The salivary microbiome as a diagnostic biomarker of periodontitis: a 16S multi-batch study before and after the removal of batch effects.

Introduction: Microbiome-based clinical applications that improve diagnosis related to oral health are of great interest to precision dentistry. Predictive studies on the salivary microbiome are scarce and of low methodological quality (low sample sizes, lack of biological heterogeneity, and absence of a validation process). None of them evaluates the impact of confounding factors as batch effects (BEs). This is the first 16S multi-batch study to analyze the salivary microbiome at the amplicon sequence variant (ASV) level in terms of differential abundance and machine learning models. This is done in periodontally healthy and periodontitis patients before and after removing BEs. Methods: Saliva was collected from 124 patients (50 healthy, 74 periodontitis) in our setting. Sequencing of the V3-V4 16S rRNA gene region was performed in Illumina MiSeq. In parallel, searches were conducted on four databases to identify previous Illumina V3-V4 sequencing studies on the salivary microbiome. Investigations that met predefined criteria were included in the analysis, and the own and external sequences were processed using the same bioinformatics protocol. The statistical analysis was performed in the R-Bioconductor environment. Results: The elimination of BEs reduced the number of ASVs with differential abundance between the groups by approximately one-third (Before=265; After=190). Before removing BEs, the model constructed using all study samples (796) comprised 16 ASVs (0.16%) and had an area under the curve (AUC) of 0.944, sensitivity of 90.73%, and specificity of 87.16%. The model built using two-thirds of the specimens (training=531) comprised 35 ASVs (0.36%) and had an AUC of 0.955, sensitivity of 86.54%, and specificity of 90.06% after being validated in the remaining one-third (test=265). After removing BEs, the models required more ASVs (all samples=200-2.03%; training=100-1.01%) to obtain slightly lower AUC (all=0.935; test=0.947), lower sensitivity (all=81.79%; test=78.85%), and similar specificity (all=91.51%; test=90.68%). Conclusions: The removal of BEs controls false positive ASVs in the differential abundance analysis. However, their elimination implies a significantly larger number of predictor taxa to achieve optimal performance, creating less robust classifiers. As all the provided models can accurately discriminate health from periodontitis, implying good/excellent sensitivities/specificities, the salivary microbiome demonstrates potential clinical applicability as a precision diagnostic tool for periodontitis.

Accuracy of salivary biomarkers in the diagnosis of periodontal status and coronary heart disease.

Inflammatory illnesses, such as periodontitis and atherosclerotic coronary heart disease (ASCHD), trigger the production of pro-inflammatory mediators. The aim of this study was to assess the accuracy of using salivary interleukin-1ß (IL-1ß), interleukin-18 (IL-18), and gasdermin D (GSDMD) in discerning patients with periodontitis with and without ASCHD from healthy individuals, and to assess their correlation with clinical periodontal parameters and low-density lipoprotein (LDL) levels. The study involved 120 participants: 30 were healthy subjects (control group, C), 30 had generalized periodontitis (group P), 30 had ASCHD and clinically healthy periodontium (group AS-C), and 30 had ASCHD and generalized periodontitis (group AS-P). Saliva and blood samples were collected, and periodontal characteristics such as plaque index, bleeding on probing, probing pocket depth, and clinical attachment loss were examined. IL-1ß, IL-18, and GSDMD levels from saliva were determined using ELISA. LDL levels were determined from the blood samples. Groups P, AS-C, and AS-P had higher levels of salivary IL-1ß, IL-18, and GSDMD than group C. The receiver operating characteristic (ROC) curves of all biomarkers showed high diagnostic accuracy, with a significant positive correlation with the clinical parameters and LDL levels. The observed correlations between the studied pro-inflammatory mediators and disease severity suggest that these biomarkers could serve as indicators of disease progression in conditions such as periodontitis and ASCHD.

Systematic review to evaluate accuracy studies of the diagnostic criteria for periodontitis in pregnant women.

