A Metabolomics Study of Retrospective Forensic Data from Whole Blood Samples of Humans Exposed to 3,4-Methylenedioxymethamphetamine: A New Approach for Identifying Drug Metabolites and Changes in Metabolism Related to Drug Consumption

Bile acids and the gut microbiome are involved in the hyperthermia mediated by 3,4-methylenedioxymethamphetamine (MDMA)

Hyperthermia induced by phenethylamines, such as 3,4-methylenedioxymethamphetamine (MDMA), can lead to life-threatening complications and death. Activation of the sympathetic nervous system and subsequent release of norepinephrine and activation of uncoupling proteins have been demonstrated to be the key mediators of phenethylamine-induced hyperthermia (PIH). Recently, the gut microbiome was shown to also play a contributing role in PIH. Here, the hypothesis that bile acids (BAs) produced by the gut microbiome are essential to PIH was tested. Changes in the serum concentrations of unconjugated primary BAs cholic acid (CA) and chenodeoxycholic acid (CDCA) and secondary BA deoxycholic acid (DCA) were measured following MDMA (20 mg/kg, sc) treatment in antibiotic treated and control rats. MDMA-induced a significant hyperthermic response and reduced the serum concentrations of three BAs 60 min post-treatment. Pretreatment with antibiotics (vancomycin, bacitracin and neomycin) in the drinking water for five days resulted in the depletion of BAs and a hypothermic response to MDMA. Gut bacterial communities in the antibiotic-treated group were distinct from the MDMA or saline treatment groups, with decreased microbiome diversity and alteration in taxa. Metagenomic functions inferred using the bioinformatic tool PICRUSt2 on 16S rRNA gene sequences indicated that bacterial genes associated to BA metabolism are less abundant in the antibiotic-MDMA treated group. Overall, these findings suggest that gut bacterial produced BAs might play an important role in MDMA-induced hyperthermia.

Postmortem metabolomics as a high-throughput cause-of-death screening tool for human death investigations

Autopsy rates are declining globally, impacting cause-of-death (CoD) diagnoses and quality control. Postmortem metabolomics was evaluated for CoD screening using 4,282 human cases, encompassing CoD groups: acidosis, drug intoxication, hanging, ischemic heart disease (IHD), and pneumonia. Cases were split 3:1 into training and test sets. High-resolution mass spectrometry data from femoral blood were analyzed via orthogonal-partial least squares discriminant analysis (OPLS-DA) to discriminate CoD groups. OPLS-DA achieved an R2 = 0.52 and Q2 = 0.30, with true-positive prediction rates of 68% and 65% for training and test sets, respectively, across all groups. Specificity-optimized thresholds predicted 56% of test cases with a unique CoD, average 45% sensitivity, and average 96% specificity. Prediction accuracies varied: 98.7% for acidosis, 80.5% for drug intoxication, 81.6% for hanging, 73.1% for IHD, and 93.6% for pneumonia. This study demonstrates the potential of large-scale postmortem metabolomics for CoD screening, offering high specificity and enhancing throughput and decision-making in human death investigations.

Metabolomics reveals the effects of Lactiplantibacillus plantarum dy-1 fermentation on the lipid-lowering capacity of barley β-glucans in an in vitro model of gut-liver axis

Bioactive polysaccharides known as the biological response modifiers, can directly interact with intestinal epithelium cells (IEC) and regulate key metabolic processes such as lipid metabolism. Here, the coculture of Caco-2/HT29 monolayer (>400 Ω × cm2) and HepG2 cells was developed to mimic the gut-liver interactions. This system was used to investigate the effects of raw and fermented barley β-glucans (RBG and FBG) on lipid metabolism by directly interacting with IEC. Both RBG and FBG significantly and consistently reduced the lipid droplets and triacylglycerol levels in monoculture and coculture of HepG2 overloaded with oleic acid. Notably, FBG significantly and distinctly elevated PPARα (p < 0.05) and PPARα-responsive ACOX-1 (p < 0.01) gene expressions, promoting lipid degradation in cocultured HepG2. Moreover, the metabolomics analyses revealed that FBG had a unique impact on extracellular metabolites, among them, the differential metabolite thiomorpholine 3-carboxylate was significantly and strongly correlated with PPARα (r = -0.68, p < 0.01) and ACOX-1 (r = -0.76, p < 0.01) expression levels. Taken together, our findings suggest that FBG-mediated gut-liver interactions play a key role in its lipid-lowering effects that are superior to those of RBG. These results support the application of Lactiplantibacillus fermentation for improving hypolipidemic outcomes.

