Multikingdom oral microbiome interactions in early-onset cryptogenic ischemic stroke.

Although knowledge of the role of the oral microbiome in ischemic stroke is steadily increasing, little is known about the multikingdom microbiota interactions and their consequences. We enrolled participants from a prospective multicentre case-control study and investigated multikingdom microbiome differences using saliva metagenomic datasets (n = 308) from young patients diagnosed with cryptogenic ischemic stroke (CIS) and age- and sex-matched stroke-free controls. Differentially abundant taxa were identified using Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC2). Functional potential was inferred using HUMANn3. Our findings revealed significant differences in the composition and functional capacity of the oral microbiota associated with CIS. We identified 51 microbial species, including 47 bacterial, 3 viral, and one fungal species associated with CIS in the adjusted model. Co-abundance network analysis highlighted a more intricate microbial network in CIS patients, indicating potential interactions and co-occurrence patterns among microbial species across kingdoms. The results of our metagenomic analysis reflect the complexity of the oral microbiome, with high diversity and multikingdom interactions, which may play a role in health and disease.

Shotgun metagenomic analysis of the oral microbiome in gingivitis: a nested case-control study.

Background: Gingivitis, i.e. inflammation of the gums, is often induced by dentalplaque. However, its exact link to the oral microbiota remains unclear. Methods: In a case-control study involving 120 participants, comprising 60 cases and 60 controls (mean age (SD) 36.6 (7.6) years; 50% males), nested within a prospective multicentre cohort study, we examined theoral microbiome composition of gingivitis patients and their controlsusing shotgun metagenomic sequencing of saliva samples. Participants underwent clinical and radiographic oral health examinations, including bleeding on probing (BOP), at six tooth sites. BOP ≥33%was considered 'generalized gingivitis/initial periodontitis'(GG/IP), and BOP <33% as 'healthy and localized gingivitis'(H/LG). Functional potential was inferred using HUMANn3. Results: GG/IP exhibited an increase in the abundance of Actinomyces, Porphyromonas, Aggregatibacter, Corynebacterium, Olsenella, and Treponema, whereas H/LG exhibited an increased abundance of Candidatus Nanosynbacter. Nineteen bacterial species and fourmicrobial functional profiles, including L-methionine, glycogen, andinosine-5'-phosphate biosynthesis, were associated with GG/IP. Constructing models with multiple markers resulted in a strong predictive value for GG/IP, with an area under the curve (ROC) of 0.907 (95% CI: 0.848-0.966). Conclusion: We observed distinct differences in the oral microbiome between the GG/IP and H/LG groups, indicating similar yet unique microbial profiles and emphasizing their potential role in progression of periodontal diseases.

High-volume evacuation mitigates viral aerosol spread in dental procedures.

Dental healthcare personnel (DHCP) are subjected to microbe-containing aerosols and splatters in their everyday work. Safer work conditions must be developed to ensure the functioning of the healthcare system. By simulating dental procedures, we aimed to compare the virus-containing aerosol generation of four common dental instruments, and high-volume evacuation (HVE) in their mitigation. Moreover, we combined the detection of infectious viruses with RT-qPCR to form a fuller view of virus-containing aerosol spread in dental procedures. The air-water syringe produced the highest number of aerosols. HVE greatly reduced aerosol concentrations during procedures. The air-water syringe spread infectious virus-containing aerosols throughout the room, while other instruments only did so to close proximity. Additionally, infectious viruses were detected on the face shields of DHCP. Virus genomes were detected throughout the room with all instruments, indicating that more resilient viruses might remain infectious and pose a health hazard. HVE reduced the spread of both infectious viruses and viral genomes, however, it did not fully prevent them. We recommend meticulous use of HVE, a well-fitting mask and face shields in dental procedures. We advise particular caution when operating with the air-water syringe. Due to limited repetitions, this study should be considered a proof-of-concept report.

Subgingival microbiome at different levels of cognition.

