Dataset Information

Subgingival microbiome of rheumatoid arthritis patients in relation to their disease status and periodontal health.

ABSTRACT:

Objective

Rheumatoid arthritis (RA) and periodontitis are chronic inflammatory diseases that share common risk factors. However, the bidirectional relationship between RA and periodontal disease is not fully understood. This study was undertaken to describe the bacterial component of the subgingival microbiome in RA patients and to relate this to RA disease activity and periodontal status.

Methods

Patients with chronic established RA (N = 78) were periodontally examined and their subgingival plaque samples were collected; their clinical and laboratory data on RA status and medication were obtained from medical records. Bacterial DNA was quantified by universal 16S rDNA qPCR, and Porphyromonas gingivalis by species-specific qPCR. For microbiome assessment, 16S rDNA amplicon sequencing was performed.

Results

Active RA was diagnosed in 58% of the patients and periodontitis in 82% (mild: 9%, moderate: 55%, severe: 18%). P. gingivalis was present in 14% of the samples. Different levels of gingival bleeding, periodontal probing depth, RA disease status, prednisolone use and smoking were associated with significantly different microbiome compositions. Two subgingival microbial community types were discerned.

Conclusion

In RA patients with active disease, anti-inflammatory medication as part of RA therapy was associated with better oral health status and a healthier subgingival microbiome compared to that of RA patients in remission, especially those in remission who were current smokers. RA patients in remission with current smoking status may particularly benefit from a systematic periodontal treatment program. The potential role of microbial community types in patient stratification and personalized therapy should be assessed in longitudinal studies.

SUBMITTER: Beyer K

PROVIDER: S-EPMC6145512 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Subgingival microbiome of rheumatoid arthritis patients in relation to their disease status and periodontal health.

Beyer Kathrin K Zaura Egija E Brandt Bernd W BW Buijs Mark J MJ Brun Johan G JG Crielaard Wim W Bolstad Anne Isine AI

PloS one 20180919 9

<h4>Objective</h4>Rheumatoid arthritis (RA) and periodontitis are chronic inflammatory diseases that share common risk factors. However, the bidirectional relationship between RA and periodontal disease is not fully understood. This study was undertaken to describe the bacterial component of the subgingival microbiome in RA patients and to relate this to RA disease activity and periodontal status.<h4>Methods</h4>Patients with chronic established RA (N = 78) were periodontally examined and their ...[more]

PMID: 30231060

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Project description:BackgroundSubgingival microbiome in disease-associated subgingival sites is known to be dysbiotic and significantly altered. In patients with rheumatoid arthritis (RA), the extent of dysbiosis in disease- and health-associated subgingival sites is not clear.Methods8 RA and 10 non-RA subjects were recruited for this pilot study. All subjects received full oral examination and underwent collection of subgingival plaque samples from both shallow (periodontal health-associated, probing depth ≤ 3mm) and deep subgingival sites (periodontal disease-associated, probing depth ≥ 4 mm). RA subjects also had rheumatological evaluation. Plaque community profiles were analyzed using 16 S rRNA sequencing.ResultsThe phylogenetic diversity of microbial communities in both RA and non-RA controls was significantly higher in deep subgingival sites compared to shallow sites (p = 0.022), and the overall subgingival microbiome clustered primarily according to probing depth (i.e. shallow versus deep sites), and not separated by RA status. While a large number of differentially abundant taxa and gene functions was observed between deep and shallow sites as expected in non-RA controls, we found very few differentially abundant taxa and gene functions between deep and shallow sites in RA subjects. In addition, compared to non-RA controls, the UniFrac distances between deep and shallow sites in RA subjects were smaller, suggesting increased similarity between deep and shallow subgingival microbiome in RA. Streptococcus parasanguinis and Actinomyces meyeri were overabundant in RA subjects, while Gemella morbillorum, Kingella denitrificans, Prevotella melaninogenica and Leptotrichia spp. were more abundant in non-RA subjects.ConclusionsThe aggregate subgingival microbiome was not significantly different between individuals with and without rheumatoid arthritis. Although the differences in the overall subgingival microbiome was driven primarily by probing depth, in contrast to the substantial microbiome differences typically seen between deep and shallow sites in non-RA patients, the microbiome of deep and shallow sites in RA patients were more similar to each other. These results suggest that factors associated with RA may modulate the ecology of subgingival microbiome and its relationship to periodontal disease, the basis of which remains unknown but warrants further investigation.

