Skip to main content
SpringerLink
Log in
Book cover

Biomarkers in Kidney Disease pp 69–82Cite as

Metabolomics and Stages of Chronic Kidney Disease

  • Reference work entry
  • First Online:

Abstract

The kidneys are critical for the secretion of cytokines and hormones, the excretion of waste metabolites, and the homeostasis of electrolytes. Chronic kidney disease (CKD) is a major epidemiologic problem and a risk factor for cardiovascular events and cerebrovascular accidents. At present, renal function is generally evaluated by measuring estimated glomerular filtration rate (eGFR). However, this method has low sensitivity during the early stages of CKD. A new biomarker that can detect CKD during its early stages is eagerly awaited: mass spectrometry (MS), an effective technology for the discovery of biomarkers due to its high sensitivity to detect many compounds, seems to fit these conditions.

Metabolomics using mass spectrometry is a powerful strategy for profiling metabolites and can be used to effectively explore unknown compounds that change in abundance with respect to disease condition. Recently, many researchers have endeavored to apply metabolomics techniques to diagnose various diseases, including CKD. Some metabolites that can serve as biomarkers for CKD severity have been discovered, thanks to their efforts.

This chapter reviews metabolomics techniques and their potential to be applied to CKD diagnosis.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   449.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   549.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Abbreviations

CE-MS:

Capillary electrophoresis-mass spectrometry

CKD:

Chronic kidney disease

CysC:

Cystatin C

DMSO:

Dimethyl sulfoxide

ESRD:

End-stage renal disease

FT-ICR-MS:

Fourier transform-ion cyclotron resonance-mass spectrometry

GC-MS:

Gas chromatography-mass spectrometry

GFR:

Glomerular filtration rate

HMDB:

Human metabolome database

KEGG:

Kyoto encyclopedia of genes and genomes

LC-MS:

Liquid chromatography-mass spectrometry

MS/MS:

Tandem mass spectrometry

PLS:

Partial least squares

SFC-MS:

Supercritical fluid chromatography-mass spectrometry

TOC:

Total organic carbon

TOF-MS:

Time-of-flight-mass spectrometry

References

  • Ackroyd H. On the purine metabolism of rats. Biochem J. 1914;8:434–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Barreto FC, Barreto DV, Liabeuf S, et al. Serum indoxyl sulfate is associated with vascular disease and mortality in chronic kidney disease patients. Clin J Am Soc Nephrol. 2009;4:1551–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dahl J, Andreassen OA, Verkerk R, et al. Ongoing episode of major depressive disorder is not associated with elevated plasma levels of kynurenine pathway markers. Psychoneuroendocrinology. 2015;56:12–22.

    Article  CAS  PubMed  Google Scholar 

  • Duranton F, Lundin U, Gayrard N, et al. Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function. Clin J Am Soc Nephrol. 2014;9:37–45.

    Article  CAS  PubMed  Google Scholar 

  • Herget-Rosenthal S, Bökenkamp A, Hofmann W, et al. How to estimate GFR-serum creatinine, serum cystatin C or equations? Clin Biochem. 2007;40:153–61.

    Article  CAS  PubMed  Google Scholar 

  • Horio M, Imai E, Yasuda Y, et al. Performance of GFR equations in Japanese subjects. Clin Exp Nephrol. 2013;17:352–8.

    Article  CAS  PubMed  Google Scholar 

  • Ikeda A, Nishiumi S, Shinohara M, et al. Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer. Biomed Chromatogr. 2012;26:548–58.

    Article  CAS  PubMed  Google Scholar 

  • Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate from serum creatinine and cystatin C. N Engl J Med. 2012;367:20–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kell DB. Metabolomics and systems biology: making sense of the soup. Curr Opin Microbiol. 2004;7:296–307.

    Article  CAS  PubMed  Google Scholar 

  • Kikuchi K, Itoh Y, Tateoka R, et al. Metabolomic search for uremic toxins as indicators of the effect of an oral sorbent AST-120 by liquid chromatography/tandem mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci. 2010;878:2997–3002.

    Article  CAS  Google Scholar 

  • Kobayashi T, Matsumura Y, Ozawa T, et al. Exploration of novel predictive markers in rat plasma of the early stages of chronic renal failure. Anal Bioanal Chem. 2014a;406:1365–76.

    Article  CAS  PubMed  Google Scholar 

  • Kobayashi T, Yoshida T, Fujisawa T, et al. A metabolomics-based approach for predicting stages of chronic kidney disease. Biochem Biophys Res Commun. 2014b;445:412–6.

    Article  CAS  PubMed  Google Scholar 

  • Levey AS, Eckardt KU, Tsukamoto Y, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2005;67:2089–100.

    Article  PubMed  Google Scholar 

  • Levey AS, de Jong PE, Coresh J, et al. The definition, classification, and prognosis of chronic kidney disease: a KDIGO controversies conference report. Kidney Int. 2011;80:17–28.

    Article  PubMed  Google Scholar 

  • Maekawa K, Hirayama A, Iwata Y, et al. Global metabolomic analysis of heart tissue in a hamster model for dilated cardiomyopathy. J Mol Cell Cardiol. 2013;59:76–85.

    Article  CAS  PubMed  Google Scholar 

  • Mallet CR, Lu Z, Mazzeo JR. A study of ion suppression effects in electrospray ionization from mobile phase additives and solid-phase extracts. Rapid Commun Mass Spectrom. 2004;18:49–58.

    Article  CAS  PubMed  Google Scholar 

  • Nishiumi S, Shinohara M, Ikeda A, et al. Serum metabolomics as a novel diagnostic approach for pancreatic cancer. Metabolomics. 2010;6:518–28.

