BACKGROUND AND AIMS: In the relationship between periodontitis and coronary heart disease (CHD), the mechanistic role of subclinical atherosclerosis remains incompletely understood. This study examines whether subclinical atherosclerosis mediates the periodontitis-incident CHD association; how a specific periodontitis phenotype modifies subclinical coronary atherosclerosis; and whether periodontitis is associated with epicardial adipose tissue (EAT) attenuation as a marker of inflammation.

METHODS: Data from the Swedish CArdioPulmonary bioImage Study (SCAPIS) were linked to national registers for dental data and CHD incidence. Coronary atherosclerosis was quantified using coronary artery calcium scores (CACS) and segment involvement scores (SIS). EAT characteristics were derived from non-contrast cardiac computed tomography. Associations between severe periodontitis and incident CHD events were examined using multivariable regression models, and mediation by CACS and SIS was explored.

RESULTS: Among 29 056 SCAPIS participants, severe periodontitis was present in 6% (n = 1809) and was associated with severe CACS [≥301, odds ratio (OR) 1.69, 95% confidence interval (CI) 1.39-2.06] and severe SIS (>4 segments, OR 1.40, 95% CI 1.17-1.67), with the strongest associations among individuals without concomitant dental caries. Moreover, periodontitis was associated with lower EAT attenuation (β = -0.27 HU, 95% CI -0.48 to -0.05) and a 42% higher risk of incident CHD events (hazard ratio 1.42, 95% CI 1.03-1.97), which was partially mediated by coronary atherosclerosis.

CONCLUSIONS: Severe periodontitis is positively associated with subclinical coronary atherosclerosis, EAT alterations reflecting inflammatory activity, and CHD event incidence. These results position periodontitis as a marker of increased coronary risk, warranting targeted cardiovascular risk assessment.

Objectives: The objectives were to: (i) assess the accuracy of dental data for adults obtained from the Swedish Quality Register on Caries and Periodontitis (SKaPa); (ii) explore whether Latent Class Analysis (LCA) can identify groups of people based on caries data; and (iii) characterise the dental, medical and behavioural characteristics of people in the LCA- derived classes. Methods: Caries data from the SKaPa register were compared with clinical data collected by five experienced dentists in a nested subgroup of the Malm & ouml; Offspring Study (MOS), namely the Malm & ouml; Offspring Dental Study (MODS) (n = 724) for validation. Dental data from SKaPa were then used to classify 61 984 adult participants of the V & auml;sterbotten Intervention Programme (VIP) into five classes using LCA and DMFS- based quintile ranking, respectively. Dental status (including caries progression over 5 years), medical, anthropometric and behavioural characteristics were compared between the groups. Analyses were replicated in 2767 adults in the MOS. Results: DMFSscores and number of teeth recorded within - 2 to +2 years showed excellent agreement between the SKaPa and reference data with intra- class correlations > 0.90. The five LCA classes differed in mean DMFS from 10.0 to 94.4. There were strong associations between LCA class and health, and health and behavioural measures respectively, including some associations that were not detected using DMFSranked quintile groups. LCA class was associated with incremental change in DMFS, DFS, and number of teeth. The results in the MOS cohort were consistent with the results in the VIP cohort. Conclusions: Dental data for adults from the SKaPa registry were considered accurate within 2 years of recording. The LCA approach can classify participants into caries subtypes based on dental charting. These groups differ in health and behavioural characteristics and future caries increment. The LCA approach may capture some information that is missing from DMFSranked quintile groups, but is also heavily influenced by total DMFS, meaning that applying LCA in cumulative, highly age- determined diseases, such as caries, is a challenge.

Aim: Periodontitis proxy variables enable an expansion of periodontal research. The study aimed to estimate the validity of questionnaire items and registry data in relation to Stage III–IV periodontitis and having 50% bone loss.

