Ghanem, M, Brown, SJ, Mohamed, AEAT and Fuller, HR (2022) A Meta-summary and Bioinformatic Analysis Identified Interleukin 6 as a Master Regulator of COVID-19 Severity Biomarkers. Cytokine, 159 (156011). ISSN 1096-0023

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With the rising demand for improved COVID-19 disease monitoring and prognostic markers, studies have aimed to identify biomarkers using a range of screening methods. However, the selection of biomarkers for validation from large datasets may result in potentially important biomarkers being overlooked when datasets are considered in isolation. Here, we have utilized a meta-summary approach to investigate COVID-19 biomarker datasets to identify conserved biomarkers of COVID-19 severity. This approach identified a panel of 17 proteins that showed a consistent direction of change across two or more datasets. Furthermore, bioinformatics analysis of these proteins highlighted a range of enriched biological processes that include inflammatory responses and compromised integrity of physiological systems including cardiovascular, neurological, and metabolic. A panel of upstream regulators of the COVID-19 severity biomarkers were identified, including chemical compounds currently under investigation for COVID-19 treatment. One of the upstream regulators, interleukin 6 (IL6), was identified as a “master regulator” of the severity biomarkers. COVID-19 disease severity is intensified due to the extreme viral immunological reaction that results in increased inflammatory biomarkers and cytokine storm. Since IL6 is the primary stimulator of cytokines, it could be used independently as a biomarker in determining COVID-19 disease progression, in addition to a potential therapeutic approach targeting IL6. The array of upstream regulators of the severity biomarkers identified here serve as attractive candidates for the development of new therapeutic approaches to treating COVID-19. In addition, the findings from this study highlight COVID-19 severity biomarkers which represent promising, robust biomarkers for future validation studies for their use in defining and monitoring disease severity and patient prognosis.

Item Type: Article
Additional Information: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( nc-nd/4.0/).
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > School of Medicine
Faculty of Medicine and Health Sciences > School of Pharmacy and Bioengineering
Depositing User: Symplectic
Date Deposited: 18 Aug 2022 14:28
Last Modified: 13 Apr 2023 10:24

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