Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature.

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Jackson, Heather R, Miglietta, Luca, Habgood-Coote, Dominic, D'Souza, Giselle, Shah, Priyen, Nichols, Samuel, Vito, Ortensia, Powell, Oliver, Davidson, Maisey Salina, Shimizu, Chisato et al (show 43 more authors) , Agyeman, Philipp KA, Beudeker, Coco R, Brengel-Pesce, Karen, Carrol, Enitan D ORCID: 0000-0001-8357-7726, Carter, Michael J, De, Tisham, Eleftheriou, Irini, Emonts, Marieke, Epalza, Cristina, Georgiou, Pantelis, De Groot, Ronald, Fidler, Katy, Fink, Colin, van Keulen, Daniëlle, Kuijpers, Taco, Moll, Henriette, Papatheodorou, Irene, Paulus, Stephane, Pokorn, Marko, Pollard, Andrew J, Rivero-Calle, Irene, Rojo, Pablo, Secka, Fatou, Schlapbach, Luregn J, Tremoulet, Adriana H, Tsolia, Maria, Usuf, Effua, Van Der Flier, Michiel, Von Both, Ulrich, Vermont, Clementien, Yeung, Shunmay, Zavadska, Dace, Zenz, Werner, Coin, Lachlan JM, Cunnington, Aubrey, Burns, Jane C, Wright, Victoria, Martinon-Torres, Federico, Herberg, Jethro A, Rodriguez Manzano, Jesus, Kaforou, Myrsini, Levin, Michael and EUCLIDS, PERFORM and DIAMONDS Consortia (2023) Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature. Journal of the Pediatric Infectious Diseases Society, 12 (6). piad035-piad035. ISSN 2048-7193, 2048-7207

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Abstract

<h4>Objective</h4>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.<h4>Study design</h4>Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020-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).<h4>Results</h4>In the discovery set, 5,696 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, 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.<h4>Conclusion</h4>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.

Item Type:	Article
Uncontrolled Keywords:	EUCLIDS, PERFORM and DIAMONDS Consortia
Divisions:	Faculty of Health & Life Sciences Faculty of Health & Life Sciences > Inst. Infection, Vet & Ecological Sciences
Depositing User:	Symplectic Admin
Date Deposited:	14 Jun 2023 08:59
Last Modified:	28 Feb 2026 20:49
DOI:	10.1093/jpids/piad035
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3170902
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