Subgingival microbial profile of obese women with periodontal disease

Influence of obesity on subgingival microbiota composition in subjects with different periodontal status: a systematic review

Objective

This systematic review aimed to investigate the changes in the composition of the subgingival microbiota among subjects with normo-weight, overweight and obesity, in conditions of periodontal health and disease.

Materials and Methods

The protocol for this study was designed following PRISMA guidelines. Records were identified using different search engines (PubMed/MedLine, Scopus and Web of Science). Observational studies, in human subjects diagnosed with obesity (BMI >30kg/m2) and periodontal disease (gingivitis and periodontitis), on the analysis of subgingival microbiota were selected. Eight articles were included.

Results

The subgingival microbiota of 1,229 subjects (n=894 exposure group and n=335 control group) was analyzed. Periodontal pathogens were the most common bacteria detected in subjects with obesity and periodontitis (Porphyromonas gingivalis, Tannerella forsythia, Campylobacter gracilis, Eubacterium nodatum, Fusobacterium nucleatum spp. vincentii, Parvimonas micra, Prevotella intermedia, Campylobacter rectus, and Aggregatibacter actinomycetemcomitans), as along with some accessory pathogens such as: Streptococcus gordonii, and Veillonella parvula that favor the virulence of late colonizers.

Conclusions

Although there are evident alterations in the composition of the subgingival microbiota in subjects with obesity and periodontitis, it is still a challenge to identify a specific pattern of microbiota in these subjects. If associations between subgingival plaque microorganisms and obesity are confirmed, microbiome analysis could be a useful tool to improve preventive measures and the management of people with obesity.

Obesity Is Associated with the Severity of Periodontal Inflammation Due to a Specific Signature of Subgingival Microbiota

The aim of this study was to analyze the link between periodontal microbiota and obesity in humans. We conducted a cohort study including 45 subjects with periodontitis divided into two groups: normo-weighted subjects with a body mass index (BMI) between 20 and 25 kg/m2 (n = 34) and obese subjects with a BMI > 30 kg/m2 (n = 11). Our results showed that obesity was associated with significantly more severe gingival inflammation according to Periodontal Inflamed Surface Area (PISA index). Periodontal microbiota taxonomic analysis showed that the obese (OB) subjects with periodontitis were characterized by a specific signature of subgingival microbiota with an increase in Gram-positive bacteria in periodontal pockets, associated with a decrease in microbiota diversity compared to that of normo-weighted subjects with periodontitis. Finally, periodontal treatment response was less effective in OB subjects with persisting periodontal inflammation, reflecting a still unstable periodontal condition and a risk of recurrence. To our knowledge, this study is the first exploring both salivary and subgingival microbiota of OB subjects. Considering that OB subjects are at higher periodontal risk, this could lead to more personalized preventive or therapeutic strategies for obese patients regarding periodontitis through the specific management of oral microbiota of obese patients.

Dysbiosis of the Subgingival Microbiome and Relation to Periodontal Disease in Association with Obesity and Overweight

Obesity causes gut dysbiosis; nevertheless, little is known about the oral microbiome. We aimed to identify differences in the subgingival microbiota influenced by body weight and periodontal status. Patients (n = 75) recruited at the University Dental Hospital Sharjah, United Arab Emirates, were distributed into three equal groups (healthy weight, overweight, and obese) sub-divided into having either no-mild (NM) or moderate-severe (MS) periodontitis. Subgingival plaques were collected. Microbiota were identified by 16S rRNA sequencing using nanopore technology. Linear discriminant analysis demonstrated significant bacterial biomarkers for body weight and periodontal health. Unique microbiota signatures were identified, with enrichment of periopathogens in patients with MS periodontitis (Aggregatibacter actinomycetemcomitans in obese, Tannerella forsythia and Treponema denticola in overweight, Porphyromonas gingivalis and Fusobacterium nucleatum in healthy weight), thus reflecting differences in the microbiota affected by body weight. Other pathogenic bacteria, such as Salmonella enterica and Klebsiella pneumoniae, were enriched in overweight subjects with NM periodontitis, suggesting an increase in the relative abundance of pathogens even in patients with good periodontal health if they were overweight. Alpha and beta diversities were significantly different among the groups. Dysbiosis of the subgingival microbiota in obese and overweight individuals was associated with increased prevalence and severity of periodontal disease, which was correlated with the body mass index. This study highlights the immense importance of the oral microbiome and the need for lifestyle and dental interventions to resolve oral dysbiosis and restore normal homeostasis.