Large-Scale metabolomics: Predicting biological age using 10,133 routine untargeted LC-MS measurements

Untargeted metabolomics is the study of all detectable small molecules, and in geroscience, metabolomics has shown great potential to describe the biological age-a complex trait impacted by many factors. Unfortunately, the sample sizes are often insufficient to achieve sufficient power and minimize potential biases caused by, for example, demographic factors. In this study, we present the analysis of biological age in ~10,000 toxicologic routine blood measurements. The untargeted screening samples obtained from ultra-high pressure liquid chromatography-quadruple time of flight mass spectrometry (UHPLC- QTOF) cover + 300 batches and + 30 months, lack pooled quality controls, lack controlled sample collection, and has previously only been used in small-scale studies. To overcome experimental effects, we developed and tested a custom neural network model and compared it with existing prediction methods. Overall, the neural network was able to predict the chronological age with an rmse of 5.88 years (r²  = 0.63) improving upon the 6.15 years achieved by existing normalization methods. We used the feature importance algorithm, Shapley Additive exPlanations (SHAP), to identify compounds related to the biological age. Most importantly, the model returned known aging markers such as kynurenine, indole-3-aldehyde, and acylcarnitines along with a potential novel aging marker, cyclo (leu-pro). Our results validate the association of tryptophan and acylcarnitine metabolism to aging in a highly uncontrolled large-s cale sample. Also, we have shown that by using robust computational methods it is possible to deploy large LC-MS datasets for metabolomics studies to reduce the risk of bias and empower aging studies.

Scalable Analysis of Untargeted LC-HRMS Data by Means of SQL Database Archiving

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is widely used to detect chemicals with a broad range of physiochemical properties in complex biological samples. However, the current data analysis strategies are not sufficiently scalable because of data complexity and amplitude. In this article, we report a novel data analysis strategy for HRMS data founded on structured query language database archiving. A database called ScreenDB was populated with parsed untargeted LC-HRMS data after peak deconvolution from forensic drug screening data. The data were acquired using the same analytical method over 8 years. ScreenDB currently holds data from around 40,000 data files, including forensic cases and quality control samples that can be readily sliced and diced across data layers. Long-term monitoring of system performance, retrospective data analysis for new targets, and identification of alternative analytical targets for poorly ionized analytes are examples of ScreenDB applications. These examples demonstrate that ScreenDB makes a significant improvement to forensic services and that the concept has potential for broad applications for all large-scale biomonitoring projects that rely on untargeted LC-HRMS data.

In Vitro and In Vivo Toxicometabolomics of the Synthetic Cathinone PCYP Studied by Means of LC-HRMS/MS

Synthetic cathinones are one important group amongst new psychoactive substances (NPS) and limited information is available regarding their toxicokinetics and -dynamics. Over the past few years, nontargeted toxicometabolomics has been increasingly used to study compound-related effects of NPS to identify important exogenous and endogenous biomarkers. In this study, the effects of the synthetic cathinone PCYP (2-cyclohexyl-1-phenyl-2-(1-pyrrolidinyl)-ethanone) on in vitro and in vivo metabolomes were investigated. Pooled human-liver microsomes and blood and urine of male Wistar rats were used to generate in vitro and in vivo data, respectively. Samples were analyzed by liquid chromatography and high-resolution mass spectrometry using an untargeted metabolomics workflow. Statistical evaluation was performed using univariate and multivariate statistics. In total, sixteen phase I and one phase II metabolite of PCYP could be identified as exogenous biomarkers. Five endogenous biomarkers (e.g., adenosine and metabolites of tryptophan metabolism) related to PCYP intake could be identified in rat samples. The present data on the exogenous biomarker of PCYP are crucial for setting up analytical screening procedures. The data on the endogenous biomarker are important for further studies to better understand the physiological changes associated with cathinone abuse but may also serve in the future as additional markers for an intake.

