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 KA, Beudeker, Coco R, Brengel-Pesce, Karen, Carrol, Enitan D, Carter, Michael J, De, Tisham, Eleftheriou, Irini, Emonts, Marieke, Epalza, Cristina, Georgiou, Pantelis, De Groot, Ronald, Fidler, Katy, Fink, Colin, van Keulen, Daniëlle, Kuijpers, Taco, Moll, Henriette, Papatheodorou, Irene, Paulus, Stephane, Pokorn, Marko, Pollard, Andrew J, Rivero-Calle, Irene, Rojo, Pablo, Secka, Fatou, Schlapbach, Luregn J, Tremoulet, Adriana H, Tsolia, Maria, Usuf, Effua, Van Der Flier, Michiel, Von Both, Ulrich, Vermont, Clementien, Yeung, Shunmay, Zavadska, Dace, Zenz, Werner, Coin, Lachlan JM, Cunnington, Aubrey, Burns, Jane C, Wright, Victoria, Martinon-Torres, Federico, Herberg, Jethro A, Rodriguez-Manzano, Jesus, Kaforou, Myrsini, and Levin, Michael
- Subjects
Paediatrics ,Medical Microbiology ,Biomedical and Clinical Sciences ,Pediatric ,Genetics ,Infectious Diseases ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,Child ,Humans ,COVID-19 ,Systemic Inflammatory Response Syndrome ,Hospitals ,Mucocutaneous Lymph Node Syndrome ,COVID-19 Testing ,MIS-C ,diagnostic signature ,host diagnostics ,host response ,pediatric infectious diseases ,rapid diagnostics ,transcriptomics ,Medical microbiology - Abstract
BackgroundTo identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections.MethodsChildren 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).ResultsIn 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.ConclusionsMIS-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.
- Published
- 2023