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Postmortem metabolomics: Strategies to assess time-dependent postmortem changes of diazepam, nordiazepam, morphine, codeine, mirtazapine and citalopram

  • Lana Brockbals
  • , Yannick Wartmann
  • , Dylan Mantinieks
  • , Linda L. Glowacki
  • , Dimitri Gerostamoulos
  • , Thomas Kraemer
  • , Andrea E. Steuer

Research output: Contribution to journal › Article › Research › peer-review

Abstract

Postmortem redistribution (PMR) can result in artificial drug concentration changes fol-lowing death and complicate forensic case interpretation. Currently, no accurate methods for PMR prediction exist. Hence, alternative strategies were developed investigating the time-dependent postmortem behavior of diazepam, nordiazepam, morphine, codeine, mirtazapine and citalopram. For 477 authentic postmortem cases, femoral blood samples were collected at two postmortem time-points. All samples were quantified for drugs of abuse (targeted; liquid chromatography-tandem mass spectrometry LC-MS/MS) and characterized for small endogenous molecules (untargeted; gas chromatography-high resolution MS (GC-HRMS). Trends for significant time-dependent concentration decreases (diazepam (n = 137), nordiazepam (n = 126)), increases (mirtazapine (n = 55), cital-opram (n = 50)) or minimal median postmortem changes (morphine (n = 122), codeine (n = 92)) could be observed. Robust mathematical mixed effect models were created for the generalized postmortem behavior of diazepam and nordiazepam, which could be used to back-calculate drug concentrations towards a time-point closer to the estimated time of death (caution: inter-individual varia-bility). Significant correlations between time-dependent concentration changes of morphine, mirtazapine and citalopram with individual endogenous molecules could be determined; no correlation was deemed strong enough for successful a posteriori estimation on the occurrence of PMR for specific cases. The current dataset did successfully lead to a significant knowledge gain in further understanding the time-dependent postmortem behavior of the studied drugs (of abuse).

Original languageEnglish
Article number643
Number of pages16
JournalMetabolites
Volume11
Issue number9
DOIs
Publication statusPublished - Sept 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Correlation analysis
  • Mathematical modeling
  • Postmortem metabolomics
  • Prediction strategies
  • Time-dependent postmortem redistribution

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