Skip to main content
SpringerLink
Log in

State-of-the-art non-targeted metabolomics in the study of chronic kidney disease

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

Here we report a metabolomics discovery study conducted on blood serum samples of patients in different stages of chronic kidney disease (CKD). Metabolites were monitored on a quality controlled holistic platform combining reversed-phase liquid chromatography coupled to high-resolution quadrupole time-of-flight mass spectrometry in both negative and positive ionization mode and gas chromatography coupled to quadrupole mass spectrometry. A substantial portion of the serum metabolome was thereby covered. Eighty-five metabolites were shown to evolve with CKD progression of which 43 metabolites were a confirmation of earlier reported uremic retention solutes and/or uremic toxins. Thirty-one unique metabolites were revealed which were increasing significantly throughout CKD progression, by a factor surpassing the level observed for creatinine, the currently used biomarker for kidney function. Additionally, 11 unique metabolites showed a decreasing trend.

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

Similar content being viewed by others

References

  • Ahmad, S., Dasgupta, A., & Kenny, M. A. (1989). Fatty acid abnormalities in haemodialysis patients: Effect of l-carnitine administration. Kidney International Supplement, 27, S243–S246.

    CAS  PubMed  Google Scholar 

  • Aronov, P. A., Luo, F. J., Plummer, N. S., et al. (2011). Colonic contribution to uremic solutes. Journal of the American Society of Nephrology, 22, 1769–1776.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Begley, P., Francis-McIntyre, S., Dunn, W. B., et al. (2009). Development and performance of a gas chromatography–time-of-flight mass spectrometry analysis for large-scale nontargeted metabolomic studies of human serum. Analytical Chemistry, 81, 7038–7046.

    Article  CAS  PubMed  Google Scholar 

  • Bellinghieri, G., Santoro, D., Calvani, M., Mallamace, A., & Savica, V. (2003). Carnitine and haemodialysis. American Journal of Kidney Diseases, 41(3), S116–S122.

    Article  CAS  PubMed  Google Scholar 

  • Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57(1), 289–300.

    Google Scholar 

  • Benton, H. P., Wong, D. M., Trauger, S. A., & Siuzdak, G. (2008). XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization. Analytical Chemistry, 80(16), 6382–6389.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bultitude, F. W., & Newham, S. J. (1975). Identification of some abnormal metabolites in plasma from uremic subjects. Clinical Chemistry, 21, 1329–1334.

    CAS  PubMed  Google Scholar 

  • Busch, M., Gobert, A., Franke, S., et al. (2010). Vitamin B-6 metabolism in chronic kidney disease—Relation to transsulfuration, advanced glycation and cardiovascular disease. Nephron Clinical Practice, 114, C38–C46.

    Article  CAS  PubMed  Google Scholar 

  • Chen, J., Zhao, X., Fritsche, J., et al. (2008). Practical approach for the identification and isomer elucidation of biomarkers detected in a metabonomic study for the discovery of individuals at risk for diabetes by integrating the chromatographic and mass spectrometric information. Analytical Chemistry, 80(4), 1280–1289.

    Article  CAS  PubMed  Google Scholar 

  • Cohen, G., Raupachova, J., Wimmer, T., Deicher, R., & Hörl, W. H. (2008). The uraemic retention solute para-hydroxy-hippuric acid attenuates apoptosis of polymorphonuclear leukocytes from healthy subjects but not from haemodialysis patients. Nephrol. Dialysis Transplantation, 23(8), 2512–2519.

    Article  CAS  Google Scholar 

  • Dasgupta, A., Kenny, M. A., & Ahmad, S. (1990). Abnormal fatty-acid profile in chronic-haemodialysis patients—Possible deficiency of essential fatty-acids. Clinical Physiology & Biochemistry, 8, 238–243.

    CAS  Google Scholar 

  • Dudley, E., Lemière, F., Van Dongen, W., et al. (2004). Analysis of urinary nucleosides. IV. Identification of urinary purine nucleosides by liquid chromatography/electrospray mass spectrometry. Rapid Communications in Mass Spectrometry, 18, 2730–2738.

