J Periodont Res. 2018;1–11. wileyonlinelibrary.com/journal/jre
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1 © 2018 John Wiley & Sons A/S.
Published by John Wiley & Sons Ltd
1 | INTRODUCTION
Rheumatoid arthritis (RA) and periodontal disease (PD) are both
complex disorders. Both involve gene-environment interaction,
aberrant immune activation, and long-standing chronic inflamma-
tion. A positive association of RA and PD is reported by a few ep-
idemiologic studies.
1-3
Shared risk factors such as smoking, older
age, and HLA-DRB1 genotype may explain this association in part.
Received: 2 October 2018
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Revised: 1 November 2018
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Accepted: 18 November 2018
DOI: 10.1111/jre.12632
ORIGINAL ARTICLE
Biological links in periodontitis and rheumatoid arthritis:
Discovery via text-mining PubMed abstracts
Aneesha Acharya
1,2
| Simin Li
3
| Xiangqiong Liu
4,5
| George Pelekos
1
|
Dirk Ziebolz
3
| Nikos Mattheos
1
1
Faculty of Dentistry, The University of
Hong Kong, Sai Yin Pun, Hong Kong
2
Department of Periodontology, Dr. D.Y.
Patil Vidyapeeth, Pune, India
3
Department of Cariology, Endodontology,
and Periodontology, University Leipzig,
Liebigstr, Germany
4
Shanghai Genomap Technologies, Shanghai,
China
5
College of Bioinformatics Science and
Technology, Harbin Medical University,
Harbin, China
Correspondence
Nikos Mattheos, Prosthodontics, Faculty
of Dentistry HKU, 3 F, Prince Philip Dental
Hospital, Sai Yin Pun, Hong Kong.
Emails: nikos@mattheos.net; mattheos@hku.hk
Funding information
The University of Hong Kong
Background and Objective: Primary research concerning molecular pathways that
link rheumatoid arthritis with periodontitis is limited. Biomedical literature data min-
ing can offer insights into putative linkage mechanisms toward hypothesis develop-
ment, based on information discovery. The aim of this study was to explore potential
Periodontitis-Rheumatoid Arthritis biological links by analysing “overlapping” genes
reported in biomedical abstracts.
Material and Methods: PubMed abstracts for terms: (a) “Periodontitis” or “Periodontal
Diseases” (PD), (b) “Rheumatoid arthritis” (RA), and (c) their combination with “AND”
(RA+PD), were each text-mined to extract genes using “Human Genome Nomenclature
Committee” (HGNC) symbols. A gene-set common to RA and PD abstracts was
determined (RA∩PD). Gene ontology (GO) profiles of RA∩PD and RA+PD were
compared using “GoProfiler.” Minimum order protein-protein interaction (PPI) and
gene-miRNA networks of “differential genes” between RA∩PD and RA+PD were
constructed with “networkAnalyst.”
Results: Among 1676 genes documented in RA (10 5241 abstracts), and 893 genes in
PD (80 982 abstracts), 535 genes were common (RA∩PD), from which 35 genes were
also documented in RA+PD (415 abstracts). 41 GO-terms significantly different be-
tween RA∩PD and RA+PD GO profiles represented 38 biological processes includ-
ing; nitric oxide metabolism, immunoglobulin production, hormonal regulation,
catabolic process down-regulation, and leukocyte proliferation. The 500 differential
genes’ PPI and gene-miRNA networks showed REL, TRAF2, AQP1 genes, and miR-
NAs 335-5p, 17-5p, 93-5p with genes HMOX1 and SP1 as hub nodes.
Conclusions: Text-mining biomedical abstracts revealed potentially shared but un-
investigated links between PD and RA, meriting further research.
KEYWORDS
bioinformatics, biomedical text mining, information extraction, periodontal diseases,
periodontal medicine, periodontitis, rheumatoid arthritis