The diversity of criteria used in the diagnosis of periodontitis in pregnant women makes it difficult to define and compare the disease. Using a systematic review, this study evaluated the accuracy of criteria for diagnosing periodontitis in pregnant women. Searches were carried out in the databases: Medline/PubMed, Embase, Scopus, Web of Science, SciELO, Lilacs, ProQuest, and CINAHL. Validation studies of the criteria used for diagnosing periodontitis met the inclusion criteria. The study steps were performed by three independent reviewers. A qualitative synthesis of the included articles was carried out and the quality methodological analysis using the QUADAS-2 instrument. The assessment of the quality of the evidence was obtained through the GRADE tool. A total of 592 records were identified, of which only 6 made up this systematic review. The included studies analyzed different criteria for diagnosing periodontitis, evaluating 3,005 pregnant women. The criteria selected as a test presented results equivalent to the performance of those recognized as the gold standard. The self-reported criteria were of lower diagnostic accuracy. A major limitation of this review was the small number of primary studies that evaluated clinical diagnosis of periodontitis in pregnant women, which was highly heterogeneous, making it impossible to carry out accuracy meta-analysis and additional analyzes. There is a lack of consensus on the criteria for the diagnosis of periodontitis, with great variability in the accuracy and prevalence of the disease in pregnant women.

Evaluation of oral health in 148 patients with systemic sclerosis-data from a prospective interdisciplinary monocentric cohort.

In daily rheumatology practice, systemic sclerosis is primarily regarded as a potentially life-threatening disease characterized by fibrosis of various organs. Therefore, other manifestations, such as orofacial involvement, are often not of primary concern. Furthermore, due to its rarity, the disease might not be well known by dentists, which contrasts with the increased risk of various problems in the oral cavity. Periodontitis in particular is a known risk factor for morbidity and mortality and is associated with various systemic diseases. The risk of periodontitis appears to be increased in patients with systemic sclerosis, but little is known about the gender-specific differences. This study aims to elucidate the health-conscious behaviour of patients, their dental care and the risk of periodontitis with regard to gender-specific differences. This descriptive study of the Interdisciplinary Centre of Rheumatic Diseases (INDIRA) in collaboration with the Department of Orthodontics at the University Hospital of Tuebingen, Germany, examined the data of 148 patients with systemic sclerosis with regard to their oral health using a questionnaire and evaluating the risk of periodontitis with the DG Paro self-assessment score in this cohort. Among the participating patients, 90% reported regular visits to the dentist and good dental care. Nevertheless, more than half of the patients had missing teeth and problems opening their mouths. Sicca symptoms in the oral cavity were also common (40%). The risk of periodontitis among female participants was high (around 60%), and even higher among male study participants (around 80%). Gingival bleeding as a surrogate parameter for periodontitis was associated with salivary flow and the modified Rodnan skin score (mRSS). Despite a high awareness of dental health, we observed a high risk of periodontitis, especially in male patients with systemic sclerosis. In addition, the association between xerostomia and missing teeth as well as gingival bleeding and mRSS may indicate an increased risk in patients with a more progressive disease. We would therefore recommend regular dental consultations and careful oral hygiene for patients with systemic sclerosis in addition to the-more organ-focused-regular examinations of patients.

The assessment of glutathione, glutathione peroxidase, glutathione reductase, and oxidized glutathione in patients with periodontitis-A systematic review and meta-analysis.

OBJECTIVE: The present systematic review explored the involvement of enzymatic and nonenzymatic antioxidants in periodontitis, drawing from established literature. MATERIALS AND METHODS: The research approach encompassed an extensive electronic search from 2000 to 2023 across databases such as PubMed, Science Direct, and Wiley Online Library and cross-referencing using specific keywords. RESULTS: The initial literature exploration generated a total of 766 articles. After thoroughly examining the abstracts, 693 articles were excluded from consideration due to duplication and lack of relevance to the central research inquiry. Following that, 73 articles were left for in-depth evaluation. Following a qualitative assessment, 35 studies that satisfied the inclusion criteria were chosen, while 38 were removed for not meeting the necessary standards. Within this selection, a meta-analysis was conducted on 11 articles that provided consistent data for quantitative synthesis. Specifically, the analysis of glutathione (GSH) levels in serum samples revealed a standardized mean difference (SMD) of -5.552 µg/mL (CI 95%: -9.078 to -2.026; P-0.002). In contrast, the analysis of glutathione peroxidase (GPx) enzymes in gingival crevicular fluid (GCF) samples displayed an overall SMD of 2.918 ng/µL (CI 95%: 0.372-5.465; P-0.025), while salivary samples exhibited an overall SMD value of 0.709 U/l (95% CI: -1.907-3.325; P-0.596) which is of insignificant. CONCLUSION: The systematic review findings suggest a notable decrease in antioxidant enzymes across various systemic biological samples among patients with periodontitis, contrasting with the results from gingival tissue samples meta-analysis of GPx enzyme.

Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics.

BACKGROUND: Since most of the commonly known oral diseases are explained in link with balance of microbial community, an accurate bacterial taxonomy profiling for determining bacterial compositional network is essential. However, compared to intestinal microbiome, research data pool related to oral microbiome is small, and general 16S rRNA screening method has a taxonomy misclassification issue in confirming complex bacterial composition at the species level. OBJECTIVE: Present study aimed to explore bacterial compositional networks at the species level within saliva of 39 oral disease patients (Dental Caries group: n = 26 and Periodontitis group: n = 13) through comparison with public Korean-specific healthy oral microbiome data. METHODS: Here, we applied comprehensive molecular diagnostics based on qRT-PCR and Sanger sequencing methods to complement the technical limitations of NGS-based 16S V3-V4 amplicon sequencing technology. RESULTS: As a result of microbiome profiling at the genus level, relative frequencies of many nitrate-reducing bacteria within each oral disease group were found to be significantly low compared to the healthy group. In addition, the molecular diagnostics-based bacterial identification method allowed the determination of the correct taxonomy of screened primary colonizers (Streptococcus and Actinomyces unclassification clusters) for each oral disease. Finally, as with the results of microbiome profiling at the genus level, many core-species classified within the saliva of each oral disease group were also related to nitrate-reduction, and it was estimated that various pathogens associated with each disease formed a bacterial network with the core-species. CONCLUSION: Our study introduced a novel approach that can compensate for the difficulty of identifying an accurate bacterial compositional network at the species level due to unclear taxonomy classification by using the convergent approach of NGS-molecular diagnostics. Ultimately, we suggest that our experimental approach and results could be potential reference materials for researchers who intend to prevent oral disease by determining the correlation between oral health and bacterial compositional network according to the changes in the relative frequency for nitrate-reducing species.

Combined assessment of lysine and N-acetyl cadaverine levels assist as a potential biomarker of the smoker periodontitis.

Periodontitis is an inflammatory condition of supporting structures of teeth leading to attachment and bone loss. Cigarette smoking is the single most important and modifiable risk factor with 5 to 20-fold susceptibility for periodontal diseases. Reverse smoking is a peculiar habit of smoking where the lit end is kept inside the mouth, which is predominant in the northern coastal districts of Andhra Pradesh. Polyamines are biologically active amines involved in tissue regeneration and modulation of inflammation. The study aimed to evaluate polyamines and check their utility as a marker in detection of periodontitis among different groups. Total polyamine levels showed significant increase in reverse smokers with periodontitis when compared to the other groups. Qualitative analysis by thin layer chromatography showed three polyamine bands with varying intensity among the different groups. Mass spectrometric and NMR analyses of the three bands identified them as N1, N8-diacetyl spermidine, N-acetyl cadaverine and lysine. Most significantly elevated levels of lysine was observed in the smoker and reverse smoker periodontitis groups when compared to healthy and non-smoker periodontitis groups. The significantly elevated levels of N-acetyl cadaverine could be responsible for the more destruction of periodontium in the reverse smoker group. Antioxidant potential decreased significantly in different smoker periodontitis groups. The present study suggests that the quantitative analysis of salivary polyamines, lysine and N-acetyl cadaverine can aid as an easy noninvasive diagnostic method for assessing the periodontal status, especially in smokers.

Diagnostic accuracy of salivary active matrix metalloproteinase (aMMP)-8 point-of-care test for detecting periodontitis in adults: A systematic review and meta-analysis.

