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In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P3 ) system.

ABSTRACT: BACKGROUND:This paper focuses on Periodontal Profile Class (PPC), a component of the Periodontal Profile Phenotype (P3 ) System that may be more representative of the periodontitis phenotype than current case definitions of periodontitis. Data illustrate the unique aspects of the PPC compared with other commonly used periodontal classification indices. METHODS:Latent Class Analysis (LCA) identified discrete classes of individuals grouped by tooth-level clinical parameters. The analysis defined seven distinct periodontal profile classes (PPC A through G) and seven distinct tooth profile classes (TPC A through G). This LCA classification was an entirely data-derived agnostic process without any preconceived presumptions of what constituted disease. RESULTS:Comparing the PPC with the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) and European indices, the PPC is unique in that it contains four disease classes not traditionally used. Less than half of individuals classified as Healthy by both the CDC/AAP and European indices were Healthy using the PPC. About 25% of those classified as Severe by CDC/AAP and European indices were PPC-Severe. The remainder spread out over the High Gingival Index, Posterior Disease, Tooth Loss, and Severe Tooth Loss phenotypes. CONCLUSIONS:The PPC classification provides a significant departure from the traditional clinical case status indices that have been used, but has resulted in clinical phenotypes that are quite familiar to most clinicians who take notice of the distribution of missing teeth, areas of recession, diminished periodontal support, and other aspects of the dentition while conducting a periodontal examination. The mutually exclusive categories provided by the PPC system provide periodontal clinical summaries that can be an important component of precision dentistry.

SUBMITTER: Beck JD

PROVIDER: S-EPMC6125155 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P<sup>3</sup> ) system.

Beck James D JD Moss Kevin L KL Morelli Thiago T Offenbacher Steven S

Journal of periodontology 20180222 2

<h4>Background</h4>This paper focuses on Periodontal Profile Class (PPC), a component of the Periodontal Profile Phenotype (P<sup>3</sup> ) System that may be more representative of the periodontitis phenotype than current case definitions of periodontitis. Data illustrate the unique aspects of the PPC compared with other commonly used periodontal classification indices.<h4>Methods</h4>Latent Class Analysis (LCA) identified discrete classes of individuals grouped by tooth-level clinical paramete ...[more]

PMID: 29520827

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Project description:BACKGROUND:Current periodontal disease taxonomies have limited utility for predicting disease progression and tooth loss; in fact, tooth loss itself can undermine precise person-level periodontal disease classifications. To overcome this limitation, the current group recently introduced a novel patient stratification system using latent class analyses of clinical parameters, including patterns of missing teeth. This investigation sought to determine the clinical utility of the Periodontal Profile Classes and Tooth Profile Classes (PPC/TPC) taxonomy for risk assessment, specifically for predicting periodontal disease progression and incident tooth loss. METHODS:The analytic sample comprised 4,682 adult participants of two prospective cohort studies (Dental Atherosclerosis Risk in Communities Study and Piedmont Dental Study) with information on periodontal disease progression and incident tooth loss. The PPC/TPC taxonomy includes seven distinct PPCs (person-level disease pattern and severity) and seven TPCs (tooth-level disease). Logistic regression modeling was used to estimate relative risks (RR) and 95% confidence intervals (CI) for the association of these latent classes with disease progression and incident tooth loss, adjusting for examination center, race, sex, age, diabetes, and smoking. To obtain personalized outcome propensities, risk estimates associated with each participant's PPC and TPC were combined into person-level composite risk scores (Index of Periodontal Risk [IPR]). RESULTS:Individuals in two PPCs (PPC-G: Severe Disease and PPC-D: Tooth Loss) had the highest tooth loss risk (RR = 3.6; 95% CI = 2.6 to 5.0 and RR = 3.8; 95% CI = 2.9 to 5.1, respectively). PPC-G also had the highest risk for periodontitis progression (RR = 5.7; 95% CI = 2.2 to 14.7). Personalized IPR scores were positively associated with both periodontitis progression and tooth loss. CONCLUSIONS:These findings, upon additional validation, suggest that the periodontal/tooth profile classes and the derived personalized propensity scores provide clinical periodontal definitions that reflect disease patterns in the population and offer a useful system for patient stratification that is predictive for disease progression and tooth loss.

Project description:Introduction The basis of orthodontic tooth movement (OTM) is the reconstruction of periodontal tissue under stress. Increasing the speed of OTM has always been the focus of attention. Objectives Periodontal ligament stem cells (PDLSCs) are direct effector cells of mechanical force, but the mechanism by which PDLSCs sense mechanical stimuli is unclear. Methods Human PDLSCs (hPDLSCs) were analyzed in the presence or absence of force loading with the Flexcell loading system in vitro. Then, periodontal tissues were analyzed after mechanical stimulation in vivo. In addition, cells in a confined microenvironment were analyzed to observe changes in the cytoskeleton and migration. Finally, TRPC6−/− mice were used to further verify the effect of TRPC6. After force application, the OTM distance, bone marrow density (BMD), TRPC6 and COL1 expression, and TRAP staining were evaluated in periodontal tissues. Results RNA sequencing (RNA-seq) and western blot analyses revealed that TRPC6 was important during mechanical force application to hPDLSCs. Appropriate mechanical force application also induced TRPC6 activation in the OTM model and the confined microenvironment. Under a slightly confined microenvironment, treatment with the TRPC6 inhibitor SKF96365 and TRPC6 knockout decreased the migration speed of hPDLSCs and mouse bone marrow mesenchymal stem cells (mBMSCs). In addition, TRPC6−/− mice showed lower OTM distances and reduced osteogenic and osteoclastic differentiation. Conclusion In summary, TRPC6 activation in PDLSCs mediated by appropriate mechanical force application contributes to periodontal tissue reconstruction. Graphical abstract PDLSCs modulate periodontal tissue remodeling under appropriate mechanical stimulation through TRPC6; however, under excessive stress, alveolar bone and tooth roots are readily absorbed. Under this condition, environmental factors play a leading role, and the regulatory effect of TRPC6 is not obvious. Supplementary Information The online version contains supplementary material available at 10.1186/s13287-022-03055-z.

Dataset Information

In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P3 ) system.

Publications

In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P<sup>3</sup> ) system.

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