Comparative analysis of blood and saliva expression profiles in chronic and refractory periodontitis patients

Unique miRomics Expression Profiles in Tannerella forsythia-Infected Mandibles during Periodontitis Using Machine Learning

T. forsythia is a subgingival periodontal bacterium constituting the subgingival pathogenic polymicrobial milieu during periodontitis (PD). miRNAs play a pivotal role in maintaining periodontal tissue homeostasis at the transcriptional, post-transcriptional, and epigenetic levels. The aim of this study was to characterize the global microRNAs (miRNA, miR) expression kinetics in 8- and 16-week-old T. forsythia-infected C57BL/6J mouse mandibles and to identify the miRNA bacterial biomarkers of disease process at specific time points. We examined the differential expression (DE) of miRNAs in mouse mandibles (n = 10) using high-throughput NanoString nCounter® miRNA expression panels, which provided significant advantages over specific candidate miRNA or pathway analyses. All the T. forsythia-infected mice at two specific time points showed bacterial colonization (100%) in the gingival surface, along with a significant increase in alveolar bone resorption (ABR) (p < 0.0001). We performed a NanoString analysis of specific miRNA signatures, miRNA target pathways, and gene network analysis. A total of 115 miRNAs were DE in the mandible tissue during 8 and 16 weeks The T. forsythia infection, compared with sham infection, and the majority (99) of DE miRNAs were downregulated. nCounter miRNA expression kinetics identified 67 downregulated miRNAs (e.g., miR-375, miR-200c, miR-200b, miR-34b-5p, miR-141) during an 8-week infection, whereas 16 upregulated miRNAs (e.g., miR-1902, miR-let-7c, miR-146a) and 32 downregulated miRNAs (e.g., miR-2135, miR-720, miR-376c) were identified during a 16-week infection. Two miRNAs, miR-375 and miR-200c, were highly downregulated with >twofold change during an 8-week infection. Six miRNAs in the 8-week infection (miR-200b, miR-141, miR-205, miR-423-3p, miR-141-3p, miR-34a-5p) and two miRNAs in the 16-week infection (miR-27a-3p, miR-15a-5p) that were downregulated have also been reported in the gingival tissue and saliva of periodontitis patients. This preclinical in vivo study identified T. forsythia-specific miRNAs (miR-let-7c, miR-210, miR-146a, miR-423-5p, miR-24, miR-218, miR-26b, miR-23a-3p) and these miRs have also been reported in the gingival tissues and saliva of periodontitis patients. Further, several DE miRNAs that are significantly upregulated (e.g., miR-101b, miR-218, miR-127, miR-24) are also associated with many systemic diseases such as atherosclerosis, Alzheimer's disease, rheumatoid arthritis, osteoarthritis, diabetes, obesity, and several cancers. In addition to DE analysis, we utilized the XGBoost (eXtreme Gradient boost) and Random Forest machine learning (ML) algorithms to assess the impact that the number of miRNA copies has on predicting whether a mouse is infected. XGBoost found that miR-339-5p was most predictive for mice infection at 16 weeks. miR-592-5p was most predictive for mice infection at 8 weeks and also when the 8-week and 16-week results were grouped together. Random Forest predicted miR-592 as most predictive at 8 weeks as well as the combined 8-week and 16-week results, but miR-423-5p was most predictive at 16 weeks. In conclusion, the expression levels of miR-375 and miR-200c family differed significantly during disease process, and these miRNAs establishes a link between T. forsythia and development of periodontitis genesis, offering new insights regarding the pathobiology of this bacterium.

Development of an miRNA-Array-Based Diagnostic Signature for Periodontitis

Periodontitis progression is accompanied by irreversible alveolar bone absorption and leads to tooth loss. Early diagnosis is important for tooth stability and periodontal tissue preservation. However, there is no recognized miRNA diagnostic signature with convincing sensitivity and specificity for periodontitis. In this study, we obtained miRNA array expression profiles of periodontitis from the Gene Expression Omnibus (GEO) database. After screening for differentially expressed miRNAs, the least absolute shrinkage and selection operator (LASSO) method was performed to identify and construct a 17-miRNA-based diagnostic signature (hsa-miR-3917, hsa-mir-4271, hsa-miR-3156, hsa-miR-3141, hsa-miR-1246, hsa-miR-125a-5p, hsa-miR-671-5p, hcmv-mir-UL70, hsa-miR-650, hsa-miR-497-3p, hsa-miR-145-3p, hsa-miR-141-3p, hsa-miR-210-3p, hsa-miR-204-3p, hsa-miR-203a-5p, hsa-miR-99a-3p, and hsa-miR-30a-3p). Periodontal tissue samples with higher risk scores were more likely to show symptoms of periodontitis. Then, the receiver operating characteristic (ROC) curves were used to assess the diagnostic value of the miRNA signature, which indicated that the optimum cutoff value in periodontitis diagnosis was 0.5056 with an area under the ROC curve (AUC) of 0.996, a sensitivity of 97.3%, a specificity of 100.0% in the training cohort; in the testing cohort, the corresponding values were as follows: an AUC of 0.998, a sensitivity of 97.9%, and a specificity of 91.7%. We next evaluated the efficacy of the signature in differentiating disease subtype and affected range. Furthermore, we conducted functional enrichment analysis of the 17 miRNA-targeted mRNAs, including the regulation of mTOR activity and cell autophagy, Th1/Th2 cell balance and immunoregulation, cell apoptosis, and so on. In summary, our study identified and validated a 17-miRNA diagnostic signature with convincing AUC, sensitivity, and specificity for periodontitis.

