Urine metabolomics analysis of sleep quality in deep-underground miners: A pilot study.

BACKGROUND

In previous questionnaire surveys of miners, sleep disorders were found among underground workers. The influence of the special deep-underground environment and its potential mechanism are still unclear. Therefore, this study intends to utilize LC-MS metabolomics to study the potential differences between different environments and different sleep qualities.

METHODS

Twenty-seven miners working at 645-1,500 m deep wells were investigated in this study, and 12 local ground volunteers were recruited as the control group. The Pittsburgh Sleep Quality Index (PSQI) was used to examine and evaluate the sleep status of the subjects in the past month, and valuable basic information about the participants was collected. PSQI scores were obtained according to specific calculation rules, and the corresponding sleep grouping and subsequent analysis were carried out. Through liquid chromatography-mass spectrometry (LC-MS) non-targeted metabolomics analysis, differences in metabolism were found by bioinformatics analysis in different environments.

RESULTS

Between the deep-underground and ground (DUvsG) group, 316 differential metabolites were identified and 125 differential metabolites were identified in the good sleep quality vs. poor sleep quality (GSQvsPSQ) group. The metabolic pathways of Phenylalanine, tyrosine and tryptophan biosynthesis ( = 0.0102) and D-Glutamine and D-glutamate metabolism ( = 0.0241) were significantly enriched in DUvsG. For GSQvsPSQ group, Butanoate metabolism was statistically significant ( = 0.0276). L-Phenylalanine, L-Tyrosine and L-Glutamine were highly expressed in the deep-underground group. Acetoacetic acid was poorly expressed, and 2-hydroxyglutaric acid was highly expressed in good sleep quality.

CONCLUSIONS

The influence of the underground environment on the human body is more likely to induce specific amino acid metabolism processes, and regulate the sleep-wake state by promoting the production of excitatory neurotransmitters. The difference in sleep quality may be related to the enhancement of glycolytic metabolism, the increase in excitatory neurotransmitters and the activation of proinflammation. L-phenylalanine, L-tyrosine and L-glutamine, Acetoacetic acid and 2-hydroxyglutaric acid may be potential biomarkers correspondingly.