OBJECTIVE: To determine the accuracy of salivary active matrix metalloproteinase (aMMP)-8 point-of-care test (POCT) for detecting periodontitis in adults, through meta-analysis. MATERIALS AND METHODS: Diagnostic studies evaluating the accuracy of salivary/oral rinse aMMP-8 POCT for detecting periodontitis in adults, when compared with clinical examination, were considered eligible. A comprehensive search was performed up to 31 August 2023 through five databases. Quality Assessment of Diagnostic Accuracy Studies 2 was utilized to evaluate the methodological quality of the included articles. Meta-analysis was performed using Bayesian bivariate hierarchical model and subgroup analysis. RESULTS: From 368 screened studies, 6 studies (4 cross-sectional and 2 longitudinal studies) were included in the meta-analysis. Overall, the pooled sensitivity and specificity of salivary aMMP-8-POCT for detecting periodontitis were 0.63 (95% CI: 0.41-0.82) and 0.84 (95% CI: 0.65-0.95), respectively. Subgroup analyses revealed that the 95% CI for oral fluid types, predefined diagnostic thresholds and the POCT systems largely overlapped, indicating that the differences between them may not be significant. CONCLUSION: Salivary aMMP-8 POCT shows fair accuracy for detecting periodontitis. The diagnostic accuracy cannot be significantly influenced by the types of oral fluids, predefined diagnostic thresholds or the specific POCT systems used. More research is needed to confirm the clinical utility and implementation of aMMP-8 POCT in the diagnosis of periodontitis.

Development of a nomogram for identifying periodontitis cases in Denmark.

Although self-reported health outcomes are of importance, attempts to validate a clinical applicable instrument (e.g., nomogram) combining sociodemographic and self-reported information on periodontitis have yet to be performed to identify periodontitis cases. Clinical and self-reported periodontitis, along with sociodemographic data, were collected from 197 adults. Akaike information criterion models were developed to identify periodontitis, and nomograms developed based on its regression coefficients. The discriminatory capability was evaluated by receiver-operating characteristic curves. Decision curve analysis was performed. Smoking [OR 3.69 (95%CI 1.89, 7.21)], poor/fair self-rated oral health [OR 6.62 (95%CI 3.23, 13.56)], previous periodontal treatment [OR 9.47 (95%CI 4.02, 22.25)], and tooth loss [OR 4.96 (95%CI 2.47, 9.97)], determined higher probability of having "Moderate/Severe Periodontitis". Age [OR 1.08 (95%CI 1.05, 1.12)], low educational level [OR 1.65 (95%CI 1.34, 2.23)], poor/fair self-rated oral health [OR 3.57 (95%CI 1.82, 6.99)], and previous periodontal treatment [OR 6.66 (95%CI 2.83, 15.68)] determined higher probability for "Any Periodontitis". Both nomograms showed excellent discriminatory capability (AUC of 0.83 (95%CI 0.75, 0.91) and 0.81 (95% CI 0.74, 0.88), good calibration, and slight overestimation of high risk and underestimation of low risk. Hence, our nomograms could help identify periodontitis among adults in Denmark.

Real-Time PCR Method as Diagnostic Tool for Detection of Periodontal Pathogens in Patients with Periodontitis.

The most common type of periodontal disease is chronic periodontitis, an inflammatory condition caused by pathogenic bacteria in subgingival plaque. The aim of our study was the development of a real-time PCR test as a diagnostic tool for the detection and differentiation of five periodontopathogenic bacteria, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Prevotella intermedia, and Treponema denticola, in patients with periodontitis. We compared the results of our in-house method with the micro-IDent® semiquantitative commercially available test based on the PCR hybridization method. DNA was isolated from subgingival plaque samples taken from 50 patients and then analyzed by both methods. Comparing the results of the two methods, they show a specificity of 100% for all bacteria. The sensitivity for A. actinomycetemcomitans was 97.5%, for P. gingivalis 96.88%, and for P. intermedia 95.24%. The sensitivity for Tannerella forsythia and T. denticola was 100%. The Spearman correlation factor of two different measurements was 0.976 for A. actinomycetemcomitans, 0.967 for P. gingivalis, 0.949 for P. intermedia, 0.966 for Tannerella forsythia, and 0.917 for T. denticola. In conclusion, the in-house real-time PCR method developed in our laboratory can provide information about relative amount of five bacterial species present in subgingival plaque in patients with periodontitis. It is likely that such a test could be used in dental diagnostics in assessing the efficacy of any treatment to reduce the bacterial burden.

Bioinformatics investigation of adaptive immune-related genes in peri-implantitis and periodontitis: Characteristics and diagnostic values.

