BACKGROUND AND OBJECTIVE

Long non-coding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to compete for micro-RNAs (miRNAs) in regulation of downstream genes, various biological functions and diseases. Yet, the expression and regulation of lncRNAs in periodontitis are not fully understood. The objective of the study was to identify potential genes (lncRNA, messenger RNA [mRNA] and miRNA) involved in periodontitis, construct lncRNA-miRNA-mRNA ceRNA networks, explore gene functions and validate gene expressions.

MATERIAL AND METHODS

The data sets for the lncRNA, mRNA and miRNA expression profiles in gingival samples from periodontally healthy subjects and chronic periodontitis patients were obtained from the Gene Expression Omnibus. The differentially expressed lncRNAs (DElncRNAs), mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) were identified, and ceRNA networks were then constructed. The expression of DElncRNAs and DEmRNAs was examined by quantitative real-time polymerase chain reaction (qPCR). Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for exploring the potential functions and biological pathways.

RESULTS

The GSE80715 and GSE54710 data sets were retrieved. Subsequently, 26 DElncRNAs, 436 DEmRNAs and 12 DEmiRNAs were identified (|fold change| ≥2, adjusted p < 0.05). Further bioinformatics analysis contributed to establishment of the ceRNA networks, which consisted of 10 DElncRNAs, 11 DEmiRNAs and 83 DEmRNAs. Notably, the qPCR results showed a marked decrease in the expression of lncRNA H19 and two mRNAs (NOS1 and MAPT) which further supported the identified ceRNA network. The GO results revealed that the up-regulated mRNAs were significantly enriched in inflammatory processes, whilst the down-regulated mRNAs were enriched in cellular potentials.

CONCLUSION

Non-coding RNAs are critically involved in the regulatory mechanisms in the pathogenesis of periodontitis. Further study is warranted to investigate the specific underlying genetic traits and networks.