Obesity influences composition of salivary and fecal microbiota and impacts the interactions between bacterial taxa

Obesity is an increasing global health concern and is associated with a broad range of morbidities. The gut microbiota are increasingly recognized as important contributors to obesity and cardiometabolic health. This study aimed to characterize oral and gut microbial communities, and evaluate host: microbiota interactions between clinical obesity classifications. We performed 16S rRNA sequencing on fecal and salivary samples, global metabolomics profiling on plasma and stool samples, and dietary profiling in 135 healthy individuals. We grouped individuals by obesity status, based on body mass index (BMI), including lean (BMI 18-124.9), overweight (BMI 25-29.9), or obese (BMI ≥30). We analyzed differences in microbiome composition, community inter-relationships, and predicted microbial function by obesity status. We found that salivary bacterial communities of lean and obese individuals were compositionally and phylogenetically distinct. An increase in obesity status was positively associated with strong correlations between bacterial taxa, particularly with bacterial groups implicated in metabolic disorders including Fretibacterium, and Tannerella. Consumption of sweeteners, especially xylitol, significantly influenced compositional and phylogenetic diversities of salivary and fecal bacterial communities. In addition, obesity groups exhibited differences in predicted bacterial metabolic activity, which was correlated with host's metabolite concentrations. Overall, obesity was associated with distinct changes in bacterial community dynamics, particularly in saliva. Consideration of microbiome community structure and inclusion of salivary samples may improve our ability to understand pathways linking microbiota to obesity and cardiometabolic disease.

The impact of the Th17:Treg axis on the IgA-Biome across the glycemic spectrum

Secretory IgA (SIgA) is released into mucosal surfaces where its function extends beyond that of host defense to include the shaping of resident microbial communities by mediating exclusion/inclusion of respective microbes and regulating bacterial gene expression. In this capacity, SIgA acts as the fulcrum on which host immunity and the health of the microbiota are balanced. We recently completed an analysis of the gut and salivary IgA-Biomes (16S rDNA sequencing of SIgA-coated/uncoated bacteria) in Mexican-American adults that identified IgA-Biome differences across the glycemic spectrum. As Th17:Treg ratio imbalances are associated with gut microbiome dysbiosis and chronic inflammatory conditions such as type 2 diabetes, the present study extends our prior work by examining the impact of Th17:Treg ratios (pro-inflammatory:anti-inflammatory T-cell ratios) and the SIgA response (Th17:Treg-SIgA axis) in shaping microbial communities. Examining the impact of Th17:Treg ratios (determined by epigenetic qPCR lymphocyte subset quantification) on the IgA-Biome across diabetes phenotypes identified a proportional relationship between Th17:Treg ratios and alpha diversity in the stool IgA-Biome of those with dysglycemia, significant changes in community composition of the stool and salivary microbiomes across glycemic profiles, and genera preferentially abundant by T-cell inflammatory phenotype. This is the first study to associate epigenetically quantified Th17:Treg ratios with both the larger and SIgA-fractionated microbiome, assess these associations in the context of a chronic inflammatory disease, and offers a novel frame through which to evaluate mucosal microbiomes in the context of host responses and inflammation.

What Are the Clinical and Systemic Results of Periodontitis Treatment in Obese Individuals?

Purpose of Review

Periodontitis and obesity are characterized by a dysregulated inflammatory state. Obese individuals have a higher chance of presenting periodontitis. Clinical studies in different populations demonstrate that individuals with obesity have worse periodontal conditions. This current review aims to explore recent literature to understand what the impacts of obesity on periodontal treatment outcomes are and to learn whether periodontal treatment can improve systemic biomarkers in obese individuals.