BACKGROUND: Peri-implantitis and periodontitis have similar immunological bioprocesses and inflammatory phenotypes. In the inflammatory process, the adaptive immune cells can drive the development of disease. This research investigated the differences and diagnostic significance of peri-implantitis and periodontitis in adaptive immune responses. METHODS: We acquired four GEO datasets of gene expressions in surrounding tissues in healthy person, healthy implant, periodontitis, and peri-implantitis patients. The structural characteristics and enrichment analyses of differential expression genes were examined. The adaptive immune landscapes in peri-implantitis and periodontitis were then evaluated using single sample gene set enrichment analysis. The STRING database and Cytoscape were used to identify adaptive hub genes, and the ROC curve was used to verify them. Finally, qRT-PCR method was used to verify the expression level of Hub gene in activated T cells on the titanium-containing or titanium-free culture plates. RESULTS: At the transcriptome level, the data of healthy implant, peri-implantitis and periodontitis were highly dissimilar. The peri-implantitis and periodontitis both exhibited adaptive immune response. Except for the activated CD4+T cells, there was no significant difference in other adaptive immune cells between peri-implantitis and periodontitis. In addition, correlation analysis showed that CD53, CYBB, and PLEK were significantly positively linked with activated CD4+T cells in the immune microenvironment of peri-implantitis, making them effective biomarkers to differentiate it from periodontitis. CONCLUSIONS: Peri-implantitis has a uniquely immunogenomic landscape that differs from periodontitis. This study provides new insights and ideas into the activated CD4+T cells and hub genes that underpin the immunological bioprocess of peri-implantitis.

Infrared spectroscopy for fast screening of diabetes and periodontitis.

SIGNIFICANCE: FT-IR is an important and emerging tool, providing information related to the biochemical composition of biofluids. It is important to demonstrate that there is an efficacy in separating healthy and diseased groups, helping to establish FT-IR uses as fast screening tool. AIM: Via saliva diagnosis evaluate the accuracy of FT-IR associate with machine learning model for classification among healthy (control group), diabetic (D) and periodontitis (P) patients and the association of both diseases (DP). APPROACH: Eighty patients diagnosed with diabetes and periodontitis through conventional methods were recruited and allocated in one of the four groups. Saliva samples were collected from participants of each group (n = 20) and were processed using Bruker Alpha II spectrometer in a FT-IR spectral fingerprint region between 600 and-1800 cm-1, followed by data preprocessing and analysis using machine learning tools. RESULTS: Various FTI-R peaks were detectable and attributed to specific vibrational modes, which were classified based on confusion matrices showed in paired groups. The highest true positive rates (TPR) appeared between groups C vs D (93.5 % ± 2.7 %), groups C vs. DP (89.2 % ± 4.1 %), and groups D and P (90.4 % ± 3.2 %). However, P vs DP presented higher TPR for DP (84.1 % ±3.1 %) while D vs. DP the highest rate for DP was 81.7 % ± 4.3 %. Analyzing all groups together, the TPR decreased. CONCLUSION: The system used is portable and robust and can be widely used in clinical environments and hospitals as a new diagnostic technique. Studies in our groups are being conducted to solidify and expand data analysis methods with friendly language for healthcare professionals. It was possible to classify healthy patients in a range of 78-93 % of accuracy. Range over 80 % of accuracy between periodontitis and diabetes were observed. A general classification model with lower TPR instead of a pairwise classification would only have advantages in scenarios where no prior patient information is available regarding diabetes and periodontitis status.

Non-invasive assessment of periodontal inflammation by continuum-removal hemodynamic spectral indices.

