Demmer, Ryan T.

AbstractBackgroundPeriodontal disease is a prevalent, preventable, and highly treatable oral infection that is (1) stratified by sociodemographic, educational, and spatial factors and (2) is believed to impact cognitive impairment and ADRD risk. However, there is very little information from community‐based, population‐representative, longitudinal studies about the association between periodontal disease and midlife cognitive functioning net of early life confounders.MethodWe use data from the U.S. High School and Beyond (HSB) cohort study, which has followed a nationally representative sample of ∼25,500 people from high school in 1980 through midlife in 2021‐22. HSB data from the 1980s includes rich information about educational contexts, opportunities, and outcomes; early life socioeconomic and family circumstances; spatial location; and demographic group memberships. HSB data from 2021‐22 include indicators of periodontal disease diagnosis and multiple measures of cognitive functioning.ResultPeople who have been diagnosed with periodontal disease score worse on measures of memory, executive function, and other domains of cognitive functioning at midlife. These associations are only partly attributable to early life confounders. Some ─ but not all ─ of the association can be attributed to the mediating role of diabetes and CVD.ConclusionPeriodontal disease is a preventable and treatable risk factor for subsequent cognitive impairment. Because risk of periodontal disease is stratified by demographic, educational, and other social factors, periodontal disease may also be important in shaping sociodemographic gradients in midlife cognitive functioning. This is the first population‐representative study using data from a community‐based cohort that has been followed from adolescence through midlife. As such, this work provides important evidence about the role of periodontal disease in stratifying cognitive outcomes.

ABSTRACTBackgroundPeriodontal disease (PD) is a prevalent, preventable and treatable oral infection associated with substantial morbidity globally. There is little information from population‐representative cohort studies about the sociodemographic, educational and other early life factors that stratify PD risk.MethodsWe used data from the U.S. ‘High School and Beyond’ (HS&B:80) study, which has followed a nationally representative sample of 26,820 people from high school in 1980 through midlife in 2021. Data from the 1980s include information about education, early life circumstances, spatial location and demographic attributes. Data from 13,080 sample members who responded in 2021 include indicators of self‐reported PD diagnosis.ResultsPeople with higher degrees and course grades have a lower risk of midlife PD. Rural adolescents and those who attended private schools are also at lower risk. We find little evidence of heterogeneity in correlates of midlife PD by gender or race/ethnicity.ConclusionsThe quantity and characteristics of people's schooling and their location of residence are associated with midlife PD.

ABSTRACTObjectiveTo study the association between dietary patterns and subgingival microbiota.MethodsParticipants (n = 651) who were enrolled in the Oral Infections, Glucose Intolerance, and Insulin Resistance Study (ORIGINS) with subgingival plaque sampling (n = 890 plaques) and a dietary assessment were included. 16S rRNA gene amplicon sequences of subgingival plaque from sites with either probing depth <4 or ≥4 mm were processed separately and used to obtain α‐diversity metrics (Faith, Shannon, Simpson, Observed) and taxa ratios (Red Complex to Corynebacterium [RCLR], Treponema to Corynebacterium [TCLR], and Treponema to Neisseria [TNLR]). Food frequency questionnaires (FFQs) were processed to calculate Alternate Healthy Eating Index (AHEI) and A Priori Diet Quality Score (APDQS) scores. Mixed regression models examined the mean levels of microbial metrics across quartiles of diet quality. Means ± standard errors are reported along with p‐values.ResultsIn multivariable models assessing the association between diet scores and α‐diversity metrics, higher AHEI values were significantly associated with lower Faith (p‐value = 0.01) and Observed (p‐value = 0.04) diversity values; similar findings were observed for APDQS (p‐value = 0.01, p‐value = 0.04). In multivariable models assessing the association between diet scores (AHEI and APDQS) and taxa ratios (RCLR, TCLR and TNLR), as the AHEI quartile increased, all taxa ratios decreased significantly as follows: −1.06 ± 0.093 in Q1 to −1.34 ± 0.099 in Q4 (RCLR), −0.43 ± 0.077 in Q1 to −0.64 ± 0.083 in Q4 (TCLR) and −0.09 ± 0.083 in Q1 to −0.38 ± 0.089 in Q4 (TNLR), respectively. In contrast, as the APDQS quartiles increased, only TNLR decreased significantly from −0.08 ± 0.085 in Q1 to −0.34 ± 0.091 in Q4.ConclusionDiets rich in fruits, vegetables, whole grains and other nutritionally rich plant foods are associated with lower oral microbial diversity and favourable ratios of pathogenic to commensal microbiota.

