Circulating IgG antibodies to periodontal bacteria and lung cancer risk in the CLUE cohorts.

BACKGROUND: Oral health is a key indicator of overall health, well-being, and quality of life. Several studies have provided new evidence about the role of oral diseases, specifically periodontitis, in generating risk for various forms of cancers, including lung, colorectal, and pancreatic cancers. METHODS: Incident lung cancer cases (n = 192) and matched controls (n = 192) were selected from participants of the CLUE I and CLUE II cohorts. Archived serum samples collected from participants in 1974 (in CLUE I) were analyzed using immunoblotting for immunoglobulin G (IgG) antibody levels to 13 bacteria of the periodontium. Associations between antibody levels and lung cancer were estimated using conditional logistic regression. RESULTS: Most of the periodontal bacterial antibodies measured were inversely associated with lung cancer risk; of these, 3 were statistically significant (Prevotellaintermedia, Actinomyces naeslundii, and Veillonella parvula). A statistically significant positive association was observed for one of the Porphyromonas gingivalis strains after adjusting for P. intermedia. The sum of the logarithm of antibodies against the 13 measured bacteria was inversely associated with risk of lung cancer when the analysis was restricted to a longer follow-up (31-44 years after blood collection, highest vs lowest quartile: odds ratio = 0.26, 95% confidence interval = 0.08 to 0.84). CONCLUSIONS: Findings from this study highlight the complexity of using serum IgG antibodies to periodontal bacteria to identify associations between oral pathogens and risk of lung cancer. The inverse associations observed for antibodies to periodontal bacteria suggest that these may represent markers of immunity that provide some advantage in reducing the development of lung cancer.

Nonsurgical periodontal treatment during pregnancy and rates of preterm birth.

BACKGROUND: Periodontitis during pregnancy is associated with an increased risk of preterm birth (<37 weeks of gestation) or low birthweight (<2500 g) offspring. Beyond periodontal disease, the risk of preterm birth varies both by previous history of preterm birth and in association with social determinants prevalent among vulnerable and marginalized populations. This study hypothesized that the timing of periodontal treatment during pregnancy and/or social vulnerability measures modified the response to dental scaling and root planing for the treatment of periodontitis and prevention of preterm birth. OBJECTIVE: This study aimed to determine the association of timing of dental scaling and root planing for gravidae with a diagnosed periodontal disease on the rates of preterm birth or low birthweight offspring among subgroups or strata of gravidae as part of the Maternal Oral Therapy to Reduce Obstetric Risk randomized controlled trial. All participants in the study had clinically diagnosed periodontal disease and differed by the timing of the periodontal treatment (dental scaling and root planing at <24 weeks [per protocol] or after delivery) or by baseline characteristics. Although all participants met the well-accepted clinical criteria for periodontitis, not all participants acknowledged a priori that they had periodontal disease. STUDY DESIGN: This was a per-protocol analysis of data from 1455 participants of the Maternal Oral Therapy to Reduce Obstetric Risk trial evaluating dental scaling and root planing on the risk of preterm birth or low birthweight offspring. Adjusted multiple logistic regression to control for confounders was used to estimate associations comparing the timing of periodontal treatment in pregnancy to receiving treatment after pregnancy (referent control) on rates of preterm birth or low birthweight among subgroups of gravidae with known periodontal disease. Study analyses were stratified, and the associations with the following characteristics-body mass index, self-described race and ethnicity, household income, maternal education, recency of immigration, and self-acknowledgment of poor oral health, were explored. RESULTS: Dental scaling and root planing during the second or third trimester of pregnancy were associated with an increased adjusted odds ratio of preterm birth among those at the lower body mass index strata (18.5 to <25.0 kg/m2) (adjusted odds ratio, 2.21; 95% confidence interval, 1.07-4.98), but not among individuals who were overweight (body mass index of 25.0 to <30.0 kg/m2; adjusted odds ratio, 0.68; 95% confidence interval, 0.29-1.59) or obese (body mass index of ≥30 kg/m2; adjusted odds ratio, 1.26; 95% confidence interval, 0.65-2.49). There was no significant difference in pregnancy outcomes related to the other evaluated variables: self-described race and ethnicity, household income, maternal education, immigration status, or self-acknowledgment of poor oral health. CONCLUSION: In this per-protocol analysis of the Maternal Oral Therapy to Reduce Obstetric Risk trial, dental scaling and root planing had no preventive benefit against adverse obstetrical outcomes and were associated with increased odds of preterm birth among individuals at lower body mass index strata. There was no significant difference in the occurrence of preterm birth or low birthweight after dental scaling and root planing periodontitis treatment concerning other analyzed social determinants of preterm birth.

