Gut microbiota species-based random forest model distinguished diabetes patients with myocardial infarction from those without with AUC 0.868, identifying distinctive microbial and functional signatures.
Observational (n=62)
No
Does gut microbiome composition and function differ between patients with type 2 diabetes mellitus complicated by myocardial infarction and those with diabetes alone?
Patients with type 2 diabetes complicated by myocardial infarction exhibit distinct gut microbial compositions and functional gene signatures that can accurately predict MI risk.
Effect estimate: AUC 0.868 for microbial species–based model distinguishing DM+MI patients
p-value: p=0.010 for KEGG KO units difference; non-significant for overall microbial diversity (p=0.076)
Abstract Objective This study aimed to investigate gut microbiota composition and metabolic functions in patients with type 2 diabetes mellitus (DM) complicated by myocardial infarction (MI) and to explore potential mechanisms linking the gut microbiome to MI development. Methods Sixty patients with DM complicated by MI and 52 patients with DM alone were initially recruited. After quality control, 29 DM + MI patients and 33 DM patients were included in the final analysis. Gut microbial profiles were characterized using shotgun metagenomic sequencing and bioinformatics analyses. Microbial diversity, composition, and gene functions were compared between groups based on KEGG, COG, and CAZy annotations. Results Overall microbial diversity and metabolic profiles were comparable between the two groups; however, significant differences were observed in specific taxa and functional genes. Taxa enriched in the DM + MI group included Bacteroidales, Prevotellaceae, and Lachnospiraceae. In total, 510 KEGG orthology (KO) units and 21 pathways—including ABC transporters, quorum sensing, and general metabolic pathways—differed significantly between groups. Carbohydrate transport and metabolism, as well as glycoside hydrolase activity, represented the most enriched functional categories. Random forest models based on selected microbial species, KO units , and KEGG pathways achieved areas under the curve (AUCs) of 0.868, 0.885, and 0.820, respectively. Conclusion Patients with DM complicated by MI exhibit distinct gut microbial compositions and functional gene signatures compared with patients with DM alone. These microbiome-based markers may contribute to early risk stratification and provide potential targets for microbiota-focused interventions to mitigate MI risk in patients with diabetes.
Zhang et al. (Mon,) conducted a observational in Patients with type 2 diabetes mellitus complicated by myocardial infarction and patients with type 2 diabetes mellitus alone (n=62). Gut microbiota metagenomic sequencing analysis vs. Patients with type 2 diabetes mellitus without myocardial infarction was evaluated on Gut microbial diversity, composition and function differences between patients with type 2 diabetes mellitus and myocardial infarction versus type 2 diabetes mellitus alone as determined by metagenomic sequencing (AUC 0.868 for microbial species–based model distinguishing DM+MI patients, p=p=0.010 for KEGG KO units difference; non-significant for overall microbial diversity (p=0.076)). Gut microbiota species-based random forest model distinguished diabetes patients with myocardial infarction from those without with AUC 0.868, identifying distinctive microbial and functional signatures.
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