Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases.

Yeoh, Sophya; Estrada-Rivadeneyra, Diego; Jackson, Heather; Keren, Ilana; Galassini, Rachel; Cooray, Samantha; Shah, Priyen; Agyeman, Philipp; Basmaci, Romain; Carrol, Enitan; Emonts, Marieke; Fink, Colin; Kuijpers, Taco; Martinon-Torres, Federico; Mommert-Tripon, Marine; Paulus, Stephane; Pokorn, Marko; Rojo, Pablo; Romani, Lorenza; Schlapbach, Luregn; ... (2024). Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases. The pediatric infectious disease journal, 43(5), pp. 444-453. Wolters Kluwer Health 10.1097/INF.0000000000004267

Preview

Text plasma_protein_biomarkers_distinguish_multisystem.744.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (767kB) | Preview

BACKGROUND

Multisystem inflammatory syndrome in children (MIS-C) is a rare but serious hyperinflammatory complication following infection with severe acute respiratory syndrome coronavirus 2. The mechanisms underpinning the pathophysiology of MIS-C are poorly understood. Moreover, clinically distinguishing MIS-C from other childhood infectious and inflammatory conditions, such as Kawasaki disease or severe bacterial and viral infections, is challenging due to overlapping clinical and laboratory features. We aimed to determine a set of plasma protein biomarkers that could discriminate MIS-C from those other diseases.

METHODS

Seven candidate protein biomarkers for MIS-C were selected based on literature and from whole blood RNA sequencing data from patients with MIS-C and other diseases. Plasma concentrations of ARG1, CCL20, CD163, CORIN, CXCL9, PCSK9 and ADAMTS2 were quantified in MIS-C (n = 22), Kawasaki disease (n = 23), definite bacterial (n = 28) and viral (n = 27) disease and healthy controls (n = 8). Logistic regression models were used to determine the discriminatory ability of individual proteins and protein combinations to identify MIS-C and association with severity of illness.

RESULTS

Plasma levels of CD163, CXCL9 and PCSK9 were significantly elevated in MIS-C with a combined area under the receiver operating characteristic curve of 85.7% (95% confidence interval: 76.6%-94.8%) for discriminating MIS-C from other childhood diseases. Lower ARG1 and CORIN plasma levels were significantly associated with severe MIS-C cases requiring inotropes, pediatric intensive care unit admission or with shock.

CONCLUSION

Our findings demonstrate the feasibility of a host protein biomarker signature for MIS-C and may provide new insight into its pathophysiology.

Interest & Impact

Downloads

8 since deposited on 20 Feb 2024
8 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item