Shared Molecular Mechanisms between Atherosclerosis and Periodontitis by Analyzing the Transcriptomic Alterations of Peripheral Blood Monocytes

Exploratory Study of Differentially Expressed Genes of Peripheral Blood Monocytes in Patients with Carotid Atherosclerosis

BACKGROUND

The abundance of circulating monocytes is closely associated with the development of atherosclerosis in humans.

OBJECTIVE

This study aimed to further research into diagnostic biomarkers and targeted treatment of carotid atherosclerosis (CAS).

METHODS

We performed transcriptomics analysis through weighted gene co-expression network analysis (WGCNA) of monocytes from patients in public databases with and without CAS. Differentially expressed genes (DEGs) were screened by R package limma. Diagnostic molecules were derived by the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) algorithms. NetworkAnalyst, miRWalk, and Star- Base databases assisted in the construction of diagnostic molecule regulatory networks. The Drug- Bank database predicted drugs targeting the diagnostic molecules. RT-PCR tested expression profiles.

RESULTS

From 14,369 hub genes and 61 DEGs, six differentially expressed monocyte-related hub genes were significantly associated with immune cells, immune responses, monocytes, and lipid metabolism. LASSO and SVM-RFE yielded five genes for CAS prediction. RT-PCR of these genes showed HMGB1 was upregulated, and CCL3, CCL3L1, CCL4, and DUSP1 were downregulated in CAS versus controls. Then, we constructed and visualized the regulatory networks of 9 transcription factors (TFs), which significantly related to 5 diagnostic molecules. About 11 miRNAs, 19 lncRNAs, and 39 edges centered on four diagnostic molecules (CCL3, CCL4, DUSP1, and HMGB1) were constructed and displayed. Eleven potential drugs were identified, including ibrutinib, CTI-01, roflumilast etc. Conclusion: A set of five biomarkers were identified for the diagnosis of CAS and for the study of potential therapeutic targets.

The Genetic Cross-Talk between Periodontitis and Chronic Kidney Failure Revealed by Transcriptomic Analysis

Periodontitis and chronic kidney failure (CKF) are potentially related to each other. This bioinformatics analysis aimed at the identification of potential cross-talk genes and related pathways between periodontitis and CKF. Based on NCBI Gene Expression Omnibus (GEO), datasets GSE10334, GSE16134, and GSE23586 were extracted for periodontitis. A differential expression analysis (p < 0.05, |log2(FC)| > 0.5) was performed to assess deregulated genes (DEGs). CKF-related genes were extracted from DisGeNET and examined regarding their overlap with periodontitis-related DEGs. Cytoscape was used to construct and analyze a protein-protein interaction (PPI) network. Based on Cytoscape plugin MCODE and a LASSO regression analysis, the potential hub cross-talk genes were identified. Finally, a complex PPI of the hub genes was constructed. A total of 489 DEGs for periodontitis were revealed. With the 805 CKF-related genes, an overlap of 47 cross-talk genes was found. The PPI network of the potential cross-talk genes was composed of 1081 nodes and 1191 edges. The analysis with MCODE resulted in 10 potential hub genes, while the LASSO regression resulted in 22. Finally, five hub cross-talk genes, CCL5, FCGR3B, MMP-9, SAA1, and SELL, were identified. Those genes were significantly upregulated in diseased samples compared to controls (p ≤ 0.01). Furthermore, ROC analysis showed a high predictive value of those genes (AUC ≥ 73.44%). Potentially relevant processes and pathways were primarily related to inflammation, metabolism, and cardiovascular issues. In conclusion, five hub cross-talk genes, i.e., CCL5, FCGR3B, MMP-9, SAA1, and SELL, could be involved in the interplay between periodontitis and CKF, whereby primarily inflammation, metabolic, and vascular issues appear to be of relevance.

