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)
(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.
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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 |
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Uncontrolled Keywords: | EUCLIDS, PERFORM and DIAMONDS Consortia |
Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Infection, Veterinary and Ecological Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 14 Jun 2023 08:59 |
Last Modified: | 07 Jul 2023 04:20 |
DOI: | 10.1093/jpids/piad035 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3170902 |