Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences
  • Register
  • Login

Urology Journal

  • Home
  • Instant Online
    • Instant 2026
    • Instant 2023
    • Instant 2021
    • Instant 2020
  • Current
  • Archives
  • Announcements
  • Submissions
  • Author Guidelines
  • About
    • About the Journal
    • Editorial Team
    • Privacy Statement
    • Contact
Advanced Search
  1. Home
  2. Archives
  3. Vol. 23 No. 00 (2026): Instant 2026
  4. ORIGINAL PAPER(UROLOGICAL ONCOLOGY)

Vol. 23 No. 00 (2026)

January 2026

Assessing the Relationship between Gut Microbiota and Kidney Stones: A Two-Sample Mendelian Randomization Analysis

  • Suchun Wang
  • Yankang Cui
  • Bo Fang
  • Tianyi Shen
  • Song Xue
  • Jingping Ge
  • Zijie Wang
  • Shuigen Zhou

Urology Journal, Vol. 23 No. 00 (2026), 24 January 2026 , Page 8573
https://doi.org/10.22037/uj.v23i00.8573 Published: 2026-07-28

  • View Article
  • Download
  • Cite
  • References
  • Statastics
  • Share

Abstract

Background There is increasing evidence that gut microbiota is associated with the risk of kidney stones diseases (KSD), but whether a causal relationship exists remains unclear. We used the Mendelian randomization (MR) method to assess the potential causal relationship between gut microbiota and KSD risk.

Methods Genetic tool variables for the gut microbiota were identified from a genome-wide association study (GWAS) of 18340 participants. Summary statistics for KSD were derived from GWAS, including 484,598 cases and 480,873 normal controls. We used the inverse variance weighting (IVW) method as the primary analysis method.  To test the robustness of our results, we further performed the weighted-median method, MR-Egger regression, and MR pleiotropy residual sum and outlier test. Finally, reverse MR analysis was performed to evaluate the possibility of reverse causation.

Results We identified suggestive associations between four bacterial traits and the risk of KSD (odds ratio (OR): 0.82, 95% confidence interval (CI): 0.69-0.98, p= 0.032 for class. Lentisphaeria; OR:0.79, 95% CI:0.66-0.96, p=0.018 for genus. Oscillibacter; OR:0.82, 95% CI:0.68-0.98, p=0.034 for order. Victivallales; OR:1.26, 95% CI:1.03-1.53, p=0.022 for genus. Olsenella). The results of sensitivity analyses for these bacterial traits were consistent. We did not find statistically significant associations between KSD and these four bacterial traits in the reverse MR analysis.

Conclusions Our systematic analysis provides evidence supporting a potential causal relationship between four gut microbiota taxa (including class. Lentisphaeria, genus. Oscillibacter, order. Victivallales and genus. Olsenella)and KSD risk. More studies are needed to demonstrate how gut microbiota influences KSD development.

Keywords:
  • Kidney stone disease, Gut microbiota, Mendelian randomization, Single nucleotide polymorphism
  • Just Accepted/8573

How to Cite

Wang, S., Cui, Y., Fang, B., Shen, T., Xue, S., Ge, J., … Zhou, S. (2026). Assessing the Relationship between Gut Microbiota and Kidney Stones: A Two-Sample Mendelian Randomization Analysis. Urology Journal, 23(00), 8573. https://doi.org/10.22037/uj.v23i00.8573
  • ACM
  • ACS
  • APA
  • ABNT
  • Chicago
  • Harvard
  • IEEE
  • MLA
  • Turabian
  • Vancouver
  • Endnote/Zotero/Mendeley (RIS)
  • BibTeX

References

S.R. Khan, M.S. Pearle, W.G. Robertson, G. Gambaro, B.K. Canales, S. Doizi, O. Traxer, H.G. Tiselius. Kidney stones, Nat. Rev. Dis. Primers 2 (2016) 16008.

Hesse A, Brändle E, Wilbert D, Köhrmann KU, Alken P (2003) . Study on the prevalence and incidence of urolithiasis in Germany

comparing the years 1979 vs. 2000. Eur Urol 44(6):709–713.

Thongprayoon C., Krambeck A.E., Rule A.D. Determining the true burden of kidney stone disease. Nat Rev Nephrol. 2020;16(12):736–746.

J.R. Kelsen, G.D. Wu, The gut microbiota, environment and diseases of modern society, Gut Microbes 3 (4) (2012) 374–382.

1000 Genomes Project Consortium. Abecasis G. R., Auton A., Brooks L. D., DePristo M. A., Durbin R. M., et al. (2012). An integrated map of genetic variation from 1,092 human genomes. Nature 491, 56–65. 6. Noonin C, Thongboonkerd V. Beneficial roles of gastrointestinal and urinary microbiomes in kidney stone prevention via their oxalate-degrading ability and beyond. Microbiol Res. 2024 May; 282:127663.

Lee K, Lim C-Y. Mendelian randomization analysis in observational epidemiology. Journal of Lipid and Atherosclerosis. 2019;8(2):67–77.

Xu Q, Ni J-J, Han B-X, Yan S-S, et al. Causal Relationship Between Gut Microbiota and Autoimmune Diseases: A Two-Sample Mendelian Randomization Study. Front Immunol. 2021; 12:5819.

