Iron Related Biomarkers Predict Disease Severity in a Cohort of Portuguese Adult Patients during COVID-19 Acute Infection

• Type: Article in International Scientific Journal
• Date: 2021

Authors

Moreira, AC (Author) Other; Teles, MJ (Author) Other; Silva, T (Author) Other; Bento, CM (Author) Other; Alves, IS (Author) Other; Pereira, L (Author) Other; guimaraes, jt (Author) FMUP; Graca Porto (Author) ICBAS; Oliveira, P (Author) Other; Gomes, MS (Author) ICBAS

Journal

Title: Viruses-Basel

Vol. 13

Final page: 2482

ISSN: 1999-4915

Indexing

ISI Web of Knowledge - 11 Citations

Scopus - 14 Citations

Other information

Authenticus ID: P-00V-XZ5

DOI: 10.3390/v13122482

Abstract (EN): Large variability in COVID-19 clinical progression urges the need to find the most relevant biomarkers to predict patients' outcomes. We evaluated iron metabolism and immune response in 303 patients admitted to the main hospital of the northern region of Portugal with variable clinical pictures, from September to November 2020. One hundred and twenty-seven tested positive for SARS-CoV-2 and 176 tested negative. Iron-related laboratory parameters and cytokines were determined in blood samples collected soon after admission. Demographic data, comorbidities and clinical outcomes were recorded. Patients were assigned into five groups according to severity. Serum iron and transferrin levels at admission were lower in COVID-19-positive than in COVID-19-negative patients. The levels of interleukin (IL)-6 and monocyte chemoattractant protein 1 (MCP-1) were increased in COVID-19-positive patients. The lowest serum iron and transferrin levels at diagnosis were associated with the worst outcomes. Iron levels negatively correlated with IL-6 and higher levels of this cytokine were associated with a worse prognosis. Serum ferritin levels at diagnosis were higher in COVID-19-positive than in COVID-19-negative patients. Serum iron is the simplest laboratory test to be implemented as a predictor of disease progression in COVID-19-positive patients.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13