Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Sulfur microbial diet, genetical predisposition, and the risk of chronic kidney disease: a cohort study

European Journal of Clinical Nutrition (2026)Cite this article

Subjects

Background/objectives

Our study evaluated the prospective association between the sulfur microbial diet (SMD), a diet associated with sulfur-metabolizing bacteria in stool, and the chronic kidney disease (CKD) risk, and further investigated whether genetic risk modified this association.

Methods

This study involved 98,491 UK Biobank participants who had completed at least two 24-hour dietary recall measurements. SMD scores were computed by summing the product of β-coefficients for each food group and their corresponding intake values. Incident CKD was identified using UK Biobank algorithms. The polygenic risk score (PRS) for CKD was constructed based on 263 single-nucleotide polymorphisms. Hazard ratios (HRs) with 95% confidence intervals (CIs) and population attributable fractions (PAFs) were calculated using Cox proportional hazard regression models.

Results

During a median follow-up of 9.38 years, we documented 2,032 incident CKD cases. We observed a dose-response association between the SMD score and increased CKD risk (P for non-linearity = 0.78). Participants in the highest tertile of the SMD score had a significantly higher risk of developing CKD compared to those in the lowest tertile (HR: 1.24, 95% CI: 1.11–1.39, PAF: 6.81, 95% CI: 3.29–10.34). No significant multiplicative or additive interactions between PRS and the SMD score were found (all P > 0.05). The positive associations between the SMD and the CKD risk were similar across low or high genetic risk groups.

Conclusion

Higher adherence to SMD was associated with an increased risk of CKD, regardless of genetic risk. Future studies are needed to validate our findings.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The dose-response association between the sulfur microbial diet score and the risk of chronic kidney disease.
Fig. 2: The joint association of the sulfur microbial diet score and PRS with CKD risk.

Similar content being viewed by others

Data availability

Data are available in a public, open access repository. This research has been conducted using the UK Biobank Resource under Application Number 524293. The UK Biobank data are available on application to the UK Biobank (www.ukbiobank.ac.uk/).

References

  1. Jager KJ, Kovesdy C, Langham R, Rosenberg M, Jha V, Zoccali C. A single number for advocacy and communication-worldwide more than 850 million individuals have kidney diseases. Nephrol Dialysis Transplant Off Publ Eur Dialysis Transpl Assoc Eur Ren Assoc. 2019;34:1803–5. https://doi.org/10.1093/ndt/gfz174. e-pub ahead of print 2019/10/01.

    Article  Google Scholar 

  2. Karakasis P, Patoulias D, Rizzo M, Fragakis N, Mantzoros CS. Association between remnant cholesterol and chronic kidney disease: Systematic review and meta-analysis. Diabetes Obes Metab 2025. e-pub ahead of print 2025/02/14; https://doi.org/10.1111/dom.16258.

  3. Kemp JA, Ribeiro M, Borges NA, Cardozo L, Fouque D, Mafra D. Dietary Intake and Gut Microbiome in Chronic Kidney Disease. Clin J American Soc Nephrol CJASN 2025. e-pub ahead of print 2025/03/12; https://doi.org/10.2215/cjn.0000000705

  4. Wang X, Yang S, Li S, Zhao L, Hao Y, Qin J, et al. Aberrant gut microbiota alters host metabolome and impacts renal failure in humans and rodents. Gut. 2020;69:2131–42. https://doi.org/10.1136/gutjnl-2019-319766.

    Article  PubMed Central  CAS  Google Scholar 

  5. Krukowski H, Valkenburg S, Madella AM, Garssen J, van Bergenhenegouwen J, Overbeek SA, et al. Gut microbiome studies in CKD: opportunities, pitfalls and therapeutic potential. Nat Rev Nephrol. 2023;19:87–101. https://doi.org/10.1038/s41581-022-00647-z.

    Article  PubMed  Google Scholar 

  6. Nguyen LH, Cao Y, Hur J, Mehta RS, Sikavi DR, Wang Y, et al. The sulfur microbial diet is associated with increased risk of early-onset colorectal cancer precursors. Gastroenterology. 2021;161:1423–.e1424. https://doi.org/10.1053/j.gastro.2021.07.008.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Wolfson SJ, Hitchings R, Peregrina K, Cohen Z, Khan S, Yilmaz T, et al. Bacterial hydrogen sulfide drives cryptic redox chemistry in gut microbial communities. Nat Metab. 2022;4:1260–70. https://doi.org/10.1038/s42255-022-00656-z.

    Article  PubMed Central  CAS  Google Scholar 

  8. Blachier F, Beaumont M, Kim E. Cysteine-derived hydrogen sulfide and gut health: a matter of endogenous or bacterial origin. Curr Opin Clin Nutr Metab Care. 2019;22:68–75. https://doi.org/10.1097/mco.0000000000000526.

