Skip to main content

Advertisement

Log in

Untargeted urine metabolomics reveals a biosignature for muscle respiratory chain deficiencies

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

Abstract

Mitochondrial diseases are a heterogeneous group of disorders characterised by impaired mitochondrial oxidative phosphorylation system. Most often for mitochondrial disease, where no metabolic diagnostic biomarkers exist, a deficiency is diagnosed after analysing the respiratory chain enzymes (complexes I-IV) in affected tissues or by identifying one of an ever expanding number of DNA mutations. This presents a great challenge to identify cases to undergo the invasive diagnostic procedures required. An untargeted liquid chromatography mass spectrometry metabolomics approach was used to search for a metabolic biosignature that can distinguish respiratory chain deficient (RCD) patients from clinical controls (CC). A cohort of 37 ethnically diverse cases was used. Sample preparation, liquid chromatography time-of-flight mass spectrometry methods and data processing methods were standardised. Furthermore the developed methodology used reverse phase chromatography in conjunction with positive electrospray ionisation and hydrophilic interaction chromatography with negative electrospray ionisation. Urine samples of 37 patients representing two different experimental groups were analysed. The two experimental groups comprised of patients with confirmed RCDs and CC. After a variety of data mining steps and statistical analyses a list of 12 features were compiled with the ability to distinguish between patients with RCDs and CC. Although the features of the biosignature needs to be identified and the biosignature validated, this study demonstrates the value of untargeted metabolomics to identify a metabolic biosignature to possibly be applied in the selection criteria for RCDs.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Bernier, F. P., Boneh, A., Dennett, X., Chow, C. W., Cleary, M. A., & Thorburn, D. R. (2002). Diagnostic criteria for respiratory chain disorders in adults and children. Neurology, 59(9), 1406–1411.

    Article  CAS  PubMed  Google Scholar 

  • Christin, C., Hoefsloot, H. C., Smilde, A. K., Hoekman, B., Suits, F., Bischoff, R., et al. (2013). A critical assessment of feature selection methods for biomarker discovery in clinical proteomics. Molecular and Cellular Proteomics, 12, 263–276.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ellis, S., & Steyn, H. (2003). Practical significance (effect sizes) versus or in combination with statistical significance (p values). Management dynamics, 12, 51–53.

    Google Scholar 

  • Hrydziuszko, O., & Viant, M. R. (2012). Missing values in mass spectrometry based metabolomics: An undervalued step in the data processing pipeline. Metabolomics, 8, 161–174.

    Article  CAS  Google Scholar 

  • Munnich, A., Rötig, A., Cormier-Daire, V. & Rustin, P. (2011). Clinical presentation of respiratory chain deficiency. In The online metabolic and molecular base of inherited disease 10.

  • Pewsner, D., Battaglia, M., Minder, C., Marx, A., Bucher, H. C., & Egger, M. (2004). Ruling a diagnosis in or out with “SpPIn” and “SnNOut”: A note of caution. British Medical Journal, 329, 209–213.

    Article  PubMed Central  PubMed  Google Scholar 

  • Phoenix, C., Schaefer, A. M., Elson, J. L., Morava, E., Bugiani, M., Uziel, G., et al. (2006). A scale to monitor progression and treatment of mitochondrial disease in children. Neuromuscular Disorders, 16(12), 814–820.

    Article  CAS  PubMed  Google Scholar 

  • Reinecke, C. J., Koekemoer, G., van der Westhuizen, F. H., Louw, R., Lindeque, J. Z., Mienie, L. J., et al. (2012). Metabolomics of urinary organic acids in respiratory chain deficiencies in children. Metabolomics, 8, 264–283.

    Article  CAS  Google Scholar 

  • Rodenburg, R. T. (2011). Biochemical diagnosis of mitochondrial disorders. Journal of Inherited Metabolic Disease, 34, 283–292.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Schaefer, A. M., Phoenix, C., Elson, J. L., McFarland, R., Chinnery, P. F., & Turnbull, D. M. (2006). Mitochondrial disease in adults: a scale to monitor progression and treatment. Neurology, 66(12), 1932–1934.

    Article  CAS  PubMed  Google Scholar 

  • Schaefer, A. M., Taylor, R. W., Turnbull, D. M., & Chinnery, P. F. (2004). The epidemiology of mitochondrial disorders—past, present and future. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1659, 115–120.

    Article  CAS  Google Scholar 

  • Smuts, I., Louw, R., Du Toit, H., Klopper, B., Mienie, L. J., & van der Westhuizen, F. H. (2010). An overview of a cohort of South African patients with mitochondrial disorders. Journal of Inherited Metabolic Disease, 33(3), 95–104.

    Article  Google Scholar 

  • Smuts, I., van der Westhuizen, F. H., Louw, R., Mienie, L. J., Engelke, U. H., Wevers, R. A., et al. (2013). Disclosure of a putative biosignature for respiratory chain disorders through a metabolomics approach. Metabolomics, 9, 379–391.

    Article  CAS  Google Scholar 

  • Warrack, B. M., Hnatyshyn, S., Ott, K. H., Reily, M. D., Sanders, M., Zhang, H., et al. (2009). Normalization strategies for metabonomic analysis of urine samples. Journal of Chromatography B, 877, 547–552.

    Article  CAS  Google Scholar 

  • Wolf, N. I., & Smeitink, J. A. (2002). Mitochondrial disorders a proposal for consensus diagnostic criteria in infants and children. Neurology, 59, 1402–1405.

    Article  PubMed  Google Scholar 

  • Xia, J., Broadhurst, D. I., Wilson, M., & Wishart, D. S. (2013). Translational biomarker discovery in clinical metabolomics: an introductory tutorial. Metabolomics, 9(2), 280–299.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Xia, J., Psychogios, N., Young, N., & Wishart, D. S. (2009). MetaboAnalyst: A web server for metabolomic data analysis and interpretation. Nucleic Acids, 37, W652–W660.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

Essential funding was obtained from the North-West University, Potchefstroom Campus.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Roan Louw.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 20 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Venter, L., Lindeque, Z., Jansen van Rensburg, P. et al. Untargeted urine metabolomics reveals a biosignature for muscle respiratory chain deficiencies. Metabolomics 11, 111–121 (2015). https://doi.org/10.1007/s11306-014-0675-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-014-0675-5

Keywords

Navigation