Reduced intestinal abundance of Gordonibacter increases risk of kidney stones: a Mendelian randomization study and evidence from rat models

doi:10.12122/j.issn.1673-4254.2025.11.13

Abstract

Abstract:

Objective To investigate the causal relationship between gut microbiota and kidney stones. Methods Mendelian randomization analysis was conducted based on data from the MiBioGen consortium gut microbiota GWAS (exposure factors) and the IEU Open GWAS kidney stone dataset ukb-b-8297 (outcome variables) using the inverse variance weighted, MR-Egger regression, weighted median, weighted mode, and simple mode methods. Heterogeneity, pleiotropy, and leave-one-out sensitivity analyses were also performed. In the animal experiment, 12 male SD rats were randomized into control group with saline treatment and kidney stone model group treated with 1% ethylene glycol and 2% ammonium chloride for 28 consecutive days. Urine, blood, and intestinal samples of the rats were collected for testing the changes in renal function and intestinal barrier-related indicators, and kidney and colon pathologies were examined with histological staining and immunohistochemistry. The changes in diversity and abundance of gut microbiota were analyzed using 16S rRNA gene sequencing. Results Mendelian randomization analysis showed that decreased abundances of Lachnospiraceae NK4A136 group (OR=0.9974, 95% CI: 0.9948-0.9999, P=0.0393) and Gordonibacter (OR=0.9987, 95% CI: 0.9974-0.9999, P=0.0403) were associated with an increased risk of kidney stones without significant heterogeneity or horizontal pleiotropy, and sensitivity analyses suggested robustness of the results. The rat models of kidney stones exhibited significant renal function impairment and calcium oxalate crystal deposition, accompanied by decreased expressions of intestinal barrier-related proteins with lowered intestinal α- and β-diversity indices. Intestinal Gordonibacter abundance was significantly reduced in the rat models while the Lachnospiraceae NK4A136 group did not differ significantly between the control and model groups. Conclusion Decreased Gordonibacter abundance in gut microbiota is associated with an increased risk of kidney stones. The protective role of the Lachnospiraceae NK4A136 group against kidney stones as suggested by Mendelian randomization analysis fails to be supported by the experimental evidence and awaits further investigation.

Key words: gut microbiota, kidney stones, Mendelian randomization, Lachnospiraceae NK4A136group, Gordonibacter

Xingxu PAN, Bingqi ZHANG, Zhihua ZHANG, Qiushi CAO. Reduced intestinal abundance of Gordonibacter increases risk of kidney stones: a Mendelian randomization study and evidence from rat models[J]. Journal of Southern Medical University, 2025, 45(11): 2405-2415.

Figures/Tables 11

Fig.1 Hypotheses and flowchart of Mendelian randomization analysis.

Tab.1 Exposure factors and outcome variables in Mendelian randomization analysis

Exposure and outcome	Sample size	Number of SNPs	Data source
Gut microbiota	S=18 340	122 110	https://mibiogen.gcc.rug.nl/menu/main/home/
Kidney stones	N=462 933	9 851 867	https://gwas.mrcieu.ac.uk/

Tab.2 SNP characteristics of bacterial genera associated with kidney stones

Gut microbiota and SNPs	EA	OA	Beta	P	R²	F
Lachnospiraceae NK4A136 group
rs10952110	G	T	0.05	9.08×10^-6	0.001179	19.794033
rs11263806	A	G	-0.05	5.07×10^-6	0.001169	20.186367
rs12611395	A	G	-0.09	5.83×10^-6	0.001238	20.432599
rs160061	A	G	0.05	2.12×10^-6	0.001309	22.593643
rs28540839	A	C	0.05	9.34×10^-6	0.001258	21.121397
rs2880566	T	C	0.06	5.61×10^-6	0.001149	19.813151
rs68104925	T	C	-0.06	2.37×10^-6	0.001313	22.644336
rs954878	A	G	-0.05	1.78×10^-6	0.001321	22.779485
Gordonibacter
rs13412653	A	C	0.11	8.61×10^-6	0.005404	20.218430
rs322296	G	A	0.18	4.02×10^-6	0.006203	22.426840
rs35042269	C	A	-0.18	8.11×10^-6	0.005528	19.974041
rs4596722	A	G	0.10	9.06×10^-6	0.005276	19.737801
rs71545975	A	G	-0.15	7.04×10^-6	0.005771	20.627711
rs7294633	C	T	0.13	3.44×10^-7	0.007068	26.486697
rs768830	G	A	0.15	7.76×10^-6	0.005398	20.201590

