The combined use of multiple omics allows to study complex interrelated biological processes in their entirety. We applied a combination of metabolomics, lipidomics and proteomics to human bones to investigate their combined potential to estimate time elapsed since death (i.e., the postmortem interval [PMI]). This ‘ForensOMICS’ approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors before their placement at the Forensic Anthropology Research Facility owned by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219-790-834-872days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic, and proteomic profiles from the pre- and post-placement bone samples. The three omics blocks were investigated independently by univariate and multivariate analyses, followed by Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers describing postmortem changes and discriminating the individuals based on their PMI. The resulting model showed that pre-placement metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement ones. Metabolites in the pre-placement samples suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules with an excellent potential for PMI estimation, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different postmortem stability, in the future we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by using proteins.

Brain damage related to perinatal asphyxia is the second cause of neuro-disability worldwide. Its incidence was estimated in 2010 as 8.5 cases per 1000 live births worldwide, with no further recent improvement even in more industrialized countries. If so, hypoxic-ischemic encephalopathy is still an issue of global health concern. It is thought that a consistent number of cases may be avoided, and its sequelae may be preventable by a prompt and efficient physical and therapeutic treatment. The lack of early, reliable, and specific biomarkers has up to now hampered a more effective use of hypothermia, which represents the only validated therapy for this condition. The urge to unravel the biological modifications underlying perinatal asphyxia and hypoxic-ischemic encephalopathy needs new diagnostic and therapeutic tools. Metabolomics for its own features is a powerful approach that may help for the identification of specific metabolic profiles related to the pathological mechanism and foreseeable outcome. The metabolomic profiles of animal and human infants exposed to perinatal asphyxia or developing hypoxic-ischemic encephalopathy have so far been investigated by means of ¹H nuclear magnetic resonance spectroscopy and mass spectrometry coupled with gas or liquid chromatography, leading to the identification of promising metabolomic signatures. In this work, an extensive review of the relevant literature was performed.

Introduction: The estimation of post-mortem interval (PMI) remains a major challenge in forensic science. Most of the proposed approaches lack the reliability required to meet the rigorous forensic standards. Objectives: We applied ¹H NMR metabolomics to estimate PMI on ovine vitreous humour comparing the results with the actual scientific gold standard, namely vitreous potassium concentrations. Methods: Vitreous humour samples were collected in a time frame ranging from 6 to 86 h after death. Experiments were performed by using ¹H NMR metabolomics and ion capillary analysis. Data were submitted to multivariate statistical data analysis. Results: A multivariate calibration model was built to estimate PMI based on 47 vitreous humour samples. The model was validated with an independent test set of 24 samples, obtaining a prediction error on the entire range of 6.9 h for PMI < 24 h, 7.4 h for PMI between 24 and 48 h, and 10.3 h for PMI > 48 h. Time-related modifications of the ¹H NMR vitreous metabolomic profile could predict PMI better than potassium up to 48 h after death, whilst a combination of the two is better than the single approach for higher PMI estimation. Conclusion: The present study, although in a proof-of-concept animal model, shows that vitreous metabolomics can be a powerful tool to predict PMI providing a more accurate estimation compared to the widely studied approach based on vitreous potassium concentrations.

Estimation of the post-mortem interval (PMI) remains a matter of concern in the forensic scenario. Traditional and novel approaches are not yet able to fully address this issue, which relies on complex biological phenomena triggered by death. For this purpose, eye compartments may be chosen for experimental studies because they are more resistant to post-mortem modifications. Vitreous humour, in particular, has been extensively investigated, with potassium concentration ([K⁺]) being the marker that is better correlated with PMI estimation. Recently, a ¹H nuclear magnetic resonance (NMR) metabolomic approach based on aqueous humour (AH) from an animal model was proposed for PMI estimation, resulting in a robust and validated regression model. Here we studied the variation in [K⁺] in the same experimental setup. [K⁺] was determined through capillary ion analysis (CIA) and a regression analysis was performed. Moreover, it was investigated whether the PMI information related to potassium could improve the metabolome predictive power in estimating the PMI. Interestingly, we found that a part of the metabolomic profile is able to explain most of the information carried by potassium, suggesting that the rise in both potassium and metabolite concentrations relies on a similar biological mechanism. In the first 24-h PMI window, the AH metabolomic profile shows greater predictive power than [K⁺] behaviour, suggesting its potential use as an additional tool for estimating the time since death.

Introduction: NMR metabolomics is increasingly used in forensics, due to the possibility of investigating both endogenous metabolic profiles and exogenous molecules that may help to describe metabolic patterns and their modifications associated to specific conditions of forensic interest. Objectives: The aim of this work was to review the recent literature and depict the information provided by NMR metabolomics. Attention has been devoted to the identification of peculiar metabolic signatures and specific ante-mortem and post-mortem profiles or biomarkers related to different conditions of forensic concern, such as the identification of biological traces, the estimation of the time since death, and the exposure to drugs of abuse. Results and Conclusion: The results of the described studies highlight how forensics can benefit from NMR metabolomics by gaining additional information that may help to shed light in several forensic issues that still deserve to be further elucidated.