Methods: Malmö Offspring Dental Study (MODS) participants (995) filled out questionnaires and underwent periodontal and panoramic radiography examinations. The questionnaire items, number of periodontal treatment procedures (PTP) in the Dental Health Register (DHR), and number of teeth with ≥ 6 mm probing depth in the Swedish Quality Register for Caries and Periodontal Disease (SKaPa) were evaluated as proxies for severe periodontitis. Stage III–IV periodontitis was the primary reference standard.

Results: For PTP‐based severe periodontitis proxy in DHR, positive predictive value (PPV) was 88% and negative predictive value (NPV) 87% for Stage III–IV. The SKaPa‐based proxy showed poor positive predictive values (PPVs, < 70%), but similar area under the curve (AUC), 0.74, compared with the DHR data (AUC 0.76). Sensitivity was < 70%, and specificity > 90% for the DHR and SKaPa proxies. Identification of cases with periodontitis by questionnaire combined with the demographic variables age, sex, smoking habits and education yielded good discriminatory ability (AUC > 0.75).

Conclusion: Register‐based data can effectively identify individuals with severe periodontitis in large cohort studies, thereby advancing periodontal research.

OBJECTIVE: The aim was to optimize diagnostics for carotid artery calcifications (CACs) on panoramic radiographs (PRs) to identify cardiovascular disease (CVD) by investigating how 4 defined CAC shapes are associated with ultrasound (US) findings indicating CVD.

STUDY DESIGN: The study included 414 participants (802 neck sides) from the Malmö Offspring Dental Study, examined with PRs. The PRs were assessed for CAC shapes stratified into 4 categories: single, scattered, vessel-width defining, and vessel-outlining. The carotid arteries were examined with US for signs of CVD: the presence of plaques, largest individual area of a plaque, number of plaques, and percentage reduction of the lumen. Associations between the different CAC categories and US characteristics were analyzed.

RESULTS: All categories of CAC were significantly associated with a higher degree of US findings indicating CVD compared with no CAC (P < .001). The most significant differences were found for vessel-outlining CAC, with the mean of the largest individual plaque area of 17.9 vs 2.3 mm², mean number of plaques 1.6 vs 0.2, and mean percentage reduction of the lumen 24.1% vs 3.5% (all P < .001).

CONCLUSIONS: Independent of shape, CACs detected on PRs were associated with a higher degree of US findings of CVD. This was most pronounced for vessel-outlining CAC. With refined differential diagnostics of CACs in PRs, dentists may contribute to improved identification of patients in need of cardiovascular prevention.

Medication can affect the gut microbiota composition and function. The aim of this study was to investigate connections between use of common non-antibiotic medicines and the gut microbiota composition and function in a large Swedish cohort (N = 2223). Use of 67 medications and polypharmacy (≥ 5 medications), based on self-reported and prescription registry data, were associated with the relative abundance of 881 gut metagenomic species (> 5% prevalence) and 103 gut metabolic modules (GMMs). Altogether, 97 associations of 26 medications with 40 species and of four medications with five GMMs were observed (false discovery rate < 5%). Several earlier findings were replicated like the positive associations of proton pump inhibitors (PPIs) with numerous oral species, and those of metformin with Escherichia species and with lactate consumption I and arginine degradation II. Several new associations were observed between, among others, use of antidepressants, beta-blockers, nonsteroidal anti-inflammatory drugs and calcium channel blockers, and specific species. Polypharmacy was positively associated with Enterococcus faecalis, Bacteroides uniformis, Rothia mucilaginosa, Escherichia coli and Limosilactobacillus vaginalis, and with 13 GMMs. We confirmed several previous findings and identified numerous new associations between use of medications/polypharmacy and the gut microbiota composition and functional potential. Further studies are needed to confirm the new findings.

