Impact of smoking on cost-effectiveness of 10-48 years of periodontal care.

The study aims were (1) to explore whether "periodontal treatment" consisting of surgical therapy (flap, resective, or regenerative) or scaling and root planing treatment with long-term periodontal maintenance treatment, is cost-effective in terms of preventing periodontitis-attributable tooth extraction and replacement by implant-supported crowns ("extraction/replacement"); (2) to assess the effect of cigarette smoking on this cost-effectiveness. Data for this observational retrospective study were collected from dental charts of patients who had received periodontal therapy and at least annual follow-up visits for >10 years were analyzed by linear regression generalized estimating equations and generalized linear models. Among 399 adults (199 males, 200 females), those with the least mean annual treatment cost experienced the greatest mean annual costs for extraction/replacement, indicating general cost-effectiveness. Cigarette smoking adversely impacted this cost-effectiveness, with current heavy smokers experiencing no cost-effectiveness. Former smokers with Grade C periodontitis benefitted most, whereas smoking did not influence cost-effectiveness for Grade B periodontitis. Assessed by mean annual costs of "extraction/replacement," periodontal treatment was cost-effective, which decreased in a dose-response manner by former and current smoking intensity. Cigarette smoking should be factored into treatment planning and cost-effective analyses of periodontal treatment. Smoking cessation should be encouraged.

Performance of three artificial intelligence (AI)-based large language models in standardized testing; implications for AI-assisted dental education.

INTRODUCTION: The emerging rise in novel computer technologies and automated data analytics has the potential to change the course of dental education. In line with our long-term goal of harnessing the power of AI to augment didactic teaching, the objective of this study was to quantify and compare the accuracy of responses provided by ChatGPT (GPT-4 and GPT-3.5) and Google Gemini, the three primary large language models (LLMs), to human graduate students (control group) to the annual in-service examination questions posed by the American Academy of Periodontology (AAP). METHODS: Under a comparative cross-sectional study design, a corpus of 1312 questions from the annual in-service examination of AAP administered between 2020 and 2023 were presented to the LLMs. Their responses were analyzed using chi-square tests, and the performance was juxtaposed to the scores of periodontal residents from corresponding years, as the human control group. Additionally, two sub-analyses were performed: one on the performance of the LLMs on each section of the exam; and in answering the most difficult questions. RESULTS: ChatGPT-4 (total average: 79.57%) outperformed all human control groups as well as GPT-3.5 and Google Gemini in all exam years (p < .001). This chatbot showed an accuracy range between 78.80% and 80.98% across the various exam years. Gemini consistently recorded superior performance with scores of 70.65% (p = .01), 73.29% (p = .02), 75.73% (p < .01), and 72.18% (p = .0008) for the exams from 2020 to 2023 compared to ChatGPT-3.5, which achieved 62.5%, 68.24%, 69.83%, and 59.27% respectively. Google Gemini (72.86%) surpassed the average scores achieved by first- (63.48% ± 31.67) and second-year residents (66.25% ± 31.61) when all exam years combined. However, it could not surpass that of third-year residents (69.06% ± 30.45). CONCLUSIONS: Within the confines of this analysis, ChatGPT-4 exhibited a robust capability in answering AAP in-service exam questions in terms of accuracy and reliability while Gemini and ChatGPT-3.5 showed a weaker performance. These findings underscore the potential of deploying LLMs as an educational tool in periodontics and oral implantology domains. However, the current limitations of these models such as inability to effectively process image-based inquiries, the propensity for generating inconsistent responses to the same prompts, and achieving high (80% by GPT-4) but not absolute accuracy rates should be considered. An objective comparison of their capability versus their capacity is required to further develop this field of study.

Clinical, immunological and microbiological evaluation of experimental peri-implant mucositis and gingivitis in subjects with Grade C, stage III/IV periodontitis background.

