Long-term Metformin Alters Gut Microbiota and Serum Metabolome in Coronary Artery Disease Patients After Percutaneous Coronary Intervention to Improve 5-year Prognoses: A Multi-omics Analysis

Abstract

Background: About 20% of patients with coronary artery disease (CAD) experience adverse events within five years of undergoing percutaneous coronary intervention (PCI) for acute myocardial infarction. In these patients, the impact of metformin on long-term prognosis remains uncertain.

Methods: This study enrolled 22 metformin (Met)-CAD patients with diabetes mellitus (DM) who had been administered metformin for at least six months before PCI, 14 non-Met CAD-DM patients with DM who had never taken metformin or had stopped taking metformin for a year before PCI, and 22 matched healthy controls. A 5-year follow-up was conducted to collect clinical prognosis data. Fecal 16S rRNA sequencing and serum untargeted metabolomics analyses were performed. BugBase was utilized to analyze the possible functional changes in the gut microbiome. Multi-omics analysis was conducted using Spearman's correlation to explore the interactions between metformin, gut microbiome, serum metabolites, and clinical prognosis.

Results: Metformin significantly lowered the 5-year major adverse cardiac events (MACEs) in Met CAD-DM patients. We found a higher abundance of Bacteroides coprocola, Bacteroides massiliensis, Phascolarctobacterium succinatutens, and Eubacterium coprostanoligenes in the Met CAD-DM patients, as well as an increase in hydroxy-alpha-sanshool (HAS) and decenoylcarnitine and a decrease in tridec-10-enoic acid, Z-vad-fmk (benzyloxycarbonyl-Val-Ala-Asp (OMe)-fluoromethylketone), 3,9-dimethyluric acid in blood serum. Multi-omics analysis revealed that alterations in the gut microbiome and serum metabolites are significantly associated with the 5-year prognosis of CAD-DM.

Conclusions: Metformin significantly improved the 5-year prognosis of CAD patients following PCI. Metformin tended to have more positive effects on the commensal flora and metabolic profiles, which may explain its beneficial effects on cardiovascular health. This study revealed the potential associations between metformin and the gut microbiome, an associated alteration in serum metabolome, and the impact on the host immune system and metabolic pathways.

Keywords: coronary artery disease; diabetes mellitus; gut microbiota; metformin; multiomic analyses.

Fig. 1.

Medication of metformin affects the taxonomic features of gut microbiota in patients with CAD-DM. (A) Observed Species Richness Index, representing the number of operational taxonomic units (OTUs) identified in each group. Box-plot features represent the mean $\pm$ SD level. (B) Beta diversity analyzed by constrained PCoAs (CPCoA) plot based on Bray-Curtis distances. (PCo1 15.26%, PCo2 9.926%). (C) Manhattan plot demonstrating the differentially abundant gut microbes and their contributions to each phylum. Filled triangles, hollow inverted triangles, and solid circles indicate OTUs enriched, depleted, and without significant difference, respectively. The color of each marker represents the different taxonomic affiliation of the OTUs, and the size corresponds to their relative abundances using log2 transformed counts per million (CPM) values. (D) Chord plot showing the dominant classes and their contribution to each group. (E) Relative abundances of bacteria among groups at the family level. (F) Differential gut microbes between the non-Met CAD-DM group and the met CAD-DM group at the genus level. (G) Volcano plots showing differential gut microbes at the species level in patients between the non-Met CAD-DM group and the met CAD-DM group. “a” means there isn’t a significant difference. PCol, principal co-ordinates 1; PCoA, principal coordinate analysis.

Fig. 2.

Metformin changed the abundance of specific microbes and altered the potential function of the gut microbiome, associated with 5-year clinical outcomes. (A) Abundance of four significantly different species among all three groups. (B) Relative abundance of a form of the bacteria containing mobile elements predicted based on BugBase database. (C) Relative abundance of a form of the bacteria forming biofilms predicted based on BugBase database. (D) Relative abundance of a form of the gram-negative bacteria predicted based on BugBase database. (E) Relative abundance of a form of the gram-positive bacteria predicted based on BugBase database. (F) Relative abundance of potentially pathogenic bacteria predicted by BugBase (FDR-adjusted p = 0.43160). (G) Relative abundance of stress-tolerant bacteria predicted by BugBase (FDR-adjusted p = 0.81). (H) Spearman correlation between differential gut microbes and 5-year clinical outcomes. The microbes or metabolites are highlighted in red (enriched in Met CAD-DM) and blue (depleted in Met CAD-DM). *FDR-adjusted p 0.05, **FDR-adjusted p 0.01, analyzed by edgeR. (I) The relative abundance of representative harmful and beneficial species. The differential microbes were filtered with FDR-adjusted p 0.05. CTA, computed tomography angiography; FDR, false discovery rate.

Fig. 3.

Spearman correlations between differential serum metabolites and microbes associated with 5-year clinical outcomes. (A) Spearman correlation between differential serum metabolites and 5-year clinical outcomes. (B) The relative abundance of six key serum metabolites associated with patients’ clinical prognosis. (C) Spearman correlation between differential serum metabolites and differential gut microbes. The microbes or metabolites are highlighted in red (enriched in Met CAD-DM) and blue (depleted in Met CAD-DM). *FDR-adjusted p 0.05, **FDR-adjusted p 0.01, analyzed by edgeR.

Fig. 4.

The potential mechanism of metformin’s beneficial effect on cardiovascular health. Metformin reshaped the gut microbiome by increasing the abundace of beneficial microbes and preserving the diversity of the gut microbiome. This change further maintained the stability of the intestinal mucus barrier and inhibited the production of inflammatory cytokines. The microbiome-derived metabolites helped stabilize atherosclerotic plaques. In contrast, individuals not taking metformin experienced disrupted gut microbiota diversity. The intestinal mucus barrier exhibited dysfunction, and the production of inflammatory factors was not inhibited. Moreover, the microbiome-derived metabolites promoted macrophage activation and further led to atherosclerotic plaque disruption. SCFAs, short-chain fatty acids; LCFAs, long-chain fatty acids; HAS, hydroxy-alpha-sanshool.