Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning?

Introduction The (un)targeted analysis of endogenous compounds has gained interest in the field of forensic postmortem investigations. The blood metabolome is influenced by many factors, and postmortem specimens are considered particularly challenging due to unpredictable decomposition processes. Objectives This study aimed to systematically investigate the influence of the time since death on endogenous compounds and its relevance in designing postmortem metabolome studies. Methods Femoral blood samples of 427 authentic postmortem cases, were collected at two time points after death (854 samples in total; t1: admission to the institute, 1.3–290 h; t2: autopsy, 11–478 h; median ∆t = 71 h). All samples were analyzed using an untargeted metabolome approach, and peak areas were determined for 38 compounds (acylcarnitines, amino acids, phospholipids, and others). Differences between t2 and t1 were assessed by Wilcoxon signed-ranked test (p < 0.05). Moreover, all samples (n = 854) were binned into time groups (6 h, 12 h, or 24 h intervals) and compared by Kruskal–Wallis/Dunn’s multiple comparison tests (p < 0.05 each) to investigate the effect of the estimated time since death. Results Except for serine, threonine, and PC 34:1, all tested analytes revealed statistically significant changes between t1 and t2 (highest median increase 166%). Unpaired analysis of all 854 blood samples in-between groups indicated similar results. Significant differences were typically observed between blood samples collected within the first and later than 48 h after death, respectively. Conclusions To improve the consistency of comprehensive data evaluation in postmortem metabolome studies, it seems advisable to only include specimens collected within the first 2 days after death

Postmortem metabolomics: strategies to assess time-dependent postmortem changes of Diazepam, Nordiazepam, Morphine, Codeine, Mirtazapine and Citalopram

Postmortem redistribution (PMR) can result in artificial drug concentration changes following 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), citalopram (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 variability). 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)

Postmortem Metabolomics: Strategies to Assess Time-Dependent Postmortem Changes of Diazepam, Nordiazepam, Morphine, Codeine, Mirtazapine and Citalopram

Postmortem redistribution (PMR) can result in artificial drug concentration changes following 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), citalopram (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 variability). 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)

Trace Residue Identification, Characterization and Longitudinal Monitoring of the Novel Synthetic Opioid β-U10, from Discarded Drug Paraphernalia

Empirical data regarding dynamic alterations in illicit drug supply markets in response to the COVID-19 pandemic, including the potential for introduction of novel drug substances and/or increased poly-drug combinations at the ‘street’ level (i.e., directly proximal to the point of consumption), is currently lacking. Here, a high-throughput strategy employing ambient ionization-mass spectrometry is described for the trace residue identification, characterization and longitudinal monitoring of illicit drug substances found within >6,600 discarded drug paraphernalia (DDP) samples collected during a pilot study of an early warning system for illicit drug use in Melbourne, Australia from August 2020-February 2021, while significant COVID-19 lockdown conditions were imposed. The utility of this approach is demonstrated for the de novo identification and structural characterization of β-U10, a previously unreported naphthamide analogue within the ‘U-series’ of synthetic opioid drugs, including differentiation from its α-U10 isomer without need for sample preparation or chromatographic separation prior to analysis. Notably, β-U10 was observed with 23 other drug substances, most commonly in temporally distinct clusters with heroin, etizolam and diphenhydramine, and in a total of 182 different poly-drug combinations. Finally, longitudinal monitoring of the number and weekly ‘average signal intensity’ (ASI) values of identified substances, developed here as a semi-quantitative proxy indicator of changes in availability, relative purity and compositions of street level drug samples, revealed that increases in the number of identifications and ASI for β-U10 and etizolam coincided with a 50% decrease in the number of positive detections and an order of magnitude decrease in the ASI for heroin