AIM: To compare individuals with a periodontitis background (Grade C, stage III/IV-formerly generalized aggressive periodontitis) (H-GAP) with periodontally healthy subjects (H-Health) in terms of molecular changes (immunological/microbiological) accompanying experimental peri-implant mucositis and gingivitis. MATERIALS AND METHODS: H-GAP and control (H-Health) subjects were recruited, and experimental mucositis/gingivitis was induced around a single screw-retained implant and one contralateral tooth. Participants refrained from oral hygiene for 21 days in the selected areas, followed by professional prophylaxis and hygiene instructions for 21 days. Clinical parameters, immunological markers (multiplex analysis) and microbial data (16S rRNA gene sequencing) were collected at baseline, during induction (7, 14 and 21 days) and following remission (42 days). RESULTS: Clinically, no significant differences were observed between the groups (n = 10/each group) (H-GAP vs. H-Health) (p > .05, Mann-Whitney test) and the type of site (tooth vs. implant) (p > .05, Wilcoxon test) at the time of onset and resolution, or severity of gingival/mucosal inflammation. H-GAP displayed lower concentrations of the cytokines interleukin (IL)-1B, IL-4, IL-17, tumor necrosis factor-α and interferon-γ around implants than H-Health at baseline and during induction of mucositis (p < .05, Mann-Whitney test). In both groups, implants showed significantly higher inflammatory background at baseline and all subsequent visits when compared with teeth (p < .05, Wilcoxon test). Alpha and ß-diversity metrics showed a significant shift in the microbiome composition and abundances of core species during induction and resolution of peri-implant mucositis and gingivitis (p < .05, restricted maximum likelihood method of Shannon and Bray-Curtis indices, respectively). Differences were not significant for these parameters between the H-Health and H-GAP groups when the periodontal and peri-implant microbiomes were compared separately; however, at each time point, the peri-implant microbiome differed significantly from the periodontal microbiome. CONCLUSIONS: Within the limitations of this pilot study (e.g. low power), it can be concluded that different microbial shifts contribute to the onset and progression of inflammatory responses around teeth and implants and that history of periodontal disease experience plays an additional role in modulating the immune response of peri-implant and periodontal tissues to biofilm accumulation.

Microbiomics: Were we all wrong before?

Periodontal microbiology has historically been based on an "us against them" paradigm, one that focuses mainly on identifying microbes and viruses that cause disease. However, such a bottom-up approach limits our appreciation of the incredible diversity of this ecosystem and the essential ways in which microbial interactions contribute to health and homeostasis of the subgingival niche. Microbiomics-the science of collectively characterizing and quantifying molecules responsible for the structure, function, and dynamics of a microbial community-has enabled us to study these communities in their natural habitat, thereby revolutionizing our knowledge of host-associated microbes and reconceptualizing our definition of "human." When this systems-biology approach is combined with ecologic principles, it explicates the complex relationship that exist between microbiota and between them and us, the human. In this volume of Periodontology 2000, a group of 12 female scientists take the lead in investigating how metagenomics, genomics, metatranscriptomics, proteomics, metaproteomics, and metabolomics have achieved the following: (a) widened our view of the periodontal microbiome; (b) expanded our understanding of the evolution of the human oral microbiome; (c) shone a light on not just bacteria, but also other prokaryotic and eukaryotic members of the community; (d) elucidated the effects of anthropogenic behavior and systemic diseases on shaping these communities; and (e) influenced traditional patterns of periodontal therapeutics.

Probing periodontal microbial dark matter using metataxonomics and metagenomics.