BACKGROUND: Hyperspectral techniques have aroused great interest in non-invasively measuring periodontal tissue hemodynamics. However, current studies mainly focused on three typical inflammation stages (healthy, gingivitis and periodontitis) and practical approaches for using optical spectroscopy for early and precisely detection of periodontal inflammation at finer disease stages have not been well studied. METHODS: This study provided novel spectroscopic insights into periodontitis at different stages of disease, and developed six simple but physically meaning hemodynamic spectral indices (HSIs) including four spectral absorption depths of oxyhemoglobin ( D HbO 2 ), deoxyhemoglobin ( D Hb ), total hemoglobin ( t Hb ) and tissue water ( D water ), and two normalized difference indices of oxyhemoglobin( N D HbO 2 I ) and deoxyhemoglobin ( N D Hb I ) from continuum-removal spectra (400-1700 nm) of periodontal tissue collected from 47 systemically healthy subjects over different severities from healthy, gingivitis, slight, moderate to severe periodontitis for early and precision diagnostics of periodontitis. Typical statistical analyses were conducted to explore the effectiveness of the proposed HSIs. RESULTS: D Hb and t Hb exerted significant increasing trends as inflammation progressed, whereas D HbO 2 exhibited significant difference (P < 0.05) from the healthy sites only at moderate and severe periodontitis and D water presented unstable sensitives to disease severity. By contrast, N D HbO 2 I and N D Hb I showed more steadily downward trends as severity increased, and demonstrated the highest correlations with clinical gold standard parameters. Particularly, the proposed normalized HSIs ( N D HbO 2 I and N D Hb I ) yielded high correlations of - 0.49 and - 0.44 with probing depth, respectively, far outperforming results achieved by previous studies. The performances of the HSIs were also confirmed using the periodontal therapy group. CONCLUSIONS: These results indicated great potentials of combination optical spectroscopy and smart devices to non-invasively probe periodontitis at earlier stages using the simple and practical HSIs. Trial registration This study was retrospectively registered in the Chinese Clinical Trial Registry on October 24, 2021, and the clinical registration number is ChiCTR2100052306.

[Oral diseases and dementia]. / Möjliga samband mellan orala sjukdomar och demens.

The aging population makes the increase in cognitive disorders a challenge. One of the risk factors is old age, but also oral diseases, especially periodontitis, have been linked to an increased risk of dementia, especially Alzheimer's disease (AD), although research studies show varying correlations. Dental care utilization also decreases after a dementia diagnosis. The periodontal diseases are inflammatory disorders and common in the adult population. Periodontitis leads to loss of the supporting tissue of the tooth and, if untreated, to loss of teeth. Inflammation also plays a role in AD, the most common form of dementia. The reason for an association could be that periodontitis may lead to a spread of pro-inflammatory mediators and oral microorganisms to the brain. Another explanation suggests that chewing may stimulate nerve impulses and increase the blood flow to the brain. Fewer teeth could lead to less stimulation and reduced blood flow. In conclusion, oral diseases and dementia appear to be associated. Whether this connection constitutes a causal connection is more uncertain.

Screening and characterization of aptamers recognizing the periodontal pathogen Tannerella forsythia.

Periodontal disease is one of the most common forms of inflammation. It is currently diagnosed by observing symptoms such as gingival bleeding and attachment loss. However, the detection of biomarkers that precede such symptoms would allow earlier diagnosis and prevention. Aptamers are short oligonucleotides or peptides that fold into three-dimensional conformations conferring the ability to bind molecular targets with high affinity and specificity. Here we report the selection of aptamers that bind specifically to the bacterium Tannerella forsythia, a pathogen frequently associated with periodontal disease. Two aptamers with the highest affinity were examined in more detail, revealing that their binding is probably dependent on mirolysin, a surface-associated protease secreted by the T. forsythia type-9 secretion system. The aptamers showed minimal cross-reactivity to other periodontopathogens and are therefore promising leads for the development of new tools to study the composition of the periodontitis-associated dysbiotic bacteriome as well as inexpensive new diagnostic assays.

Comparative Study on the Periodontal Parameters Used in Diagnosing Periodontitis in Puerperae and Periodontitis' Relationship with the Birth of Preterm Infants: A Case-Control Study.

To compare different criteria for the diagnosis of periodontitis and to evaluate the association of this condition with prematurity, this case-control study was conducted on 283 mothers of infants, divided into two groups based on gestational age (cases: <37 weeks, controls: ≥37 weeks), with 71 cases and 212 controls. The periodontal evaluation included probing depth (PD), clinical attachment level (CAL), plaque index, and bleeding on probing (BOP). Participants were classified regarding periodontitis per 14 criteria based on different periodontal parameters. The criterion selected as the gold standard was the presence of at least four teeth with one or more sites with a PD ≥ 4 mm, CAL ≥ 3 mm, and BOP at the same site. The prevalence of periodontal disease ranged from 8.1% to 55.1%. Moreover, compared to the gold standard, the sensitivities of the other criteria were 100%, while specificity ranged from 50.4% to 96.4%. Periodontitis, defined by six of the selected criteria, was associated with prematurity after multivariate adjustment, with OR ranging from 1.85 to 2.69 and 95% CI from 1.01 to 5.56; one of them was the gold standard mentioned above. Measurements using the clinical parameters of PD, CAL, and bleeding at the same site (criteria 5, 6, 7, 8), CPI (criterion 10), and at least four teeth with a PD ≥ 4 mm and CAL ≥ 3 mm (criterion 11) to define periodontitis showed a statistically significant association (p < 0.05). Given this study's limitations, we can conclude that the diagnostic criteria for a periodontitis definition using a PD ≥ 4 mm and CAL ≥ 3 mm in two or more teeth, with BOP at the same site, seem stronger when detecting an association between periodontitis and prematurity.