Several bacterial taxa enriched in inflammatory bowel diseases and colorectal cancer (CRC) are found in the oral cavity. We conducted a pilot study nested within a six-week aspirin intervention in a randomized placebo-controlled trial to test their response to aspirin intervention. Fifty healthy subjects, 50–75 years old, were randomized to receive 325 mg aspirin (n = 30) or placebo (n = 20) orally once daily for six weeks. Oral tongue swabs were collected at baseline and week six. We estimated the association between aspirin use and the temporal changes in the relative abundance of pre-specified genus level taxa from pre- to post-treatment. The temporal change in relative abundance differed for eight genus level taxa between the aspirin and placebo groups. In the aspirin group, there were significant increases in the relative abundances of Neisseria, Streptococcus, Actinomyces, and Rothia and significant decreases in Prevotella, Veillonella, Fusobacterium, and Porphyromonas relative to placebo. The log ratio of Neisseria to Fusobacterium declined more in the aspirin group than placebo, signaling a potential marker associated with aspirin intervention. These preliminary findings should be validated using metagenomic sequencing and may guide future studies on the role of aspirin on taxa in various oral ecological niches.

BACKGROUND: Systemic arterial compliance and venous capacitance are typically impaired in patients with heart failure with preserved ejection fraction (HFpEF), contributing to hemodynamic congestion with stress. Sodium-glucose cotransporter-2 inhibitors reduce hemodynamic congestion and improve clinical outcomes in patients with HFpEF, but the mechanisms remain unclear. This study tested the hypothesis that Dapagliflozin would improve systemic arterial compliance and venous capacitance during exercise in patients with HFpEF. METHODS: In this secondary analysis from the CAMEO-DAPA trial (Cardiac and Metabolic Effects of Dapagliflozin in Heart Failure With Preserved Ejection Fraction Trial), 37 patients with HFpEF (mean age 68 ± 9 years, women 65%) underwent invasive hemodynamic exercise testing with simultaneous echocardiography at baseline and following treatment for 24 weeks with Dapagliflozin or placebo. Radial artery pressure (BP) was measured continuously using a fluid-filled catheter with transformation to aortic pressure, central hemodynamics were measured using high-fidelity micromanometers, and stressed blood volume was estimated from hemodynamic indices fit to a comprehensive cardiovascular model. RESULTS: There was no statistically significant effect of Dapagliflozin on resting BP, but Dapagliflozin reduced systolic BP during peak exercise (estimated treatment difference [ETD], −18.8 mm Hg [95% CI, −33.9 to −3.7] P =0.016). Reduction in BP was related to improved exertional total arterial compliance (ETD, 0.06 mL/mm Hg/m 2 [95% CI, 0.003–0.11] P =0.039) and aortic root characteristic impedance (ETD, −2.6 mm Hg/mL*sec [95% CI: −5.1 to −0.03] P =0.048), with no significant effect on systemic vascular resistance. Dapagliflozin reduced estimated stressed blood volume at rest and during peak exercise (ETD, −292 mm Hg [95% CI, −530 to −53] P =0.018), and improved venous capacitance evidenced by a decline in ratio of estimated stressed blood volume to total blood volume (ETD, −7.3% [95% CI, −13.3 to −1.3] P =0.020). Each of these effects of Dapagliflozin at peak exercise were also observed during matched 20W exercise intensity. Improvements in total arterial compliance and estimated stressed blood volume were correlated with decreases in body weight, and reduction in systolic BP with treatment was correlated with the change in estimated stressed blood volume during exercise (r=0.40, P =0.019). Decreases in BP were correlated with reduction in pulmonary capillary wedge pressure during exercise (r=0.56, P <0.001). CONCLUSIONS: In patients with HFpEF, treatment with Dapagliflozin improved systemic arterial compliance and venous capacitance during exercise, while reducing aortic characteristic impedance, suggesting a reduction in arterial wall stiffness. These vascular effects may partially explain the clinical benefits with sodium-glucose cotransporter-2 inhibitors in HFpEF. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04730947.

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P &amp;lt; .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Background: Dysbiosis of the oral microbiome and periodontitis (an inflammatory disease induced by dysbiosis) are plausible risk factors for cardiometabolic (CM) diseases. The relationship between the oral microbiome and CM mortality is less known. Hypothesis: Greater oral microbial diversity is associated with lower risks of all-cause and CM mortality, while poorer periodontal health is associated with greater mortality risk. Methods: We included n=5,255 adults aged 30+ from the National Health and Nutrition Examination Survey (NHANES) who had periodontal examinations and provided saliva samples at baseline. Baseline enrollment occurred in the 2009-2010 (n=2,681) and 2011-2012 (n=2,574) study cycles. Salivary microbiome data were generated in NHANES via 16s gene sequencing. Shannon and Inverse Simpson alpha diversity metrics were used to quantify oral microbial diversity for each participant. Clinical attachment loss (CAL) and probing depths from periodontal exams were included as historic and active measures of periodontitis, respectively. All-cause (non-accident deaths) and CM mortality (due to cardiovascular disease, cerebrovascular disease, diabetes, nephritis) through 2019 were ascertained via National Death Index linkages. We used multivariable Cox regression to compute hazard ratios and 95% confidence intervals (HR [95%CI]) of all-cause and CM mortality among 2 nd and 3 rd tertiles (vs 1 st tertile) of alpha diversity, CAL, and probing depth. We adjusted for study cycle, demographics, CM risk factors. Results: Mean age (SE) of participants was 48.1(0.2) years and 50% were men. Across 8.8 years of median follow-up, 193 all-cause deaths and 85 CM deaths occurred. Higher alpha diversity were associated with lower risks of all-cause and CM mortality, although non-significant. Relative risk of CM mortality in CAL Tertiles 3 vs. 1 is 1.81 (1.05, 3.09) (see Table ). Conclusion: Lower oral microbiome diversity and poorer indicators of periodontitis were not associated with all-cause and CM mortality.

