Abstract
Introduction
The estimation of the time since death, or post-mortem interval (PMI), still remains a main conundrum in forensic science. Several approaches have been so far proposed from either a qualitative or a quantitative point of view, but they still lack reliability and robustness. Recently, metabolomics has shown to be a potential tool to investigate the time-related post-mortem metabolite modifications in animal models.
Objectives
Here we propose, for the first time, the use of a 1H NMR metabolomic approach for the estimation of PMI from aqueous humour (AH) in an ovine model.
Methods
AH samples were collected at different times after death (from 118 to 1429 min). 1H NMR experiments were performed and spectral data analysed by multivariate statistical tools.
Results
A multivariate calibration model was built to estimate PMI on the basis of the metabolite content of the samples. The model was validated with an independent test set, obtaining a prediction error of 59 min for PMI < 500 min, 104 min for PMI from 500 to 1000 min, and 118 min for PMI > 1000 min. Moreover, the metabolomic approach suggested a picture of the mechanisms underlying the post-mortem biological modifications, highlighting the role played by taurine, choline, and succinate.
Conclusion
The time-related modifications of the 1H NMR AH metabolomic profile seem to be encouraging in addressing the issue of a reproducible and robust model to be employed for the estimation of the time since death.
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Data availability
The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.
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EdA, EL, MS, FdG conceived and designed research; MN, RC, LN, AC, PEN collected and pre–processed samples; EL and AN performed NMR experiments; EL and MS analysed data; EL, MS, EdA wrote and review the manuscript. All authors read and approved the manuscript.
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Locci, E., Stocchero, M., Noto, A. et al. A 1H NMR metabolomic approach for the estimation of the time since death using aqueous humour: an animal model. Metabolomics 15, 76 (2019). https://doi.org/10.1007/s11306-019-1533-2
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DOI: https://doi.org/10.1007/s11306-019-1533-2