Please use this identifier to cite or link to this item: 10.1097/INF.0000000000004267
Title: Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases
Authors: Yeoh, Sophya
Estrada-Rivadeneyra, Diego
Jackson, Heather
Zavadska, Dace
PERFORM, DIAMONDS and UK KD Genetic Consortia
Keywords: Humans;Child;Proprotein Convertase 9;Mucocutaneous Lymph Node Syndrome/diagnosis;Blood Proteins;Systemic Inflammatory Response Syndrome/diagnosis;Biomarkers;COVID-19/complications;3.2 Clinical medicine;1.1. Scientific article indexed in Web of Science and/or Scopus database
Issue Date: 1-May-2024
Citation: Yeoh , S , Estrada-Rivadeneyra , D , Jackson , H , Zavadska , D & PERFORM, DIAMONDS and UK KD Genetic Consortia 2024 , ' Plasma Protein Biomarkers Distinguish Multisystem Inflammatory Syndrome in Children From Other Pediatric Infectious and Inflammatory Diseases ' , The Pediatric infectious disease journal , vol. 43 , no. 5 , pp. 444-453 . https://doi.org/10.1097/INF.0000000000004267
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.
Description: Publisher Copyright: © 2024 Lippincott Williams and Wilkins. All rights reserved.
DOI: 10.1097/INF.0000000000004267
ISSN: 0891-3668
Appears in Collections:Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure

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