Post-Mortem Metabolomics: A Novel Approach in Clinical Biomarker Discovery and a Potential Tool in Death Investigations

Abstract

Metabolomics can be defined as the scientific field aiming at characterizing all low-weight molecules (so-called metabolites) in a biological system. At the time of death, the level and type of metabolites present will most likely reflect the events leading up to death.In this proof of concept study, we investigated the potential of post-mortem metabolomics by identifying post-mortem biomarkers, correlated these identified biomarkers with those reported in clinical metabolomics studies, and finally validated the models predictability of unknown autopsy cases. In this post-mortem metabolomics setting, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry data from 404 post-mortem samples, including pneumonia cases and control cases, were processed using XCMS (R). Potential biomarkers were evaluated using principal component analysis and orthogonal partial least squares-discriminant analysis. Biomarkers were putatively annotated using an in-house database and the online databases METLIN and HMDB. The results showed that clear group separation was observed between pneumonia cases and control cases. The metabolites responsible for group separation belonged to a broad set of biological classes, such as amino acids, carnitines, lipids, nicotinamides, nucleotides, and steroids. Many of these metabolites have been reported as important in clinical manifestation of pneumonia. For the unknown autopsy cases, the sensitivity and specificity were 86 and 84%, respectively. This study successfully investigated the robustness and usability of post-mortem metabolomics in death investigations. The identified post-mortem biomarkers correlated well with biomarkers reported and identified through clinical research.

Postmortem Metabolomics of Insulin Intoxications and the Potential Application to Find Hypoglycemia-Related Deaths

“…Previously, only a few studies have investigated the associations between metabolome differences and postmortem interval (PMI) [2][3][4]. However, advances have been made recently in expanding the utility of untargeted metabolomics as a potential tool in death investigations, specifically in deaths related to pneumonia [5] and oxycodone intoxication [6]. In these studies, untargeted metabolomics using multivariate statistical modeling could classify specific causes of death, with high sensitivity and specificity, based on the metabolic fingerprint of postmortem blood samples [5,6].…”

A Retrospective Metabolomics Analysis of Gamma-Hydroxybutyrate in Humans: New Potential Markers and Changes in Metabolism Related to GHB Consumption

“…In general, OPLS-DA, Pearson correlation, and FDR q -values give the most valuable information when evaluating based on the number of prioritized metabolites found, that also have been reported in previous controlled studies ( Steuer et al, 2019 ). These feature selection methods have also been used in previous metabolomics studies ( Nielsen et al, 2016 ; Elmsjö et al, 2020 ; Jung et al, 2021 ), where meaningful results also were reported using these methods. Mass spectrometrory metabolome data analysis is complicated, since metabolites interact nonlinearly, and the data structures themselves are complex, especially when the study is retrospective and uncontrolled.…”

“…In contrast to MDMA, GHB is an endogenous compound, and the concept still needs further proof and verification for such more complicated cases. More recently, the principle was also applied by other groups to detect novel direct metabolites of valproate, as well as to examine whether data from post-mortem samples can be used to get insight into mechanism of death ( Mollerup et al, 2019 ; Elmsjö et al, 2020 ). Still, the method is yet in its infancy and needs further development to, e.g., tackle archived data produced over a longer period, as the shift of retention time (RT) and intensity is much larger in retrospective analysis compared to single or consecutive runs as is custom in the field.…”

Oxycodone in Forensic Toxicology : Analytical Strategies and Interpretation

“…Recently, Elmsjö et al suggested post mortem metabolomics to be a useful tool in death investigations by comparing the post mortem metabolome in pneumonia cases with control cases. Amino acids, carnitines, lipids, nicotinamides, nucleotides, and steroids were found to significantly separating the groups (105). In metabolomics, the biostatistic methods used are commonly unsupervised principal component analysis (PCA) to provide an overview of the data and display systematic variation, in combination with supervised orthogonal partial least square (OPLS) models to identify metabolites/biomarkers contributing to group separation.…”