Background: Dietary nitrate consumption is associated with cardiometabolic health in many but not all studies. The enterosalivary nitrate-nitrite-nitric oxide (NO 3 - NO 2 - NO) pathway requires the oral microbiome for NO production (a signaling molecule beneficial to cardiometabolic health) following nitrate intake. We hypothesize that the oral microbiome modifies the cardiometabolic benefits of nitrate intake. Methods: We analyzed cross-sectional data from 657 ORGINS participants. Dietary nitrate intakes and alternative healthy eating index (AHEI) scores were calculated from food frequency questionnaire responses and a US food database. Subgingival 16S rRNA microbial genes (Illumina, MiSeq) were sequenced, and PICRUSt2 estimated metagenomic content. The Microbiome Induced Nitric oxide Enrichment Score (MINES) was calculated as a microbial gene abundance ratio representing enhanced net capacity for NO generation. Cardiometabolic biomarker (systolic and diastolic blood pressure, HbA1C, glucose, insulin, and HOMA-IR) Z-scores were averaged to form a cardiometabolic Z-score (CMZ). Adjusted multivariable linear models regressed CMZ and individual Z-scores on nitrate intake tertiles. Results: Participants were mean age 31±9, 72% female, 31% White, 14% Black, and 28% Hispanic. Mean nitrate intake was 189±171 mg/day. Higher nitrate intake was significantly associated with lower CMZ, glucose, insulin, and HOMA-IR. Mean CMZ(SE) across dietary nitrate tertiles were 0.53(0.30), 0.35(0.31), and -0.11(0.30), p for trend=0.04; findings were attenuated after adjustment for AHEI (p for trend=0.12). In subgroup analysis by MINES level, higher nitrate intake was only associated with lower cardiometabolic biomarker levels among participants with a <median MINES even after AHEI adjustment (Table). Conclusion: Higher dietary nitrate intake was associated with lower cardiometabolic risk biomarker levels only among those with reduced potential for oral microbiome-dependent NO generation.

Introduction: Sarcopenia, characterized by loss of muscle mass and function, is prevalent in heart failure (HF) and associated with poor outcomes. We investigated alterations in sarcopenia index (SI), a surrogate marker of skeletal muscle mass, in HF, left ventricular assist device (LVAD) and heart transplant (HT) and assessed its relationship with inflammation and digestive tract (gut and oral) microbiota. Hypothesis: Sarcopenia will be associated with increased inflammation, dysbiotic microbial signatures, higher HF class, and earlier time post-HT or post LVAD. Methods: We enrolled 460 HF, LVAD and HT patients. Repeated measures pre and post procedures were obtained in a subset of LVAD and HT patients. Sarcopenia index (serum Creatinine/Cystatin C) and inflammatory biomarkers (C-reactive protein, interleukin-6, tumor necrosis factor-alpha) were measured in 271 and 622 blood samples, respectively. Gut and saliva microbiota were assessed via 16S rRNA sequencing among 335 stool and 341 saliva samples. Multivariable regression models were used to assess the relationship between SI and i) New York Heart Association class; ii) pre- vs. post-LVAD or HT; iii) biomarkers of inflammation and microbial diversity. Results: Median (interquartile range) ln-SI was -0.13(-0.32,0.05). Ln-SI decreased across worsening HF class, further declined within the 1-month after LVAD and HT and rebounded over time to the levels of symptomatic HF. Ln-SI demonstrated an inverse correlation with inflammation (r=-0.28, p<0.0001), and a positive correlation with gut (r=0.26, p<0.0001) and oral microbial diversity (r=0.24, p<0.0001). Presence of the gut taxa Roseburia inulinivorans was associated with increased SI. Conclusions: SI levels decreased in symptomatic HF and remained decreased long-term after LVAD and HT. SI levels covaried with inflammation, gut and oral microbiota in a similar fashion.