| Literature DB >> 28748030 |
Xingwen Wu1,2, Jiazhen Chen3, Meng Xu1, Danting Zhu1, Xuyang Wang3, Yulin Chen3, Jing Wu3, Chenghao Cui1, Wenhong Zhang3, Liying Yu1.
Abstract
This study investigated if chronic obstructive pulmonary disease (COPD) is correlated with periodontitis via periodontal microbiota and if certain bacteria affect periodontitis as well as COPD. Moreover, the study investigated whether suffering from COPD is associated with a decrease in the richness and diversity of periodontal microbiota. Subgingival plaque was obtained from 105 patients. Bacterial DNA was isolated from 55 COPD and 50 non-COPD participants (either with or without periodontitis). 16S rRNA gene metagenomic sequencing was used to characterize the microbiota and to determine taxonomic classification. In the non-periodontitis patients, suffering from COPD resulted in a decrease in bacteria richness and diversity in the periodontal microenvironment. An increase in the genera Dysgonomonas, Desulfobulbus, and Catonella and in four species (Porphyromonas endodontalis, Dysgonomonas wimpennyi, Catonella morbi, and Prevotella intermedia) in both COPD and periodontitis patients suggests that an increase in these periodontitis-associated microbiota may be related to COPD. Three genera (Johnsonella, Campylobacter, and Oribacterium) were associated with COPD but not with periodontitis. The decrease in the genera Arcanobacterium, Oribacterium, and Streptomyces in COPD patients implies that these genera may be health-associated genera, and the decrease in these genera may be related to disease. These data support the hypothesis that COPD is correlated with periodontitis via these significantly changed specific bacteria.Entities:
Keywords: 16s rRNA gene; Oral microbiota; chronic obstructive pulmonary disease; chronic periotontal disease; high-throughput sequencing; subgingival plaque
Year: 2017 PMID: 28748030 PMCID: PMC5508401 DOI: 10.1080/20002297.2017.1324725
Source DB: PubMed Journal: J Oral Microbiol ISSN: 2000-2297 Impact factor: 5.474
Characteristics and taxonomic data of enrolled study participants.
| C+P+ | C+P– | C–P+ | C–P– | |
|---|---|---|---|---|
| Sex (%) | ||||
| Male | 24 (80.0%) | 17 (68.0%) | 19 (76.0%) | 11 (44.0%) |
| Female | 6 (20.0%) | 8 (32.0%) | 6 (24.0%) | 14 (56.0%) |
| Age | ||||
| Mean ( | 65.2 (7.4) | 65.6 (7.1) | 63.4 (7.0) | 64.8 (6.7) |
| Smoking status (%) | ||||
| Non-smokera | 13 (43.3%) | 15 (60.0%) | 17 (68.0%) | 20 (80.0%) |
| Smoker | 17 (56.7%) | 10 (40.0%) | 8 (32.0%) | 5 (20.0%) |
| Former smokerb | 4 (13.3%) | 5 (20.0%) | 1 (4.0%) | 1 (4.0%) |
| Current smokerc | 13 (43.3%) | 5 (20.0%) | 7 (28.0%) | 4 (16.0%) |
| Cigarettes/day (mean ± | ||||
| Non-smoker | 0 ± 0 | 0 ± 0 | 0 ± 0 | 0 ± 0 |
| Smoker | 19.4 ± 12.1 | 22 ± 7.9 | 20.5 ± 13.6 | 16.4 ± 14.4 |
| Former smoker | 13.8 ± 7.5 | 24 ± 11.4 | 20 ± N/A | 20 ± N/A |
| Current smoker | 21.8 ± 12.8 | 20 ± 0 | 20.6 ± 14.6 | 15.5 ± 16.5 |
| COPD classification (%)d | ||||
| II | 16 (53.3%) | 18 (72.0%) | / | / |
| III | 14 (46.7%) | 7 (28.0%) | / | / |
| FEV1 | ||||
| Mean ( | 51.9 (14.1) | 59.3 (14.3) | / | / |
| Inhaled steroids | 4 (13.3%) | 4 (16.0%) | / | / |
| OHI-S | ||||
| Mean ( | 2.21 (0.32) | 1.52 (0.42) | 2.18 (0.43) | 1.45 (0.51) |
| Clinical attachment loss (mm) | ||||
| Mean ( | 5.5 (0.7) | / | 5.9 (1.2) | / |
| Detected sequence (thousands) | ||||
| Mean ( | 132 (83) | 204 (63) | 178 (64) | 175 (83) |
| Classified sequence (%) | ||||
| Mean ( | 94.83 (0.35) | 94.61 (1.26) | 94.8 (0.59) | 94.75 (0.46) |
aNon-smokers were those who either had never smoked or quit cigarettes at least 10 years prior to study entry.
bFormer smokers were those who quit cigarettes at least 6 months but <10 years prior to study entry.
cCurrent smokers were currently smokers or those who quit cigarettes <6 months prior to study entry.
dPatients with COPD were grouped into moderate (II predicted FEV1 = 50–80%; FEV1/FVC ≤70%) and severe (III, predicted FEV1 = 30–50%; FEV1/FVC ≤70%) categories based on spirometry.
Figure 1.Beta diversity analysis based on weighted UniFrac analysis. Red dots represent periodontitis patients with chronic obstructive pulmonary disorder (COPD; C+P+ group), green dots represent periodontitis patients without COPD (C−P+ group), yellow dots represent COPD patients without periodontitis (C+P− group), and blue dots represent participants without COPD or periodontitis (C−P− group). Red and blue circles represent different periodontal bacterial community clusters.
Figure 2.Relative abundance and composition of microbial genera (A) and species (B) in four groups of participants. The abundance cut-off in this figure was set at 0.5%. Some values <0.5% were not shown. A Kruskal–Wallis test was used to analyse diversity among the four groups. Statistical significance is indicated by the following: *p < 0.05; **p < 0.01; ***p < 0.001.
Figure 4.Statistically significant bacterial genera (A) and species (B) associated with COPD and periodontitis in periodontitis and non-periodontitis patients. The red circle represents significantly different bacterial abundance between COPD and non-COPD patients. The blue circle represents significantly different bacterial abundance between C+P+ and C−P+ groups. The green circle represents significantly different bacterial abundance between C+P− and C−P− groups. The gray circle represents significantly different bacterial abundance between C−P+ and C−P− groups. No overlapping area between blue and green circles was observed. The abundance cut-off was set at 0.1%. Some values <0.1% were not calculated or shown in the figure. ↑, increased; ↓, decreased.
Figure 3.Mean relative abundance of bacterial genera (A) and species (B) with statistical differences between COPD and non-COPD patients. Data from COPD patients (C+P+ and C+P−) and non-COPD patients (C−P+ and C−P−) are shown. The abundance cut-off was set at 0.1%. Some values <0.1% were not calculated or shown in the figure. Statistical significance is indicated by the following: #p < 0.05, significant difference between COPD and non-COPD patients using weighted Student’s t-tests; ##p < 0.01; ###p < 0.001; *p < 0.05; **p < 0.01; ***p < 0.001.