The National Road Safety Action Plan concluded that “fatigue is four times more likely to contribute to impairment than drugs or alcohol”, however, unlike drugs and alcohol, there is currently no universal method of objectively testing for fatigue. This demand for a method of assessing fatigue-induced cognitive impairment as a way of determining a driver’s ‘fitness for operating a vehicle’, however, may be addressed via metabolomics. Here, this study explored the metabolic response to sleep deprivation in the urinary metabolome of 9 individuals (6 female, 3 male) who were subjected to 24 hours of continual wakefulness using Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS). With NMR, an untargeted discovery approach, to highlight new metabolic pathways that may be impaired during sleep deprivation, as well as a targeted approach using a panel of 50 metabolites quantified by a special extraction algorithm was conducted. MS was used to investigate the effects of sleep deprivation on a panel of 19 bioactive metabolites from the Tryptophan pathway (consisting of amino acids, kynurenines and neurotransmitters). Analysis of the untargeted NMR spectral data showed a strong influence of urinary dilution on the metabolite profiles. The utilization of PQN normalisation to account for dilution revealed spectral differences that were not associated with fatigue. Further integrated multivariate statistical analysis of the targeted NMR and MS metabolites highlighted three metabolites (acetone, nicotinic acid and picolinic acid) which appeared to present in higher concentrations and four metabolites (dopamine, valine, citric acid and hydroxyindole acetic acid) in lower concentrations within the fatigue cohort. Of these seven metabolites, only acetone (p = 7.82E-05), dopamine (p = 0.026544) and hydroxyindole acetic acid (p = 0.002662) were univariately significant ( = 0.05). Whilst trying to control for diet related variables, a new confounding variable was introduced – fasting. It was determined that acetone was not significant due to fatigue, rather due to the participants fasting over the fatigue period. Further univariate comparisons of the four significant metabolites also showed no statistically significant differences between males and females. The results of this study indicate that the urinary metabolome may be useful for identifying discriminatory biomarkers of fatigue that can be used in a forensic context for both males and females, however further investigation is required. Future studies should incorporate a larger number of participants, alternate normalisation methods to correct for dilution effects and minimize the confounding effects of fasting and urine dilution
