Accuracy of periodontitis diagnosis obtained using multiple molecular biomarkers in oral fluids: A systematic review and meta‐analysis

Aim To determine the accuracy of biomarker combinations in gingival crevicular fluid (GCF) and saliva through meta-analysis to diagnose periodontitis in systemically healthy subjects. Methods Studies on combining two or more biomarkers providing a binary classification table, sensitivity/specificity values or group sizes in subjects diagnosed with periodontitis were included. The search was performed in August 2022 through PUBMED, EMBASE, Cochrane, LILACS, SCOPUS and Web of Science. The methodological quality of the articles selected was evaluated using the QUADAS-2 checklist. Hierarchical summary receiver operating characteristic modelling was employed to perform the meta-analyses (CRD42020175021). Results Twenty-one combinations in GCF and 47 in saliva were evaluated. Meta-analyses were possible for six salivary combinations (median sensitivity/specificity values): IL-6 with MMP-8 (86.2%/80.5%); IL-1β with IL-6 (83.0%/83.7%); IL-1β with MMP-8 (82.7%/80.8%); MIP-1α with MMP-8 (71.0%/75.6%); IL-1β, IL-6 and MMP-8 (81.8%/84.3%); and IL-1β, IL-6, MIP-1α and MMP-8 (76.6%/79.7%). Conclusions Two-biomarker combinations in oral fluids show high diagnostic accuracy for periodontitis, which is not substantially improved by incorporating more biomarkers. In saliva, the dual combinations of IL-1β, IL-6 and MMP-8 have an excellent ability to detect periodontitis and a good capacity to detect non-periodontitis. Because of the limited number of biomarker combinations evaluated, further research is required to corroborate these observationsThis study was funded by the Instituto de Salud Carlos III (ISCIII) through the project PI21/00588 and co-funded by the European UnionS

Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models

The present study used 16S rRNA gene amplicon sequencing to assess the impact on salivary microbiome of different grades of dental and periodontal disease and the combination of both (hereinafter referred to as oral disease), in terms of bacterial diversity, co-occurrence network patterns and predictive models. Our scale of overall oral health was used to produce a convenience sample of 81 patients from 270 who were initially recruited. Saliva samples were collected from each participant. Sequencing was performed in Illumina MiSeq with 2 × 300 bp reads, while the raw reads were processed according to the Mothur pipeline. The statistical analysis of the 16S rDNA sequencing data at the species level was conducted using the phyloseq, DESeq2, Microbiome, SpiecEasi, igraph, MixOmics packages. The simultaneous presence of dental and periodontal pathology has a potentiating effect on the richness and diversity of the salivary microbiota. The structure of the bacterial community in oral health differs from that present in dental, periodontal or oral disease, especially in high grades. Supragingival dental parameters influence the microbiota’s abundance more than subgingival periodontal parameters, with the former making a greater contribution to the impact that oral health has on the salivary microbiome. The possible keystone OTUs are different in the oral health and disease, and even these vary between dental and periodontal disease: half of them belongs to the core microbiome and are independent of the abundance parameters. The salivary microbiome, involving a considerable number of OTUs, shows an excellent discriminatory potential for distinguishing different grades of dental, periodontal or oral disease; considering the number of predictive OTUs, the best model is that which predicts the combined dental and periodontal statusThis investigation was supported by the Instituto de Salud Carlos III (General Division of Evaluation and Research Promotion, Madrid, Spain) and co-financed by FEDER (“A way of making Europe”) under grant ISCIII/PI17/01722, and the CESPU under grants MVOS2016 and MVOS-PT-IINFACTS-2019S

Accuracy of single molecular biomarkers in gingival crevicular fluid for the diagnosis of periodontitis: A systematic review and meta-analysis

