Gene Expression Profiles in Chronic Periodontitis: Gene Network-Based Microarray Analysis

Objectives: To investigate molecular biomarkers which play a role in the development of chronic periodontitis (CP) using gingival tissues through omics-based whole-genome transcriptomic while using healthy individuals as background controls.
Methods: Gene expression microarrays with network and pathway analyses to identify gene expression patterns were performed in a total of 43 subjects; 18 subjects in CP group and 25 subjects in controls. To substantiate the results of the microarray studies, Q-RT-PCR was performed to assess the mRNA expressions. The microarrays and RT-PCR resulted in similar gene expression changes, confirming the reliability of our microarray results at mRNA level.
Results: As a result of the microarray analysis, we identified 1262 downregulated and 1027 upregulated genes. The most upregulated 10 genes were MZB1, BMS1P20, IGLL1/IGLL5, TNFRSF17, ALDH1A1, KIAA0125, MMP7, PRL, MGC16025, ADAM11; the most down-regulated 10 genes were HMBOX1, GPR182, RNA18S5, RPA4, CD86, KRT79, RNA5-8S5, PPP6R1, CECR2, GPR179. Microarray results were verified by analyzing the expression values of MZB1 gene using qRT-PCR. We found 5 gene networks including both downregulated and upregulated genes for investigating molecular interactions using IPA software. These gene networks were identified around Akt group and PRD4 kinase, SMARCA4 transcription regulator and estrogen receptor group, NF-kB complex, Histone h3 group and NANOG transcription regulator, TGFB1 growth factor and TGFBR2 kinase.
Conclusions: Top functions of these genes were found to be related to cell death and survival, embryogenic development, DNA replication, recombination and repair, gene expression, organismal development, cell-to-cell signaling and interaction, cellular development, cellular growth and proliferation, cellular assembly and organization, cellular function and maintenance, cellular movement, cancer, endocrine system disorders. Our findings are important in terms of clarifying genetic factors underlying biological processes of CP. In the light of these results, we are performing the proteomic profiling and immunohistochemical analyses to identify gene expression patterns related to clinical outcome.