Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

High-Throughput Combined Analysis of Saliva Microbiota and Metabolomic Profile in Chinese Periodontitis Patients: A Pilot Study

The onset and progression of periodontitis involves complicated interactions between the dysbiotic oral microbiota and disrupted host immune-inflammatory response, which can be mirrored by the changes in salivary metabolites profile. This pilot study sought to examine the saliva microbiome and metabolome in the Chinese population by the combined approach of 16s rRNA sequencing and high-throughput targeted metabolomics to discover potential cues for host-microbe metabolic interactions. Unstimulated whole saliva samples were collected from eighteen Stage III and IV periodontitis patients and thirteen healthy subjects. Full-mouth periodontal parameters were recorded. The taxonomic composition of microbiota was obtained by 16s rRNA sequencing, and the metabolites were identified and measured by ultra-high performance liquid chromatography and mass spectrometry-based metabolomic analysis. The oral microbiota composition displayed marked changes where the abundance of 93 microbial taxa differed significantly between the periodontitis and healthy group. Targeted metabolomics identified 103 differential metabolites between the patients and healthy individuals. Functional enrichment analysis demonstrated the upregulation of protein digestion and absorption, histidine metabolism, and nicotinate and nicotinamide metabolism pathways in the dysbiotic microbiota, while the ferroptosis, tryptophan metabolism, glutathione metabolism, and carbon metabolism pathways were upregulated in the patients. Correlation analysis confirmed positive relationships between the clinical parameters, pathogen abundances, and disease-related metabolite levels. The integral analysis of the saliva microbiome and metabolome yielded an accurate presentation of the dysbiotic oral microbiome and functional alterations in host-microbe metabolism. The microbial and metabolic profiling of the saliva could be a potential tool in the diagnosis, prognosis evaluation, and pathogenesis study of periodontitis.

Mediating and moderating effects of plasma proteomic biomarkers on the association between poor oral health problems and incident dementia: The UK Biobank study

The plasma proteome can mediate poor oral health problems (POHP)'s link to incident dementia. We screened 37,269 UK Biobank participants 50-74 years old (2006-2010) for prevalent POHP, further tested against 1463 plasma proteins and incident dementia over up to 15 years of follow-up. Total effect (TE) of POHP-dementia through plasma proteomic markers was decomposed into pure indirect effect (PIE), interaction referent (INTREF), controlled direct effect (CDE), or mediated interaction (INTMED). POHP increased the risk of all-cause dementia by 17% (P < 0.05). Growth differentiation factor 15 (GDF15) exhibited the strongest mediating effects (PIE > 0, P < 0.001), explaining 28% the total effect of POHP on dementia, as a pure indirect effect. A first principal component encompassing top 4 mediators (GDF15, IL19, MMP12, and ACVRL1), explained 11% of the POHP-dementia effect as a pure indirect effect. Pathway analysis including all mediators (k = 173 plasma proteins) revealed the involvement of the immune system, signal transduction, metabolism, disease, and gene expression, while STRING analysis indicated that top mediators within the first principal component were also represented in the two largest proteomic clusters. The dominant biological GO pathway for the GDF15 cluster was GO:0007169 labeled as "transmembrane receptor protein tyrosine kinase signaling pathway." Dementia is linked to POHP mediated by GDF15 among several proteomic markers.

Opportunities offered by latent-based multiblock strategies to integrate biomarkers of chemical exposure and biomarkers of effect in environmental health studies

Modern environmental epidemiology benefits from a new generation of technologies that enable comprehensive profiling of biomarkers, including environmental chemical exposure and omic datasets. The integration and analysis of large and structured datasets to identify functional associations is constrained by computational challenges that cannot be overcome using conventional regression methods. Some extensions of Partial Least Squares (PLS) regression have been developed to efficently integrate multiple datasets, including Multiblock PLS (MB-PLS) and Sequential and Orthogonalized PLS; however, these approaches remain seldom applied in environmental epidemiology. To address that research gap, this study aimed to assess and compare the applicability of PLS-based multiblock models in an observational case study, where biomarkers of exposure to environmental chemicals and endogenous biomarkers of effect were simultaneously integrated to highlight biological links related to a health outcome. The methods were compared with and without sparsity coupling two metrics to support the variable selection: Variable Importance in Projection (VIP) and Selectivity Ratio (SR). The framework was applied to a case-study dataset mimicking the structure of 36 environmental exposure biomarkers (E-block), 61 inflammation biomarkers (M-block), and their relationships with the gestational age at delivery of 161 mother-infant pairs. The results showed an overall consistency in the selected variables across models, although some specific selection patterns were identified. The block-scaled concatenation-based approaches (e.g. MB-PLS) tended to select more variables from the E-block, while these methods were unable to identify certain variables in the M-block. Overall, the number of variables selected using the SR criterion was higher than using the VIP criterion, with lower predictive performances. The multiblock models coupled to VIP, appeared to be the methods of choice for identifying relevant variables with similar statistical performances. Overall, the use of multiblock PLS-based methods appears to be a good strategy to efficiently support the variable selection process in modern environmental epidemiology.