Recent Findings

Short- and long-term evaluations demonstrated that non-surgical periodontal treatment could improve clinical parameters in obese individuals, represented as the reduction in mean probing depth, sites with probing depth ≥ 4 mm, and extension of bleeding on probing. However, obese individuals may have less clinical improvement when compared to normal-weight individuals with a similar periodontal profile. Additionally, periodontal treatment may contribute to a reduction in systemic levels of retinol-binding protein 4 and leptin, while promoting an increase in systemic levels of adiponectin.

Summary

Overall, obese individuals with periodontitis can significantly benefit from non-surgical periodontal treatment. However, clinical improvements seem to be less prominent in obese individuals with periodontitis compared to non-obese individuals with similar periodontal status. Nevertheless, periodontal treatment may impact significantly on the reduction of several biochemical biomarkers of obesity with or without weight reduction. Further investigations are needed to improve our comprehension of the mechanisms underlying those findings.

Untargeted and targeted gingival metabolome in rodents reveal metabolic links between high-fat diet-induced obesity and periodontitis

AIM

To characterize gingival metabolome in high-fat diet (HFD)-induced obesity in mice with/without periodontitis.

METHODS

HFD-induced obesity mouse model was established by 16-week feeding, and a lean control group was fed with low-fat diet (n = 21/group). Both models were induced for periodontitis on the left sides by molar ligation for 10 days, whereas the right sides were used as controls. Gingival metabolome and arginine metabolism were analysed by non-targeted/targeted liquid chromatography-mass spectrometry.

RESULTS

Of 2247 reference features, presence of periodontitis altered 165 in lean versus 885 in HFD mice; and HFD altered 525 in absence versus 1435 in presence of periodontitis. Compared with healthy condition, periodontitis and HFD had distinct effects on gingival metabolome. Metabolomic impacts of periodontitis were generally greater in HFD mice versus lean controls. K-medoids clustering showed that HFD amplified the impacts of periodontitis on gingival metabolome in both intensity and extensity. Ten metabolic pathways were enriched, including 2 specific to periodontitis, 5 specific to HFD and 3 shared ones. Targeted validation on arginine metabolism confirmed the additive effects between HFD and periodontitis.

CONCLUSION

The obese population consuming excessive HFD display amplified metabolic response to periodontitis, presenting a metabolic susceptibility to exacerbated periodontal destruction.

Association between clinical measures of gingival inflammation and obesity in adults: systematic review and meta-analyses

OBJECTIVE

This study aimed to systematically review the literature about the association between clinical measures of gingival inflammation and obesity in adults.

MATERIAL AND METHODS

Searches for studies were performed in five databases (Medline-PubMed, Scopus, Web of Science, Cochrane Library, and Embase) to compile studies of any design that evaluated the association between clinical measures of gingival inflammation and obesity in adults. Selection of studies, data extraction and risk of bias analysis were performed independently by two reviewers, and a third researcher was involved to resolve disagreements. Meta-analyses were performed for measures of gingival inflammation as compared to body mass index (BMI). Independent analyses were performed for studies involving periodontitis, gingivitis, and population-based/studies that did not provide a periodontal diagnosis. Standard mean deviation (SMD) and its 95% confidence interval (95%CI) were estimated.

RESULTS

Ninety studies were included (cross-sectional/clinical trials [n=82], case-control [n=3], cohorts [n=5]). Most of the studies demonstrated no significant difference in the measures of gingival inflammation regardless of the comparison performed. However, meta-analysis showed that among individuals with periodontitis, significantly higher levels of gingival inflammation are observed in those with obesity (n of individuals=240) when compared to those who were not obese (n of individuals=574) (SMD:0.26; 95%CI:0.07-0.44). When considering population-based/those studies that did not provide periodontal diagnosis, significantly higher measures of gingival inflammation were observed in the groups with higher BMI.

