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

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