    Article  CAS  PubMed  Google Scholar 

  • Dudley, E., Tuytten, R., Bond, A., et al. (2005). Study of the mass spectrometric fragmentation of pseudouridine: comparison of fragmentation data obtained by matrix-assisted laser desorption/ionisation post-source decay, electrospray ion trap multistage mass spectrometry, and by a method utilising electrospray quadrupole time-of-flight tandem mass spectrometry and in-source fragmentation. Rapid Communications in Mass Spectrometry, 19, 3075–3085.

    Article  CAS  PubMed  Google Scholar 

  • Duranton, F., Cohen, G., De Smet, R., et al. (2012). Normal and pathologic concentrations of uremic toxins. Journal of the American Society of Nephrology, 23, 1258–1270.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fiehn, O., & Kind, T. (2007). Metabolite profiling in blood plasma. Methods in Molecular Biology, 358, 3–17.

    Article  CAS  PubMed  Google Scholar 

  • Flugel-Link, R. M., Jones, M. R., & Kopple, J. D. (1983). Red cell and plasma amino acid concentrations in renal failure. Journal of Parenteral and Enteral Nutrition, 7, 450–456.

    Article  CAS  PubMed  Google Scholar 

  • Hayashi, K., Sasamura, H., Hishiki, T., et al. (2011). Use of serum and urine metabolome analysis for the detection of metabolic changes in patients with stage 1–2 chronic kidney disease. Nephro-Urology Monthly, 3(3), 164–171.

    Google Scholar 

  • Herget-Rosenthal, S., Glorieux, G., Jankowski, J., & Jankowski, V. (2009). Uremic toxins in acute kidney injury. Seminars in Dialysis, 22, 445–448.

    Article  PubMed  Google Scholar 

  • Hill, A. W., & Mortishire-Smith, R. J. (2005). Automated assignment of high-resolution collisionally activated dissociation mass spectra using a systematic bond disconnection approach. Rapid Communications in Mass Spectrometry, 19, 3111–3118.

    Article  CAS  Google Scholar 

  • Jankowski, J., Tepel, M., Stephan, N., et al. (2001). Characterization of p-hydroxy-hippuric acid as an inhibitor of Ca2+ -ATPase in end-stage renal failure. Kidney International Supplement, 78, S84–S88.

    Article  CAS  PubMed  Google Scholar 

  • Jia, L., Chen, J., Yin, P., Lu, X., & Xu, G. (2008a). Serum metabonomics study of chronic renal failure by ultra performance liquid chromatography coupled with Q-TOF mass spectrometry. Metabolomics, 4, 183–189.

    Article  CAS  Google Scholar 

  • Jia, L., Schweikart, K., Tomaszewski, J., et al. (2008b). Toxicology and pharmacokinetics of 1-methyl-d-tryptophan: absence of toxicity due to saturating absorption. Food and Chemical Toxicology, 46, 203–211.

    Article  CAS  PubMed  Google Scholar 

  • Jia, L., Wang, C., Zhao, S., Lu, X., & Xu, G. (2007). Metabolomic identification of potential phospholipid biomarkers for chronic glomerulonephritis by using high performance liquid chromatography–mass spectrometry. Journal of Chromatography B, 860, 134–140.

    Article  CAS  Google Scholar 

  • Jiye, A., Trygg, J., Gullberg, J., et al. (2005). Extraction and GC/MS analysis of the human blood plasma metabolome. Analytical Chemistry, 77, 8086–8094.

    Article  Google Scholar 

  • Jourde-Chiche, N., Dou, L., Cerini, C., Dignat-George, F., Vanholder, R., & Brunet, P. (2009). Protein-bound toxins-update 2009. Seminars in Dialysis, 22, 334–339.

    Article  PubMed  Google Scholar 

  • Ju, W., Smith, S., & Kretzler, M. (2012). Genomic biomarkers for chronic kidney disease. Translational Research, 159, 290–302.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kikuchi, K., Itoh, Y., Tateoka, R., Ezawa, A., Murakami, K., & Niwa, T. (2010). Metabolomic analysis of uremic toxins by liquid chromatography/electrospray ionization-tandem mass spectrometry. Journal of Chromatography B, 878, 1662–1668.

