Jackson, Heather R; Miglietta, Luca; Habgood-Coote, Dominic; D'Souza, Giselle; Shah, Priyen; Nichols, Samuel; Vito, Ortensia; Powell, Oliver; Davidson, Maisey Salina; Shimizu, Chisato; +42 more... 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; Levin, Michael; (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. ISSN 2048-7193 DOI: https://doi.org/10.1093/jpids/piad035
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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.
Item Type | Article |
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Faculty and Department |
Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & International Health (2023-) MRC Gambia > GM-Disease Control and Elimination Theme Faculty of Infectious and Tropical Diseases > Dept of Clinical Research |
Research Centre | Centre for Maternal, Reproductive and Child Health (MARCH) |
PubMed ID | 37255317 |
Elements ID | 203962 |
Official URL | http://dx.doi.org/10.1093/jpids/piad035 |
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