A Roadmap towards Precision Periodontics

A drop-like optical fiber salivary pH sensor: A rapid and real-time detection of periodontal disease

A real-time and rapid detection of salivary pH for periodontal diagnosis is an emerging point-of-care (POC) technology trend. The precise and non-invasive sensitive POC devices, which could be used as chair-side tools to improve clinical dental inspections, are essential for an excellent periodontal diagnosis. In this paper, we report on developing a POC technology based on optical fiber sensors as a promising marker, to the best of our knowledge, to detect the role of salivary pH in periodontitis diagnosis and support dentists' inspection. The optical fiber sensor based on a drop-like structure was fabricated by bending single-mode fiber (SMF) into a section of a thin capillary tube. In this work, firstly, the performance of the proposed sensor towards different pH levels ranging from 1 to 7 was experimentally investigated. Experimentations showed that the pH sensor responded to various pH levels with a calibration curve sensitivity of -2.075 nm/pH and a high linearity of 0.985. Then, 66 patients were enrolled in this study and divided into two groups according to clinical outcomes: Group A with clinically healthy periodontium and Group B with chronic periodontitis. The real saliva from each patient was collected, and the salivary pH was evaluated immediately using the aforementioned proposed sensor. The experimental results show that Group A and Group B salivary pH mapping ranged from 6.5 to 7.3 and 5.5 to 6.4, respectively. The proposed sensor offers substantial practical benefits, providing a rapid response time of less than 2 s, instantaneous, noninvasive, and easily monitored tool for the early detection and diagnosis of periodontal health status.

Novel Insights from Comprehensive Bioinformatics Analysis Utilizing Large-Scale Human Transcriptomes and Experimental Validation: The Role of Autophagy in Periodontitis

Objective

Autophagy plays a crucial role in the pathophysiology of periodontitis, yet its precise involvement in the disease process remains elusive. The aim of the present study was thus to investigate the involvement of autophagy in the pathology of periodontitis. This investigation involved transcriptomic analysis of a broad range of human samples and complemented by in vitro experimentation.

Materials and Methods

We analyzed the transcriptomes of human gingival tissues from individuals with periodontitis and health controls to identify the differential expression of autophagy-related genes (DEARGs) and to investigate their potential interactions and functional pathways. Additionally, protein-protein interaction (PPI) networks were constructed to identify key functional modules and hub genes. Experimental validation of autophagy regulation in periodontitis and identification of key autophagy-regulating genes was accomplished through in vitro cellular experiments. Subsequently, a comprehensive analysis of immune cell infiltrate utilizing the CIBERSORT algorithm was performed. Finally, leveraging the DSigDB database, potential candidate drugs for periodontitis treatment targeting autophagy were predicted.

Results

A total of 79 genes have been identified as DEARGs in periodontitis. An intricate interplay among the DEARGs and their impact on the regulatory mechanisms of autophagy within the context of periodontitis was observed. Subsequently, 10 hub genes were discerned through the establishment of a PPI network. Furthermore, dysregulated autophagic activity in periodontitis was validated, and 9 key genes (APP, KDR, IL1B, CXCL12, CXCR4, IL6, FOS, LCK, and SHC1) were identified through in vitro experiments. Our analysis unveiled an association between these genes and altered immune cell infiltration in periodontitis. Additionally, we predicted potential therapeutic agents such as curcumin, 27-hydroxycholesterol, and Trolox, showing promise in the treatment of periodontitis by modulating the autophagic process.

Conclusion

This study identified nine key genes for autophagy regulation and potential therapeutic agents in periodontitis. These findings not only enhance our comprehension of the pathological mechanisms of periodontitis but also provide substantial evidence for the advancement of novel therapeutic strategies.

