Estimation of early postmortem interval in rats by GC–MS-based metabolomics. (March 2018)

• Record Type: Journal Article
• Authors: Wu, Zhigui; Lu, Xiang; Chen, Fan; Dai, Xinhua; Ye, Yi; Yan, Youyi; Liao, Linchuan
• Is Part Of: Legal medicine. Volume 31(2018)
• Page Start: 42
• Page End: 48
• Publication Date: 2018-03
• Subjects: Postmortem interval -- Metabolomics -- Metabolome -- GC–MS; Medical jurisprudence -- Periodicals; Forensic Medicine -- Periodicals; Médecine légale -- Périodiques; Medical jurisprudence; Periodicals; 614.1
• DOI: 10.1016/j.legalmed.2017.12.014
• Languages: English
• ISSNs: 1344-6223

Abstract

Highlights: Firstly establish model to estimate early PMI with whole metabolome. Compared gender differences in early PMI. Validate the method by forecasting set. This method was simpler to estimate early PMI not to select metabolites. Abstract: Accurately predicting the early postmortem interval (PMI) is of great significance in forensic practice. This study aimed to establish a novel method for estimating the early PMI by analyzing endogenous substances in the cardiac blood of male and female rats and compare different model for estimating early PMI using these data. Adult Sprague-Dawley (SD) rats (50% male) were sacrificed by suffocation. Then, cardiac blood was collected at various time intervals (0, 3, 6, 12, 24, 48, and 72 h) after death, and the collected samples were analyzed by gas chromatography-tandem mass spectrometry (GC–MS). The data were analyzed by multivariate statistical analysis. An orthogonal signal correction-partial least squares (OSC-PLS) regression model was constructed with whole endogenous metabolites to validate the PMI. The OSC-PLS regression model successfully predicted the PMI of the forecast set and no significant differences was observed between male and female rats. This is the first study to establish an OSC-PLS regression model for predicting PMI with the metabolome, which provides a new technical method and platform for estimating PMI through metabolomics.