4.6 Article

Fibronectin as a Marker of Disease Severity in Critically Ill COVID-19 Patients

Journal

CELLS
Volume 11, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/cells11091566

Keywords

COVID-19; fibronectin; intensive care; mortality prediction; biomarkers

Categories

Funding

  1. Wroclaw Medical University, Poland [SUBK.A411.22.048]

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This study aimed to investigate the relationship between different forms of fibronectin and disease severity and mortality in critically ill patients. The results showed that the level of EDA-FN was associated with the treatment outcome in COVID-19 patients, with significantly higher levels in non-survivors. Additionally, FN-fragments were found in most COVID-19 samples, and the amount was significantly higher in non-survivors.
The SARS-CoV-2 virus alters the expression of genes for extracellular matrix proteins, including fibronectin. The aim of the study was to establish the relationship between different forms of fibronectin, such as plasma (pFN), cellular (EDA-FN), and proteolytic FN-fragments, and disease severity and mortality of critically ill patients treated in the intensive care unit. The levels of pFN, EDA-FN, and FN-fragments were measured in patients with a viral (N = 43, COVID-19) or bacterial (N = 41, sepsis) infection, using immunoblotting and ELISA. The level of EDA-FN, but not pFN, was related to the treatment outcome and was significantly higher in COVID-19 Non-survivors than in Survivors. Furthermore, EDA-FN levels correlated with APACHE II and SOFA scores. FN-fragments were detected in 95% of COVID-19 samples and the amount was significantly higher in Non-survivors than in Survivors. Interestingly, FN-fragments were present in only 56% of samples from patients with bacterial sepsis, with no significant differences between Non-survivors and Survivors. The new knowledge gained from our research will help to understand the differences in immune response depending on the etiology of the infection. Fibronectin is a potential biomarker that can be used in clinical settings to monitor the condition of COVID-19 patients and predict treatment outcomes.

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