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Nasal Mucosal Cytokines as Potential Biomarkers for Assessing Disease Severity and Class of Pathogen in Children With Community-Acquired Pneumonia

The Journal of Infectious Diseases, 2024

Sayegh R., Tang L., Yun K., Xu Z., Marzec S., El-Assal O., Leber A., Everhart K., Mertz S., Desai A., Cohen D., Alter S., Ambroggio L., Florin T., Keaton M., Shah S., Ruddy R., Wallihan R., Mejias A., Ramilo O.

Disease areaApplication areaSample typeProducts
Respiratory Diseases
Infectious Diseases
Patient Stratification
Nasal Mucus Swabs
O

Olink Target 96

Abstract

Background

Community-acquired pneumonia (CAP) is a leading cause of morbidity and mortality in children. Assessing disease severity and etiology remains challenging in the clinical setting. The objective of this study was to identify mucosal biomarkers that could potentially assist with patient classification.

Methods

We analyzed mucosal concentrations of cytokines in nasopharyngeal samples obtained from a convenience sample of 182 children with CAP and 26 matched healthy controls. Pathogens were identified by cultures and molecular assays. Severe disease was defined by hospital stay ≥3 days and/or pediatric intensive care unit admission. Data were analyzed according to identified pathogens and disease severity.

Results

Children with CAP and detected atypical bacteria had significantly higher concentrations of monocyte chemotactic protein 2 (MCP-2), interferon gamma (IFN-γ), and CXCL10, among others, compared with those with typical bacteria. Children with influenza virus had significantly higher concentrations of MCP-2, CXCL10, CXCL11, CX3CL1, and IFN-γ than those with typical bacteria. Additionally, children with severe CAP had significantly higher concentrations of CCL23 than children with mild/moderate disease, irrespective of the pathogen(s) identified.

Conclusions

We identified differences in mucosal concentrations of inflammatory and antiviral cytokines in children with CAP according to disease severity and detected pathogens. Mucosal biomarkers represent a promising approach to help assess disease severity and etiology.

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