Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning?

INTRODUCTION: The (un)targeted analysis of endogenous compounds has gained interest in the field of forensic postmortem investigations. The blood metabolome is influenced by many factors, and postmortem specimens are considered particularly challenging due to unpredictable decomposition processes. OBJECTIVES: This study aimed to systematically investigate the influence of the time since death on endogenous compounds and its relevance in designing postmortem metabolome studies. METHODS: Femoral blood samples of 427 authentic postmortem cases, were collected at two time points after death (854 samples in total; t1: admission to the institute, 1.3-290 h; t2: autopsy, 11-478 h; median ∆t = 71 h). All samples were analyzed using an untargeted metabolome approach, and peak areas were determined for 38 compounds (acylcarnitines, amino acids, phospholipids, and others). Differences between t2 and t1 were assessed by Wilcoxon signed-ranked test (p < 0.05). Moreover, all samples (n = 854) were binned into time groups (6 h, 12 h, or 24 h intervals) and compared by Kruskal-Wallis/Dunn's multiple comparison tests (p < 0.05 each) to investigate the effect of the estimated time since death. RESULTS: Except for serine, threonine, and PC 34:1, all tested analytes revealed statistically significant changes between t1 and t2 (highest median increase 166%). Unpaired analysis of all 854 blood samples in-between groups indicated similar results. Significant differences were typically observed between blood samples collected within the first and later than 48 h after death, respectively. CONCLUSIONS: To improve the consistency of comprehensive data evaluation in postmortem metabolome studies, it seems advisable to only include specimens collected within the first 2 days after death.

Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood.

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.

The functional connectome of 3,4-methyldioxymethamphetamine-related declarative memory impairments.

The chronic intake of 3,4-methylenedioxymethamphetamine (MDMA, "ecstasy") bears a strong risk for sustained declarative memory impairments. Although such memory deficits have been repeatedly reported, their neurofunctional origin remains elusive. Therefore, we here investigate the neuronal basis of altered declarative memory in recurrent MDMA users at the level of brain connectivity. We examined a group of 44 chronic MDMA users and 41 demographically matched controls. Declarative memory performance was assessed by the Rey Auditory Verbal Learning Test and a visual associative learning test. To uncover alterations in the whole brain connectome between groups, we employed a data-driven multi-voxel pattern analysis (MVPA) approach on participants' resting-state functional magnetic resonance imaging data. Recent MDMA use was confirmed by hair analyses. MDMA users showed lower performance in delayed recall across tasks compared to well-matched controls with moderate-to-strong effect sizes. MVPA revealed a large cluster located in the left postcentral gyrus of global connectivity differences between groups. Post hoc seed-based connectivity analyses with this cluster unraveled hypoconnectivity to temporal areas belonging to the auditory network and hyperconnectivity to dorsal parietal regions belonging to the dorsal attention network in MDMA users. Seed-based connectivity strength was associated with verbal memory performance in the whole sample as well as with MDMA intake patterns in the user group. Our findings suggest that functional underpinnings of MDMA-related memory impairments encompass altered patterns of multimodal sensory integration within auditory processing regions to a functional heteromodal connector hub, the left postcentral gyrus. In addition, hyperconnectivity in regions of a cognitive control network might indicate compensation for degraded sensory processing.

Chronic 3,4-Methylenedioxymethamphetamine (MDMA) Use Is Related to Glutamate and GABA Concentrations in the Striatum But Not the Anterior Cingulate Cortex.

