Revealing a potential necroptosis-related axis (RP11-138A9.1/hsa-miR-98-5p/ZBP1) in periodontitis by construction of the ceRNA network

被引：7

作者：

Wang, Zhenxiang ^{[1
,2
,3
]}

Chen, Hang ^{[1
,2
,3
]}

Peng, Limin ^{[1
,2
,3
]}

He, Yujuan ^{[4
]}

Zhang, Xiaonan ^{[1
,2
,3
,5
]}

机构：

[1] Chongqing Med Univ, Coll Stomatol, Chongqing, Peoples R China

[2] Chongqing Med Univ, Chongqing Municipal Key Lab Oral Biomed Engn Highe, Chongqing, Peoples R China

[3] Chongqing Med Univ, Chongqing Key Lab Oral Dis & Biomed Sci, Chongqing, Peoples R China

[4] Chongqing Med Univ, Dept Lab Med, Key Lab Diagnost Med, Minist Educ, Chongqing, Peoples R China

[5] Chongqing Med Univ, Coll Stomatol, 426 Sunshine Rd, Chongqing, Peoples R China

来源：

JOURNAL OF PERIODONTAL RESEARCH | 2023年 / 58卷 / 05期

基金：

中国国家自然科学基金;

关键词：

bioinformatics; ceRNA network; diagnosis; immune cell; necroptosis; periodontitis; T-CELLS; DAMAGE; RIP1;

D O I：

10.1111/jre.13157

中图分类号：

R78 [口腔科学];

学科分类号：

1003 ;

摘要：

Background and ObjectivesPeriodontitis, a prevalent chronic inflammatory condition, poses a significant risk of tooth loosening and subsequent tooth loss. Within the realm of programmed cell death, a recently recognized process known as necroptosis has garnered attention for its involvement in numerous inflammatory diseases. Nevertheless, its correlation with periodontitis is indistinct. Our study aimed to identify necroptosis-related lncRNAs and crucial lncRNA-miRNA-mRNA regulatory axes in periodontitis to further understand the pathogenesis of periodontitis. Materials and MethodsGene expression profiles in gingival tissues were acquired from the Gene Expression Omnibus (GEO) database. Selecting hub necroptosis-related lncRNA and extracting the key lncRNA-miRNA-mRNA axes based on the ceRNA network by adding novel machine-learning models based on conventional analysis and combining qRT-PCR validation. Then, an artificial neural network (ANN) model was constructed for lncRNA in regulatory axes, and the accuracy of the model was validated by receiver operating characteristic (ROC) curve analysis. The clinical effect of the model was evaluated by decision curve analysis (DCA). Weighted correlation network analysis (WGCNA) and single-sample gene set enrichment analysis (ssGSEA) was performed to explore how these lncRNAs work in periodontitis. ResultsSeven hub necroptosis-related lncRNAs and three lncRNA-miRNA-mRNA regulatory axes (RP11-138A9.1/hsa-miR-98-5p/ZBP1 axis, RP11-96D1.11/hsa-miR-185-5p/EZH2 axis, and RP4-773 N10.4/hsa-miR-21-5p/TLR3 axis) were predicted. WGCNA revealed that RP11-138A9.1 was significantly correlated with the "purple module". Functional enrichment analysis and ssGSEA demonstrated that the RP11-138A9.1/hsa-miR-98-5p/ZBP1 axis is closely related to the inflammation and immune processes in periodontitis. ConclusionOur study predicted a crucial necroptosis-related regulatory axis (RP11-138A9.1/hsa-miR-98-5p/ZBP1) based on the ceRNA network, which may aid in elucidating the role and mechanism of necroptosis in periodontitis.

引用

页码：968 / 985

页数：18