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

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.

[1]  Clive J. Hoggart,et al.  PReMS: Parallel Regularised Regression Model Search for sparse bio-signature discovery , 2018, bioRxiv.

[2]  Sohee Park,et al.  Epidemiology and Clinical Features of Kawasaki Disease in South Korea, 2012–2014 , 2017, The Pediatric infectious disease journal.

[3]  B. McCrindle,et al.  Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association , 2017, Circulation.

[4]  Xuejuan Gao,et al.  Sets of serum exosomal microRNAs as candidate diagnostic biomarkers for Kawasaki disease , 2017, Scientific Reports.

[5]  Sung-Chou Li,et al.  Next-generation sequencing identifies micro-RNA-based biomarker panel for Kawasaki disease. , 2016, The Journal of allergy and clinical immunology.

[6]  C. Hoggart,et al.  Diagnostic Test Accuracy of a 2-Transcript Host RNA Signature for Discriminating Bacterial vs Viral Infection in Febrile Children. , 2016, JAMA.

[7]  J. Yu Use of corticosteroids during acute phase of Kawasaki disease. , 2015, World journal of clinical pediatrics.

[8]  K. Kotani,et al.  Descriptive epidemiology of Kawasaki disease in Japan, 2011-2012: from the results of the 22nd nationwide survey. , 2015, Journal of epidemiology.

[9]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[10]  C. Khor,et al.  Global gene expression profiling identifies new therapeutic targets in acute Kawasaki disease , 2014, Genome Medicine.

[11]  O. Ramilo,et al.  Infliximab for intensification of primary therapy for Kawasaki disease: a phase 3 randomised, double-blind, placebo-controlled trial , 2014, The Lancet.

[12]  L. Coin,et al.  Diagnosis of childhood tuberculosis and host RNA expression in Africa. , 2014, The New England journal of medicine.

[13]  Chin‐Yun Lee,et al.  Estimation of the incidence of Kawasaki disease in Taiwan. A comparison of two data sources: nationwide hospital survey and national health insurance claims. , 2014, Pediatrics and neonatology.

[14]  E. Frangou,et al.  Gene expression and regulation in systemic lupus erythematosus , 2013, European journal of clinical investigation.

[15]  Colin G Fink,et al.  Transcriptomic Profiling in Childhood H1N1/09 Influenza Reveals Reduced Expression of Protein Synthesis Genes , 2013, The Journal of infectious diseases.

[16]  S. Crosby,et al.  Gene expression profiles in febrile children with defined viral and bacterial infection , 2013, Proceedings of the National Academy of Sciences.

[17]  M. El-Adawy,et al.  Preventing Coronary Artery Abnormalities: A Need for Earlier Diagnosis and Treatment of Kawasaki Disease , 2012, The Pediatric infectious disease journal.

[18]  J. Burns,et al.  Kawasaki disease: late cardiovascular sequelae , 2012, Current opinion in cardiology.

[19]  T. Matsuishi,et al.  Long-Term Prognosis of Patients With Kawasaki Disease Complicated by Giant Coronary Aneurysms: A Single-Institution Experience , 2011, Circulation.

[20]  C. Weinberg,et al.  Gene expression profiles from discordant monozygotic twins suggest that molecular pathways are shared among multiple systemic autoimmune diseases , 2011, Arthritis research & therapy.

[21]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[22]  Calvin Lin,et al.  Transcript abundance patterns in Kawasaki disease patients with intravenous immunoglobulin resistance. , 2010, Human immunology.

[23]  R. Holman,et al.  Hospitalizations for Kawasaki Syndrome Among Children in the United States, 1997–2007 , 2010, The Pediatric infectious disease journal.

[24]  Sumio Watanabe,et al.  Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory , 2010, J. Mach. Learn. Res..

[25]  D. Relman,et al.  Gene transcript abundance profiles distinguish Kawasaki disease from adenovirus infection. , 2009, The Journal of infectious diseases.

[26]  T. K. van den Berg,et al.  The macrophage scavenger receptor CD163 functions as an innate immune sensor for bacteria. , 2009, Blood.

[27]  M. Goldacre,et al.  Kawasaki Disease in England: Ethnicity, Deprivation, and Respiratory Pathogens , 2009, The Pediatric infectious disease journal.

[28]  J. Abe,et al.  Elevated granulocyte colony-stimulating factor levels predict treatment failure in patients with Kawasaki disease. , 2008, The Journal of allergy and clinical immunology.

[29]  Pan Du,et al.  lumi: a pipeline for processing Illumina microarray , 2008, Bioinform..

[30]  P. Brown,et al.  Gene-expression patterns reveal underlying biological processes in Kawasaki disease , 2007, Genome Biology.

[31]  S. Colan,et al.  Delayed Diagnosis of Kawasaki Disease: What Are the Risk Factors? , 2007, Pediatrics.

[32]  Junbao Du,et al.  VALGANCICLOVIR FOR CONGENITAL CMV INFECTION: A PILOT STUDY ON PLASMA CONCENTRATION IN NEWBORNS AND INFANTS , 2007, The Pediatric infectious disease journal.

[33]  J. Banchereau,et al.  Gene expression patterns in blood leukocytes discriminate patients with acute infections. , 2007, Blood.

[34]  J. Abe,et al.  Gene Expression Profiling of the Effect of High-Dose Intravenous Ig in Patients with Kawasaki Disease1 , 2005, The Journal of Immunology.

[35]  Kunihiko Kobayashi,et al.  Differential gene expression of S100 protein family in leukocytes from patients with Kawasaki disease , 2005, European Journal of Pediatrics.

[36]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[37]  Walter R Wilson,et al.  Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Statement for Health Professionals From the Committee on Rheumatic Fever, Endocarditis and Kawasaki Disease, Council on Cardiovascular Disease in the Young, American Heart Association , 2004, Pediatrics.

[38]  M. Suarez‐Almazor,et al.  International League of Associations for Rheumatology: International League of Associations for Rheumatology classification of juvenile idiopathic arthritis: second revision, Edmonton, 2001 , 2004 .

[39]  R. Holman,et al.  Risk factors for bronchiolitis-associated deaths among infants in the United States , 2003, The Pediatric infectious disease journal.

[40]  D. Wilkinson Gene Expression Patterns , 2002, Brain Research.

[41]  K Hashino,et al.  Long-term consequences of Kawasaki disease. A 10- to 21-year follow-up study of 594 patients. , 1996, Circulation.

[42]  H. Yanagawa,et al.  A new infantile acute febrile mucocutaneous lymph node syndrome (MLNS) prevailing in Japan. , 1974, Pediatrics.

[43]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[44]  Y. Saeki,et al.  Isolation and expression profiling of genes upregulated in the peripheral blood cells of systemic lupus erythematosus patients. , 2005, DNA research : an international journal for rapid publication of reports on genes and genomes.

[45]  Alex E. Lash,et al.  Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..

[46]  José M Bernardo and Adrian F M Smith Bayesian Theory , 2001 .

[47]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[48]  W. Youden,et al.  Index for rating diagnostic tests , 1950, Cancer.