Metabolomics

, Volume 10, Issue 3, pp 425–442 | Cite as

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

  • J. Boelaert
  • R. t’Kindt
  • E. Schepers
  • L. Jorge
  • G. Glorieux
  • N. Neirynck
  • F. Lynen
  • P. Sandra
  • R. Vanholder
  • K. Sandra
Original Article

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.

Keywords

Chronic kidney disease Metabolomics GC–MS LC–MS Q-TOF Serum 

Supplementary material

11306_2013_592_MOESM1_ESM.docx (288 kb)
Supplementary material 1 (DOCX 289 kb)

References

  1. 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.PubMedGoogle Scholar
  2. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 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.CrossRefPubMedGoogle Scholar
  4. Bellinghieri, G., Santoro, D., Calvani, M., Mallamace, A., & Savica, V. (2003). Carnitine and haemodialysis. American Journal of Kidney Diseases, 41(3), S116–S122.CrossRefPubMedGoogle Scholar
  5. 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
  6. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bultitude, F. W., & Newham, S. J. (1975). Identification of some abnormal metabolites in plasma from uremic subjects. Clinical Chemistry, 21, 1329–1334.PubMedGoogle Scholar
  8. 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.CrossRefPubMedGoogle Scholar
  9. 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.CrossRefPubMedGoogle Scholar
  10. 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.CrossRefGoogle Scholar
  11. 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.Google Scholar
  12. 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.CrossRefPubMedGoogle Scholar
  13. 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.CrossRefPubMedGoogle Scholar
  14. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  15. Fiehn, O., & Kind, T. (2007). Metabolite profiling in blood plasma. Methods in Molecular Biology, 358, 3–17.CrossRefPubMedGoogle Scholar
  16. 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.CrossRefPubMedGoogle Scholar
  17. 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
  18. Herget-Rosenthal, S., Glorieux, G., Jankowski, J., & Jankowski, V. (2009). Uremic toxins in acute kidney injury. Seminars in Dialysis, 22, 445–448.CrossRefPubMedGoogle Scholar
  19. 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.CrossRefGoogle Scholar
  20. 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.CrossRefPubMedGoogle Scholar
  21. 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.CrossRefGoogle Scholar
  22. 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.CrossRefPubMedGoogle Scholar
  23. 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.CrossRefGoogle Scholar
  24. 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.CrossRefGoogle Scholar
  25. 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.CrossRefPubMedGoogle Scholar
  26. Ju, W., Smith, S., & Kretzler, M. (2012). Genomic biomarkers for chronic kidney disease. Translational Research, 159, 290–302.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 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.CrossRefGoogle Scholar
  28. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 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.PubMedGoogle Scholar
  30. Kussmann, M., Raymond, F., & Affolter, M. (2006). OMICS-driven biomarker discovery in nutrition and health. Journal of Biotechnology, 124, 758–787.CrossRefPubMedGoogle Scholar
  31. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  32. 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.PubMedGoogle Scholar
  33. 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.CrossRefPubMedGoogle Scholar
  34. 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.Google Scholar
  35. 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.CrossRefGoogle Scholar
  36. 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
  37. Mischak, H., Massy, Z. A., & Jankowski, J. (2009). Proteomics in uremia and renal disease. Seminars in Dialysis, 22, 409–416.CrossRefPubMedGoogle Scholar
  38. 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.CrossRefPubMedGoogle Scholar
  39. 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.Google Scholar
  40. 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.CrossRefPubMedGoogle Scholar
  41. Pero, R. W. (2010). Health consequences of catabolic synthesis of hippuric acid in humans. Current Clinical Pharmacology, 5(1), 67–73.CrossRefPubMedGoogle Scholar
  42. 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
  43. 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.CrossRefPubMedGoogle Scholar
  44. 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.CrossRefGoogle Scholar
  45. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  46. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  47. 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.PubMedPubMedCentralGoogle Scholar
  48. 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.CrossRefPubMedGoogle Scholar
  49. 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.PubMedGoogle Scholar
  50. 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
  51. 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.CrossRefPubMedGoogle Scholar
  52. 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.CrossRefPubMedGoogle Scholar
  53. 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.CrossRefPubMedGoogle Scholar
  54. 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.CrossRefPubMedGoogle Scholar
  55. 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.CrossRefPubMedGoogle Scholar
  56. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  57. 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.CrossRefPubMedGoogle Scholar
  58. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  59. Toyohara, T., Akiyama, Y., Suzuki, T., et al. (2010). Metabolomic profiling of uremic solutes in CKD patients. Hypertension Research, 33, 944–952.CrossRefPubMedGoogle Scholar
  60. 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.CrossRefGoogle Scholar
  61. 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.CrossRefGoogle Scholar
  62. Vanholder, R., De Smet, R., Glorieux, G., et al. (2003a). Review on uremic toxins: Classification, concentration, and interindividual variability. Kidney International, 63, 1934–1943.CrossRefPubMedGoogle Scholar
  63. Vanholder, R., Glorieux, G., De Smet, R., & Lameire, N. (2003b). New insights in uremic toxins. Kidney International, 63, S6–S10.CrossRefGoogle Scholar
  64. 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.CrossRefPubMedPubMedCentralGoogle Scholar
  65. 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.CrossRefPubMedGoogle Scholar
  66. 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.CrossRefPubMedGoogle Scholar
  67. Weiss, R. H., & Kim, K. (2012). Metabolomics in the study of kidney diseases. Nature Reviews Nephrology, 8, 22–33.CrossRefGoogle Scholar
  68. Wu, I., & Parikh, C. R. (2008). Screening for kidney diseases: Older measures versus novel biomarkers. Clinical Journal American Society of Nephrology, 3, 1895–1901.CrossRefGoogle Scholar
  69. 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.CrossRefPubMedGoogle Scholar
  70. 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.CrossRefGoogle Scholar
  71. 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.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • J. Boelaert
    • 2
  • R. t’Kindt
    • 1
  • E. Schepers
    • 3
  • L. Jorge
    • 1
  • G. Glorieux
    • 3
  • N. Neirynck
    • 3
  • F. Lynen
    • 2
  • P. Sandra
    • 1
  • R. Vanholder
    • 3
  • K. Sandra
    • 1
  1. 1.Metablys, Research Institute for ChromatographyKortrijkBelgium
  2. 2.Separation Science Group, Department of Organic ChemistryGhent UniversityGhentBelgium
  3. 3.Nephrology SectionUniversity Hospital GhentGhentBelgium

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