Researchers from the Zurich Institute of Forensic Medicine and the Kümmerli Lab at DQBM used high resolution UPLC QTOF MS to profile metabolites from 100 samples spanning nine forensically relevant fluids and tissues, including semen, vaginal fluid, menstrual blood and skin. Multivariate analysis (sPLS DA and generalized local learning) revealed fluid specific clustering with high classification performance and highlighted a subset of informative features.
From 2,534 detected features, the team proposes nine promising metabolite markers - one for each body fluid or tissue - as a first candidate panel for confirmatory body fluid identification in casework. As a pilot study, the authors emphasize that larger cohorts and tests under realistic forensic conditions will be needed before routine implementation.
DOI: https://doi.org/10.1021/acs.analchem.5c04864