Wu Wei-Sheng, Yang Tzu-Hsien, Chen Kuang-Den, Lin Po-Heng, Chen Guan-Ru, Kuo Ho-Chang
Department of Electrical Engineering, National Cheng Kung University, University Road, 701 Tainan, Taiwan.
Department of Information Management, National University of Kaohsiung, Kaohsiung University Rd, 811 Kaohsiung, Taiwan.
Comput Struct Biotechnol J. 2022 Mar 10;20:1295-1305. doi: 10.1016/j.csbj.2022.02.032. eCollection 2022.
Kawasaki disease (KD) is a form of acute systemic vasculitis that primarily affects children and has become the most common cause of acquired heart disease. While the etiopathogenesis of KD remains unknown, the diagnostic criteria of KD have been well established. Nevertheless, the diagnosis of KD is currently based on subjective clinical symptoms, and no molecular biomarker is yet available. We have previously performed and combined methylation array (Illumina HumanMethylation450 BeadChip) and transcriptome array (Affymetrix GeneChip Human Transcriptome Array 2.0) to identify genes that are differentially methylated/expressed in KD patients compared with control subjects. We have found that decreased methylation levels combined with elevated gene expression can indicate genes (e.g., toll-like receptors and CD177) involved in the disease mechanisms of KD. In this study, we constructed a database called KDmarkers to allow researchers to access these valuable potential KD biomarkers identified via methylation array and transcriptome array. KDmarkers provides three search modes. First, users can search genes differentially methylated and/or differentially expressed in KD patients compared with control subjects. Second, users can check the KD patient groups in which a given gene is differentially methylated and/or differentially expressed. Third, users can explore the DNA methylation levels and gene expression levels in all samples (KD patients and controls) for a particular gene of interest. We further demonstrated that the results in KDmarkers are strongly associated with KD immune responses. All analysis results can be downloaded for downstream experimental designs. KDmarkers is available online at https://cosbi.ee.ncku.edu.tw/KDmarkers/.
川崎病（KD）是一种主要影响儿童的急性全身性血管炎，已成为后天性心脏病最常见的病因。虽然KD的发病机制尚不清楚，但KD的诊断标准已经明确确立。然而，目前KD的诊断基于主观临床症状，尚无分子生物标志物可用。我们之前进行并结合了甲基化芯片（Illumina HumanMethylation450 BeadChip）和转录组芯片（Affymetrix GeneChip Human Transcriptome Array 2.0），以鉴定与对照组相比在KD患者中差异甲基化/表达的基因。我们发现甲基化水平降低与基因表达升高相结合可表明参与KD疾病机制的基因（如Toll样受体和CD177）。在本研究中，我们构建了一个名为KDmarkers的数据库，以便研究人员能够获取通过甲基化芯片和转录组芯片鉴定出的这些有价值的潜在KD生物标志物。KDmarkers提供三种搜索模式。首先，用户可以搜索与对照组相比在KD患者中差异甲基化和/或差异表达的基因。其次，用户可以查看给定基因差异甲基化和/或差异表达的KD患者组。第三，用户可以探索感兴趣的特定基因在所有样本（KD患者和对照组）中的DNA甲基化水平和基因表达水平。我们进一步证明KDmarkers中的结果与KD免疫反应密切相关。所有分析结果均可下载用于下游实验设计。KDmarkers可在https://cosbi.ee.ncku.edu.tw/KDmarkers/在线获取。
