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利用基因对特征区分川崎病与发热性传染病。

Distinguishing Kawasaki Disease from Febrile Infectious Disease Using Gene Pair Signatures.

机构信息

Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Guangzhou, 510623 Guangdong, China.

Department of Pediatric Cardiology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623 Guangdong, China.

出版信息

Biomed Res Int. 2020 Apr 26;2020:6539398. doi: 10.1155/2020/6539398. eCollection 2020.

Abstract

Kawasaki disease (KD) is an acute systemic vasculitis of childhood with prolonged fever, and the diagnosis of KD is mainly based on clinical criteria, which is prone to misdiagnosis with other febrile infectious (FI) diseases. Currently, there remain no effective molecular markers for KD diagnosis. In this study, we aimed to use a relative-expression-based method k-TSP and resampling framework to identify robust gene pair signatures to distinguish KD from bacterial and virus febrile infectious diseases. Our study pool consisted of 808 childhood patients from several studies and assigned to three groups, namely, the discovery set ( = 224), validation set-1 ( = 197), and validation set-2 ( = 387). We had identified 60 biologically relevant gene pairs and developed a top-ranked gene pair classifier (TRGP) using the first seven signatures, with the area under the receiver-operating characteristic curves (AUROC) of 0.947 (95% CI, 0.918-0.976), a sensitivity of 0.936 (95% CI, 0.872-0.987), and a specificity of 0.774 (95% CI, 0.705-0.836) in the discovery set. In the validation set-1, the TRGP classifier distinguished KD from FI with AUROC of 0.955 (95% CI, 0.919-0.991), a sensitivity of 0.959 (95% CI, 0.925-0.986), and a specificity of 0.863 (95% CI, 0.764-0.961). In the validation set-2, the predictive performance of classification was with an AUROC of 0.796 (95% CI, 0.747-0.845), a sensitivity of 0.797 (95% CI, 0.720-0.864), and a specificity of 0.661 (95% CI, 0.606-0.717). Our study reveals that gene pair signatures are robust across diverse studies and can be utilized as objective biomarkers to distinguish KD from FI, helping to develop a fast, simple, and effective molecular approach to improve the diagnosis of KD.

摘要

川崎病(KD)是一种儿童期的急性全身性血管炎,其诊断主要基于临床标准,容易与其他发热性传染病(FI)混淆。目前,KD 诊断仍没有有效的分子标志物。在这项研究中,我们旨在使用相对表达的 k-TSP 方法和重采样框架,以识别稳健的基因对特征,以区分 KD 与细菌性和病毒性发热性传染病。我们的研究队列由来自多个研究的 808 名儿童患者组成,并分为三组,即发现组(n=224)、验证集-1(n=197)和验证集-2(n=387)。我们鉴定了 60 个有生物学意义的基因对,并使用前七个特征开发了一个顶级基因对分类器(TRGP),在发现组中,该分类器的受试者工作特征曲线下面积(AUROC)为 0.947(95%置信区间,0.918-0.976),敏感性为 0.936(95%置信区间,0.872-0.987),特异性为 0.774(95%置信区间,0.705-0.836)。在验证集-1 中,TRGP 分类器将 KD 与 FI 区分开来,AUROC 为 0.955(95%置信区间,0.919-0.991),敏感性为 0.959(95%置信区间,0.925-0.986),特异性为 0.863(95%置信区间,0.764-0.961)。在验证集-2 中,分类的预测性能为 AUROC 为 0.796(95%置信区间,0.747-0.845),敏感性为 0.797(95%置信区间,0.720-0.864),特异性为 0.661(95%置信区间,0.606-0.717)。我们的研究表明,基因对特征在不同的研究中是稳健的,可以作为区分 KD 与 FI 的客观生物标志物,有助于开发一种快速、简单、有效的分子方法来提高 KD 的诊断水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2370/7201505/1140579832f1/BMRI2020-6539398.001.jpg

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