Antibodies to oral pathobionts and colon cancer risk in the CLUE I cohort study.

Periodontitis has been associated with an increased risk for gastrointestinal cancers. The objective of our study was to investigate the association of antibodies to oral bacteria and the risk of colon cancer in a cohort setting. Using the CLUE I cohort, a prospective cohort initiated in 1974 in Washington County, Maryland, we conducted a nested case-control study to examine the association of levels of IgG antibodies to 11 oral bacterial species (13 total strains) with risk of colon cancer diagnosed a median of 16 years later (range: 1-26 years). Antibody response was measured using checkerboard immunoblotting assays. We included 200 colon cancer cases and 200 controls matched on age, sex, cigarette smoking status, time of blood draw and pipe or cigar smoking status. Controls were selected using incidence density sampling. Conditional logistic regression models were used to assess the association between antibody levels and colon cancer risk. In the overall analysis, we observed significant inverse associations for 6 of the 13 antibodies measured (P-trends <.05) and one positive association for antibody levels to Aggregatibacter actinomycetemcomitans (ATCC 29523; P-trend = .04). While we cannot rule out a role for periodontal disease in colon cancer risk, findings from our study suggest that a strong adaptive immune response may be associated with a lower risk of colon cancer. More studies will need to examine whether the positive associations we observed with antibodies to A. actinomycetemcomitans reflect a true causal association for this bacterium.

RNA sequence to structure analysis from comprehensive pairwise mutagenesis of multiple self-cleaving ribozymes.

Self-cleaving ribozymes are RNA molecules that catalyze the cleavage of their own phosphodiester backbones. These ribozymes are found in all domains of life and are also a tool for biotechnical and synthetic biology applications. Self-cleaving ribozymes are also an important model of sequence-to-function relationships for RNA because their small size simplifies synthesis of genetic variants and self-cleaving activity is an accessible readout of the functional consequence of the mutation. Here, we used a high-throughput experimental approach to determine the relative activity for every possible single and double mutant of five self-cleaving ribozymes. From this data, we comprehensively identified non-additive effects between pairs of mutations (epistasis) for all five ribozymes. We analyzed how changes in activity and trends in epistasis map to the ribozyme structures. The variety of structures studied provided opportunities to observe several examples of common structural elements, and the data was collected under identical experimental conditions to enable direct comparison. Heatmap-based visualization of the data revealed patterns indicating structural features of the ribozymes including paired regions, unpaired loops, non-canonical structures, and tertiary structural contacts. The data also revealed signatures of functionally critical nucleotides involved in catalysis. The results demonstrate that the data sets provide structural information similar to chemical or enzymatic probing experiments, but with additional quantitative functional information. The large-scale data sets can be used for models predicting structure and function and for efforts to engineer self-cleaving ribozymes.

Antepartum periodontitis treatment and risk of offspring screening positive for autism spectrum disorder.

BACKGROUND: To evaluate if treating maternal periodontal disease, a pro-inflammatory condition, during pregnancy (intervention) compared to after pregnancy (control) reduces the likelihood of offspring screening positive for autism spectrum disorder (ASD). METHODS: In a follow-up study to the MOTOR randomized trial, we compared rates of positive screens on the Modified Checklist for Autism in Toddlers (M-CHAT) among n = 306 two-year-old toddlers and correlated findings to maternal and cord blood pro-inflammatory interleukin-6 (IL-6). RESULTS: Toddlers in the intervention group had decreased risk of a positive M-CHAT screen (adjusted RR = 0.53, 95% CI 0.29-0.99). Toddlers screening positive compared to negative had higher mean IL-6 in cord blood (1.58 ± 1.14 vs. 1.09 ± 0.72 p = 0.001) and maternal IL-6 change from baseline (1.30 ± 0.61 vs 0.96 ± 0.62 p = 0.03). CONCLUSIONS: Treating periodontal disease during pregnancy reduced risk of a positive ASD screen. M-CHAT positivity was associated with increased IL-6 in maternal and cord blood. CLINICAL TRIAL: Trial Registration numbers: Clinicaltrials.gov NCT03423836.