    Article  CAS  Google Scholar 

  • Kind, T., Wohlgemuth, G., Lee, D. Y., et al. (2009). FiehnLib: mass spectral and retention index libraries for metabolomics based on quadrupole and time-of-flight gas chromatography/mass spectrometry. Analytical Chemistry, 81, 10038–10048.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kumps, A., Duez, P., & Mardens, Y. (2002). Metabolic, nutritional, iatrogenic, and artifactual sources of urinary organic acids: a comprehensive table. Clinical Chemistry, 48, 708–717.

    CAS  PubMed  Google Scholar 

  • Kussmann, M., Raymond, F., & Affolter, M. (2006). OMICS-driven biomarker discovery in nutrition and health. Journal of Biotechnology, 124, 758–787.

    Article  CAS  PubMed  Google Scholar 

  • Lawrence, J. R., Peter, R., Baxter, G. J., Robson, J., Graham, A. B., & Paterson, J. R. (2003). Urinary excretion of salicyluric and salicylic acids by non-vegetarians, vegetarians, and patients taking low dose aspirin. Journal of Clinical Pathology, 56(9), 651–653.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lees, H., Swann, J. R., Wilson, I. D., Nicholson, J. K., & Holmes, E. (2013). Hippurate: the natural history of a mammalian-microbial co-metabolite. Journal of Proteome Research. doi:10.1021/pr300900b.

    PubMed  Google Scholar 

  • Levey, A. S., Coresh, J., Balk, E., et al. (2003). National kidney foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Annals of Internal Medicine, 139, 137–147.

    Article  PubMed  Google Scholar 

  • Lipkin, G. W., Forbes, M. A., Cooper, E. H., & Turney, J. H. (1993). Hyaluronic acid metabolism and its clinical significance in patients treated by continuous ambulatory peritoneal dialysis. Nephrology Dialysis Transplantation, 8(4), 357–360.

    CAS  Google Scholar 

  • Meert, N., Schepers, E., Glorieux, G., et al. (2012). Novel method for simultaneous determination of p-cresylsulphate and p-cresylglucuronide: Clinical data and pathophysiological implications. Nephrology Dialysis Transplantation, 27, 2388–2396.

    Article  CAS  Google Scholar 

  • Mischak, H., Allmaier, G., Apweiler, R., et al. (2010). Recommendations for biomarker identification and qualification in clinical proteomics. Science Translational Medicicne, 2(46), 46ps42.

    Google Scholar 

  • Mischak, H., Massy, Z. A., & Jankowski, J. (2009). Proteomics in uremia and renal disease. Seminars in Dialysis, 22, 409–416.

    Article  PubMed  Google Scholar 

  • Niwa, T., Takeda, N., & Yoshizumi, H. (1998). RNA metabolism in uremic patients: Accumulation of modified ribonucleosides in uremic serum—Technical note. Kidney International, 53, 1801–1806.

    Article  CAS  PubMed  Google Scholar 

  • Palazoglu, M., & Fiehn, O. (2009). Metabolite identification in blood plasma using GC/MS and the Agilent Fiehn GC/MS metabolomics RTL library. Agilent Application Note 5990-3638EN. Palo Alto, CA: Agilent Technologies.

  • Perco, P., Pleban, C., Kainz, A., et al. (2006). Protein biomarkers associated with acute renal failure and chronic kidney disease. European Journal of Clinical Investigation, 36, 753–763.

    Article  CAS  PubMed  Google Scholar 

  • Pero, R. W. (2010). Health consequences of catabolic synthesis of hippuric acid in humans. Current Clinical Pharmacology, 5(1), 67–73.

    Article  CAS  PubMed  Google Scholar 

  • Pletinck, A., Vanholder, R., & Glorieux, G. (2012). p-Cresyl sulfate. In T. Niwa (Ed.), Uremic toxins. Hoboken: Wiley. doi:10.1002/9781118424032.ch5.

    Google Scholar 

  • Qi, S., Ouyang, X., Wang, L., Peng, W., Wen, J., & Dai, Y. (2012). A pilot metabolic profiling study in serum of patients with chronic kidney disease based on (1) H-NMR-spectroscopy. Clinical and Translational Science, 5(5), 379–385.

    Article  CAS  PubMed  Google Scholar 

  • Rechner, A. R., Spencer, J. P., Kuhnle, G., Hahn, U., & Rice-Evans, C. A. (2001). Novel biomarkers of the metabolism of caffeic acid derivatives in vivo. Free Radical Biology & Medicine, 30(11), 1213–1222.

