Molecular mechanisms linking peri-implantitis and type 2 diabetes mellitus revealed by transcriptomic analysis

PeerJ. 2019 Jun 21;7:e7124. doi: 10.7717/peerj.7124. eCollection 2019.


Aims: To explore molecular mechanisms that link peri-implantitis and type 2 diabetes mellitus (T2DM) by bioinformatic analysis of publicly available experimental transcriptomic data.

Materials and methods: Gene expression data from peri-implantitis were downloaded from the Gene Expression Omnibus database, integrated and differentially expressed genes (DEGs) in peri-implantitis were identified. Next, experimentally validated and computationally predicted genes related to T2DM were downloaded from the DisGeNET database. Protein-protein interaction network (PPI) pairs of DEGs related to peri-implantitis and T2DM related genes were constructed, "hub" genes and overlapping DEG were determined. Functional enrichment analysis was used to identify significant shared biological processes and signaling pathways. The PPI networks were subjected to cluster and specific class analysis for identifying "leader" genes. Module network analysis of the merged PPI network identified common or cross-talk genes connecting the two networks.

Results: A total of 92 DEGs overlapped between peri-implantitis and T2DM datasets. Three hub genes (IL-6, NFKB1, and PIK3CG) had the highest degree in PPI networks of both peri-implantitis and T2DM. Three leader genes (PSMD10, SOS1, WASF3), eight cross-talk genes (PSMD10, PSMD6, EIF2S1, GSTP1, DNAJC3, SEC61A1, MAPT, and NME1), and one signaling pathway (IL-17 signaling) emerged as peri-implantitis and T2DM linkage mechanisms.

Conclusions: Exploration of available transcriptomic datasets revealed IL-6, NFKB1, and PIK3CG expression along with the IL-17 signaling pathway as top candidate molecular linkage mechanisms between peri-implantitis and T2DM.

Keywords: Bioinformatics; Gene; Pathway; Peri-implantitis; Type 2 diabetes.

Grant support

The authors received doctoral study support from the China Scholarship Council (CSC) for Simin Li (CSC No: 201608080010) at University Leipzig. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.