Periodontal and Other Oral Bacteria and Risk of Lung Cancer in the Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: Evidence suggests that periodontal disease is associated with increased lung cancer risk, but whether periodontal pathogens are explanatory is unknown. We prospectively studied associations of prediagnostic circulating antibodies with oral bacteria and of periodontal bacteria in subgingival plaque with lung cancer. METHODS: We included 4,263 cancer-free participants in the Atherosclerosis Risk in Communities study with previously measured serum IgG antibodies to 18 oral bacteria. In 1,287 participants for whom subgingival plaque was collected, counts for 8 periodontal bacteria were previously measured. Incident lung cancers (N = 118) were ascertained through 2015 (median follow-up = 17.5 years). We used Cox regression to estimate multivariable-adjusted associations, including for sums of antibodies to orange (C. rectus, F. nucleatum, P. intermedia, P. micra, and P. nigrescens) and red (P. gingivalis, T. forsythensis, and T. denticola) complex bacteria. RESULTS: Orange complex bacteria antibodies were positively associated with lung cancer [per IQR hazard ratios (HR) = 1.15; 95% confidence intervals (CI), 1.02-1.29], which was stronger in men (HR = 1.27, 95% CI 1.08-1.49), and explained by P. intermedia and P. nigrescens (HR = 1.15; 95% CI, 1.04-1.26). Suggestive positive associations with lung cancer (N = 40) were observed for F. nucleatum, A. actinomycetemcomitans, and P. gingivalis counts. Significant positive associations were found for the count to antibody ratio for P. intermedia and P. gingivalis. CONCLUSIONS: We identified positive associations with lung cancer for oral bacteria, especially orange complex that are moderately pathogenic for periodontal disease. IMPACT: This prospective study supports the need for more research on periodontal bacteria in lung cancer etiology. If associations are supported, this may inform novel lung cancer prevention strategies.

Patterns of site-level periodontal disease and within-mouth correlation among older adults in the Hispanic Community Health Study/Study of Latinos.

OBJECTIVES: Clinical measures of periodontal disease such as attachment loss (CAL) and probing depth (PD) vary considerably between and within individuals with periodontitis and are known to be influenced by person-level factors (e.g. age and race/ethnicity) as well as intraoral characteristics (e.g. tooth type and location). This study sought to characterize site-level disease patterns and correlations using both person-level and intraoral factors through a model-based approach. METHODS: This study used full-mouth, six sites per tooth, periodontal examination data collected from 2301 Hispanic/Latino adults aged 60-74 years in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). The presence of site-level CAL ≥3 mm and PD ≥4 mm was estimated using generalized estimating equations (GEE), explicitly modelling pairwise periodontal site correlations, while adjusting for number of teeth, sex and Hispanic/Latino background. Subsequently tooth- and tooth-site patterns of intraoral CAL ≥3 mm and PD ≥4 mm were estimated and visualized in the HCHS/SOL population. RESULTS: The findings showed that posterior sites had the highest odds of CAL ≥3 mm and PD ≥4 mm. Sites located in the interproximal space had higher odds of PD ≥4 mm but lower odds of CAL ≥3 mm than non-interproximal sites. Mexicans had the lowest odds of CAL ≥3 mm among all Hispanic/Latino backgrounds. While Mexicans had lower odds of PD ≥4 mm than Central Americans and Cubans, they had higher odds than Dominicans and Puerto Ricans. Site-level proportions and pairwise correlations of PD ≥4 mm were generally smaller than those of CAL ≥3 mm. CONCLUSIONS: The patterns of site-level probabilities of clinical measures of periodontal disease can be defined based on tooth, site and individual-level characteristics. Intraoral correlation patterns, while complex, are quantifiable. The risk factors for site-level CAL ≥3 mm may differ from those of PD ≥4 mm. Likewise, participant risk factors for site-level clinical measures of periodontal disease are distinct from those that affect individual-level periodontitis prevalence. Future epidemiological investigations should consider model-based approaches when examining site-level disease probabilities to identify intra-oral patterns of periodontal disease and make inferences about the larger population.

Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data.

Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection (in vitro evolution). Improving a ribozyme-based system often requires several mutations to achieve the desired function, but extensive pairwise and higher-order epistasis prevent a simple prediction of the effect of multiple mutations that is needed for rational design. Recently, high-throughput sequencing-based approaches have produced data sets on the effects of numerous mutations in different ribozymes (RNA fitness landscapes). Here we used such high-throughput experimental data from variants of the CPEB3 self-cleaving ribozyme to train a predictive model through machine learning approaches. We trained models using either a random forest or long short-term memory (LSTM) recurrent neural network approach. We found that models trained on a comprehensive set of pairwise mutant data could predict active sequences at higher mutational distances, but the correlation between predicted and experimentally observed self-cleavage activity decreased with increasing mutational distance. Adding sequences with increasingly higher numbers of mutations to the training data improved the correlation at increasing mutational distances. Systematically reducing the size of the training data set suggests that a wide distribution of ribozyme activity may be the key to accurate predictions. Because the model predictions are based only on sequence and activity data, the results demonstrate that this machine learning approach allows readily obtainable experimental data to be used for RNA design efforts even for RNA molecules with unknown structures. The accurate prediction of RNA functions will enable a more comprehensive understanding of RNA fitness landscapes for studying evolution and for guiding RNA-based engineering efforts.

Periodontal Status, C-Reactive Protein, NT-proBNP, and Incident Heart Failure: The ARIC Study.

BACKGROUND: Periodontal disease (PD), resulting from inflammatory host response to dysbiotic subgingival microbiota, has been linked to cardiovascular disease; however, its relationship to heart failure (HF) and its subtypes (heart failure with reduced ejection fraction [HFrEF] and heart failure with preserved ejection fraction [HFpEF]) is unexplored. OBJECTIVES: The authors hypothesize that the presence of PD is associated with increased risk of incident HF, HFpEF, and HFrEF. METHODS: A total of 6,707 participants (mean age 63 ± 6 years) of the ARIC (Atherosclerosis Risk In Communities) study with full-mouth periodontal examination at visit 4 (1996-1998) and longitudinal follow-up for any incident HF (visit 4 to 2018), or incident HFpEF and HFrEF (2005-2018) were included. Periodontal status was classified as follows: healthy, PD (as per Periodontal Profile Classification [PPC]), or edentulous. Multivariable-adjusted Cox proportional hazards models were used to calculate HRs and 95% CIs for the association between PPC levels and incident HF, HFpEF, or HFrEF. Additionally, biomarkers of inflammation (C-reactive protein [CRP]) and congestion (N-terminal brain natriuretic peptide [NT-proBNP]) were assessed. RESULTS: In total, 1,178 incident HF cases occurred (350 HFpEF, 319 HFrEF, and 509 HF of unknown type) over a median of 13 years. Of these cases, 59% had PD, whereas 18% were edentulous. PD was associated with an increased risk for HFpEF (HR: 1.35 [95% CI: 0.98-1.86]) and significantly increased risk for HFrEF (HR: 1.69 [95% CI: 1.18-2.43]), as was edentulism: HFpEF (HR: 2.00 [95% CI: 1.37-2.93]), HFrEF (HR: 2.19 [95% CI: 1.43-3.36]). Edentulism was associated with unfavorable change in CRP and NT-proBNP, whereas PD was associated only with CRP. CONCLUSIONS: Periodontal status was associated with incident HF, HFpEF, and HFrEF, as well as unfavorable changes in CRP and NT-proBNP.

Periodontal disease measures and risk of incident peripheral artery disease: The Atherosclerosis Risk in Communities (ARIC) Study.

