Comparison of the oral microbiome of patients with generalized aggressive periodontitis and periodontitis-free subjects

Schulz, Susanne; Porsch, Martin; Große, Ivo; Hoffmann, Katrin; Schaller, Hans‐Günter; Reichert, Stefan

doi:10.1016/j.archoralbio.2019.01.015

Cited by 62 publications

(59 citation statements)

References 45 publications

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“…The average number of taxa at the species level per individual (16) that we found was lower than what has been reported in other studies, which is around 200-600 species (13, 30). This is probably because the 16s RNA fragment we have used had a relatively low capacity to discriminate within the lowest taxonomic levels (genus and species).…”

Section: Discussioncontrasting

confidence: 97%

Characterization of the oral microbiome of medically controlled type-2 diabetes patients

Santos

Martins-Mendes

Gayà-Vidal

et al. 2020

Preprint

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28Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that is becoming a 29 significant global health care problem. Several studies have shown that people with 30 diabetes are more susceptible to oral problems, such as periodontitis and, although the 31 causes are still inconclusive, the oral microbiota seems to be an important factor in this 32 interaction. This study aimed to characterize the oral microbiome of a sample representing 33 T2DM patients from Portugal and exploit potential associations between some 34 microorganisms and variables like teeth brushing, smoking habits, and nutrient intake. 35 By sequencing the hypervariable regions V3-V4 of the 16S rRNA gene in 50 individuals 36 belonging to a group of diabetes patients and a control group, we found a total of 233 37 taxa, from which only 65% were shared between both groups. No differences were found 38 in terms of alpha and beta diversity between groups or habits categories. Also, there were 39 no significant differences in the oral microbiome profiles of control and diabetes patients. 40Only the class Synergistia and the genus TG5, which are related to periodontitis, were 41 statistically more frequent in the control group. This finding can be justified by the fact 42 that these diabetic patients usually have their oral health under close medical control than 43 an average healthy person, which in this study was represented by the control group. 44 45 IMPORTANCE: Diabetes has become a significant global health care issue as its 46 incidence continues to increase exponentially, with type 2 diabetes being responsible for 47 more than 90% of these cases. Portugal is one of the countries with a higher prevalence 48 of diabetes in Europe. It has been reported that diabetic people have an increased risk of 49 developing several health problems such as oral infections mostly caused by opportunistic 50 pathogens. Some studies have pointed out a relationship between diabetes and oral 51 3 microbiome. Therefore, the characterization of the microbial ecosystem of the mouth in 52 reference groups is crucial to provide information to tackle oral health pathogen-borne 53 conditions. In this study, we provide the first characterization of the oral microbiome of 54 type 2 diabetes mellitus patients from Portugal, and therefore, contributing new data and 55 knowledge to elucidate the relationship between diabetes and the oral microbiome. 56 57 58 59 60 61 62 Keywords: oral microbiome, type 2 diabetes mellitus, 16S rRNA gene sequencing, 63 microbiota, Next-Generation Sequencing, Portugal 64 65 67hyperglycemia caused by defects in insulin secretion, which can contribute to the 68 development of resistance to its action (1, 2). T2DM is becoming more common, also in 69 children and adolescents, and therefore, represents a significant global health care 70 problem (3). 71As more studies are focused on the impact of T2DM on the medium-term patients' health, 72 a growing number of studies have been reporting a close association between diabetes 73 and susce...

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Section: Discussioncontrasting

confidence: 97%

Characterization of the oral microbiome of medically controlled type-2 diabetes patients

Santos

Martins-Mendes

Gayà-Vidal

et al. 2020

Preprint

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“…The experimental protocol was approved by the Institutional Review Board of Pusan National University. Even though the sample size in the current study was larger than those of previous microbiome studies associated with periodontal disease [14,[23][24][25][26], a power analysis for sample size was performed using a web application of microbiome power calculator, which is based on Monte Carlo simulations and Wilcoxon-Mann-Whitney test [27]. The simulation results demonstrated that the current study with 272 samples had sufficient power (equal or greater than 0.8 for both buccal and supragingival parameters) to detect at least significant differences in community diversity between groups, as well as differences in abundance of the 20 most important operational taxonomic units (OTUs).…”

Section: Study Population and Clinical Examinationmentioning

confidence: 84%

Identification of Potential Oral Microbial Biomarkers for the Diagnosis of Periodontitis

