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.

Transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is possible among symptom-free individuals. Patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. We screened 489 symptom-free healthcare workers for SARS-CoV-2 and found no positive results, strongly suggesting that the prevalence of SARS-CoV-2 was <1%.

Background

While the gut microbiota is relatively stable through adulthood, its composition is influenced by various host and environmental factors, including changes in health, gastrointestinal processes (e.g., transit time, gastric acidity), medication use, and diet. The association of habitual diet, in the form of a posteriori-derived dietary patterns, and microbiota composition has not been adequately studied, particularly in older men.

Objective

The objective was to investigate the association of dietary patterns with the composition and diversity of the gut bacterial microbiota in community-dwelling, older men.

Methods

This cross-sectional study included 517 men who were participants in the Osteoporotic Fractures in Men (MrOS) Study (≥65 y of age at baseline in 2000-2002) and who provided a stool sample and completed an FFQ at MrOS Visit 4 in 2014-2016. Dietary patterns were derived by factor analysis. 16S ribosomal RNA target gene sequencing was performed and taxonomy assignments were derived using the Greengenes database. Linear regression and permutational multivariate analysis of variance (PERMANOVA) considered variations in alpha and beta diversity by dietary pattern, and a model that implements a 0-inflated Gaussian distribution of mean group abundance for each taxa (metagenomeSeq) assessed taxonomic variations by dietary pattern.

Results

In multivariable-adjusted models, greater adherence to the Western pattern was positively associated with families Mogibacteriaceae and Veillonellaceae and genera Alistipes, Anaerotruncus, CC-115, Collinsella, Coprobacillus, Desulfovibrio, Dorea, Eubacterium, and Ruminococcus, while greater adherence to the prudent pattern was positively associated with order Streptophyta, family Victivallaceae, and genera Cetobacterium, Clostridium, Faecalibacterium, Lachnospira, Paraprevotella, and Veillonella. The relative abundance of the dominant gut bacterial phyla, Bacteroidetes and Firmicutes, did not differ between participants with greater adherence to the Western pattern, compared with those with greater adherence to the prudent pattern. Dietary patterns were not associated with measures of alpha diversity, but beta diversity measures were significantly associated with both Western and prudent patterns.

Conclusions

We observed significant associations between dietary patterns and measures of gut microbial composition in this sample of community-dwelling, older men.

Periodontitis affects up to 50% of individuals worldwide, and 8.5% are diagnosed with diabetes. The high-comorbidity rate of these diseases may suggest, at least in part, a shared etiology and pathophysiology. Changes in oral microbial communities have been documented in the context of severe periodontitis and diabetes, both independently and together. However, much less is known about the early oral microbial markers of these diseases. We used a subset of the ORIGINS project dataset, which collected detailed periodontal and cardiometabolic information from 787 healthy individuals, to identify early microbial markers of periodontitis and its association with markers of cardiometabolic health. Using state-of-the-art compositional data analysis tools, we identified the log-ratio of Treponema to Corynebacterium bacteria to be a novel Microbial Indicator of Periodontitis (MIP), and found that this MIP correlates with poor periodontal health and cardiometabolic markers early in disease pathogenesis in both subgingival plaque and saliva.

Background The enterosalivary nitrate-nitrite-nitric oxide (NO₃-NO₂-NO) pathway generates NO following oral microbiota-mediated production of salivary nitrite, potentially linking the oral microbiota to reduced cardiometabolic risk. Nitrite depletion by oral bacteria may also be important for determining the net nitrite available systemically. We examine if higher abundance of oral microbial genes favoring increased oral nitrite generation and decreased nitrite depletion is associated with a better cardiometabolic profile cross-sectionally. Methods and Results This study includes 764 adults (mean [SD] age 32 [9] years, 71% women) enrolled in ORIGINS (Oral Infections, Glucose Intolerance, and Insulin Resistance Study). Microbial DNA from subgingival dental plaques underwent 16S rRNA gene sequencing; PICRUSt2 was used to estimate functional gene profiles. To represent the different components and pathways of nitrogen metabolism in bacteria, predicted gene abundances were operationalized to create summary scores by (1) bacterial nitrogen metabolic pathway or (2) biochemical product (NO₂, NO, or ammonia [NH₃]) formed by the action of the bacterial reductases encoded. Finally, nitrite generation-to-depletion ratios of gene abundances were created from the above summary scores. A composite cardiometabolic Z score was created from cardiometabolic risk variables, with higher scores associated with worse cardiometabolic health. We performed multivariable linear regression analysis with cardiometabolic Z score as the outcome and the gene abundance summary scores and ratios as predictor variables, adjusting for sex, age, race, and ethnicity in the simple adjusted model. A 1 SD higher NO versus NH₃ summary ratio was inversely associated with a -0.10 (false discovery rate q=0.003) lower composite cardiometabolic Z score in simple adjusted models. Higher NH₃ summary score (suggestive of nitrite depletion) was associated with higher cardiometabolic risk, with a 0.06 (false discovery rate q=0.04) higher composite cardiometabolic Z score. Conclusions Increased net capacity for nitrite generation versus depletion by oral bacteria, assessed through a metagenome estimation approach, is associated with lower levels of cardiometabolic risk.

