Investigation of metabolites for estimating blood deposition time

Trace deposition timing reflects a novel concept in forensic molecular biology involving the use of rhythmic biomarkers for estimating the time within a 24-h day/night cycle a human biological sample was left at the crime scene, which in principle allows verifying a sample donor’s alibi. Previously,...

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Bibliographic Details
Published in:International journal of legal medicine 2018-01, Vol.132 (1), p.25-32
Main Authors: Lech, Karolina, Liu, Fan, Davies, Sarah K., Ackermann, Katrin, Ang, Joo Ern, Middleton, Benita, Revell, Victoria L., Raynaud, Florence J., Hoveijn, Igor, Hut, Roelof A., Skene, Debra J., Kayser, Manfred
Format: Article
Language:English
Subjects:
Alibi
Biomarkers
Biomarkers - blood
Blood - metabolism
Categories
Crime
Deposition
Estimation
Forensic Medicine
Hormones
Humans
Hydrocortisone - blood
Hydrocortisone - genetics
Intracellular Signaling Peptides and Proteins - blood
Intracellular Signaling Peptides and Proteins - genetics
Logistic Models
Male
Mathematical models
Medical Law
Medicine & Public Health
Melatonin
Melatonin - blood
Melatonin - genetics
Metabolites
Metabolome - genetics
Metabolomics
Modelling
Molecular biology
Morning
Night
Original
Original Article
Protein Serine-Threonine Kinases - blood
Protein Serine-Threonine Kinases - genetics
Ribonucleic acid
RNA
RNA, Messenger - blood
Time Factors
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Summary:Trace deposition timing reflects a novel concept in forensic molecular biology involving the use of rhythmic biomarkers for estimating the time within a 24-h day/night cycle a human biological sample was left at the crime scene, which in principle allows verifying a sample donor’s alibi. Previously, we introduced two circadian hormones for trace deposition timing and recently demonstrated that messenger RNA (mRNA) biomarkers significantly improve time prediction accuracy. Here, we investigate the suitability of metabolites measured using a targeted metabolomics approach, for trace deposition timing. Analysis of 171 plasma metabolites collected around the clock at 2-h intervals for 36 h from 12 male participants under controlled laboratory conditions identified 56 metabolites showing statistically significant oscillations, with peak times falling into three day/night time categories: morning/noon, afternoon/evening and night/early morning. Time prediction modelling identified 10 independently contributing metabolite biomarkers, which together achieved prediction accuracies expressed as AUC of 0.81, 0.86 and 0.90 for these three time categories respectively. Combining metabolites with previously established hormone and mRNA biomarkers in time prediction modelling resulted in an improved prediction accuracy reaching AUCs of 0.85, 0.89 and 0.96 respectively. The additional impact of metabolite biomarkers, however, was rather minor as the previously established model with melatonin, cortisol and three mRNA biomarkers achieved AUC values of 0.88, 0.88 and 0.95 for the same three time categories respectively. Nevertheless, the selected metabolites could become practically useful in scenarios where RNA marker information is unavailable such as due to RNA degradation. This is the first metabolomics study investigating circulating metabolites for trace deposition timing, and more work is needed to fully establish their usefulness for this forensic purpose.
ISSN:0937-9827
1437-1596
DOI:10.1007/s00414-017-1638-y