Skip to main content
SpringerLink
Log in

Urine metabolomics reveals biomarkers and the underlying pathogenesis of diabetic kidney disease

  • Nephrology - Original Paper
  • Published:
International Urology and Nephrology Aims and scope Submit manuscript

Abstract

Purpose

Diabetic kidney disease (DKD) is the most common complication of type 2 diabetes mellitus (T2DM), and its pathogenesis is not yet fully understood and lacks noninvasive and effective diagnostic biomarkers. In this study, we performed urine metabolomics to identify biomarkers for DKD and to clarify the potential mechanisms associated with disease progression.

Methods

We applied a liquid chromatography–mass spectrometry-based metabolomics method combined with bioinformatics analysis to investigate the urine metabolism characteristics of 79 participants, including healthy subjects (n = 20), T2DM patients (n = 20), 39 DKD patients that included 19 DKD with microalbuminuria (DKD + micro) and 20 DKD with macroalbuminuria (DKD + macro).

Results

Seventeen metabolites were identified between T2DM and DKD that were involved in amino acid, purine, nucleotide and primarily bile acid metabolism. Ultimately, a combined model consisting of 2 metabolites (tyramine and phenylalanylproline) was established, which had optimal diagnostic performance (area under the curve (AUC) = 0.94). We also identified 19 metabolites that were co-expressed within the DKD groups and 41 metabolites specifically expressed in the DKD + macro group. Ingenuity pathway analysis revealed three interaction networks of these 60 metabolites, involving the sirtuin signaling pathway and ferroptosis signaling pathway, as well as the downregulation of organic anion transporter 1, which may be important mechanisms that mediate the progression of DKD.

Conclusions

This work reveals the metabolic alterations in T2DM and DKD, constructs a combined model to distinguish them and delivers a novel strategy for studying the underlying mechanism and treatment of DKD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, Colagiuri S, Guariguata L, Motala AA, Ogurtsova K, Shaw JE, Bright D, Williams R, Committee IDFDA (2019) Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the international diabetes federation diabetes atlas, 9(th) edition. Diabetes Res Clin Pract 157:107843. https://doi.org/10.1016/j.diabres.2019.107843

    Article  PubMed  Google Scholar 

  2. Akin S, Boluk C (2020) Prevalence of comorbidities in patients with type-2 diabetes mellitus. Prim Care Diabetes 14:431–434. https://doi.org/10.1016/j.pcd.2019.12.006

    Article  PubMed  Google Scholar 

  3. Bhensdadia NM, Hunt KJ, Lopes-Virella MF, Michael Tucker J, Mataria MR, Alge JL, Neely BA, Janech MG, Arthur JM, Veterans Affairs Diabetes Trial study g (2013) Urine haptoglobin levels predict early renal functional decline in patients with type 2 diabetes. Kidney Int 83:1136-1143. https://doi.org/10.1038/ki.2013.57

  4. Halimi JM (2012) The emerging concept of chronic kidney disease without clinical proteinuria in diabetic patients. Diabetes Metab 38:291–297. https://doi.org/10.1016/j.diabet.2012.04.001

    Article  CAS  PubMed  Google Scholar 

  5. Macisaac RJ, Jerums G (2011) Diabetic kidney disease with and without albuminuria. Curr Opin Nephrol Hypertens 20:246–257. https://doi.org/10.1097/MNH.0b013e3283456546

    Article  CAS  PubMed  Google Scholar 

  6. Krolewski AS, Niewczas MA, Skupien J, Gohda T, Smiles A, Eckfeldt JH, Doria A, Warram JH (2014) Early progressive renal decline precedes the onset of microalbuminuria and its progression to macroalbuminuria. Diabetes Care 37:226–234. https://doi.org/10.2337/dc13-0985

    Article  CAS  PubMed  Google Scholar 

  7. Krolewski AS (2015) Progressive renal decline: the new paradigm of diabetic nephropathy in type 1 diabetes. Diabetes Care 38:954–962. https://doi.org/10.2337/dc15-0184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Lin CH, Chang YC, Chuang LM (2016) Early detection of diabetic kidney disease: present limitations and future perspectives. World J Diabetes 7:290–301. https://doi.org/10.4239/wjd.v7.i14.290

    Article  PubMed  PubMed Central  Google Scholar 

  9. Chen CJ, Liao WL, Chang CT, Lin YN, Tsai FJ (2018) Identification of urinary metabolite biomarkers of type 2 diabetes nephropathy using an untargeted metabolomic approach. J Proteome Res 17:3997–4007. https://doi.org/10.1021/acs.jproteome.8b00644

    Article  CAS  PubMed  Google Scholar 

  10. Shao M, Lu H, Yang M, Liu Y, Yin P, Li G, Wang Y, Chen L, Chen Q, Zhao C, Lu Q, Wu T, Ji G (2020) Serum and urine metabolomics reveal potential biomarkers of T2DM patients with nephropathy. Ann Transl Med 8:199. https://doi.org/10.21037/atm.2020.01.42.

