目的 支气管哮喘是严重影响全球公众健康的重大慢病之一，通过使用GEO数据集和孟德尔随机化方法确定哮喘新的遗传靶点，为临床治疗和机制研究提供依据。方法 通过基因表达综合数据库（GEO）获得相关数据集，获得数据后进行差异基因的表达数量性状位点（expression quantitative trait locus，eQTL）分析和孟德尔随机化（mendelian randomization，MR）分析，确定潜在靶点；再通过基因集合富集分析（gene set enrichment analysis，GSEA）和基因本体论（gene ontology，GO）/京都基因和基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）富集分析来探索这些基因的功能和富集通路；通过免疫浸润方法探索靶点与相关免疫细胞的关联；利用医学本体信息检索平台Coremine Medical数据库，筛选核心基因相关治疗中药并进行归纳分析，最后设立外部验证集进行验证。结果 共鉴定出280个高表达基因和1 127个低表达基因；MR分析确定了12个与哮喘显著相关的核心基因靶点：PGAP3、FAM177A1、UGDH、AASDH、CREB1、ZNF429、CCNG2、SKAP2、ANKRD10、DR1、ISOC1以及LPAR6；预测出人参、五味子、麻黄、杜仲、北沙参等67味靶向中药，主要涉及补虚药、活血化瘀药；MR分析结果与外部验证集的结果一致，强调了本研究的可靠性。结论 筛选并验证了12个哮喘潜在靶点，并对相关干预中药进行了预测，为进一步深入探究哮喘的发病机制、早期筛查诊断、早期预防、靶向治疗以及中医药临床诊疗提供了新的线索。

Objective Bronchial asthma is one of the major chronic diseases that seriously affects public health worldwide. This study aims to identify new genetic targets for asthma by using GEO datasets and mendelian randomization (MR) methods, providing a basis for clinical treatment and mechanism studies. Methods The relevant datasets were obtained through the Gene Expression Omnibus (GEO) database, and after obtaining the data, the expression quantitative trait locus (eQTL) analysis and MR analysis were performed to identify potential targets; the functional roles and pathways of these genes were explored through gene set enrichment analysis (GSEA) and gene ontology (GO)/Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the associations of the targets with relevant immune cells were explored through immune infiltration methods, and core genes were screened through Coremine medical database, which was a platform for medical ontology information retrieval. Coremine medical database to screen core gene-related therapeutic herbal medicines and generalize and analyze them, and finally set up an external validation set for confirmation. Results A total of 280 highly-expressed and 1 127 low-expressed genes were identified. MR analysis identified 12 core genes significantly associated with asthma, which includes PGAP3, FAM177A1, UGDH, AASDH, CREB1, ZNF429, CCNG2, SKAP2, ANKRD10, DR1, ISOC1, and LPAR6; Additionally, 67 traditional Chinese medicines (TCMs) were predicted, including Renshen (Ginseng Radix et Rhizoma), Wuweizi (Schisandrae Chinensis Fructus), Mahuang (Ephedrae Herba), Duzhong (Eucommiae Cortex), and Beishashen (Glehniae Radix), which were mainly involved in the categories of deficiency tonic, blood circulation and blood stasis removing medicines; The MR analysis results were consistent with those of the external validation set, which emphasized the reliability of the present study. Conclusion The present study screened and validated 12 potential asthma targets and predicted the related TCMs, which provides new insights into asthma pathogenesis, early screening, targeted therapy, and the clinical application of TCMs.

Q811.4;R285

国家自然科学基金项目（82474483）;国家重点研发计划（2023YFC3502602，2023YFC3502600）;河南省高校科技创新团队（23IRTSTHN027）;国家中医临床研究基地科研专项（2022JDZX046）;河南省科技攻关项目（232102310472）;河南省中医药科学研究专项（2022ZY1047）