    Article  PubMed  CAS  Google Scholar 

  9. Chen CJ, Cheng MC, Hsu CN, Tain YL. Sulfur-containing amino acids, hydrogen sulfide, and sulfur compounds on kidney health and disease. Metabolites 2023; 13. e-pub ahead of print 2023/06/27; https://doi.org/10.3390/metabo13060688.

  10. Liu X, Wan X, Zhang L, Li Y, Ao Y, Zhuang P, et al. The sulfur microbial diet and increased risk of obesity: Findings from a population-based prospective cohort study. Clin Nutr. 2023;42:764–72. https://doi.org/10.1016/j.clnu.2023.03.011.

    Article  PubMed  CAS  Google Scholar 

  11. Zhang X, Liu YM, Lei F, Huang X, Liu W, Sun T, et al. Association between questionnaire-based and accelerometer-based physical activity and the incidence of chronic kidney disease using data from UK Biobank: a prospective cohort study. EClinicalMedicine. 2023;66:102323. https://doi.org/10.1016/j.eclinm.2023.102323.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Zheng G, Zhang Y, Ou F, Chang Q, Ji C, Yang H, et al. Sugar types, genetic predictors of the gut microbiome, and the risk of chronic kidney disease: a prospective cohort study. Food Funct. 2024;15:4925–35. https://doi.org/10.1039/d4fo00724g.

    Article  PubMed  CAS  Google Scholar 

  13. Zhang H, Wang B, Chen C, Sun Y, Chen J, Tan X, et al. Sleep patterns, genetic susceptibility, and incident chronic kidney disease: a prospective study of 370 671 participants. Front Neurosci. 2022;16:725478. https://doi.org/10.3389/fnins.2022.725478.

    Article  PubMed  Google Scholar 

  14. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9. https://doi.org/10.1038/s41586-018-0579-z.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Peng M, Yuan S, Lu D, Ling Y, Huang X, Lyu J, et al. Dietary inflammatory index, genetic susceptibility and risk of incident dementia: a prospective cohort study from UK Biobank. J Neurol. 2024;271:1286–96. https://doi.org/10.1007/s00415-023-12065-7.

    Article  PubMed  Google Scholar 

  16. Bradbury KE, Young HJ, Guo W, Key TJ. Dietary assessment in UK Biobank: an evaluation of the performance of the touchscreen dietary questionnaire. J Nutr Sci. 2018;7:e6. https://doi.org/10.1017/jns.2017.66.

    Article  Google Scholar 

  17. Wang Y, Nguyen LH, Mehta RS, Song M, Huttenhower C, Chan AT. Association Between the Sulfur Microbial Diet and Risk of Colorectal Cancer. JAMA Netw Open. 2021;4:e2134308 https://doi.org/10.1001/jamanetworkopen.2021.34308.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Sikavi DR, Nguyen LH, Haruki K, Ugai T, Ma W, Wang DD, et al. The sulfur microbial diet and risk of colorectal cancer by molecular subtypes and intratumoral microbial species in adult men. Clin Transl Gastroenterol. 2021;12:e00338. https://doi.org/10.14309/ctg.0000000000000338.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Liu Z, Huang H, Ruan J, Wang Z, Xu C. The sulfur microbial diet and risk of nonalcoholic fatty liver disease: a prospective gene-diet study from the UK Biobank. Am J Clin Nutr. 2024;119:417–24. https://doi.org/10.1016/j.ajcnut.2023.11.012.

    Article  PubMed  CAS  Google Scholar 

  20. Tang R, Wang X, Li X, Ma H, Liang Z, Heianza Y, et al. Adherence to Life’s Essential 8 and incident chronic kidney disease: a prospective study of 147,988 UK Biobank participants. Am J Clin Nutr. 2023;118:804–11. https://doi.org/10.1016/j.ajcnut.2023.08.007.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Tang R, Kou M, Wang X, Ma H, Li X, Heianza Y, et al. Self-reported frequency of adding salt to food and risk of incident chronic kidney disease. JAMA Netw Open. 2023;6:e2349930 https://doi.org/10.1001/jamanetworkopen.2023.49930.

    Article  PubMed  Google Scholar 

  22. Yang H, Li Z, Zhang Y, Chang Q, Jiang J, Liu Y, et al. Associations between frailty, genetic predisposition, and chronic kidney disease risk in middle-aged and older adults: a prospective cohort study. Maturitas. 2024;187:108059. https://doi.org/10.1016/j.maturitas.2024.108059.

    Article  PubMed  CAS  Google Scholar 

  23. Lipsky AM, Greenland S. Causal directed acyclic graphs. Jama. 2022;327:1083–4. https://doi.org/10.1001/jama.2022.1816.

