Unveiling the role of lipopolysaccharide-related genes in diabetic retinopathy: identification of key biomarkers and immune infiltration analysis.

IF 3.4 3区医学 Q2 ENDOCRINOLOGY & METABOLISM

Diabetology & Metabolic Syndrome Pub Date : 2024-12-23 DOI:10.1186/s13098-024-01557-9

Hongyi Sun, Shaohua Liu, Chao Wei

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引用次数: 0

Abstract

Background: Growing evidence suggests a link between systemic lipopolysaccharide (LPS) exposure and worsening diabetic retinopathy (DR). This study aims to investigate DR's pathogenesis by analyzing LPS-related genes (LRGs) through bioinformatics.

Methods: The CTD database was utilized to identify LRGs. The datasets associated with DR were acquired from the GEO database. The Venn diagram was used to identify the differentially expressed LRGs (DLRGs), and the putative molecular mechanism of these DLRGs was investigated through functional enrichment analysis. We used WGCNA, Lasso regression, and RF to identify hub DLRGs. The expression levels of these hub DLRGs were validated in an independent dataset (GSE102485) and cell experiments. Employing the CIBERSORT algorithm, we examined the infiltration of 22 distinct immune cell types in DR and assessed the association between key DLRGs and immune infiltrates through correlation analysis.

Results: A total of 71 DLRGs were detected. These genes exhibited significant enrichment in pathways associated with inflammation. In addition, the in-depth analysis uncovered that five hub DLRGs (STK33 and EPHX2) linked to bacterial LPS displayed noteworthy diagnostic potential for individuals diagnosed with DR. The hub DLRGs expression in the high glucose-induced DR model was confirmed by qRT-PCR analysis. Furthermore, examination of immune infiltration indicated a significant association between these five genes and the extent of immune cell infiltration.

Conclusion: STK33 and EPHX2 serve as biomarkers related to bacterial LPS. Exploring these genes in-depth could provide innovative ideas and a foundation for comprehending the progression of the disease and developing targeted treatments for DR.

查看原文本刊更多论文

揭示脂多糖相关基因在糖尿病视网膜病变中的作用：关键生物标志物的鉴定和免疫浸润分析。

背景：越来越多的证据表明，全身性脂多糖（LPS）暴露与糖尿病视网膜病变（DR）恶化之间存在联系。本研究旨在通过生物信息学方法分析脂多糖相关基因（LRGs），探讨DR的发病机制。方法：利用CTD数据库对LRGs进行鉴定。DR相关数据集从GEO数据库中获取。利用维恩图对差异表达LRGs （DLRGs）进行鉴定，并通过功能富集分析对这些差异表达LRGs的分子机制进行推测。我们使用WGCNA、Lasso回归和RF来识别集线器DLRGs。这些hub DLRGs的表达水平在独立数据集（GSE102485）和细胞实验中得到验证。我们采用CIBERSORT算法检测了22种不同免疫细胞类型在DR中的浸润情况，并通过相关性分析评估了关键DLRGs与免疫浸润之间的关系。结果：共检出71个DLRGs。这些基因在与炎症相关的通路中表现出显著的富集。此外，深入分析发现，与细菌LPS相关的5个hub DLRGs （STK33和EPHX2）在DR诊断个体中显示出值得注意的诊断潜力。qRT-PCR分析证实了hub DLRGs在高糖诱导DR模型中的表达。此外，免疫浸润检查表明这五个基因与免疫细胞浸润程度有显著关联。结论：STK33和EPHX2是与细菌LPS相关的生物标志物。深入探索这些基因可以为理解疾病的进展和开发针对DR的靶向治疗提供创新思路和基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Diabetology & Metabolic Syndrome ENDOCRINOLOGY & METABOLISM-

CiteScore

6.20

自引率

0.00%

发文量

170

审稿时长

7.5 months

期刊介绍： Diabetology & Metabolic Syndrome publishes articles on all aspects of the pathophysiology of diabetes and metabolic syndrome. By publishing original material exploring any area of laboratory, animal or clinical research into diabetes and metabolic syndrome, the journal offers a high-visibility forum for new insights and discussions into the issues of importance to the relevant community.