Hailun Zhou1,2,3,4, Donghui Chen2,3,4,5, Guifang Xie6, Jiaojie Li1,2,3,4, Jianjia Tang1,2,3,4, Li Tang1,2,3,4. 1. Department of Implant Dentistry, Stomatology Hospital, Guangxi Medical University, Nanning, China. 2. Guangxi Key Laboratory of the Rehabilitation and Reconstruction of Oral and Maxillofacial Research, Nanning, China. 3. Guangxi Colleges and Universities Key Laboratory of Treatment and Research for Oral and Maxillofacial Surgery Disease, Nanning, China. 4. Guangxi Clinical Research Center for Craniofacial Deformity, Nanning, China. 5. Department of Periodontology, Stomatology Hospital, Guangxi Medical University, Nanning, Guangxi, China. 6. Department of Prosthodontics, Affiliated Stomatology Hospital of Guilin Medical College, Guilin, China.
Abstract
BACKGROUND AND OBJECTIVE: Although periimplantitis and periodontitis share similar features, particularly clinical features, they are two different diseases and should be analyzed separately. Thus far, few omics-level differences in periimplantitis and periodontitis have been reported. This study was aimed at exploring the differential effects of expression mRNAs, lncRNAs, and miRNAs in periodontitis and periimplantitis by high-throughput sequencing and competitive endogenous RNA (ceRNA) analysis. METHODS: Gingival tissues of healthy individuals (HI) and periimplantitis (PI) and periodontitis (P) patients were collected and used for genome-wide sequencing. The differentially expressed genes (DEGs) were screened and visualized by R software. The functions and pathways of DEGs were analyzed using Metascape, and the ceRNA network was constructed using the Cytoscape software. Finally, gene set enrichment analysis (GSEA) was used to predict the function of key nodes in ceRNA. RESULTS AND CONCLUSION: By constructing the regulated ceRNA network, six genes (FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1) and 16 miRNAs (hsa-miR-338-5p, hsa-miR-650, hsa-miR-9-5p, hsa-miR-1290, hsa-miR-544a, hsa-miR-3179, hsa-miR-1269a, hsa-miR-3679-5p, hsa-miR-149-5p, hsa-miR-615-3p, hsa-miR-33b-5p, hsa-miR-31-5p, hsa-miR-4639-5p, hsa-miR-204-5p, hsa-miR-5588-5p, and hsa-mir-196a-5p) were detected. Five long non-coding RNAs (lnc-CORO2B-1, lnc-MBL2-7, lnc-TRIM45-1, lnc-CHST10-2, and lnc-TNP1-6) were found to target these miRNAs in this ceRNA network. The ceRNA network based on transcriptome data revealed that FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1 were crucial proteins of differential effects in periodontitis and periimplantitis. The lncRNA-miRNA-mRNA interaction involved the regulation of the Hippo signaling pathway, Wnt signaling pathway, Toll-like receptor signaling pathway, NOD signaling pathway, oxidative stress, and innate immune process. These regulated pathways and biological processes may be factors contributing to the pathogenesis of periimplantitis being distinct from that of periodontitis.
BACKGROUND AND OBJECTIVE: Although periimplantitis and periodontitis share similar features, particularly clinical features, they are two different diseases and should be analyzed separately. Thus far, few omics-level differences in periimplantitis and periodontitis have been reported. This study was aimed at exploring the differential effects of expression mRNAs, lncRNAs, and miRNAs in periodontitis and periimplantitis by high-throughput sequencing and competitive endogenous RNA (ceRNA) analysis. METHODS: Gingival tissues of healthy individuals (HI) and periimplantitis (PI) and periodontitis (P) patients were collected and used for genome-wide sequencing. The differentially expressed genes (DEGs) were screened and visualized by R software. The functions and pathways of DEGs were analyzed using Metascape, and the ceRNA network was constructed using the Cytoscape software. Finally, gene set enrichment analysis (GSEA) was used to predict the function of key nodes in ceRNA. RESULTS AND CONCLUSION: By constructing the regulated ceRNA network, six genes (FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1) and 16 miRNAs (hsa-miR-338-5p, hsa-miR-650, hsa-miR-9-5p, hsa-miR-1290, hsa-miR-544a, hsa-miR-3179, hsa-miR-1269a, hsa-miR-3679-5p, hsa-miR-149-5p, hsa-miR-615-3p, hsa-miR-33b-5p, hsa-miR-31-5p, hsa-miR-4639-5p, hsa-miR-204-5p, hsa-miR-5588-5p, and hsa-mir-196a-5p) were detected. Five long non-coding RNAs (lnc-CORO2B-1, lnc-MBL2-7, lnc-TRIM45-1, lnc-CHST10-2, and lnc-TNP1-6) were found to target these miRNAs in this ceRNA network. The ceRNA network based on transcriptome data revealed that FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1 were crucial proteins of differential effects in periodontitis and periimplantitis. The lncRNA-miRNA-mRNA interaction involved the regulation of the Hippo signaling pathway, Wnt signaling pathway, Toll-like receptor signaling pathway, NOD signaling pathway, oxidative stress, and innate immune process. These regulated pathways and biological processes may be factors contributing to the pathogenesis of periimplantitis being distinct from that of periodontitis.
Authors: Anna Starzyńska; Piotr Wychowański; Maciej Nowak; Bartosz Kamil Sobocki; Barbara Alicja Jereczek-Fossa; Monika Słupecka-Ziemilska Journal: Int J Mol Sci Date: 2022-02-24 Impact factor: 5.923