Association between the gut microbiota and cystitis: A two-sample mendelian randomization study combined with the GEO database

database[Title] 2025-05-13

Microb Pathog. 2025 May 8:107683. doi: 10.1016/j.micpath.2025.107683. Online ahead of print.

ABSTRACT

BACKGROUND: Disturbances within the intestinal microbiota have emerged as a significant factor contributing to systemic inflammation, thereby rendering distant anatomical sites more vulnerable to various illnesses, including inflammatory conditions in the urinary tract such as cystitis. However, the causal relationship between dysbiosis of the gut microbiota and cystitis remains unclear. We sought to elucidate the causal relationship between the intestinal microbiota and cystitis employing Mendelian randomization (MR), offering insights into novel preventive and therapeutic strategies for managing cystitis.

METHOD: Summary statistics for the Genome-Wide Association Study (GWAS) of cystitis were sourced from the R5 release dataset provided by the FinnGen consortium, which included 8,081 cystitis cases and 195,140 controls. Single Nucleotide Polymorphisms (SNPs) that showed strong associations with 196 microbial taxa (encompassing 18,340 individuals) were selected as instrumental variables. To analyse the causal relationships between cystitis and gut microbiota, we employed four MR analysis methods: random effects, inverse variance weighting, weighted medians, and MR-Egger regression. Sensitivity analyses were performed using the Cochran's Q test, funnel plots, leave-one-out analyses, and the MR-Egger intercept test. We conducted metagenomic analysis of fecal samples from 7 patients with cystitis and 7 healthy controls to validate the findings from our MR results. To further elucidate the biological mechanisms, we conducted positional mapping of the extracted SNPs associated with the significant taxa. Additionally, we curated differentially expressed genes (DEGs) from three datasets about cystitis obtained from the Gene Expression Omnibus (GEO). Finally, we intersected the DEGs with the mapped genes to identify common genes of cystitis.

RESULTS: Our analysis revealed significant associations between specific gut microbiota and cystitis. IVW results revealed that four gut microorganisms, specifically, the genus RuminococcaceaeUCG011, genus Sutterella, family Porphyromonadaceae, and family Veillonellaceae (P < 0.05), contributed to a reduction in the incidence of cystitis. Similarly, four cystitis-related bacteria, namely, the genus Marvinbryantia, the genus Odoribacter, the genus Ruminiclostridium6, and the genus Sellimonas, are thought to play a significant role in elevating the risk of cystitis (P < 0.05). The metagenomic analysis revealed significant differences in the abundance of the genera Sutterella and Odoribacter in patients with cystitis compared to healthy controls. Additionally, we mapped causal SNPs to genes and identified 62 genes. Bioinformatics analysis reveals 161 common DEGs in cystitis. Through MR and bioinformatics analysis, we identified two common genes-ICAM1 and HP-as potential targets for cystitis.

CONCLUSION: Our research identified genetic connections between eight components of gut microbiota and two genes related to cystitis. These results offer important insights for subsequent studies into the complex relationship between gut microbiota and cystitis.