Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking.
Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking.
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基于机器学习和分子对接鉴定糖尿病视网膜病变中潜在的铁死亡相关生物标志物和药理化合物
DOI：
10.3389/fendo.2022.988506
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发表时间：
2022
影响因子：
5.2
通讯作者：
中科院分区：
文献类型：
--
作者：
糖尿病视网膜病变（DR）是一种神经血管疾病，是世界范围内视力丧失的主要原因，严重影响生活质量。多项研究表明，铁下垂在DR发病机制中起重要作用；然而，其分子机制尚未完全阐明。因此，本研究旨在研究铁下垂的发病机制，探索潜在的铁下垂相关基因生物标志物和治疗dr的药理学化合物。在GSE102485数据集中鉴定了铁下垂相关差异表达基因（DEGs）。然后进行功能富集分析，并构建蛋白相互作用（PPI）网络来筛选铁凋亡相关枢纽基因（FRHGs）的候选基因。基于最小绝对收缩和选择算子（LASSO）回归和随机森林算法进一步筛选FRHGs，然后使用GSE60436数据集和前人研究进行验证。采用受试者工作特征（ROC）曲线单因素分析评价frhg的诊断效能，并进行免疫浸润分析。此外，通过分子对接验证了靶向FRHGs的药理化合物。最后，使用定量实时聚合酶链反应（qRT-PCR）分析对frhg进行验证。提取了40个与铁死亡相关的deg，功能富集分析主要涉及凋亡信号，氧化应激反应，铁死亡以及脂质和动脉粥样硬化途径。通过整合PPI、LASSO回归和随机森林分析来筛选FRHGs，并通过验证，我们确定了5个诊断效果良好的FRHGs （CAV1、CD44、NOX4、TLR4和TP53）。免疫浸润分析显示，DR患者的免疫微环境变化可能与这5种frhg有关。分子对接也表明谷胱甘肽与CAV1和TLR4蛋白结合较强。最后，通过qRT-PCR分析，在高糖环境下培养的人视网膜毛细血管内皮细胞中，FRHGs （CD44、NOX4、TLR4和TP53）的表达上调。CAV1, CD44, NOX4， TLR4和TP53是DR的潜在生物标志物，可能通过调节铁下垂和免疫微环境参与其发生和发展。此外，谷胱甘肽通过针对铁下垂表现出潜在的治疗DR疗效。本研究为DR的发病机制、诊断和治疗提供了新的认识。
Diabetic retinopathy (DR), a neurovascular disease, is a leading cause of visual loss worldwide and severely affects quality of life. Several studies have shown that ferroptosis plays an important role in the pathogenesis of DR; however, its molecule mechanism remains incompletely elucidated. Hence, this study aimed to investigate the pathogenesis of ferroptosis and explore potential ferroptosis-related gene biomarkers and a pharmacological compound for treating DR. Ferroptosis-related differentially expressed genes (DEGs) were identified in the GSE102485 dataset. Functional enrichment analyses were then performed and a protein-protein interaction (PPI) network was constructed to screen candidates of ferroptosis-related hub genes (FRHGs). FRHGs were further screened based on least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms, and were then validated with the GSE60436 dataset and previous studies. A receiver operating characteristic (ROC) curve monofactor analysis was conducted to evaluate the diagnostic performance of the FRHGs, and immune infiltration analysis was performed. Moreover, the pharmacological compound targeting the FRHGs were verified by molecular docking. Finally, the FRHGs were validated using quantitative real-time polymerase chain reaction (qRT-PCR) analysis. The 40 ferroptosis-related DEGs were extracted, and functional enrichment analyses mainly implicated apoptotic signaling, response to oxidative stress, ferroptosis, and lipid and atherosclerosis pathways. By integrating the PPI, LASSO regression, and random forest analyses to screen the FRHGs, and through validation, we identified five FRHGs that performed well in the diagnosis (CAV1, CD44, NOX4, TLR4, and TP53). Immune infiltration analysis revealed that immune microenvironment changes in DR patients may be related to these five FRHGs. Molecular docking also showed that glutathione strongly bound the CAV1 and TLR4 proteins. Finally, the upregulated expression of FRHGs (CD44, NOX4, TLR4, and TP53) was validated by qRT-PCR analysis in human retinal capillary endothelial cells cultured under high-glucose environment. CAV1, CD44, NOX4, TLR4, and TP53 are potential biomarkers for DR and may be involved in its occurrence and progression by regulating ferroptosis and the immune microenvironment. Further, glutathione exhibits potential therapeutic efficacy on DR by targeting ferroptosis. Our study provides new insights into the ferroptosis-related pathogenesis of DR, as well as its diagnosis and treatment.
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