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. 2024 Sep 21;25(18):10161.
doi: 10.3390/ijms251810161.

The Molecular Comorbidity Network of Periodontal Disease

Mireya Martínez-García  1 , Enrique Hernández-Lemus  2   3
Affiliations

The Molecular Comorbidity Network of Periodontal Disease

Mireya Martínez-García et al. Int J Mol Sci. .

Abstract

Periodontal disease, a multifactorial inflammatory condition affecting the supporting structures of the teeth, has been increasingly recognized for its association with various systemic diseases. Understanding the molecular comorbidities of periodontal disease is crucial for elucidating shared pathogenic mechanisms and potential therapeutic targets. In this study, we conducted comprehensive literature and biological database mining by utilizing DisGeNET2R for extracting gene-disease associations, Romin for integrating and modeling molecular interaction networks, and Rentrez R libraries for accessing and retrieving relevant information from NCBI databases. This integrative bioinformatics approach enabled us to systematically identify diseases sharing associated genes, proteins, or molecular pathways with periodontitis. Our analysis revealed significant molecular overlaps between periodontal disease and several systemic conditions, including cardiovascular diseases, diabetes mellitus, rheumatoid arthritis, and inflammatory bowel diseases. Shared molecular mechanisms implicated in the pathogenesis of these diseases and periodontitis encompassed dysregulation of inflammatory mediators, immune response pathways, oxidative stress pathways, and alterations in the extracellular matrix. Furthermore, network analysis unveiled the key hub genes and proteins (such as TNF, IL6, PTGS2, IL10, NOS3, IL1B, VEGFA, BCL2, STAT3, LEP and TP53) that play pivotal roles in the crosstalk between periodontal disease and its comorbidities, offering potential targets for therapeutic intervention. Insights gained from this integrative approach shed light on the intricate interplay between periodontal health and systemic well-being, emphasizing the importance of interdisciplinary collaboration in developing personalized treatment strategies for patients with periodontal disease and associated comorbidities.

Keywords: biological databases; comorbidities; genetic associations; inflammatory pathways; molecular mechanisms of systemic diseases; periodontal disease.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
A periodontitis-centered molecular comorbidity network. Diseases sharing biomolecular players with periodontitis (dark blue node) are shown. Links indicate diseases sharing associated genes with periodontitis. Node sizes correspond to the Jaccard index (relative size of the intersection of the gene sets) with periodontitis.
Figure 2
Figure 2
Numbers of genes shared between peridontitis and its main comorbidities. Diseases are also tagged according to the relative size of their intersection as given by Jaccard indices.
Figure 3
Figure 3
Molecular diseasome network depicting the interconnections created between periodontitis other diseases sharing common genetic associations. Every disease is connected to their associated genes. Red nodes correspond to the more significant health conditions associated with periodontitis. Yellow nodes correspond to the genes linked with each condition. This bipartite network consists of 80 disease nodes and 1197 gene nodes, with 2212 genetic associations between them. For visualization purposes, all disease nodes are depicted with the same size and all gene nodes are depicted with the same size irrespective of their degree of connectivity.
Figure 4
Figure 4
Diseasome network depicting the interconnections between periodontitis and its significant related conditions in a comprehensive manner. It considers molecular associations between any pair of conditions with a comorbidity relationship with periodontitis.
Figure 5
Figure 5
Top significant genes in the gene–disease map projected from the periodontitis-associated diseasome.
Figure 6
Figure 6
Heatmap of protein classes for the genes in the periodontitis-associated diseasome.
Figure 7
Figure 7
Functional enrichment analysis (over-representation) of genes shared by periodontitis and its comorbidity-related diseases. Notice that g:SCS-corrected p-values less than 1×10−16 are capped.
Figure 8
Figure 8
Workflow for the analysis presented. A list of periodontitis-associated genes was curated from a literature (NCBI-Pubmed) and database (OMIM) rigurous search. This list was used to mine high-confidence reported associations for diseases and conditions sharing genetic and molecular hits with periodontitis (DISGENET) to build comorbidity and diseasome Networks. The same list was also used to mine (GProfileR) biomolecular, pathway, and phenotype databases and to perform statistical tests for functional over-representation.
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References

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