Diagnosis of Kawasaki Disease Using a Minimal Whole-Blood Gene Expression Signature

Victoria J Wright, Jethro A Herberg, Myrsini Kaforou, Chisato Shimizu, Hariklia Eleftherohorinou, Hannah Shailes, Anouk M Barendregt, Stephanie Menikou, Stuart Gormley, Maurice Berk, Long Truong Hoang, Adriana H Tremoulet, John T Kanegaye, Lachlan J M Coin, Mary P Glodé, Martin Hibberd, Taco W Kuijpers, Clive J Hoggart, Jane C Burns, Michael Levin, Immunopathology of Respiratory, Inflammatory and Infectious Disease Study (IRIS) Consortium and the Pediatric Emergency Medicine Kawasaki Disease Research Group (PEMKDRG), Victoria J Wright, Jethro A Herberg, Myrsini Kaforou, Chisato Shimizu, Hariklia Eleftherohorinou, Hannah Shailes, Anouk M Barendregt, Stephanie Menikou, Stuart Gormley, Maurice Berk, Long Truong Hoang, Adriana H Tremoulet, John T Kanegaye, Lachlan J M Coin, Mary P Glodé, Martin Hibberd, Taco W Kuijpers, Clive J Hoggart, Jane C Burns, Michael Levin, Immunopathology of Respiratory, Inflammatory and Infectious Disease Study (IRIS) Consortium and the Pediatric Emergency Medicine Kawasaki Disease Research Group (PEMKDRG)

Abstract

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.

Conflict of interest statement

Conflict of Interest Disclosures: The 13-transcript signature distinguishing Kawasaki disease from other conditions is being patented by Imperial Innovations, a subsidiary of Imperial College London. No other disclosures were reported.

Figures

Figure 1.. Assignment of Patients to Diagnostic…
Figure 1.. Assignment of Patients to Diagnostic Groups
The diagnostic algorithm demonstrates the method of assigning patients to diagnostic groups. AHA indicates American Heart Association; CAA, coronary artery aneurysm; CRP, C-reactive protein; HSP, Henoch-Schönlein purpura; JIA, juvenile idiopathic arthritis; and KD, Kawasaki disease. To convert C-reactive protein level to nanomoles per liter, multiply by 9.524; to convert neutrophil count to ×109/L, multiply by 0.001.
Figure 2.. Study Design
Figure 2.. Study Design
The overall study pipeline shows sample handling, derivation of test and training data sets, data processing, and analysis pipeline. Version 3 arrays indicate HumanHT-12, version 3.0 BeadChip (Illumina); version 4 arrays indicate HumanHT-12, version 4.0 BeadChip (Illumina); and ComBat indicates the ComBat algorithm. DB indicates definite bacterial; DV, definite viral; FC, fold change; HC, healthy controls; HSP, Henoch-Schönlein purpura; JIA, juvenile idiopathic arthritis; KD, Kawasaki disease; PReMS, parallel regularized regression model search; SDE, significantly differentially expressed; and U, infections of uncertain bacterial or viral etiology. aSee Supplemental Methods (RNA sample extraction and processing), as well as Statistical Methods in eMethods in the Supplement. bHealthy controls were used in model building but were excluded from estimates of model accuracy. cSee Statistical Methods in eMethods in the Supplement; 146 acute KD samples (HumanHT-12, version 4.0) were used in Combat, of which 101 were taken forward. dDiagnostic performance was assessed on 72 patients (within the first 7 days of illness). eIncludes convalescent KD and healthy controls.
Figure 3.. Performance of the 13-Transcript Signature…
Figure 3.. Performance of the 13-Transcript Signature on the Discovery Test Set and the Validation Set
Shown is classification (A) and ROC curve (B) of the 13-transcript signature in the discovery test set, comprising patients with KD and patients with other diseases, using the disease risk score. Shown is classification (C) and ROC curves (D) of the 13-transcript signature in the validation set, comprising 3 KD clinical subgroups of differing diagnostic certainty and patients with other diseases. In box plots, horizontal lines represent the median; lower and upper edges represent interquartile ranges; and whiskers represent the range or 1.5 times the interquartile range, whichever is smaller. The horizontal blue line indicates the disease risk score threshold that separates patients predicted as having KD (above the line) or not having KD (below the line) as determined by the point in the ROC curve that maximized sensitivity and specificity in the discovery training group. DB indicates definite bacterial; DV, definite viral; HSP, Henoch-Schönlein purpura; JIA, juvenile idiopathic arthritis; KD, Kawasaki disease; KD-Def, definite KD; KD-HP, highly probable KD; KD-P, possible KD; ROC, receiver operating characteristic; and U, infections of uncertain bacterial or viral etiology.

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Source: PubMed

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