CONCLUSIONS

Within the limitations of the present study, it was concluded that higher measures of gingival inflammation may be expected for those with higher BMI.

CLINICAL RELEVANCE

Clinicians must be aware that higher measures of gingival inflammation may be expected for individuals with higher BMI. However, there is a necessity for further longitudinal studies regarding the association between obesity and gingival inflammation.

Obesity Drives an Oral Microbiota Signature of Female Patients with Periodontitis: A Pilot Study

The aim of this study was to analyze the link between oral microbiota and obesity in humans. We conducted a pilot study including 19 subjects with periodontitis divided into two groups: normo-weighted subjects (NWS) with a body mass index (BMI) between 20 and 25 (n = 9) and obese subjects (OS) with a BMI > 30 (n = 10). Obesity was associated with a poor oral health status characterized by an increased number of missing teeth and a higher score of periodontal-support loss associated with dysbiotic oral microbiota (39.45 ± 3.74 vs. 26.41 ± 11.21, p = 0.03 for the Chao 1 index). Oral microbiota taxonomic analysis showed that the abundance of the Capnocytophaga genus was higher (2.47% ± 3.02 vs. 0.27% ± 0.29, p = 0.04) in OS compared to NWS. Obese females (OF) were characterized by an increase in the Streptococcus genus (34.12% ± 14.29 vs. 10.55% ± 10.42, p = 0.05) compared to obese males (OM), where the Neisseria genus was increased (5.75% ± 5.03 vs. 58.05% ± 30.64, p = 0.008). These first data suggest that sex/gender is determinant in the link between oral dysbiotic microbiota and obesity in patients with periodontitis. Our results could lead to recommendations concerning therapeutic strategies for obese patients with periodontitis following the sex/gender.

Characteristics of the gut microbiome profile in obese patients with colorectal cancer

Background and Aim

Obesity affects the gut microbiome, which in turn increases the risk for colorectal cancer. Several studies have shown the mechanisms by which some bacteria may influence the development of colorectal cancer; however, gut microbiome characteristics in obese patients with colorectal cancer remain unclear. Therefore, this study evaluated their gut microbiome profile and its relationship with metabolic markers.

Methods

The study assessed fecal samples from 36 consecutive patients with colorectal cancer and 38 controls without colorectal cancer. To identify microbiotic variations between patients with colorectal cancer and controls, as well as between nonobese and obese individuals, 16S rRNA gene amplicon sequencing was performed.

Results

Principal coordinate analysis showed significant differences in the overall structure of the microbiome among the study groups. The α‐diversity, assessed by the Chao1 index or Shannon index, was higher in patients with colorectal cancer versus controls. The relative abundance of the genera Enterococcus, Capnocytophaga, and Polaribacter was significantly altered in obese patients with colorectal cancer, whose serum low‐density lipoprotein concentrations were positively correlated with the abundance of the genus Enterococcus; among the most abundant species was Enterococcus faecalis, observed at lower levels in obese versus nonobese patients.

Conclusions

This study demonstrated several compositional alterations of the gut microbiome in patients with colorectal cancer and showed that a reduced presence of E. faecalis may be associated with obesity‐related colorectal cancer development. The gut microbiome may provide novel insights into the potential mechanisms in obesity‐related colorectal carcinogenesis.

Subgingival microbiota in overweight and obese young adults with no destructive periodontal disease

BACKGROUND

This study analyzed the levels of a specific group of periodontal health/disease-related oral bacteria in the subgingival biofilm of young adults with overweight (OW) and obesity (OB), and no destructive periodontal disease.

METHODS

Full-mouth periodontal assessment and subgingival biofilm sampling were performed in individuals with normal weight (NW) (BMI [body mass index] ≥18.5 to ≤24.9 kg/m² ; n = 29), OW (BMI ≥25 to ≤29.9 kg/m² ; n = 26), or OB (BMI ≥30 kg/m² ; n = 22). BMI, waist (WC) and hip (HC) circumferences, and waist-hip ratio (WHR) were established for every individual. Biofilm samples were analyzed by checkerboard. Spearman coefficient, linear, and logistic regression analyses were obtained.

