Bohn, Bruno

ABSTRACT Aims To investigate whether the association between the nitrite‐generating capacity of the subgingival microbiome and early cardiometabolic risk biomarkers varies by dietary nitrate intake. Materials and Methods Cross‐sectional data from 668 participants (mean age 31 ± 9 years, 73% women) were analysed. Dietary nitrate intake was calculated from food frequency questionnaires. Subgingival 16S rRNA sequencing (Illumina, MiSeq) and PICRUSt2 estimated microbial genes. The Microbiome‐Induced Nitric Oxide Enrichment Score (MINES) was calculated as a ratio of microbial gene abundances representing enhanced net capacity for NO generation. Adjusted multivariable linear models regressed cardiometabolic risk biomarkers (HbA1c, glucose, insulin, insulin resistance (HOMA‐IR), blood pressure) on nitrate intake and MINES together with a MINES × nitrate intake interaction term. Results Mean nitrate intake was 190 ± 171 mg/day. Significant interactions of MINES and nitrate intake were observed for insulin and HOMA‐IR ( p < 0.05). Among participants with a low MINES, higher nitrate intake was associated with lower HOMA‐IR (1.2 [1.1–1.4] vs. 1.5 [1.3–1.6]; p = 0.002), but levels were similar in those with high MINES ( p = 0.84). Conclusions A biomarker of higher microbial NO‐generating capacity in subgingival plaque is associated with lower insulin and insulin resistance among individuals with lower dietary nitrate intake. Future trials evaluating the cardiometabolic benefits of nitrate‐rich diets should incorporate measures of the entire oral microbiome.

Background The immune response to infections may become dysregulated and promote myocardial damage contributing to heart failure (HF). We examined the relationship between infection‐related hospitalization (IRH) and HF, HF with preserved ejection fraction, and HF with reduced ejection fraction. Methods and Results We studied 14 468 adults aged 45 to 64 years in the ARIC (Atherosclerosis Risk in Communities) Study who were HF free at visit 1 (1987–1989). IRH was identified using select International Classification of Diseases ( ICD ) codes in hospital discharge records and was treated as a time‐varying exposure. HF incidence was defined as the first occurrence of either a hospitalization that included an ICD, Ninth Revision ( ICD‐9 ) discharge code of 428 (428.0–428.9) among the primary or secondary diagnoses or a death certificate with an ICD‐9 code of 428 or an ICD, Tenth Revision ( ICD‐10 ) code of I50 among any of the listed diagnoses or underlying causes of death. We used multivariable‐adjusted Cox proportional hazards models to assess the association between IRH and incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. Median follow‐up time was 27 years, 55% were women, 26% were Black, mean age at baseline was 54±6 years, 46% had an IRH, and 3565 had incident HF. Hazard ratio (HR) for incident HF events among participants who had an IRH compared with those who did not was 2.35 (95% CI, 2.19–2.52). This relationship was consistent across different types of infections. Additionally, IRH was associated with both HF with reduced ejection fraction and HF with preserved ejection fraction: 1.77 (95% CI, 1.35–2.32) and 2.97 (95% CI, 2.36–3.75), respectively. Conclusions IRH was associated with incident HF, HF with reduced ejection fraction, and HF with preserved ejection fraction. IRH might represent a modifiable risk factor for HF pathophysiology.

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.

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.

AbstractAimWe investigated whether periodontal measures are cross‐sectionally associated with prediabetes and cardiometabolic biomarkers among non‐diabetic younger adults.Materials and MethodsOne thousand seventy‐one participants (mean age = 32.2 years [SE = 0.3]; 73% female) from the Oral Infections, Glucose Intolerance and Insulin Resistance Study were enrolled. Full‐mouth clinical attachment loss (fm‐CAL), probing depth (fm‐PD) and bleeding on probing were ascertained. Interproximal CAL (i‐CAL) and probing depths (i‐PD) served as our primary exposures. Glucose, HbA1c, insulin and insulin resistance (HOMA‐IR) outcomes were assessed from fasting blood. Prediabetes was defined per American Diabetes Association guidelines. Prediabetes prevalence ratios (PR [95% CI]) and mean [SE] cardiometabolic biomarkers were regressed on periodontal variables via multivariable robust variance Poisson regression or multivariable linear regression.ResultsPrevalence of prediabetes was 12.5%. Fully adjusted prediabetes PR in Tertiles 3 versus 1 of mean i‐CAL was 2.42 (1.77, 3.08). Fully adjusted fasting glucose estimates across i‐CAL tertiles were 83.29 [0.43], 84.31 [0.37], 86.48 [0.46]; p for trend <.01. Greater percent of sites with i‐PD ≥3 mm showed elevated natural‐log‐HOMA‐IR after adjustment (0%–12% of sites = 0.33 [0.03], 13%–26% of sites = 0.39 [0.03], ≥27% of sites = 0.42 [0.03]; p for trend = .04).Conclusionsi‐CAL (vs. fm‐CAL) was associated with elevated fasting glucose and prediabetes, whereas i‐PD (vs. fm‐PD) was associated with insulin resistance. Future studies are needed to examine periodontal disease and incident prediabetes.