GUT MICROBIOTA AND CARDIOMETABOLIC RISK FACTORS IN CORONARY ARTERY DISEASE PATIENTS WITH ATRIAL FIBRILLATION

The aim: To estimate gut microbiota composition peculiarities in patients with coronary artery disease (CAD) and atrial fibrillation (AF) and to evaluate their connections with known cardiometabolic risk factors (CRF). Materials and methods: 300 patients formed 3 groups: I group – 149 CAD patients without rhythm disorders, II group – 124 patients with CAD and AF paroxysm and control group (CG) – 27 patients without CAD and arrhythmias. 16-S rRNA sequencing checked gut microbiota composition. CRF which was explored are total cholesterol (TC), triglycerides (TG), low density lipoproteins (LDL), high density lipoproteins (HDL), lipoprotein α (Lpα), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), C-reactive protein (CRP), interleukin-6 (IL-6), trymetilamine (TMA) and trymetilamine-N-oxide (TMAO). Results: The significant changes of gut microbiota composition were found in CAD patients with AF paroxysm in comparison with CAD patients without arrythmia as increasing Actinomycetota phulum (P<0.05); increasing Actinobacter Spp. and decreasing Blautia Spp., Roseburia Inulinivorans, Bacteroides Thetaiotaomicron (P<0.05). Moreover, Actinobacter Spp., Akkermansia Muciniphila, Streptococcus Spp., Bacteroides Thetaiotaomicron, Bifidobacterium Spp. have the highest amount of significant correlations with CRF (body mass index, LDL levels; P<0.05). By the ROC-analysis we found the acceptable role of Lactobacillus Spp., Bifidobacterium Spp., Bacteroides Thetaiotaomicron, Blautia Spp., Actinobacter Spp. and Eubacterium Rectale in AF paroxysm occurrence in CAD patients (area under ROC-curve (AUC)<0.7). We found gut microbiota combinations with highest AUC for AF paroxysm in CAD patient: all of them include Actinobacter Spp (Actinobacter Spp. + 0.32 * Streptococcus Spp., AUC = 0.9008; 1.56 * Actinobacter Spp. – Blautia Spp., AUC = 0.9008;1.84 * Actinobacter Spp. – Akkermansia Muciniphila, AUC = 0.9008). AF paroxysm duration in CAD patients depends of plasma IL-6, TMAO, fecal Actinobacter Spp. and Akkermansia Muciniphila by the linear multifactorial regression analysis (AF paroxysm duration = 0.68*(Actinobacter Spp., lg/CFU/ml) – 3.33*(Akkermansia Muciniphila, lg/CFU/ml) – 0.6*IL6 – 0.34*TMAO – 0.98). Conclusions: Gut microbiota condition is closely connected with occurrence AF of paroxysm in CAD patients. To find out the new ways of gut microbiota and CRF correction will be interesting in future investigations.