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. 2025 Jun;55(3):217-231.
doi: 10.5051/jpis.2401500075. Epub 2024 Nov 20.

Identification of susceptibility modules and genes for peri-implantitis compared to periodontitis within the same host environment using weighted gene co-expression network analysis

Ju-Young Lee  1   2 , Yeongjoo Kim  3 , Jung-Min Oh  4   5 , Yun Hak Kim  6   7 , Hyun-Joo Kim  1   8
Affiliations

Identification of susceptibility modules and genes for peri-implantitis compared to periodontitis within the same host environment using weighted gene co-expression network analysis

Ju-Young Lee et al. J Periodontal Implant Sci. 2025 Jun.

Abstract

Purpose: This study aimed to identify new susceptibility modules and genes by analyzing the transcriptional profiles of peri-implantitis and periodontitis within the same host environment, using weighted gene co-expression network analysis (WGCNA).

Methods: Gingival tissue samples were collected from 10 patients, each presenting with both periodontitis and peri-implantitis sites, and were used for RNA sequencing. We conducted WGCNA to identify key modules that showed distinct transcriptional expression profiles between periodontitis and peri-implantitis. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were carried out using R software. Genes with an adjusted P value greater than 0.05 were excluded from gene selection using the Pearson correlation method.

Results: A total of 2,226 regulated genes were identified, and those with similar expression patterns were grouped into 5 color-coded functional modules using WGCNA. Among these, 3 modules showed distinct differences in expression profiles between peri-implantitis and periodontitis. The turquoise and yellow modules were associated with upregulation in peri-implantitis, while the blue module was linked to periodontitis. This finding suggests that peri-implantitis and periodontitis have significantly different transcriptional signatures. Over-representation analysis was conducted to explore the component genes of the established modules. The top-ranked genes, selected based on their network connectivity within the modules, were identified using DESeq2 and were considered hub genes.

Conclusions: WGCNA revealed distinct modular gene patterns in peri-implantitis and periodontitis, highlighting transcriptional differences between the 2 conditions. Notably, we identified 10 key genes from each of the 3 modules-the blue module associated with periodontitis-dominant pathways, and the turquoise and yellow modules associated with peri-implantitis-dominant pathways. The hub genes and pathways unveiled in this research are likely key contributors to the progression of peri-implantitis and warrant further exploration as promising candidates.

Keywords: Gingiva; Peri-implantitis; Periodontitis; Sequence analysis, RNA.

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Conflict of interest statement

No potential conflict of interest relevant to this article was reported.

Figures

Figure 1
Figure 1. Study design described in a flowchart.
WGCNA: weighted gene co-expression network analysis, DEG: differentially expressed gene, GO: Gene Ontology, KEGG: Kyoto Encyclopedia of Genes and Genomes.
Figure 2
Figure 2. Cluster dendrogram of the provided genes.
Figure 3
Figure 3. Heatmap of enrichment level across samples (A) and identified modules (B) based on each expression level of the overall component genes.
See this image and copyright information in PMC

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