The Genetic and Epigenetic Mechanisms Involved in Irreversible Pulp Neural Inflammation

Identification and characterization of the ferroptosis-related ceRNA network in irreversible pulpitis

Background

The role of ferroptosis in irreversible pulpitis (IP) remains unclear. The competing endogenous RNA (ceRNA) theory that has been widely investigated is rarely used studied in IP. Hub lncRNAs selected from a ceRNA network may provide a novel hypothesis for the interaction of ferroptosis and IP.

Methods

Differentially expressed genes (DEGs) were intersected with 484 ferroptosis markers to identify differentially expressed ferroptosis-related genes (DE-FRGs). Functional analysis and protein-protein interaction (PPI) networks were constructed to reveal the functions of DE-FRGs. Then, coexpression analyses were conducted between DE-FRGs and DElncRNAs to define ferroptosis-related DElncRNAs (FR-DElncRNAs). Predictions of DE-FRG- and FR-DElncRNA-related miRNAs were obtained, and members of both groups were selected. Additionally, two ceRNA networks consisting of FR-DElncRNAs, miRNAs and DE-FRGs from upregulated and downregulated groups were built. Finally, the hub lncRNAs of the ceRNA networks were used for immuno-infiltration analysis and qPCR verification.

Results

According to the results of PCA and clustering analysis, 5 inflamed and 5 healthy pulp tissue samples were selected for analysis. The intersection of DEGs with 484 ferroptosis marker genes identified 72 DE-FRGs. The response to stimulus, cellular process, signaling, localization, and biological regulation pathways related to DE-FRGs were enriched. In total, 161 downregulated and 40 upregulated FR-DElncRNAs were chosen by coexpression analysis for further investigation. The MultimiR package and starBase were used to predict miRNAs of DE-FRGs and FR-DElncRNAs, respectively. The upregulated ceRNA network contained 2 FR-DElncRNAs (↑), 19 miRNAs (↓) and 22 DE-FRGs (↑). The downregulated network contained 44 FR-DElncRNAs (↓), 251 miRNAs (↑) and 10 DE-FRGs (↓). Six hub lncRNAs were identified based on the MCC method (LUCAT1 and AC106897.1 ↑; LINC00943, AL583810.1, AC068888.1, and AC125257.1↓). In addition, strong relationships between hub lncRNAs and immune cells were shown by immune infiltration analysis. Finally, validated by qPCR assays of the pulp tissue of IP patients, the expression levels in clinical samples were consistent with the microarray data.

Conclusion

Two ceRNA networks were comprehensively constructed, and 6 hub lncRNAs were identified. These genes provide novel insights into the relationship between ferroptosis and IP. Intriguingly, the LINC00943/hsa-miR-29a-3p/PDK4 axis was deemed to be the key node in this network.

Establishment and validation of the autophagy-related ceRNA network in irreversible pulpitis

BACKGROUND

The molecular mechanisms underlying the onset and progression of irreversible pulpitis have been studied for decades. Many studies have indicated a potential correlation between autophagy and this disease. Against the background of the competing endogenous RNA (ceRNA) theory, protein-coding RNA functions are linked with long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). This mechanism has been widely studied in various fields but has rarely been reported in the context of irreversible pulpitis. The hub genes selected under this theory may represent the key to the interaction between autophagy and irreversible pulpitis.

RESULTS

Filtering and differential expression analyses of the GSE92681 dataset, which contains data from 7 inflamed and 5 healthy pulp tissue samples, were conducted. The results were intersected with autophagy-related genes (ARGs), and 36 differentially expressed ARGs (DE-ARGs) were identified. Functional enrichment analysis and construction of the protein‒protein interaction (PPI) network of DE-ARGs were performed. Coexpression analysis was conducted between differentially expressed lncRNAs (DElncRNAs) and DE-ARGs, and 151 downregulated and 59 upregulated autophagy-related DElncRNAs (AR-DElncRNAs) were identified. StarBase and multiMiR were then used to predict related microRNAs of AR-DElncRNAs and DE-ARGs, respectively. We established ceRNA networks including 9 hub lncRNAs (HCP5 and AC112496.1 ↑; FENDRR, AC099850.1, ZSWIM8-AS1, DLX6-AS1, LAMTOR5-AS1, TMEM161B-AS1 and AC145207.5 ↓), which were validated by a qRT‒PCR analysis of pulp tissue from patients with irreversible pulpitis.