Association of Early Childhood Caries with Bitter Taste Receptors: A Meta-Analysis of Genome-Wide Association Studies and Transcriptome-Wide Association Study

Although genetics affects early childhood caries (ECC) risk, few studies have focused on finding its specific genetic determinants. Here, we performed genome-wide association studies (GWAS) in five cohorts of children (aged up to 5 years, total N = 2974, cohorts: Center for Oral Health Research in Appalachia cohorts one and two [COHRA1, COHRA2], Iowa Fluoride Study, Iowa Head Start, Avon Longitudinal Study of Parents and Children [ALSPAC]) aiming to identify genes with potential roles in ECC biology. We meta-analyzed the GWASs testing ~3.9 million genetic variants and found suggestive evidence for association at genetic regions previously associated with caries in primary and permanent dentition, including the β-defensin anti-microbial proteins. We then integrated the meta-analysis results with gene expression data in a transcriptome-wide association study (TWAS). This approach identified four genes whose genetically predicted expression was associated with ECC (p-values < 3.09 × 10−6; CDH17, TAS2R43, SMIM10L1, TAS2R14). Some of the strongest associations were with genes encoding members of the bitter taste receptor family (TAS2R); other members of this family have previously been associated with caries. Of note, we identified the receptor encoded by TAS2R14, which stimulates innate immunity and anti-microbial defense in response to molecules released by the cariogenic bacteria, Streptococcus mutans and Staphylococcus aureus. These findings provide insight into ECC genetic architecture, underscore the importance of host-microbial interaction in caries risk, and identify novel risk genes.

Potential Roles of Selectins in Periodontal Diseases and Associated Systemic Diseases: Could They Be Targets for Immunotherapy?

Periodontal diseases are predisposing factors to the development of many systemic disorders, which is often initiated via leukocyte infiltration and vascular inflammation. These diseases could significantly affect human health and quality of life. Hence, it is vital to explore effective therapies to prevent disease progression. Periodontitis, which is characterized by gingival bleeding, disruption of the gingival capillary's integrity, and irreversible destruction of the periodontal supporting bone, appears to be caused by overexpression of selectins in periodontal tissues. Selectins (P-, L-, and E-selectins) are vital members of adhesion molecules regulating inflammatory and immune responses. They are mainly located in platelets, leukocytes, and endothelial cells. Furthermore, selectins are involved in the immunopathogenesis of vascular inflammatory diseases, such as cardiovascular disease, diabetes, cancers, and so on, by mediating leukocyte recruitment, platelet activation, and alteration of endothelial barrier permeability. Therefore, selectins could be new immunotherapeutic targets for periodontal disorders and their associated systemic diseases since they play a crucial role in immune regulation and endothelium dysfunction. However, the research on selectins and their association with periodontal and systemic diseases remains limited. This review aims to discuss the critical roles of selectins in periodontitis and associated systemic disorders and highlights the potential of selectins as therapeutic targets.

Integrated analysis and exploration of potential shared gene signatures between carotid atherosclerosis and periodontitis

BACKGROUND

Increasing evidence has suggested an association between carotid atherosclerosis (CAS) and periodontitis (PD); however, the mechanisms have not been fully understood. This study aims to investigate the shared genes and molecular mechanisms underlying the co-pathogenesis of CAS and PD.

METHODS

Gene Expression Omnibus (GEO) datasets GSE100927 and GSE10334 were downloaded, and differentially expressed genes (DEGs) shared by both datasets were identified. The functional enrichment analysis of these overlapping DEGs was then conducted. A protein-protein interaction (PPI) network was created using the STRING database and Cytoscape software, and PPI key genes were identified using the cytoHubba plugin. Then, weighted gene co-expression network analysis (WGCNA) was performed on GSE100927 and GSE10334, and the gene modules most correlated with CAS and PD were identified as key modules. The genes in key modules overlapping with PPI key genes were determined to be the key crosstalk genes. Subsequently, the key crosstalk genes were validated in three independent external datasets (GSE43292 [CAS microarray dataset], GSE16134 [PD microarray dataset], and GSE28829 [CAS microarray dataset]). In addition, the immune cell patterns of PD and CAS were evaluated by single-sample gene set enrichment analysis (ssGSEA), and the correlation of key crosstalk genes with each immune cell was calculated. Finally, we investigated the transcription factors (TFs) that regulate key crosstalk genes using NetworkAnalyst 3.0 platform.

RESULTS

355 overlapping DEGs of CAS and PD were identified. Functional enrichment analysis highlighted the vital role of immune and inflammatory pathways in CAS and PD. The PPI network was constructed, and eight PPI key genes were identified by cytoHubba, including CD4, FCGR2A, IL1B, ITGAM, ITGAX, LCK, PTPRC, and TNF. By WGCNA, the turquoise module was identified as the most correlated module with CAS, and the blue module was identified as the most correlated module with PD. Ultimately, ITGAM and LCK were identified as key crosstalk genes as they appeared both in key modules and PPI key genes. Expression levels of ITGAM and LCK were significantly elevated in the case groups of the test datasets (GSE100927 and GSE10334) and validation datasets (GSE43292, GSE16134, and GSE28829). In addition, the expression of multiple immune cells was significantly elevated in PD and CAS compared to controls, and the two key crosstalk genes were both significantly associated with CD4 T cells. Finally, SPI1 was identified as a potential key TF, which regulates the two key crosstalk genes.

