Imperial College London


Faculty of MedicineDepartment of Infectious Disease

Research Fellow



+44 (0)20 7594 3577v.wright




PaediatricsMedical SchoolSt Mary's Campus






BibTex format

author = {Wright, V and Herberg, J and Kaforou, M and Shimizu, C and Eleftherohorinou, H and Shailes, H and Barendregt, A and Menikou, S and Gormley, S and Berk, M and Hoang, L and Tremoulet, A and Kanegaye, J and Coin, L and Glode, M and Hibberd, M and Kuijpers, T and Hoggart, C and Burns, J and Levin, M},
doi = {10.1001/jamapediatrics.2018.2293},
journal = {JAMA Pediatrics},
title = {Diagnosis of Kawasaki disease using a minimal whole blood gene expression signature},
url = {},
volume = {172},
year = {2018}

RIS format (EndNote, RefMan)

AB - Importance 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 Case-control discovery study groups comprising training, test, and validation groups of children with KD or comparator febrile illness. Setting Hospitals in the UK, Spain, Netherlands and USA.Participants The training and test discovery group comprised 404 children with infectious and inflammatory conditions (78 KD, 84 other inflammatory diseases, 242 bacterial or viral infections) and 55 healthy controls. The independent validation group included 130 febrile children and 102 KD patients, including 72 in the first 7 days of illness.Exposures Whole blood gene expression was evaluated using microarrays, and minimal transcript sets distinguishing KD were identified using a novel variable selection method (Parallel Deterministic Model Search).Main outcomes and measures 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 Youden’s index. Results 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, sensitivity, and specificity (95% confidence intervals (CI)) of 96.2% (92.5-99.9), 81.7% (60.0-94.8), and 92.1% (84.0-97.0), respectively. In the validation set, the signature distinguished KD from febrile controls with AUC, sensitivity, and specificity (95% CI) of 94.6% (91.3-98.0), 85.9% (76.8-92.6), and 89.1% (83.0-93.7) respectively. The signature was applied to clinically defin
AU - Wright,V
AU - Herberg,J
AU - Kaforou,M
AU - Shimizu,C
AU - Eleftherohorinou,H
AU - Shailes,H
AU - Barendregt,A
AU - Menikou,S
AU - Gormley,S
AU - Berk,M
AU - Hoang,L
AU - Tremoulet,A
AU - Kanegaye,J
AU - Coin,L
AU - Glode,M
AU - Hibberd,M
AU - Kuijpers,T
AU - Hoggart,C
AU - Burns,J
AU - Levin,M
DO - 10.1001/jamapediatrics.2018.2293
PY - 2018///
SN - 2168-6203
TI - Diagnosis of Kawasaki disease using a minimal whole blood gene expression signature
T2 - JAMA Pediatrics
UR -
UR -
VL - 172
ER -