Investigation of periodontitis, halitosis, xerostomia, and serological characteristics of patients with osteoarthritis and rheumatoid arthritis and identification of new biomarkers.

Rheumatoid arthritis (RA) and osteoarthritis (OA) are two different types of arthritis. Within RA, the subsets between seronegative RA (snRA) and seropositive RA (spRA) represent distinct disease entities; however, identifying clear distinguishing markers between them remains a challenge. This study investigated and compared the oral health conditions in patients with RA and OA to clarify the differences from healthy controls. In addition, we investigated the serological characteristics of the patients, the factors that distinguished patients with RA from those with OA, and the main factors that differentiated between snRA and spRA patients. A total of 161 participants (mean age: 52.52 ± 14.57 years, 32 males and 129 females) were enrolled in this study and categorized as: normal (n = 33), OA (n = 31), and RA (n = 97). Patients with RA were divided into the following two subtypes: snRA (n = 18) and spRA (n = 79). Demographics, oral health, and serological characteristics of these patients were compared. The prevalence of periodontal diseases was significantly higher in patients with OA (100%) and RA (92.8%) than in healthy controls (0.0%). However, the presence of periodontal diseases was not utilized as a distinguishing factor between OA and RA. Xerostomia occurred more frequently in patients with RA (84.5%) than in patients with OA (3.2%) and healthy controls (0.0%) (all p < 0.001). ROC analysis revealed that periodontal disease was a very strong predictor in the diagnosis of OA compared to healthy controls, with an AUC value of 1.00 (p < 0.001). Additionally, halitosis (AUC = 0.746, 95% CI 0.621-0.871, p < 0.001) and female sex (AUC = 0.663, 95% CI 0.529-0.797, p < 0.05) were also significant predictors of OA. The strongest predictors of RA diagnosis compared to healthy controls were periodontal diseases (AUC = 0.964), followed by xerostomia (AUC = 0.923), age (AUC = 0.923), female sex (AUC = 0.660), and halitosis (AUC = 0.615) (all p < 0.05). Significant serological predictors of RA were anti-CCP Ab (AUC = 0.808), and RF (AUC = 0.746) (all p < 0.05). In multiple logistic regression analysis, xerostomia (odds ratio, OR: 8124.88, 95% CI 10.37-6368261.97, p-value = 0.008) and Anti-CCP Ab (OR: 671.33, 95% CI 2.18-207,074.02, p = 0.026) were significant predictors for RA compared to OA. When diagnosing spRA compared to snRA, anti-CCP Ab (AUC = 1.000, p < 0.001) and RF (AUC = 0.910, 95%CI 0.854-0.967, p < 0.001) had outstanding predictive performances. Therefore, clinicians and researchers should thoroughly evaluate the oral status of both OA and RA patients, alongside serological factors, and consider these elements as potential predictors.

Identification of potential diagnostic biomarkers associated with periodontitis by comprehensive bioinformatics analysis.