BACKGROUND: 3,4-Methylenedioxymethamphetamine (MDMA) is a widely used recreational substance inducing acute release of serotonin. Previous studies in chronic MDMA users demonstrated selective adaptations in the serotonin system, which were assumed to be associated with cognitive deficits. However, serotonin functions are strongly entangled with glutamate as well as γ-aminobutyric acid (GABA) neurotransmission, and studies in MDMA-exposed rats show long-term adaptations in glutamatergic and GABAergic signaling. METHODS: We used proton magnetic resonance spectroscopy (MRS) to measure the glutamate-glutamine complex (GLX) and GABA concentrations in the left striatum and medial anterior cingulate cortex (ACC) of 44 chronic but recently abstinent MDMA users and 42 MDMA-naïve healthy controls. While the Mescher-Garwood point-resolved-spectroscopy sequence (MEGA-PRESS) is best suited to quantify GABA, recent studies reported poor agreement between conventional short-echo-time PRESS and MEGA-PRESS for GLX measures. Here, we applied both sequences to assess their agreement and potential confounders underlying the diverging results. RESULTS: Chronic MDMA users showed elevated GLX levels in the striatum but not the ACC. Regarding GABA, we found no group difference in either region, although a negative association with MDMA use frequency was observed in the striatum. Overall, GLX measures from MEGA-PRESS, with its longer echo time, appeared to be less confounded by macromolecule signal than the short-echo-time PRESS and thus provided more robust results. CONCLUSION: Our findings suggest that MDMA use affects not only serotonin but also striatal GLX and GABA concentrations. These insights may offer new mechanistic explanations for cognitive deficits (e.g., impaired impulse control) observed in MDMA users.

Advances in testing for sample manipulation in clinical and forensic toxicology - Part A: urine samples.

In many countries, adherence testing is used to monitor consumption behavior or to prove abstinence. Urine and hair are most commonly used, although other biological fluids are available. Positive test results are usually associated with serious legal or economic consequences. Therefore, various sample manipulation and adulteration strategies are used to circumvent such a positive result. In these critical review articles on sample adulteration of urine (part A) and hair samples (part B) in the context of clinical and forensic toxicology, recent trends and strategies to improve sample adulteration and manipulation testing published in the past 10 years are described and discussed. Typical manipulation and adulteration strategies include undercutting the limits of detection/cut-off by dilution, substitution, and adulteration. New or alternative strategies for detecting sample manipulation attempts can be generally divided into improved detection of established urine validity markers and direct and indirect techniques or approaches to screening for new adulteration markers. In this part A of the review article, we focused on urine samples, where the focus in recent years has been on new (in)direct substitution markers, particularly for synthetic (fake) urine. Despite various and promising advances in detecting manipulation, it remains a challenge in clinical and forensic toxicology, and simple, reliable, specific, and objective markers/techniques are still lacking, for example, for synthetic urine.

Advances in testing for sample manipulation in clinical and forensic toxicology-part B: hair samples.

As a continuation of part A, focusing on advances in testing for sample manipulation of urine samples in clinical and forensic toxicology, part B of the review article relates to hair, another commonly used matrix for abstinence control testing. Similar to urine manipulation, relevant strategies to manipulate a hair test are lowering drug concentrations in hair to undercut the limits of detection/cut-offs, for instance, by forced washout effects or adulteration. However, distinguishing between usual, common cosmetic hair treatment and deliberate manipulation to circumvent a positive drug test is often impossible. Nevertheless, the identification of cosmetic hair treatment is very relevant in the context of hair testing and interpretation of hair analysis results. Newly evaluated techniques or elucidation of specific biomarkers to unravel adulteration or cosmetic treatment often focused on specific structures of the hair matrix with promising strategies recently proposed for daily routine work. Identification of other approaches, e.g., forced hair-washing procedures, still remains a challenge in clinical and forensic toxicology.

Analytical description of adolescent binge drinking patients.

BACKGROUND: Binge drinking is a widespread health compromising behavior among adolescents and young adults, leading to significant health problems, injuries and mortality. However, data on alcohol consumption is often unreliable, as it is mainly based on self-reporting surveys. In this five-year study (2014-2019) at the University Children's Hospital Zurich, we analyzed blood samples from adolescent binge drinking patients to investigate blood alcohol concentrations (BACs), co-ingestion of drugs, assess compliance between self-reported and measured substance use, and test for genetic components of innate alcohol tolerance. Furthermore, hair analysis was performed to retrospectively access drug exposure and to evaluate the potential of hair analysis to assess binge drinking. METHODS: In a prospective, single-center study, patients with alcohol intoxications aged 16 years and younger were included. Blood and hair samples were analyzed by sensitive liquid chromatography - tandem mass spectrometry drug analysis. HTTLPR genotyping was performed with PCR and fragment analysis. RESULTS: Among 72 cases, 72 blood and 13 hair samples were analyzed. BACs ranged from 0.08-3.20‰ (mean 1.63‰, median 1.60‰), while a mean concentration of 3.64 pg/mg hair (median 3.0 pg/mg) of the alcohol marker ethyl glucuronide (EtG) was detected in eleven hair samples, providing no evidence of chronic excessive drinking. In 47% of the cases, co-ingested drugs were qualitatively detected next to ethanol, but only 9% of the detected drugs had blood concentrations classified as pharmacologically active. Cannabis consumption (22%) and stimulant intake (16%) were the most frequently observed drugs. Compliance between patients' statements and measured substances matched well. Although we investigated the genetic contribution to innate alcohol tolerance via the 5-HTTLPR polymorphism, the diverse genetic background of the cohort and small sample size did not allow any conclusions to be drawn. CONCLUSION: Almost half of our binge drinking patients tested positive for other substances, primarily cannabis. We anticipate that our study enhances understanding of consumption behavior of young people and encourage continued efforts to address the harmful effects of binge drinking and co-occurring substance use.

