Abstract Body (Do not enter title and authors here): Background:
Early identification of acute coronary syndrome (ACS) is critical for reducing mortality, especially in patients with stable coronary artery disease (sCAD). While the gut microbiome is implicated in atherosclerosis, its role in ACS onset and recovery remains unclear.
Objective:
To characterize gut microbial and plasma metabolic alterations specific to ACS, and evaluate their potential as biomarkers for diagnosis and recovery monitoring.
Methods:
We enrolled 548 participants, including 175 with normal coronary arteries (NCA), 161 with primary sCAD, and 212 with ACS. Multi-omics analyses were performed, including metagenomic sequencing of fecal samples and untargeted LC-MS-based metabolomics of plasma. Additionally, 52 patients with a history of ACS who recovered post-revascularization were included to assess biomarker reversibility. Statistical analyses and machine learning models were used to identify key features and evaluate their discriminative power.
Results:
ACS patients exhibited a distinct pro-inflammatory gut microbiota profile, with increased abundance of Streptococcus, Rothia, Bifidobacterium, and Clostridium species, and a concurrent rise in plasma levels of 2-hydroxybutyrate (2-HB), succinate, and phenylalanine metabolites (all FDR-adjusted p＜0.05). These changes were only partially present in sCAD and largely normalized in recovery patients. Integration of microbiome, metabolome, and clinical data in machine learning models markedly improved diagnostic accuracy (AUC = 0.91 for ACS vs NCA; AUC = 0.85 for ACS vs sCAD). Furthermore, metabolite-pathway correlations suggested that ACS-specific bacteria modulate key metabolic pathways such as propionate and ketone metabolism, while anti-inflammatory metabolites like tryptophan derivatives were depleted.
Conclusions:
This study reveals a distinct gut microbial and metabolic signature associated with ACS and its resolution. These findings highlight the potential of integrating microbial and metabolic biomarkers into cardiovascular risk stratification, offering new avenues for early ACS detection and personalized therapeutic interventions.