1. Proteomic Signatures of Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with COVID-19: A Narrative Review
- Author
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Maria-Myrto Dourdouna, Elizabeth-Barbara Tatsi, Vasiliki Syriopoulou, and Athanasios Michos
- Subjects
SARS-CoV-2 ,MIS-C ,Kawasaki disease ,omics ,proteomics ,biomarker ,Pediatrics ,RJ1-570 - Abstract
Background/Objectives: Multisystem Inflammatory Syndrome in Children (MIS-C) is a post-infectious complication of COVID-19. MIS-C has overlapping features with other pediatric inflammatory disorders including Kawasaki Disease (KD), Macrophage Activation Syndrome (MAS), Toxic Shock Syndrome and sepsis. The exact mechanisms responsible for the clinical overlap between MIS-C and these conditions remain unclear, and biomarkers that could distinguish MIS-C from its clinical mimics are lacking. This study aimed to provide an overview of how proteomic methods, like Mass Spectrometry (MS) and affinity-based proteomics, can offer a detailed understanding of pathophysiology and aid in the diagnosis and prognosis of MIS-C. Methods: A narrative review of relevant studies published up to July 2024 was conducted. Results: We identified 15 studies and summarized their key proteomic findings. These studies investigated the serum or plasma proteome of MIS-C patients using MS, Proximity Extension, or Aptamer-based assays. The studies associated the proteomic profile of MIS-C with laboratory and clinical parameters and/or compared it with that of other diseases including acute COVID-19, KD, MAS, pediatric rheumatic diseases, sepsis and myocarditis or pericarditis following COVID-19 mRNA immunization. Depending on the method and the control group, different proteins were increased or decreased in the MIS-C group. The limitations and challenges in MIS-C proteomic research are also discussed, and future research recommendations are provided. Conclusions: Although proteomics appear to be a promising approach for understanding the pathogenesis and uncovering candidate biomarkers in MIS-C, proteomic studies are still needed to recognize and validate biomarkers that could accurately discriminate MIS-C from its clinical mimics.
- Published
- 2024
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