BACKGROUND: Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is possible among symptom-free individuals and some patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. Limited data are available on the point prevalence of SARS-CoV-2 infection in symptom-free U.S. healthcare workers (HCW). METHODS: A cross-sectional convenience sample of symptom-free HCWs from the metropolitan area surrounding Minneapolis and St. Paul, Minnesota was enrolled between April 20 th and June 24 th , 2020. A participant self-collected nasopharyngeal swab (NPS) was obtained. SARS-CoV-2 infection was assessed via polymerase chain reaction. Participants were queried about their willingness to repeat a self-collection NPS for diagnostic purposes. We had >95% power to detect at least one positive test if the true underlying prevalence of SARS-CoV2 was ≥1%. RESULTS: Among n=489 participants 80% were female and mean age±SD was 41±11. Participants reported being physicians (14%), nurse practitioners (8%), physician's assistants (4%), nurses (51%), medics (3%), or other which predominantly included laboratory technicians and administrative roles (22%). Exposure to a known/suspected COVID-19 case in the 14 days prior to enrollment was reported in 40% of participants. SARS-CoV-2 was not detected in any participant. Over 95% of participants reported a willingness to repeat a self-collected NP swab in the future. CONCLUSIONS: The point prevalence of SARS-CoV-2 infection was likely <1% in a convenience sample of symptom-free Minnesota healthcare workers from April 20 th and June 24 th , 2020. Self-collected NP swabs are well-tolerated and a viable alternative to provider-collected swabs to preserve PPE.

Background

We examined the relationship between glucose homeostasis and comprehensive measures of cardiac structure and function among a representative sample of US Hispanics.

Methods and results

ECHO-SOL (Echocardiographic Study of Latinos), an echocardiographic ancillary study of the HCHS/SOL (Hispanic Community Health Study/Study of Latinos), enrolled 1818 Hispanic/Latino men (43%) and women (57%) aged ≥45 years (mean=56). Glucose intolerance was defined as follows: (1) prediabetes: hemoglobin (HbA1c) ≥5.7 and <6.5% and (2) diabetes mellitus: fasting plasma glucose ≥126 mg/dL, 2-hour postload glucose ≥200 mg/dL, HbA1c ≥6.5%, or hypoglycemic agent use. Uncontrolled diabetes mellitus was defined as HbA1c ≥7.0%. Insulin resistance was defined using the homeostatic model assessment for insulin resistance. Echocardiography examinations assessed left ventricular structure and systolic/diastolic function. Multivariable linear and logistic regression models were used. Prediabetes prevalence was 42%, and diabetes mellitus prevalence was 28% (47% uncontrolled). Glucose intolerance was associated with increased left ventricular posterior wall and interventricular septal and relative wall thicknesses (all P<0.05), reduced ejection fraction (P<0.01), reduced stroke and end-diastolic volumes (both P<0.001), decreased peak E' velocity (lateral and septal P<0.001), and increased E/E' ratio (lateral and septal P<0.01). The odds ratios (95% confidence intervals) for diastolic dysfunction among individuals with prediabetes and diabetes mellitus (versus diabetes mellitus free) were 1.36 (0.96-1.9) and 1.90 (1.3-2.8), respectively(P=0.006). Results were consistent for uncontrolled diabetes mellitus versus diabetes mellitus. Homeostatic model assessment for insulin resistance was associated with increased E/E' (P<0.001), and greater relative wall thickness and septal thickness (both P<0.05); lower stroke volume (P<0.0001); and lower peak lateral and septal E' velocities (both P<0.01).

Conclusions

Glucose intolerance and insulin resistance are associated with unfavorable cardiac structure and function, particularly worsened measures of diastolic function, even before the development of diabetes mellitus.

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.