Proteomic profiling reveals diagnostic signatures and pathogenic insights in multisystem inflammatory syndrome in children.

Autor: Nygaard U; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark. Ulrikka.Nygaard@regionh.dk.; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. Ulrikka.Nygaard@regionh.dk., Nielsen AB; NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Dungu KHS; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark., Drici L; NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Holm M; Department of Pediatrics and Adolescent Medicine, Aarhus University Hospital, Aarhus, Denmark., Ottenheijm ME; NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Nielsen AB; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark., Glenthøj JP; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital North Zealand, Hillerød, Denmark., Schmidt LS; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital Herlev, Herlev, Denmark., Cortes D; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark., Jørgensen IM; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital North Zealand, Hillerød, Denmark., Mogensen TH; Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark., Schmiegelow K; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark., Mann M; NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.; Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany., Vissing NH; Department of Pediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark., Wewer Albrechtsen NJ; NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.; Department of Clinical Biochemistry, Copenhagen University Hospital - Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark.
Jazyk: angličtina
Zdroj: Communications biology [Commun Biol] 2024 Jun 05; Vol. 7 (1), pp. 688. Date of Electronic Publication: 2024 Jun 05.
DOI: 10.1038/s42003-024-06370-8
Abstrakt: Multisystem inflammatory syndrome in children (MIS-C) is a severe disease that emerged during the COVID-19 pandemic. Although recognized as an immune-mediated condition, the pathogenesis remains unresolved. Furthermore, the absence of a diagnostic test can lead to delayed immunotherapy. Using state-of-the-art mass-spectrometry proteomics, assisted by artificial intelligence (AI), we aimed to identify a diagnostic signature for MIS-C and to gain insights into disease mechanisms. We identified a highly specific 4-protein diagnostic signature in children with MIS-C. Furthermore, we identified seven clusters that differed between MIS-C and controls, indicating an interplay between apolipoproteins, immune response proteins, coagulation factors, platelet function, and the complement cascade. These intricate protein patterns indicated MIS-C as an immunometabolic condition with global hypercoagulability. Our findings emphasize the potential of AI-assisted proteomics as a powerful and unbiased tool for assessing disease pathogenesis and suggesting avenues for future interventions and impact on pediatric disease trajectories through early diagnosis.
(© 2024. The Author(s).)
Databáze: MEDLINE
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