Our view of the periodontal microbial community has been shaped by a century or more of cultivation-based and microscopic investigations. While these studies firmly established the infection-mediated etiology of periodontal diseases, it was apparent from the very early days that periodontal microbiology suffered from what Staley and Konopka described as the "great plate count anomaly", in that these culturable bacteria were only a minor part of what was visible under the microscope. For nearly a century, much effort has been devoted to finding the right tools to investigate this uncultivated majority, also known as "microbial dark matter". The discovery that DNA was an effective tool to "see" microbial dark matter was a significant breakthrough in environmental microbiology, and oral microbiologists were among the earliest to capitalize on these advances. By identifying the order in which nucleotides are arranged in a stretch of DNA (DNA sequencing) and creating a repository of these sequences, sequence databases were created. Computational tools that used probability-driven analysis of these sequences enabled the discovery of new and unsuspected species and ascribed novel functions to these species. This review will trace the development of DNA sequencing as a quantitative, open-ended, comprehensive approach to characterize microbial communities in their native environments, and explore how this technology has shifted traditional dogmas on how the oral microbiome promotes health and its role in disease causation and perpetuation.

Interventions to prevent periodontal disease in tobacco-, alcohol-, and drug-dependent individuals.

Substance abuse affects more than one sixth of the world's population. More importantly, the nature of the abuse and the type of addictive substances available to individuals is increasing exponentially. All substances with abusive potential impact both the human immuno-inflammatory system and oral microbial communities, and therefore play a critical role in the etiopathogenesis of periodontal diseases. Evidence strongly supports the efficacy of professionally delivered cessation counseling. Dentists, dental therapists, and hygienists are ideally placed to deliver this therapy, and to spearhead efforts to provide behavioral and pharmacologic support for cessation. The purpose of this review is to examine the biologic mechanisms underlying their role in disease causation, to understand the pharmacologic and behavioral basis for their habituation, and to investigate the efficacy of population-based and personalized interventions in prevention of periodontal disease.

Systemic Risk Factors for the Development of Periimplant Diseases.

PURPOSE: Although periimplantitis results from the tissue destructive effects of a dysbiotic periimplant microbiome, several factors may either contribute to the dysbiosis or influence the host response to this bacterial challenge and thereby increase the risk of disease. The goal of this narrative review is examine extrinsic factors that might increase the risk at both subject and site levels. MATERIALS AND METHODS: The PubMed (MEDLINE) database was searched for articles examining the influence of systemic conditions on periimplantitis or implant failure. Key search terms included "systemic," "medications," "periodontitis," "dental implant," "periimplantitis," "implant failure" and related terms. Manual searches were also performed for the following journals: Clinical Oral Implants Research, International Journal of Periodontics and Restorative Dentistry, Journal of Clinical Periodontology, International Journal of Oral and Maxillofacial Implants, Implant Dentistry, and Journal of Periodontology. The inclusion criteria were cohort studies and case-control studies with at least 10 participants per group and with at least 6 months of follow-up. RESULTS: Certain systemic diseases, medications, radiotherapy, and behavioral factors, such as oral hygiene and compliance with periodontal maintenance therapy, appear to significantly increase the risk of disease.

Site-level risk predictors of peri-implantitis: A retrospective analysis.

AIM: The goal of the present investigation was to identify site-level factors that might allow prognostication of individual implants in partially dentate patients with multiple non-splinted restorations. METHODS: We analysed clinical and radiographic characteristics of 222 non-splinted single implants in function for at least 5 years in 86 partially dentate individuals at the time of functional loading and at follow-up, with the outcome variable being peri-implantitis. Principal component analysis identified factors contributing to greatest variability and linear discriminant analysis coupled with Random Forest Classifier used to identify risk predictors. RESULTS: After controlling for patient-level factors, the following characteristics were associated with significantly increased risk for peri-implantitis: Periodontal disease on adjoining teeth at the time of restoration (Odds Ratio (OR): 8.0), implant placement at a depth of 6 mm or more in relation to the CEJ of adjacent tooth (OR: 8.5), asymmetric prosthesis (OR: 4.3), history of tooth loss due to periodontitis (OR: 2.4) and a mean baseline plaque index of 1.6 or more (OR: 7.9). CONCLUSIONS: Our findings suggest that a system that incorporates both subject level and implant-level factors is required to effectively prognosticate the success of individual implants.

