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Background The objective of this study was to evaluate and present evidence from animal and human clinical studies on associations between dental caries and systemic diseases, and to suggest potential mechanisms that might explain such associations. Methods An electronic search was conducted of PubMed, Embase and Cochrane Central Register of Controlled Trials for articles published from 2010 to 2020 in the English language. From the initial search, 404 full-text studies were assessed for eligibility. After excluding studies for technical and study limitations, a total of 67 studies were included in the summary tables and additional studies were included in the review to support evidence. Results Few systemic disease and conditions were found to be clinically meaningfully associated with caries experience. Best evidence from human and animal studies described association between metabolic diseases and dental caries. Several interesting animal studies were noted that could generate clinical hypotheses and further investigations in rodent models for cardiovascular injury and hyperglycemia. Inadequate data was found to suggest any modifications to current clinical practice or prevention guidelines. Conclusions Limited clinical evidence was found connecting several systemic diseases and dental caries. Inadequate data was found to suggest any modifications to current clinical practice or prevention guidelines. Clinical significance Understanding of associations between dental caries and systemic diseases play a crucial role in the treatment planning and education of the dental patient.

Poor oral hygiene often leads to chronic diseases such as periodontitis and dental caries resulting in substantial economic costs and diminished quality of life in not only adults but also in children. In this study, the salivary microbiome was characterized in a group of children stratified by the Simplified Oral Hygiene Index (OHI-S). Illumina MiSeq high-throughput sequencing based on the 16S rRNA was utilized to analyze 90 salivary samples (24 Good, 31 Moderate and 35 Poor oral hygiene) from a cohort of Thai children. A total of 38,521 OTUs (Operational Taxonomic Units) with a 97% similarity were characterized in all of the salivary samples. Twenty taxonomic groups (Seventeen genera, two families and one class; Streptococcus, Veillonella, Gemellaceae, Prevotella, Rothia, Porphyromonas, Granulicatella, Actinomyces, TM-7-3, Leptotrichia, Haemophilus, Selenomonas, Neisseria, Megasphaera, Capnocytophaga, Oribacterium, Abiotrophia, Lachnospiraceae, Peptostreptococcus, and Atopobium) were found in all subjects and constituted 94.5-96.5% of the microbiome. Of these twenty genera, the proportion of Streptococcus decreased while Veillonella increased with poor oral hygiene status (P < 0.05). Furthermore, an unassigned species of Veillonella, Veillonella dispar and Veillonella parvula tended to be elevated in the Poor oral hygiene group. This is the first study demonstrating an important association between increase of Veillonella and poor oral hygiene status in children. However, further studies are required to identify the majority of Veillonella at species level in salivary microbiome of the Poor oral hygiene group.

There is emerging evidence linking diabetes with periodontal disease. Diabetes is a well-recognized risk factor for periodontal disease. Conversely, pro-inflammatory molecules released by periodontally-diseased tissues may enter the circulation to induce insulin resistance. While this association has been demonstrated in adults, there is little information regarding periodontal status in obese children with and without type 2 diabetes (T2D). We hypothesized that children with T2D have higher rates of gingivitis, elevated salivary inflammatory markers, and an altered salivary microbiome compared to children without T2D. Three pediatric cohorts ages 10-19 years were studied: lean (normal weight-C), obese (Ob), and obese with T2D (T2D). Each subject completed an oral health survey, received a clinical oral examination, and provided unstimulated saliva for measurement of inflammatory markers and microbiome analysis. The diabetes group was less likely to have had a dental visit within the last six months. Body mass index (BMI) Z-scores and waist circumference/height ratios were similar between Ob and T2D cohorts. The number of carious lesions and fillings were similar for all three groups. The gingival index was greater in the T2D group compared to the Ob and C groups. Although salivary microbial diversity was minimal between groups, a few differences in bacterial genus composition were noted. Obese children with T2D show a trend toward poorer oral health compared to normal weight and obese children without T2D. This study characterizes the salivary microbiome of children with and without obesity and T2D. This study supports a modest link between T2D and periodontal inflammation in the pediatric population.

Background. Ventilator-associated pneumonia (VAP) is a leading cause of morbidity and mortality in patients hospitalized in intensive care units. Recent studies suggest that dental plaque biofilms serve as a reservoir for respiratory pathogens. The goal of this study was to determine the genetic relationship between strains of respiratory pathogens first isolated from the oral cavity and later isolated from bronchoalveolar lavage fluid from the same patient undergoing mechanical ventilation with suspected VAP. Methods. Plaque and tracheal secretion samples were obtained on the day of hospital admission and every other day thereafter until discharge from the intensive care unit from 100 patients who underwent mechanical ventilation. Bronchoalveolar lavage was performed for 30 patients with suspected VAP. Pulse-field gel electrophoresis and multilocus sequence typing were used to determine the genetic relatedness of strains obtained from oral, tracheal, and bronchoalveolar lavage samples. Results. Isolates of Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter species, and enteric species recovered from plaque from most patients were indistinguishable from isolates recovered from bronchoalveolar lavage fluid (i.e., had >95% similarity of pulse-field gel electrophoresis patterns). Nearly one-half of the Pseudomonas strains showed identical genetic profiles between patients, which suggested a common environmental source of infection. Conclusions. Respiratory pathogens isolated from the lung are often genetically indistinguishable from strains of the same species isolated from the oral cavity in patients who receive mechanical ventilation who are admitted to the hospital from the community. Thus, dental plaque serves as an important reservoir for respiratory pathogens in patients who undergo mechanical ventilation. Trial registration. ClinicalTrials.gov identifier: NCT00123123

