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dc.contributor.authorVenter, Leonie
dc.contributor.authorLindeque, Zander
dc.contributor.authorJansen van Rensburg, Peet
dc.contributor.authorVan der Westhuizen, Francois
dc.contributor.authorLouw, Roan
dc.date.accessioned2016-09-05T14:09:35Z
dc.date.available2016-09-05T14:09:35Z
dc.date.issued2015
dc.identifier.citationVenter, L. et al. 2015. Untargeted urine metabolomics reveals a biosignature for muscle respiratory chain deficiencies. Metabolomics, 11(1):111-121. [https://doi.org/10.1007/s11306-014-0675-5]en_US
dc.identifier.issn1573-3882
dc.identifier.issn1573-3890 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/18541
dc.identifier.urihttps://doi.org/10.1007/s11306-014-0675-5
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs11306-014-0675-5
dc.description.abstractMitochondrial 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 RCDsen_US
dc.description.sponsorshipNorth- West University, Potchefstroom Campusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectRespiratory chain deficiencyen_US
dc.subjectmetabolomicsen_US
dc.subjecturinary biomarkeren_US
dc.subjectLC-MSen_US
dc.titleUntargeted urine metabolomics reveals a biosignature for muscle respiratory chain deficienciesen_US
dc.typeArticleen_US
dc.contributor.researchID21834350 - Venter, Leonie
dc.contributor.researchID12662275 - Lindeque, Jeremie Zander
dc.contributor.researchID10211705 - Jansen van Rensburg, Petrus Johannes
dc.contributor.researchID10213503 - Van der Westhuizen, Francois Hendrikus
dc.contributor.researchID10986707 - Louw, Roan


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