Periodontitis: Consensus report of workgroup 2 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions.

A new periodontitis classification scheme has been adopted, in which forms of the disease previously recognized as "chronic" or "aggressive" are now grouped under a single category ("periodontitis") and are further characterized based on a multi-dimensional staging and grading system. Staging is largely dependent upon the severity of disease at presentation as well as on the complexity of disease management, while grading provides supplemental information about biological features of the disease including a history-based analysis of the rate of periodontitis progression; assessment of the risk for further progression; analysis of possible poor outcomes of treatment; and assessment of the risk that the disease or its treatment may negatively affect the general health of the patient. Necrotizing periodontal diseases, whose characteristic clinical phenotype includes typical features (papilla necrosis, bleeding, and pain) and are associated with host immune response impairments, remain a distinct periodontitis category. Endodontic-periodontal lesions, defined by a pathological communication between the pulpal and periodontal tissues at a given tooth, occur in either an acute or a chronic form, and are classified according to signs and symptoms that have direct impact on their prognosis and treatment. Periodontal abscesses are defined as acute lesions characterized by localized accumulation of pus within the gingival wall of the periodontal pocket/sulcus, rapid tissue destruction and are associated with risk for systemic dissemination.

From focal sepsis to periodontal medicine: a century of exploring the role of the oral microbiome in systemic disease.

The oral microbiome is established within a few minutes after birth and consists of stable multi-species communities that engage in a dynamic equilibrium with the host immune system. Dental caries, endodontic infections and periodontal diseases are bacterially driven diseases that are caused by dysbiotic microbiomes. Over a century ago, the focal infection theory implicated these infections in the aetiology of several systemic diseases, ranging from arthritis to neurodegenerative diseases. However, a lack of concrete evidence, combined with the urgency with which clinicians embraced this approach without regard for appropriate case selection, led to its demise within 30 years. In the last decade of the 20th century, the concept of periodontal medicine was introduced to explain the correlations that were being observed between periodontitis and cardiovascular disease, rheumatoid arthritis, Alzheimer's disease, pulmonary disease, pre-term delivery of low birth weight infants and metabolic disease. It was proposed that periodontal pathobionts played a causal role in the initiating or exacerbating certain diseases either by direct invasion or by stimulating a florid immune-inflammatory response that extended into the systemic circulation. This review will examine the strength of current evidence in establishing a causal link between oral pathobionts and systemic disease.

Bacterial community shifts during healing of palatal wounds: comparison of two graft harvesting approaches.

OBJECTIVES: The aim of this study was to investigate the postoperative healing and microbial profile of donor sites of routine and pre-wounded free gingival grafts (FGGs). METHODS: Ten volunteers, recruited into a split mouth study, had one side of the palate pre-wounded. Five days later, grafts were harvested from both the pre-wounded and the contra-lateral site (routine graft). Wound healing was assessed on postoperative day 3, 7, 14 and 21. Microbiological samples were collected at baseline, graft harvest and the aforementioned postoperative days, and analysed by terminal restriction fragment length polymorphism for bacterial community profiling. RESULTS: On postoperative day 14, 0% of routine and 40% of pre-wounded sites exhibited epithelial closure; 90% of routine and 30% of pre-wounded sites were painful on day 7. Microbial profiles differed significantly between routine and pre-wounded sites at graft harvest and postoperative days 3 and 7. The number of bacterial species increased from surgical intervention to closure. While the number of species in pre-wounded sites was similar from harvest to day 7, the number in routine sites increased. The Shannon diversity and equitability indices showed statistically significant differences between routine and pre-wounded sites for days 3 and 7. CONCLUSIONS: Pre-wounding FGG donor sites might accelerate the healing course and wounding the palate was associated with significant bacterial community shifts.

Exposure to a social stressor disrupts the community structure of the colonic mucosa-associated microbiota.

