Peng Changfan, Hu Long, Su Wanwen, Hu Xin
Department of Ophthalmology, The Affiliated Panyu Central Hospital,Guangzhou Medical University, Guangzhou, Guangdong, 511400, People's Republic of China.
XJTLU Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, 215123, People's Republic of China.
Sci Rep. 2025 Jul 12;15(1):25244. doi: 10.1038/s41598-025-10656-0.
An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms remain unclear. This study integrates epidemiological and bioinformatics approaches to investigate their relationship, aiming to identify common molecular pathways and validate clinical correlations. Epidemiological data from 3,015 participants in the CHARLS database were analyzed using multivariate logistic regression and Cox proportional hazards models to assess the association between COVID-19 and POAG, with stratification by gender, smoking status, and alcohol consumption. Concurrently, gene expression datasets from GEO (POAG: GSE27276; COVID-19: GSE171110, GSE152418) were used to identify 57 crosstalk genes (CGs) via differential expression analysis. Machine learning algorithms (LASSO, SVM-RFE, Random Forest) were applied to screen POAG diagnostic biomarkers from CGs, followed by construction of transcription factor (TF)-microRNA (miRNA)-protein-compound regulatory networks and consensus clustering to characterize COVID-19 immune microenvironment subtypes. Epidemiological analyses revealed that COVID-19 was an independent risk factor for POAG, with adjusted odds ratios (ORs) of 12.775-15.688 and hazard ratios (HRs) of 4.893-5.060 (all P < 0.001), with stronger associations in males (OR = 15.054, HR = 5.645) and smokers (OR = 29.828, HR = 9.323). HDL levels were significantly higher in POAG patients (P = 0.028), while vb001_s1 positivity was negatively associated with POAG (P < 0.001). Bioinformatics identified CGs enriched in inflammatory response, oxidative stress, and hypoxia pathways. Five potential biomarkers (CA12, ECRG4, CEBPD, HBB, HBA2) showed high diagnostic efficacy (AUC > 0.9) but limited specificity (expressed in uveitis and diabetic retinopathy). COVID-19 patients were stratified into three clusters, with Cluster B exhibiting hyperactive immune microenvironments characterized by elevated HLA class I/II and immune checkpoint genes (CTLA4, PDCD1LG2) in antigen-presenting cells and T cells. This study provides epidemiological and molecular evidence linking POAG to COVID-19, highlighting inflammation and immune dysregulation as shared mechanisms. Gender and smoking modify this association, warranting targeted POAG screening in male COVID-19 survivors and smokers. While identified biomarkers require specificity improvement, findings underscore the need for mechanistic studies (e.g., ACE2-mediated ocular injury, T-cell neuroinflammation) to validate causality and inform clinical management.
原发性开角型青光眼（POAG）与2019冠状病毒病（COVID-19）之间潜在的关联已被提出假说，但因果关系和共同机制仍不清楚。本研究整合流行病学和生物信息学方法来探究它们之间的关系，旨在识别共同的分子途径并验证临床相关性。使用多变量逻辑回归和Cox比例风险模型分析中国健康与养老追踪调查（CHARLS）数据库中3015名参与者的流行病学数据，以评估COVID-19与POAG之间的关联，并按性别、吸烟状况和饮酒情况进行分层。同时，利用来自基因表达综合数据库（GEO）的基因表达数据集（POAG：GSE27276；COVID-19：GSE171110、GSE152418），通过差异表达分析识别57个相互作用基因（CGs）。应用机器学习算法（套索回归、支持向量机递归特征消除法、随机森林）从CGs中筛选POAG诊断生物标志物，随后构建转录因子（TF）-微小RNA（miRNA）-蛋白质-化合物调控网络并进行一致性聚类，以表征COVID-19免疫微环境亚型。流行病学分析显示，COVID-19是POAG的独立危险因素，校正比值比（ORs）为12.775至15.688，风险比（HRs）为4.893至5.060（均P < 0.001），在男性（OR = 15.054，HR = 5.645）和吸烟者（OR = 29.828，HR = 9.323）中关联更强。POAG患者的高密度脂蛋白（HDL）水平显著更高（P = 0.028），而vb001_s1阳性与POAG呈负相关（P < 0.001）。生物信息学确定CGs在炎症反应、氧化应激和缺氧途径中富集。五种潜在生物标志物（CA12、ECRG4、CEBPD、HBB、HBA2）显示出较高的诊断效能（曲线下面积 > 0.9），但特异性有限（在葡萄膜炎和糖尿病视网膜病变中表达）。COVID-19患者被分为三个聚类，聚类B表现出免疫微环境活跃，其特征是抗原呈递细胞和T细胞中HLA I/II类和免疫检查点基因（CTLA4、PDCD1LG2）升高。本研究提供了将POAG与COVID-19联系起来的流行病学和分子证据，突出炎症和免疫失调作为共同机制。性别和吸烟会改变这种关联，因此有必要对男性COVID-19幸存者和吸烟者进行针对性的POAG筛查。虽然已识别的生物标志物需要提高特异性，但研究结果强调需要进行机制研究（如血管紧张素转换酶2介导的眼部损伤、T细胞神经炎症）以验证因果关系并为临床管理提供信息。