  11. Liang L, Rasmussen MH, Piening B, Shen X, Chen S, Rost H, Snyder JK, Tibshirani R, Skotte L, Lee NC, Contrepois K, Feenstra B, Zackriah H, Snyder M, Melbye M (2020) Metabolic dynamics and prediction of gestational age and time to delivery in pregnant women. Cell 181(1680–1692):e1615. https://doi.org/10.1016/j.cell.2020.05.002

    Article  CAS  Google Scholar 

  12. Cordero-Perez P, Sanchez-Martinez C, Garcia-Hernandez PA, Saucedo AL (2020) Metabolomics of the diabetic nephropathy: behind the fingerprint of development and progression indicators. Nefrologia (Engl Ed) 40:585–596. https://doi.org/10.1016/j.nefro.2020.07.002

    Article  PubMed  Google Scholar 

  13. Zhang S, Li X, Luo H, Fang ZZ, Ai H (2020) Role of aromatic amino acids in pathogeneses of diabetic nephropathy in Chinese patients with type 2 diabetes. J Diabetes Complications 34:107667. https://doi.org/10.1016/j.jdiacomp.2020.107667

    Article  PubMed  Google Scholar 

  14. Zhu XR, Yang FY, Lu J, Zhang HR, Sun R, Zhou JB, Yang JK (2019) Plasma metabolomic profiling of proliferative diabetic retinopathy. Nutr Metab (Lond) 16:37. https://doi.org/10.1186/s12986-019-0358-3

    Article  PubMed  Google Scholar 

  15. Zhang Q, Yin X, Wang H, Wu X, Li X, Li Y, Zhang X, Fu C, Li H, Qiu Y (2019) Fecal Metabolomics and Potential Biomarkers for Systemic Lupus Erythematosus. Front Immunol 10:976. https://doi.org/10.3389/fimmu.2019.00976

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Masereeuw R, Mutsaers HA, Toyohara T, Abe T, Jhawar S, Sweet DH, Lowenstein J (2014) The kidney and uremic toxin removal: glomerulus or tubule? Semin Nephrol 34:191–208. https://doi.org/10.1016/j.semnephrol.2014.02.010

    Article  CAS  PubMed  Google Scholar 

  17. Michael ES, Covic L, Kuliopulos A (2019) Trace amine-associated receptor 1 (TAAR1) promotes anti-diabetic signaling in insulin-secreting cells. J Biol Chem 294:4401–4411. https://doi.org/10.1074/jbc.RA118.005464

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Visentin V, Bour S, Boucher J, Prevot D, Valet P, Ordener C, Parini A, Carpene C (2005) Glucose handling in streptozotocin-induced diabetic rats is improved by tyramine but not by the amine oxidase inhibitor semicarbazide. Eur J Pharmacol 522:139–146. https://doi.org/10.1016/j.ejphar.2005.08.051

    Article  CAS  PubMed  Google Scholar 

  19. Fontaine J, Tavernier G, Morin N, Carpene C (2020) Vanadium-dependent activation of glucose transport in adipocytes by catecholamines is not mediated via adrenoceptor stimulation or monoamine oxidase activity. World J Diabetes 11:622–643. https://doi.org/10.4239/wjd.v11.i12.622

    Article  PubMed  PubMed Central  Google Scholar 

  20. Wassenberg T, Willemsen MA, Geurtz PB, Lammens M, Verrijp K, Wilmer M, Lee WT, Wevers RA, Verbeek MM (2010) Urinary dopamine in aromatic L-amino acid decarboxylase deficiency: the unsolved paradox. Mol Genet Metab 101:349–356. https://doi.org/10.1016/j.ymgme.2010.08.003

    Article  CAS  PubMed  Google Scholar 

  21. Zhang MZ, Yao B, Yang S, Yang H, Wang S, Fan X, Yin H, Fogo AB, Moeckel GW, Harris RC (2012) Intrarenal dopamine inhibits progression of diabetic nephropathy. Diabetes 61:2575–2584. https://doi.org/10.2337/db12-0046

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Spanier B, Rohm F (2018) Proton coupled oligopeptide transporter 1 (PepT1) function, regulation, and influence on the intestinal homeostasis. Compr Physiol 8:843–869. https://doi.org/10.1002/cphy.c170038

