Analytical strategy for MS-based thanatochemistry to estimate postmortem interval

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 (R2) 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 R2 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 R2 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.