tetano
Editor, Senior Moderator
Front Immunol
. 2023 Jan 5;13:1060438.
doi: 10.3389/fimmu.2022.1060438. eCollection 2022.
IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study
Maryam Shojaei[SUP] 1 2 3 [/SUP], Amir Shamshirian[SUP] 4 [/SUP], James Monkman[SUP] 5 [/SUP], Laura Grice[SUP] 6 7 [/SUP], Minh Tran[SUP] 6 [/SUP], Chin Wee Tan[SUP] 8 9 [/SUP], Siok Min Teo[SUP] 6 [/SUP], Gustavo Rodrigues Rossi[SUP] 5 [/SUP], Timothy R McCulloch[SUP] 5 [/SUP], Marek Nalos[SUP] 1 [/SUP], Maedeh Raei[SUP] 4 [/SUP], Alireza Razavi[SUP] 10 [/SUP], Roya Ghasemian[SUP] 11 [/SUP], Mobina Gheibi[SUP] 12 [/SUP], Fatemeh Roozbeh[SUP] 13 [/SUP], Peter D Sly[SUP] 14 [/SUP], Kirsten M Spann[SUP] 15 [/SUP], Keng Yih Chew[SUP] 16 [/SUP], Yanshan Zhu[SUP] 16 [/SUP], Yao Xia[SUP] 17 [/SUP], Timothy J Wells[SUP] 5 [/SUP], Alexandra Cristina Senegaglia[SUP] 18 19 [/SUP], Carmen Lúcia Kuniyoshi[SUP] 18 19 [/SUP], Claudio Luciano Franck[SUP] 18 [/SUP], Anna Flavia Ribeiro Dos Santos[SUP] 20 [/SUP], Lucia de Noronha[SUP] 20 [/SUP], Sepideh Motamen[SUP] 21 [/SUP], Reza Valadan[SUP] 22 23 [/SUP], Omolbanin Amjadi[SUP] 4 [/SUP], Rajan Gogna[SUP] 24 25 [/SUP], Esha Madan[SUP] 26 [/SUP], Reza Alizadeh-Navaei[SUP] 4 [/SUP], Liliana Lamperti[SUP] 27 [/SUP], Felipe Zuñiga[SUP] 28 [/SUP], Estefania Nova-Lamperti[SUP] 28 [/SUP], Gonzalo Labarca[SUP] 27 29 [/SUP], Ben Knippenberg[SUP] 30 [/SUP], Velma Herwanto[SUP] 31 [/SUP], Ya Wang[SUP] 1 2 3 [/SUP], Amy Phu[SUP] 1 32 [/SUP], Tracy Chew[SUP] 33 [/SUP], Timothy Kwan[SUP] 1 [/SUP], Karan Kim[SUP] 2 [/SUP], Sally Teoh[SUP] 1 [/SUP], Tiana M Pelaia[SUP] 1 [/SUP], Win Sen Kuan[SUP] 34 35 [/SUP], Yvette Jee[SUP] 34 [/SUP], Jon Iredell[SUP] 36 37 38 [/SUP], Ken O'Byrne[SUP] 39 [/SUP], John F Fraser[SUP] 40 [/SUP], Melissa J Davis[SUP] 8 9 41 [/SUP], Gabrielle T Belz[SUP] 5 [/SUP], Majid E Warkiani[SUP] 42 [/SUP], Carlos Salomon Gallo[SUP] 27 43 [/SUP], Fernando Souza-Fonseca-Guimaraes[SUP] 5 [/SUP], Quan Nguyen[SUP] 6 [/SUP], Anthony Mclean[SUP] 1 [/SUP], Arutha Kulasinghe[SUP] 5 [/SUP], Kirsty R Short[SUP] 16 [/SUP], Benjamin Tang[SUP] 1 2 [/SUP]
Affiliations
Abstract
Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.
Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.
Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.
Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.
Keywords: COVID-19; IFI27; SARS-CoV-2; biomarkers; early predictor.
. 2023 Jan 5;13:1060438.
doi: 10.3389/fimmu.2022.1060438. eCollection 2022.
IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study
Maryam Shojaei[SUP] 1 2 3 [/SUP], Amir Shamshirian[SUP] 4 [/SUP], James Monkman[SUP] 5 [/SUP], Laura Grice[SUP] 6 7 [/SUP], Minh Tran[SUP] 6 [/SUP], Chin Wee Tan[SUP] 8 9 [/SUP], Siok Min Teo[SUP] 6 [/SUP], Gustavo Rodrigues Rossi[SUP] 5 [/SUP], Timothy R McCulloch[SUP] 5 [/SUP], Marek Nalos[SUP] 1 [/SUP], Maedeh Raei[SUP] 4 [/SUP], Alireza Razavi[SUP] 10 [/SUP], Roya Ghasemian[SUP] 11 [/SUP], Mobina Gheibi[SUP] 12 [/SUP], Fatemeh Roozbeh[SUP] 13 [/SUP], Peter D Sly[SUP] 14 [/SUP], Kirsten M Spann[SUP] 15 [/SUP], Keng Yih Chew[SUP] 16 [/SUP], Yanshan Zhu[SUP] 16 [/SUP], Yao Xia[SUP] 17 [/SUP], Timothy J Wells[SUP] 5 [/SUP], Alexandra Cristina Senegaglia[SUP] 18 19 [/SUP], Carmen Lúcia Kuniyoshi[SUP] 18 19 [/SUP], Claudio Luciano Franck[SUP] 18 [/SUP], Anna Flavia Ribeiro Dos Santos[SUP] 20 [/SUP], Lucia de Noronha[SUP] 20 [/SUP], Sepideh Motamen[SUP] 21 [/SUP], Reza Valadan[SUP] 22 23 [/SUP], Omolbanin Amjadi[SUP] 4 [/SUP], Rajan Gogna[SUP] 24 25 [/SUP], Esha Madan[SUP] 26 [/SUP], Reza Alizadeh-Navaei[SUP] 4 [/SUP], Liliana Lamperti[SUP] 27 [/SUP], Felipe Zuñiga[SUP] 28 [/SUP], Estefania Nova-Lamperti[SUP] 28 [/SUP], Gonzalo Labarca[SUP] 27 29 [/SUP], Ben Knippenberg[SUP] 30 [/SUP], Velma Herwanto[SUP] 31 [/SUP], Ya Wang[SUP] 1 2 3 [/SUP], Amy Phu[SUP] 1 32 [/SUP], Tracy Chew[SUP] 33 [/SUP], Timothy Kwan[SUP] 1 [/SUP], Karan Kim[SUP] 2 [/SUP], Sally Teoh[SUP] 1 [/SUP], Tiana M Pelaia[SUP] 1 [/SUP], Win Sen Kuan[SUP] 34 35 [/SUP], Yvette Jee[SUP] 34 [/SUP], Jon Iredell[SUP] 36 37 38 [/SUP], Ken O'Byrne[SUP] 39 [/SUP], John F Fraser[SUP] 40 [/SUP], Melissa J Davis[SUP] 8 9 41 [/SUP], Gabrielle T Belz[SUP] 5 [/SUP], Majid E Warkiani[SUP] 42 [/SUP], Carlos Salomon Gallo[SUP] 27 43 [/SUP], Fernando Souza-Fonseca-Guimaraes[SUP] 5 [/SUP], Quan Nguyen[SUP] 6 [/SUP], Anthony Mclean[SUP] 1 [/SUP], Arutha Kulasinghe[SUP] 5 [/SUP], Kirsty R Short[SUP] 16 [/SUP], Benjamin Tang[SUP] 1 2 [/SUP]
Affiliations
- PMID: 36685600
- PMCID: PMC9850159
- DOI: 10.3389/fimmu.2022.1060438
Abstract
Purpose: Robust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.
Methods: We conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.
Results: We show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.
Conclusion: These data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.
Keywords: COVID-19; IFI27; SARS-CoV-2; biomarkers; early predictor.