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Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session E

Poster L28 - Individual health factors inform the link between gut microbiome and cardiovascular health: Insights from a cross-sectional analysis of resting heart rate

Saturday, October 26, 2024
10:00 AM – 11:00 AM EST
Location: Exhibit Hall E, F & G

Introduction:  The composition and diversity of the gut microbiome is associated with physical fitness level in humans. Targeted intervention studies in specific groups have demonstrated that exercise and the gut microbiome influence each other 1,2. A healthy lifestyle with adequate exercise can cultivate a healthy gut microbiome that in turn can help improve how the body responds to exercise training. One important component of physical fitness is overnight resting heart rate (RHR), with a lower RHR typically indicating higher fitness. The microbiome plays a role in cardiovascular disease 3 so it is important to better understand its role in cardiovascular health as a component of overall fitness. This observational study investigates how RHR is associated with the gut microbiome in the Project Baseline Health Study, a large cross-sectional representative group of United States residents. It further investigates how this relationship varies across key demographic and health covariates chosen according to data availability and literature support: age 4, sex 4, race 5, ethnicity 4, waist-height ratio 4,6, smoking status 4, alcohol use level 4, acid reflux disease 4, prediabetes or type 2 diabetes 4,5, depression 4,7, blood pressure 8,9, and self-reported bowel movement quality (con, constipation; and dia, diarrhea) 4. This work sought to understand how gut microbiome is associated with RHR, and also how other health conditions interact with this association.

Materials and

Methods:  Overnight resting heart rate was computed as the average of the first week of overnight resting heart rate measurements reported by the Verily Study Watch provided to all Project Baseline participants. Participants provided a stool sample at their first study visit the first day of that same week, which was used to profile their gut microbiome by sequencing 16S ribosomal RNA. Sequences were denoised with dada2 10, taxonomy was assigned with DECIPHER 11 referencing Genome Taxonomy Database, and a custom phylogenetic tree was constructed with FastTree 12. Community alpha diversity was computed as the number of observed species, Shannon diversity, inverse Simpson diversity, and Faith’s Phylogenetic Diversity (PD). Pearson correlations between RHR and each alpha diversity measure were calculated, and Pearson correlations between RHR and Shannon diversity were calculated for health covariate subgroups. Subgroups were defined as binary groupings of all covariates; with thresholds for continuous covariates (for this analysis only; thresholds were not used for any other analyses) as follows: elevated systolic blood pressure > 120 mmHg 13, elevated alcohol use score > 2 on AUDIT-C 14, age > 65 15,16, waist > 0.5 times height 6. The association between across-individual gut microbiome similarity (beta diversity) and RHR were assessed with MirKAT statistical test 17, accounting for Bray-Curtis, Unifrac, and Weighted Unifrac community distances, and correcting for all covariates. Individual bacteria strains differentially associated with RHR were assessed with LinDA tests 18, including both uncorrected and corrected for several covariates.

Results, Conclusions, and Discussions: There is a rich connection between gut microbial diversity and RHR in this representative cohort of adult United States residents. Increased gut microbial diversity, measured by multiple indices, was significantly correlated with reduced RHR (Pearson R = 0.2, p< 0.001). This correlation between microbiome and RHR was slightly stronger within certain subgroups (see Figure ). Gut microbial community similarity has a significant association (MirKAT P = 0.002) with resting heart rate even after correcting for all health covariates; thus, across health phenotypes, individuals with similar gut microbiomes may have similar resting heart rates. At a granular level, several amplicon sequences showed a significant association with resting heart rate. Without correction for covariates, 22 amplicon sequences had an adjusted p-value under 0.01, including 10 from the family Lachnospiraceae and 4 from the family Ruminococcaceae, both families previously known for associations with health outcomes 19–21. Correction for covariates weakened but did not eliminate the statistical significance of associations of specific amplicons with RHR. In addition to the measured covariates, there are other unmeasured variables, such as diet, exercise, or other cardiac conditions which are important to heart rate regulation, and it remains to be seen how the gut microbiome fits in the context of these factors. Given this context, our preliminary findings do support an association between the gut microbiome and cardiovascular health. The results also suggest that the proposed connection between people’s cardiovascular health and gut microbiome may also be associated with their other health conditions, and accordingly that future research exploring the possibility of the gut microbiome as a potential target for therapeutic interventions may be most effective if it targets and/or adjusts for specific populations.

Acknowledgements (Optional):  References
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