Untargeted urine metabolomics reveals a biosignature for muscle respiratory chain deficiencies

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.

The cross-tissue metabolic response of abalone (Haliotis midae) to functional hypoxia

“…Data pre-processing in the form of zero filtering was performed ( Venter et al, 2015 ) to ensure a more complete dataset. The NMR data were normalised as a relative concentration by using the internal standard 2-acetamidophenol.…”

“…GC-TOF data were normalised relative to the internal standard 3-phenylbutyric acid ( Luier and Loots, 2016 ). Mass spectrometry total useful signal (MSTUS) was the preferred normalisation method for the data acquired by LC-QTOF, GC-MSD and LC-MS/MS analysis ( Venter et al, 2015 ). Data pre-treatment steps were completed by using the webserver MetaboAnalyst (3.0) ( Xia et al, 2015 ).…”

Clinical Metabolomics: The New Metabolic Window for Inborn Errors of Metabolism Investigations in the Post-Genomic Era

“…Given the increasing potential of metabolomics in IEM, different groups published work regarding the usefulness of untargeted-metabolomics-based approaches in IEM in disease characterization, diagnosis, and biomarker discovery. For characterization of disease biosignatures, respiratory chain deficiencies have been investigated by several research groups to track specific metabolic signatures using metabolomics [ 161 , 162 , 163 ]. Wikoff et al used MS-based untargeted metabolomics in plasma to characterize methylmalonic acidemia and propionic aciduria.…”

Integration of genomics and metabolomics for prioritization of rare disease variants: a 2018 literature review

“…The creation of processing tools and metabolomic databases has greatly facilitated the use of untargeted metabolomics in diagnosing IEMs. Both univariate and multivariate tests have been used to identify biomarkers of IEMs through untargeted metabolomics (Wikoff et al 2007 ; Dercksen et al 2013 ; Venter et al 2014 ; Najdekr et al 2015 ; Abella et al, 2016 ; Kennedy et al 2017 ; Pappan et al 2017 ). Many of these identified biomarkers have been added to newborn IEM screenings, enabling the detection of a wider variety of IEMs.…”