CONCLUSION

This study identified the key crosstalk genes and TF in PD and CAS, which provides new insights for further studies on the co-morbidity mechanisms of CAS and PD from an immune and inflammatory perspective.

Transcriptomic Analysis Reveals Genetic Cross-Talk between Periodontitis and Hypothyroidism

Background. Aim of this bioinformatics study based on transcriptomic analysis was to reveal the cross-talk between periodontitis (PD) and hypothyroidism (HT). Methods. The gene expression datasets GSE18152 and GSE176153 of HT and GSE10334, GSE16134, and GSE173078 of PD were downloaded through the Gene Expression Omnibus (GEO) database. Differential Expression Genes (DEG) between cases and controls in each microarray were assessed by using the “limma” (linear models for microarray data) R package (|log2 fold change (FC)| >0 and $P$ -value <0.05). To analyze the cross-talk effect between HT and PD, the intersection of DEG of HT and PD was selected. To investigate the biological function of cross-talk genes, the gene ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied. Protein-Protein Interaction (PPI) network was constructed using Cytoscape software. Top 10 cross-talk genes were screened, and the expression values of these 10 genes were extracted. ROC analysis was performed by using the pROC package and GGplot2 package of R language to predict the classification accuracy. Results. The overlapping DEG between HT and PD were 107 cross-talk genes. The results revealed that developmental process ( $P$ -value =1.06E-21) was the most significantly enriched biological process, followed by cell differentiation ( $P$ -value =8.49E-18) and immune system process ( $P$ -value =6.78E-11). KEGG analysis showed that Complement and coagulation cascades ( $P$ -value =2.29E-05), Hematopoietic cell lineage ( $P$ -value =2.66E-05), Phospholipase D signaling pathway ( $P$ -value =0.034367878) and Chemokine signaling pathway ( $P$ -value =0.04946333) were significantly enriched. The top 10 genes with most connections were LCE1B, LCE2B, LCE2A, LCE2C, LCE1C, LCE1F, ITGAM, C1QB, TREM2, and CD19. The AUC values of the two datasets of HT were both greater than 65% (GSE18152 = 81.42%, GSE176153 = 68.75%). AUC values of three datasets of PD were all greater than 60% (GSE10334 = 69.23%, GSE16134 = 73.72%, GSE173078 = 81.6%). Conclusions. A genetic cross-talk between HT and PD was detected, whereby LCE family genes appeared to play the most important role.

PAMPs and DAMPs as the Bridge Between Periodontitis and Atherosclerosis: The Potential Therapeutic Targets

Atherosclerosis is a chronic artery disease characterized by plaque formation and vascular inflammation, eventually leading to myocardial infarction and stroke. Innate immunity plays an irreplaceable role in the vascular inflammatory response triggered by chronic infection. Periodontitis is a common chronic disorder that involves oral microbe-related inflammatory bone loss and local destruction of the periodontal ligament and is a risk factor for atherosclerosis. Periodontal pathogens contain numerous pathogen-associated molecular patterns (PAMPs) such as lipopolysaccharide, CpG DNA, and Peptidoglycan, that initiate the inflammatory response of the innate immunity depending on the recognition of pattern-recognition receptors (PRRs) of host cells. The immune-inflammatory response and destruction of the periodontal tissue will produce a large number of damage-associated molecular patterns (DAMPs) such as neutrophil extracellular traps (NETs), high mobility group box 1 (HMGB1), alarmins (S100 protein), and which can further affect the progression of atherosclerosis. Molecular patterns have recently become the therapeutic targets for inflammatory disease, including blocking the interaction between molecular patterns and PRRs and controlling the related signal transduction pathway. This review summarized the research progress of some representative PAMPs and DAMPs as the molecular pathological mechanism bridging periodontitis and atherosclerosis. We also discussed possible ways to prevent serious cardiovascular events in patients with periodontitis and atherosclerosis by targeting molecular patterns.