BACKGROUND: The association of periodontal disease with atherosclerotic cardiovascular diseases is well known, but not specifically with incident peripheral artery disease (PAD). Therefore, we studied the associations of periodontal disease with incident PAD in a population-based setting. METHODS: Among 9,793 participants (aged 53-75 years) without prevalent PAD, self-reported history of periodontal disease was ascertained. Of these, 5,872 participants underwent full-mouth examinations from which periodontal status was defined using the US Centers for Disease Control and Prevention-American Academy of Periodontology (CDC-AAP) definition. We quantified the association of periodontal disease with incident PAD (defined by hospital admission diagnosis or procedures) using multivariable Cox regression models. RESULTS: During a median follow-up of 20.1 years, 360 participants (3.6%) developed PAD. In models accounting for potential confounders including diabetes and smoking pack-years, there was higher hazard of PAD in participants with self-reported tooth loss because of periodontal disease (hazard ratio:1.54 [95% CI:1.20-1.98]), history of periodontal disease treatment (1.37 [1.05-1.80]), and periodontal disease diagnosis (1.38 [1.09-1.74]), compared to their respective counterparts. The clinical measure of periodontal disease (n = 5,872) was not significantly associated with incident PAD in the fully adjusted model (e.g., 1.53 [0.94-2.50] in CDC-AAP-defined severe periodontal disease versus no disease). CONCLUSION: We observed a modest association of self-reported periodontal disease, especially when resulting in tooth loss, with incident PAD in the general population. Nonetheless, a larger study with the clinical measure of periodontal disease is warranted.

Fragmentation of Apolipoprotein E4 is Required for Differential Expression of Inflammation and Activation Related Genes in Microglia Cells.

The apolipoprotein E4 (APOE4) allele represents the single greatest risk factor for late-onset Alzheimer's disease (AD) and accumulating evidence suggests that fragmentation with a toxic-gain of function may be a key molecular step associated with this risk. Recently, we demonstrated strong immunoreactivity of a 151 amino-terminal fragment of apoE4 (E4-fragment) within the nucleus of microglia in the human AD brain. In vitro, this fragment led to toxicity and activation of inflammatory processes in BV2 microglia cells. Additionally, a transcriptome analysis following exogenous treatment of BV2 microglia cells with this E4 fragment led to a > 2-fold up regulation of 1,608 genes, with many genes playing a role in inflammation and microglia activation. To extend these findings, we here report a similar transcriptome analysis in BV2 microglia cells following treatment with full-length ApoE4 (FL-ApoE4). The results indicated that full-length ApoE4 had a very small effect on gene expression compared to the fragment. Only 48 differentially expressed genes (DEGs) were identified (p < 0.05, and greater than 2-fold change). A gene ontology analysis of these DEGs indicated that they are not involved in inflammatory and activation processes, in contrast to the genes up regulated by the E4-fragment. In addition, genes that showed a negative fold-change upon FL-E4 treatment typically showed a strong positive fold-change upon treatment with the fragment (Pearson's r = -0.7). Taken together, these results support the hypothesis that a key step in the conversion of microglia to an activated phenotype is proteolytic cleavage of FL-ApoE4. Therefore, the neutralization of this amino-terminal fragment of ApoE4, specifically, may serve as an important therapeutic strategy in the treatment of AD.

Periodontitis and Risk of Diabetes in the Atherosclerosis Risk In Communities (ARIC) Study: A BMI-Modified Association.

PURPOSE: To determine whether periodontal disease is positively associated with incident diabetes across the continuum of body mass levels (BMI) and test the hypothesis that the periodontal risk for incident diabetes is modified by BMI. METHODS: We included 5569 diabetes-free participants from Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities study and followed them until 2018. Periodontal disease status was classified by periodontal profile class (PPC)-Stages , and incident diabetes was based on participant report of physician diagnosis. We estimated the hazard ratios (HR) for diabetes using a competing risk model for each PPC-Stage. We assessed multiplicative interactions between periodontal disease and BMI (as a continuous variable) on risk of diabetes. RESULTS: During a median time of 19.4 years of follow-up, 1348 incident diabetes cases and 1529 deaths occurred. Compared to the "Health/Incidental Disease" stage, participants with PPC "Severe Periodontal Disease" or "Severe Tooth Loss" stage and lower BMI had elevated risk for diabetes adjusting for demographic, smoking, education, and biological variables when accounting for death as a competing risk with HRs of 1.76 (95% CI 1.10-2.80) and 2.11 (95% CI 1.46-3.04), respectively. The interaction between PPC-Stages and BMI was significant (P = 0.01). No significant associations of PPC-Stages with incident diabetes were present when BMI was above 31 kg/m2. CONCLUSION: Periodontal disease was associated with incident diabetes, especially in nonobese participants. Dentists should be aware that periodontal disease is associated with incident diabetes but the association may be modified for patient's at higher BMI levels.

