Dataset Information

Whole blood transcriptional profiles as a prognostic tool in complete and incomplete Kawasaki Disease.

ABSTRACT: Background: Early identification of children with Kawasaki Disease (KD) is key for timely initiation of intravenous immunoglobulin (IVIG) therapy. However, the diagnosis of the disease remains challenging, especially in children with an incomplete presentation (inKD). Moreover, we currently lack objective tools for identification of non-response (NR) to IVIG.

Methods: Children with KD were enrolled and samples obtained before IVIG treatment and sequentially at 24 h and 4-6 weeks post-IVIG in a subset of patients. We also enrolled children with other febrile illnesses [adenovirus (AdV); group A streptococcus (GAS)] and healthy controls (HC) for comparative analyses. Blood transcriptional profiles were analyzed to define: a) the cKD and inKD biosignature, b) compare the KD signature with other febrile illnesses and, c) identify biomarkers predictive of clinical outcomes.

Results: We identified a cKD biosignature (n = 39; HC, n = 16) that was validated in two additional cohorts of children with cKD (n = 37; HC, n = 20) and inKD (n = 13; HC, n = 8) and was characterized by overexpression of inflammation, platelets, apoptosis and neutrophil genes, and underexpression of T and NK cell genes. Classifier genes discriminated KD from adenovirus with higher sensitivity and specificity (92% and 100%, respectively) than for GAS (75% and 87%, respectively). We identified a genomic score (MDTH) that was higher at baseline in IVIG-NR [median 12,290 vs. 5,572 in responders, p = 0.009] and independently predicted IVIG-NR.

Conclusion: A reproducible biosignature from KD patients was identified, and was similar in children with cKD and inKD. A genomic score allowed early identification of children at higher risk for non-response to IVIG.

SUBMITTER: Jaggi P

PROVIDER: S-EPMC5973615 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Whole blood transcriptional profiles as a prognostic tool in complete and incomplete Kawasaki Disease.

Jaggi Preeti P Mejias Asuncion A Xu Zhaohui Z Yin Han H Moore-Clingenpeel Melissa M Smith Bennett B Burns Jane C JC Tremoulet Adriana H AH Jordan-Villegas Alejandro A Chaussabel Damien D Texter Karen K Pascual Virginia V Ramilo Octavio O

PloS one 20180529 5

<h4>Background</h4>Early identification of children with Kawasaki Disease (KD) is key for timely initiation of intravenous immunoglobulin (IVIG) therapy. However, the diagnosis of the disease remains challenging, especially in children with an incomplete presentation (inKD). Moreover, we currently lack objective tools for identification of non-response (NR) to IVIG.<h4>Methods</h4>Children with KD were enrolled and samples obtained before IVIG treatment and sequentially at 24 h and 4-6 weeks pos ...[more]

PMID: 29813106

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Project description: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. 113 samples, no replicates, 9 HAdV, 57 cKD, 12 FUO, 13 GAS, 3 GAS/SF, 5 inKD, 14 healthy control

Project description:Importance:To date, there is no diagnostic test for Kawasaki disease (KD). Diagnosis is based on clinical features shared with other febrile conditions, frequently resulting in delayed or missed treatment and an increased risk of coronary artery aneurysms. Objective:To identify a whole-blood gene expression signature that distinguishes children with KD in the first week of illness from other febrile conditions. Design, Setting, and Participants:The case-control study comprised a discovery group that included a training and test set and a validation group of children with KD or comparator febrile illness. The setting was pediatric centers in the United Kingdom, Spain, the Netherlands, and the United States. The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, and 242 bacterial or viral infections) and 55 healthy controls. The independent validation group comprised 102 patients with KD, including 72 in the first 7 days of illness, and 130 febrile controls. The study dates were March 1, 2009, to November 14, 2013, and data analysis took place from January 1, 2015, to December 31, 2017. Main Outcomes and Measures:Whole-blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (parallel regularized regression model search). The ability of transcript signatures (implemented as disease risk scores) to discriminate KD cases from controls was assessed by area under the curve (AUC), sensitivity, and specificity at the optimal cut point according to the Youden index. Results:Among 404 patients in the discovery set, there were 78 with KD (median age, 27 months; 55.1% male) and 326 febrile controls (median age, 37 months; 56.4% male). Among 202 patients in the validation set, there were 72 with KD (median age, 34 months; 62.5% male) and 130 febrile controls (median age, 17 months; 56.9% male). A 13-transcript signature identified in the discovery training set distinguished KD from other infectious and inflammatory conditions in the discovery test set, with AUC of 96.2% (95% CI, 92.5%-99.9%), sensitivity of 81.7% (95% CI, 60.0%-94.8%), and specificity of 92.1% (95% CI, 84.0%-97.0%). In the validation set, the signature distinguished KD from febrile controls, with AUC of 94.6% (95% CI, 91.3%-98.0%), sensitivity of 85.9% (95% CI, 76.8%-92.6%), and specificity of 89.1% (95% CI, 83.0%-93.7%). The signature was applied to clinically defined categories of definite, highly probable, and possible KD, resulting in AUCs of 98.1% (95% CI, 94.5%-100%), 96.3% (95% CI, 93.3%-99.4%), and 70.0% (95% CI, 53.4%-86.6%), respectively, mirroring certainty of clinical diagnosis. Conclusions and Relevance:In this study, a 13-transcript blood gene expression signature distinguished KD from other febrile conditions. Diagnostic accuracy increased with certainty of clinical diagnosis. A test incorporating the 13-transcript disease risk score may enable earlier diagnosis and treatment of KD and reduce inappropriate treatment in those with other diagnoses.

Dataset Information

Whole blood transcriptional profiles as a prognostic tool in complete and incomplete Kawasaki Disease.

Publications

Whole blood transcriptional profiles as a prognostic tool in complete and incomplete Kawasaki Disease.

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