Tab.3 Main results of Mendelian randomization analysis after excluding palindromic and confounding factors

Gut microbiota and methods	Number of SNPs	Beta	P	OR (95% CI)
Lachnospiraceae NK4A136 group
MR-Egger	8	-0.0124	0.1751	0.9877 (0.9723, 1.0034)
WME	8	-0.0017	0.3190	0.9983 (0.9950, 1.0016)
IVW	8	-0.0026	0.0393	0.9974 (0.9948, 0.9999)
SM	8	-0.0003	0.9142	0.9997 (0.9944, 1.0051)
WM	8	-0.0003	0.9148	0.9997 (0.9943, 1.0051)
Gordonibacter
MR-Egger	7	-0.0012	0.7112	0.9988 (0.9926, 1.0050)
WME	7	-0.0013	0.1220	0.9987 (0.9970, 1.0004)
IVW	7	-0.0013	0.0403	0.9987 (0.9974, 0.9999)
SM	7	-0.0014	0.2828	0.9986 (0.9963, 1.0009)
WM	7	-0.0014	0.3155	0.9986 (0.9960, 1.0011)

Fig.2 Mendelian randomization analysis scatter plot.

Tab.4 Sensitivity analysis

Exposure factor	Cochran's Q heterogeneity test			Genetic pleiotropy		MR-PRESSO
Exposure factor	Methods	Q	P	MR-Egger intercept	P	P
Lachnospiraceae NK4A136 group	IVW	6.031	0.536	5.40×10^-4	0.267	0.543
Lachnospiraceae NK4A136 group	MR-Egger	4.533	0.605	5.40×10^-4	0.267	0.543
Gordonibacter	IVW	4.719	0.580	-1.32×10^-5	0.976	0.594
Gordonibacter	MR-Egger	4.718	0.451	-1.32×10^-5	0.976	0.594

Fig.3 Leave-one-out method analysis results.

Fig.4 Changes in metabolism and renal-related indicators in the rat models of calcium oxalate kidney stone. A: Urinary oxalate. B: Serum creatinine. C: Blood urea nitrogen. D: Kidney injury molecule-1 (KIM-1). (Mean±SD, n=6). **P<0.01, ****P<0.0001 vs control group. EN: Model group.

Fig.5 Changes in renal and intestinal tissue morphology in the rat modes of calcium oxalate kidney stone. A: HE staining. B: Von Kossa staining. C: Alcian blue staining of the intestine (scale bar=100 μm). D-F: Immunohistochemical staining showing changes in Occludin, ZO-1, and the oxalate transporter SLC26A6 in the intestine. G: Quantitative analysis of mucin by Alcian blue staining. H-J: Optical density (OD) values of Occludin, ZO-1, and SLC26A6 (Mean±SD, n=3). *P<0.05 vs control group.

Fig.6 Changes in the composition of gut microbiota in the rat modes of calcium oxalate kidney stones. A: α-diversity assessed using Observed species, Shannon, and Simpson indices. B: β-diversity evaluated by PCA, PCoA, and NMDS analyses. C: Bar chart of bacterial community composition at the genus level. D: Heatmap of the differential genera identified by Wilcoxon rank-sum test. E: Heatmap analysis of the control and model groups at the genus level further illustrates that the relative abundance of bacterial taxa is positively correlated with color intensity.

Fig.7 LEfSe analysis. A: Bar chart showing the major differential taxa between the control and model groups identified by LEfSe analysis. B: Bar chart of intergroup differences in Gordonibacter (the solid line represents the mean, and the dashed line represents the median).

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