Microbial Network Remodeling in Aortic Stenosis and Regurgitation

B. C. Bartsch (Bonn)1, C. Hesse (Bonn)1, S. Nesic (Bonn)2, M. Al Zaidi (Bonn)1, R. N. Jamin (Bonn)1, A. Ackerschott (Bonn)1, H. Billig (Bonn)1, N. Lübbering (Bonn)1, A. H. Schott (Bonn)1, M. Parcina (Bonn)3, M. Hamiko (Bonn)4, F. Bakhtiary (Bonn)4, G. Nickenig (Bonn)1, C. Kurts (Bonn)5, C. K. Weisheit (Bonn)6, S. Zimmer (Bonn)1
1Universitätsklinikum Bonn Medizinische Klinik und Poliklinik II Bonn, Deutschland; 2Universität Bonn Core Unit for Bioinformatics Data Analysis Bonn, Deutschland; 3Universitätsklinikum Bonn Institut für Medizinische Mikrobiologie, Immunologie und Parasitologie (IMMIP) Bonn, Deutschland; 4Universitätsklinikum Bonn Klinik und Poliklinik für Herzchirurgie Bonn, Deutschland; 5Institute of Molecular Medicine and Experimental Immunology, University of Bonn Bonn, Deutschland; 6Universitätsklinikum Bonn Klinik für Anästhesiologie und Operative Intensivmedizin Bonn, Deutschland

Background:

The gut microbiome is increasingly recognized as a key contributor to cardiovascular pathophysiology. However, its role in aortic valve disorders, particularly aortic stenosis (AS), is still poorly understood. This study aimed to compare gut microbiome profiles across patients with different aortic valve diseases, including aortic regurgitation (AR) as well as bicuspid (BS) and tricuspid aortic stenosis (TS).

 

Methods:

We conducted a prospective, cross-sectional analysis of 122 patients: 33 with AR, 22 with BS, and 67 with TS. Microbiota composition was assessed from anal swabs using 16S rRNA gene sequencing. Beta diversity was evaluated via UniFrac distances, and discriminant taxa were identified using linear discriminant analysis effect size (LEfSe).

 

Results:

Baseline characteristics were generally comparable between groups, although BS patients were younger and less frequently diabetic, while AR patients showed reduced renal function. Beta-diversity analysis demonstrated distinct microbial communities in AS (both BS and TS) compared with AR, independent of clinical covariates. Only minor differences were observed between BS and TS. AR samples were enriched in Bacteroides, Faecalibacterium, Lachnoclostridium, and Alistipes, whereas AS samples showed higher levels of Corynebacterium, Anaerococcus, Peptoniphilus, and Finegoldia. Co-abundance network analysis revealed a pronounced bacterial interaction network in AS characterized by strong interconnections among Bacteroides, Alistipes, Parabacteroides, and Faecalibacterium.

 

Conclusions:

Patients with AS and AR display distinct gut microbiome signatures that are not explained by clinical factors. The extensive bacterial co-abundance network identified in AS, centered around three major microbial hubs, may represent a key feature in the disease’s pathogenesis and a potential pharmaceutical target worth further investigation.