Application of omics technologies in cariology research: A critical review with bibliometric analysis

OBJECTIVES

To review the application of omics technologies in the field of cariology research and provide critical insights into the emerging opportunities and challenges.

DATA & SOURCES

Publications on the application of omics technologies in cariology research up to December 2022 were sourced from online databases, including PubMed, Web of Science and Scopus. Two independent reviewers assessed the relevance of the publications to the objective of this review.

STUDY SELECTION

Studies that employed omics technologies to investigate dental caries were selected from the initial pool of identified publications. A total of 922 publications with one or more omics technologies adopted were included for comprehensive bibliographic analysis. (Meta)genomics (676/922, 73 %) is the predominant omics technology applied for cariology research in the included studies. Other applied omics technologies are metabolomics (108/922, 12 %), proteomics (105/922, 11 %), and transcriptomics (76/922, 8 %).

CONCLUSION

This study identified an emerging trend in the application of multiple omics technologies in cariology research. Omics technologies possess significant potential in developing strategies for the detection, staging evaluation, risk assessment, prevention, and management of dental caries. Despite the numerous challenges that lie ahead, the integration of multi-omics data obtained from individual biological samples, in conjunction with artificial intelligence technology, may offer potential avenues for further exploration in caries research.

CLINICAL SIGNIFICANCE

This review presented a comprehensive overview of the application of omics technologies in cariology research and discussed the advantages and challenges of using these methods to detect, assess, predict, prevent, and treat dental caries. It contributes to steering research for improved understanding of dental caries and advancing clinical translation of cariology research outcomes.

Metabolomics analysis in saliva from periodontally healthy, gingivitis and periodontitis patients

OBJECTIVE

The aim of this study was to investigate metabolomics markers in the saliva of patients with periodontal health, gingivitis and periodontitis.

BACKGROUND

The use of metabolomics for diagnosing and monitoring periodontitis is promising. Although several metabolites have been reported to be altered by inflammation, few studies have examined metabolomics in saliva collected from patients with different periodontal phenotypes.

METHODS

Saliva samples collected from a total of 63 patients were analysed by nuclear magnetic resonance (NMR) followed by ELISA for interleukin (IL)-1β. The patient sample, well-characterised clinically, included periodontal health (n = 8), gingivitis (n = 19) and periodontitis (n = 36) cases, all non-smokers and not diabetic.

RESULTS

Periodontal diagnosis (healthy/gingivitis/periodontitis) was not associated with any salivary metabolites in this exploratory study. Periodontal staging showed nominal associations with acetoin (p = .030) and citrulline (p = .047). Among other investigated variables, the use of systemic antibiotics in the previous 3 months was associated with higher values of the amino acids taurine, glycine and ornithine (p = .002, p = .05 and p = .005, respectively, at linear regression adjusted for age, gender, ethnicity, body mass index and staging).

CONCLUSION

While periodontal staging was marginally associated with some salivary metabolites, other factors such as systemic antibiotic use may have a much more profound effect on the microbial metabolites in saliva. Metabolomics in periodontal disease is still an underresearched area that requires further observational studies on large cohorts of patients, aiming to obtain data to be used for clinical translation.

