID-19 disease.

Design of novel multiepitope constructs-based peptide vaccine against the structural S, N and M proteins of human COVID-19 using immunoinformatics analysis.

The causative agent of severe acute respiratory syndrome (SARS) reported by the Chinese Center for Disease Control (China CDC) has been identified as a novel Betacoronavirus (SARS-CoV-2). A computational approach was adopted to identify multiepitope vaccine candidates against SARS-CoV-2 based on S, N and M proteins being able to elicit both humoral and cellular immune responses. In this study, the sequence of the virus was obtained from NCBI database and analyzed with in silico tools such as NetMHCpan, IEDB, BepiPred, NetCTL, Tap transport/proteasomal cleavage, Pa3P, GalexyPepDock, I-TASSER, Ellipro and ClusPro. To identify the most immunodominant regions, after analysis of population coverage and epitope conservancy, we proposed three different constructs based on linear B-cell, CTL and HTL epitopes. The 3D structure of constructs was assessed to find discontinuous B-cell epitopes. Among CTL predicted epitopes, S257-265, S603-611 and S360-368, and among HTL predicted epitopes, N167-181, S313-330 and S1110-1126 had better MHC binding rank. We found one putative CTL epitope, S360-368 related to receptor-binding domain (RBD) region for S protein. The predicted epitopes were non-allergen and showed a high quality of proteasomal cleavage and Tap transport efficiency and 100% conservancy within four different clades of SARS-CoV-2. For CTL and HTL epitopes, the highest population coverage of the world's population was calculated for S27-37 with 86.27% and for S196-231, S303-323, S313-330, S1009-1030 and N328-349 with 90.33%, respectively. We identified overall 10 discontinuous B-cell epitopes for three multiepitope constructs. All three constructs showed strong interactions with TLRs 2, 3 and 4 supporting the hypothesis of SARS-CoV-2 susceptibility to TLRs 2, 3 and 4 like other Coronaviridae families. These data demonstrated that the novel designed multiepitope constructs can contribute to develop SARS-CoV-2 peptide vaccine candidates. The in vivo studies are underway using several vaccination strategies.