Exercise Regulates the Metabolic Homeostasis of Methamphetamine Dependence

Physical exercise is effective in enhancing cognitive function, reducing anxiety and depressive symptoms, reducing cravings, and improving quality of life in methamphetamine (METH) addiction. However, little is known about the effect of exercise on metabolic profiles. We performed LC/MS-based targeted metabolic profiling on serum samples to investigate the metabolic characteristics of METH dependence and find the differences between METH-dependent individuals and nonusers and evaluated the metabolomic profiles of individuals with METH dependence following aerobic exercise training. We identified a total of 201 metabolites, among which 115 were differentially expressed under METH use. Among the differentially regulated metabolites, 72 were selected as potential biomarkers. Further analysis identified 19 pathways, among which glyoxylate and dicarboxylate metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were most significantly affected by METH. The aerobic exercise intervention differentially regulated 55 metabolites, of which 51 were selected as potential biomarkers and were mainly enriched in 10 pathways. Interestingly, alanine, aspartate, and glutamate metabolism and nitrogen metabolism were the remarkably affected pathways. Furthermore, METH increased the serum levels of glutamate and decreased GABA, whereas exercise decreased the serum levels of glutamate and increased GABA. Results suggested that METH dependency disturbed normal metabolic homeostasis, whereas exercise restored metabolism.

A Retrospective Metabolomics Analysis of Gamma-Hydroxybutyrate in Humans: New Potential Markers and Changes in Metabolism Related to GHB Consumption

GHB is an endogenous short-chain organic acid presumably also widely applied as a rape and knock out drug in cases of drug-facilitated crimes or sexual assaults (DFSA). Due to the endogenous nature of GHB and its fast metabolism in vivo, the detection window of exogenous GHB is however narrow, making it challenging to prove use of GHB in DFSA cases. Alternative markers of GHB intake have recently appeared though none has hitherto been validated for forensic use. UHPLC-HRMS based screening of blood samples for drugs of abuse is routinely performed in several forensic laboratories which leaves an enormous amount of unexploited data. Recently we devised a novel metabolomics approach to use archived data from such routine screenings for elucidating both direct metabolites from exogenous compounds, but potentially also regulation of endogenous metabolism and metabolites. In this paper we used UHPLC-HRMS data acquired over a 6-year period from whole blood analysis of 51 drivers driving under the influence of GHB as well as a matched control group. The data were analyzed using a metabolomics approach applying a range of advanced analytical methods such as OPLS-DA, LASSO, random forest, and Pearson correlation to examine the data in depth and demonstrate the feasibility and potential power of the approach. This was done by initially detecting a range of potential biomarkers of GHB consumption, some that previously have been found in controlled GHB studies, as well as several new potential markers not hitherto known. Furthermore, we investigate the impact of GHB intake on human metabolism. In aggregate, we demonstrate the feasibility to extract meaningful information from archived data here exemplified using GHB cases. Hereby we hope to pave the way for more general use of the principle to elucidate human metabolites of e.g. new legal or illegal drugs as well as for applications in more global and large scale metabolomics studies in the future.

Developments in high-resolution mass spectrometric analyses of new psychoactive substances

The proliferation of new psychoactive substances (NPS) has necessitated the development and improvement of current practices for the detection and identification of known NPS and newly emerging derivatives. High-resolution mass spectrometry (HRMS) is quickly becoming the industry standard for these analyses due to its ability to be operated in data-independent acquisition (DIA) modes, allowing for the collection of large amounts of data and enabling retrospective data interrogation as new information becomes available. The increasing popularity of HRMS has also prompted the exploration of new ways to screen for NPS, including broad-spectrum wastewater analysis to identify usage trends in the community and metabolomic-based approaches to examine the effects of drugs of abuse on endogenous compounds. In this paper, the novel applications of HRMS techniques to the analysis of NPS is reviewed. In particular, the development of innovative data analysis and interpretation approaches is discussed, including the application of machine learning and molecular networking to toxicological analyses.

Metabolomics-driven determination of targets for salicylic acid and ibuprofen in positive electrospray ionization using LC-HRMS

