Gut Microbiome-Based Diagnostic Model to Predict Coronary Artery Disease

In the present study, we aimed to characterize gut microbiome and develop a gut microbiome-based diagnostic model in patients with coronary artery disease (CAD). Prospectively, we collected 309 fecal samples from Central China and Northwest China and carried out the sequencing of the V3–V4 regions of the 16S rRNA gene. The gut microbiome was characterized, and microbial biomarkers were identified in 152 CAD patients and 105 healthy controls (Xinjiang cohort, n = 257). Using the biomarkers, we constructed a diagnostic model and validated it externally in 34 CAD patients and 18 healthy controls (Zhengzhou cohort, n = 52). Fecal microbial diversity was increased in CAD patients compared to that in healthy controls (P = 0.021). Phylum Bacteroidetes was increased in CAD patients versus healthy controls (P = 0.001). Correspondingly, 48 microbial markers were identified through a 10-fold cross-validation on a random forest model, and an area under the curve (AUC) of 87.7% (95% CI: 0.832 to 0.916, P < 0.001) was achieved in the Xinjiang cohort (development cohort, n = 257). Notably, an AUC of 90.4% (95% CI: 0.848 to 0.928, P < 0.001) was achieved using combined analysis of gut microbial markers and clinical variables. This model provided a robust tool for the prediction of CAD. It could be widely employed to complement the clinical assessment and prevention of CAD.