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基于机器学习和分子对接的糖尿病视网膜病变中潜在铁死亡相关生物标志物和药理学化合物的鉴定。

Identification of potential ferroptosis-related biomarkers and a pharmacological compound in diabetic retinopathy based on machine learning and molecular docking.

机构信息

Jiangxi Province Division of National Clinical Research Center for Ocular Diseases, Jiangxi Clinical Research Center for Ophthalmic Disease, Jiangxi Research Institute of Ophthalmology and Visual Science, Affiliated Eye Hospital of Nanchang University, Nanchang, Jiangxi, China.

出版信息

Front Endocrinol (Lausanne). 2022 Nov 24;13:988506. doi: 10.3389/fendo.2022.988506. eCollection 2022.

Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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 (, , , , and ). 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 (, , , and ) was validated by qRT-PCR analysis in human retinal capillary endothelial cells cultured under high-glucose environment.

CONCLUSIONS

, and 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.

摘要

背景

糖尿病视网膜病变(DR)是一种神经血管疾病,是全球视力丧失的主要原因,严重影响生活质量。几项研究表明,铁死亡在 DR 的发病机制中起重要作用;然而,其分子机制尚不完全阐明。因此,本研究旨在探讨铁死亡的发病机制,寻找潜在的铁死亡相关基因生物标志物和治疗 DR 的药物化合物。

方法

在 GSE102485 数据集识别铁死亡相关差异表达基因(DEG)。然后进行功能富集分析,并构建蛋白质-蛋白质相互作用(PPI)网络筛选铁死亡相关关键基因(FRHG)候选物。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 FRHG,并结合 GSE60436 数据集和以往研究进行验证。采用单因素分析的受试者工作特征(ROC)曲线评估 FRHG 的诊断性能,并进行免疫浸润分析。此外,通过分子对接验证针对 FRHG 的药物化合物。最后,采用实时定量聚合酶链反应(qRT-PCR)分析验证 FRHG。

结果

提取了 40 个铁死亡相关 DEG,并进行功能富集分析,主要涉及凋亡信号、氧化应激反应、铁死亡、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筛选 FRHG,并通过验证,我们确定了在诊断中表现良好的五个 FRHG(,,,,和)。免疫浸润分析表明,DR 患者免疫微环境的变化可能与这五个 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验证了 FRHG(,,,和)的上调表达。

结论

,,和可能是 DR 的潜在生物标志物,可能通过调节铁死亡和免疫微环境参与其发生和发展。此外,谷胱甘肽通过靶向铁死亡对 DR 具有潜在的治疗效果。本研究为 DR 的铁死亡相关发病机制及其诊断和治疗提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/197d/9729554/4fa7b7bf7563/fendo-13-988506-g001.jpg

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