Cystatin SN (CST1) as a Novel Salivary Biomarker of Periodontitis

Identification of biomarkers could help in assessing periodontal health status and monitoring treatment outcomes. Therefore, the aim of this cross-sectional study was to identify potential innovative salivary biomarkers for the diagnosis of periodontitis using an untargeted proteomic approach. Forty-five healthy non-smoker participants diagnosed as having periodontally healthy conditions (H), severe periodontitis (P), and healthy but reduced periodontium after active periodontal treatment (T) were consecutively enrolled (15 per each group) in the study. A higher number of spots were identified in the proteome of unstimulated whole saliva collected from H and T subjects compared with P group, mainly within the range of 8-40 kDa. Protein spots of interest were analysed by MALDI-TOF-MS, allowing the identification of cystatin SN (CST1) isoform, as confirmed by Western blot. CST1 was markedly expressed in the H group, while it was absent in most P samples (p < 0.001). Interestingly, a distinct CST1 expression was observed in saliva from T patients. CST1 was negatively correlated with the percentage of pathological sites (p < 0.001) and was effective in discriminating active periodontitis from healthy periodontal status (whether H or T). Therefore, salivary CST1 may be a promising non-invasive biomarker for periodontal disease diagnosis and monitoring.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

Impact of peri-implantitis on the proteome biology of crevicular fluid: A pilot study

BACKGROUND

The proteome of the peri-implant crevicular fluid (PICF) has not been systematically investigated. The aim of the present study was to reveal the proteome biology of dental implants affected with peri-implantitis.

METHODS

Patients with at least one diseased implant were included (probing depth ≥6 mm, ≥3 mm peri-implant radiological bone loss). Using sterile paper strips, samples were collected from healthy implants (I), healthy teeth (T) and peri-implantitis affected implants (P). Proteome analysis was performed using liquid chromatography - tandem mass spectrometry (LC-MS/MS) and data independent acquisition, allowing the identification and quantification of human and bacterial proteins as well as semi-specific peptides.

RESULTS

A total of 38 samples from 14 patients were included in the study; 2332 different human proteins were identified across all samples. No differentially expressed proteins between T and I were found. Comparing P to I, 59 proteins were found upregulated and 31 downregulated in P with significance. Upregulated proteins included proinflammatory proteins such as immunoglobulins, dysferlin, and S100P, as well as antimicrobial proteins, for example, myeloperoxidase or azurocidin. Gene ontology analysis further revealed higher activity of immunological pathways. Proteolytic patterns indicated the activity of inflammatory proteins such as cathepsin G. A total of 334 bacterial proteins were identified and quantified. Peri-implantitis showed elevated proteolytic activity.

CONCLUSION

I and T share similarities in their proteome, while diseased implants deviate strongly from healthy conditions. The PICF proteome of peri-implantitis affected sites exhibits an inflammatory fingerprint, dominated by neutrophil activity when compared with healthy implants.

A review of statistical strategies to integrate biomarkers of chemical exposure with biomarkers of effect applied in omic-scale environmental epidemiology

Humans are exposed to a growing list of synthetic chemicals, some of them becoming a major public health concern due to their capacity to impact multiple biological endpoints and contribute to a range of chronic diseases. The integration of endogenous (omic) biomarkers of effect in environmental health studies has been growing during the last decade, aiming to gain insight on the potential mechanisms linking the exposures and the clinical conditions. The emergence of high-throughput omic platforms has raised a list of statistical challenges posed by the large dimension and complexity of data generated. Thus, the aim of the present study was to critically review the current state-of-the-science about statistical approaches used to integrate endogenous biomarkers in environmental-health studies linking chemical exposures with health outcomes. The present review specifically focused on internal exposure to environmental chemical pollutants, involving both persistent organic pollutants (POPs), non-persistent pollutants like phthalates or bisphenols, and metals. We identified 42 eligible articles published since 2016, reporting 48 different statistical workflows, mostly focused on POPs and using metabolomic profiling in the intermediate layer. The outcomes were mainly binary and focused on metabolic disorders. A large diversity of statistical strategies were reported to integrate chemical mixtures and endogenous biomarkers to characterize their associations with health conditions. Multivariate regression models were the most predominant statistical method reported in the published workflows, however some studies applied latent based methods or multipollutant models to overcome the specific constraints of omic or exposure of data. A minority of studies used formal mediation analysis to characterize the indirect effects mediated by the endogenous biomarkers. The principles of each specific statistical method and overall workflow set-up are summarized in the light of highlighting their applicability, strengths and weaknesses or interpretability to gain insight into the causal structures underlying the triad: exposure, effect-biomarker and outcome.