Diagnostic Potential of Salivary Interleukin-1β and IL-10 for Distinguishing Periodontal Health From Periodontitis and Stable From Unstable Periodontitis: A Case-Control Study

Objective: This case-control study aimed to investigate the diagnostic accuracy of salivary interleukin (IL)-1β, IL-10, and IL-1β/IL-10 ratio to discriminate periodontitis from periodontal health and stable from unstable periodontitis. Methods: Saliva samples were collected from 135 (healthy on an intact periodontium = 45 [as healthy control], stable periodontitis = 39, and unstable periodontitis = 51) participants, and then clinical periodontal parameters were recorded. An enzyme-linked immunosorbent assay was used to determine salivary levels of IL-1β and IL-10. Area under the curves (AUCs), sensitivity, and specificity of IL-1β, IL-10, and IL-1β/IL-10 were estimated to discriminate between groups. Result: The level of salivary IL-1β was significantly higher in unstable periodontitis than in stable periodontitis and healthy control groups (426 ± 59, 247 ± 55, and 204 ± 36 pg/ml [picograms per milliliter], respectively). While the level of salivary IL-10 was significantly higher in the control group (360.7 ± 80.5 pg/ml) than unstable periodontitis group (146.92 ± 1.8 pg/ml), no significant difference was found between the control and stable periodontitis (317.04 ± 59.8 pg/ml) groups. IL-1β, IL-10, and IL-1β/IL-10 had significant diagnostic accuracy for differentiating healthy control from unstable periodontitis (AUCs = 0.99, 0.96, and 1; sensitivity = 0.98,1, and 1; specificity = 0.95, 0.95, and 1, respectively). Similarly, they showed significant diagnostic accuracy in distinguishing unstable from stable periodontitis (AUCs = 0.98, 0.99, and 1; sensitivity = 0.94, 1, and 1; specificity = 0.94, 0.97, and 1, respectively). Conclusion: Salivary IL-1β, IL-10, and IL-1β/IL-10 have a high potential to discriminate healthy control from periodontitis and stable from unstable periodontitis. Trial Registration: ClinicalTrials.gov identifier: NCT05722613.

Precision Medicine in Periodontics: A Literature Review

Periodontitis, a widespread health issue, requires effective prevention and management strategies due to its increasing prevalence and detrimental social consequences. The chronic inflammation associated with periodontitis also exacerbates systemic conditions, emphasizing the need for advanced approaches in addressing this public health concern. The traditional methods of periodontal diagnosis, which primarily rely on clinical indicators such as pocket depth, clinical attachment loss, mobility, and radiographic measurements of alveolar bone loss, have limitations in guiding therapy due to the intricate and multifaceted nature of periodontal diseases. Precision periodontics is the amalgamation of genomics, bioinformatics, and advanced technology, mainly biomarkers reflecting a precise patient-centered treatment. However, implementing this approach in periodontology is new due to the lack of validated periodontal biomarkers for diagnostic use. This article explores the foundations of personalized therapy in periodontal diagnosis. It discusses the current state and prospects of periodontal biomarkers as a crucial step toward realizing a precision approach in periodontal practice.

Effect of scaling and root planing with and without minocycline HCl microspheres on periodontal pathogens and clinical outcomes: A randomized clinical trial

BACKGROUND

This study tests the effects of scaling and root planing (SRP) versus SRP plus minocycline hydrochloride microspheres (SRP+MM) on 11 periodontal pathogens and clinical outcomes in Stage II-IV Grade B periodontitis participants.

METHODS

Seventy participants were randomized to receive SRP (n = 35) or SRP+MM (n = 35). Saliva and clinical outcomes were collected for both groups at baseline before SRP, 1-month reevaluation, and at 3- and 6-month periodontal recall. MM were delivered to pockets ≥5 mm immediately after SRP and immediately after the 3-month periodontal maintenance in the SRP+MM group. A proprietary saliva test* was utilized to quantitate 11 putative periodontal pathogens. Microorganisms and clinical outcomes were compared between groups using generalized linear mixed-effects models with fixed effects and random effects terms. Mean changes from baseline were compared between groups via group-by-visit interaction tests.

RESULTS

Significant reduction in Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Parvimonas micra, and Eikenella corrodens were identified at the 1-month reevaluation after SRP+MM. Six months after SRP with a re-application of MM 3 months after SRP, Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens were significantly reduced. SRP+MM participants had significant clinical outcome reductions in pockets ≥5 mm at the reevaluation, 3- and 6-month periodontal maintenance, and clinical attachment loss gains at the 6-month periodontal maintenance.

