ArticleFrontiers in cellular and infection microbiology2024
Genetic insights into MIS-C Post-COVID-19 in Kuwaiti children: investigating monogenic factors.
Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Post-COVID Multisystem Inflammatory Syndrome in Children with Kawasaki-like Features: A Scoping Review of Middle Eastern Evidence.Medicina (Kaunas, Lithuania) · 2026Article
- Screening of autoinflammatory genes in patients with SARS-CoV-2-associated MIS-C.Human genomics · 2026Article
- Inflammatory cytokines as biomarkers for disease severity in pediatric viral pneumonia: a systematic review and meta-analysis.Translational pediatrics · 2026Article
- Association of blood group B and of rare variants affecting immune system with multisystem inflammatory syndrome in children in an Italian cohort.Frontiers in immunology · 2026Article
- Genetic Variants Affect Distinct Metabolic Pathways in Pediatric Multisystem Inflammatory Syndrome and Severe COVID-19.Journal of medical virology · 2025Article
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Authors and funding
13 authors.
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Abstract
Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication arising from SARS-CoV-2 infection, with indications that rare inborn errors of immunity may play a role in its pathogenesis. Recent studies suggest that genetic predispositions, particularly monogenic forms, could significantly influence the immune responses to SARS-CoV-2 in MIS-C. Methods: We analysed 24 children under 12 years old, all of whom met the criteria provided by the World Health Organization, 2020 for MIS-C diagnosis, from the Paediatric COVID-19 Registry in Kuwait (PCR-Q8). Demographic and clinical data were collected from medical records, and exome sequencing was performed on the children and their parents to identify rare exonic variants. These variants were prioritized using two approaches: a candidate genes approach employing trio segregation analysis, and a candidate variants approach using a gene panel informed by previous studies on MIS-C-related genetic variants and datasets of differentially expressed genes in MIS-C patients. Results: The candidate genes approach identified 53 unique genes in 20 of the 24 probands, including Conclusion: This study underscores the monogenic susceptibility to MIS-C, enhancing the evidence base through comprehensive genetic analysis. The findings highlight the critical role of genetic predispositions in MIS-C and suggest that further functional genomics work is necessary to explore the mechanistic contributions of these genes, facilitating the development of targeted diagnostic strategies.
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