The interaction between human salivary alpha-amylase (HSAmy) and amylase-binding oral streptococci (ABS) helps determine the bacteria that colonize the oral cavity by establishing dental biofilms. Streptococci are important pioneer species of the oral cavity and influence oral health as well as common diseases such as dental caries. Various oral streptococcal species express distinct amylase-binding proteins, among which amylase-binding protein A (AbpA), encoded by the abpA gene in Streptococcus gordonii and several other species, which is the most extensively studied. Amylase binding facilitates microbial adhesion to host surfaces and biofilm formation and enables bacteria to harness the host’s amylase enzymatic activity at their cell surface, enhancing their capacity to metabolize dietary starch for nutritional gain. Additionally, amylase binding may also influence bacterial cell division and stress tolerance by engaging novel bacterial signaling pathways. From an evolutionary perspective, both Neanderthals and modern humans exhibit functional adaptations in nutrient metabolism, including selection for salivary amylase-binding oral streptococci, highlighting the importance of microbial co-adaptation in response to host diet. Further research is warranted to elucidate the broader roles of amylase binding to bacteria in host-bacterial signaling, bacterial cell division and fitness and the evolutionary trajectory of the oral microbiome.

Background Mounting evidence indicates potential associations between poor oral health status (OHS) and increased pneumonia risk. Relative pneumonia risk was assessed in the context of longitudinally documented OHS. Methods Electronic medical/dental patient data captured from 2007 through 2019 were retrieved from the integrated health records of Marshfield Clinic Health Systems. Participant eligibility initiated with an assessment of OHS, stratified into the best, moderate, or worst OHS groups, with the additional criterion of ‘no pneumonia diagnosis in the past 90 days’. Pneumonia incidence was longitudinally monitored for up to 1 year from each qualifying dental visit. Models were assessed, with and without adjustment for prior pneumonia incidence, adjusted for smoking and subjected to confounding mitigation attributable to known pneumonia risk factors by applying propensity score analysis. Time-to-event analysis and proportional hazard modeling were applied to investigate relative pneumonia risk over time among the OHS groups. Results Modeling identified associations between any incident pneumonia subtype and ‘number of missing teeth’ ( p  < 0.001) and ‘clinically assessed periodontal status’ ( p  < 0.01), which remained significant following adjustment for prior pneumonia incidence and smoking. The hazard ratio (HR) for ‘any incident pneumonia’ in the best OHS group for ‘number of missing teeth’ was 0.65, 95% confidence interval (CI) [0.54 − 0.79] (unadjusted) and 0.744, 95% CI [0.61 − 0.91] (adjusted). The HR for ‘any incident pneumonia’ in the best ‘clinically assessed periodontal status’ group was 0.72, 95% CI [0.58 − 0.90] (unadjusted) and 0.78, 95% CI [0.62 − 0.97] (adjusted). Conclusion/clinical relevance Poor OHS increased pneumonia risk. Proactive attention of medical providers to patient OHS and health literacy surrounding oral-systemic disease association is vital, especially in high-risk populations.

Multiplexing arrays increase the throughput and decrease sample requirements for studies employing multiple biomarkers. The goal of this project was to examine the performance of Multiplex arrays for measuring multiple protein biomarkers in saliva and serum. Specimens from the OsteoPerio ancillary study of the Women's Health Initiative Observational Study were used. Participants required the presence of at least 6 teeth and were excluded based on active cancer and certain bone issues but were not selected on any specific condition. Quality control (QC) samples were created from pooled serum and saliva. Twenty protein markers were measured on five multiplexing array panels. Sample pretreatment conditions were optimized for each panel. Recovery, lower limit of quantification (LLOQ) and imprecision were determined for each analyte. Statistical adjustment at the plate level was used to reduce imprecision estimates and increase the number of usable observations. Sample pre-treatment improved recovery estimates for many analytes. The LLOQ for each analyte agreed with manufacturer specifications except for MMP-1 and MMP-2 which were significantly higher than reported. Following batch adjustment, 17 of 20 biomarkers in serum and 9 of 20 biomarkers in saliva demonstrated acceptable precision, defined as <20% coefficient of variation (<25% at LLOQ). The percentage of cohort samples having levels within the reportable range for each analyte varied from 10% to 100%. The ratio of levels in saliva to serum varied from 1∶100 to 28∶1. Correlations between saliva and serum were of moderate positive magnitude and significant for CRP, MMP-2, insulin, adiponectin, GM-CSF and IL-5. Multiplex arrays exhibit high levels of analytical imprecision, particularly at the batch level. Careful sample pre-treatment can enhance recovery and reduce imprecision. Following statistical adjustments to reduce batch effects, we identified biomarkers that are of acceptable quality in serum and to a lesser degree in saliva using Multiplex arrays.

