Estimation of Age of Bloodstains by Mass-Spectrometry: A Metabolomic Approach

• Published in: Analytical chemistry (Washington) Vol. 90; no. 21; pp. 12431 - 12441
• Main Authors: Seok, Ae Eun, Lee, Jiyeong, Lee, You-Rim, Lee, Yoo-Jin, Kim, Hyo-Jin, Ihm, Chunhwa, Sung, Ho Joong, Hyun, Sung Hee, Kang, Hee-Gyoo
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 06-11-2018
• Subjects: Age determination; Analytical chemistry; Blood; Blood Stains; Chromatography, High Pressure Liquid; Crime; Discriminant analysis; Ergothioneine - analysis; Ergothioneine - metabolism; Estimating techniques; Filter paper; High performance liquid chromatography; Humans; Least-Squares Analysis; Liquid chromatography; Mass Spectrometry; Mass spectroscopy; Metabolites; Metabolomics; Multivariate Analysis; Spectroscopy; Time; Tryptophan; Tryptophan - analysis; Tryptophan - metabolism; Venn diagrams
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.8b01367

Bloodstains are common evidence in crime scenes, containing significant information, including genetic information. Although efforts have been made to reliably determine the time of incident by analyzing the elapsed time of the bloodstain, there has been limited success. To identify candidate metabolites in bloodstains over time, we prepared bloodstain samples using filter paper and analyzed the metabolites by high-performance liquid chromatography–mass spectrometry (HPLC-MS)/MS over a 21-day period. Using Venn diagrams and by multivariate analysis, we selected 62 candidate molecular features. We found by partial least-squares discriminant analysis (PLS-DA) that the group can be classified with an accuracy of 75.0%, and the R 2 and Q 2 values were 0.7513 and 0.6998, respectively. Five metabolites were successfully identified based on candidate molecular features. The level of two metabolites, l-tryptophan and ergothioneine, decreased with time. The concentration of candidate metabolites that we propose reliably increased or decreased with time, thus, enabling the measurement of elapsed time of the bloodstain. This study is the first to identify markers used to analyze the elapsed time of bloodstains through metabolomics analysis.