Genetic insights into MIS-C Post-COVID-19 in Kuwaiti children: investigating monogenic factors

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.

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.

The candidate genes approach identified 53 unique genes in 20 of the 24 probands, including DDX60 and TMEM154, which were also differentially expressed between MIS-C and control groups. The candidate variants approach identified 33 rare, predicted deleterious heterozygous variants across 19 unique genes in 19 of the 24 probands, including both previously described and novel candidate variants for MIS-C. Pathway analysis of the identified genes from both approaches revealed significant involvement in immune response, viral defence, and inflammatory pathways.

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.