    Article  CAS  Google Scholar 

  • Nishiumi S, Kobayashi T, Ikeda A, et al. A novel serum metabolomics-based diagnostic approach for colorectal cancer. PLoS One. 2012;7:e40459.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Niwa T. Mass spectrometry in the search for uremic toxins. Mass Spectrom Rev. 1997;16:307–32.

    Article  CAS  PubMed  Google Scholar 

  • Niwa T. Recent progress in the analysis of uremic toxins by mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci. 2009;877:2600–6.

    Article  CAS  Google Scholar 

  • Niwa T. Update of uremic toxin research by mass spectrometry. Mass Spectrom Rev. 2011;30:510–21.

    Article  CAS  PubMed  Google Scholar 

  • Peralta CA, Katz R, Sarnak MJ, et al. Cystatin C identifies chronic kidney disease patients at higher risk for complications. J Am Soc Nephrol. 2011a;22:147–55.

    Article  PubMed  PubMed Central  Google Scholar 

  • Peralta CA, Shlipak MG, Judd S, et al. Detection of chronic kidney disease with creatinine, cystatin C, and urine albumin-to-creatinine ratio and association with progression to end-stage renal disease and mortality. JAMA. 2011b;305:1545–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rhee EP, Clish CB, Ghorbani A, et al. A combined epidemiologic and metabolomic approach improves CKD prediction. J Am Soc Nephrol. 2013;24:1330–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Richard JG, Shaul GM. Uremic toxins: an integrated overview of definition and classification. In: Niwa T, editor. Uremic toxins. Hoboken: Wiley; 2012. p. 3–12.

    Google Scholar 

  • Saito K, Fujigaki S, Heyes MP, et al. Mechanism of increases in L-kynurenine and quinolinic acid in renal insufficiency. Am J Physiol Ren Physiol. 2000;279:F565–72.

    CAS  Google Scholar 

  • Sato E, Kohno M, Yamamoto M, et al. Metabolomic analysis of human plasma from haemodialysis patients. Eur J Clin Invest. 2011;41:241–55.

    Article  CAS  PubMed  Google Scholar 

  • Shah VO, Townsend RR, Feldman HI, et al. Plasma metabolomic profiles in different stages of CKD. Clin J Am Soc Nephrol. 2013;8:363–70.

    Article  CAS  PubMed  Google Scholar 

  • Soga T, Sugimoto M, Honma M, et al. Serum metabolomics reveals gamma-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. J Hepatol. 2011;55:896–905.

    Article  CAS  PubMed  Google Scholar 

  • Sumner LW, Amberg A, Barrett D, et al. Proposed minimum reporting standards for chemical analysis. Metabolomics. 2007;3:211–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Taguchi K, Fukusaki E, Bamba T. Determination of niacin and its metabolites using supercritical fluid chromatography coupled to tandem mass spectrometry. Mass Spectrom (Tokyo). 2014;3:A0029.

    Article  Google Scholar 

  • Tangri N, Stevens LA, Griffith J, et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA. 2011;305:1553–9.

    Article  CAS  PubMed  Google Scholar 

  • Toyohara T, Akiyama Y, Suzuki T, et al. Metabolomic profiling of uremic solutes in CKD patients. Hypertens Res. 2010;33:944–52.

    Article  PubMed  Google Scholar 

  • Vanholder R, De Smet R, Glorieux G, et al. Review on uremic toxins: classification, concentration, and interindividual variability. Kidney Int. 2003;63:1934–43.

    Article  CAS  PubMed  Google Scholar 

  • Yeldandi AV, Yeldandi V, Kumar S, et al. Molecular evolution of the urate oxidase-encoding gene in hominoid primates: nonsense mutations. Gene. 1991;109:281–4.

    Article  CAS  PubMed  Google Scholar 

  • Yokokura Y, Isobe Y, Matsueda S, et al. Identification of 14,20-dihydroxy-docosahexaenoic acid as a novel anti-inflammatory metabolite. J Biochem. 2014;156:315–21.

    Article  CAS  PubMed  Google Scholar 

  • Yoshida M, Hatano N, Nishiumi S, et al. Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry. J Gastroenterol. 2012;47:9–20.

    Article  CAS  PubMed  Google Scholar 

  • Zhao YY. Metabolomics in chronic kidney disease. Clin Chim Acta. 2013;422:59–69.

    Article  CAS  PubMed  Google Scholar 

  • Zhao YY, Cheng XL, Wei F, et al. Serum metabolomics study of adenine-induced chronic renal failure in rats by ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Biomarkers. 2012;17:48–55.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Nutrition, Koshien University, 10-1, Momijigaoka, Takarazuka, Hyogo, Japan

    Toshihiro Kobayashi

Authors
  1. Toshihiro Kobayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Toshihiro Kobayashi .

Editor information

Editors and Affiliations

  1. DeptofBiomedlSci,FacltyofSci&Technology, University of Westminster , London, United Kingdom

    Vinood B. Patel

  2. Department of Nutrition and Dietetics,Division of Diabetes and Nutritional Sciences, Faculty of Life Science and Medicine, King’s College London, London, United Kingdom

    Victor R. Preedy

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Dordrecht

About this entry

Cite this entry

Kobayashi, T. (2016). Metabolomics and Stages of Chronic Kidney Disease. In: Patel, V., Preedy, V. (eds) Biomarkers in Kidney Disease. Biomarkers in Disease: Methods, Discoveries and Applications. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7699-9_41

Download citation

Publish with us

Policies and ethics

Search

Navigation