Determination of the Time since Deposition of Blood Traces Utilizing a Liquid Chromatography-Mass Spectrometry-Based Proteomics Approach.

Knowledge about when a bloodstain was deposited at a crime scene can be of critical value in forensic investigation. A donor of a genetically identified bloodstain could be linked to a suspected time frame and the crime scene itself. Determination of the time since deposition (TsD) has been extensively studied before but has yet to reach maturity. We therefore conducted a proof-of-principle study to study time- and storage-dependent changes of the proteomes of dried blood stains. A bottom-up proteomics approach was employed, and high-resolution liquid-chromatography-mass-spectrometry (HR-LC-MS) and data-independent acquisition (DIA) were used to analyze samples aged over a 2 month period and two different storage conditions. In multivariate analysis, samples showed distinct clustering according to their TsD in both principal component analysis (PCA) and in partial least square discriminant analysis (PLS DA). The storage condition alters sample aging and yields different separation-driving peptides in hierarchical clustering and in TsD marker peptide selection. Certain peptides and amino acid modifications were identified and further assessed for their applicability in assessing passed TsD. A prediction model based on data resampling (Jackknife) was applied, and prediction values for selected peptide ratios were created. Depending on storage conditions and actual sample age, mean prediction performances ranges in between 70 and 130% for the majority of peptides and time points. This places this study as a first in investigating LC-MS based bottom-up proteomics approaches for TsD determination.

Towards a New Qualitative Screening Assay for Synthetic Cannabinoids Using Metabolomics and Machine Learning.

BACKGROUND: Synthetic cannabinoids (SCs) are steadily emerging on the drug market. To remain competitive in clinical or forensic toxicology, new screening strategies including high-resolution mass spectrometry (HRMS) are required. Machine learning algorithms can detect and learn chemical signatures in complex datasets and use them as a proxy to predict new samples. We propose a new screening tool based on a SC-specific change of the metabolome and a machine learning algorithm. METHODS: Authentic human urine samples (n = 474), positive or negative for SCs, were used. These samples were measured with an untargeted metabolomics liquid chromatography (LC)-quadrupole time-of-flight-HRMS method. Progenesis QI software was used to preprocess the raw data. Following feature engineering, a random forest (RF) model was optimized in R using a 10-fold cross-validation method and a training set (n = 369). The performance of the model was assessed with a test (n = 50) and a verification (n = 55) set. RESULTS: During RF optimization, 49 features, 200 trees, and 7 variables at each branching node were determined as most predictive. The optimized model accuracy, clinical sensitivity, clinical specificity, positive predictive value, and negative predictive value were 88.1%, 83.0%, 92.7%, 91.3%, and 85.6%, respectively. The test set was predicted with an accuracy of 88.0%, and the verification set provided evidence that the model was able to detect cannabinoid-specific changes in the metabolome. CONCLUSIONS: An RF approach combined with metabolomics enables a novel screening strategy for responding effectively to the challenge of new SCs. Biomarkers identified by this approach may also be integrated in routine screening methods.

Interpretable machine learning model to detect chemically adulterated urine samples analyzed by high resolution mass spectrometry.

