Metabolomics analysis in acute paraquat poisoning patients based on UPLC-Q-TOF-MS and machine learning approach.

Most paraquat (PQ) poisoned patients died from acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a blood metabolomics study based on ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q:TOF-MS) and efficient machine learning approach was performed on 23 PQ poisoned patients and 29 healthy subjects. The initial PQ plasma concentrations of PQ poisoned patients were >1000 ng/mL, and the blood samples were collected at before first hemoperfusion (HP), after first HP, and after last HP. The results showed that PQpoisoned patients all differed from healthy subjects, whatever they were before or after first HP or after last HP. The efficient machine learning approaches selected key metabolites from three UPLC/Q-TOF-MS data sets which had the highest classification performance in terms of classification accuracy, Matthews Correlation Coefficients, sensitivity, and specificity, respectively. The mass identification revealed that the most important metabolite was adenosine, which sustained in low level, regardless of whether PQpoisoned patients received HP treatment. In conclusion, decreased adenosine was the most important metabolite in PQpoisoned patients. The metabolic disturbance caused by PQ poisoning cannot be improved by HP treatment even the PQ was cleared from the blood.