    Article  CAS  Google Scholar 

  • Rhee, E. P., Souza, A., Farrell, L., et al. (2010). Metabolite profiling identifies markers of uremia. Journal of the American Society of Nephrology, 21, 1041–1051.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Salisbury, P. F., Dunn, M. S., & Murphy, E. A. (1957). Apparent free amino acids in deproteinized plasma of normal and uremic persons. Journal of clinical Investigation, 36, 1227–1232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sana, T. R., Roark, J. C., Li, X., Waddell, K., & Fischer, S. M. (2008). Molecular formula and METLIN personal metabolite database matching applied to the identification of compounds generated by LC/TOF–MS. Journal of Biomolecular Techniques, 19(4), 258–266.

    PubMed  PubMed Central  Google Scholar 

  • Sato, E., Kohno, M., Yamamoto, M., Fujisawa, T., Fujiwara, K., & Tanaka, N. (2011). Metabolomic analysis of human plasma from haemodialysis patients. European Journal of Clinical Investigation, 41, 241–255.

    Article  CAS  PubMed  Google Scholar 

  • Seppala, R., Renlund, M., Bernardini, I., Tietze, F., & Gahl, W. A. (1990). Renal handling of free sialic acid in normal humans and patients with Salla disease or renal disease. Laboratory Investigation, 63(2), 197–203.

    CAS  PubMed  Google Scholar 

  • Shah, V. O., Townsend, R. R., Feldman, H. I., Pappan, K. L., Kensicki, E., & Vander Jagt, D. L. (2013). Plasma metabolomic profiles in different stages of CKD. Clinical Journal of the American Society of Nephrology. doi:10.2215/CJN.05540512.

    Google Scholar 

  • Smith, C. A., O’Maille, G., Want, E. J., et al. (2005). METLIN: A metabolite mass spectral database. Therapeutic Drug Monitoring, 27(6), 747–751.

    Article  CAS  PubMed  Google Scholar 

  • Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R., & Siuzdak, G. (2006). XCMS: Processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Analytical Chemistry, 78(3), 779–787.

    Article  CAS  PubMed  Google Scholar 

  • Spagou, K., Wilson, I. D., Masson, P., et al. (2011). HILIC–UPLC–MS for exploratory urinary metabolic profiling in toxicological studies. Analytical Chemistry, 83, 382–390.

    Article  CAS  PubMed  Google Scholar 

  • Spasovski, G., Ortiz, A., Vanholder, R., & El Nahas, M. (2011). Proteomics in chronic kidney disease: The issues clinical nephrologists need an answer for. Proteomics Clinical Applications, 5, 233–240.

    Article  CAS  PubMed  Google Scholar 

  • Stanislaus, A., Guo, K., & Li, L. (2012). Development of an isotope labeling ultra-high performance liquid chromatography mass spectrometric method for quantification of acylglycines in human urine. Analytica Chimica Acta, 750, 161–172.

    Article  CAS  PubMed  Google Scholar 

  • T’Kindt, R., Scheltema, R. A., Jankevics, A., et al. (2010). Metabolomics to unveil and understand phenotypic diversity between pathogen populations. PLoS Neglected Tropical Diseases, 4(11), e904.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tao, X., Liu, Y., Wang, Y., et al. (2008). GC–MS with ethyl chloroformate derivatization for comprehensive analysis of metabolites in serum and its application to human uremia. Analytical and Bioanalytical Chemistry, 391, 2881–2889.

    Article  CAS  PubMed  Google Scholar 

  • Tautenhahn, R., Cho, K., Uritboonthai, W., Zhu, Z., Patti, G. J., & Siuzdak, G. (2012). An accelerated workflow for untargeted metabolomics using the METLIN database. Nature Biotechnology, 30(9), 826–828.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Toyohara, T., Akiyama, Y., Suzuki, T., et al. (2010). Metabolomic profiling of uremic solutes in CKD patients. Hypertension Research, 33, 944–952.

    Article  PubMed  Google Scholar 

  • Turney, J. H., Davison, A. M., Forbes, M. A., & Cooper, E. H. (1991). Hyaluronic acid in end-stage renal failure treated by haemodialysis: clinical correlates and implications. Nephrology Dialysis Transplantation, 6, 566–570.

