DataSheet_1_Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma.pdf

BackgroundAlthough studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking.MethodsTranscriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs.ResultsNineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors.ConclusionPyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma.

尽管已有研究表明细胞焦亡与哮喘的进展密切相关，但对于哮喘患者中免疫细胞与焦亡相关基因（PRGs）相互作用的临床意义进行系统分析的研究尚显不足。方法：采用不同病程哮喘患者的转录组测序数据集，筛选焦亡相关差异表达基因并执行生物学功能分析。通过K-means无监督聚类方法进行聚类，以识别哮喘中的焦亡相关亚型，并探讨难以控制的亚型的生物学功能特征。利用哮喘小鼠模型筛选和验证亚型间的诊断标志物。基于CIBERSORT评估气道上皮中免疫细胞的浸润，并分析诊断标志物与免疫细胞之间的相关性。最终，通过结合焦亡亚型中的差异表达基因与哮喘控制情况，建立了风险预测模型并进行实验验证。利用cMAP数据库和分子对接预测潜在的药物治疗药物。结果：在轻度至重度哮喘患者中，鉴定出19个差异表达的PRGs和两种亚型。两种亚型在哮喘控制和FEV1可逆性方面存在显著差异。难以控制的亚型与糖皮质激素抵抗和气道重塑密切相关。BNIP3被鉴定为诊断标志物，并与M2巨噬细胞等免疫细胞浸润相关。包含四个基因的风险预测模型具有准确的分类效率和预测价值。cMAP数据库中可能对哮喘具有治疗作用的小分子主要是DPP4抑制剂。结论：焦亡及其介导的免疫表型在哮喘的发生、发展和预后中至关重要。基于PRGs开发的预测模型和药物可能为哮喘的管理提供新的解决方案。