    Article  PubMed  Google Scholar 

  23. Banno A, Wang J, Okada K, Mori R, Mijiti M, Nagaoka S (2019) Identification of a novel cholesterol-lowering dipeptide, phenylalanine-proline (FP), and its down-regulation of intestinal ABCA1 in hypercholesterolemic rats and Caco-2 cells. Sci Rep 9:19416. https://doi.org/10.1038/s41598-019-56031-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Liang LM, Zhou JJ, Xu F, Liu PH, Qin L, Liu L, Liu XD (2020) Diabetes downregulates peptide transporter 1 in the rat jejunum: possible involvement of cholate-induced FXR activation. Acta Pharmacol Sin 41:1465–1475. https://doi.org/10.1038/s41401-020-0408-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Tramonti G, Xie P, Wallner EI, Danesh FR, Kanwar YS (2006) Expression and functional characteristics of tubular transporters: P-glycoprotein, PEPT1, and PEPT2 in renal mass reduction and diabetes. Am J Physiol Renal Physiol 291:F972-980. https://doi.org/10.1152/ajprenal.00110.2006

    Article  CAS  PubMed  Google Scholar 

  26. Chen H, Cao G, Chen DQ, Wang M, Vaziri ND, Zhang ZH, Mao JR, Bai X, Zhao YY (2016) Metabolomics insights into activated redox signaling and lipid metabolism dysfunction in chronic kidney disease progression. Redox Biol 10:168–178. https://doi.org/10.1016/j.redox.2016.09.014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Bell TD, Welch WJ (2009) Regulation of renal arteriolar tone by adenosine: novel role for type 2 receptors. Kidney Int 75:769–771. https://doi.org/10.1038/ki.2009.18

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Jackson EK, Gillespie DG (2013) Extracellular 2’,3’-cAMP-adenosine pathway in proximal tubular, thick ascending limb, and collecting duct epithelial cells. Am J Physiol Renal Physiol 304:F49-55. https://doi.org/10.1152/ajprenal.00571.2012

    Article  CAS  PubMed  Google Scholar 

  29. Jiang T, Wang XX, Scherzer P, Wilson P, Tallman J, Takahashi H, Li J, Iwahashi M, Sutherland E, Arend L, Levi M (2007) Farnesoid X receptor modulates renal lipid metabolism, fibrosis, and diabetic nephropathy. Diabetes 56:2485–2493. https://doi.org/10.2337/db06-1642

    Article  CAS  PubMed  Google Scholar 

  30. Wang XX, Edelstein MH, Gafter U, Qiu L, Luo Y, Dobrinskikh E, Lucia S, Adorini L, D’Agati VD, Levi J, Rosenberg A, Kopp JB, Gius DR, Saleem MA, Levi M (2016) G Protein-coupled bile acid receptor TGR5 activation inhibits kidney disease in obesity and diabetes. J Am Soc Nephrol 27:1362–1378. https://doi.org/10.1681/ASN.2014121271

    Article  CAS  PubMed  Google Scholar 

  31. Morigi M, Perico L, Benigni A (2018) Sirtuins in renal health and disease. J Am Soc Nephrol 29:1799–1809. https://doi.org/10.1681/ASN.2017111218

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liu R, Zhong Y, Li X, Chen H, Jim B, Zhou MM, Chuang PY, He JC (2014) Role of transcription factor acetylation in diabetic kidney disease. Diabetes 63:2440–2453. https://doi.org/10.2337/db13-1810

    Article  PubMed  PubMed Central  Google Scholar 

  33. Du L, Qian X, Li Y, Li XZ, He LL, Xu L, Liu YQ, Li CC, Ma P, Shu FL, Lu Q, Yin XX (2021) Sirt1 inhibits renal tubular cell epithelial-mesenchymal transition through YY1 deacetylation in diabetic nephropathy. Acta Pharmacol Sin 42:242–251. https://doi.org/10.1038/s41401-020-0450-2

    Article  CAS  PubMed  Google Scholar 

  34. Jiao X, Li Y, Zhang T, Liu M, Chi Y (2016) Role of Sirtuin3 in high glucose-induced apoptosis in renal tubular epithelial cells. Biochem Biophys Res Commun 480:387–393. https://doi.org/10.1016/j.bbrc.2016.10.060

    Article  CAS  PubMed  Google Scholar 

  35. Shi JX, Wang QJ, Li H, Huang Q (2017) SIRT4 overexpression protects against diabetic nephropathy by inhibiting podocyte apoptosis. Exp Ther Med 13:342–348. https://doi.org/10.3892/etm.2016.3938