CONCLUSION

We constructed two networks consisting of 9 hub lncRNAs based on the comprehensive identification of autophagy-related ceRNAs. This study may provide novel insights into the interactive relationship between autophagy and irreversible pulpitis and identifies several lncRNAs that may serve as potential biological markers.

Identification of the characteristics of infiltrating immune cells in pulpitis and its potential molecular regulation mechanism by bioinformatics method

OBJECTIVE

The inflammation of dental pulp will also trigger an immune response. The purpose of this study is to demonstrate the immune cell's function and explore their regulatory molecules and signal pathways in pulpitis.

METHOD

The CIBERSORTx method was used to quantitatively analyze 22 types of immune cells infiltrating in the GSE77459 dataset of dental pulp tissues. The immune-related differential genes (IR-DEGs) were further screened and enriched for the GO and KEGG pathways. Protein-protein interaction (PPI) networks were constructed and the hub IR-DEGs were screened. Finally, we constructed the regulatory network of hub genes.

RESULTS

The GSE77459 dataset screened 166 IR-DEGs and was enriched for three signal pathways involved in pulpitis development: chemokine signaling, TNF signaling, and NF-κB signaling. Significant differences in immune cell infiltration were observed between normal and inflamed dental pulp. The proportions of M0 macrophages, neutrophils, and follicular helper T cells were significantly higher than that of the normal dental pulp, while the proportions of resting mast cells, resting dendritic cells, CD8 T cells, and monocytes were significantly lower. The random forest algorithm concluded that M0 macrophages and neutrophils were the two most important immune cells. We identified five immune-related hub genes IL-6, TNF-α, IL-1β, CXCL8, and CCL2. In addition, IL-6, IL-1β, and CXCL8 are highly correlated with M0 macrophages and neutrophils, and the five hub genes have many shared regulatory molecules: four miRNAs and two lncRNAs, three transcription factors.

CONCLUSION

Immune cell infiltration plays an important role in pulpitis among which M0 macrophages and neutrophils are the most significant immune cells. IL-6, TNF-α, IL-1, CXCL8, and CCL2 may be essential molecule of the immune response regulation network in pulpitis. This will help us understand the immune regulatory network in pulpitis.

Identification of key module and hub genes in pulpitis using weighted gene co-expression network analysis

BACKGROUND

Pulpitis is a common disease mainly caused by bacteria. Conventional approaches of diagnosing the state of dental pulp are mainly based on clinical symptoms, thereby harbor deficiencies. The accurate and rapid diagnosis of pulpitis is important for choosing the suitable therapy. The study aimed to identify pulpits related key genes by integrating micro-array data analysis and systems biology network-based methods such as weighted gene co-expression network analysis (WGCNA).

METHODS

The micro-array data of 13 inflamed pulp and 11 normal pulp were acquired from Gene Expression Omnibus (GEO). WGCNA was utilized to establish a genetic network and categorize genes into diverse modules. Hub genes in the most associated module to pulpitis were screened out using high module group members (MM) methods. Pulpitis model in rat was constructed and iRoot BP plus was applied to cap pulp. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for validation of hub genes.

RESULTS

WGCNA was established and genes were categorized into 22 modules. The darkgrey module had the highest correlation with pulpitis among them. A total of 5 hub genes (HMOX1, LOX, ACTG1, STAT3, GNB5) were identified. RT-qPCR proved the differences in expression levels of HMOX1, LOX, ACTG1, STAT3, GNB5 in inflamed dental pulp. Pulp capping reversed the expression level of HMOX1, LOX, ACTG1.

