Whole blood Transcriptional Profiles as a Prognostic and Diagnostic Tool in Complete and Incomplete Kawasaki Disease

The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information.

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Jaggi P, Mejias A, Xu Z, Yin H, Moore-Clingenpeel M, Smith B, Burns JC, Tremoulet AH, Jordan-Villegas A, Chaussabel D, Texter K, Pascual V, Ramilo O