Qualitative and Quantitative Mass Spectrometry in Salivary Metabolomics and Proteomics

The metabolomics and proteomics analysis of saliva, an excellent biofluid that is a rich source of biological compounds, allows for the safe and frequent screening of drugs, their metabolites, and molecular biomarkers of various diseases. One of the most frequently used analytical methods in saliva analysis is liquid chromatography coupled with mass spectrometry (LC-MS) and tandem mass spectrometry. The low ionisation efficiency of some compounds and a complex matrix makes their identification by MS difficult. Furthermore, quantitative analysis by LC-MS frequently cannot be performed without isotopically labelled standards, which usually have to be specially synthesised. This review presented reports on qualitative and quantitative approaches in salivary metabolomics and proteomics. The purpose of this manuscript was to present the challenges, advances, and future prospects of mass spectrometry, both in the analysis of salivary metabolites and proteins. The presented review should appeal to those interested in the recent advances and trends in qualitative and quantitative mass spectrometry in salivary metabolomics and proteomics, which may facilitate a diagnostic accuracy, the evaluation of treatment efficacy, the early diagnosis of disease, and a forensic investigation of some unapproved drugs for any medical or dietary administration.

Periodontal disease metabolomics signatures from different biofluids: a systematic review

BACKGROUND

Periodontitis is resulted from a complex interaction between genetics and epigenetics, microbial factors, and the host response. Metabolomics analyses reflect both the steady-state physiological equilibrium of cells or organisms as well as their dynamic metabolic responses to environmental stimuli.

AIM OF REVIEW

This systematic review of the literature aimed to assess which low molecular weight metabolites are more often found in biological fluids of individuals with periodontitis compared to individuals with gingivitis or periodontal health.

KEY SCIENTIFIC CONCEPTS OF REVIEW

All the included studies employed untargeted analysis. One or more biological fluids were analyzed, including saliva (n = 14), gingival crevicular fluid (n = 6), mouthwash (n = 1), serum (n = 3) and plasma (n = 1). Fifty-six main metabolites related to periodontitis have been identified in at least two independent studies by NMR spectroscopy or MS-based metabolomics. Saliva was the main biological fluid sampled. It is noteworthy that 14 metabolites of the 56 detected were identified as main metabolites in all studies that sampled the saliva. The majority of metabolites found consistently among studies were amino acids, organic acids and derivates: acetate, alanine, butyrate, formate, GABA, lactate, propionate, phenylalanine and valine. They were either up- or down-regulated in the studies or this information was not mentioned. The main metabolic pathway was related to phenylalanine, tyrosine and tryptophan biosynthesis. Metabolites more frequently found in individuals with periodontitis were related to both the host and to microorganism responses. Future studies are needed, and they should follow some methodological standards to facilitate their comparison.

Effect of a Stannous Fluoride Dentifrice on Biofilm Composition, Gene Expression and Biomechanical Properties

An in situ study was conducted to examine the mode of action of a 0.454% stannous fluoride (SnF₂)-containing dentifrice in controlling the composition and properties of oral biofilm. Thirteen generally healthy individuals participated in the study. Each participant wore an intra-oral appliance over a 48-h period to measure differences in the resulting biofilm’s architecture, mechanical properties, and bacterial composition after using two different toothpaste products. In addition, metatranscriptomics analysis of supragingival plaque was conducted to identify the gene pathways influenced. The thickness and volume of the microcolonies formed when brushing with the SnF₂ dentifrice were dramatically reduced compared to the control 0.76% sodium monofluorophosphate (MFP)-containing toothpaste. Similarly, the biophysical and nanomechanical properties measured by atomic force microscopy (AFM) demonstrated a significant reduction in biofilm adhesive properties. Metatranscriptomic analysis identified pathways associated with biofilm formation, cell adhesion, quorum sensing, and N-glycosylation that are significantly downregulated with SnF₂. This study provides a clinically relevant snapshot of how the use of a stabilized, SnF₂ toothpaste formulation can change the spatial organization, nanomechanical, and gene expression properties of bacterial communities.