    Article  PubMed  Google Scholar 

  24. Mansournia MA, Altman DG. Population attributable fraction. BMJ. 2018;360:k757 https://doi.org/10.1136/bmj.k757.

    Article  PubMed  Google Scholar 

  25. Sjölander A, Vansteelandt S. Doubly robust estimation of attributable fractions in survival analysis. Stat methods Med Res. 2017;26:948–69. https://doi.org/10.1177/0962280214564003.

    Article  PubMed  Google Scholar 

  26. Chen L, Lin DY, Zeng D. Attributable fraction functions for censored event times. Biometrika. 2010;97:713–26. https://doi.org/10.1093/biomet/asq023.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Vanderweele TJ, Knol MJJEM. A Tutorial on Interaction. 2014; 3.

  28. Shams-White MM, Pannucci TE, Lerman JL, Herrick KA, Zimmer M, Meyers Mathieu K, et al. Healthy Eating Index-2020: review and update process to reflect the dietary guidelines for Americans,2020-2025. J Acad Nutr Dietetics. 2023;123:1280–8. https://doi.org/10.1016/j.jand.2023.05.015.

    Article  Google Scholar 

  29. Jiang S, Xie S, Lv D, Zhang Y, Deng J, Zeng L, et al. A reduction in the butyrate producing species Roseburia spp. and Faecalibacterium prausnitzii is associated with chronic kidney disease progression. Antonie van Leeuwenhoek. 2016;109:1389–96. https://doi.org/10.1007/s10482-016-0737-y.

    Article  PubMed  CAS  Google Scholar 

  30. Mazidi M, Shekoohi N, Covic A, Mikhailidis DP, Banach MJN. Advers impact Desulfovibrio spp beneficial role Anaerostipes spp Ren Funct: Insights a Mendel randomization Anal. 2020;12:2216.

    Google Scholar 

  31. Garcia-Martinez Y, Alexandrova E, Iebba V, Ferravante C, Spinelli M, Franci G, et al. Does gut microbiota dysbiosis impact the metabolic alterations of hydrogen sulfide and lanthionine in patients with chronic kidney disease?. BMC Microbiol. 2024;24:436. https://doi.org/10.1186/s12866-024-03590-0.

    Article  PubMed Central  CAS  Google Scholar 

  32. Zheng HJ, Guo J, Wang Q, Wang L, Wang Y, Zhang F, et al. Probiotics, prebiotics, and synbiotics for the improvement of metabolic profiles in patients with chronic kidney disease: a systematic review and meta-analysis of randomized controlled trials. Crit Rev Food Sci Nutr. 2021;61:577–98. https://doi.org/10.1080/10408398.2020.1740645.

    Article  PubMed  CAS  Google Scholar 

  33. Xie R, Yuen SK, Tsang Z, Tai WCS, Yap DYH. The relationship between probiotics and prebiotics, kidney dysfunction and mortality - Results from a longitudinal cohort study and Mendelian randomization. Clin Nutr ESPEN. 2025;65:272–81. https://doi.org/10.1016/j.clnesp.2024.11.035.

    Article  PubMed  Google Scholar 

  34. Xiao Y, Yang Y, Gao S, Zhang H, Wang J, Lin T, et al. Dietary index for gut microbiota, a novel protective factor for the prevalence of chronic kidney diseases in the adults: insight from NHANES 2007-2018. Front Nutr. 2025;12:1561235. https://doi.org/10.3389/fnut.2025.1561235.

    Article  PubMed  Google Scholar 

  35. Ren X, Xin L, Peng L, Xiao Y, Zhou Z, Luo H, et al. Association between sulfur microbial diet and the risk of esophageal cancer: a prospective cohort study in 101,752 American adults. Nutr J. 2024;23:139. https://doi.org/10.1186/s12937-024-01035-y.

    Article  PubMed Central  CAS  Google Scholar 

  36. van Westing AC, Küpers LK, Geleijnse JM. Diet and kidney function: a literature review. Curr Hypertens Rep. 2020;22:14. https://doi.org/10.1007/s11906-020-1020-1.

    Article  PubMed Central  Google Scholar 

  37. Joshi S, Kalantar-Zadeh K, Chauveau P, Carrero JJ. Risks and benefits of different dietary patterns in CKD. Am J Kidney Dis: Off J Natl Kidney Found. 2023;81:352–60. https://doi.org/10.1053/j.ajkd.2022.08.013.

    Article  Google Scholar 

  38. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505:559–63. https://doi.org/10.1038/nature12820.

    Article  PubMed  CAS  Google Scholar 

  39. Nguyen LH, Ma W, Wang DD, Cao Y, Mallick H, Gerbaba TK, et al. Association between sulfur-metabolizing bacterial communities in stool and risk of distal colorectal cancer in men. Gastroenterology. 2020;158:1313–25. https://doi.org/10.1053/j.gastro.2019.12.029.