BACKGROUND: The microbiota of the mammalian gastrointestinal (GI) tract consists of diverse populations of commensal bacteria that interact with host physiological function. Dysregulating these populations, through exogenous means such as antibiotics or dietary changes, can have adverse consequences on the health of the host. Studies from laboratories such as ours have demonstrated that exposure to psychological stressors disrupts the population profile of intestinal microbiota. To date, such studies have primarily focused on prolonged stressors (repeated across several days) and have assessed fecal bacterial populations. It is not known whether shorter stressors can also impact the microbiota, and whether colonic mucosa-associated populations can also be affected. The mucosa-associated microbiota exist in close proximity to elements of the host immune system and the two are tightly interrelated. Therefore, alterations in these populations should be emphasized. Additionally, stressors can induce differential responses in anxiety-like behavior and corticosterone outputs in variant strains of mice. Thus, whether stressor exposure can have contrasting effects on the colonic microbiota in inbred C57BL/6 mice and outbred CD-1 mice was also examined. RESULTS: In the present study, we used high throughput pyrosequencing to assess the effects of a single 2-hour exposure to a social stressor, called social disruption (SDR), on colonic mucosa-associated microbial profiles of C57BL/6 mice. The data indicate that exposure to the stressor significantly changed the community profile and significantly reduced the relative proportions of two genera and one family of highly abundant intestinal bacteria, including the genus Lactobacillus. This finding was confirmed using a quantitative real-time polymerase chain reaction (qPCR) technique. The use of qPCR also identified mouse strain-specific differences in bacterial abundances. L. reuteri, an immunomodulatory species, was decreased in stressor-exposed CD-1 mice, but not C57BL/6 mice. CONCLUSIONS: These data illustrate that stressor exposure can affect microbial populations, including the lactobacilli, that are closely associated with the colonic mucosa. Because the lactobacilli can have beneficial effects on human health, stressor-induced reductions of their population could have important health implications.

Placental TLR recognition of salivary and subgingival microbiota is associated with pregnancy complications.

BACKGROUND: Pre-term birth, the leading cause of neonatal mortality, has been associated with maternal periodontal disease and the presence of oral pathogens in the placenta. However, the mechanisms that underpin this link are not known. This investigation aimed to identify the origins of placental microbiota and to interrogate the association between parturition complications and immune recognition of placental microbial motifs. Video Abstract METHODS: Saliva, plaque, serum, and placenta were collected during 130 full-term (FT), pre-term (PT), or pre-term complicated by pre-eclampsia (PTPE) deliveries and subjected to whole-genome shotgun sequencing. Real-time quantitative PCR was used to measure toll-like receptors (TLR) 1-10 expression in placental samples. Source tracking was employed to trace the origins of the placental microbiota. RESULTS: We discovered 10,007 functionally annotated genes representing 420 taxa in the placenta that could not be attributed to contamination. Placental microbial composition was the biggest discriminator of pregnancy complications, outweighing hypertension, BMI, smoking, and maternal age. A machine-learning algorithm trained on this microbial dataset predicted PTPE and PT with error rates of 4.05% and 8.6% (taxonomy) and 6.21% and 7.38% (function). Logistic regression revealed 32% higher odds of parturition complication (95% CI 2.8%, 81%) for every IQR increase in the Shannon diversity index after adjusting for maternal smoking status, maternal age, and gravida. We also discovered distinct expression patterns of TLRs that detect RNA- and DNA-containing antigens in the three groups, with significant upregulation of TLR9, and concomitant downregulation of TLR7 in PTPE and PT groups, and dense correlation networks between microbial genes and these TLRs. 70-82% of placental microbiota were traced to serum and thence to the salivary and subgingival microbiomes. The oral and serum microbiomes of PTPE and PT groups displayed significant enrichment of genes encoding iron transport, exosome, adhesion, quorum sensing, lipopolysaccharide, biofilm, and steroid degradation. CONCLUSIONS: Within the limits of cross-sectional analysis, we find evidence to suggest that oral bacteria might translocate to the placenta via serum and trigger immune signaling pathways capable of inducing placental vascular pathology. This might explain, in part, the higher incidence of obstetric syndromes in women with periodontal disease.