Metagenomic and Transcriptomic Analyses Reveal the Differences and Associations Between the Gut Microbiome and Muscular Genes in Angus and Chinese Simmental Cattle

Gut microbiome and heredity are two important factors affecting the intramuscular fat (IMF) of cattle, excluding age, sex, and nutrition. This study aimed at deciphering these two differences by analyzing the gut microbiome and intramuscular differentially expressed genes (DEGs) in the Angus and Chinese Simmental cattle. Feces and longissimus dorsi were collected from the two groups of animals (n = 20/group) for multiomics analysis. Angus holds a significantly higher diversity than Chinese Simmental, and the relative abundance of Roseburia, Prevotella, Coprococcus, etc., was obviously higher in Angus. Chinese Simmental had higher levels of isobutyrate, isovalerate, and valerate, although similar levels of acetate, propionate, and butyrate were observed for the two groups. The DEGs upregulated in Chinese Simmental were mainly involved in immune and inflammatory responses, while those in Angus were associated with the regulation of muscle system and myofibril. We finally identified 17 species, including Eubacterium rectale, etc., which were positively correlated to muscle and fat metabolism genes (MSTN, MYLPF, TNNT3, and FABP3/4) and illustrate the associations between them. Our study unveils the gut microbial differences and significant DEGs as well as their associations between the two breeds, providing valuable guidance for future mechanism research and development of intervention strategies to improve meat quality.

The Role of Candida albicans Virulence Factors in the Formation of Multispecies Biofilms With Bacterial Periodontal Pathogens

Periodontal disease depends on the presence of different microorganisms in the oral cavity that during the colonization of periodontal tissues form a multispecies biofilm community, thus allowing them to survive under adverse conditions or facilitate further colonization of host tissues. Not only numerous bacterial species participate in the development of biofilm complex structure but also fungi, especially Candida albicans, that often commensally inhabits the oral cavity. C. albicans employs an extensive armory of various virulence factors supporting its coexistence with bacteria resulting in successful host colonization and propagation of infection. In this article, we highlight various aspects of individual fungal virulence factors that may facilitate the collaboration with the associated bacterial representatives of the early colonizers of the oral cavity, the bridging species, and the late colonizers directly involved in the development of periodontitis, including the “red complex” species. In particular, we discuss the involvement of candidal cell surface proteins—typical fungal adhesins as well as originally cytosolic “moonlighting” proteins that perform a new function on the cell surface and are also present within the biofilm structures. Another group of virulence factors considered includes secreted aspartic proteases (Sap) and other secreted hydrolytic enzymes. The specific structure of the candidal cell wall, dynamically changing during morphological transitions of the fungus that favor the biofilm formation, is equally important and discussed. The non-protein biofilm-composing factors also show dynamic variability upon the contact with bacteria, and their biosynthesis processes could be involved in the stability of mixed biofilms. Biofilm-associated changes in the microbe communication system using different quorum sensing molecules of both fungal and bacterial cells are also emphasized in this review. All discussed virulence factors involved in the formation of mixed biofilm pose new challenges and influence the successful design of new diagnostic methods and the application of appropriate therapies in periodontal diseases.

Metabolomic Evaluation of Chronic Periodontal Disease in Older Adults

Periodontal disease is an infectious inflammatory disease related to the destruction of supporting tissues of the teeth, leading to a functional loss of the teeth. Inflammatory molecules present in the exudate are catalyzed and form different metabolites that can be identified and quantified. Thus, we evaluated the inflammatory exudate present in crevicular fluid to identify metabolic biological markers for diagnosing chronic periodontal disease in older adults. Research participants were selected from long-term institutions in Brazil. Participants were individuals aged 65 years or older, healthy, or with chronic periodontal disease. Gas chromatography/mass spectrometry was used to evaluate potential biomarkers in 120 crevicular fluid samples. We identified 969 metabolites in the individuals. Of these, 15 metabolites showed a variable importance with projection score > 1 and were associated with periodontal disease. Further analysis showed that among the 15 metabolites, two (5-aminovaleric acid and serine, 3TMS derivative) were found at higher concentrations in the crevicular fluid, indicating their potential diagnostic power for periodontal disease in older adults. Our findings indicated that some metabolites are present at high concentrations in the crevicular fluid in older adults with periodontal disease and can be used as biomarkers of periodontal disease.

