Inflammasomes NLRP3 and AIM2 in peri-implantitis: A cross-sectional study

Deciphering peri-implantitis: Unraveling signature genes and immune cell associations through bioinformatics and machine learning

Early diagnosis of peri-implantitis (PI) is crucial to understand its pathological progression and prevention. This study is committed to investigating the signature genes, relevant signaling pathways and their associations with immune cells in PI. We analyzed differentially expressed genes (DEGs) from a PI dataset in the gene expression omnibus database. Functional enrichment analysis was conducted for these DEGs. Weighted Gene Co-expression Network Analysis was used to identify specific modules. Least absolute shrinkage and selection operator and support vector machine recursive feature elimination were ultimately applied to identify the signature genes. These genes were subsequently validated in an external dataset. And the immune cells infiltration was classified using CIBERSORT. A total of 180 DEGs were screened from GSE33774. Weighted Gene Co-expression Network Analysis revealed a significant association between the MEturquoise module and PI (cor = 0.6, P < .0001). Least absolute shrinkage and selection operator and support vector machine recursive feature elimination algorithms were applied to select the signature genes, containing myeloid-epithelial-reproductive tyrosine kinase, microfibrillar-associated protein 5, membrane-spanning 4A 4A, tribbles homolog 1. In the validation on the external dataset GSE106090, all these genes achieved area under curve values exceeding 0.95. GSEA analysis showed that these genes were correlated with the NOD-like receptor signaling pathway, metabolism of xenobiotics by cytochrome P450, and arachidonic acid metabolism. CIBERSORT revealed elevated levels of macrophage M2 and activated mast cells in PI. This study provides novel insights into understanding the molecular mechanisms of PI and contributes to advancements in its early diagnosis and prevention.

Detection and comparison of neutrophil extracellular traps in tissue samples of peri-implantitis, periodontitis, and healthy patients: A pilot study

OBJECTIVE

The aim of this study was to detect and compare the tissular expression of neutrophil extracellular traps (NETs) in peri-implant and periodontal samples of patients with peri-implantitis, periodontitis, and controls.

MATERIALS AND METHODS

An observational study was performed on patients with peri-implantitis, periodontitis, and controls. Peri-implant and/or periodontal clinical examinations were performed on each participant. Tissue samples were collected during tooth/implant extraction for clinical reasons. Electron microscopy analysis, Picro-Sirius red staining, immunohistochemical (CD15), and immunofluorescence (citrullinated H3 and myeloperoxidase) techniques were performed to detect NET-related structures and the degree of connective tissue destruction, between the study groups.

RESULTS

Sixty-four patients were included in the study: 28 peri-implantitis, 26 periodontitis, and 10 controls, with a total of 51 implants, 26 periodontal teeth, and 10 control teeth. Neutrophil release of nuclear content was observed in transmission electron microscopy. Immunohistochemical analysis showed a greater CD15 expression in both peri-implantitis and periodontitis compared to controls (p < 0.001), and peri-implantitis presented lower levels of connective tissue and collagen compared to both periodontitis (p = 0.044; p < 0.001) and controls (p < 0.001). Immunofluorescence showed greater citH3 expression in peri-implantitis than the one found in both periodontitis (p = 0.003) and controls (p = 0.048).

CONCLUSIONS

A greater presence and involvement of neutrophils, as well as a greater connective tissue destruction were observed in cases of peri-implantitis. A higher expression of NET-related markers was found in mucosal samples of peri-implantitis compared to periodontitis and controls.

Correlation between Inflammasomes and Microbiota in Peri-Implantitis

The activation of inflammasomes is thought to induce the inflammatory process around dental implants. No information is available on the correlation between microbiota and inflammasomes in clinical samples from patients suffering peri-implantitis. For this cross-sectional study, 30 biofilm samples were obtained from 19 patients undergoing surgical treatment for peri-implantitis because of the presence of bleeding on probing, probing depth higher than 6 mm, and radiographic bone loss higher than 3 mm. Then, soft tissue samples from around the implant were also collected. The relative abundance of bacteria and alpha-diversity indexes were calculated after analyzing the 16S rRNA gene using next-generation sequencing. The soft-tissue samples were processed for evaluation of the inflammasomes NLRP3 and AIM2 as well as caspase-1 and IL-1β. The relative abundance (mean (SD)) of specific species indicated that the most abundant species were Porphyromonas gingivalis (10.95 (14.17)%), Fusobacterium vincentii (10.93 (13.18)%), Porphyromonas endodontalis (5.89 (7.23)%), Prevotella oris (3.88 (4.94)%), Treponema denticola (2.91 (3.19)%), and Tannerella forsythia (2.84 (4.15)%). Several correlations were found between the species and the immunohistochemical detection of the inflammasomes NLRP3 and AIM2 as well as caspase-1 and IL-1β, both in the epithelium and the lamina propria. A network analysis found an important cluster of variables formed by NLRP3 in the lamina propria and AIM2, caspase-1, and IL-1β in the lamina propria and the epithelium with Prevotella dentalis, Prevotella tannerae, Tannerella forsythia, or Selenomonas timonae. Thus, it could be concluded that inflammasomes NLRP3 and AIM2 and their downstream effectors caspase-1 and interleukin-1β can be significantly associated with specific bacteria.