Project description:Understanding of the oral microbiome in relation to periodontal disease in older adults is limited. The composition and diversity of the subgingival microflora and their oligotypes in health and levels of periodontal disease were investigated in this study on older postmenopausal women. The 16S rRNA gene was sequenced using the Illumina MiSeq platform in 1,206 women aged 53 to 81 y. Presence and severity of periodontal disease were defined by Centers for Disease Control and Prevention/American Academy of Periodontology criteria. Composition of the microbiome was determined by 16S rRNA amplicon sequencing and the abundance of taxa described by the centered log2-ratio (CLR) transformed operational taxonomic unit (OTU) values. Differences according to periodontal disease status were determined by analysis of variance with Bonferroni correction. Bacteria oligotypes associated with periodontal disease and health were determined by minimum entropy decomposition and their functions estimated in silico using PICRUSt. Prevalence of none/mild, moderate, and severe periodontal disease was 25.1%, 58.3%, and 16.6%, respectively. Alpha diversity of the microbiome differed significantly across the 3 periodontal disease categories. β-Diversity differed between no/mild and severe periodontal disease, although considerable overlap was noted. Of the 267 bacterial species identified at ≥0.02% abundance, 56 (20.9%) differed significantly in abundance according to periodontal disease status. Significant linear correlations for pocket depth and clinical attachment level with bacterial amounts were observed for several taxa. Of the taxa differing in abundance according to periodontal disease status, 53% had multiple oligotypes appearing to differ between none/mild and severe periodontal disease. Among older women, taxonomic differences in subgingival microbiome composition and diversity were observed in relation to clinical periodontal disease measures. Potential differences in bacterial subspecies (oligotypes) and their function were also identified in periodontal disease compared with health.

Project description:Objectives: Periodontal disease (PD) and rheumatoid arthritis (RA) are known chronic conditions with sustained inflammation leading to osteolysis. Cardiovascular diseases (CVD) are frequent comorbidities that may arise from sustained inflammation associated with both PD and RA. In order to determine CVD risk, alterations at the molecular level need to be identified. The objective of this study, therefore, was to assess the relationship of CVD associated biomarkers in RA patients and how it is influenced by PD. Methods: The study consisted of patient (26 RA with PD, 21 RA without PD, 51 patients with PD only) and systemically and periodontally healthy control (n = 20) groups. Periodontal parameters bleeding on probing, probing pocket depth, and marginal bone loss were determined to characterize the patient groups. Proteomic analysis of 92 CVD-related protein biomarkers was performed using a multiplex proximity extension assay. Biomarkers were clustered using the search tool for retrieval of interacting genes (STRING) to determine protein−protein interaction (PPI) networks. Results: RA patients with PD had higher detection levels for 47% of the measured markers (ANGPT1, BOC, CCL17, CCL3, CD4, CD84, CTRC, FGF-21, FGF-23, GLO1, HAOX1, HB-EGF, hOSCAR, HSP 27, IL16, IL-17D, IL18, IL-27, IL6, LEP, LPL, MERTK, MMP12, MMP7, NEMO, PAPPA, PAR-1, PARP-1, PD-L2, PGF, PIgR, PRELP, RAGE, SCF, SLAMF7, SRC, THBS2, THPO, TNFRSF13B, TRAIL-R2, VEGFD, VSIG2, and XCL1) as compared to RA without PD. Furthermore, a strong biological network was identified amongst these proteins (clustering coefficient = 0.52, PPI enrichment p-value < 0.0001). Coefficients for protein clusters involved in CVD (0.59), metabolic (0.53), and skeletal (0.51) diseases were strongest in the PD group. Conclusion: Periodontal disease augments CVD-related biomarkers in RA through shared pathological clusters, concurrently enhancing metabolic and skeletal disease protein interactions, independent of autoimmune status.

Project description:Since periodontitis and type 2 diabetes mellitus are complex diseases, a thorough understanding of their pathogenesis requires knowing the relationship of these pathologies with other disorders and environmental factors. In this study, the representability of the subgingival periodontal microbiome of 46 subjects was studied by 16S rRNA gene sequencing and shotgun sequencing of pooled samples. We examined 15 patients with chronic periodontitis (CP), 15 patients with chronic periodontitis associated with type 2 diabetes mellitus (CPT2DM), and 16 healthy subjects (Control). The severity of generalized chronic periodontitis in both periodontitis groups of patients (CP and CPT2DM) was moderate (stage II). The male to female ratios were approximately equal in each group (22 males and 24 females); the average age of the subjects was 53.9 ± 7.3 and 54.3 ± 7.2 years, respectively. The presence of overweight patients (Body Mass Index (BMI) 30-34.9 kg/m2) and patients with class 1-2 obesity (BMI 35-45.9 kg/m2) was significantly higher in the CPT2DM group than in patients having only chronic periodontitis or in the Control group. However, there was no statistically significant difference in all clinical indices between the CP and CPT2DM groups. An analysis of the metagenomic data revealed that the alpha diversity in the CPT2DM group was increased compared to that in the CP and Control groups. The microbiome biomarkers associated with experimental groups were evaluated. In both groups of patients with periodontitis, the relative abundance of Porphyromonadaceae was increased compared to that in the Control group. The CPT2DM group was characterized by a lower relative abundance of Streptococcaceae/Pasteurellaceae and a higher abundance of Leptotrichiaceae compared to those in the CP and Control groups. Furthermore, the CP and CPT2DM groups differed in terms of the relative abundance of Veillonellaceae (which was decreased in the CPT2DM group compared to CP) and Neisseriaceae (which was increased in the CPT2DM group compared to CP). In addition, differences in bacterial content were identified by a combination of shotgun sequencing of pooled samples and genome-resolved metagenomics. The results indicate that there are subgingival microbiome-specific features in patients with chronic periodontitis associated with type 2 diabetes mellitus.

Dataset Information

Subgingival microbiome of rheumatoid arthritis patients in relation to their disease status and periodontal health.

Objective

Methods

Results

Conclusion

Publications

Subgingival microbiome of rheumatoid arthritis patients in relation to their disease status and periodontal health.

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