OBJECTIVES: Urine sample manipulation including substitution, dilution, and chemical adulteration is a continuing challenge for workplace drug testing, abstinence control, and doping control laboratories. The simultaneous detection of sample manipulation and prohibited drugs within one single analytical measurement would be highly advantageous. Machine learning algorithms are able to learn from existing datasets and predict outcomes of new data, which are unknown to the model. METHODS: Authentic human urine samples were treated with pyridinium chlorochromate, potassium nitrite, hydrogen peroxide, iodine, sodium hypochlorite, and water as control. In total, 702 samples, measured with liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, were used. After retention time alignment within Progenesis QI, an artificial neural network was trained with 500 samples, each featuring 33,448 values. The feature importance was analyzed with the local interpretable model-agnostic explanations approach. RESULTS: Following 10-fold cross-validation, the mean sensitivity, specificity, positive predictive value, and negative predictive value was 88.9, 92.0, 91.9, and 89.2%, respectively. A diverse test set (n=202) containing treated and untreated urine samples could be correctly classified with an accuracy of 95.4%. In addition, 14 important features and four potential biomarkers were extracted. CONCLUSIONS: With interpretable retention time aligned liquid chromatography high-resolution mass spectrometry data, a reliable machine learning model could be established that rapidly uncovers chemical urine manipulation. The incorporation of our model into routine clinical or forensic analysis allows simultaneous LC-MS analysis and sample integrity testing in one run, thus revolutionizing this field of drug testing.

Comparison of the beta-hydroxybutyrate, glucose, and lactate concentrations derived from postmortem proton magnetic resonance spectroscopy and biochemical analysis for the diagnosis of fatal metabolic disorders.

PURPOSE: The detection and quantification of metabolites relevant for the diagnosis of fatal metabolic disorders by proton magnetic resonance spectroscopy (1H-MRS) was recently demonstrated. This prospective study aimed to compare the concentrations of beta-hydroxybutyrate (BHB), glucose (GLC), and lactate (LAC) derived from both biochemical analyses and 1H-MRS for the diagnosis of fatal metabolic disorders. METHODS: In total, 20 cases with suspected fatal metabolic disorders were included in the study. For the agreement based on thresholds, the concentrations of BHB and GLC in the vitreous humor (VH) from the right vitreous and in cerebrospinal fluid (CSF) from the right lateral ventricle were derived from 1H-MRS and biochemical analyses. The predefined thresholds for pathological elevations were 2.5 mmol/l for BHB and 10 mmol/l for GLC based on the literature. In addition, concentrations of the same metabolites in white matter (WM) tissue from the corona radiata of the right hemisphere were analyzed experimentally using both methods. To enable the biochemical analysis, a dialysate of WM tissue was produced. For all three regions, the LAC concentration was determined by both methods. RESULTS: The conclusive agreement based on thresholds was almost perfect between both methods with only one disagreement in a total of 70 comparisons due to the interference of a ferromagnetic dental brace. The differences in the concentrations between both methods showed high standard deviations. Confidence intervals of the bias not including 0 were found in CSF-GLC (- 3.1 mmol/l), WM-GLC (1.1 mmol/l), and WM-LAC (- 6.5 mmol/l). CONCLUSION: Despite a considerable total error attributable to both methods, MRS derives the same forensic conclusions as conventional biochemical analyses. An adaptation of the protocol to reduce the detected errors and more data are needed for the long-term validation of MRS for the diagnosis of fatal metabolic disorders. The production of WM dialysates cannot be recommended due to high glycolytic loss.

Cheating on forensic hair testing? Detection of potential biomarkers for cosmetically altered hair samples using untargeted hair metabolomics.

Hair analysis has become an integral part in forensic toxicological laboratories for e.g. assessment of drug or alcohol abstinence. However, hair samples can be manipulated by cosmetic treatments, altering drug concentrations which eventually leads to false negative hair test results. In particular oxidative bleaching of hair samples under alkaline conditions significantly affects incorporated drug concentrations. To date, current techniques to detect cosmetic hair adulterations bear limitations such as the implementation of cut-off values or the requirement of specialized instrumentations. As a new approach, untargeted hair metabolomics analysis was applied to detect altered, endogenous biomolecules that could be used as biomarkers for oxidative cosmetic hair treatments. For this, genuine hair samples were treated in vitro with 9% hydrogen peroxide (H2O2) for 30 minutes. Untreated and treated hair samples were analyzed using liquid-chromatography high-resolution time-of-flight mass spectrometry. In total, 69 metabolites could be identified as significantly altered after hair bleaching. The majority of metabolites decreased after bleaching, yet totally degraded metabolites were most promising as suitable biomarkers. The formation of biomarker ratios of metabolites decreasing and increasing in concentrations improved the discrimination of untreated and treated hair samples. With the results of this study, the high variety of identified biomarkers now offers the possibility to include single biomarkers or biomarker selections into routine screening methods for improved data interpretation of hair test results.