RESULTS

Gingivitis was detected in 45% NW, 65% OW, and 73% OB individuals. NW patients presented significantly less calculus and supragingival biofilm than OB. OW, and OB individuals had significantly higher levels of Porphyromonas gingivalis and Tannerella forsythia than NW patients (P <0.05). Treponema denticola correlated with BMI (rho = 0.31), WC (rho = 0.28), and HC (rho = 0.29), P≤0.01. Linear regression analysis showed significant (P <0.05) positive associations between BMI, WC, HC, and WHR indicators and Prevotella spp., Lactobacillus spp., V. parvula, and A. actinomycetemcomitans (Aa); negative associations were found between Capnocytophaga spp., WC, and HC (β = -0.29 and β = -0.37, respectively; P <0.01). However, the interaction of Prevotella spp. and T. forsythia decreased the likelihood of an individual to be diagnosed as OW/OB (OR 0.183 [95% CI, 0.062-0.540]).

CONCLUSIONS

Few periodontal pathogens differed in levels between NW and OW/OB individuals without destructive periodontal disease. Moreover, Aa, T. denticola, and Prevotella spp. were associated with clinical parameters of obesity.

Screening for prevalence and abundance of Capnocytophaga spp by analyzing NGS data: A scoping review

BACKGROUND

Capnocytophaga spp. are commensal bacteria of the oral cavity and constitute a genus of the core microbiome.

OBJECTIVE

This genus is responsible for many local and systemic conditions in both the immunocompetent and immunocompromised patients, but its beneficial or deleterious role in the microbiota has been little explored.

DESIGN

Online databases were used to identify papers published from 1999 to 2019 based on next-generation sequencing (NGS) data to study comparative trials. Work using other identification methods, case reports, reviews, and non-comparative clinical trials was excluded.

RESULTS AND CONCLUSION

We selected 42 papers from among 668 publications. They showed a link between the abundance of Capnocytophaga spp. in the oral microbiota and various local pathologies (higher for gingivitis and halitosis; lower in active smokers, etc.) or systemic diseases (higher for cancer and carcinomas, IgA nephropathy, etc.). After discussing the limits inherent to the NGS techniques, we present several technical and biological hypotheses to explain the diversity of results observed between studies, as well as the links between the higher or lower abundance of Capnocytophaga spp and the appearance of local or systemic conditions and diseases.

Biomarkers in biological fluids in adults with periodontitis and/or obesity: A meta-analysis

Obesity and periodontal diseases have been investigated to be interconnected, but the molecular mechanism underlying this association is still not clear. The aim of this systematic review is to assess the association of serum, salivary and gingival crevicular fluid (GCF) inflammatory markers (IMs), obesity, and periodontitis. Studies that evaluated IM of adults according to obesity status (O) and periodontitis status (P) (O+P+; O-P+; O+P-) were screened on several electronic databases and grey literature up until February 2019. Risk of bias assessment and level of evidence were evaluated through Fowkes and Fulton scale and Grading of Recommendations Assessment, Development and Evaluation (GRADE). Meta-analyses were grouped according to the biological matrix studied (serum/GCF) and groups (O+P+ vs. O−P+/O+P+ vs. O+P−). Out of the 832 studies screened, 21 were considered in qualitative synthesis and 15 in quantitative synthesis (meta-analysis). Although included studies showed mostly “no” or “minor” problems during the quality assessment, GRADE assessment indicated very low to moderate level of evidence based on the question answered. O+P+ adults exhibited significantly higher serum levels of C-reactive protein (CRP), interleukin 6 (IL-6), leptin, and tumor necrosis factor-α (TNF-alpha) and higher resistin GCF levels than O−P+. O+P+ adults showed significantly higher serum levels of IL-6 and leptin and lower adiponectin serum levels than O+P−. Only qualitative information could be obtained of the IM vaspin, omentin-1, chemerin, IL-10, progranulin, MCP-4, IL-1β, and interferon-γ (IFN-γ). Obesity and periodontitis, together or separately, are associated with altered serum and GCF levels of CRP, IL-6, leptin, TNF-alpha, adiponectin, and resistin. It was not possible to evaluate the association between obesity and periodontitis at salivary levels. The role of recently investigated biomarkers as vaspin, omentin-1, chemerin, IL-10, progranulin, MCP-4, IL-1β, and IFN-γ, which can be key points underlying the association between obesity and periodontitis, remains to be further investigated.