Aim: To investigate the association between periodontitis and lung function in the Malmo Offspring Dental Study.Materials and Methods: In all 1001 individuals (49.9% female, mean age: 44.6) from Malmo Offspring Dental Study were included. Periodontitis was assessed by a full-mouth examination protocol including bleeding on probing and classified according to the American Academy of Periodontology/Center for Disease Control definitions. Forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were expressed as absolute values and %predicted according to Global Lung Function Initiative reference values. FEV1, FVC and FEV1/FVC were analysed in relation to periodontal status using linear regression.Results:Severe periodontitis was found in 7% of the population. Adjusted regression models showed significant associations between lung function and severe periodontitis with 2.1 unit lower FEV1/FVC ratio (95% CI: -3.91, -0.23) and odds ratio (adjusted) of 2.56 (95% CI: 1.40, 4.75, p = .003) for airflow obstruction (FEV1/FVC less than the lower limit of normal) if having severe periodontitis. Lower values of %predicted FEV1 and %predicted FVC, but not FEV1/FVC, were found in individuals with >25% bleeding on probing.Conclusions: Severe periodontitis was associated with lower FEV1/FVC ratio and airflow obstruction in the present cohort. More large-scale prospective studies and intervention studies are required for a comprehensive evaluation.

BACKGROUND: Gut microbiota have been implicated in atherosclerotic disease, but their relation with subclinical coronary atherosclerosis is unclear. This study aimed to identify associations between the gut microbiome and computed tomography–based measures of coronary atherosclerosis and to explore relevant clinical correlates.

METHODS: We conducted a cross-sectional study of 8973 participants (50 to 65 years of age) without overt atherosclerotic disease from the population-based SCAPIS (Swedish Cardiopulmonary Bioimage Study). Coronary atherosclerosis was measured using coronary artery calcium score and coronary computed tomography angiography. Gut microbiota species abundance and functional potential were assessed with shotgun metagenomics sequencing of fecal samples, and associations with coronary atherosclerosis were evaluated with multivariable regression models adjusted for cardiovascular risk factors. Associated species were evaluated for association with inflammatory markers, metabolites, and corresponding species in saliva.

RESULTS: The mean age of the study sample was 57.4 years, and 53.7% were female. Coronary artery calcification was detected in 40.3%, and 5.4% had at least 1 stenosis with >50% occlusion. Sixty-four species were associated with coronary artery calcium score independent of cardiovascular risk factors, with the strongest associations observed for Streptococcus anginosus and Streptococcus oralis subsp oralis (P<1×10–5). Associations were largely similar across coronary computed tomography angiography–based measurements. Out of the 64 species, 19 species, including streptococci and other species commonly found in the oral cavity, were associated with high-sensitivity C-reactive protein plasma concentrations, and 16 with neutrophil counts. Gut microbial species that are commonly found in the oral cavity were negatively associated with plasma indole propionate and positively associated with plasma secondary bile acids and imidazole propionate. Five species, including 3 streptococci, correlated with the same species in saliva and were associated with worse dental health in the Malmö Offspring Dental Study. Microbial functional potential of dissimilatory nitrate reduction, anaerobic fatty acid β-oxidation, and amino acid degradation were associated with coronary artery calcium score.

CONCLUSIONS: This study provides evidence of an association of a gut microbiota composition characterized by increased abundance of Streptococcus spp and other species commonly found in the oral cavity with coronary atherosclerosis and systemic inflammation markers. Further longitudinal and experimental studies are warranted to explore the potential implications of a bacterial component in atherogenesis.

Objective: The primary aim of this current systematic review and meta-analysis was to evaluate the potential microbiological effect of probiotics on the implant microbiota. The secondary aim was to evaluate if probiotics have any effect as an adjunct to non-surgical peri-implant treatment in reducing peri-implant mucositis and peri-implantitis clinical parameters-bleeding on probing, modified Gingival Index, and pocket depth.

Methods: the PubMed, Scopus, and Web of Science Core Collection databases was conducted. Two independent reviewers screened the reports based on the PICO criteria-inclusion and exclusion criteria.