Primers to highly conserved elements optimized for qPCR-based telomere length measurement in vertebrates.

Telomere length dynamics are an established biomarker of health and ageing in animals. The study of telomeres in numerous species has been facilitated by methods to measure telomere length by real-time quantitative PCR (qPCR). In this method, telomere length is determined by quantifying the amount of telomeric DNA repeats in a sample and normalizing this to the total amount of genomic DNA. This normalization requires the development of genomic reference primers suitable for qPCR, which remains challenging in nonmodel organism with genomes that have not been sequenced. Here we report reference primers that can be used in qPCR to measure telomere lengths in any vertebrate species. We designed primer pairs to amplify genetic elements that are highly conserved between evolutionarily distant taxa and tested them in species that span the vertebrate tree of life. We report five primer pairs that meet the specificity and reproducibility standards of qPCR. In addition, we demonstrate an approach to choose the best primers for a given species by testing the primers on multiple individuals within a species and then applying an established computational tool. These reference primers can facilitate qPCR-based telomere length measurements in any vertebrate species of ecological or economic interest.

Periodontal disease, undiagnosed diabetes, and body mass index: Implications for diabetes screening by dentists.

BACKGROUND: Periodontal disease and diabetes are widespread comorbid conditions that are detrimental to oral and overall health. Dentists' performing chairside screenings for undiagnosed diabetes mellitus (UDM) can be beneficial to both patients and providers. The authors determined UDM rates in a population-based study and whether UDM and periodontal disease were independently associated. METHODS: Data from 7,343 participants in the Atherosclerosis Risk in Communities study visit 4 were used to determine rates of UDM by periodontal status, edentulism, and body mass index. The authors used a χ2 test or analysis of variance, along with a 2-stage logistic regression model, to determine relationships with UDM. UDM was defined as no self-reported diabetes and blood glucose levels (fasting glucose ≥ 126 milligrams/deciliter or nonfasting glucose > 200 mg/dL). Periodontal disease was defined using the Periodontal Profile Classes system adapted to stages and the Centers for Disease Control and Prevention and American Academy of Periodontology index. RESULTS: UDM rates overall were 5.6%. The highest rates occurred in patients who were obese and edentulous (12.6%) and obese and had severe periodontal disease (12.2%). Significant associations were found for UDM and severe periodontal disease (Periodontal Profile Classes system stage IV) (odds ratio, 1.78; 95% confidence interval, 1.10 to 2.88). Edentulism was significantly associated with UDM in the Periodontal Profile Classes system model (odds ratio, 1.87; 95% confidence interval, 1.27 to 2.75) and Centers for Disease Control and Prevention and American Academy of Periodontology index (odds ratio, 1.70; 95% confidence interval, 1.08 to 2.67). Hyperglycemia was found in participants of all body mass index categories. CONCLUSIONS: UDM is significantly associated with obesity, edentulism, and periodontitis. These characteristics could help dentists identify patients at higher risk of developing DM. Patients without these characteristics still have UDM, so dentists performing chairside diabetes screening for all patients would yield additional benefit. PRACTICAL IMPLICATIONS: Dental offices are a major point of contact within the US health care system. Diabetes screening in this setting can provide important health information with direct relevance to patient care.

Quantile regression to estimate the survivor average causal effect of periodontal treatment effects on birthweight and gestational age.