CONCLUSION

MM delivered immediately after SRP and reapplication at 3 months appeared to contribute to improved clinical outcomes and sustained decreased numbers of Fusobacterium nucleatum, Prevotella intermedia, Campylobacter rectus, and Eikenella corrodens at 6 months.

Peri-implantitis and systemic inflammation: A critical update

Peri-implantitis is an inflammatory condition induced by bacterial biofilm that affects the soft and hard tissues surrounding dental implants, compromising the success of implant therapy. Recent studies have highlighted the potential links between peri-implant health and systemic inflammation, including uncontrolled diabetes mellitus, psychological stress, cardiovascular disease, obesity, and infectious diseases such as COVID-19. As an inflammatory disease, peri-implantitis may trigger systemic inflammation by elevating circulating levels of pro-inflammatory cytokines, which could have unknown impacts on overall health. While the relationship between periodontal health and systemic conditions is better understood, the association between peri-implant disease and systemic inflammation remains unclear. Therefore, this comprehensive review aims to summarize the most recent evidence on the relationship between peri-implantitis and systemic inflammation, focusing on biological complications, microbiology, and biomarkers. This review aims to enhance our understanding of the links between peri-implantitis and systemic inflammation and promote further research in this field by discussing the latest insights and clinical implications.

Peri-implant diseases diagnosis, prognosis and dental implant monitoring: a narrative review of novel strategies and clinical impact

BACKGROUND

The diagnosis of peri-implantar and periodontal relies mainly on a set of clinical measures and the evaluation of radiographic images. However, these clinical settings alone are not sufficient to determine, much less predict, periimplant bone loss or future implant failure. Early diagnosis of periimplant diseases and its rate of progress may be possible through biomarkers assessment. Once identified, biomarkers of peri-implant and periodontal tissue destruction may alert the clinicians before clinical signs show up. Therefore, it is important to consider developing chair-side diagnostic tests with specificity for a particular biomarker, indicating the current activity of the disease.

METHODS

A search strategy was created at Pubmed and Web of Science to answer the question: "How the molecular point-of-care tests currently available can help in the early detection of peri-implant diseases and throws light on improvements in point of care diagnostics devices?"

RESULTS

The PerioSafe® PRO DRS (dentognostics GmbH, Jena) and ImplantSafe® DR (dentognostics GmbH, Jena ORALyzer® test kits, already used clinically, can be a helpful adjunct tool in enhancing the diagnosis and prognosis of periodontal/peri-implantar diseases. With the advances of sensor technology, the biosensors can perform daily monitoring of dental implants or periodontal diseases, making contributions to personal healthcare and improve the current status quo of health management and human health.

CONCLUSIONS

Based on the findings, more emphasis is given to the role of biomarkers in diagnosing and monitoring periodontal and peri-implant diseases. By combining these strategies with traditional protocols, professionals could increase the accuracy of early detection of peri-implant and periodontal diseases, predicting disease progression, and monitoring of treatment outcomes.

Use of bioinformatic strategies as a predictive tool in implant-supported oral rehabilitation: A scoping review

STATEMENT OF PROBLEM

The use of bioinformatic strategies is growing in dental implant protocols. The current expansion of Omics sciences and artificial intelligence (AI) algorithms in implant dentistry applications have not been documented and analyzed as a predictive tool for the success of dental implants.

PURPOSE

The purpose of this scoping review was to analyze how artificial intelligence algorithms and Omics technologies are being applied in the field of oral implantology as a predictive tool for dental implant success.

MATERIAL AND METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist was followed. A search strategy was created at PubMed and Web of Science to answer the question "How is bioinformatics being applied in the area of oral implantology as a predictive tool for implant success?"

RESULTS

Thirteen articles were included in this review. Only 3 applied bioinformatic models combining AI algorithms and Omics technologies. These studies highlighted 2 key points for the creation of precision medicine: deep population phenotyping and the integration of Omics sciences in clinical protocols. Most of the studies identified applied AI only in the identification and classification of implant systems, quantification of peri-implant bone loss, and 3-dimensional bone analysis, planning implant placement.