Sex and the subgingival microbiome: do female sex steroids affect periodontal bacteria?

Fluctuations in the levels of sex steroid hormones begin at menarche and end with menopause in the human female. The association between gingivitis and increases in systemic sex steroids has been extensively reported and the biological mechanisms underlying this florid inflammatory state have been examined over several decades. The purpose of this review is to critically examine the evidence in the literature on the effect of female sex steroids on oral bacterial communities.

Oral microbiota and systemic disease.

It is well known that bacteria are the primary cause of infectious diseases, however, evidence is emerging that these organisms are also indirectly responsible for several diseases including cancer and rheumatoid arthritis. The oral cavity is home to several million bacteria that can cause two major diseases-periodontitis and caries. The relationship between periodontopathic bacteria and systemic diseases has been explored for several years. The concept of the oral cavity as a source of distant infection has been debated for at least a century. This review will discuss the historic aspects of the development of the focal infection theory, the reasons for its demise, its re-emergence and current status.

Pyrosequencing reveals unique microbial signatures associated with healthy and failing dental implants.

AIM: Although it is established that peri-implantitis is a bacterially induced disease, little is known about the bacterial profile of peri-implant communities in health and disease. The purpose of the present investigation was to examine the microbial signatures of the peri-implant microbiome in health and disease. MATERIALS AND METHODS: Subgingival and submucosal plaque samples were collected from forty subjects with periodontitis, peri-implantitis, periodontal and peri-implant health and analysed using 16S pyrosequencing. RESULTS: Peri-implant biofilms demonstrated significantly lower diversity than subgingival biofilms in both health and disease, however, several species, including previously unsuspected and unknown organisms, were unique to this niche. The predominant species in peri-implant communities belonged to the genera Butyrivibrio, Campylobacter, Eubacterium, Prevotella, Selenomonas, Streptococcus, Actinomyces, Leptotrichia, Propionibacterium, Peptococcus, Lactococcus and Treponema. Peri-implant disease was associated with lower levels of Prevotella and Leptotrichia and higher levels of Actinomyces, Peptococcus, Campylobacter, non-mutans Streptococcus, Butyrivibrio and Streptococcus mutans than healthy implants. These communities also demonstrated lower levels of Prevotella, non-mutans Streptococcus, Lactobacillus, Selenomonas, Leptotrichia, Actinomyces and higher levels of Peptococcus, Mycoplasma, Eubacterium, Campylobacter, Butyrivibrio, S. mutans and Treponema when compared to periodontitis-associated biofilms. CONCLUSION: The peri-implant microbiome differs significantly from the periodontal community in both health and disease. Peri-implantitis is a microbially heterogeneous infection with predominantly gram-negative species, and is less complex than periodontitis.

Biome-microbiome interactions in peri-implantitis: A pilot investigation.

BACKGROUND: Dental implants replace missing teeth in at least 100 million people, yet over one million implants fail every year due to peri-implantitis, a bacterially induced inflammatory disease. Our ability to treat peri-implantitis is hampered by a paucity of information on host-microbiome interactions that underlie the disease. Here, we present the first open-ended characterization of transcriptional events at the mucosal-microbial interface in the peri-implant crevice. METHODS: We simultaneously sequenced microbial and human mRNA from five pairs of healthy and diseased implants from the same patient and used graph theoretics to examine correlations between microbial and host gene expression in the peri-implant crevice. RESULTS: We identified a transcriptionally active peri-implant microbiome surrounding healthy implants. Microbial genes encoding phenylalanine, tyrosine, and tryptophan biosynthesis, cysteine, methionine, arginine, proline, and histidine metabolism correlated to human genes encoding cell development, metabolism, morphogenesis, adhesion, gap junctions, cell-cell signaling, and immunoinflammatory pathways, suggesting a role for commensals in protecting epithelial integrity. In disease, we found 4- to 200-fold upregulation in microbial genes encoding biofilm thickness, heme transport and utilization, and Gram-negative cell membrane synthesis. These genes correlated with mucosal zinc finger proteins, apoptosis, membrane transport, inflammation, and cell-cell communication. CONCLUSIONS: Within the limitations of a small sample size, our data suggest that microbial dysbiosis in the peri-implant sulcus might promote abandonment of host-bacterial transactions that dictate health and instead drive a move towards chronic programming of a non-healing wound.