Due to the large number of basic therapeutic and illicit drugs, systematic toxicological analysis has widely been performed with liquid chromatography coupled to mass spectrometry using positive electrospray ionization. However, there exists a smaller number of drugs, typically acidic drugs, which require the use of negative electrospray ionization either via a separate injection or polarity switching. Here, targets relating to salicylic acid and ibuprofen in positive electrospray ionization were determined through a metabolomics-driven retrospective investigation of forensic casework. Samples were previously screened using liquid chromatography coupled with high-resolution mass spectrometry with quantification of target analytes performed using liquid chromatography with tandem mass spectrometry. Of the 1717 whole-blood samples submitted between 2014 and 2019, 48 were positive for salicylic acid (1.1-1400 mg/kg) and 78 for ibuprofen (1-46 mg/kg). Based on the retrospective analysis, 19 and 90 targets were identified for salicylic acid and ibuprofen, respectively. For targets of salicylic acid, the protonated adduct of salicyluric acid ([M+H]⁺ , m/z 196.0605) was present in 89.6% (n = 32) of the salicylic acid positive cases while the [M+HCOOH+CH₃ CN+Ca-H]⁺ adduct (m/z 264.0179) of salicylic acid was present in all positive samples with concentrations above 66 mg/kg salicylic acid. Similarly, the [M + 2Na - H]⁺ adduct (m/z 251.1018) of ibuprofen was present in 98.7% (n = 77) of positive cases and was present in all samples with concentrations above 3 mg/kg ibuprofen.

The Application of Metabolomics in Forensic Science with Focus on Forensic Toxicology and Time-of-Death Estimation

Recently, the diagnostic methods used by scientists in forensic examinations have enormously expanded. Metabolomics provides an important contribution to analytical method development. The main purpose of this review was to investigate and summarize the most recent applications of metabolomics in forensic science. The primary research method was an extensive review of available international literature in PubMed. The keywords “forensic” and “metabolomics” were used as search criteria for the PubMed database scan. Most authors emphasized the analysis of different biological sample types using chromatography methods. The presented review is a summary of recently published implementations of metabolomics in forensic science and types of biological material used and techniques applied. Possible opportunities for valuable metabolomics’ applications are discussed to emphasize the essential necessities resulting in numerous nontargeted metabolomics’ assays.

The Future of Analytical and Interpretative Toxicology: Where are We Going and How Do We Get There?

(Forensic) toxicology has faced many challenges, both analytically and interpretatively, especially in relation to an increase in potential drugs of interest. Analytical toxicology and its application to medicine and forensic science have progressed rapidly within the past centuries. Technological innovations have enabled detection of more substances with increasing sensitivity in a variety of matrices. Our understanding of the effects (both intended and unintended) have also increased along with determination and degree of toxicity. However, it is clear there is even more to understand and consider. The analytical focus has been on typical matrices such as blood and urine but other matrices could further increase our understanding, especially in postmortem (PM) situations. Within this context, the role of PM changes and potential redistribution of drugs requires further research and identification of markers of its occurrence and extent. Whilst instrumentation has improved, in the future, nanotechnology may play a role in selective and sensitive analysis as well as bioassays. Toxicologists often only have an advisory impact on pre-analytical and pre-interpretative considerations. The collection of appropriate samples at the right time in an appropriate way as well as obtaining sufficient circumstance background is paramount in ensuring an effective analytical strategy to provide useful results that can be interpreted within context. Nevertheless, key interpretative considerations such as pharmacogenomics and drug-drug interactions as well as determination of tolerance remain and in the future, analytical confirmation of an individual's metabolic profile may support a personalized medicine and judicial approach. This should be supported by the compilation and appropriate application of drug data pursuant to the situation. Specifically, in PM circumstances, data pertaining to where a drug was not/may have been/was contributory will be beneficial with associated pathological considerations. This article describes the challenges faced within toxicology and discusses progress to a future where they are being addressed.

Post-Mortem Metabolomics: A Novel Approach in Clinical Biomarker Discovery and a Potential Tool in Death Investigations

Metabolomics can be defined as the scientific field aiming at characterizing all low-weight molecules (so-called metabolites) in a biological system. At the time of death, the level and type of metabolites present will most likely reflect the events leading up to death.In this proof of concept study, we investigated the potential of post-mortem metabolomics by identifying post-mortem biomarkers, correlated these identified biomarkers with those reported in clinical metabolomics studies, and finally validated the models predictability of unknown autopsy cases. In this post-mortem metabolomics setting, ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry data from 404 post-mortem samples, including pneumonia cases and control cases, were processed using XCMS (R). Potential biomarkers were evaluated using principal component analysis and orthogonal partial least squares-discriminant analysis. Biomarkers were putatively annotated using an in-house database and the online databases METLIN and HMDB. The results showed that clear group separation was observed between pneumonia cases and control cases. The metabolites responsible for group separation belonged to a broad set of biological classes, such as amino acids, carnitines, lipids, nicotinamides, nucleotides, and steroids. Many of these metabolites have been reported as important in clinical manifestation of pneumonia. For the unknown autopsy cases, the sensitivity and specificity were 86 and 84%, respectively. This study successfully investigated the robustness and usability of post-mortem metabolomics in death investigations. The identified post-mortem biomarkers correlated well with biomarkers reported and identified through clinical research.