    Article  PubMed  CAS  Google Scholar 

  40. Blachier F, Andriamihaja M, Larraufie P, Ahn E, Lan A, Kim E. Production of hydrogen sulfide by the intestinal microbiota and epithelial cells and consequences for the colonic and rectal mucosa. Am J Physiol Gastrointest Liver Physiol. 2021;320:G125–g135. https://doi.org/10.1152/ajpgi.00261.2020.

    Article  PubMed  CAS  Google Scholar 

  41. Ramezani A, Massy ZA, Meijers B, Evenepoel P, Vanholder R, Raj DSJAJoKD. Role of the gut microbiome in uremia: a potential therapeutic target. 2016; 67: 483-98.

  42. McCullough F, Cheung J, Miller LJ. A systematic review evaluating the impact of fibre supplementation on gut health and other clinical outcomes in adults with haematological malignancies during haematopoietic stem cell transplantation. Nutrients 2025; 17. e-pub ahead of print 2025/09/27; https://doi.org/10.3390/nu17182973

  43. García-Martínez Y, Borriello M, Capolongo G, Ingrosso D, Perna AF. The Gut Microbiota in Kidney Transplantation: A Target for Personalized Therapy? Biology 2023; 12. e-pub ahead of print 2023/02/26; https://doi.org/10.3390/biology12020163

  44. Genetic and developmental factors in chronic kidney disease hotspots. Seminars in nephrology. Elsevier, 2019.

  45. Galante J, Adamska L, Young A, Young H, Littlejohns TJ, Gallacher J, et al. The acceptability of repeat Internet-based hybrid diet assessment of previous 24-h dietary intake: administration of the Oxford WebQ in UK Biobank. Br J Nutr. 2016;115:681–6. https://doi.org/10.1017/s0007114515004821.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to all participants and staff in the UK Biobank Study.

Funding

This work was supported by the JieBangGuaShuai Project of Liaoning Province (grant number 2021JH1/1040050 to Yuhong Zhao), the LiaoNing Revitalization Talents Program (grant number XLYC2203168 to Yang Xia), and the General Program of Natural Science Foundation of Liaoning Province (grant numbers: 2025-MS-221 to Yang Xia). The funders had no role in the conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Author information

Author notes

  1. These authors contributed equally: Honghao Yang, Yixiao Zhang.

  2. These authors contributed equally: Yang Xia, Yuhong Zhao.

Authors and Affiliations

  1. Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China

    Honghao Yang, Zheng Ma, Liuxin Li, Gang Zheng, Qing Chang, Chao Ji, Yang Xia & Yuhong Zhao

  2. Liaoning Key Laboratory of Precision Medical Research on Major Chronic Disease, Shenyang, China

    Honghao Yang, Zheng Ma, Liuxin Li, Gang Zheng, Qing Chang, Chao Ji, Yang Xia & Yuhong Zhao

  3. Department of Urology Surgery, Shengjing Hospital of China Medical University, Shenyang, China

    Yixiao Zhang

Authors
  1. Honghao Yang
    View author publications

    Search author on:PubMed Google Scholar

  2. Yixiao Zhang
    View author publications

    Search author on:PubMed Google Scholar

  3. Zheng Ma
    View author publications

    Search author on:PubMed Google Scholar

  4. Liuxin Li
    View author publications

    Search author on:PubMed Google Scholar

  5. Gang Zheng
    View author publications

    Search author on:PubMed Google Scholar

  6. Qing Chang
    View author publications

    Search author on:PubMed Google Scholar

  7. Chao Ji
    View author publications

    Search author on:PubMed Google Scholar

  8. Yang Xia
    View author publications

    Search author on:PubMed Google Scholar

  9. Yuhong Zhao
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Honghao Yang and Yixiao Zhang contributed to study concept and design, and interpreting the data, composed the statistical dataset, performed the analyses, and wrote and revised the manuscript. Zheng Ma, Gang Zheng, Liuxin Li, Gang Zheng, Qing Chang, and Chao Ji contributed to study concept and design and interpreting the data. Yang Xia and Yuhong Zhao designed the research and had primary responsibility for the final content. All authors had full access to all the data in the study and read and approved the final manuscript.

Corresponding authors

Correspondence to Yang Xia or Yuhong Zhao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

The National Health Service National Research Ethics Service (21/NW/0157). All methods were performed in accordance with the relevant guidelines and regulations.

Informed consent

Written informed consent was obtained from each participant prior to enrollment.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, H., Zhang, Y., Ma, Z. et al. Sulfur microbial diet, genetical predisposition, and the risk of chronic kidney disease: a cohort study. Eur J Clin Nutr (2026). https://doi.org/10.1038/s41430-026-01710-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • DOI: https://doi.org/10.1038/s41430-026-01710-9

Keywords

Search

Advanced search

Quick links