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. 2023 Jun 10;12(12):1601.
doi: 10.3390/cells12121601.

Analysis of Plasma Proteins Involved in Inflammation, Immune Response/Complement System, and Blood Coagulation upon Admission of COVID-19 Patients to Hospital May Help to Predict the Prognosis of the Disease

Daniele Castro di Flora  1   2 , Aline Dionizio  1 , Heloisa Aparecida Barbosa Silva Pereira  1 , Thais Francini Garbieri  1 , Larissa Tercilia Grizzo  1 , Thiago José Dionisio  1 , Aline de Lima Leite  3 , Licia C Silva-Costa  4 , Nathalia Rabelo Buzalaf  1 , Fernanda Navas Reis  1 , Virginia Bodelão Richini Pereira  5 , Deborah Maciel Cavalcanti Rosa  2 , Carlos Ferreira Dos Santos  1 , Marília Afonso Rabelo Buzalaf  1
Affiliations

Analysis of Plasma Proteins Involved in Inflammation, Immune Response/Complement System, and Blood Coagulation upon Admission of COVID-19 Patients to Hospital May Help to Predict the Prognosis of the Disease

Daniele Castro di Flora et al. Cells. .

Abstract

The development of new approaches allowing for the early assessment of COVID-19 cases that are likely to become critical and the discovery of new therapeutic targets are urgently required. In this prospective cohort study, we performed proteomic and laboratory profiling of plasma from 163 COVID-19 patients admitted to Bauru State Hospital (Brazil) between 4 May 2020 and 4 July 2020. Plasma samples were collected upon admission for routine laboratory analyses and shotgun quantitative label-free proteomics. Based on the course of the disease, the patients were divided into three groups: (a) mild (n = 76) and (b) severe (n = 56) symptoms, whose patients were discharged without or with admission to an intensive care unit (ICU), respectively, and (c) critical (n = 31), a group consisting of patients who died after admission to an ICU. Based on our data, potential therapies for COVID-19 should target proteins involved in inflammation, the immune response and complement system, and blood coagulation. Other proteins that could potentially be employed in therapies against COVID-19 but that so far have not been associated with the disease are CD5L, VDBP, A1BG, C4BPA, PGLYRP2, SERPINC1, and APOH. Targeting these proteins' pathways might constitute potential new therapies or biomarkers of prognosis of the disease.

Keywords: COVID-19; biomarker; plasma; prognosis; proteomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Experimental design of the study.
Figure 2
Figure 2
Functional distribution of proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with severe or mild COVID-19. Categories of proteins are based on the following GO annotation terms: biological process, immune system, and molecular function. Terms’ significance (Kappa = 0.4) and distribution were determined according to percentages based on the number of associated genes. The green region of the graph indicates upregulated proteins, and the red region indicates downregulated proteins.
Figure 3
Figure 3
Functional distribution of proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with critical or mild COVID-19. Categories of proteins are based on the following GO annotation terms: biological process, immune system, and molecular function. Terms’ significance (Kappa = 0.4) and distribution were determined according to percentages based on the number of associated genes. The green region of the graph indicates upregulated proteins, and the red region indicates downregulated proteins.
Figure 4
Figure 4
Functional distribution of proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with critical or severe COVID-19. Categories of proteins are based on the following GO annotation terms: biological process, immune system, and molecular function. Terms’ significance (Kappa = 0.4) and distribution were determined according to percentages based on the number of associated genes. The green region of the graph indicates upregulated proteins, and the red region indicates downregulated proteins.
Figure 5
Figure 5
Subnetwork created via String to establish the relationship between proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with severe or mild COVID-19. The color of the nodes indicates differences in expression of the respective protein defined by its genes. Light red and light green nodes indicate down- and upregulation in the severe group in comparison to mild. The grey nodes indicate interacting proteins that were offered by CYTOSCAPE but were not identified in the present study.
Figure 6
Figure 6
Subnetwork created via String to establish the relationship between proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with critical or mild COVID-19. The color of the nodes indicates differences in the expression of the respective protein defined by its genes. Light red and light green nodes indicate down- and upregulation in the critical group with respect to the mild group. The grey nodes indicate interacting proteins that were offered by CYTOSCAPE but were not identified in the present study.
Figure 7
Figure 7
Subnetwork created via String to establish the relationship between proteins identified with differential expression in the plasma of patients admitted to Bauru State Hospital, Brazil, between 4 May and 4 July 2020, who were diagnosed with critical or severe COVID-19. The color of the nodes indicates differences in the expression of the respective protein defined by genes. Light red and light green nodes indicate down- and upregulation in the critical group with respect to the severe group. The grey nodes indicate interacting proteins that were offered by CYTOSCAPE but were not identified in the present study.
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Grants and funding

We would like to thank the State of São Paulo Research Foundation (FAPESP, #2015/03965-2, #2018/12041-7, #2019/00098-7), the National Council for Scientific and Technological Development (CNPq, #302371/2018-4, #307986/2017-9 and #303986/2021-2), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001—for their financial support.