4.7 Article

Analytical Strategy for MS-Based Thanatochemistry to Estimate Postmortem Interval

Journal

JOURNAL OF PROTEOME RESEARCH
Volume 20, Issue 5, Pages 2607-2617

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.0c01038

Keywords

vitreous humor; postmortem interval; untargeted metabolomics; mass spectrometry; principal component regression; partial least squares regression

Funding

  1. Ministero dell'Istruzione, dell'Universitae della Ricerca (MIUR), Project PRIN 2015 (Progetti di Rilevante Interesse Nazionale) [201545245K_002]

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An analytical strategy was developed for an untargeted metabolomic study on vitreous humor using matrix-assisted laser desorption mass spectrometry, aiming to identify statistically significant parameters related to death time estimation. PCR and PLSR were used to assess PMI, with validation R-2 of about 0.95 and a prediction error of 6 hours.
An analytical strategy for a matrix-assisted laser desorption mass spectrometry-based untargeted metabolomic study on vitreous humor (VH) was developed, looking for statistically significant parameters correlated to death time estimation. Five incubation stages of VH, 0, 24, 48, 72, and 96 h, at physiological pH and controlled temperature, were adopted to monitor time-dependent changes and correlate them with the postmortem interval (PMI). Using two multivariate statistical approaches, principal component regression (PCR) and partial least squares regression (PLSR), the PMI was assessed, considering the m/z values from mass spectra and the incubation time (ISt) as predictors. An independent validation set was used to evaluate the predictive capability of the models through the coefficient of determination (R-2) and the root-mean-square error (RMSE). Different pre-treatments were applied to the raw mass spectra, and their performance in assessing PMI was evaluated. Based on the best outcomes in terms of both R-2 and RMSE, multiplicative scatter correction combined with a logarithmic transformation was chosen. The results of PCR and PLSR based on the selected pre-treatment are encouraging because validation R-2 is about 0.95 for both models. Moreover, the prediction error is 6 h for both models, when PMI is lower than 1 day. Although these results are obtained by the uncritical application of the models, they are comparable to or even better than those reported in the literature. Notwithstanding, we consider that many in situ influences, such as passive diffusion, functional loss of tissues, and advanced autolytic processes, could not get captured in vitro. However, the developed approach was optimized using VH samples and overcomes the limitations of the vast majority of methods that require validation for serum and/or urine samples.

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