Findings and methodology are presented for a project whose objective was to provide the forensic community with validated equations for estimating postmortem interval (PMI), using biomarkers from human skeletal muscle tissue.
This study expands upon the authors’ previous preliminary findings that structural glycerophospholipids (GPLs) of human skeletal muscle are accurate biomarkers of slower degenerative processes in the postmortem period (Wood and Shirley, 2013). Skeletal muscle tissue is a focus because it is one of the last of the soft tissues to break down during decomposition. Skeletal muscle is also easily sampled with minimal disturbance to the corpse. The study used mass spectrometry on biomarkers of longer term PMI that are specific to the corpse and not invading microbes. Mass spectrometry was able to extract lipids from 293 tissue samples with an ADD (accumulated degree-days) between 0 and just over 2,000 accumulated degree-hours (ADH) up to 47,800. Six bimolecular were extracted with sufficient consistency to be used in multivariate analyses. Multiplelinear regression was used to analyze the data after log transformations were performed. Stepwise variable selection was used to derive a parsimonious model that accounted for a considerable degree of variation in the dependent variables (ADD and ADH). This study succeeded in using analytical data from cadaver metabolites to provide a validated scientific standard for determining postmortem interval by using biomarkers unique to human tissues. The method uses a small amount of tissue, is less subjective than visual methods, and is robust to drastic fluctuations in temperature. 6 tables and 4 references
Date Published: September 1, 2017