Predicted functional and taxonomic analysis of subgingival biofilm of Grade C periodontitis in young patients under maintenance therapy.

BACKGROUND: In Grade C periodontitis in young patients (PerioC-Y), the functional roles of the subgingival community after years of periodontal treatment are still underexplored. This study evaluated the taxonomic and predicted functional content of the subgingival microbiome of PerioC-Y patients under supportive periodontal therapy (SPT). METHODS: Clinical and microbiological data from subgingival biofilm were assessed from 10 PerioC-Y patients at two time points: at baseline and after 5.7 ± 1.3 years of SPT. This was compared with 15 patients without a history of periodontitis. The V1-V3 and V4-V5 regions of the 16S rRNA were sequenced using the Illumina Miseq. Microbial composition was evaluated by the core microbiome, and alpha- and beta-diversity. The microbiome functional content was predicted using Picrust2, and the gene differential abundance was analyzed with DESeq2. RESULTS: Clinical improvements were seen in PerioC-Y-SPT. Differences in ß-diversity between PerioC-Y and health were observed (health x PerioC-Y-baseline, P = 0.02; health x PerioC-Y-SPT, P = 0.05). Moreover, although ß-diversity did not statistically change between baseline and SPT in PerioC-Y, the microbial correlation evidenced increased Streptococcus and decreased Treponema network contributions during SPT. Based on predicted functional data, treatment induced a reduction in genes related to flagellar protein and signal transduction in PerioC-Y. However, compared with healthy individuals, some genes remained more highly abundant in PerioC-Y-SPT, such as quorum sensing and efflux pump transporters. CONCLUSION: Despite clinical improvements and a shift in taxonomic composition, the PerioC-Y patients' periodontal treatment was not enough to reach a similar microbiome to patients without disease experience. Some functional content in this biofilm remained altered in PerioC-Y regardless of disease control.

Tobacco smoking affects bacterial acquisition and colonization in oral biofilms.

Recent evidence suggests that smoking affects the composition of the disease-associated subgingival biofilm, yet little is known about its effects during the formation of this biofilm. The present investigation was undertaken to examine the contributions of smoking to the composition and proinflammatory characteristics of the biofilm during de novo plaque formation. Marginal and subgingival plaque and gingival crevicular fluid samples were collected from 15 current smokers and from 15 individuals who had never smoked (nonsmokers) following 1, 2, 4, and 7 days of undisturbed plaque formation. 16S rRNA gene cloning and sequencing were used for bacterial identification, and multiplex bead-based flow cytometry was used to quantify the levels of 27 immune mediators. Smokers demonstrated a highly diverse, relatively unstable initial colonization of both marginal and subgingival biofilms, with lower niche saturation than that seen in nonsmokers. Periodontal pathogens belonging to the genera Fusobacterium, Cardiobacterium, Synergistes, and Selenomonas, as well as respiratory pathogens belonging to the genera Haemophilus and Pseudomonas, colonized the early biofilms of smokers and continued to persist over the observation period, suggesting that smoking favors early acquisition and colonization of pathogens in oral biofilms. Smokers also demonstrated an early proinflammatory response to this colonization, which persisted over 7 days. Further, a positive correlation between proinflammatory cytokine levels and commensal bacteria was observed in smokers but not in nonsmokers. Taken together, the data suggest that smoking influences both the composition of the nascent biofilm and the host response to this colonization.