Abstract

Specific alterations of gut microbiota (GM) in atrial fibrillation (AF) patients, including elevated microbial diversity, particularly perturbed composition, imbalanced microbial function, and associated metabolic pattern modifications have been described in our previous report. The current work aimed to assess the association of GM composition with AF recurrence (RAF) after ablation, and to construct a GM-based predictive model for RAF. Gut microbial composition and metabolic profiles were assessed based on metagenomic sequencing and metabolomic analyses. Compared with non-AF controls (50 individuals), GM composition and metabolomic profile were significantly altered between patients with recurrent AF (17 individuals) and the non-RAF group (23 individuals). Notably, discriminative taxa between the non-RAF and RAF groups, including the families Nitrosomonadaceae and Lentisphaeraceae, the genera Marinitoga and Rufibacter, and the species Faecalibacterium sp. CAG:82, Bacillus gobiensis, and Desulfobacterales bacterium PC51MH44, were selected to construct a taxonomic scoring system based on LASSO analysis. An elevated area under curve (0.954) and positive net reclassification index (1.5601) for predicting RAF compared with traditional clinical scoring (AUC=0.6918) were obtained. The GM-based taxonomic scoring system theoretically improves the model performance. These data provide novel evidence that supports incorporating the GM factor into future recurrent risk stratification.