Metabolic phenotyping of opioid and psychostimulant addiction: A novel approach for biomarker discovery and biochemical understanding of the disorder

Despite the progress in characterising the pharmacological profile of drugs of abuse, their precise biochemical impact remains unclear. The metabolome reflects the multifaceted biochemical processes occurring within a biological system. This includes those encoded in the genome but also those arising from environmental/exogenous exposures and interactions between the two. Using metabolomics, the biochemical derangements associated with substance abuse can be determined as the individual transitions from recreational drug to chronic use (dependence). By understanding the biomolecular perturbations along this time course and how they vary across individuals, metabolomics can elucidate biochemical mechanisms of the addiction cycle (dependence/withdrawal/relapse) and predict prognosis (recovery/relapse). In this review, we summarise human and animal metabolomic studies in the field of opioid and psychostimulant addiction. We highlight the importance of metabolomics as a powerful approach for biomarker discovery and its potential to guide personalised pharmacotherapeutic strategies for addiction targeted towards the individual's metabolome.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Metabolic Alterations Associated with γ-Hydroxybutyric Acid and the Potential of Metabolites as Biomarkers of Its Exposure

γ-Hydroxybutyric acid (GHB) is an endogenous short chain fatty acid that acts as a neurotransmitter and neuromodulator in the mammalian brain. It has often been illegally abused or misused due to its strong anesthetic effect, particularly in drug-facilitated crimes worldwide. However, proving its ingestion is not straightforward because of the difficulty in distinguishing between endogenous and exogenous GHB, as well as its rapid metabolism. Metabolomics and metabolism studies have recently been used to identify potential biomarkers of GHB exposure. This mini-review provides an overview of GHB-associated metabolic alterations and explores the potential of metabolites for application as biomarkers of GHB exposure. For this, we discuss the biosynthesis and metabolism of GHB, analytical issues of GHB in biological samples, alterations in metabolic pathways, and changes in the levels of GHB conjugates in biological samples from animal and human studies. Metabolic alterations in organic acids, amino acids, and polyamines in urine enable discrimination between GHB-ingested animals or humans and controls. The potential of GHB conjugates has been investigated in a variety of clinical settings. Despite the recent growth in the application of metabolomics and metabolism studies associated with GHB exposure, it remains challenging to distinguish between endogenous and exogenous GHB. This review highlights the significance of further metabolomics and metabolism studies for the discovery of practical peripheral biomarkers of GHB exposure.

Targeted and non-targeted unexpected food contaminants analysis by LC/HRMS: Feasibility study on rice

A widely applicable analytical LC/HRMS method based on ion source optimization, data treatment optimization on rice matrix was developed. The effects of key parameters of ion source, and their interactions on ESI response were studied on HPLC-QTOF. Compared with center points, 40% and 20% increase of response factors in the positive and negative mode can be achieved by ion source optimization, respectively. Data processing strategies inspired from metabolomics and multi-targeted analysis were compared and developed using case and control rice samples. Highly automated workflow using XCMS achieved highest mass accuracy, highest detection rate of 96% for 5 μg/kg in a non-targeted way. A clear distinction between the control and contaminated samples by PCA and PLS-DA was also achieved by this workflow using XCMS, even for the concentration of 5 μg/kg.

Comparative Untargeted Metabolomics Analysis of the Psychostimulants 3,4-Methylenedioxy-Methamphetamine (MDMA), Amphetamine, and the Novel Psychoactive Substance Mephedrone after Controlled Drug Administration to Humans

Psychoactive stimulants are a popular drug class which are used recreationally. Over the last decade, large numbers of new psychoactive substances (NPS) have entered the drug market and these pose a worldwide problem to human health. Metabolomics approaches are useful tools for simultaneous detection of endogenous metabolites affected by drug use. They allow identification of pathways or characteristic metabolites, which might support the understanding of pharmacological actions or act as indirect biomarkers of consumption behavior or analytical detectability. Herein, we performed a comparative metabolic profiling of three psychoactive stimulant drugs 3,4-methylenedioxymethamphetamine (MDMA), amphetamine and the NPS mephedrone by liquid chromatography-high resolution mass spectrometry (LC-HRMS) in order to identify common pathways or compounds. Plasma samples were obtained from controlled administration studies to humans. Various metabolites were identified as increased or decreased based on drug intake, mainly belonging to energy metabolism, steroid biosynthesis and amino acids. Linoleic acid and pregnenolone-sulfate changed similarly in response to intake of all drugs. Overall, mephedrone produced a profile more similar to that of amphetamine than MDMA in terms of affected energy metabolism. These data can provide the basis for further in-depth targeted metabolome studies on pharmacological actions and search for biomarkers of drug use.

