Machine learning implicates the IL-18 signaling axis in severe asthma.
Machine learning implicates the IL-18 signaling axis in severe asthma.
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DOI：
10.1172/jci.insight.149945
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发表时间：
2021-11-08
期刊：
影响因子：
8
通讯作者：
Wenzel SE
中科院分区：
文献类型：
--
作者：
Camiolo MJ;Zhou X;Wei Q;Trejo Bittar HE;Kaminski N;Ray A;Wenzel SE
哮喘是一种常见疾病，其自然病史和患者发病率变化很大。长期以来，异质性一直受到重视，许多工作都集中在识别具有相似病理生物学基础的患者亚群。先前的重症哮喘研究计划(SARP)队列研究将基因表达变化与特定的临床和生理特征联系起来。虽然这些数据对于假设生成非常有价值，但这些数据包括大量的候选基因列表，这使得目标识别和验证变得复杂。在这项分析中，我们使用支气管上皮细胞基因表达数据对SARP队列进行了无监督的聚类，确定了易加重哮喘并伴有肺功能受损的参与者的转录特征。在临床上，这个哮喘组的参与者表现出一种混合的炎症过程，并具有核因子-κB和激活蛋白1(AP-1)激活的转录特征，尽管皮质类固醇水平很高。使用有监督的机器学习，我们发现了一组31个基因，它们对患者进行了高精度的分类，并可以重建我们的患者聚集在外部队列中的临床和转录特征。在这些基因中，IL18R1(IL-18受体1)与肺功能呈负相关，并且在最严重的患者群中高表达。我们验证了IL18R1蛋白在肺组织中的表达，并确定了下游的NF-κB和AP-1活性，支持了IL-18在重症哮喘发病机制中的信号转导，并强调了这一途径用于基因和通路的发现。
Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous studies of the Severe Asthma Research Program (SARP) cohort linked gene expression changes to specific clinical and physiologic characteristics. While invaluable for hypothesis generation, these data include extensive candidate gene lists that complicate target identification and validation. In this analysis, we performed unsupervised clustering of the SARP cohort using bronchial epithelial cell gene expression data, identifying a transcriptional signature for participants suffering exacerbation-prone asthma with impaired lung function. Clinically, participants in this asthma cluster exhibited a mixed inflammatory process and bore transcriptional hallmarks of NF-κB and activator protein 1 (AP-1) activation, despite high corticosteroid exposure. Using supervised machine learning, we found a set of 31 genes that classified patients with high accuracy and could reconstitute clinical and transcriptional hallmarks of our patient clustering in an external cohort. Of these genes, IL18R1 (IL-18 Receptor 1) negatively associated with lung function and was highly expressed in the most severe patient cluster. We validated IL18R1 protein expression in lung tissue and identified downstream NF-κB and AP-1 activity, supporting IL-18 signaling in severe asthma pathogenesis and highlighting this approach for gene and pathway discovery.
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