This is the peer reviewed version of the following article: Arias‐Bujanda, N, Regueira‐Iglesias, A, Balsa‐Castro, C, Nibali, L, Donos, N, Tomás, I. Accuracy of single molecular biomarkers in gingival crevicular fluid for the diagnosis of periodontitis: A systematic review and meta‐analysis. J Clin Periodontol. 2019; 46: 1166– 1182. https://doi.org/10.1111/jcpe.13188, which has been published in final form at https://doi.org/10.1111/jcpe.13188. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsAbstract Aim To analyse, by means of a meta‐analytical approach, the diagnostic accuracy of molecular biomarkers in gingival crevicular fluid (GCF) for the detection of periodontitis in systemically healthy subjects. Material and Methods Studies on GCF molecular biomarkers providing a binary classification table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. The search was performed using six electronic databases. The methodological quality of studies was assessed through the tool Quality Assessment of Diagnostic Studies. Meta‐analyses were performed using the Hierarchical Summary Receiver Operating Characteristic, which adjusts classification data using random effects logistic regression. Results The included papers identified 36 potential biomarkers for the detection of periodontitis and for four of them meta‐analyses were performed. The median sensitivity and specificity were for MMP8, 76.7% and 92.0%; for elastase, 74.6% and 81.1%; for cathepsin, 72.8% and 67.3%, respectively. The worst estimates of sensitivity and specificity were for trypsin (71.3% and 66.1%, respectively). Conclusions MMP8 showed good sensitivity and excellent specificity, which resulted in this biomarker being clinically the most useful or effective for the diagnosis of periodontitis in systemically healthy subjects, regardless of smoking conditionInstituto de Salud Carlos III FEDER. Grant Number: ISCIII/PI17/01722 Consellería de Cultura, Educación e Ordenación Universitaria da Xunta de Galicia. Grant Numbers: ED431B 2017/029, ED481A‐201

Cross-disease Meta-analysis of Genome-wide Association Studies for Systemic Sclerosis and Rheumatoid Arthritis Reveals IRF4 as a New Common Susceptibility Locus

Objectives: Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that share clinical and immunological characteristics. To date, several shared SSc- RA loci have been identified independently. In this study, we aimed to systematically search for new common SSc-RA loci through an inter-disease meta-GWAS strategy. Methods: We performed a meta-analysis combining GWAS datasets of SSc and RA using a strategy that allowed identification of loci with both same-direction and opposingdirection allelic effects. The top single-nucleotide polymorphisms (SNPs) were followed-up in independent SSc and RA case-control cohorts. This allowed us to increase the sample size to a total of 8,830 SSc patients, 16,870 RA patients and 43,393 controls. Results: The cross-disease meta-analysis of the GWAS datasets identified several loci with nominal association signals (P-value < 5 x 10-6), which also showed evidence of association in the disease-specific GWAS scan. These loci included several genomic regions not previously reported as shared loci, besides risk factors associated with both diseases in previous studies. The follow-up of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these two diseases (Pcombined = 3.29 x 10-12). In addition, the analysis of the biological relevance of the known SSc-RA shared loci pointed to the type I interferon and the interleukin 12 signaling pathways as the main common etiopathogenic factors. Conclusions: Our study has identified a novel shared locus, IRF4, for SSc and RA and highlighted the usefulness of cross-disease GWAS meta-analysis in the identification of common risk loci

A cross-disease meta-GWAS identifies four new susceptibility loci shared between systemic sclerosis and Crohn’s disease

Abstract: Genome-wide association studies (GWASs) have identified a number of genetic risk loci associated with systemic sclerosis (SSc) and Crohn’s disease (CD), some of which confer susceptibility to both diseases. In order to identify new risk loci shared between these two immune-mediated disorders, we performed a cross-disease meta-analysis including GWAS data from 5,734 SSc patients, 4,588 CD patients and 14,568 controls of European origin. We identified 4 new loci shared between SSc and CD, IL12RB2, IRF1/SLC22A5, STAT3 and an intergenic locus at 6p21.31. Pleiotropic variants within these loci showed opposite allelic effects in the two analysed diseases and all of them showed a significant effect on gene expression. In addition, an enrichment in the IL-12 family and type I interferon signaling pathways was observed among the set of SSc-CD common genetic risk loci. In conclusion, through the first cross-disease meta-analysis of SSc and CD, we identified genetic variants with pleiotropic effects on two clinically distinct immune-mediated disorders. The fact that all these pleiotropic SNPs have opposite allelic effects in SSc and CD reveals the complexity of the molecular mechanisms by which polymorphisms affect diseases

Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta-analysis

This is the peer reviewed version of the following article: Arias‐Bujanda, N, Regueira‐Iglesias, A, Balsa‐Castro, C, Nibali, L, Donos, N, Tomás, I. Accuracy of single molecular biomarkers in saliva for the diagnosis of periodontitis: A systematic review and meta‐analysis. J Clin Periodontol. 2020; 47: 2– 18. https://doi.org/10.1111/jcpe.13202, which has been published in final form at https://doi.org/10.1111/jcpe.13202. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsAim To analyse, using a meta‐analytical approach, the diagnostic accuracy of single molecular biomarkers in saliva for the detection of periodontitis in systemically healthy subjects. Materials and Methods Articles on molecular biomarkers in saliva providing a binary contingency table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. Searches for candidate articles were conducted in six electronic databases. The methodological quality was assessed through the tool Quality Assessment of Diagnostic Studies. Meta‐analyses were performed using the Hierarchical Summary Receiver Operating Characteristic model. Results Meta‐analysis was possible for 5 of the 32 biomarkers studied. The highest values of sensitivity for the diagnosis of periodontitis were obtained for IL1beta (78.7%), followed by MMP8 (72.5%), IL6 and haemoglobin (72.0% for both molecules); the lowest sensitivity value was for MMP9 (70.3%). In terms of specificity estimates, MMP9 had the best result (81.5%), followed by IL1beta (78.0%) and haemoglobin (75.2%); MMP8 had the lowest specificity (70.5%). Conclusions MMP8, MMP9, IL1beta, IL6 and Hb were salivary biomarkers with good capability to detect periodontitis in systemically healthy subjects. MMP8 and IL1beta are the most researched biomarkers in the field, both showing clinically fair effectiveness for the diagnosis of periodontitis.the Instituto de Salud Carlos III (General Division of Evaluation and Research Promotion, Madrid, Spain) and co‐financed by FEDER. Grant Number: Grant ISCIII/PI17/01722 the Consellería de Cultura, Educación e Ordenación Universitaria da Xunta de Galicia (Spain). Grant Number: Grant ED431B 2017/02

Short-term anti-plaque effect of a cymenol mouthwash analysed using the DenTiUS Deep Plaque software: a randomised clinical trial

Abstract Background The effect of cymenol mouthwashes on levels of dental plaque has not been evaluated thus far. Objective To analyse the short-term, in situ, anti-plaque effect of a 0.1% cymenol mouthwash using the DenTiUS Deep Plaque software. Methods Fifty orally healthy participants were distributed randomly into two groups: 24 received a cymenol mouthwash for eight days (test group A) and 26 a placebo mouthwash for four days and a cymenol mouthwash for a further four days thereafter (test group B). They were instructed not to perform other oral hygiene measures. On days 0, 4, and 8 of the experiment, a rinsing protocol for staining the dental plaque with sodium fluorescein was performed. Three intraoral photographs were taken per subject under ultraviolet light. The 504 images were analysed using the DenTiUS Deep Plaque software, and visible and total plaque indices were calculated (ClinicalTrials ID NCT05521230). Results On day 4, the percentage area of visible plaque was significantly lower in test group A than in test group B (absolute = 35.31 ± 14.93% vs. 46.57 ± 18.92%, p = 0.023; relative = 29.80 ± 13.97% vs. 40.53 ± 18.48%, p = 0.024). In comparison with the placebo, the cymenol mouthwash was found to have reduced the growth rate of the area of visible plaque in the first four days by 26% (absolute) to 28% (relative). On day 8, the percentage areas of both the visible and total plaque were significantly lower in test group A than in test group B (visible absolute = 44.79 ± 15.77% vs. 65.12 ± 16.37%, p < 0.001; visible relative = 39.27 ± 14.33% vs. 59.24 ± 16.90%, p < 0.001; total = 65.17 ± 9.73% vs. 74.52 ± 13.55%, p = 0.007). Accounting for the growth rate with the placebo mouthwash on day 4, the above results imply that the cymenol mouthwash in the last four days of the trial reduced the growth rate of the area of visible plaque (absolute and relative) by 53% (test group A) and 29% (test group B), and of the area of total plaque by 48% (test group A) and 41% (test group B). Conclusions The 0.1% cymenol mouthwash has a short-term anti-plaque effect in situ, strongly conditioning the rate of plaque growth, even in clinical situations with high levels of dental plaque accumulation