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

Tianliang Yu; Aneesha Acharya; Nikos Mattheos; Simin Li; Dirk Ziebolz; Gerhard Schmalz; Rainer Haak; Jana Schmidt; Yu Sun

doi:10.7717/peerj.7124

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.

Authors

Tianliang Yu¹, Aneesha Acharya^{2

3}, Nikos Mattheos², Simin Li⁴, Dirk Ziebolz⁴, Gerhard Schmalz⁴, Rainer Haak⁴, Jana Schmidt⁴, Yu Sun¹

Affiliations

¹ Department of Prosthodontics, School of Dentistry, Harbin Medical University, Harbin, Heilongjiang, China.
² Faculty of Dentistry, University of Hong Kong, Hong Kong, China.
³ Dr D Y Patil Dental College and Hospital, Pimpri, Pune, India.
⁴ Department of Cariology, Endodontology and Periodontology, University Leipzig, Leipzig, Saxon, Germany.

Abstract

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.

Grants and funding

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.