Analytical considerations for postmortem metabolomics using GC-high-resolution MS.

Metabolomics studies that aim to qualitatively and quantitatively characterize the entirety of small endogenous biomolecules in an organism are widely conducted in the clinical setting. They also become more and more popular in the field of forensics (toxicology), e.g., to assist in postmortem investigations by objective postmortem interval estimation. However, other issues in postmortem toxicology, such as the phenomenon of (time-dependent) postmortem redistribution, have not yet been tackled by metabolomics studies. Hence, the aim of the current study was to develop an (un)targeted gas chromatography-high-resolution mass spectrometry-based method for endogenous metabolites as a tool for large-scale (un)targeted human postmortem metabolomics investigations (e.g., to objectively assess PMR) with thorough analytical evaluation of this method to ensure fitness-to-purpose in terms of reliability and robustness. This was achieved by using a targeted metabolite subset (n = 56) and a targeted processing workflow. Evaluation experiments have shown that using an artificial matrix (revised simulated body fluid (rSBF) + 5% bovine serum albumin (BSA)) for calibration purposes, all parameters lay within the scope of the method (sensitivity, selectivity, calibration model, accuracy, precision, processed sample stability, and extraction efficiency). When applying this method to large-scale studies, samples should be run in randomized order if analysis time is expected to exceed 18-24 h and potential biomarkers that are found with this method should be verified by a specialized, targeted method (e.g., by using standard addition in authentic matrix for quantification purposes). Overall, the current method can be successfully used for conduction of time-dependent postmortem metabolomics investigations. Graphical abstract.

Hair Analysis: Contamination versus Incorporation from the Circulatory System-Investigations on Single Hair Samples Using Time-of-Flight Secondary Ion Mass Spectrometry and Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry.

Contamination is a highly controversial issue in hair analysis. Therefore, hair testing protocols typically include wash steps to remove contamination. However, recent studies claim that washing could also lead to permanent incorporation of contaminants into hair, thus questioning the validity of hair testing at all. In the present study, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) with longitudinal sectioning of single hairs and different decontamination protocols was used to reveal differences between the incorporation of a substance into hair from external sources and an incorporation via bloodstream. Single hairs were longitudinally sectioned using a custom-made sample holder. Data were acquired with MALDI-MS by rastering each hair individually. Single hair samples from drug users, blank hairs, and zolpidem- and zolpidem-D6-soaked hairs were investigated. Different published washing protocols were tested, and an in-house washing protocol was developed. For images with higher spatial resolution, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used. Longitudinal sectioning of hairs dramatically increased sensitivity; even single-dose administrations of zolpidem in single hairs could thus be detected using MALDI-MS. Zolpidem from external sources could be detected in large quantities in superficial hair structures. Zolpidem from consumer hairs, proposed to be strongly bound to inner hair structures, could not be completely removed even by the strongest tested decontamination protocol, whereas zolpidem-soaked hairs could be cleared almost completely with the developed in-house wash protocol. The applied methods allowed a first insight into the connection of decontamination protocols and wash-in phenomena in hair analysis. Further studies with other drugs are necessary to assess the general validity of these findings.

In situ postmortem ethanol quantification in the cerebrospinal fluid by non-water-suppressed proton MRS.

