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


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.

[img] XML Word Processing Document (DOCX)
ARTICLE_FILE_MISC transcriptional signature Jackson_et_al_JPID.docx - Submitted version
Download (191kB)

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 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
Dimensions
Altmetric
CORE (COnnecting REpositories)