Abstract
In this work, untargeted lipidomics was employed to analyze the effects of coal dust exposure on serum metabolite profiles. Furthermore, the potential of differential metabolites as novel biomarkers for diagnosis was investigated by binary logistic classification model. Nineteen differential metabolites were found among the three groups. The compounds were enriched in pathways associated with linoleic acid metabolism and pyrimidine metabolism. Fifty-three differential metabolites were found in coal dust–exposed people and CWP patients, and they were mainly enriched in glycerophospholipid metabolism. Three differential metabolites were correlated with lung function values. The diagnostic model, composed of lysoPI (16:0/0:0), bilirubin, and lysoPC (24:1/0:0), showed strong discrimination ability between dust-exposed people and CWP patients. The sensitivity, specificity, and AUC values of the model were 0.869, 0.600, and 0.750, respectively. The results suggest that coal worker’s pneumoconiosis causes abnormal lipid metabolism in the body. A diagnostic model may aid current CWP diagnostic methods, and lysoPI (16:0/0:0), bilirubin, and lysoPC (24:1/0:0) can be used as potential CWP biomarkers. Further study is warranted to validate the findings in larger populations.
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This work was supported by the National Center for Occupational Safety and Health Self-management Project of China (2019009) and Key Technology Project of State Administration of Work Safety (2017005).
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Chunguang Ding, Huanqiang Wang, and Tao Li contributed to the study conception and design. Sample collection, physical examination, and lipidomics profiling were performed by Fangda Peng, Jing Dai, Qingjun Qian, Xiangfu Cao, Lifang Wang, Min Zhu, Shujin Han, Wubin Liu, Yan Li, Xiaoli Yang, and Jiaolei Wang. Fangda Peng, Teng Xue, and Xianyang Chen contributed to collated data and performed the statistical analyses. The first draft of the manuscript was written by Fangda Peng, and all the authors commented on previous versions of the manuscript. All the authors read and approved the final manuscript.
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Peng, F., Dai, J., Qian, Q. et al. Serum metabolic profiling of coal worker’s pneumoconiosis using untargeted lipidomics. Environ Sci Pollut Res 29, 85444–85453 (2022). https://doi.org/10.1007/s11356-022-21905-4
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DOI: https://doi.org/10.1007/s11356-022-21905-4