BACKGROUND: Survival average causal effect (SACE) can give valid estimates of the periodontal treatment effect on birth outcomes in randomized controlled trials when fetal losses are unequal across the treatment arms. A regression-based method to estimate SACE using ordinary least squares (OLS) regression can be biased if the treatment effect varies across the outcome distribution. In this case quantile regression may be a suitable alternative. METHODS: We compared OLS and quantile regression models estimating SACE to calculate the effect of periodontal treatment on birthweight and gestational age in secondary analyses of publicly available Obstetrics and Periodontal Therapy (OPT) trial data. RESULTS: Periodontal treatment tended to increase birthweight and gestational age at the lowest quantiles, remained flat in the middle quantiles, and trended to decrease both birthweight and gestational age in the highest quantiles. In quantile regression models estimating SACE the ß-coefficients: 95% confidence intervals (CI) for the 5th, 50th, and 95th percentiles were 277.5:  -141.0 to 696.0 g, 1.4: -107 to 110.3 g, and -84: -344 to 175.3 g for birthweight, and 0.6: -1.0 to 2.2 weeks, -0.1: -0.5 to 0.2 weeks, and -0.6: -1.0 to -0.1 weeks for gestational age. Estimates from OLS models estimating SACE were close to the null, ß: 95% CI -4.7: 132.3 to 123.0 g for birthweight, and 0.03: -0.72 to 0.78 weeks for gestational age. CONCLUSIONS: OLS models to evaluate SACE for periodontal treatment effects on birthweight and gestational age may be biased towards the null. Quantile regression may be a preferable alternative.

Biologically informed stratification of periodontal disease holds the key to achieving precision oral health.

Medicine and dentistry need to treat the individual not the "average patient." This personalized or precision approach to health care involves correctly diagnosing and properly classifying people to effectively customize prevention, diagnosis, and treatment. This is not a trivial undertaking. Achieving precision health requires making sense of big data, both at the population level and at the molecular level. The latter can include genetic, epigenetic, transcriptomic, proteomic, metabolomic data, and microbiome data. This biological information can augment established clinical measurements and supplement data on socioeconomic status, lifestyle, behaviors, and environmental conditions. Here, the central thesis is that, with sufficient data and appropriate methods, it is possible to segregate symptom-based and phenotypically based categories of patients into clinically and biologically similar groups. These groups are likely to have different clinical trajectories and benefit from different treatments. Additionally, such groups are optimal for investigations seeking to unveil the genomic basis of periodontal disease susceptibility. Analysis of these complex data to produce actionable and replicable health and disease categories requires appropriately sophisticated bioinformatics approaches and thorough validation in diverse patient samples and populations. Successful research programs will need to consider both population-level and well-controlled deep phenotyping approaches. Biologically informed stratification of periodontal disease is both feasible and desirable. Ultimately, this approach can accelerate the development of precision health through improvements in research and clinical applications.

Periodontal disease classifications and incident coronary heart disease in the Atherosclerosis Risk in Communities study.

BACKGROUND: Periodontal disease has been linked to coronary heart disease (CHD), but studies have been inconclusive. This study investigates the link between periodontal disease and incident CHD. METHODS: Baseline periodontal data from a full-mouth periodontal exam (N = 6,300) and CHD outcomes through 2017 were obtained from the Atherosclerosis Risk in Communities Study. Periodontitis was defined by the Periodontal Profile Class System adapted to Stages (PPC stages) and the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) index. Competing risk models were used to determine hazard ratios (HR) for incident CHD, congestive heart failure (CHF), and other causes of death. Secondary analysis included myocardial infarction (MI) and fatal CHD. RESULTS: Females comprised 56% of participants and males 44% with a combined mean age of 62.3 years (range: 52 to 74). Participants were followed for an average of 16.7 (SD: 5.5) years. In a fully adjusted model, PPC stage VII (Severe Tooth Loss) was moderately significantly related to incident CHD, (HR 1.51 [1.11 to 2.09]). PPC stage V (Mild Tooth Loss/High Gingival Inflammation) was significant for fatal CHD (HR, 5.27 [1.80 to 15.4]) and PPC stage VII was significant for incident MI (HR, 1.59 [1.13 to 2.23]). The CDC/AAP definition was not significantly associated with incident CHD. CONCLUSIONS: Incident CHD was moderately significantly associated with a specific stage of periodontal disease characterized by severe tooth loss, while none of the categories of the CDC/AAP were significantly associated. Thus, while periodontal therapy may improve oral health, it may be effective at impacting CHD incidence in only certain groups of people.

Advances in precision oral health.

