Informatics in Medicine Unlocked (Jan 2023)
A dual covariant biomarker approach to Kawasaki disease, using vascular endothelial growth factor A and B gene expression; implications for coronary pathogenesis
Abstract
Introduction: Kawasaki disease (KD) is the most common vasculitis in young children, with coronary artery lesions (CALs) and coronary aneurysms (CAAs) being responsible for most KD-related deaths. Objective: We hypothesized that Vascular Endothelial Growth Factors (VEGFs) are pivotal in KD inflammation and coronary artery lesions. This study assessed VEGF-A and VEGF-B gene expression (GE) as potential biomarkers in KD inflammation. Study design: We analyzed NCBI-GEO datasets, categorizing gene expression patterns as ''inflammatory'' or ''non-inflammatory''. We focused on TNF-, NFKB1, VEGF-A, and VEGF-B GEs. Datasets were filtered based on differential changes in TNF and NFKB1 levels to isolate those with inflammatory shifts. Results: Inflammatory datasets (GSE63881, GSE73464, and GSE68004) displayed elevated TNF, NFKB1, and VEGF-A GE levels during acute KD. VEGF-B GE exhibited a distinctive trend: an initial drop and subsequent rise during recovery, a pattern that was missing in the non-inflammatory group. The treatment response was also studied, with intravenous immunoglobulin (IVIG) responders showing significant downregulation of NFKB1 GE after treatment: GSE16797 [IVIG ± methylprednisolone; p = 8.6443-03], GSE48498 [IVIG; p = 6.618e-02, infliximab; p = 3.240e-03], and GSE18606 [IVIG; p = 3.518e-02]. Considering the similar binding of VEGF-A and VEGF-B to the VEGFR1 receptor, a co-variate and inverse relationship is suggested. Conclusion: Temporal VEGF-A, VEGF-B, and GE changes show promise as new post-inflammatory biomarkers for KD. Novelty results with the biomarker approach, with the potential for a dual temporal relationship between VEGF-A and VEGF-A. A comprehensive exploration of VEGF-A and VEGF-B genes and protein analysis in KD is warranted to understand the functional aspects of these changes and how best to utilize the pattern of changes for therapeutic benefit.