The oral microbiome in alcohol use disorder: a longitudinal analysis during inpatient treatment.

BACKGROUND: Alcohol use disorder (AUD)-induced disruption of oral microbiota can lead to poor oral health; there have been no studies published examining the longitudinal effects of alcohol use cessation on the oral microbiome. AIM: To investigate the oral microbiome during alcohol cessation during inpatient treatment for AUD. METHODS: Up to 10 oral tongue brushings were collected from 22 AUD patients during inpatient treatment at the National Institutes of Health. Alcohol use history, smoking, and periodontal disease status were measured. Oral microbiome samples were sequenced using 16S rRNA gene sequencing. RESULTS: Alpha diversity decreased linearly during treatment across the entire cohort (P = 0.002). Alcohol preference was associated with changes in both alpha and beta diversity measures. Characteristic tongue dorsum genera from the Human Microbiome Project such as Streptococcus, Prevotella, Veillonella and Haemophilus were highly correlated in AUD. Oral health-associated genera that changed longitudinally during abstinence included Actinomyces, Capnocytophaga, Fusobacterium, Neisseria and Prevotella. CONCLUSION: The oral microbiome in AUD is affected by alcohol preference. Patients with AUD often have poor oral health but abstinence and attention to oral care improve dysbiosis, decreasing microbiome diversity and periodontal disease-associated genera while improving acute oral health.

The oral microbiome of patients undergoing treatment for severe aplastic anemia: a pilot study.

The microbiome, an intriguing component of the human body, composed of trillions of microorganisms, has prompted scientific exploration to identify and understand its function and role in health and disease. As associations between microbiome composition, disease, and symptoms accumulate, the future of medicine hinges upon a comprehensive knowledge of these microorganisms for patient care. The oral microbiome may provide valuable and efficient insight for predicting future changes in disease status, infection, or treatment course. The main aim of this pilot study was to characterize the oral microbiome in patients with severe aplastic anemia (SAA) during their therapeutic course. SAA is a hematologic disease characterized by bone marrow failure which if untreated is fatal. Treatment includes either hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST). In this study, we examined the oral microbiome composition of 24 patients admitted to the National Institutes of Health (NIH) Clinical Center for experimental SAA treatment. Tongue brushings were collected to assess the effects of treatment on the oral microbiome. Twenty patients received standard IST (equine antithymocyte globulin and cyclosporine) plus eltrombopag. Four patients underwent HSCT. Oral specimens were obtained at three time points during treatment and clinical follow-up. Using a novel approach to 16S rRNA gene sequence analysis encompassing seven hypervariable regions, results demonstrated a predictable decrease in microbial diversity over time among the transplant patients. Linear discriminant analysis or LefSe reported a total of 14 statistically significant taxa (p < 0.05) across time points in the HSCT patients. One-way plots of relative abundance for two bacterial species (Haemophilus parainfluenzae and Rothia mucilaginosa) in the HSCT group, show the differences in abundance between time points. Only one bacterial species (Prevotella histicola) was noted in the IST group with a p value of 0.065. The patients receiving immunosuppressive therapy did not exhibit a clear change in diversity over time; however, patient-specific changes were noted. In addition, we compared our findings to tongue dorsum samples from healthy participants in the Human Microbiome Project (HMP) database and found among HSCT patients, approximately 35% of bacterial identifiers (N = 229) were unique to this study population and were not present in tongue dorsum specimens obtained from the HMP. Among IST-treated patients, 45% (N = 351) were unique to these patients and not identified by the HMP. Although antibiotic use may have likely influenced bacterial composition and diversity, some literature suggests a decreased impact of antimicrobials on the oral microbiome as compared to their effect on the gut microbiome. Future studies with larger sample sizes that focus on the oral microbiome and the effects of antibiotics in an immunosuppressed patient population may help establish these potential associations.

Mobile Health Technology Can Objectively Capture Physical Activity (PA) Targets Among African-American Women Within Resource-Limited Communities-the Washington, D.C. Cardiovascular Health and Needs Assessment.

BACKGROUND: Little is understood about using mobile health (mHealth) technology to improve cardiovascular (CV) health among African-American women in resource-limited communities. METHODS: We conducted the Washington, D.C. CV Health and Needs Assessment in predominantly African-American churches in city wards 5, 7, and 8 with the lowest socioeconomic status based on community-based participatory research (CBPR) principles. The assessment measured CV health factors: body mass index (BMI), fasting blood glucose and cholesterol, blood pressure, fruit/vegetable (F/V) intake, physical activity (PA), and smoking. Participants were trained to use a PA monitoring wristband to measure 30 days of PA, wirelessly upload the PA data to hubs at the participating churches, and access their data from a church/home computer. CV health factors were compared across weight classes. RESULTS: Among females (N = 78; 99 % African-American; mean age = 59 years), 90 % had a BMI categorized as overweight/obese. Across weight classes, PA decreased and self-reported sedentary time (ST) increased (p ≤ 0.05). Diastolic blood pressure and glucose increased across weight classes (p ≤ 0.05); however, cholesterol, glucose, and BP were near intermediate CV health goals. CONCLUSIONS: Decreased PA and increased ST are potential community intervention targets for overweight and obese African-American women in resource-limited Washington D.C. areas. mHealth technology can assist in adapting CBPR intervention resources to improve PA for African-American women in resource-limited communities.

Discrepancies in Race and Ethnicity Documentation: a Potential Barrier in Identifying Racial and Ethnic Disparities.

BACKGROUND: Data collection on race and ethnicity is critical in the assessment of racial disparities related to health. Studies comparing clinical and administrative data show discrepancies in race documentation and attribution. METHODS: Self-reported data from two studies were compared to demographics in the electronic health record (EHR) extracted from the Biomedical Translational Research Information System (BTRIS) repository. McNemar and Bhapkar analyses were conducted to quantify the agreement of ethnicity and race between self-reported and EHR data. Pearson's chi-square tests were used to explore the relationship between acculturation, length of time in the USA, country of residence, and how individuals self-reported their race. RESULTS: The sample (n = 280) was predominantly female (52.1 %), with a mean age of 47 (SD ± 13.74), mean years in the USA were 12.8 (SD ± 11.67) and the majority were born outside of the USA. (55.6 %). Those who self-identified as Hispanic (n = 208) scored a mean of 5.5 (SD ± 3.07) on the short acculturation scale (SAS) that ranges 4 to 20; lower scores indicate less acculturation. A significant difference was found between the way race is reported in the electronic medical record and self-reported data among those people who identified as Hispanic, with significant differences in the white (p < 0.0001) and other (p < 0.0001) categories. CONCLUSIONS: The misclassification of race is most frequent in those individuals who self-identified as Hispanic. As the Hispanic population in the USA continues to grow, understanding the factors that affect the way that individuals from this heterogeneous population self-report race may provide important guidance in tailoring care to address health disparities.