The Use of Gas Chromatography Coupled with High-Resolution Mass Spectrometry-Based Untargeted Metabolomics to Discover Metabolic Changes and Help in the Determination of Complex Causes of Death: A Preliminary Study

[Image: see text] The determination of cause of death (COD) is one of the most important tasks in forensic practice and is mainly based on macroscopical and microscopical morphological signatures. However, some CODs are hard to determine because the significant morphological signatures can be nonspecific, variable, subjective, or even absent in the real world. In this study, gas chromatography coupled with high-resolution mass spectrometry (GC–HRMS)-based untargeted metabolomics was employed to obtain plasma metabolic profiles of rats that died from anaphylactic shock (AS), mechanical asphyxia (MA), or sudden cardiac death (SCD). The metabolic alterations of each COD group compared to the control group were investigated using a principal component analysis, partial least-squares discriminant analysis, the Wilcoxon test, and fold change analysis. A range of differential features was screened, and 11, 8, and 7 differential metabolites were finally verified for the AS, MA, and SCD groups, respectively. We proposed some explanations that may account for these metabolic differences, including glucose metabolism, the tricarboxylic acid cycle, glycolysis, lipid metabolism, creatinine catabolism, and purine metabolism. Next, for each COD, we used its differential metabolites, which were obtained through comparisons of each COD group to the control group and represented the metabolic changes of the individual COD, to perform a receiver operating characteristic (ROC) analysis to preliminarily evaluate their ability to discriminate each COD group from the other COD groups. We found that creatinine in the AS group and malic acid and uric acid in the MA group might represent some specific metabolic changes for the relevant COD with high areas under the curve in the ROC curve analysis. Moreover, the combination panel for AS or MA also showed a good ability to discriminate it from the others. However, SCD had fewer metabolic signatures and was relatively harder to discriminate from the other CODs in our work. The preliminary study demonstrates the feasibility of GC–HRMS-based untargeted metabolomics as a promising tool to reveal metabolic changes in different death processes and to determine the complex CODs.