Integrated Non-targeted and Targeted Metabolomics Uncovers Dynamic Metabolic Effects during Short-Term Abstinence in Methamphetamine Self-Administering Rats

Persistent neurochemical disturbances by repeating drug reward and withdrawal lead to addiction. Particularly, drug withdrawal, usually starting within hours of the last dose, is considered as a critical step in the transition to addiction and a treatment clue. The aim of this study was to uncover metabolic effects associated with methamphetamine (MA) short-term abstinence using both non-targeted and targeted metabolomics. Metabolic alterations were investigated in rat plasma collected immediately after 16 days of MA self-administration and after 12 and 24 h of abstinence. Principal component analysis revealed that the highest level of separation occurred between the 24 h and saline (control) groups based on the significantly changed ion features, 257/320/333 and 331/409/388, in the SA/12 h/24 h groups in positive and negative modes of UPLC-QTOF-ESI-MS, respectively. Targeted metabolomics revealed dynamic changes in the biosynthesis/metabolism of amino acids, including the phenylalanine, tyrosine, and tryptophan biosynthesis and the valine, leucine, and isoleucine biosynthesis. Integrating non-targeted and targeted metabolomics data uncovered rapid and distinct changes in the metabolic pathways involved in energy metabolism, the nervous system, and membrane lipid metabolism. These findings provide essential knowledge of the dynamic metabolic effects associated with short-term MA abstinence and may help identify early warning signs of MA dependence.

Metabolomic Strategies in Biomarker Research-New Approach for Indirect Identification of Drug Consumption and Sample Manipulation in Clinical and Forensic Toxicology?

Drug of abuse (DOA) consumption is a growing problem worldwide, particularly with increasing numbers of new psychoactive substances (NPS) entering the drug market. Generally, little information on their adverse effects and toxicity are available. The direct detection and identification of NPS is an analytical challenge due to their ephemerality on the drug scene. An approach that does not directly focus on the structural detection of an analyte or its metabolites, would be beneficial for this complex analytical scenario and the development of alternative screening methods could help to provide fast response on suspected NPS consumption. A metabolomics approach might represent such an alternative strategy for the identification of biomarkers for different questions in DOA testing. Metabolomics is the monitoring of changes in small (endogenous) molecules (<1,000 Da) in response to a certain stimulus, e.g., DOA consumption. For this review, a literature search targeting "metabolomics" and different DOAs or NPS was conducted. Thereby, different applications of metabolomic strategies in biomarker research for DOA identification were identified: (a) as an additional tool for metabolism studies bearing the major advantage that particularly a priori unknown or unexpected metabolites can be identified; and (b) for identification of endogenous biomarker or metabolite patterns, e.g., for synthetic cannabinoids or also to indirectly detect urine manipulation attempts by chemical adulteration or replacement with artificial urine samples. The majority of the currently available literature in that field, however, deals with metabolomic studies for DOAs to better assess their acute or chronic effects or to find biomarkers for drug addiction and tolerance. Certain changes in endogenous compounds are detected for all studied DOAs, but often similar compounds/pathways are influenced. When evaluating these studies with regard to possible biomarkers for drug consumption, the observed changes appear, albeit statistically significant, too small to reliably work as biomarker for drug consumption. Further, different drugs were shown to affect the same pathways. In conclusion, metabolomic approaches possess potential for detection of biomarkers indicating drug consumption. More studies, including more sensitive targeted analyses, multi-variant statistical models or deep-learning approaches are needed to fully explore the potential of omics science in DOA testing.