Results: In total, 467 records were identified, and ultimately, 7 papers were included: 3 papers in the qualitative synthesis of microbiological effect and 4 in the meta-analysis synthesis on pocket depth. The data synthesis showed that probiotics had no detectable effect on the implant microflora, and in the following data synthesis, no clinical peri-implantitis variable showed a significantly beneficial effect from probiotics in the test group compared to the control group.

Conclusion: Within the limitations of this review, the oral implant microflora is not affected by probiotics nor do probiotics add any effect to the conventional non-surgical treatment of peri-implant mucositis and peri-implantitis.

Type 2 diabetes (T2D) has a complex etiology which is not yet fully elucidated. The identification of gene perturbations and hub genes of T2D may deepen our understanding of its genetic basis. We aimed to identify highly perturbed genes and hub genes associated with T2D via an extensive bioinformatics analytic workflow consisting of five steps: systematic review of Gene Expression Omnibus and associated literature; identification and classification of differentially expressed genes (DEGs); identification of highly perturbed genes via meta-analysis; identification of hub genes via network analysis; and downstream analysis of highly perturbed genes and hub genes. Three meta-analytic strategies, random effects model, vote-counting approach, and p value combining approach, were applied. Hub genes were defined as those nodes having above-average betweenness, closeness, and degree in the network. Downstream analyses included gene ontologies, Kyoto Encyclopedia of Genes and Genomes pathways, metabolomics, COVID-19-related gene sets, and Genotype-Tissue Expression profiles. Analysis of 27 eligible microarrays identified 6284 DEGs (4592 downregulated and 1692 upregulated) in four tissue types. Tissue-specific gene expression was significantly greater than tissue non-specific (shared) gene expression. Analyses revealed 79 highly perturbed genes and 28 hub genes. Downstream analyses identified enrichments of shared genes with certain other diabetes phenotypes; insulin synthesis and action-related pathways and metabolomics; mechanistic associations with apoptosis and immunity-related pathways; COVID-19-related gene sets; and cell types demonstrating over- and under-expression of marker genes of T2D. Our approach provided valuable insights on T2D pathogenesis and pathophysiological manifestations. Broader utility of this pipeline beyond T2D is envisaged.

Genetic risk factors play important roles in the etiology of oral, dental, and craniofacial diseases. Identifying the relevant risk loci and understanding their molecular biology could highlight new prevention and management avenues. Our current understanding of oral health genomics suggests that dental caries and periodontitis are polygenic diseases, and very large sample sizes and informative phenotypic measures are required to discover signals and adequately map associations across the human genome. In this article, we introduce the second wave of the Gene-Lifestyle Interactions and Dental Endpoints consortium (GLIDE2) and discuss relevant data analytics challenges, opportunities, and applications. In this phase, the consortium comprises a diverse, multiethnic sample of over 700,000 participants from 21 studies contributing clinical data on dental caries experience and periodontitis. We outline the methodological challenges of combining data from heterogeneous populations, as well as the data reduction problem in resolving detailed clinical examination records into tractable phenotypes, and describe a strategy that addresses this. Specifically, we propose a 3-tiered phenotyping approach aimed at leveraging both the large sample size in the consortium and the detailed clinical information available in some studies, wherein binary, severity-encompassing, and "precision," data-driven clinical traits are employed. As an illustration of the use of data-driven traits across multiple cohorts, we present an application of dental caries experience data harmonization in 8 participating studies (N = 55,143) using previously developed permanent dentition tooth surface-level dental caries pattern traits. We demonstrate that these clinical patterns are transferable across multiple cohorts, have similar relative contributions within each study, and thus are prime targets for genetic interrogation in the expanded and diverse multiethnic sample of GLIDE2. We anticipate that results from GLIDE2 will decisively advance the knowledge base of mechanisms at play in oral, dental, and craniofacial health and disease and further catalyze international collaboration and data and resource sharing in genomics research.