Oral health and declining cognition may have a bi-directional association. We characterized the subgingival microbiota composition of subjects from normal cognition to severe cognitive decline in two cohorts. Memory and Periodontitis (MINOPAR) include 202 home-living participants (50-80 years) in Sweden. Finnish Oral Health Studies in Older Adults (FINORAL) include 174 participants (≥65 years) living in long-term care in Finland. We performed oral examination and assessed the cognitive level with Mini Mental State Examination (MMSE). We sequenced the 16S-rRNA gene (V3-V4 regions) to analyse the subgingival bacterial compositions. The microbial diversities only tended to differ between the MMSE categories, and the strongest determinants were increased probing pocket depth (PPD) and presence of caries. However, abundances of 101 taxa were associated with the MMSE score. After adjusting for age, sex, medications, PPD, and caries, only eight taxa retained the significance in the meta-analyses of the two cohorts. Especially Lachnospiraceae [XIV] at the family, genus, and species level increased with decreasing MMSE. Cognitive decline is associated with obvious changes in the composition of the oral microbiota. Impaired cognition is accompanied with poor oral health status and the appearance of major taxa of the gut microbiota in the oral cavity. Good oral health-care practices require special deliberations among older adults.

Working conditions during the COVID-19 pandemic in primary and tertiary healthcare: a comparative cross-sectional study.

OBJECTIVES: The COVID-19 pandemic has globally affected healthcare workers' (HCWs) health and wellbeing. Most studies on COVID-19 have focused on tertiary healthcare. The aim of this study was to increase the knowledge on the effects of the pandemic on working conditions in tertiary and primary healthcare. MATERIAL AND METHODS: The comparative cross-sectional study consisted of an online questionnaire sent to HCWs of the City of Helsinki (primary healthcare) and Helsinki University Hospital (tertiary healthcare). Altogether 1580 HCWs with direct patient contact participated in the study: 895 from tertiary and 685 from primary healthcare. Statistical analysis used SPSS 25 from IBM. The tests used were the χ2 test, Fisher's exact test, and binary logistic regression analysis. RESULTS: Primary HCWs were less likely to treat COVID-19 patients (OR = 0.45, 95% CI: 0.37-0.56). However, both groups reported a similar number of COVID-19 infections, primary HCWs 4.9% and tertiary HCWs 5.0%, and workrelated quarantine was significantly more prevalent (OR = 1.96, 95% CI: 1.38-2.79) among primary HCWs. In addition, work-related wellbeing was poorer among primary HCWs than tertiary HCWs in terms of feeling more stressed at work (OR = 3.20, 95% CI: 2.55-4.02), not recovering from work (OR = 0.49, 95% CI: 0.39-0.62), reported mental wellbeing below normal levels (OR: 1.59, 95% CI: 1.26-2.00), and increased working hours (OR = 1.63, 95% CI: 1.25-2.12). CONCLUSIONS: The study demonstrates how the pandemic has affected the wellbeing and working conditions of not only tertiary but also less studied primary HCWs. The authors' findings suggest that the challenges identified during the COVID-19 pandemic in the health and wellbeing of healthcare workers are even greater in primary care than in tertiary care. Int J Occup Med Environ Health. 2023;36(1):139-50.

"As protective gear began to run low, guidance on protection became looser" - Healthcare workers' perspectives on infection prevention and control during the COVID-19 pandemic.