Metatranscriptomic analysis to define the Secrebiome, and 16S rRNA profiling of the gut microbiome in obesity and metabolic syndrome of Mexican children

Background

In the last decade, increasing evidence has shown that changes in human gut microbiota are associated with diseases, such as obesity. The excreted/secreted proteins (secretome) of the gut microbiota affect the microbial composition, altering its colonization and persistence. Furthermore, it influences microbiota-host interactions by triggering inflammatory reactions and modulating the host's immune response. The metatranscriptome is essential to elucidate which genes are expressed under diseases. In this regard, little is known about the expressed secretome in the microbiome. Here, we use a metatranscriptomic approach to delineate the secretome of the gut microbiome of Mexican children with normal weight (NW) obesity (O) and obesity with metabolic syndrome (OMS). Additionally, we performed the 16S rRNA profiling of the gut microbiota.

Results

Out of the 115,712 metatranscriptome genes that codified for proteins, 30,024 (26%) were predicted to be secreted, constituting the Secrebiome of the gut microbiome. The 16S profiling confirmed an increased abundance in Firmicutes and decreased in Bacteroidetes in the obesity groups, and a significantly higher richness and diversity than the normal weight group. We found novel biomarkers for obesity with metabolic syndrome such as increased Coriobacteraceae, Collinsela, and Collinsella aerofaciens; Erysipelotrichaceae, Catenibacterium and Catenibacterium sp., and decreased Parabacteroides distasonis, which correlated with clinical and anthropometric parameters associated to obesity and metabolic syndrome. Related to the Secrebiome, 16 genes, homologous to F. prausniitzi, were overexpressed for the obese and 15 genes homologous to Bacteroides, were overexpressed in the obesity with metabolic syndrome. Furthermore, a significant enrichment of CAZy enzymes was found in the Secrebiome. Additionally, significant differences in the antigenic density of the Secrebiome were found between normal weight and obesity groups.

Conclusions

These findings show, for the first time, the role of the Secrebiome in the functional human-microbiota interaction. Our results highlight the importance of metatranscriptomics to provide novel information about the gut microbiome’s functions that could help us understand the impact of the Secrebiome on the homeostasis of its human host. Furthermore, the metatranscriptome and 16S profiling confirmed the importance of treating obesity and obesity with metabolic syndrome as separate conditions to better understand the interplay between microbiome and disease.

Hyperuricemia as a potential plausible risk factor for periodontitis

Elevated blood uric acid (UA) levels have been positively associated with the severity of periodontitis. It thus brings out a hypothesis that hyperuricemia, a pathological elevation of blood UA, might be a risk factor for periodontitis. Namely, periodontitis individuals with Hu might acquire more severe periodontal destruction compared to those without Hu. To support the hypothesis, four aspects of evidences are proposed. First, hyperuricemia and periodontitis share many metabolic and inflammatory comorbidities such as metabolic syndrome, diabetes and cardiovascular diseases which are commonly related to elevated UA levels and gout. Second, observational and interventional studies have found altered UA levels in blood and saliva in periodontitis patients or after periodontal treatment, suggesting an epidemiological connection between hyperuricemia and periodontitis. Third, plausible immuno-metabolic mechanisms by which hyperuricemia might promote the progression of periodontitis are suggested, such as impaired immune response, oxidative stress, pathological bone remodeling and dysbiosis. The last, our empirical data exhibited elevated UA levels in gingival tissue in periodontitis mice compared to controls. If the hypothesis is true, given the high prevalence of the two conditions, hyperuricemia would be a significant risk factor increasing the global burden of periodontal diseases. Evidences on a directional correlation between hyperuricemia and periodontitis are sparse. Longitudinal and experimental studies would be necessary to determine the magnitude of periodontal risk, if any, exacerbated by hyperuricemia and the underlying mechanisms.