CONCLUSION

The study was the first to produce a holistic view of pulpitis, screen out and validate hub genes involved in pulpitis using WGCNA method. Pulp capping using iRoot BP plus could reverse partial hub genes.

Identification of Immune-Related lncRNA Regulatory Network in Pulpitis

Background. Long noncoding RNAs (lncRNAs) are emerging as critical regulators of various biological processes, including immune regulation. Methods. Due to the critical significance of immunological responses in the development and progression of pulpitis, we used an integrated algorithm to identify immune-related lncRNAs and then examined the lncRNA-immunity regulation network in pulpitis. Before identifying immune-related lncRNAs, the data from GEO datasets were precleaned. ConsensusClusterPlus was used to differentiate immune-related pulpitis subgroups. Enrichment analysis using GO and MSigDB databases was employed to determine the differences in molecular function, cellular component, and biological process between the two pulpitis subtypes. Results. An integrated algorithm was designed to filtrate immune-related lncRNAs accurately. 790 immune-related lncRNAs were found in 17 immunological categories, with 38 of them perturbated in pulpitis. The Cytoscape software was used to visualize the relationship between representative immune regulatory pathways and immune-related lncRNAs. Two immune-related pulpitis subtypes were discovered using differentially expressed immune-related lncRNAs. Subtype 2 has a stronger association with immune-related pathways than subtype 1 does. Conclusions. Our study identified many immune-related lncRNAs and investigated potential lncRNA regulation networks; meanwhile, the molecular subtypes of pulpitis were identified, all of which will be relevant for further research into inflammatory and immunological processes in pulpitis.

Comprehensive Analysis of Differentially Expressed Genes in Clinically Diagnosed Irreversible Pulpitis by Multiplatform Data Integration Using a Robust Rank Aggregation Approach

INTRODUCTION

Molecular diagnosis may overcome the limitations of clinical and histologic diagnosis in pulpitis, thereby benefiting many treatment techniques, such as vital pulp therapies. In this study, integrated microarray data on pulpitis were used to obtain a list of normalized differentially expressed (DE) genes for analyzing the molecular mechanisms underlying pulpitis and identifying potential diagnostic biomarkers.

METHODS

A systematic search of public microarray and sequencing databases was performed to obtain expression data of pulpitis. Robust rank aggregation (RRA) was used to obtain DE gene lists (RRA_DEmRNAs and RRA_DElncRNAs) between inflamed pulp and normal samples. DE genes were evaluated by functional enrichment analyses, correlation analyses for inflammation-related RRA_DEmRNAs, and protein-protein interaction and competing endogenous RNA network construction. Quantitative real-time polymerase chain reaction validation was applied in snap-frozen pulp tissues.

RESULTS

Using the GSE77459 and GSE92681 data sets, 280 RRA_DEmRNAs and 90 RRA_DElncRNAs were identified. RRA_DEmRNAs were significantly enriched in inflammation-related biological processes and osteoclast differentiation and tumor necrosis factor, chemokine, and B-cell receptor signaling pathways. The molecular complex detection and cytoHubba methods identified 2 clusters and 10 hub genes in the protein-protein interaction network. The competing endogenous RNA network was composed of 2 long noncoding RNAs (ADAMTS9-AS2 and LINC00290), 2 microRNAs (hsa-miR-30a-5p and hsa-miR-128-3p), and 3 messenger RNAs (ABCA1, FBLN5, and SOCS3). The expression between most top inflammation-related RRA_DEmRNAs in pulpitis showed positive correlations. Quantitative real-time polymerase chain reacation validated the expression trends of selected genes, including ITGAX, TREM1, CD86, FCGR2A, ADAMTS9-AS2, LINC00290, hsa-miR-30a-5p, hsa-miR-128-3p, RASGRP3, IL3RA, CCDC178, CRISPLD1, LINC01857, AC007991.2, ARHGEF26-AS1, and AL021408.1.

CONCLUSIONS

The identified biomarkers provide insight into the pathology and may aid in the molecular diagnosis of pulpitis.