Analytical considerations for (un)-targeted metabolomic studies with special focus on forensic applications

Over the past few years, the interest in metabolomics has increased in various fields including forensic toxicology. Forensic analysis typically requires a high degree of accuracy, which is often a problem in metabolomics applications. We aimed for a systematic evaluation of different analytical considerations of a metabolomics workflow allowing a targeted approach within an untargeted setup. Samples with 69 metabolites from different chemical classes were qualitatively and quantitatively analyzed on a high resolution quadrupole time of flight mass spectrometer coupled to liquid chromatography (UHPLC-QTOF). Three issues were addressed: (a) Two different approaches on "blind matrix" a simulated body fluid (SBF) and plasma-filtrate, were tested for calibration samples; (b) comparison of two different HPLC columns, reverse-phase (RP) and hydrophilic interaction chromatography (HILIC); and (c) comparison of three different acquisition modes (TOF-MS, information dependent data acquisition (IDA), and sequential window acquisition of all theoretical fragment-ion spectra (SWATH). Samples were measured repeatedly for method comparison based on sensitivity, accuracy, precision, and detection robustness. The blind matrices showed similar accuracy for most analytes, while SBF provided an easier preparation with satisfying results. To cover a wide part of the human metabolome, a combination of RP and HILIC showed the best results. The different scan modes performed equally regarding metabolite quantification while TOF-MS was more sensitive but lacked MS/MS spectra generation. IDA and SWATH files were aligned to various databases where IDA showed good MS/MS spectra matches. SWATH seemed to be beneficial in detection rate but was incompatible with many important software tools in metabolomics.

GC-MS metabolomics reveals disturbed metabolic pathways in primary mouse hepatocytes exposed to subtoxic levels of 3,4-methylenedioxymethamphetamine (MDMA)

3,4-Methylenedioxymethamphetamine (MDMA, ecstasy) is a well-known hepatotoxic drug. Although its toxicity has been thoroughly studied at high concentrations, there is still insufficient knowledge on possible alterations of cell function at subtoxic concentrations, which are in fact more representative concentrations of intoxication scenarios. In this study, a gas chromatography-mass spectrometry (GC-MS) metabolomics approach was used to investigate the metabolic changes in primary mouse hepatocytes (PMH) exposed to two subtoxic concentrations of MDMA (LC₀₁ and LC₁₀) for 24 h. Metabolomic profiling of both intracellular metabolites and volatile metabolites in the extracellular medium of PMH was performed. Multivariate analysis showed that the metabolic pattern of cells exposed to MDMA discriminates from the controls in a concentration-dependent manner. Exposure to LC₁₀ MDMA induces a significant increase in some intracellular metabolites, including oleic acid and palmitic acid, and a decrease in glutamate, aspartate, 5-oxoproline, fumarate, malate, phosphoric acid, α-ketoglutarate and citrate. Extracellular metabolites such as acetophenone, formaldehyde, pivalic acid, glyoxal and 2-butanone were found significantly increased after exposure to MDMA, compared to controls, whereas 4-methylheptane, 2,4-dimethyl-1-heptene, nonanal, among others, were found significantly decreased. The panel of discriminatory metabolites is mainly involved in tricarboxylic acid (TCA) cycle, fatty acid metabolism, glutamate metabolism, antioxidant defenses and possibly changes in the liver enzyme machinery. Overall, these results highlight the potential of the intra- and extracellular metabolome to study alterations triggered by subtoxic concentrations of MDMA in hepatic cell functions, which represents a more realistic appraisal of early toxicity events posed by exposure to this drug. In addition, these results also revealed some metabolites that may be used as potential biomarkers indicative of early events in the hepatotoxicity induced by MDMA.

Development of surface-enhanced Raman spectroscopy application for determination of illicit drugs: Towards a practical sensor

Surface-enhanced Raman spectroscopy (SERS) has been widely applied to identify or detect illicit drugs, because of the ability for highly specific molecular fingerprint and independence of aqueous solutions impact. We summarize the progress in determination of illicit drugs using SERS, including trace illicit drugs, suspicious objects and drugs or their metabolites in real biological system (urine, saliva and so on). Even though SERS detection of illicit drugs in real samples still remains a huge challenge because of the complex unknown environment, the efficient sample separation and the improved hand-held Raman analyzer will provide the possibility to make SERS a practically analytical technique. Moreover, we put forward a prospective overview for future perspectives of SERS as a practical sensor for illicit drugs determination. Perhaps the review is not exhaustive, we expect to help researchers to understand the evolution and challenges in this field and further interest in promoting Raman and SERS as a practical analyzer for convenient and automated illicit drugs identification.

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.

