Subgroups Of Children with Kawasaki Disease A Data-Driven Cluster Analysis

Kawasaki disease, a prominent acute vasculitis in pediatric populations, stands as a leading contributor to acquired cardiovascular ailments among children in high-income nations. Initially characterized in 1967 based on clinical presentations such as fever, mucocutaneous inflammation, and lymphadenopathy, it has since revealed itself as a multifaceted condition. Coronary artery aneurysms, recognized as its most worrisome complication, underscore the significance of understanding its diverse manifestations. Although the precise pathogenesis remains elusive, a intricate interplay between genetic predisposition and environmental triggers is strongly implicated. Recent insights suggest that Kawasaki disease is far from a uniform entity, manifesting substantial heterogeneity. Notably, a multitude of clinical features across seven major organ systems, previously unaccounted for, have been identified. Additionally, varied risks of coronary artery aneurysms have been linked to factors such as age, ethnicity, gender, inflammation markers, and early coronary dilation. Furthermore, a comprehensive multiomic study in 2021 unveiled distinct transcriptomic and proteomic profiles categorizing Kawasaki disease patients into three distinct groups, indicating diverse host responses shaped by different triggers interacting with unique genetic backgrounds. In clinical practice, patients are classified as complete or incomplete Kawasaki disease based on diagnostic criteria. To enhance clinical management, risk prognosis for coronary artery aneurysms, and unravel pathophysiological nuances, we embarked on an unsupervised, data-driven cluster analysis. This approach aims to delineate Kawasaki disease subgroups, shedding light on their distinct characteristics and underlying biological mechanisms. By delving into the intricacies of this condition, we hope to pave the way for more precise patient care and deeper scientific exploration.