Periodontitis is a chronic inflammatory disease that affects the tissues surrounding the teeth, including the gums and the bones supporting the teeth. Early detection and intervention are crucial for effective management of periodontitis. Our study aims to identify a diagnostic biomarker for periodontitis and explore the pathways associated with the occurrence and development of periodontitis. The expression of gingival tissue from periodontitis and healthy control were downloaded from the Gene Expression Omnibus. The weighted gene co-expression network analysis (WGCNA) were used to analyze module genes associated with periodontitis and DESeq2 were performed to identify differently expressed genes (DEGs) between periodontitis and healthy control. Then the candidate genes were obtained by intersecting the genes from interest modules and DEGs. Functional enrichment analysis was performed using gene ontology and kyoto encyclopedia of gene and genomes, followed by the protein-protein interaction (PPI) network analysis. The hub genes were identified by the cytoCNA plugin in Cytoscape. Finally, immunohistochemical staining of the hub genes was performed to validate the findings. WGCNA analysis found that the expression of the MEblack module was significantly higher in individuals with periodontitis compared to those in the healthy control group. A total of 888 DEGs, including 750 upregulated and 138 downregulated genes, were identified. Finally, 427 candidate genes were identified potentially associated with periodontitis after intersecting the DEGs and the black module genes. Several critical signaling pathways were identified associated with periodontitis by functional enrichment analysis, including cytokine-cytokine receptor interaction, neutrophil extracellular trap formation, Staphylococcus aureus infection, and Interleukin-17 signaling pathway. The PPI network analysis revealed that C-X-C motif chemokine ligand 5 (CXCL5) and C-X-C motif chemokine ligand 6 (CXCL6) could play an important role in the process of periodontitis. The gene expression level of CXCL5 and CXCL6 detected using immunohistochemical verified the findings. In conclusion, we found that CXCL5 and CXCL6 are closely associated with the occurrence of periodontitis. Our present pilot study suggests that CXCL5 and CXCL6 have the potential to be used as a diagnostic biomarker of periodontitis.

Feasibility of Utilizing Electronic Dental Record Data and Periodontitis Case Definition to Automate Diagnosis.

Periodontitis is an irreversible disease leading to tooth loss, and 42% U.S. population suffers from periodontitis. Hence, diagnosing, monitoring, and determining its prevalence is critical to develop preventive strategies. However, a nationwide epidemiological study estimating the prevalence reported a concern about the discontinuation of such studies due to cost and ethical reasons. Therefore, this study determined the feasibility of utilizing electronic dental record (EDR) data and periodontitis case definition to automate periodontitis diagnosis. We utilized EDR data from the Indiana University School of Dentistry of 28,908 unique patients. We developed and tested a computer algorithm to diagnose periodontitis using the case definition. We found 44%, 22%, and 1% of patients with moderate, severe, and mild periodontitis, respectively. The algorithm worked with 100% sensitivity, specificity, and accuracy because of the excellent quality of the EDR data. We concluded the feasibility of providing automated periodontitis diagnosis from EDR data to conduct epidemiological studies across the US.

Multiple Imputation for Partial Recording Periodontal Examination Protocols.

AIM: Partial-mouth recording protocols often result in underestimation of population prevalence and extent of periodontitis. We posit that multiple imputation of measures such as clinical attachment loss for nonselected tooth sites in partial-mouth samples can reduce bias in periodontitis estimates. METHODS: Multiple imputation for correlated site-level dichotomous outcomes in a generalized estimating equations framework is used to impute site-level binary indicators for clinical attachment loss exceeding a fixed threshold in partial-mouth samples. Periodontitis case definitions are applied to the imputed "complete" dentitions, enabling estimation of prevalence and other summaries of periodontitis for partial-mouth samples as if for full-mouth examinations. A multiple imputation-bootstrap procedure is described and applied for point and variance estimation of these periodontitis measures. The procedure is evaluated with pseudo-partial-mouth samples based on random site selection protocols of 28 to 84 periodontal sites repeatedly generated from full-mouth periodontal examinations of 3,621 participants in the 2013 to 2014 National Health and Nutrition Examination Survey (NHANES) survey. RESULTS: Multiple imputation applied to partial-mouth samples overestimated periodontitis mean extent, defined as the number of sites with clinical attachment loss 3 mm or greater, by 9.5% in random site selection protocols with 84 sites and overestimated prevalence by 5% to 10% in all the evaluated protocols. CONCLUSIONS: In the 2013 to 2014 NHANES data, multiple imputation of site-level periodontal indicators provides less biased estimates of periodontitis prevalence and extent than has been reported from estimates based on the direct application of full-mouth case definitions to partial-mouth samples. Multiple imputation provides a promising solution to the longstanding, vexing problem of estimation bias in partial-mouth recording, with potential application to a wide array of case definitions, periodontitis measures, and partial recording protocols. KNOWLEDGE TRANSFER STATEMENT: Partial-mouth sampling, while a resource-efficient strategy for obtaining oral disease estimates, often results in underestimation of periodontitis metrics. Multiple imputation for nonselected periodontal sites produces pseudo-full-mouth data sets that may be analyzed and combined to produce estimates with small bias.