Objectives: The COVID-19 pandemic has posed several risk factors to healthcare workers' (HCWs') emotional distress. The purpose of the study was to enhance understanding of the experiences and feelings of HCWs during the COVID-19 pandemic, with specific reference to infection prevention and control (IPC) practices and guidance, focusing on the quality and availability of personal protective equipment (PPE), guidelines, and management. With a qualitative approach, we aimed to enable a wider narrative; to gain a more detailed understanding related to PPE use and identify experiences that can be overlooked in forced-choice questionnaires. Methods: An online questionnaire was conducted among HCWs of the City of Helsinki and Helsinki University Hospital between 12.6.2020 and 5.4.2021. Altogether 1,580 HCWs participated in the study, from whom 579 shared 1,666 free-text responses. These responses were analyzed qualitatively, and the results were combined with statistical data on the participants' working conditions and backgrounds. Results: We identified problems in PPE availability and changing guidelines as factors causing the most distress in the participants. Regarding availability, running out of masks and respirators emerged as the most worrying issue, and inadequate PPE was associated with the excessive workload (OR 1.51, CI 95% 1.01-2.25). The results also highlight the importance of transparent and clear communication regarding IPC instructions and guidance, and clear IPC guidance was associated with better levels of reported recovery from work (OR 1.51, CI 95% 1.06-2.14). Conclusions: Our study highlights the importance of adequate PPE provision, transparent communication, clear guidance, and supportive supervisory work in this ongoing pandemic and potential new ones. We suggest more rigorous preparation, with crisis communication planning and emergency storage of PPE.

Aerosol concentrations and size distributions during clinical dental procedures.

Background: Suspected aerosol-generating dental instruments may cause risks for operators by transmitting pathogens, such as the SARS-CoV-2 virus. The aim of our study was to measure aerosol generation in various dental procedures in clinical settings. Methods: The study population comprised of 84 patients who underwent 253 different dental procedures measured with Optical Particle Sizer in a dental office setting. Aerosol particles from 0.3 to 10 µm in diameter were measured. Dental procedures included oral examinations (N = 52), restorative procedures with air turbine handpiece (N = 8), high-speed (N = 6) and low-speed (N = 30) handpieces, ultrasonic scaling (N = 31), periodontal treatment using hand instruments (N = 60), endodontic treatment (N = 12), intraoral radiographs (N = 24), and dental local anesthesia (N = 31). Results: Air turbine handpieces significantly elevated <1 µm particle median (p = 0.013) and maximum (p = 0.016) aerosol number concentrations as well as aerosol particle mass concentrations (p = 0.046 and p = 0.006) compared to the background aerosol levels preceding the operation. Low-speed dental handpieces elevated >5 µm median (p = 0.023), maximum (p = 0.013) particle number concentrations,> 5 µm particle mass concentrations (p = 0.021) and maximum total particle mass concentrations (p = 0.022). High-speed dental handpieces elevated aerosol concentration levels compared to the levels produced during oral examination. Conclusions: Air turbine handpieces produced the highest levels of <1 µm aerosols and total particle number concentrations when compared to the other commonly used instruments. In addition, high- and low-speed dental handpieces and ultrasonic scalers elevated the aerosol concentration levels compared to the aerosol levels measured during oral examination. These aerosol-generating procedures, involving air turbine, high- and low-speed handpiece, and ultrasonic scaler, should be performed with caution. Clinical significance: Aerosol generating dental instruments, especially air turbine, should be used with adequate precautions (rubber dam, high-volume evacuation, FFP-respirators), because aerosols can cause a potential risk for operators and substitution of air turbine for high-speed dental handpiece in poor epidemic situations should be considered to reduce the risk of aerosol transmission.

Blood and saliva SARS-CoV-2 antibody levels in self-collected dried spot samples.

We examined the usefulness of dried spot blood and saliva samples in SARS-CoV-2 antibody analyses. We analyzed 1231 self-collected dried spot blood and saliva samples from healthcare workers. Participants filled in a questionnaire on their COVID-19 exposures, infections, and vaccinations. Anti-SARS-CoV-2 IgG, IgA, and IgM levels were determined from both samples using the GSP/DELFIA method. The level of exposure was the strongest determinant of all blood antibody classes and saliva IgG, increasing as follows: (1) no exposure (healthy, non-vaccinated), (2) exposed, (3) former COVID-19 infection, (4) one vaccination, (5) two vaccinations, and (6) vaccination and former infection. While the blood IgG assay had a 99.5% sensitivity and 75.3% specificity to distinguish participants with two vaccinations from all other types of exposure, the corresponding percentages for saliva IgG were 85.3% and 65.7%. Both blood and saliva IgG-seropositivity proportions followed similar trends to the exposures reported in the questionnaires. Self-collected dry blood and saliva spot samples combined with the GSP/DELFIA technique comprise a valuable tool to investigate an individual's immune response to SARS-CoV-2 exposure or vaccination. Saliva IgG has high potential to monitor vaccination response wane, since the sample is non-invasive and easy to collect.