Kim

Han

et al. 2020

JCM

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Periodontitis is a chronic and multifactorial inflammatory disease that can lead to tooth loss. At present, the diagnosis for periodontitis is primarily based on clinical examination and radiographic parameters. Detecting the periodontal pathogens at the subgingival plaque requires skilled professionals to collect samples. Periodontal pathogens are also detected on various mucous membranes in patients with periodontitis. In this study, we characterized the oral microbiome profiles from buccal mucosa and supragingival space in a total of 272 healthy subjects as a control group, and periodontitis patients as a disease group. We identified 13 phyla, 193 genera, and 527 species and determined periodontitis-associated taxa. Porphyromonas gingivalis, Tannerella forsythia, Treponema denticolar, Filifactor alocis, Porphyromonas endodontalis, Fretibacterium fastiosum and Peptostreptococcus species were significantly increased in both the buccal mucosa and the supragingival space in periodontitis patients. The identified eight periodontitis-associated bacterial species were clinically validated in an independent cohort. We generated the prediction model based on the oral microbiome profiles using five machine learning algorithms, and validated its capability in predicting the status of patients with periodontitis. The results showed that the oral microbiome profiles from buccal mucosa and supragingival space can represent the microbial composition of subgingival plaque and further be utilized to identify potential microbial biomarkers for the diagnosis of periodontitis. Besides, bacterial community interaction network analysis found distinct patterns associated with dysbiosis in periodontitis. In summary, we have identified oral bacterial species from buccal and supragingival sites which can predict subgingival bacterial composition and can be used for early diagnosis of periodontitis. Therefore, our study provides an important basis for developing easy and noninvasive methods to diagnose and monitor periodontitis.

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“…Recently, the pathophysiological understanding of the aetiology of infectious diseases, like periodontitis, is increasingly changing. The consideration of the oral microbiome as a complex microbiological network was highlighted in previous studies (Schulz et al, ). A characteristic feature of the aetiology of periodontitis is a pathological shift of the oral microbiome leading to dysbiosis (Hajishengallis, ).…”

Section: Discussionmentioning

confidence: 99%

Periodontal pathogens and their role in cardiovascular outcome

Schulz

Schlitt

Hofmann

et al. 2019

J Clinic Periodontology

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Aim: Periodontitis has been identified as a moderate but independent risk factor for cardiovascular (CV) disease and progression. The objective of this study (ClinicalTrials.gov Identifier: NCT01045070) was to assess subgingival colonization with selected periodontal pathogens on the occurrence of further adverse CV events in a cohort of CV patients. Methods: The prevalence of severe periodontitis including the detection of 11 periodontal pathogens (Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Prevotella intermedia, Tannerella forsythia, Treponema denticola, P. intermdia, Peptostreptococcus micros, Fusobacterium nucleatum, Campylobacter rectus, Eubacterium nodatum, Eikenella corrodens, Capnocytophaga sputigena, Capnocytophaga gingivalis, Capnocytophaga ochracea; HAIN-Diagnostica ® ) was analysed in 1,002 CV patients The prognostic impact of periodontal pathogens for combined CV endpoint (stroke/TIA, myocardial infarction, CV death, death from stroke) was evaluated after a 3-year follow-up period. Hazard ratios (HRs) were adjusted for established CV risk factors applying Cox regression. Results:In the Kaplan-Meier analysis (log-rank test: p < .001) and Cox regression (HR: 0.545, 95%-CI: 0.387-0.773; p = .001), the decreased occurrence of E. corrodens was shown to be an independent predictor for adverse CV events after 3 years of follow-up. Conclusions:The detection of E. corrodens was associated with a reduced risk of adverse CV events in patients with CV disease. The pathophysiological background underlying this association should be investigated in further studies. K E Y W O R D Sadverse cardiovascular events, cardiovascular disease, E. corrodens, longitudinal cohort study, microbiology, severe periodontitis

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Comparison of the oral microbiome of patients with generalized aggressive periodontitis and periodontitis-free subjects

Cited by 62 publications

References 45 publications

Characterization of the oral microbiome of medically controlled type-2 diabetes patients

Characterization of the oral microbiome of medically controlled type-2 diabetes patients

Identification of Potential Oral Microbial Biomarkers for the Diagnosis of Periodontitis

Periodontal pathogens and their role in cardiovascular outcome

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