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.
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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.
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.
Ellis, S., & Steyn, H. (2003). Practical significance (effect sizes) versus or in combination with statistical significance (p values). Management dynamics, 12, 51–53.
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.
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.
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.
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.
Rodenburg, R. T. (2011). Biochemical diagnosis of mitochondrial disorders. Journal of Inherited Metabolic Disease, 34, 283–292.
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.
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.
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.
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.
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.
Wolf, N. I., & Smeitink, J. A. (2002). Mitochondrial disorders a proposal for consensus diagnostic criteria in infants and children. Neurology, 59, 1402–1405.
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.
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.
Essential funding was obtained from the North-West University, Potchefstroom Campus.
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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
- Respiratory chain deficiency
- Urinary biomarker