IFI27 transcription is an early predictor for COVID-19 outcomes, a multi-cohort observational study

Maryam Shojaei*, Amir Shamshirian, James Monkman, Laura Grice, Minh Tran, Chin Wee Tan, Siok Min Teo, Gustavo Rodrigues Rossi, Timothy R. McCulloch, Marek Nalos, Maedeh Raei, Alireza Razavi, Roya Ghasemian, Mobina Gheibi, Fatemeh Roozbeh, Peter D. Sly, Kirsten M. Spann, Keng Yih Chew, Yanshan Zhu, Yao XiaTimothy J. Wells, Alexandra Cristina Senegaglia, Carmen Lúcia Kuniyoshi, Claudio Luciano Franck, Anna Flavia Ribeiro dos Santos, Lucia de Noronha, Sepideh Motamen, Reza Valadan, Omolbanin Amjadi, Rajan Gogna, Esha Madan, Reza Alizadeh-Navaei, Liliana Lamperti, Felipe Zuñiga, Estefania Nova-Lamperti, Gonzalo Labarca, Ben Knippenberg, Velma Herwanto, Ya Wang, Amy Phu, Tracy Chew, Timothy Kwan, Karan Kim, Sally Teoh, Tiana M. Pelaia, Win Sen Kuan, Yvette Jee, Jon Iredell, Ken O’Byrne, John F. Fraser, Melissa J. Davis, Gabrielle T. Belz, Majid E. Warkiani, Carlos Salomon Gallo, Fernando Souza-Fonseca-Guimaraes, Quan Nguyen, Anthony Mclean, Arutha Kulasinghe, Kirsty R. Short, Benjamin Tang

*Corresponding author af dette arbejde

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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.

OriginalsprogEngelsk
Artikelnummer1060438
TidsskriftFrontiers in Immunology
Vol/bind13
Antal sider14
ISSN1664-3224
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
Research Grant, and a US Department of Defence – Breast Cancer Research Program – breakthrough award level 1 (#BC200025). CS is supported by the Lion Medical Research Foundation (2015001964). EN-L is supported by Agencia Nacional de Investigación y Desarrollo (COVID1005-ANID). The funders did not influence any of the data analysis and interpretation presented in this manuscript. This research was funded by Centre of Research Excellence in Emerging Infectious Diseases (CREID; MS, BT), grants and fellowships from the National Health and Medical Research Council of Australia (2007919 KRS; 1157741 AK; 1135898 GB, 1140406 FSFG 1195451 CS), Priority driven Collaborative Cancer Research Scheme, funded by Cure Cancer Australia with the assistance of Cancer Australia and the Can Too Foundation (1182179 AK; 1158085 FS-F-G), University of Queensland (GB, FS-F-G, AK), Walter and Eliza Hall Institute of Medical Research (CT, MD). MD is supported by the Betty Smyth Centenary Fellowship in Bioinformatics. TM is supported by an UQ PhD scholarship. FS-F-G is funded by the Australian and New Zealand Sarcoma Association Sarcoma

Funding Information:
Research Grant, and a US Department of Defence – Breast Cancer Research Program – breakthrough award level 1 (#BC200025). CS is supported by the Lion Medical Research Foundation (2015001964). EN-L is supported by Agencia Nacional de Investigación y Desarrollo (COVID1005-ANID). The funders did not influence any of the data analysis and interpretation presented in this manuscript. This research was funded by Centre of Research Excellence in Emerging Infectious Diseases (CREID; MS, BT), grants and fellowships from the National Health and Medical Research Council of Australia (2007919 KRS; 1157741 AK; 1135898 GB, 1140406 FSFG 1195451 CS), Priority driven Collaborative Cancer Research Scheme, funded by Cure Cancer Australia with the assistance of Cancer Australia and the Can Too Foundation (1182179 AK; 1158085 FS-F-G), University of Queensland (GB, FS-F-G, AK), Walter and Eliza Hall Institute of Medical Research (CT, MD). MD is supported by the Betty Smyth Centenary Fellowship in Bioinformatics. TM is supported by an UQ PhD scholarship. FS-F-G is funded by the Australian and New Zealand Sarcoma Association Sarcoma Acknowledgments

Funding Information:
We would like to acknowledge the following institutions/individuals: L. Pan, A. Nam (Nanostring Technologies, Seattle, USA), T. Y. Drennon, C. R. Uytingco, S. R Williams (10X Genomics, Pleasanton, USA), Nepean Institute of Critical Care Education and Research and Westmead Scientific Platforms supported by Westmead Institute for Medical Research, Cancer Institute New South Wales and the National Health and Medical Research Council. Tania Sorrell and Sue Maddock for their support of the study in Cohort 7 and patients and families that made this study possible.

Publisher Copyright:
Copyright © 2023 Shojaei, Shamshirian, Monkman, Grice, Tran, Tan, Teo, Rodrigues Rossi, McCulloch, Nalos, Raei, Razavi, Ghasemian, Gheibi, Roozbeh, Sly, Spann, Chew, Zhu, Xia, Wells, Senegaglia, Kuniyoshi, Franck, dos Santos, Noronha, Motamen, Valadan, Amjadi, Gogna, Madan, Alizadeh-Navaei, Lamperti, Zuñiga, Nova-Lamperti, Labarca, Knippenberg, Herwanto, Wang, Phu, Chew, Kwan, Kim, Teoh, Pelaia, Kuan, Jee, Iredell, O’Byrne, Fraser, Davis, Belz, Warkiani, Gallo, Souza-Fonseca-Guimaraes, Nguyen, Mclean, Kulasinghe, Short and Tang.

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