Determination of the ethanol concentration in corpses with MRS would allow a reproducible forensic assessment by which evidence is collected in a noninvasive manner. However, although MRS has been successfully used to detect ethanol in vivo, it has not been applied to postmortem ethanol quantification in situ. The present study examined the feasibility of the noninvasive measurement of the ethanol concentration in human corpses with MRS. A total of 15 corpses with suspected alcohol consumption before demise underwent examination in a 3 T whole body scanner. To address the partial overlap of the ethanol and lactate signal in the postmortem spectrum, non-water-suppressed single voxel spectra were recorded in the cerebrospinal fluid (CSF) of the left lateral ventricle via the metabolite cycling technique. The ethanol signals were quantified using the internal water as reference standard, as well as based on a reference signal acquired in a phantom. The measured values were compared with biochemically determined concentrations in the blood (BAC) and CSF (CSFAC). In 8 of the 15 corpses a BAC above zero was determined (range 0.03-1.68 g/kg). In all of these 8 corpses, ethanol was measured in CSF with the proposed MRS protocol. The two applied MRS calibration strategies resulted in similar concentrations. However, the MRS measurements generally overestimated the ethanol concentration by 0.09 g/kg (4%) to 0.72 g/kg (45%) as compared with the CSFAC value. The presented MRS protocol allows the measurement of ethanol in the CSF in human corpses and provides an estimation of the ethanol concentration prior to autopsy. Observed deviations from biochemically determined concentrations are mainly explained by the approximate correction of the relaxation attenuation of the ethanol signal.

(Un)targeted hair metabolomics: first considerations and systematic evaluation on the impact of sample preparation.

The interest in metabolomic studies has rapidly increased over the past few years. Changes of endogenous compounds are typically detected in plasma or urine. However, the use of hair allows for long-term monitoring of metabolomic changes and has recently started being applied to metabolomic studies. Within the proposed study, we aimed for a systematical investigation of different pre-analytical parameters on detected metabolites from different chemical classes in hair. For this purpose, three different parameters were varied: (1) multi-step decontamination (dichloromethane (DCM), acetone, H2O, acetone; H2O, acetone, DCM, acetone; and H2O, methanol/acetone), (2) homogenization (pulverization vs. cutting into snippets), and (3) extraction (acetonitrile (ACN)/buffer pH 4 vs. ACN/H2O vs. ACN/buffer pH 8.5). To include as many metabolites as possible, samples were analyzed by high-resolution time of flight mass spectrometry coupled to liquid chromatography (HPLC-HRMS) and additionally by gas chromatography high-resolution mass spectrometry (GC-HRMS) followed by untargeted-like data processing, respectively. The application of different decontamination procedures yielded similar results, although pointing to a trend towards increased washing-out effects if protic solvents were used as a first washing step. Pulverization of hair samples was favorable in terms of detected and tentatively identified metabolites. Evaluation of extraction solvents showed differences in extraction yield for the majority of investigated metabolites, yet, a prediction of metabolite extraction according to their pKa values was not possible. Overall, successive decontamination with DCM, acetone, H2O, and acetone; homogenization by pulverization; and extraction with ACN/H2O produced reliable results. Graphical abstract.

Human Metabolome Changes after a Single Dose of 3,4-Methylenedioxymethamphetamine (MDMA) with Special Focus on Steroid Metabolism and Inflammation Processes.

The intake of 3,4-methylenedioxymethamphetamine (MDMA) is known to increase several endogenous substances involved in steroid and inflammation pathways. Untargeted metabolomics screening approaches can determine biochemical changes after drug exposure and can reveal new pathways, which might be involved in the pharmacology and toxicology of a drug of abuse. We analyzed plasma samples from a placebo-controlled crossover study of a single intake of MDMA. Plasma samples from a time point before and three time points after the intake of a single dose of 125 mg MDMA were screened for changes of endogenous metabolites. An untargeted metabolomics approach on a high-resolution quadrupole time-of-flight mass spectrometer coupled to liquid chromatography with two different chromatographic systems (reversed-phase and hydrophobic interaction liquid chromatography) was applied. Over 10 000 features of the human metabolome were detected. Hence, 28 metabolites were identified, which showed significant changes after administration of MDMA compared with placebo. The analysis revealed an upregulation of cortisol and pregnenolone sulfate 4 h after MDMA intake, suggesting increased stress and serotonergic activity. Furthermore, calcitriol levels were decreased after the intake of MDMA. Calcitriol is involved in the upregulation of trophic factors, which have protective effects on brain dopamine neurons. The inflammation mediators hydroxyeicosatetraenoic acid, dihydroxyeicosatetraenoic acid, and octadecadienoic acid were found to be upregulated after the intake of MDMA compared with placebo, which suggested a stimulation of inflammation pathways.

Parameter Optimization for Feature and Hit Generation in a General Unknown Screening Method-Proof of Concept Study Using a Design of Experiment Approach for a High Resolution Mass Spectrometry Procedure after Data Independent Acquisition.

