1. Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature.
- Author
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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, and Georgiou, Pantelis
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HOSPITALS , *BIOMARKERS , *REVERSE transcriptase polymerase chain reaction , *MULTISYSTEM inflammatory syndrome , *COVID-19 , *SEQUENCE analysis , *CONFIDENCE intervals , *RNA , *SYSTEMIC inflammatory response syndrome , *CONNECTIVE tissue diseases , *GENE expression profiling , *VIRUS diseases , *COVID-19 testing , *MUCOCUTANEOUS lymph node syndrome , *BACTERIAL diseases , *RECEIVER operating characteristic curves , *LONGITUDINAL method , *CHILDREN - Abstract
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. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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