Metabolites (Dec 2022)

In Vitro Animal Model for Estimating the Time since Death with Attention to Early Postmortem Stage

  • Michal Szeremeta,
  • Paulina Samczuk,
  • Karolina Pietrowska,
  • Tomasz Kowalczyk,
  • Katarzyna Przeslaw,
  • Julia Sieminska,
  • Adam Kretowski,
  • Anna Niemcunowicz-Janica,
  • Michal Ciborowski

DOI
https://doi.org/10.3390/metabo13010026
Journal volume & issue
Vol. 13, no. 1
p. 26

Abstract

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Estimating the postmortem interval (PMI) has remained the subject of investigations in forensic medicine for many years. Every kind of death results in changes in metabolites in body tissues and fluids due to lack of oxygen, altered circulation, enzymatic reactions, cellular degradation, and cessation of anabolic production of metabolites. Metabolic changes may provide markers determining the time since death, which is challenging in current analytical and observation-based methods. The study includes metabolomics analysis of blood with the use of an animal model to determine the biochemical changes following death. LC-MS is used to fingerprint postmortem porcine blood. Metabolites, significantly changing in blood after death, are selected and identified using univariate statistics. Fifty-one significant metabolites are found to help estimate the time since death in the early postmortem stage. Hypoxanthine, lactic acid, histidine, and lysophosphatidic acids are found as the most promising markers in estimating an early postmortem stage. Selected lysophosphatidylcholines are also found as significantly increased in blood with postmortal time, but their practical utility as PMI indicators can be limited due to a relatively low increasing rate. The findings demonstrate the great potential of LC-MS-based metabolomics in determining the PMI due to sudden death and provide an experimental basis for applying this attitude in investigating various mechanisms of death. As we assume, our study is also one of the first in which the porcine animal model is used to establish PMI metabolomics biomarkers.

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