The concept of precision dentistry as it relates to precision medicine is relatively new to the field of oral health. Precision dentistry is a contemporary, multifaceted, data-driven approach to oral health care that uses individual characteristics to stratify similar patients into phenotypic groups. The objective is to provide clinicians with the information that will allow them to improve treatment planning and a patient's response to treatment. Providers that use a precision oral health approach would move away from using an "average treatment" for all patients with a particular diagnosis and move toward more specific treatments for patients within each diagnostic subgroup. Precision dentistry requires a method or a model that places each individual in a subgroup where each member is the same as every other member in relation to the disease of interest. Precision dentistry is a paradigm shift that requires a new way of thinking about diagnostic categories. This approach uses patients' risk factor data (including, but not limited to, genetic, environmental, and health behavioral), rather than expert opinion or clinical presentation alone, to redefine traditional categories of health and disease. We review aspects of current efforts to allow precision dentistry to be realized and focus on one of the major innovations that may help precision dentistry to be practiced by periodontists, the World Workshop Model. Another approach is the Periodontal Profile Class system. These two approaches represent examples of supervised and unsupervised learning systems, respectively. This review compares and contrasts these two learning systems for their ability to classify patients into homogeneous disease and risk groups, as well as their feasibility at achieving the objective of enabling precision dentistry. We conclude that: (a) the World Workshop Model concept of stages and grades works as expected, in that periodontal status appears to be more serious in each successive stage. In addition, the seriousness and the complexity of the disease are greater as the grade increases within each stage. Stages and grades are important for precision dentistry because they consider the risk of future disease and the prognosis, and enable practitioners to use more signs, symptoms, and other associated factors when placing a patient in a diagnostic category; (b) the assignment of stages and grades using unsupervised learning systems is superior to using supervised learning systems for the prediction of 10-year tooth loss and 3-year attachment loss progression. In addition, the unsupervised learning approach (Periodontal Profile Class stages) results in stronger associations between the periodontal phenotypes and systemic diseases and conditions (prevalent diabetes, C-reactive protein, and incident stroke). This probably occurs because an unsupervised learning model produces more data-driven, mutually exclusive, homogeneous groups than a supervised learning model.

Biologically Defined or Biologically Informed Traits Are More Heritable Than Clinically Defined Ones: The Case of Oral and Dental Phenotypes.

The genetic basis of oral health has long been theorized, but little information exists on the heritable variance in common oral and dental disease traits explained by the human genome. We sought to add to the evidence base of heritability of oral and dental traits using high-density genotype data in a well-characterized community-based cohort of middle-age adults. We used genome-wide association (GWAS) data combined with clinical and biomarker information in the Dental Atherosclerosis Risk In Communities (ARIC) cohort. Genotypes comprised SNPs directly typed on the Affymetrix Genome-Wide Human SNP Array 6.0 chip with minor allele frequency of >5% (n = 656,292) or were imputed using HapMap II-CEU (n = 2,104,905). We investigated 30 traits including "global" [e.g., number of natural teeth (NT) and incident tooth loss], clinically defined (e.g., dental caries via the DMFS index, periodontitis via the CDC/AAP and WW17 classifications), and biologically informed (e.g., subgingival pathogen colonization and "complex" traits). Heritability (i.e., variance explained; h2) was calculated using Visscher's Genome-wide Complex Trait Analysis (GCTA), using a random-effects mixed linear model and restricted maximum likelihood (REML) regression adjusting for ancestry (10 principal components), age, and sex. Heritability estimates were modest for clinical traits-NT = 0.11 (se = 0.07), severe chronic periodontitis (CDC/AAP) = 0.22 (se = 0.19), WW17 Stage 4 vs. 1/2 = 0.15 (se = 0.11). "High gingival index" and "high red complex colonization" had h2 > 0.50, while a periodontal complex trait defined by high IL-1ß GCF expression and Aggregatibacter actinomycetemcomitans subgingival colonization had the highest h2 = 0.72 (se = 0.32). Our results indicate that all GWAS SNPs explain modest levels of the observed variance in clinical oral and dental measures. Subgingival bacterial colonization and complex phenotypes encompassing both bacterial colonization and local inflammatory response had the highest heritability, suggesting that these biologically informed traits capture aspects of the disease process and are promising targets for genomics investigations, according to the notion of precision oral health.