The oral microbiome: Role of key organisms and complex networks in oral health and disease

States of oral health and disease reflect the compositional and functional capacities of, as well as the interspecies interactions within, the oral microbiota. The oral cavity exists as a highly dynamic microbial environment that harbors many distinct substrata and microenvironments that house diverse microbial communities. Specific to the oral cavity, the nonshedding dental surfaces facilitate the development of highly complex polymicrobial biofilm communities, characterized not only by the distinct microbes comprising them, but cumulatively by their activities. Adding to this complexity, the oral cavity faces near-constant environmental challenges, including those from host diet, salivary flow, masticatory forces, and introduction of exogenous microbes. The composition of the oral microbiome is shaped throughout life by factors including host genetics, maternal transmission, as well as environmental factors, such as dietary habits, oral hygiene practice, medications, and systemic factors. This dynamic ecosystem presents opportunities for oral microbial dysbiosis and the development of dental and periodontal diseases. The application of both in vitro and culture-independent approaches has broadened the mechanistic understandings of complex polymicrobial communities within the oral cavity, as well as the environmental, local, and systemic underpinnings that influence the dynamics of the oral microbiome. Here, we review the present knowledge and current understanding of microbial communities within the oral cavity and the influences and challenges upon this system that encourage homeostasis or provoke microbiome perturbation, and thus contribute to states of oral health or disease.

Morphological alterations, activity, mRNA fold changes, and aging changes before and after orthodontic force application in young and adult human-derived periodontal ligament cells

BACKGROUND

The response of periodontal ligament cells (PDLC) from adult subjects in comparison to those obtained from younger ones to mechanical forces has been a matter of interest recently because of induced senescent changes. This study evaluated and compared cell surface changes and activity, integrin beta 1, and β-actin mRNA fold changes as well as klotho protein secretion capabilities of PDLC from young and adult donors before and after subjecting to orthodontic forces.

METHODS

A total of 40 subjects with bimaxillary dentoalveolar protrusion requiring extraction of first premolars for orthodontic treatment were selected and divided into two groups. Force ranging from 80 to 90 g was applied to maxillary first premolars and extraction was carried out at two different time periods-pre-treatment (control group) and 28 days after force application (experimental group). Periodontal ligament was obtained, and cell surface changes and activity were observed with atomic force microscopy (AFM) and fluorescent tagging. mRNA fold change of integrin beta-1 and β-actin mRNA, as well as beta-galactosidase assay, was performed, and levels of klotho protein were evaluated.

RESULTS

AFM nanoindentation and fluorescent tagging indicated increased surface morphological changes in younger cells compared to adult ones. We observed a decrease in integrin beta 1 but an increase in β-actin mRNA levels in PDLC obtained from younger subjects compared to adults, while an increase was observed in SA-β-GAL from adult cells. The level of klotho protein was lower in adult cells in comparison to younger ones.

LIMITATIONS

Large sample studies are required to find out a variation in aging characteristics between young and adult PDLC.

CONCLUSIONS

The study observed significant differences between PDLC obtained from younger and adult subjects in response to orthodontic force application.

Metabolomics of gingival crevicular fluid to identify biomarkers for periodontitis: A systematic review with meta-analysis

The present systematic review aimed to examine periodontitis-specific biomarkers in the gingival crevicular fluid (GCF) that could have a diagnostic relevance, and to provide a qualitative assessment of the current literature. Metabolites are reliable indicators of pathophysiological statuses, and their quantification in the GCF can provide an outlook of the changes associated with periodontitis and have diagnostic value. Relevant studies identified from PubMed, Embase, Cochrane Library, and Scopus databases were examined to answer the following PECO question: "In systemically healthy individuals, can concentration of specific metabolites in the GCF be used to discriminate subjects with healthy periodontium (H) or gingivitis from patients with periodontitis (P) and which is the diagnostic accuracy?" Quality of included studies was rated using a modified version of the QUADOMICS tool. Meta-analysis was conducted whenever possible. After the screening of 1,554 titles, 15 studies were selected, with sample size ranging from 30 to 93 subjects. Eleven studies performed targeted metabolomics analysis and provided data for 10 metabolites. Among the most consistent markers, malondialdehyde levels were found higher in the P group compared with H group (SMD = 2.86; 95% CI: 1.64, 4.08). Also, a significant increase of 8-hydroxy-deoxyguanosine, 4-hydroxynonenal, and neopterin was detected in periodontally diseased sites, while glutathione showed an inverse trend. When considering data from untargeted metabolomic analysis in four studies, more than 40 metabolites were found significantly discriminant, mainly related to amino acids and lipids degradation pathways. Notably, only one study reported measures of diagnostic accuracy. Several metabolites were differentially expressed in GCF of subjects across different periodontal conditions, having a major potential for investigating periodontal pathophysiology and for site-specific diagnosis. Oxidative stress-related molecules, such as malondialdehyde and 8-hydroxy-deoxyguanosine, were the most consistently associated to periodontitis (PROSPERO CRD42020188482).

