Gene-Expression Profiles in Generalized Aggressive Periodontitis: A Gene Network-Based Microarray Analysis

被引:28
|
作者
Guzeldemir-Akcakanat, Esra [1 ]
Sunnetci-Akkoyunlu, Deniz [2 ]
Orucguney, Begum [1 ]
Cine, Naci [2 ]
Kan, Bahadir [3 ]
Yilmaz, Elif Busra [2 ]
Gumuslu, Esen [2 ]
Savli, Hakan [2 ]
机构
[1] Kocaeli Univ, Fac Dent, Dept Periodontol, TR-41190 Basiskele, Kocaeli, Turkey
[2] Kocaeli Univ, Fac Med, Dept Med Genet, TR-41190 Basiskele, Kocaeli, Turkey
[3] Kocaeli Univ, Fac Dent, Dept Oral & Maxillofacial Surg, TR-41190 Basiskele, Kocaeli, Turkey
关键词
Aggressive periodontitis; genes; gingiva; inflammation; microarray analysis; TRANSCRIPTOMES; ANTIBODY;
D O I
10.1902/jop.2015.150175
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Background: In this study, molecular biomarkers that play a role in the development of generalized aggressive periodontitis (GAgP) are investigated using gingival tissue samples through omics-based whole-genome transcriptomics while using healthy individuals as background controls. Methods: Gingival tissue biopsies from 23 patients with GAgP and 25 healthy individuals were analyzed using gene-expression microarrays with network and pathway analyses to identify gene-expression patterns. To substantiate the results of the microarray studies, real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to assess the messenger RNA (mRNA) expression of MZB1 and DSC1. The microarrays and qRT-PCR resulted in similar gene-expression changes, confirming the reliability of the microarray results at the mRNA level. Results: As a result of the gene-expression microarray studies, four significant gene networks were identified. The most upregulated genes were found as MZB1, TNFRSF17, PNOC, FCRL5, LAX1, BMS1P20, IGLL5, MMP7, SPAG4, and MEI1; the most downregulated genes were found as LOR, LAMB4, AADACL2, MAPT, ARG1, NPR3, AADAC, DSC1, LRRC4, and CHP2. Conclusions: Functions of the identified genes that were involved in gene networks were cellular development, cell growth and proliferation, cellular movement, cell-cell signaling and interaction, humoral immune response, protein synthesis, cell death and survival, cell population and organization, organismal injury and abnormalities, molecular transport, and small-molecule biochemistry. The data suggest new networks that have important functions as humoral immune response and organismal injury/abnormalities. Future analyses may facilitate proteomic profiling analyses to identify gene-expression patterns related to clinical outcome.
引用
收藏
页码:58 / 65
页数:8
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