59 research outputs found

    Evaluation of mRNA markers for estimating blood deposition time : towards alibi testing from human forensic stains with rhythmic biomarkers

    Get PDF
    This study was supported by grant 27.011.001 by the Netherlands Organization for Scientific Research (NWO) Forensic Science Program, Erasmus MC University Medical Center Rotterdam, by the EU 6th Framework project EUCLOCK (018741), UK Biotechnology and Biological Sciences Research Council (BBSRC) Grant BB/I019405/1, and by a previous grant from the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) within the framework of the Forensic Genomics Consortium Netherlands (FGCN). D.J.S. is a Royal Society Wolfson Research Merit Award holder.Determining the time a biological trace was left at a scene of crime reflects a crucial aspect of forensic investigations as - if possible - it would permit testing the sample donor's alibi directly from the trace evidence, helping to link (or not) the DNA-identified sample donor with the crime event. However, reliable and robust methodology is lacking thus far. In this study, we assessed the suitability of mRNA for the purpose of estimating blood deposition time, and its added value relative to melatonin and cortisol, two circadian hormones we previously introduced for this purpose. By analysing 21 candidate mRNA markers in blood samples from 12 individuals collected around the clock at 2 h intervals for 36 h under real-life, controlled conditions, we identified 11 mRNAs with statistically significant expression rhythms. We then used these 11 significantly rhythmic mRNA markers, with and without melatonin and cortisol also analysed in these samples, to establish statistical models for predicting day/night time categories. We found that although in general mRNA-based estimation of time categories was less accurate than hormone-based estimation, the use of three mRNA markers HSPA1B, MKNK2 and PER3 together with melatonin and cortisol generally enhanced the time prediction accuracy relative to the use of the two hormones alone. Our data best support a model that by using these five molecular biomarkers estimates three time categories, i.e., night/early morning, morning/noon, and afternoon/evening with prediction accuracies expressed as AUC values of 0.88, 0.88, and 0.95, respectively. For the first time, we demonstrate the value of mRNA for blood deposition timing and introduce a statistical model for estimating day/night time categories based on molecular biomarkers, which shall be further validated with additional samples in the future. Moreover, our work provides new leads for molecular approaches on time of death estimation using the significantly rhythmic mRNA markers established here.PostprintPeer reviewe

    Machine learning estimation of human body time using metabolomic profiling

    Get PDF
    This work was supported in part by the Netherlands Forensic Institute, Netherlands Genomics Initiative/Netherlands Organization for Scientific Research within the framework of the Forensic Genomics Consortium Netherlands, the 6th Framework project EUCLOCK (018741), and UK Biotechnology and Biological Sciences Research Council Grant BB/I019405/1. Additional funding was received from the Cancer Research UK Cancer Therapeutics Unit award (Ref: C2739/A22897) and a Cancer Therapeutics Centre award (Ref: C309/A25144 to FR), the NWO-STW Perspective Program grant ‘OnTime’ (project 12185 to TW and RAH).Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.Publisher PDFPeer reviewe

    THE INFLUENCE OF THE VARIOUS TEMPERATURES ON THE PUPAS OF MEDITERRANEAN FRUITFLY AND ON THE EARLY DEVELOPMENT OF PLASE OPIUS CONCOLORA SZEPL

    Get PDF
    The identification and investigation of novel clock-controlled genes (CCGs) has been conducted thus far mainly in model organisms such as nocturnal rodents, with limited information in humans. Here, we aimed to characterize daily and circadian expression rhythms of CCGs in human peripheral blood during a sleep/sleep deprivation (S/SD) study and a constant routine (CR) study. Blood expression levels of 9 candidate CCGs (SREBF1, TRIB1, USF1, THRA1, SIRT1, STAT3, CAPRIN1, MKNK2, and ROCK2), were measured across 48 h in 12 participants in the S/SD study and across 33 h in 12 participants in the CR study. Statistically significant rhythms in expression were observed for STAT3, SREBF1, TRIB1, and THRA1 in samples from both the S/SD and the CR studies, indicating that their rhythmicity is driven by the endogenous clock. The MKNK2 gene was significantly rhythmic in the S/SD but not the CR study, which implies its exogenously driven rhythmic expression. In addition, we confirmed the circadian expression of PER1, PER3, and REV-ERBÎą in the CR study samples, while BMAL1 and HSPA1B were not significantly rhythmic in the CR samples; all 5 genes previously showed significant expression in the S/SD study samples. Overall, our results demonstrate that rhythmic expression patterns of clock and selected clock-controlled genes in human blood cells are in part determined by exogenous factors (sleep and fasting state) and in part by the endogenous circadian timing system. Knowledge of the exogenous and endogenous regulation of gene expression rhythms is needed prior to the selection of potential candidate marker genes for future applications in medical and forensic settings

    Uncle Jesse and the seven “early career” ladies of the night

    Get PDF
    Jesse Leonard Greenstein (1909–2002) was apparently a very hard sell when it came to women in astronomy. Early in his autobiography, he wrote of “Miss Payne, a person of wide culture and astronomical knowledge. The obvious discrimination against her as a woman scientist, worthy of normal academic recognition, exacerbated the stressful life she led. She was unhappy, emotional, in a rivalry with Menzel and Plaskett.” She (a.k.a. Cecilia Helena Payne, later Gaposchkin) is the only woman with an explicit mention in that memoir, and Greenstein's impression of her left him uncertain whether women belonged in astronomy. In addition, some of us remember him as saying there was no use in educating women through to a Ph.D. because they only get married and quit

    Investigation of metabolites for estimating blood deposition time

    Get PDF
    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 PDFPeer reviewe

    Mitochondrial echoes of first settlement and genetic continuity in El Salvador

    Get PDF
    Background: From Paleo-Indian times to recent historical episodes, the Mesoamerican isthmus played an important role in the distribution and patterns of variability all around the double American continent. However, the amount of genetic information currently available on Central American continental populations is very scarce. In order to shed light on the role of Mesoamerica in the peopling of the New World, the present study focuses on the analysis of the mtDNA variation in a population sample from El Salvador. Methodology/Principal Findings: We have carried out DNA sequencing of the entire control region of the mitochondrial DNA (mtDNA) genome in 90 individuals from El Salvador. We have also compiled more than 3,985 control region profiles from the public domain and the literature in order to carry out inter-population comparisons. The results reveal a predominant Native American component in this region: by far, the most prevalent mtDNA haplogroup in this country (at ~90%) is A2, in contrast with other North, Meso- and South American populations. Haplogroup A2 shows a star-like phylogeny and is very diverse with a substantial proportion of mtDNAs (45%; sequence range 16090–16365) still unobserved in other American populations. Two different Bayesian approaches used to estimate admixture proportions in El Salvador shows that the majority of the mtDNAs observed come from North America. A preliminary founder analysis indicates that the settlement of El Salvador occurred about 13,400±5,200 Y.B.P.. The founder age of A2 in El Salvador is close to the overall age of A2 in America, which suggests that the colonization of this region occurred within a few thousand years of the initial expansion into the Americas. Conclusions/Significance: As a whole, the results are compatible with the hypothesis that today's A2 variability in El Salvador represents to a large extent the indigenous component of the region. Concordant with this hypothesis is also the observation of a very limited contribution from European and African women (~5%). This implies that the Atlantic slave trade had a very small demographic impact in El Salvador in contrast to its transformation of the gene pool in neighbouring populations from the Caribbean facade
    • …
    corecore