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Background: To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections.
Methods: Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138). Genes significantly differentially expressed (SDE) between MIS-C and comparator groups were identified. Feature selection was used to identify genes that optimally distinguish MIS-C from other diseases, which were subsequently translated into RT-qPCR assays and evaluated in an independent validation set comprising MIS-C (n = 37), KD (n = 19), DB (n = 56), DV (n = 43), and COVID-19 (n = 39).
Results: In the discovery set, 5696 genes were SDE between MIS-C and combined comparator disease groups. Five genes were identified as potential MIS-C diagnostic biomarkers (HSPBAP1, VPS37C, TGFB1, MX2, and TRBV11-2), achieving an AUC of 96.8% (95% CI: 94.6%-98.9%) in the discovery set, and were translated into RT-qPCR assays. The RT-qPCR 5-gene signature achieved an AUC of 93.2% (95% CI: 88.3%-97.7%) in the independent validation set when distinguishing MIS-C from KD, DB, and DV.
Conclusions: MIS-C can be distinguished from KD, DB, and DV groups using a 5-gene blood RNA expression signature. The small number of genes in the signature and good performance in both discovery and validation sets should enable the development of a diagnostic test for MIS-C.
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http://dx.doi.org/10.1093/jpids/piad035 | DOI Listing |
Eur J Pediatr
September 2025
Department of Pediatrics, Riga Stradins University, Children's Clinical University Hospital, Riga, Latvia.
Circ Cardiovasc Imaging
September 2025
Department of Cardiology, Boston Children's Hospital, Harvard Medical School, MA (F.S., A. Dionne, J.W.N., K.G.F.).
Background: 2D-speckle tracking echocardiography may help detect subclinical ventricular dysfunction, but data in multisystem inflammatory syndrome in children (MIS-C) are scarce. We investigated left ventricular (LV) strain parameters in MIS-C and their association with outcomes.
Methods: We performed an ambi-directional, 32-center cohort study on hospitalized MIS-C patients (March 2020-November 2021) with at least 1 echocardiogram read by the Core Lab.
Medicine (Baltimore)
August 2025
Kasralainy Faculty of Medicine, Cairo University, Cairo, Egypt.
Rationale: This case report highlights the complex clinical course and successful multidisciplinary management of a pediatric patient with multisystem inflammatory syndrome in children (MIS-C), who posed clinical dilemma at presentation. It underscores the ongoing clinical relevance of MIS-C as a post-Coronavirus disease 2019 sequelae and emphasizes the importance of maintaining a high index of suspicion for MIS-C in pediatric differential diagnoses, especially when symptoms overlap with other common conditions.
Patient Concerns: An 11-year-old previously healthy Saudi girl presented with gastrointestinal symptoms initially suggestive of acute appendicitis.
ARYA Atheroscler
January 2025
Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Background: Cardiovascular involvement represents a potentially serious complication associated with novel coronavirus disease 2019 (COVID-19), particularly among pediatric patients. Data regarding echocardiographic findings remain sparse, especially in low- and middle-income countries. The primary objective of this study was to investigate the echocardiographic findings of hospitalized children with COVID-19 in southeast Iran.
View Article and Find Full Text PDFActa Paediatr
September 2025
Department of Pediatrics, University of California San Diego (UCSD) & Rady Children's Hospital, San Diego, California, USA.
Aim: We aimed to develop and test machine learning algorithms for the prediction of severe outcomes associated with MIS-C.
Method: An observational ambispective cohort study was conducted including children aged from 1 month to 18 years old in 84 hospitals from the REKAMLATINA (Red de la Enfermedad de Kawasaki en America Latina) network diagnosed with MIS-C from 1st January 2020 to 31st June 2022. Multiple models were developed to predict four main outcomes: paediatric intensive care unit (PICU) admission, need for inotropes, need for mechanical ventilation, and death.