The genus Veillonella is a common and abundant member of the oral microbiome. It includes eight species, V. atypica, V. denticariosi, V. dispar, V. infantium, V. nakazawae, V. parvula, V. rogosae and V. tobetusensis. They possess important metabolic pathways that utilize lactate as an energy source. However, the overall metabolome of these species has not been studied. To further understand the metabolic framework of Veillonella in the human oral microbiome, we conducted a comparative pan-genome analysis of the eight species of oral Veillonella. Analysis of the oral Veillonella pan-genome revealed features based on KEGG pathway information to adapt to the oral environment. We found that the fructose metabolic pathway was conserved in all oral Veillonella species, and oral Veillonella have conserved pathways that utilize carbohydrates other than lactate as an energy source. This discovery may help to better understand the metabolic network among oral microbiomes and will provide guidance for the design of future in silico and in vitro studies.

Background Successful commensal bacteria have evolved to maintain colonization in challenging environments. The oral viridans streptococci are pioneer colonizers of dental plaque biofilm. Some of these bacteria have adapted to life in the oral cavity by binding salivary α-amylase, which hydrolyzes dietary starch, thus providing a source of nutrition. Oral streptococcal species bind α-amylase by expressing a variety of amylase-binding proteins (ABPs). Here we determine the genotypic basis of amylase binding where proteins of diverse size and function share a common phenotype. Results ABPs were detected in culture supernatants of 27 of 59 strains representing 13 oral Streptococcus species screened using the amylase-ligand binding assay. N-terminal sequences from ABPs of diverse size were obtained from 18 strains representing six oral streptococcal species. Genome sequencing and BLAST searches using N-terminal sequences, protein size, and key words identified the gene associated with each ABP. Among the sequenced ABPs, 14 matched amylase-binding protein A (AbpA), 6 matched amylase-binding protein B (AbpB), and 11 unique ABPs were identified as peptidoglycan-binding, glutamine ABC-type transporter, hypothetical, or choline-binding proteins. Alignment and phylogenetic analyses performed to ascertain evolutionary relationships revealed that ABPs cluster into at least six distinct, unrelated families (AbpA, AbpB, and four novel ABPs) with no phylogenetic evidence that one group evolved from another, and no single ancestral gene found within each group. AbpA-like sequences can be divided into five subgroups based on the N-terminal sequences. Comparative genomics focusing on the abpA gene locus provides evidence of horizontal gene transfer. Conclusion The acquisition of an ABP by oral streptococci provides an interesting example of adaptive evolution.

Background Evidence suggest an association between periodontal disease (PerioD) and Alzheimer's disease (AD), with PerioD‐associated microbial ecosystems driving oral and systemic inflammation that may activate or accelerate neuroinflammation, a hallmark of AD. Social determinants of health (SDoH) are critical factors influencing both oral health and AD risk yet are often overlooked, and rarely investigated together. This study aims to characterize and compare the oral microbiome of age‐ and education‐matched individuals at high risk for AD by virtue of family history, with and without PerioD, and to investigate the relationships between PerioD‐associated microbiome features, SDoH, systemic inflammation and brain inflammation, and AD biomarkers (in cerebrospinal fluid [CSF]). Method This two‐year NINDS‐funded study collects oral microbiome samples, blood, and CSF annually in a cognitively normal, racially diverse cohort (n = 165). Metagenomic sequencing will be used to investigate cross‐kingdom microbial communities and their association with inflammatory and systemic markers. Surveys and interviews investigate behaviors and SDoH influencing PerioD and AD risk. Result To date, 55 participants have been recruited. Participants are 62 years of age on average, predominantly white (70%), female (63.3%), with Stage 1–2 periodontitis (85.7%). Preliminary analyses found no significant relationships between bleeding on probing, behavioral factors, SDoH variables, and Montreal Cognitive Assessment (MoCA) scores, which was expected given the small sample size. As recruitment continues, we anticipate identifying associations between oral microbiome features, inflammatory markers, AD biomarkers and cognitive outcomes. SDoH, such as access to dental care and oral hygiene behaviors, may mediate these relationships, offering insights into the interplay between periodontal disease, systemic inflammation, and AD risk. Conclusion By leveraging longitudinal data and exploring upstream sociocultural factors, this research addresses critical gaps in understanding PerioD's contribution to AD risk. Findings will provide novel insights into the interplay between the oral microbiome, systemic inflammation, brain inflammation, and AD risk.