BACKGROUND: There are no specific bacterial profiles or diagnostic tests capable of identifying refractory periodontitis patients before a treatment regimen is initiated. Therefore, in this high-risk cohort of patients who do not respond appropriately, host factors that might be partly under genetic control may play a crucial role in their susceptibility. Specifically, we tested the hypothesis that patients with refractory periodontitis have multiple upregulated and/or downregulated genes that might be important in influencing clinical risk. METHODS: Oral subepithelial connective tissues were harvested aseptically from seven refractory periodontitis and seven periodontally well-maintained patients. An RNA isolation kit was used to isolate total RNA from tissue samples that had been stabilized in the RNA stabilizing reagent. The isolated total RNA was then subjected to gene expression profiling using the microarray to measure gene expression levels. The retrieved data were analyzed with a computer program for the differential analysis of gene expression microarray experiments. In addition, real-time polymerase chain reaction (PCR) analysis was performed on selected samples to confirm the microarray data's gene expression patterns. RESULTS: A total of 68 upregulated and six downregulated genes were identified that were differentially expressed at least two-fold out of 22,283 genes we analyzed. The selected model provided a 93% intrinsic validation along with a 93% extrinsic validation. To validate the microarray data, five upregulated genes (lactotransferrin [LTF], matrix metalloproteinase-1 [MMP-1], MMP-3, interferon induced-15 [IFI-15], and Homo sapiens hypothetical protein MGC5566) and two downregulated genes (keratin 2A [KRT2A] and desmocollin-1 [DSC-1]) were randomly selected for further analysis by real-time PCR. The relative RNA expression level of these genes measured by real-time PCR was similar to those measured by microarrays. CONCLUSION: The combined use of microarray technology with the computer program for the differential analysis of gene expression microarray experiments provided a set of candidate genes that may serve as novel therapeutic intervention points and improved diagnostic and screening procedures for high-risk individuals.
BACKGROUND: There are no specific bacterial profiles or diagnostic tests capable of identifying refractory periodontitispatients before a treatment regimen is initiated. Therefore, in this high-risk cohort of patients who do not respond appropriately, host factors that might be partly under genetic control may play a crucial role in their susceptibility. Specifically, we tested the hypothesis that patients with refractory periodontitis have multiple upregulated and/or downregulated genes that might be important in influencing clinical risk. METHODS: Oral subepithelial connective tissues were harvested aseptically from seven refractory periodontitis and seven periodontally well-maintained patients. An RNA isolation kit was used to isolate total RNA from tissue samples that had been stabilized in the RNA stabilizing reagent. The isolated total RNA was then subjected to gene expression profiling using the microarray to measure gene expression levels. The retrieved data were analyzed with a computer program for the differential analysis of gene expression microarray experiments. In addition, real-time polymerase chain reaction (PCR) analysis was performed on selected samples to confirm the microarray data's gene expression patterns. RESULTS: A total of 68 upregulated and six downregulated genes were identified that were differentially expressed at least two-fold out of 22,283 genes we analyzed. The selected model provided a 93% intrinsic validation along with a 93% extrinsic validation. To validate the microarray data, five upregulated genes (lactotransferrin [LTF], matrix metalloproteinase-1 [MMP-1], MMP-3, interferon induced-15 [IFI-15], and Homo sapiens hypothetical protein MGC5566) and two downregulated genes (keratin 2A [KRT2A] and desmocollin-1 [DSC-1]) were randomly selected for further analysis by real-time PCR. The relative RNA expression level of these genes measured by real-time PCR was similar to those measured by microarrays. CONCLUSION: The combined use of microarray technology with the computer program for the differential analysis of gene expression microarray experiments provided a set of candidate genes that may serve as novel therapeutic intervention points and improved diagnostic and screening procedures for high-risk individuals.
Authors: Francisco Morinha; Carlos Albuquerque; João Requicha; Isabel Dias; José Leitão; Ivo Gut; Henrique Guedes-Pinto; Carlos Viegas; Estela Bastos Journal: Mol Biol Rep Date: 2011-09-24 Impact factor: 2.316
Authors: Jeffrey L Ebersole; Radhakrishnan Nagarajan; David Akers; Craig S Miller Journal: Front Cell Infect Microbiol Date: 2015-08-19 Impact factor: 5.293