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Jackson, HR; Miglietta, L; Habgood-Coote, D; D'Souza, G; Shah, P; Nichols, S; Vito, O; Powell, O; Davidson, MS; Shimizu, C; Agyeman, PKA; Beudeker, CR; Brengel-Pesce, K; Carrol, ED; Carter, MJ; De, T; Eleftheriou, I; Emonts, M; Epalza, C; Georgiou, P; De, Groot, R; Fidler, K; Fink, C; van, Keulen, D; Kuijpers, T; Moll, H; Papatheodorou, I; Paulus, S; Pokorn, M; Pollard, AJ; Rivero-Calle, I; Rojo, P; Secka, F; Schlapbach, LJ; Tremoulet, AH; Tsolia, M; Usuf, E; Van, Der, Flier, M; Von, Both, U; Vermont, C; Yeung, S; Zavadska, D; Zenz, W; Coin, LJM; Cunnington, A; Burns, JC; Wright, V; Martinon-Torres, F; Herberg, JA; Rodriguez-Manzano, J; Kaforou, M; Levin, M.
Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature.
J Pediatric Infect Dis Soc. 2023; 12(6): 322-331. Doi: 10.1093/jpids/piad035 [OPEN ACCESS]
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Co-authors Med Uni Graz: Zenz Werner
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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.
Find related publications in this database (using NLM MeSH Indexing): Child - administration & dosage; Humans - administration & dosage; COVID-19 - diagnosis, genetics; Systemic Inflammatory Response Syndrome - diagnosis, genetics; Hospitals - administration & dosage; Mucocutaneous Lymph Node Syndrome - diagnosis, genetics; COVID-19 Testing - administration & dosage
Find related publications in this database (Keywords): COVID-19; diagnostic signature; host diagnostics; host response; MIS-C; pediatric infectious diseases; rapid diagnostics; transcriptomics