Periodontal pathogens and clinical parameters in chronic periodontitis

The use of next generation sequencing and bioinformatics has revealed the complexity and richness of the human oral microbiota. While some species are well known for their periodontal pathogenicity, the molecular-based approaches for bacterial identification have raised awareness about new putative periodontal pathogens. Although they are found increased in case of periodontitis, there is currently a lack of data on their interrelationship with the periodontal measures. We processed the sequencing data of the subgingival microbiota of 75 patients with hemochromatosis and chronic periodontitis in order to characterize the well-described and newly identified subgingival periodontal pathogens. We used correlation tests and statistical models to assess the association between the periodontal pathogens and mean pocket depth, and to determine the most relevant bacterial biomarkers of periodontitis severity. Based on correlation test results, nine taxa were selected and included in the statistical models. The multiple linear regression models adjusted for systemic and periodontal clinical variables showed that mean pocket depth was negatively associated with Aggregatibacter and Rothia, and positively associated with Porphyromonas. Furthermore, a bacterial ratio that was previously described as a signature of dysbiosis in periodontitis (%Porphyromonas+%Treponema+%Tannerella)/(%Rothia+%Corynebacterium) was the most significant predictor. In this specific population, we found that the best model in predicting the mean pocket depth was microbial dysbiosis using the dysbiosis ratio taxa formula. While further studies are needed to assess the validity of these results on the general population, such a dysbiosis ratio could be used in the future to monitor the subgingival microbiota.

The gut microbiota to the brain axis in the metabolic control

The regulation of glycemia is under a tight neuronal detection of glucose levels performed by the gut-brain axis and an efficient efferent neuronal message sent to the peripheral organs, as the pancreas to induce insulin and inhibit glucagon secretions. The neuronal detection of glucose levels is performed by the autonomic nervous system including the enteric nervous system and the vagus nerve innervating the gastro-intestinal tractus, from the mouth to the anus. A dysregulation of this detection leads to the one of the most important current health issue around the world i.e. diabetes mellitus. Furthemore, the consequences of diabetes mellitus on neuronal homeostasis and activities participate to the aggravation of the disease establishing a viscious circle. Prokaryotic cells as bacteria, reside in our gut. The strong relationship between prokaryotic cells and our eukaryotic cells has been established long ago, and prokaryotic and eukaryotic cells in our body have evolved synbiotically. For the last decades, studies demonstrated the critical role of the gut microbiota on the metabolic control and how its shift can induce diseases such as diabetes. Despite an important increase of knowledge, few is known about 1) how the gut microbiota influences the neuronal detection of glucose and 2) how the diabetes mellitus-induced gut microbiota shift observed participates to the alterations of autonomic nervous system and the gut-brain axis activity.

Subgingival Microbiota of Mexicans with Type 2 Diabetes with Different Periodontal and Metabolic Conditions

BACKGROUND

Type-2-Diabetes (T2D) and Periodontitis are major inflammatory diseases. However, not much is known about the specific subgingival microbiota in Mexicans with diabetes and metabolic dysbiosis. The aim of this study was to describe the subgingival microbiota of Mexicans with T2D and the different periodontal and metabolic conditions, through "Checkerboard" DNA-DNA hybridization.

METHODS

Subjects were divided into two groups-periodontal-health (PH) (PH_non-T2D; n = 59, PH_T2D; n = 14) and generalized-periodontitis (GP) (GP_non-T2D; n = 67, GP_T2D; n = 38). Obesity (BMI ≥ 30 kg/m2) and serum levels of glycated-hemoglobin (HbA1c), total-lipids, triglycerides, total-cholesterol, high-density-lipids, and low-density-lipids were measured for the T2D individuals. Subgingival microbial identification was processed for 40 species through DNA-probes.