A machine learning approach to predict resilience and sickness absence in the healthcare workforce during the COVID-19 pandemic.

During the COVID-19 pandemic, healthcare workers (HCWs) have faced unprecedented workloads and personal health risks leading to mental disorders and surges in sickness absence. Previous work has shown that interindividual differences in psychological resilience might explain why only some individuals are vulnerable to these consequences. However, no prognostic tools to predict individual HCW resilience during the pandemic have been developed. We deployed machine learning (ML) to predict psychological resilience during the pandemic. The models were trained in HCWs of the largest Finnish hospital, Helsinki University Hospital (HUS, N = 487), with a six-month follow-up, and prognostic generalizability was evaluated in two independent HCW validation samples (Social and Health Services in Kymenlaakso: Kymsote, N = 77 and the City of Helsinki, N = 322) with similar follow-ups never used for training the models. Using the most predictive items to predict future psychological resilience resulted in a balanced accuracy (BAC) of 72.7-74.3% in the HUS sample. Similar performances (BAC = 67-77%) were observed in the two independent validation samples. The models' predictions translated to a high probability of sickness absence during the pandemic. Our results provide the first evidence that ML techniques could be harnessed for the early detection of COVID-19-related distress among HCWs, thereby providing an avenue for potential targeted interventions.

Effect of RNA quality to SARS-CoV-2 RT-qPCR detection from saliva.

Saliva is an alternative sample material to nasopharyngeal swab in SARS-CoV-2 diagnostics. We investigated possible aspects to improve the reliability of SARS-CoV-2 detection from saliva. Saliva was collected from asymptomatic healthy subjects (n=133) and COVID-19 patients (n=9). SARS-CoV-2 detection was performed with quantitative reverse-transcriptase PCR (RT-qPCR) with two viral and one host target serving as an internal control. The use of internal control revealed that in the first RT-qPCR run 25-30 % of assays failed. The failure is associated with poor RNA quality. When the amount of RNA was cut down to half from the original amount, the performance of RT-qPCR was greatly enhanced (95 % of the assays succeeded). The quality of RNA was not affected by the use of different nucleic acid stabilizing buffers. Our study showed that saliva is suitable material for RT-qPCR based SARS-CoV-2 diagnostics, but the use of internal control is essential to distinguish the true negative samples from failed assays.

Common complement factor H polymorphisms are linked with periodontitis in elderly patients.

BACKGROUND: In our recent genome-wide association study, we found that genetic polymorphisms in the complement factor H (CFH) gene and S100A gene region are strongly associated with serum matrix metalloproteinase 8 (MMP-8) concentration and the release of MMP-8 from neutrophils. As MMP-8 is centrally involved in the pathogenesis of periodontitis, we aimed to evaluate the presence of genetic polymorphisms of S100A8/A9/A12, MMP8, and CFH in periodontitis. In addition, we studied whether polymorphisms of these genes affect the concentrations of S100A8, S100A12, MMP-8, or complement activation marker in saliva. METHODS: We genotyped four single-nucleotide polymorphisms (SNPs, rs1560833 in S100A8/A9/A12, rs11225395 in MMP8, rs800292 in CFH, and rs1061170 in CFH) and measured salivary concentrations of S100A8, S100A12, MMP-8, and terminal complement complex (TCC) in the Parogene cohort (n = 508). The cohort was composed of patients with an indication to coronary angiography and all underwent a clinical and radiographic oral examination. RESULTS: CFH polymorphisms rs800292 and rs1061170 were associated with periodontal parameters. None of the polymorphisms showed association with salivary proteins. However, salivary concentrations of S100A8, S100A12, MMP-8, and TCC were strongly associated with the number of periodontal pockets and alveolar bone loss. CONCLUSION: Interestingly, genetic variants of CFH, MMP8, and S100A8/A9/A12 gene regions did not affect salivary levels of measured proteins. However, saliva levels of S100A8, S100A12, MMP-8, and TCC, and CFH polymorphisms were associated with clinical and radiographic signs of periodontitis. Our study further supports the observations that any dysregulation of complement may increase the risk of inflammatory disorders, such as periodontitis.