High resolution mass spectrometry and modern data independent acquisition (DIA) methods enable the creation of general unknown screening (GUS) procedures. However, even when DIA is used, its potential is far from being exploited, because often, the untargeted acquisition is followed by a targeted search. Applying an actual GUS (including untargeted screening) produces an immense amount of data that must be dealt with. An optimization of the parameters regulating the feature detection and hit generation algorithms of the data processing software could significantly reduce the amount of unnecessary data and thereby the workload. Design of experiment (DoE) approaches allow a simultaneous optimization of multiple parameters. In a first step, parameters are evaluated (crucial or noncrucial). Second, crucial parameters are optimized. The aim in this study was to reduce the number of hits, without missing analytes. The obtained parameter settings from the optimization were compared to the standard settings by analyzing a test set of blood samples spiked with 22 relevant analytes as well as 62 authentic forensic cases. The optimization lead to a marked reduction of workload (12.3 to 1.1% and 3.8 to 1.1% hits for the test set and the authentic cases, respectively) while simultaneously increasing the identification rate (68.2 to 86.4% and 68.8 to 88.1%, respectively). This proof of concept study emphasizes the great potential of DoE approaches to master the data overload resulting from modern data independent acquisition methods used for general unknown screening procedures by optimizing software parameters.

First Time View on Human Metabolome Changes after a Single Intake of 3,4-Methylenedioxymethamphetamine in Healthy Placebo-Controlled Subjects.

3,4-Methylenedioxymethamphetamine (MDMA; "ecstasy") is widely consumed recreationally. Little is known about its effects on the human metabolome. Mapping biochemical changes after drug exposure can complement traditional approaches by revealing potential biomarkers of organ toxicity or discovering new metabolomic features in a time- and dose-dependent manner. We aimed to analyze for the first time plasma samples from a randomized, double-blind, placebo-controlled crossover study in healthy adults to explore changes in endogenous plasma metabolites following a single intake of MDMA. Plasma samples from 15 subjects taken at four different time points were analyzed with the commercially available AbsoluteIDQ kit (Biocrates). Time series analysis revealed a total of nine metabolites, which showed a significant concentration change after MDMA administration compared with placebo. Paired t tests of the single time points showed statistically significant concentration changes mainly of glycerophospholipids and the metabolic ratio of methionine-sulfoxide over methionine. Changes of this metabolic ratio may be indicative for changes in systemic oxidative stress levels, and the increased amount of glycerophospholipids could be interpreted as an upregulation of energy production. Baseline samples within the experimental study design were crucial for evaluation of metabolomics data as interday individuality within subjects was high otherwise resulting in overestimations of the findings.

Time-dependent postmortem redistribution of morphine and its metabolites in blood and alternative matrices-application of CT-guided biopsy sampling.

Interpretation of postmortem morphine concentrations in forensic toxicology provides several pitfalls such as missing information on tolerance, analyte stability, or postmortem redistribution (PMR). Recently, it had been shown that computed tomography (CT)-guided collection of biopsies using a robotic arm (virtobot) provides a valuable strategy for systematic studies on time-dependent PMR. Using this technique, time-dependent PMR of morphine and its metabolites was investigated in 12 cases. At admission to the institute (t1), femoral and heart blood (right ventricle) as well as biopsies from the right lung, the right kidney, liver, spleen, and muscle tissue were collected. At autopsy approximately 24 h later (t2), samples from the same body regions were collected again. Additionally, gastric contents, urine, brain tissue, and heart blood from the left ventricle was collected. Morphine, normorphine, hydromorphone, morphine-3-glucuronide, morphine-6-glucuronide, and morphine-sulfate were quantified with LC-MS/MS. In femoral blood, significant increase of morphine concentrations was observed, although ultimately not relevant for forensic interpretation. In the alternative matrices, increases as well as decreases were observed without a clear trend. The morphine metabolites did not exhibit relevant concentration changes. Investigation of underlying redistribution mechanisms indicated that concentration change (i.e., increase) of morphine in femoral blood rather resulted from diffusion processes than from release of morphine from its conjugates. Concentration changes in heart blood might have been caused by redistribution from lung tissue or gastric content. This study also proved that CT-guided collection of biopsies using a virtobot arm is an invaluable tool for future studies on PMR redistribution of other substance groups.