摘要
意图
本研究的目的是确定牙周炎中关键的自噬相关基因（ARGs），并构建信使核糖核酸-核糖核酸网络，以进一步了解牙周炎的发病机制。
方法
我们使用基因表达综合数据库（GEO）和人类自噬数据库（HADb）来鉴定差异表达的mRNA、miRNA和ARGs。对这些ARG进行基因本体论（GO）、KEGG（京都基因和基因组百科全书）途径和PPI（蛋白质-蛋白质相互作用）网络分析。两个数据库（miRDB和StarBase v2.0）用于反向预测miRNA，而miRNA-lncRNA的相互作用则使用StarBasev2.0和LncBase predicted v.2数据库进行预测。在排除仅存在于细胞核中的lncRNA后，建立了竞争性内源性RNA（ceRNA）网络。最后，我们使用定量实时PCR（qRT-PCR）来确认ceRNA网络中mRNA的表达水平。
后果
差异表达分析显示10个上调和10个下调的差异表达ARG。在将反向预测的miRNA与差异表达的miRNA交叉后，构建了由4个mRNA（LAMP2、NFE2L2、NCKAP1和EGFR）、3个miRNA（hsa-miR-140-3p、hsa-miR.142-5p和hsa-miR-671-5p）和30个lncRNA组成的ceRNA网络。此外，qRT-PCR结果显示，牙周炎患者患病牙龈组织中EGFR的表达下调。
结论
四个自噬相关基因，尤其是EGFR，可能在牙周炎的进展中发挥关键作用。新的ceRNA网络可能有助于阐明自噬在牙周炎中的作用和机制，这对开发新的治疗方案可能很重要。
Abstract
Purpose
The goal of this study was to identify the crucial autophagy-related genes (ARGs) in periodontitis and construct mRNA-miRNA-lncRNA networks to further understand the pathogenesis of periodontitis.

Methods
We used the Gene Expression Omnibus (GEO) database and Human Autophagy Database (HADb) to identify differentially expressed mRNAs, miRNAs, and ARGs. These ARGs were subjected to Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, and PPI (protein–protein interaction) network analysis. Two databases (miRDB and StarBase v2.0) were used to reverse-predict miRNAs while the miRNA-lncRNA interaction was predicted using the StarBase v2.0 and LncBase Predicted v.2 databases. After excluding the lncRNAs only present in the nucleus, a competing endogenous RNA (ceRNA) network was built. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the levels of mRNA expression in the ceRNA network.

Results
The differential expression analysis revealed 10 upregulated and 10 downregulated differentially expressed ARGs. After intersecting the reverse-predicted miRNAs with the differentially expressed miRNAs, a ceRNA network consisting of 4 mRNAs (LAMP2, NFE2L2, NCKAP1, and EGFR), 3 miRNAs (hsa-miR-140-3p, hsa-miR-142-5p, and hsa-miR-671-5p), and 30 lncRNAs was constructed. In addition, qRT-PCR results revealed that EGFR expression was downregulated in diseased gingival tissue of periodontitis patients.

Conclusion
Four autophagy-related genes, especially EGFR, may play a key role in periodontitis progression. The novel ceRNA network may aid in elucidating the role and the mechanism of autophagy in periodontitis, which could be important in developing new therapeutic options.

https://www.tandfonline.com/doi/full/10.2147/JIR.S353092