Periodontitis and cardiometabolic disorders: The role of lipopolysaccharide and endotoxemia.

Lipopolysaccharide is a virulence factor of gram-negative bacteria with a crucial importance to the bacterial surface integrity. From the host's perspective, lipopolysaccharide plays a role in both local and systemic inflammation, activates both innate and adaptive immunity, and can trigger inflammation either directly (as a microbe-associated molecular pattern) or indirectly (by inducing the generation of nonmicrobial, danger-associated molecular patterns). Translocation of lipopolysaccharide into the circulation causes endotoxemia, which is typically measured as the biological activity of lipopolysaccharide to induce coagulation of an aqueous extract of blood cells of the assay. Apparently healthy subjects have a low circulating lipopolysaccharide activity, since it is neutralized and cleared rapidly. However, chronic endotoxemia is involved in the pathogenesis of many inflammation-driven conditions, especially cardiometabolic disorders. These include atherosclerotic cardiovascular diseases, obesity, liver diseases, diabetes, and metabolic syndrome, where endotoxemia has been recognized as a risk factor. The main source of endotoxemia is thought to be the gut microbiota. However, the oral dysbiosis in periodontitis, which is typically enriched with gram-negative bacterial species, may also contribute to endotoxemia. As endotoxemia is associated with an increased risk of cardiometabolic disorders, lipopolysaccharide could be considered as a molecular link between periodontal microbiota and cardiometabolic diseases.

Salivary IgA antibody to malondialdehyde-acetaldehyde associates with mild periodontal pocket depth.

OBJECTIVE: Oxidized epitopes such as malondialdehyde-acetaldehyde (MAA) play a crucial role in the progression of atherosclerosis through activation of the humoral immune response. The exact mechanism of the association between atherosclerosis and periodontal diseases is not fully understood. The aim of the current study is to evaluate the association of oral humoral immune response to oxidized epitopes with parameters of periodontal disease. MATERIALS AND METHODS: The Parogene cohort consist of patients who have undergone coronary angiography due to cardiac symptoms. In this study, 423 patients were randomly selected for an extensive oral examination. Salivary Immunoglobulin A to oxidized epitopes and bacterial antigens was determined by chemiluminescence immunoassay. RESULTS: In a binary logistic regression model adjusted with periodontal disease confounders, periodontal pocket depth (PPD) 4-5 mm associated with salivary IgA antibodies to MAA-LDL (p = 0.034), heat shock protein 60 of Aggregatibacter actinomycetemcomitans (p = 0.045), Porphyromonas gingivalis (p = 0.045), A. actinomycetemcomitans (p = 0.005), P. intermedia (p = 0.020), and total IgA (p = 0.003). CONCLUSIONS: The current study shows the association of salivary IgA to MAA-LDL with PPD 4-5 mm in a cohort of patients with chronic coronary artery disease. Humoral immune cross-reactivation to oxidized epitopes such MAA-LDL could partly explain the link of periodontitis with systemic diseases.

Systemic Antibiotics Influence Periodontal Parameters and Oral Microbiota, But Not Serological Markers.