Lee YH. Causal association of gut microbiome on the risk of rheumatoid arthritis: a Mendelian randomization study. Ann Rheum Dis. 2022;81(1): e3–e3.

Xiang K, Wang P, Xu Z, et al. Causal Effects of Gut Microbiome on Systemic Lupus Erythematosus: A Two-Sample Mendelian Randomization Study. Front Immunol. 2021; 12:667097.

Liu M, Zhang Y, Wu J, Gao M, Zhu Z and Chen H. (2023) Causal relationship between kidney stones and gut microbiota contributes to the gut-kidney axis: a two-sample Mendelian randomization study. Front. Microbiol. 14:1204311.

Palmer TM, Lawlor DA, Harbord RM, et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res.2012;21(3):223–42.

Kamat MA, Blackshaw JA, Young R, et al. PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations. Bioinformatics. 2019;35(22):4851–3.

Sanna, S., van Zuydam, N. R., Mahajan, A., et al. (2019). Causal relationships among the gut microbiome, short-chain fatty acids and metabolic diseases. Nat. Genet. 51, 600–605.

Kurilshikov A, Medina-Gomez C, Bacigalupe R, et al. Large-scale association analyses identify host factors influencing human gut microbiome composition. Nat Genet. 2021;53(2):156–65.

Eijsbouts C, Zheng T, Kennedy NA, et al. Genome-wide analysis of 53,400 people with irritable bowel syndrome highlights shared genetic pathways with mood and anxiety disorders. Nat Genet. 2021;53(11):1543–52.

Bowden, J., Davey Smith, G., and Burgess, S. (2015). Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525.

Bowden, J., and Holmes, M. V. (2019). Meta-analysis and Mendelian randomization: A review. Res. synthesis Methods 10, 486–496.

Bowden, J., Davey Smith, G., Haycock, P. C., and Burgess, S. (2016). Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet. Epidemiol. 40, 304–314.

Burgess, S., Butterworth, A., and Thompson, S. G. (2013). Mendelian randomization analysis with multiple genetic variants using summarized data. Genet. Epidemiol. 37, 658–665.

Hemani, G., Tilling, K., and Davey Smith, G. (2017). Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLOS Genetics 13, 11.

Frochot, V., Daudon, M., 2016. Clinical value of crystalluria and quantitative morphoconstitutional analysis of urinary calculi. Int J. Surg. 36, 624–632.

Abid, A., Raza, A., Khan, A.R., Firasat, S., et al, 2023. Primary hyperoxaluria: comprehensive mutation screening of the disease

causing genes and spectrum of disease-associated pathogenic variants. Clin. Genet 103, 53–66.

Moore, J.P., Mauler, D.J., Narang, G.L., et al, 2022. Etiology, urine metabolic risk factors, and urine oxalate patterns in patients with significant hyperoxaluria and recurrent nephrolithiasis. Int Urol. Nephrol. 54, 2819–2825.

Siener R, Bade DJ, Hesse A, Hoppe B. Dietary hyperoxaluria is not reduced by treatment with lactic acid bacteria. J Transl Med. 2013 Dec 12; 11:306. doi: 10.1186/1479-5876-11-306. PMID: 24330782; PMCID: PMC4029792.

Stern JM, Moazami S, Qiu Y, et al. Evidence for a distinct gut microbiome in kidney stone formers compared to non-stone formers. Urolithiasis. 2016 Oct;44(5):399-407.

Colombo APV, do Souto RM, Araújo LL, et al. Anti-microbial resistance and virulence of subgingival staphylococci isolated from periodontal health and diseases. Sci Rep. 2023 Jul 18;13(1):11613.

Yuan T, Xia Y, Li B, et al. Gut microbiota in patients with kidney stones: a systematic review and meta-analysis. BMC Microbiol. 2023 May 19;23(1):143.

Lopes M, Shintaku D, de Oliveira AC, et al. P045 Prevalence of non-alcoholic fatty liver disease (NAFLD) in patients with

inflammatory bowel disease (IBD) in a Brazilian public healthcare clinic. Am J Gastroenterol. 2021 Dec 1;116(Suppl 1): S11-S12. 30. Hara M, Suzuki H, Hayashi D, et al. Gut microbiota of one-and-a-half-year-old food-allergic and healthy children. Allergol

Int. 2024 Apr 9: S1323-8930(24)00042-X.

Noonin C, Thongboonkerd V. Beneficial roles of gastrointestinal and urinary microbiomes in kidney stone prevention via their oxalate-degrading ability and beyond. Microbiol Res. 2024 May; 282:127663.

Al KF, Joris BR, Daisley BA, Chmiel JA, et al. Multi-site microbiota alteration is a hallmark of kidney stone formation. Microbiome. 2023 Nov 25;11(1):263.

  • Abstract Viewed: 0 times
  • Just Accepted/8573 Downloaded: 0 times

Download Statastics

  • Linkedin
  • Twitter
  • Facebook
  • Google Plus
  • Telegram

Information

  • For Readers
  • For Authors

Developed By

Open Journal Systems
  • Home
  • Archives
  • Submissions
  • About the Journal
  • Editorial Team
  • Contact
Powered by OJSPlus