综合生物信息学分析确定谷胱甘肽代谢相关基因作为牙周炎的诊断生物标志物。

IF 3.1 2区 医学 Q1 DENTISTRY, ORAL SURGERY & MEDICINE
Leilei Meng, Haoshu Fang, Wenjie Wen
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引用次数: 0

摘要

背景:牙周炎影响全球超过10亿人,氧化应激和谷胱甘肽耗竭在疾病进展中起着至关重要的作用。本研究旨在利用综合生物信息学方法鉴定谷胱甘肽代谢相关基因作为牙周炎的诊断生物标志物。方法:对独立数据集进行加权基因共表达网络分析(WGCNA)。结合GSE16134数据集差异表达分析鉴定关键基因,然后在GSE10334数据集中进行验证。利用CIBERSORT算法进行免疫浸润分析、一致聚类进行分子分型、竞争性内源性RNA (ceRNA)网络构建来探索调控机制。药物-基因相互作用分析和分子对接研究确定了潜在的治疗化合物。用结扎性牙周炎大鼠进行实验验证。结果:在牙周炎患者中鉴定出三个关键谷胱甘肽代谢相关基因:GSTA4和GGT6(下调)和SLC7A11(上调)。该诊断模型在AUC值大于0.8时取得了较好的诊断效果。根据免疫浸润模式确定了两种不同的分子亚型。ceRNA调控网络分析揭示了涉及所有三个基因的复杂相互作用。药物-基因相互作用分析显示,erastin是一种潜在的靶向SLC7A11的治疗化合物。大鼠牙周炎的实验验证证实了SLC7A11在牙周组织中的上调。结论:我们的研究确定SLC7A11、GSTA4和GGT6是具有良好诊断准确性的强大牙周炎生物标志物。SLC7A11基因的不断上调和实验验证使其成为有前景的治疗靶点,为牙周治疗领域的精准医学奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated bioinformatics analysis identifies glutathione metabolism-related genes as diagnostic biomarkers for periodontitis.

Background: Periodontitis affects over 1 billion people globally, with oxidative stress and glutathione depletion playing crucial roles in disease progression. This study aimed to identify glutathione metabolism-related genes as diagnostic biomarkers for periodontitis using integrated bioinformatics approaches.

Methods: Weighted Gene Co-expression Network Analysis (WGCNA) was performed on independent datasets. Key genes were identified in combination with GSE16134 dataset differential expression analysis, which were then validated in the GSE10334 dataset. Immune infiltration analysis using CIBERSORT algorithm, consensus clustering for molecular subtyping, and competing endogenous RNA (ceRNA) network construction were conducted to explore regulatory mechanisms. Drug-gene interaction analysis and molecular docking studies identified potential therapeutic compounds. Experimental validation was performed using ligature-induced periodontitis in rats.

Results: Three key glutathione metabolism-related genes were identified: GSTA4 and GGT6 (downregulated) and SLC7A11 (upregulated) in periodontitis patients. The diagnostic model achieved superior performance with AUC values exceeding 0.8. Two distinct molecular subtypes were identified based on immune infiltration patterns. ceRNA regulatory network analysis revealed complex interactions involving all three genes. Drug-gene interaction analysis revealed erastin as a potential therapeutic compound targeting SLC7A11. Experimental validation in rat periodontitis confirmed the upregulation of SLC7A11 in periodontal tissues.

Conclusions: Our study identifies SLC7A11, GSTA4, and GGT6 as robust periodontitis biomarkers with excellent diagnostic accuracy. The continuous up-regulation and experimental verification of SLC7A11 genes have established them as promising therapeutic targets, laying the foundation for precision medicine in the field of periodontal therapy.

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来源期刊
BMC Oral Health
BMC Oral Health DENTISTRY, ORAL SURGERY & MEDICINE-
CiteScore
3.90
自引率
6.90%
发文量
481
审稿时长
6-12 weeks
期刊介绍: BMC Oral Health is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of disorders of the mouth, teeth and gums, as well as related molecular genetics, pathophysiology, and epidemiology.
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