Chemical profiling of fingerprints using mass spectrometry

Abstract

Fingerprints are widely used in forensic science for individualization purposes. However, not every fingermark found at a crime scene is suitable for comparison, for instance due to distortion of ridge detail, or when the reference fingerprint is not in the database. To still retrieve information from these fingermarks, several studies have been initiated into the chemical composition of fingermarks, which is believed to be influenced by several donor traits. Yet, it is still unclear what donor information can be retrieved from the composition of one's fingerprint, mainly because of limited sample sizes and the focus on analytical method development. It this paper, we analyzed the chemical composition of 1852 fingerprints, donated by 463 donors during the Dutch music festival Lowlands in 2016. In a targeted approach we compared amino acid and lipid profiles obtained from different types of fingerprints. We found a large inter-variability in both amino acid and lipid content, and significant differences in L-(iso)leucine, L-phenylalanine and palmitoleic acid levels between male and female donors. In an untargeted approach we used full-scan MS data to generate classification models to predict gender (77.9% accuracy) and smoking habit (90.4% accuracy) of fingerprint donors. In the latter, putatively, nicotine and cotinine are used as predictors.