    Article  CAS  Google Scholar 

  • Vanholder, R., Bammens, B., de Loor, H., et al. (2011). Warning: the unfortunate end of p-cresol as a uraemic toxin. Nephrology Dialysis Transplantation, 26, 1464–1467.

    Article  CAS  Google Scholar 

  • Vanholder, R., De Smet, R., Glorieux, G., et al. (2003a). Review on uremic toxins: Classification, concentration, and interindividual variability. Kidney International, 63, 1934–1943.

    Article  CAS  PubMed  Google Scholar 

  • Vanholder, R., Glorieux, G., De Smet, R., & Lameire, N. (2003b). New insights in uremic toxins. Kidney International, 63, S6–S10.

    Article  Google Scholar 

  • Vaziri, N. D. (2012). CKD impairs barrier function and alters microbial flora of the intestine: a major link to inflammation and uremic toxicity. Current Opinion in Nephrology and Hypertension, 21(6), 587–592.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Vazquez, S., Truscott, R. J., O’Hair, R. A., Weimann, A., & Sheil, M. M. (2001). A study of kynurenine fragmentation using electrospray tandem mass spectrometry. Journal of the American Society for Mass Spectrometry, 12(7), 786–794.

    Article  CAS  PubMed  Google Scholar 

  • Weimann, A., Sabroe, M., & Poulsen, H. E. (2005). Measurement of caffeine and five of the major metabolites in urine by high-performance liquid chromatography/tandem mass spectrometry. Journal of Mass Spectrometry, 40, 307–316.

    Article  CAS  PubMed  Google Scholar 

  • Weiss, R. H., & Kim, K. (2012). Metabolomics in the study of kidney diseases. Nature Reviews Nephrology, 8, 22–33.

    Article  CAS  Google Scholar 

  • Wu, I., & Parikh, C. R. (2008). Screening for kidney diseases: Older measures versus novel biomarkers. Clinical Journal American Society of Nephrology, 3, 1895–1901.

    Article  CAS  Google Scholar 

  • Zhao, Y. Y., Cheng, X. L., Wei, F., et al. (2012a). Serum metabonomics study of adenine-induced chronic renal failure in rats by ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Biomarkers, 17, 48–55.

    Article  CAS  PubMed  Google Scholar 

  • Zhao, Y. Y., Liu, J., Cheng, X. L., Bai, X., & Lin, R. C. (2012b). Urinary metabonomics study on biochemical changes in an experimental model of chronic renal failure by adenine based on UPLC Q-TOF/MS. Clinica Chimica Acta, 413, 642–649.

    Article  CAS  Google Scholar 

  • Zhu, Z. J., Schultz, A. W., Wang, J., et al. (2013). Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database. Nature Protocols, 8(3), 451–460.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors acknowledge Steve Fischer (Agilent Technologies, Santa Clara, CA), Gordon Ross (Agilent Technologies, Cheadle, UK) and Kai Chen (Ghent University, Belgium) for their valuable input. This research was funded by the Flemish Agency for Innovation by Science and Technology (IWT, Flanders). JB was supported by an IWT study grant.

Author information

Authors and Affiliations

  1. Metablys, Research Institute for Chromatography, President Kennedypark 26, Kortrijk, Belgium

    R. t’Kindt, L. Jorge, P. Sandra & K. Sandra

  2. Separation Science Group, Department of Organic Chemistry, Ghent University, Krijgslaan 281, S4-bis, Ghent, Belgium

    J. Boelaert & F. Lynen

  3. Nephrology Section, University Hospital Ghent, De Pintelaan 185, Ghent, Belgium

    E. Schepers, G. Glorieux, N. Neirynck & R. Vanholder

Authors
  1. J. Boelaert
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. t’Kindt
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Schepers
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. L. Jorge
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. G. Glorieux
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. N. Neirynck
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. F. Lynen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. P. Sandra
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. R. Vanholder
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. K. Sandra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. Sandra.

Additional information

J. Boelaert and R. t’Kindt have contributed equally to this study.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 289 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Boelaert, J., t’Kindt, R., Schepers, E. et al. State-of-the-art non-targeted metabolomics in the study of chronic kidney disease. Metabolomics 10, 425–442 (2014). https://doi.org/10.1007/s11306-013-0592-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-013-0592-z

Keywords

Search

Navigation