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; Agyeman, Philipp K A; Beudeker, Coco R; Brengel-Pesce, Karen; Carrol, Enitan D; Carter, Michael J; De, Tisham; Eleftheriou, Irini; Emonts, Marieke; Epalza, Cristina; Georgiou, Pantelis; ... (2023). Diagnosis of multisystem inflammatory syndrome in children by a whole-blood transcriptional signature. Journal of the Pediatric Infectious Diseases Society, 12(6), pp. 322-331. Oxford University Press 10.1093/jpids/piad035

Preview

Text piad035.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (6MB) | Preview

OBJECTIVE

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.

STUDY DESIGN

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).

RESULTS

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.

CONCLUSION

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.

Interest & Impact

Downloads

43 since deposited on 01 Jun 2023
25 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item