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Investigation of metabolites for estimating blood deposition time
- Source :
- International journal of legal medicine, 132, 25-32. SPRINGER, International Journal of Legal Medicine, International Journal of Legal Medicine, 132(1), 25-32. Springer-Verlag
- Publication Year :
- 2018
- Publisher :
- SPRINGER, 2018.
-
Abstract
- This study was supported by a UK Biotechnology and Biological Sciences Research Council (BBSRC) Grant (BB/I019405/1) to DJS, grant 727.011.001 from the Netherlands Organization for Scientific Research (NWO) Forensic Science Program to MK and by Erasmus MC University Medical Centre Rotterdam. DJS is a Royal Society Wolfson Research Merit Award holder. RAH and IH were funded by the Dutch applied research foundation (STW Perspectief Program ‘OnTime’ project 12185). 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. Publisher PDF
- Subjects :
- 0301 basic medicine
QH301 Biology
Metabolite
Physiology
melatonin
Bioinformatics
chemistry.chemical_compound
0302 clinical medicine
time factor
Metabolites
genetics
Morning
messenger RNA
16. Peace & justice
biological marker
metabolomics
RB Pathology
Original Article
metabolome
Evening
Circadian biomarkers
mRNA
NDAS
forensic medicine
QH426 Genetics
Blood deposition time
Biology
MKNK2 protein
Pathology and Forensic Medicine
QH301
03 medical and health sciences
Metabolomics
male
blood
protein serine threonine kinase
Metabolome
signal peptide
Circadian rhythm
hydrocortisone
human
QH426
MKNK2 protein, human
SDG 16 - Peace, Justice and Strong Institutions
statistical model
Trace time estimation
030104 developmental biology
chemistry
RB
Deposition (chemistry)
metabolism
030217 neurology & neurosurgery
Targeted metabolomics
Subjects
Details
- Language :
- English
- ISSN :
- 09379827
- Volume :
- 132
- Database :
- OpenAIRE
- Journal :
- International journal of legal medicine
- Accession number :
- edsair.doi.dedup.....d0a476934e0d555f9eceb5f14039ade7