CONCLUSIONS

The conventional criteria currently used as a technique for the diagnosis and monitoring of dental implants are insufficient and have low accuracy. Models that apply AI algorithms combined with precision methodologies-biomarkers-are extremely useful in the creation of precision medicine, allowing medical dentists to forecast the success of the implant. Tools that integrate the different types of data, including imaging, molecular, risk factor, and implant characteristics, are needed to make a more accurate and personalized prediction of implant success.

Potential Impact of Prosthetic Biomaterials on the Periodontium: A Comprehensive Review

The success of a prosthetic treatment is closely related to the periodontal health of the individual. The aim of this article was to review and present the importance of prosthetic restorative materials on the condition of the periodontium, the changes that occur in the composition of the subgingival microbiota and the levels of inflammatory markers in gingival crevicular fluid. Articles on the influence of different prosthetic restorative materials on subgingival microbiota and proinflammatory cytokines were searched for using the keywords "prosthetic biomaterials", "fixed prosthesis", "periodontal health", "subgingival microbiota", "periodontal biomarkers" and "gingival crevicular fluid" in PubMed/Medline, Science Direct, Scopus and Google Scholar. The type of material used for prosthesis fabrication together with poor marginal and internal fit can result in changes in the composition of the subgingival microbiota, as well as increased accumulation and retention of dentobacterial plaque, thus favoring the development of periodontal disease and prosthetic treatment failure. Biological markers have helped to understand the inflammatory response of different prosthetic materials on periodontal tissues with the main purpose of improving their clinical application in patients who need them. Metal-free ceramic prostheses induce a lower inflammatory response regardless of the fabrication method; however, the use of CAD/CAM systems is recommended for their fabrication. In addition, it is presumed that metal-ceramic prostheses cause changes in the composition of the subgingival microbiota producing a more dysbiotic biofilm with a higher prevalence of periodontopathogenic bacteria, which may further favor periodontal deterioration.

Next-Generation Examination, Diagnosis, and Personalized Medicine in Periodontal Disease

Periodontal disease, a major cause of tooth loss, is an infectious disease caused by bacteria with the additional aspect of being a noncommunicable disease closely related to lifestyle. Tissue destruction based on chronic inflammation is influenced by host and environmental factors. The treatment of periodontal disease varies according to the condition of each individual patient. Although guidelines provide standardized treatment, optimization is difficult because of the wide range of treatment options and variations in the ideas and skills of the treating practitioner. The new medical concepts of “precision medicine” and “personalized medicine” can provide more predictive treatment than conventional methods by stratifying patients in detail and prescribing treatment methods accordingly. This requires a new diagnostic system that integrates information on individual patient backgrounds (biomarkers, genetics, environment, and lifestyle) with conventional medical examination information. Currently, various biomarkers and other new examination indices are being investigated, and studies on periodontal disease-related genes and the complexity of oral bacteria are underway. This review discusses the possibilities and future challenges of precision periodontics and describes the new generation of laboratory methods and advanced periodontal disease treatment approaches as the basis for this new field.

Periodontitis, Metabolic and Gastrointestinal Tract Diseases: Current Perspectives on Possible Pathogenic Connections

Comprehensive research conducted over the past decades has shown that there is a definite connection between periodontal and systemic conditions, leading to the development and consolidation of the “periodontal medicine” concept. The 2018 classification of periodontal conditions uses this concept as a key element of the precise diagnosis of and individualized therapeutical protocols for periodontitis patients. The topic of this review is the pathogenic connections that exist between periodontal disease and metabolic/digestive tract conditions. It is important to remember that the oral cavity is a key element of the digestive tract and that any conditions affecting its integrity and function (such as periodontitis or oral cancer) can have a significant impact on the metabolic and gastrointestinal status of a patient. Thus, significant diseases with links to metabolic or digestive disruptions were chosen for inclusion in the review, such as diabetes mellitus, hepatic conditions and gastric cancers. Periodontal pathogenic mechanisms share several significant elements with these conditions, including mutual pro-inflammatory mediators, bacterial elements and genetic predisposition. Consequently, periodontal screening should be recommended for affected patients, and conversely, periodontitis patients should be considered for careful monitoring of their metabolic and digestive status.