A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us?

Abstract:

INTRODUCTION: Manifestations of fatigue range from chronic fatigue up to a severe syndrome and myalgic encephalomyelitis. Fatigue grossly affects the functional status and quality of life of affected individuals, prompting the World Health Organization to recognize it as a chronic non-communicable condition.

OBJECTIVES: Here, we explore the potential of urinary metabolite information to complement clinical criteria of fatigue, providing an avenue towards an objective measure of fatigue in patients presenting with the full spectrum of fatigue levels.

METHODS: The experimental group consisted of 578 chronic fatigue female patients. The measurement design was composed of (1) existing clinical fatigue scales, (2) a hepatic detoxification challenge test, and (3) untargeted proton nuclear magnetic resonance (1H-NMR) procedure to generate metabolomics data. Data analysed via an in-house Matlab script that combines functions from a Statistics and a PLS Toolbox.

RESULTS: Multivariate analysis of the original 459 profiled 1H-NMR bins for the low (control) and high (patient) fatigue groups indicated complete separation following the detoxification experimental challenge. Important bins identified from the 1H-NMR spectra provided quantitative metabolite information on the detoxification challenge for the fatigue groups.

CONCLUSIONS: Untargeted 1H-NMR metabolomics proved its applicability as a global profiling tool to reveal the impact of toxicological interventions in chronic fatigue patients. No clear potential biomarker emerged from this study, but the quantitative profile of the phase II biotransformation products provide a practical visible effect directing to up-regulation of crucial phase II enzyme systems in the high fatigue group in response to a high xenobiotic-load.

Source: Erasmus E, Mason S, van Reenen M, Steffens FE, Vorster BC, Reinecke CJ. A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us? Metabolomics. 2019 Nov 27;15(12):158. doi: 10.1007/s11306-019-1620-4. https://www.ncbi.nlm.nih.gov/pubmed/31776682