Using Metabolomics to Investigate Biomarkers of Drug Addiction

Drug addiction has been associated with an increased risk for cancer, psychological complications, heart, liver, and lung disease, as well as infection. While genes have been identified that can mark individuals at risk for substance abuse, the initiation step of addiction is attributed to persistent metabolic disruptions occurring following the first instance of narcotic drug use. Advances in analytical technologies can enable the detection of thousands of signals in body fluids and excreta that can be used to define biochemical profiles of addiction. Today, these approaches hold promise for determining how exposure to drugs, in the absence or presence of other environmentally relevant factors, can impact human metabolism. We posit that these can lead to candidate biomarkers of drug dependence, treatment, withdrawal, or relapse.

Estimation of early postmortem interval in rats by GC-MS-based metabolomics

Accurately predicting the early postmortem interval (PMI) is of great significance in forensic practice. This study aimed to establish a novel method for estimating the early PMI by analyzing endogenous substances in the cardiac blood of male and female rats and compare different model for estimating early PMI using these data. Adult Sprague-Dawley (SD) rats (50% male) were sacrificed by suffocation. Then, cardiac blood was collected at various time intervals (0, 3, 6, 12, 24, 48, and 72 h) after death, and the collected samples were analyzed by gas chromatography-tandem mass spectrometry (GC-MS). The data were analyzed by multivariate statistical analysis. An orthogonal signal correction-partial least squares (OSC-PLS) regression model was constructed with whole endogenous metabolites to validate the PMI. The OSC-PLS regression model successfully predicted the PMI of the forecast set and no significant differences was observed between male and female rats. This is the first study to establish an OSC-PLS regression model for predicting PMI with the metabolome, which provides a new technical method and platform for estimating PMI through metabolomics.

NMR-based metabolomics for the environmental assessment of Kaohsiung Harbor sediments exemplified by a marine amphipod (Hyalella azteca)

Inflow of wastewater from upstream causes a large flux of pollutants to enter Kaohsiung Harbor in Taiwan daily. To reveal the ecological risk posed by Kaohsiung Harbor sediments, an ecological metabolomic approach was employed to investigate environmental factors pertinent to the physiological regulation of the marine amphipod Hyalella azteca. The amphipods were exposed to sediments collected from different stream inlets of the Love River (LR), Canon River (CR), Jen-Gen River (JR), and Salt River (SR). Harbor entrance 1 (E1) was selected as a reference site. After 10-day exposure, metabolomic analysis of the Hyalella azteca revealed differences between two groups: {E1, LR, CR} and {JR, SR}. The metabolic pathways identified in the two groups of amphipods were significantly different. The results demonstrated that NMR-based metabolomics can be effectively used to characterize metabolic response related to sediment from polluted areas.

Targeted toxicological screening for acidic, neutral and basic substances in postmortem and antemortem whole blood using simple protein precipitation and UPLC-HR-TOF-MS

A broad targeted screening method based on broadband collision-induced dissociation (bbCID) ultra-performance liquid chromatography high-resolution time-of-flight mass spectrometry (UPLC-HR-TOF-MS) was developed and evaluated for toxicological screening of whole blood samples. The acidic, neutral and basic substances covered by the method were identified in postmortem and antemortem whole blood samples from forensic autopsy cases, clinical forensic cases and driving under the influence of drugs (DUID) cases by a reverse target database search. The screening method covered 467 substances. Validation was performed on spiked whole blood samples and authentic postmortem and antemortem whole blood samples. For most of the basic drugs, the established cut-off limits were very low, ranging from 0.25ng/g to 50ng/g. The established cut-off limits for most neutral and acidic drugs, were in the range from 50ng/g to 500ng/g. Sample preparation was performed using simple protein precipitation of 300μL of whole blood with acetonitrile and methanol. Ten microliters of the reconstituted extract were injected and separated within a 13.5min UPLC gradient reverse-phase run. Positive electrospray ionization (ESI) was used to generate the ions in the m/z range of 50-1000. Fragment ions were generated by bbCID. Identification was based on retention time, accurate mass, fragment ion(s) and isotopic pattern. A very sensitive broad toxicological screening method using positive electrospray ionization UPLC-HR-TOF-MS was achieved in one injection. This method covered basic substances, substances traditionally analyzed in negative ESI (e.g., salicylic acid), small highly polar substances such as beta- and gamma-hydroxybutyric acid (BHB and GHB, respectively) and highly non-polar substances such as amiodarone. The new method was shown to combine high sensitivity with a very broad scope that has not previously been reported in toxicological whole blood screening when using only one injection.