# Gut microbiome compositional clusters in association with cardiovascular risk: An observational cohort study

## TL;DR

This study found that different gut microbiome profiles are linked to varying levels of cardiovascular risk, suggesting potential for personalized risk assessment and treatment.

## Contribution

The study introduces unsupervised gut microbiome profiling as a novel method for cardiovascular risk stratification.

## Key findings

- Two distinct gut microbiome clusters were identified, with one associated with lower cardiovascular risk.
- Cluster L showed healthier profiles and lower incidence of major adverse cardiac events over 7.4 years.
- Cluster L had higher microbial diversity and a lower Bacillota-to-Bacteroidetes ratio compared to Cluster H.

## Abstract

The gut microbiome (GM) is increasingly recognized for its role in atherosclerosis development. However, its potential as a biomarker for risk-stratification in patients with atherosclerotic cardiovascular (CV) comorbidities remains under-explored. This study aimed to identify distinct GM clusters associated with elevated CV risk.

In this prospective observational cohort, patients with coronary artery disease, hypertension, hyperlipidemia, or diabetes mellitus referring to Mayo Clinic from 2013 to 2018 were enrolled. Bacterial DNA was analyzed in the V3-V5 region of 16S rDNA. Beta-diversity was plotted using Principal Coordinates Analysis. Unsupervised hierarchical clustering of the GM classified participants into two clusters. Cox regression evaluated the association between clusters and Major Adverse Cardiac Events (MACE), defined as a composite of cardiac events, heart failure, and all-cause mortality. Permutational Multivariate Analysis of Variance identified clinical factors contributing to cluster assignment. Linear Discriminant analysis identified GM taxa with differential abundance among clusters and their effect sizes.

Among 211 participants (median age 60 [IQR: 50–70] years; 57.3% male), two distinct GM profiles emerged (Cluster H: N = 104; Cluster L: N = 107, P < 0.001). Cluster L participants were younger (P < 0.001), more likely female (P = 0.009), and had healthier CV profiles, including lower BMI (P = 0.007), hypertension (P = 0.010), hyperlipidemia (P = 0.005), and lower coronary artery disease prevalence (P = 0.003). Over a median follow-up of 7.4 years, Cluster L had a significantly lower incidence of MACE compared to Cluster H (HR = 0.48, 95% CI: 0.26–0.91, P = 0.024). Cluster L had higher operational taxonomic units (P < 0.001) and lower Bacillota-to-Bacteroidetes ratio (P < 0.001) compared to Cluster H. The predominant taxa in Cluster L included Bacteroides, Alistipes, and Parabacteroides, whereas Blautia, Agathobacter, and Clostridium sensu stricto-1 were more abundant in Cluster H.

Distinct GM profiles are associated with varying CV risk, highlighting the potential of unsupervised GM profiling as a novel tool for risk stratification and individualized therapy.