Immunometabolic Dichotomy Underlying Monocyte-Driven Kawasaki Disease and Lymphocyte-Driven MIS-C Pathogenesis 2309868

Abstract

Abstract Introduction Kawasaki Disease (KD) and Multisystem Inflammatory Syndrome in Children (MIS-C) share overlapping clinical features but differ markedly in severity and cardiac outcomes. Both conditions involve systemic hyperinflammation, yet the cellular and metabolic mechanisms underlying their divergent pathogenesis remain unclear. Because immune cell function is tightly regulated by metabolic programs, we hypothesized that KD and MIS-C are driven by distinct cell-type—specific immunometabolic alterations. Methods Publicly available single-cell RNA sequencing datasets of PBMCs from KD and MIS-C patients (GSE184330, GSE168732) were analyzed. Metabolic pathway activity was quantified using KEGG and Reactome gene sets. Pathway scores were compared between both diseases, and Random Forest analysis was used to identify pathways and cell types that best discriminated disease states. Results Both KD and MIS-C showed shared metabolic activation in classical monocytes, including increased glycolysis, fatty acid synthesis, and cholesterol metabolism. However, a clear immunometabolic divergence was observed. KD was characterized by metabolically hyperactive monocytes with reduced itaconate-associated anti-inflammatory signaling, while adaptive immune cells retained higher itaconate pathway activity. In contrast, MIS-C exhibited relative metabolic restraint in monocytes but marked suppression of itaconate-linked regulatory pathways in lymphoid populations, including NK cells, γδ T cells, Th1 cells and regulatory T cells. Random Forest analysis identified lymphocyte-specific loss of itaconate regulation as the strongest feature distinguishing MIS-C from KD. Conclusion KD is driven by innate myeloid metabolic overactivation, whereas MIS-C reflects loss of metabolic regulation in adaptive lymphoid cells. This immunometabolic divergence highlights cell-type—specific itaconate pathway activity as a potential diagnostic biomarker. Funding Source IIT Palakkad Topic Categories Immune Mechanisms of Human Disease (HUM)