Smoking-induced subgingival dysbiosis precedes clinical signs of periodontal disease

Tamashiro, Ryan; Strange, Leah; Schnackenberg, Kristin; Santos, Janelle; Gadalla, Hana; Zhao, Lisa; Li, Eric C.; Hill, Emilie; Hill, Brett; Sidhu, G. S.; Kirst, Mariana E.; Walker, Clay; Wang, Gary P.

doi:10.1038/s41598-023-30203-z

Cited by 4 publications

(3 citation statements)

References 37 publications

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“…The balanced gender representation is crucial, considering emerging evidence suggesting gender-based differences in the oral microbiome [ 11 ]. Smoking and antibiotic use history, common confounding factors, are well-documented contributors to dysbiosis and periodontal diseases [ 12 , 13 ].…”

Section: Discussionmentioning

confidence: 99%

Exploring the Microbiome Landscape of Dental Plaque: A Cross-Sectional Analysis in Periodontal Health and Disease

Boyapati,

Lanke,

Mudaliyar

et al. 2024

Cureus

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Objective: This study aimed to comprehensively analyze the microbiome of dental plaque in individuals with varying periodontal statuses, encompassing both periodontal health and disease. The primary objectives were to identify microbial markers associated with different clinical conditions, explore variations in microbial diversity, and investigate potential correlations between the oral microbiome and clinical parameters. Methods: A cross-sectional design was employed, involving 164 participants aged 18 to 65 years. Inclusion criteria comprised individuals with good oral and systemic health for the periodontal health group and those diagnosed with various stages of periodontal disease for the periodontal disease group. Dental plaque samples were meticulously collected from diverse tooth surfaces, and clinical examinations were conducted to assess periodontal health status. High-throughput sequencing of the 16S ribosomal RNA (rRNA) gene was utilized for microbiome analysis. Results: Demographic characteristics revealed a balanced distribution between the periodontal health and disease groups. Clinical parameters, including probing depth, clinical attachment loss, and bleeding on probing, exhibited significant differences between the two groups (p < 0.001). Microbial diversity indices indicated a higher diversity in the periodontal health group compared to the disease group (p < 0.001). Analysis of relative abundance of bacterial phyla identified significant variations, with Firmicutes, Bacteroidetes, and Actinobacteria showing differential prevalence between health and disease (p < 0.05). Differentially abundant taxa analysis highlighted specific species associated with each clinical condition, including Prevotella intermedia and Porphyromonas gingivalis. Network analysis revealed complex microbial interactions within the oral microbiome. Functional predictions indicated variations in metabolic capabilities between health and disease, with potential implications for virulence and antibiotic resistance. Conclusion: This study provides a comprehensive analysis of the oral microbiome in periodontal health and disease, revealing significant associations between microbial composition and clinical parameters. The identification of microbial markers and functional insights enhances our understanding of the complex interplay within the oral ecosystem. These findings hold promise for advancing diagnostic and therapeutic approaches tailored to individual microbial profiles.

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Section: Discussionmentioning

confidence: 99%

Exploring the Microbiome Landscape of Dental Plaque: A Cross-Sectional Analysis in Periodontal Health and Disease

Boyapati,

Lanke,

Mudaliyar

et al. 2024

Cureus

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“…Alveolar bone resorption caused by periodontitis is the leading cause of tooth loss in adults. The key to the treatment of periodontitis is to inhibit bacterial inflammation on the one hand and promote the regeneration of periodontal tissue on the other hand [ 33 ]. Several techniques for reconstructing bones have been employed in the restoration of maxillofacial abnormalities.…”

Section: Discussionmentioning

confidence: 99%

Inhibition of ZDHHC16 promoted osteogenic differentiation and reduced ferroptosis of dental pulp stem cells by CREB

Liu,

Yu,

Zhou

et al. 2024

BMC Oral Health

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Background The repair of bone defects caused by periodontal diseases is a difficult challenge in clinical treatment. Dental pulp stem cells (DPSCs) are widely studied for alveolar bone repair. The current investigation aimed to examine the specific mechanisms underlying the role of Zinc finger DHHC-type palmitoyl transferases 16 (ZDHHC16) in the process of osteogenic differentiation (OD) of DPSCs. Methods The lentiviral vectors ZDHHC16 or si-ZDHHC16 were introduced in the DPSCs and then the cells were induced by an odontogenic medium for 21 days. Subsequently, Quantitate Polymerase Chain Reaction (PCR), immunofluorescent staining, proliferation assay, ethynyl deoxyuridine (EdU) staining, and western blot analysis were used to investigate the specific details of ZDHHC16 contribution in OD of DPSCs. Results Our findings indicate that ZDHHC16 exhibited a suppressive effect on cellular proliferation and oxidative phosphorylation, while concurrently inducing ferroptosis in DPSCs. Moreover, the inhibition of ZDHHC16 promoted cell development and OD and reduced ferroptosis of DPSCs. The expression of p-CREB was suppressed by ZDHHC16, and immunoprecipitation (IP) analysis revealed that ZDHHC16 protein exhibited interconnection with cAMP-response element binding protein (CREB) of DPSCs. The CREB suppression reduced the impacts of ZDHHC16 on OD and ferroptosis of DPSCs. The activation of CREB also reduced the influences of si-ZDHHC16 on OD and ferroptosis of DPSCs. Conclusions These findings provide evidences to support a negative association between ZDHHC16 and OD of DPSCs, which might be mediated by ferroptosis of DPSCs via CREB.

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“…Many studies have sought to measure the overall stability of the microbiome using a cross-sectional study design [11][12][13][14][15]. However, cross-sectional studies have their limitations, including a lack of ability to account for the noise introduced by microbiomes changing over time.…”

Section: Introductionmentioning

confidence: 99%

MD3F: Multivariate Distance Drift Diffusion Framework for High-Dimensional Datasets

Zielinski,

Corby,

Alekseyenko

2024

Genes

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High-dimensional biomedical datasets have become easier to collect in the last two decades with the advent of multi-omic and single-cell experiments. These can generate over 1000 measurements per sample or per cell. More recently, focus has been drawn toward the need for longitudinal datasets, with the appreciation that important dynamic changes occur along transitions between health and disease. Analysis of longitudinal omics data comes with many challenges, including type I error inflation and corresponding loss in power when thousands of hypothesis tests are needed. Multivariate analysis can yield approaches with higher statistical power; however, multivariate methods for longitudinal data are currently limited. We propose a multivariate distance-based drift-diffusion framework (MD3F) to tackle the need for a multivariate approach to longitudinal, high-throughput datasets. We show that MD3F can result in surprisingly simple yet valid and powerful hypothesis testing and estimation approaches using generalized linear models. Through simulation and application studies, we show that MD3F is robust and can offer a broadly applicable method for assessing multivariate dynamics in omics data.

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Smoking-induced subgingival dysbiosis precedes clinical signs of periodontal disease

Cited by 4 publications

References 37 publications

Exploring the Microbiome Landscape of Dental Plaque: A Cross-Sectional Analysis in Periodontal Health and Disease

Exploring the Microbiome Landscape of Dental Plaque: A Cross-Sectional Analysis in Periodontal Health and Disease

Inhibition of ZDHHC16 promoted osteogenic differentiation and reduced ferroptosis of dental pulp stem cells by CREB

MD3F: Multivariate Distance Drift Diffusion Framework for High-Dimensional Datasets

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