The use of systemic antibiotics may influence the oral microbiota composition. Our aim was to investigate in this retrospective study whether the use of prescribed antibiotics associate with periodontal status, oral microbiota, and antibodies against the periodontal pathogens. The Social Insurance Institution of Finland Data provided the data on the use of systemic antibiotics by record linkage to purchased medications and entitled reimbursements up to 1 year before the oral examination and sampling. Six different classes of antibiotics were considered. The Parogene cohort included 505 subjects undergoing coronary angiography with the mean (SD) age of 63.4 (9.2) years and 65% of males. Subgingival plaque samples were analysed using the checkerboard DNA-DNA hybridisation. Serum and saliva antibody levels to periodontal pathogens were analysed with immunoassays and lipopolysaccharide (LPS) activity with the LAL assay. Systemic antibiotics were prescribed for 261 (51.7%) patients during the preceding year. The mean number of prescriptions among them was 2.13 (range 1-12), and 29.4% of the prescriptions were cephalosporins, 25.7% penicillins, 14.3% quinolones, 12.7% macrolides or lincomycin, 12.0% tetracycline, and 5.8% trimethoprim or sulphonamides. In linear regression models adjusted for age, sex, current smoking, and diabetes, number of antibiotic courses associated significantly with low periodontal inflammation burden index (PIBI, p < 0.001), bleeding on probing (BOP, p = 0.006), and alveolar bone loss (ABL, p = 0.042). Cephalosporins associated with all the parameters. The phyla mainly affected by the antibiotics were Bacteroidetes and Spirochaetes. Their levels were inversely associated with the number of prescriptions (p = 0.010 and p < 0.001) and directly associated with the time since the last prescription (p = 0.019 and p < 0.001). Significant inverse associations were observed between the number of prescriptions and saliva concentrations of Prevotella intermedia, Tannerella forsythia, and Treponema denticola and subgingival bacterial amounts of Porphyromonas gingivalis, P. intermedia, T. forsythia, and T. denticola. Saliva or serum antibody levels did not present an association with the use of antibiotics. Both serum (p = 0.031) and saliva (p = 0.032) LPS activity was lower in patients having any antibiotic course less than 1 month before sampling. Systemic antibiotics have effects on periodontal inflammation and oral microbiota composition, whereas the effects on host immune responses against the periodontal biomarker species seem unchanged.

Immunological and Microbiological Profiling of Cumulative Risk Score for Periodontitis.

The cumulative risk score (CRS) is a mathematical salivary diagnostic model to define an individual's risk of having periodontitis. In order to further validate this salivary biomarker, we investigated how periodontal bacteria, lipopolysaccharide (LPS), and systemic and local host immune responses relate to CRS. Subgingival plaque, saliva, and serum samples collected from 445 individuals were used in the analyses. Plaque levels of 28 microbial species, especially those of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Porphyromonas endodontalis, Prevotella intermedia, and Tannerella forsythia, and serum and salivary levels of IgA and IgG against these five species were determined. Additionally, LPS activity was measured. High CRS associated strongly with all IgA/IgG antibody and LPS levels in saliva, whereas in serum the associations were not that obvious. In the final logistic regression model, the best predictors of high CRS were saliva IgA burden against the five species (OR 7.04, 95% CI 2.25-22.0), IgG burden (3.79, 1.78-8.08), LPS (2.19, 1.38-3.47), and the sum of 17 subgingival Gram-negative species (6.19, 2.10-18.3). CRS is strongly associated with microbial biomarker species of periodontitis and salivary humoral immune responses against them.

Saliva and Serum Immune Responses in Apical Periodontitis.

Apical periodontitis is an inflammatory reaction at the apex of an infected tooth. Its microbiota resembles that of marginal periodontitis and may induce local and systemic antibodies binding to bacteria- and host-derived epitopes. Our aim was to investigate the features of the adaptive immune response in apical periodontitis. The present Parogene cohort (n = 453) comprises patients with cardiac symptoms. Clinical and radiographic oral examination was performed to diagnose apical and marginal periodontitis. A three-category endodontic lesion score was designed. Antibodies binding to the bacteria- and host-derived epitopes were determined from saliva and serum, and bacterial compositions were examined from saliva and subgingival samples. The significant ORs (95% CI) for the highest endodontic scores were observed for saliva IgA and IgG to bacterial antigens (2.90 (1.01-8.33) and 4.91 (2.48-9.71)/log10 unit), saliva cross-reacting IgG (2.10 (1.48-2.97)), serum IgG to bacterial antigens (4.66 (1.22-10.1)), and Gram-negative subgingival species (1.98 (1.16-3.37)). In a subgroup without marginal periodontitis, only saliva IgG against bacterial antigens associated with untreated apical periodontitis (4.77 (1.05-21.7)). Apical periodontitis associates with versatile adaptive immune responses against both bacterial- and host-derived epitopes independently of marginal periodontitis. Saliva immunoglobulins could be useful biomarkers of oral infections including apical periodontitis-a putative risk factor for systemic diseases.

