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.