Causal effects of gut microbiota on the risk of urinary tract stones: A bidirectional two-sample mendelian randomization study

Abstract

Background: Recent studies increasingly suggest notable changes in both the quantity and types of gut microbiota among individuals suffering from urinary tract stones. However, the causal relationship between GMB and urinary tract stone formation remains elusive, which we aim to further investigate in this research through Mendelian Randomization (MR) analysis.

Materials and methods: Single nucleotide polymorphisms (SNPs) associated with the human GMB were selected from MiBioGen International Consortium GWAS dataset. Data on urinary tract stone-related traits and associated SNPs were sourced from the IEU Open GWAS database. To investigate the causal relationships between gut microbiota and urinary tract stones, Mendelian Randomization (MR) was applied using genetic variants as instrumental variables, utilizing a bidirectional two-sample MR framework. This analysis incorporated various statistical techniques such as inverse variance weighting, weighted median analysis, MR-Egger, and the maximum likelihood method. To ensure the reliability of the findings, a range of sensitivity tests were conducted, including Cochran's Q test, the MR-Egger intercept, leave-one-out cross-validation, and examination of funnel plots.

Results: The results revealed the causal relationship between the increase in the abundance of 10 microbial taxa, including Genus-Barnesiella (IVW OR = 0.73, 95%CI 0.73-0.89, P = 2.29 × 10-3) and Genus-Flavonifractor (IVW OR = 0.69, 95%CI 0.53-0.91, P = 8.57 × 10-3), and the decreased risk of urinary tract stone formation. Conversely, the development of urinary tract stones was observed to potentially instigate alterations in the abundance of 13 microbial taxa, among which Genus-Ruminococcus torques group was notably affected (IVW OR = 1.07, 95%CI 0.64-0.98, P = 1.86 × 10-3). In this context, Genus-Clostridium sensustricto1 exhibited a bidirectional causal relationship with urinary tract stones, while the remaining significant microbial taxa demonstrated unidirectional causal effects in the two-sample MR analysis. Sensitivity analyses did not identify significant estimates of heterogeneity or pleiotropy.

Conclusion: To summarize, the results of this study suggest a likely causative link between gut microbiota and the incidence of urinary tract stones. This insight opens up potential pathways for discovering biomarkers and therapeutic targets in the management and prevention of urolithiasis. However, further in-depth research is warranted to investigate these associations.

Keywords: Causal relationship; Gut microbiota; Mendelian randomization; Urinary tract stones; Urolithiasis.

Fig. 1

An overview of the study design. SNP, single nucleotide polymorphisms.

Fig. 2

Assessment of the relationships between GMB and urolithiasis using MR. ‘A-B′ indicates the analysis with GMB as the influencing agent and urolithiasis as the resultant condition, whereas ‘B-A′ represents the reverse scenario, suggesting urolithiasis as the influencing factor. Concentric circles illustrate estimates from three different MR methodologies: inverse variance weighted, MR-Egger, and weighted median, each providing unique insights in the bidirectional analysis. Color intensity variations in the graphic signify the range of p-values, offering a visual depiction of each estimate's statistical relevance. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

This diagram presents MR findings and the outcomes of sensitivity assessments for the notable correlations between GMB and urolithiasis. The notation ‘A-B′ represents GMB as the influencing factor and urolithiasis as the resultant event, with ‘B-A′ illustrating the inverse relationship. The graphic transitions from external to internal rings, detailing estimates derived via diverse MR approaches, including inverse variance weighted, MR-Egger, and weighted median methods, complemented by sensitivity evaluations like Cochran's Q test, Egger intercept, and MR-PRESSO global test in the bidirectional MR framework. The gradations of color within the figure correlate with the p-value magnitudes, providing a visual tool to interpret the statistical impact of both the MR estimates and sensitivity analysis outcomes. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

The figure illustrates the magnitude of influence each notable gut microbiota has on the development of urolithiasis. An odds ratio less than 1 implies a protective effect against urolithiasis, whereas an odds ratio greater than 1 suggests a contributory role in the disease's pathogenesis.

Fig. 5

Scatter diagrams representing the MR investigations that link 10 distinct gut bacterial groups with the likelihood of developing urolithiasis. In these analyses, SNP stands for single nucleotide polymorphisms, and MR denotes Mendelian randomization.

Fig. 6

This figure illustrates the impact of urolithiasis on each of the significant GMB. An odds ratio value < 1 indicates a decreasing causal effect, while a value > 1 suggests the causal pathogenic incremental impact.

Fig. 7

Scatter diagrams illustrating the results of reverse MR studies exploring the relationship between urolithiasis and 13 different taxa of GMB. In these charts, SNP refers to single nucleotide polymorphisms, and MR signifies Mendelian randomization.

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