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支气管哮喘是以慢性气道炎症为核心特征的呼吸系统疾病,现有治疗难以逆转气道重塑且病情易反复,亟须挖掘早期诊断标志物与新型治疗靶点。本研究整合GEO数据库哮喘转录组数据,开展差异表达基因(differentially expressed genes,DEGs)分析;运用Finn Gen数据库的全基因组关联研究(genome-wide association studies, GWAS)汇总统计数据,利用表达数量性状位点(expression quantitative trait loci, e QTL)信息筛选工具变量,进行孟德尔随机化(Mendelian randomization, MR)分析,将MR得到的遗传风险基因与DEGs取交集,筛选出关键共表达基因。进一步采用最小绝对收缩和选择算子(least absolute shrinkage and selection operator, LASSO)回归进行特征基因选择,通过CTD数据库、 ITCM数据库、古今医案云平台预测潜在调控支气管哮喘的中药,并分析其性味归经及功效。最后运用分子对接验证活性成分与靶蛋白的结合能力。本研究共鉴定933个哮喘DEGs与374个MR风险基因,交集获得10个核心基因(5个风险基因和5个保护基因),主要参与B细胞受体信号转导、糖代谢、可溶性NSF附着蛋白受体(soluble NSF attachment protein receptor, SNARE)介导囊泡运输等通路;经LASSO回归确定VAMP8、 MRPL48、 DDIT3、 TOM1和TRANK1共5个具有良好诊断价值的特征基因;预测得到276味相关中药,药性以温、寒、平为主,药味以苦、辛、甘为主,归经以肝、肺、胃、脾、肾经为主,分类以清热药、补虚药、活血化瘀药等为主;分子对接表明,茯苓活性成分与靶蛋白可稳定结合。综上,本研究通过遗传学与生物信息学整合分析,鉴定出10个与哮喘因果关联的核心基因及5个候选诊断标志物,为哮喘的机制阐释与精准诊疗提供了理论依据。
Abstract：Bronchial asthma is a respiratory disease characterized by chronic airway inflammation. Existing treatments are difficult to reverse airway remodeling and the disease course is prone to recurrence, which highlights an urgent need to explore early diagnostic biomarkers and novel therapeutic targets. This study integrated asthma transcriptomic data from the GEO database and performed differentially expressed genes( DEGs) analysis. Summary statistics from genome-wide association studies( GWAS) in the Finn Gen database were adopted, and instrumental variables were selected using expression quantitative trait loci( e QTL) data for Mendelian randomization( MR) analysis. Key co-expressed genes were identified by intersecting MR-derived genetic risk genes with DEGs. Furthermore, the least absolute shrinkage and selection operator( LASSO) regression was applied for characteristic gene screening. Potential Chinese herbs for regulating bronchial asthma were predicted via the CTD database, ITCM database, and Ancient and Modern Medical Records Cloud Platform, followed by an analysis of their natures, flavors, meridian tropism, and pharmacological efficacies. Finally, molecular docking was conducted to validate the binding affinity between active ingredients and target proteins. A total of 933 asthma-related DEGs and 374 MR-derived risk genes were identified in this study, and 10 core genes(5 risk genes and 5 protective genes) were obtained by intersection analysis. These genes were primarily enriched in B-cell receptor signaling pathway, glucose metabolism, and soluble NSF-attachment protein receptor( SNARE)-mediated vesicular trafficking pathways. Five characteristic genes(VAMP8, MRPL48, DDIT3, TOM1, and TRANK1) with favorable diagnostic value were identified using LASSO regression. A total of 276 relevant Chinese herbs were predicted, which were mostly warm, cold, and neutral in nature, bitter, pungent, and sweet in flavor, and predominantly acted on the liver, lung, stomach, spleen, and kidney meridians. These herbs were mainly classified as heat-clearing herbs, tonifying herbs, and blood-activating and stasis-resolving herbs. Molecular docking results demonstrated that the active ingredients of Poria cocos could bind stably to the target proteins. Collectively, this study identified 10 core genes causally associated with asthma and 5 candidate diagnostic biomarkers through integrative genetic and bioinformatic analyses, providing a theoretical foundation for illustrating the pathoge-nesis and precision diagnosis and treatment of bronchial asthma.
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基本信息:
DOI：10.13417/j.gab.045.000945
中图分类号:R562.25;Q811.4
引用信息:
[1]罗成,叶远航,覃琬婷.基于孟德尔随机化、生物信息学和机器学习筛选支气管哮喘关键基因[J].基因组学与应用生物学,2026,45(04):945-963.DOI:10.13417/j.gab.045.000945.
基金信息:
国家自然科学基金项目(82505509); 四川省自然科学基金项目(2025ZNSFSC1853); 中国博士后科学基金第75批面上资助项目(地区专项支持计划)(2024MD753905); 成都市卫生健康委员会-成都中医药大学委校院联合创新基金项目(WXLH202403266)共同资助
2026-06-04
2026-06-04
2026-06-04