Dataset Information

Identification of key genes and pathways for peri-implantitis through the analysis of gene expression data.

ABSTRACT: The present study attempted to identify potential key genes and pathways of peri-implantitis, and to investigate the possible mechanisms associated with it. An array data of GSE57631 was downloaded, including six samples of peri-implantitis tissue and two samples of normal tissue from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in the peri-implantitis samples compared with normal ones were analyzed with the limma package. Moreover, Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEGs were performed by DAVID. A protein-protein interaction (PPI) network was established using Cytoscape software, and significant modules were analyzed using Molecular Complex Detection. A total of 819 DEGs (759 upregulated and 60 downregulated) were identified in the peri-implantitis samples compared with normal ones. Moreover, the PPI network was constructed with 413 nodes and 1,114 protein pairs. Heat shock protein HSP90AA1 (90 kDa ?, member 1), a hub node with higher node degrees in module 4, was significantly enriched in antigen processing, in the presentation pathway and nucleotide-binding oligomerization domain (NOD)-like receptor-signaling pathway. In addition, nuclear factor-?-B1 (NFKB1) was enriched in the NOD-like receptor-signaling pathway in KEGG pathway enrichment analysis for upregulated genes. The proteasome is the most significant pathway in module 1 with the highest P-value. Therefore, the results of the present study suggested that HSP90AA1 and NFKB1 may be potential key genes, and the NOD-like receptor signaling pathway and proteasome may be potential pathways associated with peri-implantitis development.

SUBMITTER: Zhang H

PROVIDER: S-EPMC5443169 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Identification of key genes and pathways for peri-implantitis through the analysis of gene expression data.

Zhang Huang H Zhang Xiong X Huang Jie J Fan Xusheng X

Experimental and therapeutic medicine 20170302 5

The present study attempted to identify potential key genes and pathways of peri-implantitis, and to investigate the possible mechanisms associated with it. An array data of GSE57631 was downloaded, including six samples of peri-implantitis tissue and two samples of normal tissue from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in the peri-implantitis samples compared with normal ones were analyzed with the limma package. Moreover, Gene Ontology annotati ...[more]

PMID: 28565775

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Project description:ObjectivePeri-implantitis is a condition resulting in destructive inflammation in the peri-implant soft tissue barrier. Clinically, it demonstrates vast clinical differences to periodontitis that suggest distinct inflammatory mechanisms. Implant-derived titanium particles (i-TiPs) frequently found around diseased implants appear to alter the microenvironment and confer resistance to antibiotic treatments. Studies in orthopedic implants have demonstrated potent inflammatory responses to i-TiPs involving a variety of cell types in aseptic conditions. Nonetheless, the genetic programs of cells surveilling and supporting the peri-implant soft tissue barrier in response to the combined challenges of biomaterial degradation products and oral bacteria are poorly defined. Thus, we studied gene expression specific to oral peri-implant inflammatory disease.MethodsPeri-implant tissues were collected from healthy or diseased implants (N = 10) according to the 2018 classification criteria. Following RNA extraction and purification, a gene-level view of the transcriptome was obtained via a next-generation transcriptome-wide microarray profiling workflow (Clariom S; Applied Biosystems) that covers >20,000 well-annotated genes. A discovery analysis assessed global differential expression of genes and identified pathways in peri-implant health versus disease.ResultsGenes involved in the endosomal-lysosomal pathway, such as actin polymerization, were strongly upregulated in diseased tissues (P < .05), proposing increased intracellular activities in response to bacteria and i-TiPs. Cellular respiration pathways involved in oxidative stress were highly transcribed in all peri-implant samples, suggesting that implant-specific factors may trigger a constant state of oxidative stress.ConclusionWithin the limitations of this discovery study, expressive upregulation of genes in the endosomal-lysosomal and oxidative stress pathway suggests that inflammation related to receptor-driven responses to extracellular signals, such as i-TiPs and pathogens, may have a crucial role in peri-implantitis. Results warrant external replication in validation cohorts.Knowledge transfer statementOur findings regarding physiologic processes affected by peri-implantitis could advance knowledge of the mechanisms and consequences of the disease. Understanding the cellular programs that partake in peri-implant inflammation has the potential to translate to novel treatment strategies for patients with peri-implantitis.

Project description:Atherosclerotic cardiovascular disease (ASCVD) caused by atherosclerosis (AS) is one of the highest causes of mortality worldwide. Although there have been many studies on AS, its etiology remains unclear. In order to carry out molecular characterization of different types of AS, we retrieved two datasets composed of 151 AS samples and 32 normal samples from the Gene Expression Omnibus database. Using the non-negative matrix factorization (NMF) algorithm, we successfully divided the 151 AS samples into two subgroups. We then compared the molecular characteristics between the two groups using weighted gene co-expression analysis (WGCNA) and identified six key modules associated with the two subgroups. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analysis were used to identify the potential functions and pathways associated with the modules. In addition, we used the cytoscape software to construct and visualize protein-protein networks so as to identify key genes in the modules of interest. Three hub genes including PTGER3, GNAI1, and IGFBP5 were further screened using the least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Since the modules were associated with immune pathways, we performed immune cell infiltration analysis. We discovered a significant difference in the level of immune cell infiltration by naïve B cells, CD8 T cells, T regulatory cells (Tregs), resting NK cells, Monocytes, Macrophages M0, Macrophages M1, and Macrophages M2 between the two subgroups. In addition, we observed the three hub genes were positively correlated with Tregs but negatively correlated with Macrophages M0. We also found that the three key genes are differentially expressed between normal and diseased tissue, as well as in the different subgroups. Receiver operating characteristic (ROC) results showed a good performance in the validation dataset. These results may provide novel insight into cellular and molecular characteristics of AS and potential markers for diagnosis and targeted therapy.

Dataset Information

Identification of key genes and pathways for peri-implantitis through the analysis of gene expression data.

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Identification of key genes and pathways for peri-implantitis through the analysis of gene expression data.

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