Exploratory analysis to identify the best antigen and the best immune biomarkers to study SARS-CoV-2 infection
BACKGROUND: Recent studies proposed the whole-blood based IFN-γ-release assay to study the antigen-specific SARS-CoV-2 response. Since the early prediction of disease progression could help to assess the optimal treatment strategies, an integrated knowledge of T-cell and antibody response lays the foundation to develop biomarkers monitoring the COVID-19. Whole-blood-platform tests based on the immune response detection to SARS-CoV2 peptides is a new approach to discriminate COVID-19-patients from uninfected-individuals and to evaluate the immunogenicity of vaccine candidates, monitoring the immune response in vaccine trial and supporting the serological diagnostics results. Here, we aimed to identify in the whole-blood-platform the best immunogenic viral antigen and the best immune biomarker to identify COVID-19-patients.
METHODS: Whole-blood was overnight-stimulated with SARS-CoV-2 peptide pools of nucleoprotein-(NP) Membrane-, ORF3a- and Spike-protein. We evaluated: IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12p70, IL-13, IL- 15, IL-17A, eotaxin, FGF, G-CSF, GM-CSF, IFN-γ, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF, RANTES, TNF-α, VEGF. By a sparse partial least squares discriminant analysis we identified the most important soluble factors discriminating COVID-19- from NO-COVID-19-individuals.
RESULTS: We identified a COVID-19 signature based on six immune factors: IFN-γ, IP-10 and IL-2 induced by Spike; RANTES and IP-10 induced by NP and IL-2 induced by ORF3a. We demonstrated that the test based on IP-10 induced by Spike had the highest AUC (0.85, p < 0.0001) and that the clinical characteristics of the COVID-19-patients did not affect IP-10 production. Finally, we validated the use of IP-10 as biomarker for SARS-CoV2 infection in two additional COVID-19-patients cohorts.
CONCLUSIONS: We set-up a whole-blood assay identifying the best antigen to induce a T-cell response and the best biomarkers for SARS-CoV-2 infection evaluating patients with acute COVID-19 and recovered patients. We focused on IP-10, already described as a potential biomarker for other infectious disease such as tuberculosis and HCV. An additional application of this test is the evaluation of immune response in SARS-CoV-2 vaccine trials: the IP-10 detection may define the immunogenicity of a Spike-based vaccine, whereas the immune response to the virus may be evaluated detecting other soluble factors induced by other viral-antigens.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:19 |
|---|---|
| Enthalten in: |
Journal of translational medicine - 19(2021), 1 vom: 26. Juni, Seite 272 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Petruccioli, Elisa [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Biomarkers |
|---|
| Anmerkungen: |
Date Completed 30.06.2021 Date Revised 17.03.2022 published: Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1186/s12967-021-02938-8 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM32721953X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM32721953X | ||
| 003 | DE-627 | ||
| 005 | 20231225200309.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1186/s12967-021-02938-8 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1090.xml |
| 035 | |a (DE-627)NLM32721953X | ||
| 035 | |a (NLM)34174875 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Petruccioli, Elisa |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Exploratory analysis to identify the best antigen and the best immune biomarkers to study SARS-CoV-2 infection |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 30.06.2021 | ||
| 500 | |a Date Revised 17.03.2022 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a BACKGROUND: Recent studies proposed the whole-blood based IFN-γ-release assay to study the antigen-specific SARS-CoV-2 response. Since the early prediction of disease progression could help to assess the optimal treatment strategies, an integrated knowledge of T-cell and antibody response lays the foundation to develop biomarkers monitoring the COVID-19. Whole-blood-platform tests based on the immune response detection to SARS-CoV2 peptides is a new approach to discriminate COVID-19-patients from uninfected-individuals and to evaluate the immunogenicity of vaccine candidates, monitoring the immune response in vaccine trial and supporting the serological diagnostics results. Here, we aimed to identify in the whole-blood-platform the best immunogenic viral antigen and the best immune biomarker to identify COVID-19-patients | ||
| 520 | |a METHODS: Whole-blood was overnight-stimulated with SARS-CoV-2 peptide pools of nucleoprotein-(NP) Membrane-, ORF3a- and Spike-protein. We evaluated: IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12p70, IL-13, IL- 15, IL-17A, eotaxin, FGF, G-CSF, GM-CSF, IFN-γ, IP-10, MCP-1, MIP-1α, MIP-1β, PDGF, RANTES, TNF-α, VEGF. By a sparse partial least squares discriminant analysis we identified the most important soluble factors discriminating COVID-19- from NO-COVID-19-individuals | ||
| 520 | |a RESULTS: We identified a COVID-19 signature based on six immune factors: IFN-γ, IP-10 and IL-2 induced by Spike; RANTES and IP-10 induced by NP and IL-2 induced by ORF3a. We demonstrated that the test based on IP-10 induced by Spike had the highest AUC (0.85, p < 0.0001) and that the clinical characteristics of the COVID-19-patients did not affect IP-10 production. Finally, we validated the use of IP-10 as biomarker for SARS-CoV2 infection in two additional COVID-19-patients cohorts | ||
| 520 | |a CONCLUSIONS: We set-up a whole-blood assay identifying the best antigen to induce a T-cell response and the best biomarkers for SARS-CoV-2 infection evaluating patients with acute COVID-19 and recovered patients. We focused on IP-10, already described as a potential biomarker for other infectious disease such as tuberculosis and HCV. An additional application of this test is the evaluation of immune response in SARS-CoV-2 vaccine trials: the IP-10 detection may define the immunogenicity of a Spike-based vaccine, whereas the immune response to the virus may be evaluated detecting other soluble factors induced by other viral-antigens | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Biomarkers | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a IFN-γ | |
| 650 | 4 | |a IP-10 | |
| 650 | 4 | |a Immune response | |
| 650 | 4 | |a Immunity | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Spike | |
| 650 | 4 | |a T-cell | |
| 650 | 4 | |a Whole-blood | |
| 650 | 7 | |a Biomarkers |2 NLM | |
| 650 | 7 | |a COVID-19 Vaccines |2 NLM | |
| 650 | 7 | |a RNA, Viral |2 NLM | |
| 700 | 1 | |a Najafi Fard, Saeid |e verfasserin |4 aut | |
| 700 | 1 | |a Navarra, Assunta |e verfasserin |4 aut | |
| 700 | 1 | |a Petrone, Linda |e verfasserin |4 aut | |
| 700 | 1 | |a Vanini, Valentina |e verfasserin |4 aut | |
| 700 | 1 | |a Cuzzi, Gilda |e verfasserin |4 aut | |
| 700 | 1 | |a Gualano, Gina |e verfasserin |4 aut | |
| 700 | 1 | |a Pierelli, Luca |e verfasserin |4 aut | |
| 700 | 1 | |a Bertoletti, Antonio |e verfasserin |4 aut | |
| 700 | 1 | |a Nicastri, Emanuele |e verfasserin |4 aut | |
| 700 | 1 | |a Palmieri, Fabrizio |e verfasserin |4 aut | |
| 700 | 1 | |a Ippolito, Giuseppe |e verfasserin |4 aut | |
| 700 | 1 | |a Goletti, Delia |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Journal of translational medicine |d 2003 |g 19(2021), 1 vom: 26. Juni, Seite 272 |w (DE-627)NLM142679194 |x 1479-5876 |7 nnns |
| 773 | 1 | 8 | |g volume:19 |g year:2021 |g number:1 |g day:26 |g month:06 |g pages:272 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1186/s12967-021-02938-8 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 19 |j 2021 |e 1 |b 26 |c 06 |h 272 | ||