RESULTS

Subjects with T2D harbored significantly higher mean total levels (PH: p < 0.001, and GP_NS), a lower proportion of "red" complex (GP: p < 0.01), a higher proportion of "yellow" (GP; p < 0.001), and "orange" (GP; p < 0.01) complex than the non-T2D. GP_T2D individuals exhibited a greater proportion of putative-species-Campylobacter gracilis and S. constellatus (p < 0.001), and Parvimonas micra and Prevotella nigrescens (p < 0.01), than GP_non-T2D. T2D individuals with HbA1c > 8% had presented significantly higher mean pocket-depth and higher levels of G. morbillorum (p < 0.05) and those with obesity or dyslipidemia harbored higher levels, prevalence, or proportion of Streptococcus sp., Actinomyces sp., and Capnocytophaga sp.

CONCLUSIONS

T2D individuals harbored a particular microbial profile different to non-T2D microbiota. Metabolic control was related to dysbiosis of microbiota-HbA1c>8% related to periodontitis and obesity or dyslipidemia with the predominance of saccharolytic bacteria, irrespective of their periodontal condition.

Obesity alters composition and diversity of the oral microbiota in patients with type 2 diabetes mellitus independently of glycemic control

Background and objective

The involvement of the oral microbiota as a possible link between periodontitis, type 2 diabetes mellitus and obesity is still not well understood. The objective of the study was to investigate if glycemic control and obesity play a role in modulating the composition and diversity of the oral microbial ecology.

Material and methods

A cohort of patients with type 2 diabetes mellitus (n = 18) was recruited. Participants demonstrating improved glycemic control after 3 months (n = 6) were included in a second examination. A full mouth examination was performed to estimate periodontitis severity followed by sample collection (subgingival plaque and saliva). Generation of large sequence libraries was performed using the high-throughput Illumina MiSeq sequencing platform.

Results

The majority of participants (94.4%, n = 17) presented with moderate or severe forms of periodontitis. Differences in microbial composition and diversity between obese (BMI ≥ 30 kg/m²) and non-obese (BMI < 30 kg/m²) groups were statistically significant. Cross-sectional and longitudinal approaches failed to reveal statistically significant associations between HbA_1c level and species composition or diversity.

Conclusions

Obesity was significantly associated with the oral microbial composition. The impact of glycemic control on oral microbiota, however, could not be assured statistically.

Genetic Association with Subgingival Bacterial Colonization in Chronic Periodontitis

Chronic periodontitis is the most prevalent form of inflammatory destructive bone disease and has been affecting humans since antiquity. Evidence suggest that genetic factors can highly influence periodontitis risk, modulating disease elements such as the susceptibility to microbial colonization and the nature of subsequent host-microbe interaction. Several single-nucleotide polymorphisms (SNPs) have been associated with the occurrence of periodontitis, but the full range of genetic influence in periodontitis outcomes remains to be determined. In this context, this study comprises an analysis of possible correlation between periodontitis-related genetic variants with changes in the subgingival microbiological pattern performed in a Brazilian population (n = 167, comprising 76 chronic periodontitis patients and 91 healthy subjects). For the genetic characterization, 19 candidate SNPs were selected based on the top hits of previous large genome wide association studies (GWAS), while the subgingival microbiota was characterized for the presence and relative quantity of 40 bacterial species by DNA-DNA checkerboard. The case/control association test did not demonstrate a significant effect of the target SNPs with the disease phenotype. The polymorphism rs2521634 proved significantly associated with Tannerella forsythia, Actinomyces gerencseriae, Fusobacterium periodonticum, and Prevotella nigrescens; rs10010758 and rs6667202 were associated with increased counts of Porphyromonas gingivalis; and rs10043775 proved significantly associated with decreased counts of Prevotella intermedia. In conclusion, we present strong evidence supporting a direct connection between the host’s genetic profile, specifically rs2521634, rs10010758, rs6667202, and rs10043775 polymorphisms, and the occurrence of chronic periodontitis-associated bacteria.