Association of Childhood Oral Infections With Cardiovascular Risk Factors and Subclinical Atherosclerosis in Adulthood.

Importance: Severe forms of common chronic oral infections or inflammations are associated with increased cardiovascular risk in adults. To date, the role of childhood oral infections in cardiovascular risk is not known because no long-term studies have been conducted. Objective: To investigate whether signs of oral infections in childhood are associated with cardiovascular risk factors and subclinical atherosclerosis in adulthood. Design, Setting, and Participants: The cohort study (n = 755) was derived from the Cardiovascular Risk in Young Finns Study, an ongoing prospective cohort study in Finland initiated in 1980. Participants underwent clinical oral examinations during childhood, when they were aged 6, 9, or 12 years and a clinical cardiovascular follow-up in adulthood in 2001 at age 27, 30, or 33 years and/or in 2007 at age 33, 36, or 39 years. Cardiovascular risk factors were measured at baseline and during the follow-up until the end of 2007. Final statistical analyses were completed on February 19, 2019. Main Outcomes and Measures: Four signs of oral infections (bleeding on probing, periodontal probing pocket depth, caries, and dental fillings) were documented. Cumulative lifetime exposure to 6 cardiovascular risk factors was calculated from dichotomized variables obtained by using the area-under-the-curve method. Subclinical atherosclerosis (ie, carotid artery intima-media thickness [IMT]) was quantified in 2001 (n = 468) and 2007 (n = 489). Results: This study included 755 participants, of whom 371 (49.1%) were male; the mean (SD) age at baseline examination was 8.07 (2.00) years. In this cohort, 33 children (4.5%) had no sign of oral infections, whereas 41 (5.6%) had 1 sign, 127 (17.4%) had 2 signs, 278 (38.3%) had 3 signs, and 248 (34.1%) had 4 signs. The cumulative exposure to risk factors increased with the increasing number of oral infections both in childhood and adulthood. In multiple linear regression models, childhood oral infections, including signs of either periodontal disease (R2 = 0.018; P = .01), caries (R2 = 0.022; P = .008), or both (R2 = 0.024; P = .004), were associated with adulthood IMT. The presence of any sign of oral infection in childhood was associated with increased IMT (third tertile vs tertiles 1 and 2) with a relative risk of 1.87 (95% CI, 1.25-2.79), whereas the presence of all 4 signs produced a relative risk of 1.95 (95% CI, 1.28-3.00). The associations were more obvious in boys: if periodontal disease were present, the corresponding estimate was 1.69 (95% CI, 1.21-2.36); if caries, 1.46 (95% CI, 1.04-2.05); and if all 4 signs of oral infections, 2.25 (95% CI, 1.30-3.89). The associations were independent of cardiovascular risk factors. Conclusions and Relevance: Oral infections in childhood appear to be associated with the subclinical carotid atherosclerosis seen in adulthood.

Smoking confounds the periodontal diagnostics using saliva biomarkers.