Environmental factors and periodontal microbiome

Periodontal diseases are chronic inflammatory, multifactorial diseases where the major triggering factors for disease onset are bacteria and their toxins, but the major part of tissue destruction occurs as a result of host response towards the periodontal microbiome. Periodontal microbiome consists of a wide range of microorganisms including obligate and facultative anaerobes. In health, there is a dynamic balance between the host, environment, and the microbiome. Environmental factors, mainly tobacco smoking and psychological stress, disrupt the symbiotic relationship. Tobacco smoke and its components alter the bacterial surface and functions such as growth. Psychological stressors and stress hormones may affect the outcome of an infection by changing the virulence factors and/or host response. This review aims to provide currently available data on the effects of the major environmental factors on the periodontal microbiome.

An Evidence-Based Update on the Molecular Mechanisms Underlying Periodontal Diseases

Several investigators have reported about the intricate molecular mechanism underlying periodontal diseases (PD). Nevertheless, the role of specific genes, cells, or cellular mechanisms involved in the pathogenesis of periodontitis are still unclear. Although periodontitis is one of the most prevalent oral diseases globally, there are no pre-diagnostic markers or therapeutic targets available for such inflammatory lesions. A pivotal role is played by pro- and anti-inflammatory markers in modulating pathophysiological and physiological processes in repairing damaged tissues. In addition, effects on osteoimmunology is ever evolving due to the ongoing research in understanding the molecular mechanism lying beneath periodontal diseases. The aim of the current review is to deliver an evidence-based update on the molecular mechanism of periodontitis with a particular focus on recent developments. Reports regarding the molecular mechanism of these diseases have revealed unforeseen results indicative of the fact that significant advances have been made to the periodontal medicine over the past decade. There is integrated hypothesis-driven research going on. Although a wide picture of association of periodontal diseases with immune response has been further clarified with present ongoing research, small parts of the puzzle remain a mystery and require further investigations.

The Nexus Between Periodontal Inflammation and Dysbiosis

The nexus between periodontal inflammation and the polymicrobial biofilm in the gingival sulcus is critical to understanding the pathobiology of periodontitis. Both play a major role in the etiology and pathogenesis of periodontal diseases and each reinforces the other. However, this nexus is also at the center of a significant conundrum for periodontology. For all mucosal polymicrobial biofilms, the most confounding issue is the paradoxical relationship between inflammation, infection, and disease. Despite significant advances made in both periodontal microbiology and periodontal pathobiology, the issue of which comes first, the inflammatory response or the change to a dysbiotic subgingival microbiota, is still debated. In this paper, we present a model for the pathogenesis of periodontitis based on the central role of inflammation and how this modulates the polymicrobial biofilm within the context of the continuum of health, gingivitis, and periodontitis. We propose a new model termed “Inflammation-Mediated Polymicrobial-Emergence and Dysbiotic-Exacerbation” (IMPEDE), which is designed to integrate into and complement the 2017 World Workshop Classification of Periodontitis.

Periodontics in the USA: An introduction

The United States continues to be an incubator for new concepts and approaches to the diagnosis, treatment, and prevention of periodontal diseases. This volume of Periodontology 2000 presents some of these newer areas of research and paradigms that have emerged in the United States from both long-established and new investigators. These areas include: (1) more comprehensive approaches to assessing the total periodontal microbiome, including bacteria, viruses, and fungi, and their interactions with both the local and systemic inflammatory and immune responses, as well as with other oral and systemic conditions and diseases; (2) new developments for a more comprehensive characterization of the patient genome, transcriptome, and proteome profiles and the role of these profiles in periodontal disease pathogenesis; (3) new developments in nonsurgical approaches to periodontal diseases, including broad-based lines of attack using natural antimicrobials and host-modulation therapies and more focused approaches that target specific interactions in the host response; and (4) new big data analysis, machine learning, and imaging approaches, both for understanding the pathogenesis of periodontal diseases and for developing improved risk-assessment tools and better treatment outcomes.