Metabonomics Analysis of Brain Stem Tissue in Rats with Primary Brain Stem Injury Caused Death

Abstract

Objective To explore the potential biomarkers for the diagnosis of primary brain stem injury （PBSI） by using metabonomics method to observe the changes of metabolites in rats with PBSI caused death. Methods PBSI, non-brain stem brain injury and decapitation rat models were established, and metabolic maps of brain stem were obtained by LC-MS metabonomics method and annotated to the HMDB database. Partial least square-discriminant analysis （PLS-DA） and random forest methods were used to screen potential biomarkers associated with PBSI diagnosis. Results Eighty-six potential metabolic markers associated with PBSI were screened by PLS-DA. They were modeled and predicted by random forest algorithm with an accuracy rate of 83.3%. The 818 metabolic markers annotated to HMDB database were used for random forest modeling and prediction, and the accuracy rate was 88.9%. According to the importance in the identification of cause of death, the most important metabolic markers that were significantly up-regulated in PBSI group were HMDB0038126 （genipinic acid, GA）, HMDB0013272 （N-lauroylglycine）, HMDB0005199 [（R）-salsolinol] and HMDB0013645 （N,N-dimethylsphingosine）. Conclusion GA, N-lauroylglycine, （R）-salsolinol and N,N-dimethylsphingosine are expected to be important metabolite indicators in the diagnosis of PBSI caused death, thus providing clues for forensic medicine practice.

Keywords

• |forensic pathology|metabonomics|cause of death|primary brain stem injury|liquid chromato-graphy-mass spectroscopy （lc-ms）|partial least square-discriminant analysis （pls-da）|random forest algorithm|rats