目的 支氣管哮喘是嚴重影響全球公眾健康的重大慢病之一，通過使用GEO數據集和孟德爾隨機化方法確定哮喘新的遺傳靶點，為臨床治療和機制研究提供依據。方法 通過基因表達綜合數據庫（GEO）獲得相關數據集，獲得數據后進行差異基因的表達數量性狀位點（expression quantitative trait locus，eQTL）分析和孟德爾隨機化（mendelian randomization，MR）分析，確定潛在靶點；再通過基因集合富集分析（gene set enrichment analysis，GSEA）和基因本體論（gene ontology，GO）/京都基因和基因組百科全書（Kyoto encyclopedia of genes and genomes，KEGG）富集分析來探索這些基因的功能和富集通路；通過免疫浸潤方法探索靶點與相關免疫細胞的關聯(lián)；利用醫(yī)學本體信息檢索平臺Coremine Medical數據庫，篩選核心基因相關治療中藥并進行歸納分析，最后設立外部驗證集進行驗證。結果 共鑒定出280個高表達基因和1 127個低表達基因；MR分析確定了12個與哮喘顯著相關的核心基因靶點：PGAP3、FAM177A1、UGDH、AASDH、CREB1、ZNF429、CCNG2、SKAP2、ANKRD10、DR1、ISOC1以及LPAR6；預測出人參、五味子、麻黃、杜仲、北沙參等67味靶向中藥，主要涉及補虛藥、活血化瘀藥；MR分析結果與外部驗證集的結果一致，強調了本研究的可靠性。結論 篩選并驗證了12個哮喘潛在靶點，并對相關干預中藥進行了預測，為進一步深入探究哮喘的發(fā)病機制、早期篩查診斷、早期預防、靶向治療以及中醫(yī)藥臨床診療提供了新的線索。

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

國家自然科學基金項目（82474483）;國家重點研發(fā)計劃（2023YFC3502602，2023YFC3502600）;河南省高校科技創(chuàng)新團隊（23IRTSTHN027）;國家中醫(yī)臨床研究基地科研專項（2022JDZX046）;河南省科技攻關項目（232102310472）;河南省中醫(yī)藥科學研究專項（2022ZY1047）