Dataset Information

Assessment of the Clinical Heterogeneity of Kawasaki Disease Using Genetic Variants of BLK and FCGR2A.

ABSTRACT: BACKGROUND AND OBJECTIVES:Patients with Kawasaki disease (KD) are clinically heterogeneous because its diagnosis is based solely on clinical observation and there are no definitive biomarkers. We dissected the clinical heterogeneity of KD patients using the KD-associated genetic variants. METHODS:We performed a genetic association analysis in several KD subgroups categorized by clinical characteristics using the KD-associated variants of the B lymphoid tyrosine kinase (BLK; rs6993775) and Fc gamma receptor II a (FCGR2A; rs1801274) in a large number of case (n=1,011) and control (n=4,533) samples. RESULTS:BLK and FCGR2A were very significantly associated with KD in Korean KD patients (odds ratio [OR],1.48; p=4.63×10?¹¹ for BLK, and OR, 1.26; p=1.42×10?? for FCGR2A). However, in KD subgroup analysis, we found that neither BLK nor FCGR2A were associated with either incomplete Kawasaki disease (iKD) type patients or those older than 5 years of age (p>0.2), suggesting that patients with iKD or those older than 5 years of age are a unique subgroup of KD. In genetic association analysis after excluding iKD patients and those older than 5 years old, we found that BLK was associated with all KD subgroups, whereas FCGR2A was specifically associated with male KD patients younger than 1 year of age (OR, 2.22; p=2.35×10??). CONCLUSIONS:KD is a clinically and genetically heterogeneous disease. These findings will provide new insights into the clinical and genetic heterogeneity of KD.

SUBMITTER: Sim BK

PROVIDER: S-EPMC6331319 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Assessment of the Clinical Heterogeneity of Kawasaki Disease Using Genetic Variants of <i>BLK</i> and <i>FCGR2A</i>.

Sim Bo Kyung BK Park Hyein H Kim Jae Jung JJ Yun Sin Weon SW Yu Jeong Jin JJ Yoon Kyung Lim KL Lee Kyung Yil KY Kil Hong Ryang HR Kim Gi Beom GB Han Myung Ki MK Song Min Seob MS Lee Hyoung Doo HD Ha Kee Soo KS Sohn Sejung S Hong Young Mi YM Jang Gi Young GY Lee Jong Keuk JK

Korean circulation journal 20181019 1

<h4>Background and objectives</h4>Patients with Kawasaki disease (KD) are clinically heterogeneous because its diagnosis is based solely on clinical observation and there are no definitive biomarkers. We dissected the clinical heterogeneity of KD patients using the KD-associated genetic variants.<h4>Methods</h4>We performed a genetic association analysis in several KD subgroups categorized by clinical characteristics using the KD-associated variants of the B lymphoid tyrosine kinase (<i>BLK</i>; ...[more]

PMID: 30468029

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Project description:BackgroundAbout 10-20% of Kawasaki disease (KD) patients are resistant to the initial infusion of intravenous immunoglobin (IVIG). The aim of this study was to assess whether IVIG resistance in KD patients could be predicted using standard clinical and laboratory features.MethodsData were from two cohorts: a Korean cohort of 7101 KD patients from 2015 to 2017 and a cohort of 649 KD patients from San Diego enrolled from 1998 to 2021. Features included laboratory values, the worst Z-score from the initial echocardiogram or during hospitalization, and the five clinical KD signs at presentation.ResultsFive machine learning models achieved a maximum median AUC of 0.711 [IQR: 0.706-0.72] in the Korean cohort and 0.696 [IQR: 0.609-0.722] in the San Diego cohort during stratified 10-fold cross-validation using significant laboratory features identified from univariate analysis. Adding the Z-score, KD clinical signs, or both did not considerably improve the median AUC in either cohort.ConclusionsUsing commonly measured clinical laboratory data alone or in conjunction with echocardiographic findings and clinical features is not sufficient to predict IVIG resistance. Further attempts to predict IVIG resistance will need to incorporate additional data such as transcriptomics, proteomics, and genetics to achieve meaningful predictive utility.ImpactWe demonstrated that laboratory, echocardiographic, and clinical findings cannot predict intravenous immunoglobin (IVIG) resistance to a clinically meaningful extent using machine learning in a homogenous Asian or ethnically diverse population of patients with Kawasaki disease (KD). Visualizing these features using uniform manifold approximation and projection (UMAP) is an important step to evaluate predictive utility in a qualitative manner. Further attempts to predict IVIG resistance in KD patients will need to incorporate novel biomarkers or other specialized features such as genetic differences or transcriptomics to be clinically useful.

Dataset Information

Assessment of the Clinical Heterogeneity of Kawasaki Disease Using Genetic Variants of BLK and FCGR2A.

Publications

Assessment of the Clinical Heterogeneity of Kawasaki Disease Using Genetic Variants of <i>BLK</i> and <i>FCGR2A</i>.

Similar Datasets

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