Evidence map›Paper›PMID 28780758›Full record

ArticleInternational journal of legal medicine2018

Investigation of metabolites for estimating blood deposition time.

Karolina Lech, Fan Liu, Sarah K Davies, Katrin Ackermann, Joo Ern Ang, Benita Middleton, Victoria L Revell, Florence J Raynaud, Igor Hoveijn, Roelof A Hut and 2 more

Erratum issuedAbstract read
In one paragraph

Article in International journal of legal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Ten years of molecular ballistics-a review and a field guide.International journal of legal medicine · 2021
    Review
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Karolina LechDepartment of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Fan LiuDepartment of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.
Sarah K DaviesChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Katrin AckermannEaStCHEM School of Chemistry, Biomedical Sciences Research Complex and Centre of Magnetic Resonance, University of St. Andrews, St. Andrews, UK.
Joo Ern AngCancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.
Benita MiddletonChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Victoria L RevellChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Florence J RaynaudCancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.
Igor HoveijnGroningen Institute for Evolutionary Life Sciences, Chronobiology unit, University of Groningen, Groningen, The Netherlands.
Roelof A HutGroningen Institute for Evolutionary Life Sciences, Chronobiology unit, University of Groningen, Groningen, The Netherlands.
Debra J SkeneChronobiology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Manfred KayserDepartment of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands. m.kayser@erasmusmc.nl.

Funding

Cancer Research UK 11566Nederlandse Organisatie voor Wetenschappelijk Onderzoek 727.011.001Stichting voor de Technische Wetenschappen 12185UK Biotechnology and Biological Sciences Research Council BB/I019405/1
6 · The paper itself

Abstract

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.

Indexed as

BiomarkersBloodForensic MedicineHumansHydrocortisoneIntracellular Signaling Peptides and ProteinsLogistic ModelsMaleMelatoninMetabolomeMetabolomicsProtein Serine-Threonine KinasesRNA, MessengerTime FactorsBiomarkersHydrocortisoneIntracellular Signaling Peptides and ProteinsMelatoninMKNK2 protein, humanProtein Serine-Threonine KinasesRNA, MessengerBlood deposition timeCircadian biomarkersMetabolitesmRNATrace time estimation

Identifiers

PMID28780758
PMCPMC5748410

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.