DNER and GNL2 are differentially m6A methylated in periodontitis in comparison with periodontal health revealed by m6A microarray of human gingival tissue and transcriptomic analysis

作者全名："Wang, Zhenxiang; Chen, Hang; Peng, Limin; He, Yujuan; Wei, Jingjing; Zhang, Xiaonan"

作者地址："[Wang, Zhenxiang; Chen, Hang; Peng, Limin; Wei, Jingjing; Zhang, Xiaonan] Chongqing Med Univ, Coll Stomatol, Chongqing, Peoples R China; [Wang, Zhenxiang; Chen, Hang; Peng, Limin; Wei, Jingjing; Zhang, Xiaonan] Chongqing Municipal Key Lab Oral Biomed Engn Highe, Chongqing, Peoples R China; [Wang, Zhenxiang; Chen, Hang; Peng, Limin; Wei, Jingjing; Zhang, Xiaonan] Chongqing Key Lab Oral Dis & Biomed Sci, Chongqing, Peoples R China; [He, Yujuan] Chongqing Med Univ, Dept Lab Med, Key Lab Diagnost Med, Minist Educ, Chongqing, Peoples R China; [Zhang, Xiaonan] Chongqing Med Univ, Coll Stomatol, 426 Songshibei Rd, Chongqing, Peoples R China"

通信作者："Zhang, XA (通讯作者)，Chongqing Med Univ, Coll Stomatol, 426 Songshibei Rd, Chongqing, Peoples R China."

来源：JOURNAL OF PERIODONTAL RESEARCH

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:000950738000001

JCR分区：Q1

影响因子：3.4

年份：2023

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期号：　

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文献类型：Article; Early Access

关键词：bioinformatics; epigenetics; m6A; MeRIP; microarray; periodontitis

摘要："ObjectiveThis study aims to investigate the differences in the epigenomic patterns of N6-methyladenosine (m6A) methylation in gingival tissues between patients with periodontitis (PD) and healthy controls, identifying potential biomarkers. BackgroundAs a multifactorial disease, PD involves multiple genetic and environmental effects. The m6A modification is the most prevalent internal mRNA modification and linked to various inflammatory diseases. However, the m6A modification pattern and m6A-related signatures in PD remain unclear. Materials and MethodsAn m6A microarray of human gingival tissues was conducted in eight subjects: four diagnosed with PD and four healthy controls. Microarray analysis was performed to identify the differentially m6A methylated mRNAs (DMGs) and the differentially expressed mRNAs (DEGs). The differentially methylated and expressed mRNAs (DMEGs) were subjected to functional enrichment analysis by Metascape. The weighted gene co-expression network analysis (WGCNA) algorithm, the least absolute shrinkage and selection operator (LASSO) regression, and univariate logistic regression were performed to identify potential biomarkers. The cell type localization of the target genes was determined using single-cell RNA-seq (scRNA-seq) analysis. The m6A methylation level and gene expression of hub genes were subsequently verified by m6A methylated RNA immunoprecipitation (MeRIP) and quantitative real-time PCR (qRT-PCR). ResultsIn total, 458 DMGs, 750 DEGs, and 279 DMEGs were identified based on our microarray. Pathway analyses conducted for the DMEGs revealed that biological functions were mainly involved in the regulation of stem cell differentiation, ossification, circadian rhythm, and insulin secretion pathways. Besides, the genes involved in crucial biological processes were mainly expressed in fibroblast and epithelial cells. Furthermore, the m6A methylation and expression levels of two hub biomarkers (DNER and GNL2) were validated. ConclusionThe current study exhibited a distinct m6A epitranscriptome, identified and verified two PD-related biomarkers (DNER and GNL2), which may provide novel insights into revealing the new molecular mechanisms and latent targets of PD."

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