BACKGROUND: Smoking is a risk factor for periodontal disease because of its complex impact on the inflammatory response in the periodontium. We investigated the effect of smoking on salivary periodontal biomarkers, matrix metalloproteinase (MMP)-8, MMP-9, tissue inhibitor of metalloproteinase (TIMP)-1 and myeloperoxidase (MPO). METHODS: Saliva biomarkers were analyzed in the Parogene population (n = 480) comprising a random cohort of patients that have undergone coronary angiography and oral examination. The effect of time since cessation and pack years of smoking on biomarkers were investigated. RESULTS: Saliva MMP-8, MMP-9, TIMP-1, and MPO concentrations distinguished periodontitis patients significantly from patients without periodontitis. When the time since cessation was considered, the area-under-the-curve values (p-value) for periodontitis were 0.76 (<0.001), 0.74 (<0.001), 0.70 (<0.001), and 0.76 (<0.001), respectively. Adding information about smoking habits in the models improved slightly the sensitivities of all biomarkers. In logistic regression model saliva, MMP-8 was mainly affected by pack years of smoking, whereas saliva MMP-9, TIMP-1, and MPO were mostly affected by time since cessation, especially if smoking currently or quit recently (<1 year ago). CONCLUSION: Smoking confounds the salivary diagnostics of periodontitis and should be considered when interpreting the results obtained by potential diagnostic tests.

Salivary biomarkers in association with periodontal parameters and the periodontitis risk haplotype.

Genetic factors play a role in periodontitis. Here we examined whether the risk haplotype of MHC class III region BAT1-NFKBIL1-LTA and lymphotoxin-α polymorphisms associate with salivary biomarkers of periodontal disease. A total of 455 individuals with detailed clinical and radiographic periodontal health data were included in the study. A 610 K genotyping chip and a Sequenom platform were used in genotyping analyses. Phospholipid transfer protein activity, concentrations of lymphotoxin-α, IL-8 and myeloperoxidase, and a cumulative risk score (combining Porphyromonas gingivalis, IL-1ß and matrix metalloproteinase-8) were examined in saliva samples. Elevated IL-8 and myeloperoxidase concentrations and cumulative risk scores associated with advanced tooth loss, deepened periodontal pockets and signs of periodontal inflammation. In multiple logistic regression models adjusted for periodontal parameters and risk factors, myeloperoxidase concentration (odds ratio (OR); 1.37, P = 0.007) associated with increased odds for having the risk haplotype and lymphotoxin-α concentration with its genetic variants rs2857708, rs2009658 and rs2844482. In conclusion, salivary levels of IL-8, myeloperoxidase and cumulative risk scores associate with periodontal inflammation and tissue destruction, while those of myeloperoxidase and lymphotoxin-α associate with genetic factors as well.

Saliva and serum biomarkers in periodontitis and coronary artery disease.

AIM: Matrix metalloproteinase (MMP)-8, MMP-9, tissue inhibitor of matrix metalloproteinase (TIMP)-1 and myeloperoxidase (MPO) participate in extracellular matrix breakdown both in periodontium and atherosclerotic plaques. We investigated the diagnostic value of serum and saliva biomarkers in periodontitis and acute coronary syndrome (ACS). MATERIALS AND METHODS: The population was PAROGENE (n = 481), a random cohort of patients with an indication for coronary angiography. All patients underwent a clinical and radiographic oral examination. Groups consisting of periodontitis versus non-periodontitis, and ACS versus non-ACS patients were compared. RESULTS: Saliva MMP-8, MMP-9 and MPO provided significant area-under-curve (AUC) values for periodontitis, 0.69 (<0.001), 0.66 (<0.001) and 0.68 (<0.001), respectively. Serum MMP-8, MMP-9 and MPO levels distinguished ACS from non-ACS patients with AUCs of 0.73 (<0.001), 0.58 (0.03) and 0.68 (<0.001), respectively. Periodontitis confounded the use of serum MMP-9 in diagnostics of ACS. Cardiac status complicated the use of saliva TIMP-1 in periodontal diagnostics. Saliva biomarkers could not be used in ACS diagnosis, and serum biomarkers were not useful in diagnosis of periodontitis. CONCLUSIONS: MMP-8, MMP-9, TIMP-1and MPO are valuable biomarkers for both ACS and periodontitis, but the selection of sample material is crucial; serum is suitable for ACS and saliva for periodontal diagnostic aid.