학술논문
Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases
Document Type
Academic Journal
Author
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; Schweintzger, Nina; Shen, Ching-Fen; Tsolia, Maria; Usuf, Effua; van der Flier, Michiel; Vermont, Clementien; von Both, Ulrich; Yeung, Shunmay; Zavadska, Dace; Coin, Lachlan; Cunnington, Aubrey; Herberg, Jethro; Levin, Michael; Kaforou, Myrsini; Hamilton, Shea
Source
The Pediatric Infectious Disease Journal. May 01, 2024 43(5):444-453
Subject
Language
English
ISSN
0891-3668
Abstract
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.