Transcriptomic profiles and their correlations in saliva and gingival tissue biopsy samples from periodontitis and healthy patients

Purpose

This study was conducted to analyze specific RNA expression profiles in gingival tissue and saliva samples in periodontitis patients and healthy individuals, and to determine their correlations in light of the potential use of microarray-based analyses of saliva samples as a periodontal monitoring tool.

Methods

Gingival tissue biopsies and saliva samples from 22 patients (12 with severe periodontitis and 10 with a healthy periodontium) were analyzed using transcriptomic microarray analysis. Differential gene expression was assessed, and pathway and clustering analyses were conducted for the samples. The correlations between the results for the gingival tissue and saliva samples were analyzed at both the gene and pathway levels.

Results

There were 621 differentially expressed genes (DEGs; 320 upregulated and 301 downregulated) in the gingival tissue samples of the periodontitis group, and 154 DEGs (44 upregulated and 110 downregulated) in the saliva samples. Nine of these genes overlapped between the sample types. The periodontitis patients formed a distinct cluster group based on gene expression profiles for both the tissue and saliva samples. Database for Annotation, Visualization and Integrated Discovery analysis revealed 159 enriched pathways from the tissue samples of the periodontitis patients, as well as 110 enriched pathways In the saliva samples. Thirty-four pathways overlapped between the sample types.

Conclusions

The present results indicate the possibility of using the salivary transcriptome to distinguish periodontitis patients from healthy individuals. Further work is required to enhance the extraction of available RNA from saliva samples.

Detection of Salivary miRNAs Reflecting Chronic Periodontitis: A Pilot Study

The purpose of this cross-sectional pilot study was to find salivary microRNAs (miRNAs) reflecting periodontal condition in chronic periodontitis. One hundred and twenty chronic periodontitis patients (mean age, 68.4 years) participated in the study, from whom unstimulated whole saliva was collected. A multiphase study was conducted to explore salivary miRNAs as biomarkers of periodontitis. At first, a polymerase chain reaction (PCR) array was performed to compare salivary miRNAs profiles in no and mild (no/mild) and severe periodontitis patients. Next, the relative expression of salivary miRNAs on individual samples was assessed by real-time reverse transcription-PCR. The numbers (%) of patients were 26 (21.6%, no/mild), 58 (48.3%, moderate) and 36 (30.0%, severe), respectively. Among 84 miRNAs, only the relative expression of hsa-miR-381-3p in the severe periodontitis group was significantly higher than that of the no/mild periodontitis group (p < 0.05). Among the 120 patients, there was also a significant correlation between the relative expression of hsa-miR-381-3p and the mean probing pocket depth (PPD) (r = 0.181, p < 0.05). Salivary hsa-miR-381-3p was correlated with periodontitis condition in chronic periodontitis patients.

Regulat-INGs in tumors and diseases: Focus on ncRNAs

ING family genes (Inhibitor of Growth) are tumor suppressor genes that play a vital role in cell homeostasis. It has been shown that their expression is lost or diminished in many cancers and other diseases. The main mechanisms by which they are regulated in oncogenesis have not yet been fully elucidated. The involvement of non-coding RNAs (ncRNAs) and in particular microRNAs (miRNAs) in post-transcriptional gene regulation is well established. miRNAs are short sequences (18-25 nucleotides) that can bind to the 3 'UTR sequence of the targeted messenger RNA (mRNA), leading to its degradation or translational repression. Interactions between the ING family and miRNAs have been described in some cancers but also in other diseases. The involvement of miRNAs in ING family regulation opens up new fields of investigation, particularly for targeted therapies. In this review, we will summarize the regulatory mechanisms at the RNA and protein level of the ING family and focus on the interactions with ncRNAs.

The use of systemic antibiotics in the treatment of refractory periodontitis: A systematic review

BACKGROUND

The goal in treating refractory periodontitis (RP) is to arrest or slow disease progression, which usually has included the use of systemic antibiotics adjunct to conventional mechanical debridement. The aim of this systematic review was to evaluate the evidence that the association of systemic antibiotics with conventional mechanical debridement increases the efficacy of periodontal therapy in the treatment of RP.

TYPES OF STUDIES REVIEWED

The authors searched for studies in PubMed MEDLINE, Cochrane Central Register of Controlled Trials, Thomson Reuters Web of Science, Scopus, Latin American and Caribbean Center on Health Sciences Information, and Scientific Electronic Library Online electronic databases by using selected key words from the earliest records up through October 31, 2014. Only clinical intervention studies in which investigators compared the treatment of participants with RP with either mechanical debridement alone or associated with systemic antibiotics were eligible for selection. Two authors independently assessed the risk of bias of each selected study.

RESULTS

The authors identified 13 articles and included 6 of them. Investigators in all studies reported greater reductions in probing depth or in loss of clinical attachment level after adjunct systemic antibiotic therapy when compared with mechanical debridement alone. Antibiotics tested included metronidazole, clindamycin, tetracycline hydrochloride, amoxicillin, and amoxicillin and potassium clavulanate. Five studies presented a high risk of bias, and 1 study presented an unclear risk.

CONCLUSIONS AND PRACTICAL IMPLICATIONS

The overall quality of the evidence does not allow the conclusion that adjunct systemic antibiotics are of additional benefit to conventional mechanical debridement alone.