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Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature
Heather R Jackson1,2, Luca Miglietta1,3, Dominic Habgood-Coote1,2
1Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.
Insights
A five-gene blood RNA signature accurately distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease and other infections. This finding supports the development of a new diagnostic test for MIS-C.
Area of Science:
- Pediatric immunology
- Molecular diagnostics
- Infectious diseases
Background:
- Multisystem inflammatory syndrome in children (MIS-C) shares clinical features with Kawasaki disease (KD) and other infections.
- Accurate differentiation is crucial for timely and appropriate treatment.
Purpose of the Study:
- To identify a blood transcriptomic signature for diagnosing MIS-C.
- To differentiate MIS-C from KD, bacterial infections (DB), and viral infections (DV).
Main Methods:
- Whole-blood RNA sequencing was performed on MIS-C, KD, DB, and DV patient cohorts.
- Significantly differentially expressed genes (SDE) were identified.
- A 5-gene signature was developed and validated using RT-qPCR.
Main Results:
- A 5-gene signature (HSPBAP1, VPS37C, TGFB1, MX2, TRBV11-2) achieved 96.8% AUC in discovery.
- The signature demonstrated 93.2% AUC in an independent validation set.
- This signature effectively distinguished MIS-C from KD, DB, and DV.
Conclusions:
- A 5-gene blood RNA expression signature can reliably distinguish MIS-C from KD, DB, and DV.
- The signature's performance supports its potential as a diagnostic tool for MIS-C.
- This molecular signature may facilitate earlier MIS-C diagnosis and management.
Background:
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.
Methods:
Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and 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, 5696 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, and 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.
Conclusions:
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.
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