Institut National de la Santé et de la Recherche Médicale, Centre de Recherche des Cordeliers, Sorbonne Université, Université de Paris, F-75006 Paris, France.
École D'ingénieur Généraliste en Informatique et Technologies du Numérique, 30-32 Avenue de la République, F-94800 Villejuif, France.
Autoimmun Rev. 2021 Jul;20(7):102850. doi: 10.1016/j.autrev.2021.102850. Epub 2021 May 7.
Intravenous immunoglobulin (IVIG) is used to treat several autoimmune and inflammatory diseases, but some patients are refractory to IVIG and require alternative treatments. Identifying a biomarker that could segregate IVIG responders from non-responders has been a subject of intense research. Unfortunately, previous transcriptomic studies aimed at addressing IVIG resistance have failed to predict a biomarker that could identify IVIG-non-responders. Therefore, we used a novel data mining technique on the publicly available transcriptomic data of Kawasaki disease (KD) patients treated with IVIG to identify potential biomarkers of IVIG response. By studying the boolean patterns hidden in the expression profiles of KD patients undergoing IVIG therapy, we have identified new metabolic pathways implicated in IVIG resistance in KD. These pathways could be used as biomarkers to segregate IVIG non-responders from responders prior to IVIG infusion. Also, boolean analysis of the transcriptomic data could be further extended to identify a universal biomarker that might predict IVIG response in other autoimmune diseases.
静脉注射免疫球蛋白（IVIG）用于治疗多种自身免疫性和炎症性疾病，但有些患者对 IVIG 无反应，需要替代治疗。确定一种生物标志物，将 IVIG 应答者与非应答者区分开来，一直是研究的热点。不幸的是，以前旨在解决 IVIG 耐药性的转录组学研究未能预测出可识别 IVIG 无反应者的生物标志物。因此，我们使用一种新的数据挖掘技术对接受 IVIG 治疗的川崎病（KD）患者的公开转录组学数据进行分析，以确定 IVIG 反应的潜在生物标志物。通过研究接受 IVIG 治疗的 KD 患者表达谱中隐藏的布尔模式，我们确定了与 KD 中 IVIG 耐药性相关的新代谢途径。这些途径可用于在 IVIG 输注前将 IVIG 无反应者与应答者区分开来。此外，对转录组数据的布尔分析还可以进一步扩展，以确定一种通用的生物标志物，可能预测其他自身免疫性疾病中 IVIG 的反应。
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