Background

From the results of physiological, epidemiological, and omics-based studies, complemented by cellular and animal experiments, microbial communities might coordinate or modify a significant portion of environmental impacts on human health [1,141]. Prior observational investigation has upheld the connection between periodontitis and AF irrespective of known confounders [142]. In an animal model, periodontitis has been observed to strengthen the immune activation of the atrial myocardium, thereby subverting the electrophysiological properties of the atria [143]. A recent population-based cohort study of 161,286 subjects revealed that improvements in oral hygiene such as regular professional dental cleanings and frequent tooth brushing were linked to a decreased risk of AF [144]. However, few experiments have been conducted to study the role and mechanisms of oral flora in AF pathophysiology. Future investigations may benefit from interrogating the connection between the characteristics as well as the metabolism of oral flora and AF. Considering the treatment of periodontitis as a highly feasible and daily manageable measure for AF prevention, randomized clinical trials dealing with standardized oral flora interventions are warranted to demonstrate the advantage of periodontal treatment in mitigating AF risk.

Because of the heterogeneity and transparency of the gut microbiome as well as state-of-the-art technological advances, meta-omics approaches hold a prospect as a gateway to unveiling host-microbiome interactions and evaluating causality in the clinical milieu. Nevertheless, it has restrictions and requires further innovation. A portion of the data could not be allotted on account of insufficient reference databases, especially the scarcity of eukaryotic and viral matches, which hampered the extraction of organismal and functional information. Currently, only the bacterial community has been extensively studied, whilst other constituents of the gut microbiota, such as viruses, fungi, or archaea, have not been prolifically explored. Zuo et al. [38] have demonstrated that enterovirus features were correlated with AF for the first time, which has tremendous potential value in anticipating ablation outcomes (Table 1). Therefore, the conjunction of these members in microbial-AF association analysis may unlock a fresh door for potential therapeutic approaches. Furthermore, another difficulty of special pertinence to microbiome studies is the drastic inter-individual variation in the configuration of the gut microbiome and the subsequent host metabolism induced by dietary interventions. In turn, applying machine learning to datasets encompassing diet, gut flora, and genetics might deliver the solution. Apart from direct causal routes, specific bacteria or microbiota constituents may be implied by incident or simply as modifying variables in drug regimens and genetic studies. Thus, the microbiome remains a crucial segment of personalized and precision medicine.