糖尿病肾病中精氨酸甲基化的生物标记物：生物信息学分析的新发现

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-09-13 DOI:10.2147/dmso.s472412

Yiming Guan, Xiayan Yin, Liyan Wang, Zongli Diao, Hongdong Huang, Xueqi Wang

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引用次数: 0

摘要

背景：糖尿病肾病（DN）是一种受精氨酸甲基化影响的严重糖尿病并发症。本研究旨在阐明蛋白质精氨酸甲基化相关基因（PRMT-RGs）在 DN 中的作用，并确定潜在的生物标志物：方法：将两个 GEO 数据集（GSE30122 和 GSE104954）中的差异表达基因与 9 个 PRMT-RGs 整合。使用 WGCNA 和差异表达分析确定候选基因，然后使用支持向量机递归特征消除和最小绝对收缩与选择算子进行筛选。生物标记物被定义为在两个数据集中具有一致差异表达的基因。使用 miRNet 和 Network Analyst 数据库构建调控网络。进行基因组富集分析，以确定 DN 中生物标记物富集的信号通路。利用免疫浸润分析确定了 DN 中不同的免疫细胞。同时，通过药物预测和分子对接确定了潜在的 DN 治疗方法。最后，qRT-PCR 和免疫组化验证了 STZ 诱导的 DN 小鼠和 DN 患者体内的两个生物标记物：结果：本研究发现了两个 DN 的生物标志物（FAM98A 和 FAM13B）。分子调控网络显示，FAM98A和FAM13B受6个microRNA和1个转录因子共同调控，并在信号通路中富集。免疫浸润和相关性分析表明，FAM98A和FAM13B与PRMT-RGs和免疫细胞一起参与了DN的发生。通过 qRT-PCR 分析发现，Fam98a 和 Fam13b 在 DN 小鼠肾脏中的表达水平显著上调。免疫组化染色显示，FAM98A在DN患者肾脏中的表达水平明显上调。分子对接显示，雌二醇和鱼藤酮通过靶向 FAM98A 对 DN 具有潜在的治疗作用：综合生物信息学分析表明，FAM98A和FAM13B是与PRMT-RGs和免疫细胞相关的潜在DN生物标志物。这项研究为阐明 DN 的分子机制和开发靶向疗法提供了有益的启示。

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Biomarkers of Arginine Methylation in Diabetic Nephropathy: Novel Insights from Bioinformatics Analysis

Background: Diabetic nephropathy (DN) is a severe complication of diabetes influenced by arginine methylation. This study aimed to elucidate the role of protein arginine methylation-related genes (PRMT-RGs) in DN and identify potential biomarkers.
Methods: Differentially expressed genes in two GEO datasets (GSE30122 and GSE104954) were integrated with 9 PRMT-RGs. Candidate genes were identified using WGCNA and differential expression analysis, then screened using support vector machine-recursive feature elimination and least absolute shrinkage and selection operator. Biomarkers were defined as genes with consistent differential expression across both datasets. Regulatory networks were constructed using the miRNet and Network Analyst databases. Gene set enrichment analysis was performed to identify the signaling pathways in which the biomarkers were enriched in DN. Different immune cells in DN were identified using immune infiltration analysis. Meanwhile, drug prediction and molecular docking identified potential DN therapies. Finally, qRT-PCR and immunohistochemistry validated two biomarkers in STZ-induced DN mice and DN patients.
Results: Two biomarkers (FAM98A and FAM13B) of DN were identified in this study. The molecular regulatory network revealed that FAM98A and FAM13B were co-regulated by 6 microRNAs and 1 transcription factor and were enriched in signaling pathways. Immune infiltration and correlation analyses revealed that FAM98A and FAM13B were involved in developing DN along with PRMT-RGs and immune cells. The expression levels of Fam98a and Fam13b were significantly upregulated in the kidneys of DN mice revealed by qRT-PCR analysis. The expression levels of FAM98A were significantly upregulated in the kidneys of DN patients revealed by immunohistochemistry staining. Molecular docking showed that estradiol and rotenone exerted potential therapeutic effects on DN by targeting FAM98A.
Conclusion: Comprehensive bioinformatics analysis revealed that FAM98A and FAM13B were potential DN biomarkers correlated with PRMT-RGs and immune cells. This study provided useful insights for elucidating the molecular mechanisms and developing targeted therapy for DN.

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来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464