慢性呼吸系统疾病关键标志物筛选与辅助诊断模型建立研究
Research on Key Biomarker Screening and Auxiliary Diagnostic Model Building for Chronic Respiratory Diseases
摘要: 目的：探讨COVID-19与慢性阻塞性肺疾病及哮喘的生物学共同作用机制并建立基于少数基因的疾病诊断模型。方法：本研究结合转录组数据分析、差异基因筛选、GO和KEGG功能富集分析、蛋白互作网络构建、统计学分析及机器学习方法，从多角度解析COVID-19对慢性呼吸系统疾病患者的影响。结果：筛选出差异共同表达基因，并通过富集分析揭示其主要参与免疫应答、炎症信号传递及病毒感染相关的分子通路；蛋白互作网络分析发现了TLR2、MMP9、CXCR4、CCR7、IL1A和CXCL8等关键基因，可能在炎症调控和疾病进展中起重要作用；同时，对于慢性阻塞性肺疾病，建立了PTPN7等少数基因的诊断模型，对于哮喘，建立了CLC等少数基因的诊断模型。结论：COVID-19通过多系统通路加剧慢性呼吸系统疾病的炎症和免疫失调，为个性化治疗策略提供了新的研究方向。同时，建立了基于基因的疾病诊断模型，为未来的治疗和管理提供了重要的启示。
Abstract: Objective: To explore the common biological mechanisms of interaction between COVID-19 and chronic obstructive pulmonary disease (COPD) as well as asthma, and to establish disease diagnostic models based on a small number of genes. Methods: This study combined transcriptome data analysis, differential gene screening, GO and KEGG functional enrichment analysis, protein-protein interaction network construction, statistical analysis, and machine learning methods to comprehensively analyze the impact of COVID-19 on patients with chronic respiratory diseases from multiple perspectives. Results: Differential co-expressed genes were identified, and enrichment analysis revealed that they mainly participate in immune responses, inflammatory signaling pathways, and virus infection-related molecular pathways. Protein-protein interaction network analysis identified key genes such as TLR2, MMP9, CXCR4, CCR7, IL1A, and CXCL8, which may play important roles in inflammation regulation and disease progression. Meanwhile, for COPD, a diagnostic model based on a small number of genes including PTPN7 was established, and for asthma, a diagnostic model based on a small number of genes including CLC was established. Conclusion: COVID-19 exacerbates the inflammation and immune dysregulation in chronic respiratory diseases through multiple systemic pathways, providing new research directions for personalized treatment strategies. Additionally, the establishment of gene-based disease diagnostic models offers important insights for future treatment and management.
文章引用：李祖豪, 吴元斌. 慢性呼吸系统疾病关键标志物筛选与辅助诊断模型建立研究[J]. 生物医学, 2025, 15(4): 780-797. https://doi.org/10.12677/hjbm.2025.154084

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