    Article  CAS  PubMed  Google Scholar 

  36. Muraoka H, Hasegawa K, Sakamaki Y, Minakuchi H, Kawaguchi T, Yasuda I, Kanda T, Tokuyama H, Wakino S, Itoh H (2019) Role of Nampt-Sirt6 axis in renal proximal tubules in extracellular matrix deposition in diabetic nephropathy. Cell Rep 27(199–212):e195. https://doi.org/10.1016/j.celrep.2019.03.024

    Article  CAS  Google Scholar 

  37. Kim S, Kang SW, Joo J, Han SH, Shin H, Nam BY, Park J, Yoo TH, Kim G, Lee P, Park JT (2021) Characterization of ferroptosis in kidney tubular cell death under diabetic conditions. Cell Death Dis 12:160. https://doi.org/10.1038/s41419-021-03452-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Nigam SK (2018) The SLC22 transporter family: a paradigm for the impact of drug transporters on metabolic pathways, signaling, and disease. Annu Rev Pharmacol Toxicol 58:663–687. https://doi.org/10.1146/annurev-pharmtox-010617-052713

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Liu HC, Jamshidi N, Chen Y, Eraly SA, Cho SY, Bhatnagar V, Wu W, Bush KT, Abagyan R, Palsson BO, Nigam SK (2016) An organic anion transporter 1 (OAT1)-centered metabolic network. J Biol Chem 291:19474–19486. https://doi.org/10.1074/jbc.M116.745216

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the Guangdong Province Blood Depuration Clinical Engineering Technology Research Center (No: 507204531040); the 2019 Dongguan Social Science and Technology Development (key) project (No: 201950715002195); the Guangdong Province Union Training Postgraduate Demonstration base (No: 20190630); the Guangdong Science and Technology Projects (No: 2020A1313030112); the Guangzhou International Conference capital construction project (No: X20210101); the Postdoctoral Fund of the First Affiliated Hospital, Jinan University (No. 809001); the Young Innovative Talents Project of General Colleges and Universities in Guangdong Province (No. 2018KQNCX010); the GuangDong Basic and Applied Basic Research Foundation (No. 2020A1515111209); and the Key Diabetes Specialty Construction of Liwan District People’s Hospital (Grant No: 201804001). We thank Bioruqi (Guangzhou, China) for technical assistance and analysis guidance.

Author information

Author notes

  1. Maolin Luo and Zeyu Zhang contributed equally to this work.

Authors and Affiliations

  1. Department of Nephrology and Blood Purification, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510632, China

    Maolin Luo, Zeyu Zhang, Yongping Lu, Hongwei Wu, Lijing Fan, Baozhang Guan, Xiangnan Dong, Berthold Hocher & Lianghong Yin

  2. Department of Endocrinology and Metabolism, People’s Hospital of Liwan District, Guangzhou, 510380, People’s Republic of China

    Maolin Luo

  3. The First Affiliated Hospital of Southern University of Science and Technology, The Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen, CN, 518020, People’s Republic of China

    Zeyu Zhang, Yong Dai & Donge Tang

  4. Department of Traditional Chinese Medicine, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, 510632, People’s Republic of China

    Weifeng Feng

  5. Department of Nephrology, Charité -Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany

    Chen Yun & Berthold Hocher

  6. Department of Medicine Nephrology, University Medicai Centre Mannheim, Heidelberg, Germany

    Berthold Hocher

  7. The Second People’s Hospital of Lianping County, Guangdong, 517139, People’s Republic of China

    Haiping Liu

  8. Dongguan Hospital of Guangzhou University of Traditional Chinese Medicine, Guangdong, 523000, People’s Republic of China

    Qiang Li

Authors
  1. Maolin Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zeyu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yongping Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weifeng Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hongwei Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lijing Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Baozhang Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yong Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Donge Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Xiangnan Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Chen Yun
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Berthold Hocher
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Haiping Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Qiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Lianghong Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Corresponding authors

Correspondence to Haiping Liu, Qiang Li or Lianghong Yin.

Ethics declarations

Conflict of interest

All authors declare that they have no conflicts of interest.

Ethical approval

The study protocol was accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of Jinan University.

Consent to participate

All individuals had given written informed consent to be included in this study before participation.

Consent to publish

All individuals had signed informed consent for the publishing of their data.

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 283 KB)

Rights and permissions

Springer Nature or its licensor 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

Luo, M., Zhang, Z., Lu, Y. et al. Urine metabolomics reveals biomarkers and the underlying pathogenesis of diabetic kidney disease. Int Urol Nephrol 55, 1001–1013 (2023). https://doi.org/10.1007/s11255-022-03326-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11255-022-03326-x

Keywords

Search

Navigation