AUTHOR=Kardol-Hoefnagel Tineke , Luijk Bart , Reteig Leon , Haitjema Saskia , Leavis Helen L. , Otten Henny G. 

TITLE=Clara cell 16 kDa protein: an important marker for COVID-19 severity

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1527377

DOI=10.3389/fimmu.2025.1527377

ISSN=1664-3224

ABSTRACT=The coronavirus disease 19 (COVID-19) is a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that invades lung epithelial cells and can lead to severe respiratory failure. In this study, we evaluated whether Clara cell 16 kDa protein (CC16), a serum marker of lung alveolar cell damage, is predictive for disease severity. Patients suspected of SARS-CoV-2 infection were included in this study. Serum levels of Clara cell 16 kDa protein (CC16), soluble Fas Ligand, cytochrome C, thymus- and activation regulated chemokine (TARC) and of oxidate stress related proteins were analyzed. Clinical patient data were extracted from the Utrecht Patient Oriented Database. COVID-19 positive patients were divided in two groups according to disease severity. The mean day difference between COVID-19 diagnosis date and sampling date was +11 days. Concentrations of TARC were lower in COVID-19 positive versus COVID-19 negative patients (unpaired t-test, p=0.002). In addition, CC16 serum levels were significantly elevated in sera taken from patients that were admitted at the intensive care unit (ICU) (p=0.0082). In a matched cohort, sera taken prior to ICU admission (-3 days) contained higher CC16 levels (paired t-test, p=0.0072). Multivariable analyses adjusted for known risk factors (age, gender, blood counts, lactate dehydrogenase, c-reactive protein, underlying disease) showed that CC16 levels were independently associated to COVID-19 severity (interquartile-range, odds ratio 1.53, p=0.0102). In conclusion, our findings highlight CC16 as a promising biomarker for early identification of severe COVID19 cases, which could improve patient management and resource allocation.