Metabolites In Blood Samples Research Articles

Characterizing the Metabolism of Tire Rubber-Derived p-Phenylenediamine Quinones to Identify Potential Exposure Biomarkers in Humans.

There is growing evidence of the frequent detection of tire rubber-derived contaminants p-phenylenediamine-derived quinones (PPD-Qs) (e.g., highly toxic N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6PPD-Q)) in the environment and biota and the adverse impact on organisms. Hence, a better understanding of their biotransformation/metabolism in humans is essential. However, relevant data are lacking owing to recent discoveries. Herein, the biotransformation patterns of 6PPD-Q and other five commonly detected PPD-Qs were characterized via combined in vitro assay and maternal cord blood screening monitoring. Rapid metabolism was found for each PPD-Q incubated with human liver S9 fraction and microsomes, resulting in the formation of abundant phase I and phase II metabolites. The subsequent screening for potential PPD-Q metabolites in blood samples showed the presence of suspect metabolites. Three detected metabolites were confirmed by matching the mass spectra and retention times of in vitro metabolites. N-Dealkylated, carboxy, carbonyl, and reductive metabolites and glucose, cysteine, and methionine conjugates were observed for the first time. The semiquantitative concentrations of metabolites were higher than those of the parent PPD-Qs, and several metabolites such as carboxy products were proposed as candidate biomarkers of PPD-Q exposure to humans. 6PPD-Q and N,N'-diphenyl-p-phenylenediamine quinone were detected in maternal and/or cord whole blood samples for the first time. This study holds great importance in elucidating the potential risks and health effects of PPD-Qs.

Abstract 3682: Pre-surgical blood metabolites associated with ovarian cancer prognosis

Abstract Background: Ovarian cancer has a poor prognosis with a 5-year survival less than 50%, resulting > 14,000 deaths in the US annually and > 150,000 globally. Identifying prognostic biomarkers at time of diagnosis and elucidating the biological dysregulation among those who are more likely to progress after first-line treatment could inform personalized treatment strategies. Thus, we evaluated metabolites and metabolomic profiles in pretreatment blood associated with survival in women with high-grade serous ovarian cancer, the most common and most deadly histologic subtype. Method: We examined plasma metabolites in blood samples collected prior to ovarian cancer treatment in 80 high-grade serous ovarian cancer patients who participated in the PreOperative Pelvic Mass Study, a clinic-based study enrolling women undergoing surgery for a pelvic mass. Liquid chromatography tandem mass spectrometry was used to measure 524 known metabolites. We excluded metabolites with coefficient of variation ≥ 25% (n = 104), then removed metabolites with missing in > 20% of the samples (n = 3). Metabolites missing in < 20% of the samples were imputed to be half the minimum value for that metabolite, resulting in 417 unduplicated metabolites. All metabolite values were transformed to probit scores to achieve normality. Cox proportional hazard models were used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) adjusting for age at diagnosis, body mass index (BMI), and stage. False discovery rate (FDR) was used for multiple testing correction. Metabolite set enrichment analysis (MSEA) was used to identify metabolite classes associated with prognosis. Results: Overall, none of the individual metabolites were significantly associated with survival after multiple testing correction (FDR > 0.05). However, 32 metabolites were associated with survival with p< 0.05, with 12 metabolites being associated with worse survival (HR range: 1.38 - 1.98) and 20 metabolites being associated with better survival (HR range: 0.54 - 0.73). MSEA revealed triglycerides (normalized enrichment score (NES) = 3.14), cholesteryl esters (NES = 2.43), and phosphatidylcholines (NES = 2.30) were positively associated with risk of death (FDR < 0.001). Steroids and steroid derivatives (NES = -1.93), sphingomyelins (NES = -2.45), and carnitines (NES = -2.27) were negatively associated with risk of death (FDR < 0.001). Diglycerides (NES = 1.96), lysophosphatidylethanolamines (NES = 1.72), and phosphatidylcholine plasmalogens (NES = 1.58) were positively associated and phosphatidylethanolamines (NES = -1.93) was negatively associated with risk of death with FDR < 0.05. Discussion: In this study, we explored plasma metabolites associated with mortality in high-grade serous ovarian cancer patients and observed multiple classes of lipid-related metabolites being associated with worse prognosis. Citation Format: Nan Lin, Oana A. Zeleznik, Julian Avila-Pacheco, Clary B. Clish, Allison F. Vitonis, Daniel W. Cramer, Kathryn L. Terry, Naoko Sasamoto. Pre-surgical blood metabolites associated with ovarian cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3682.

LC-MS/MS-MS3 for the Determination and Quantification of Δ9-Tetrahydrocannabinol and Metabolites in Blood Samples.

Due to the high prevalence of cannabinoids in forensic toxicology analysis, it is crucial to have an efficient method that allows the use of a small sample amount and that requires a minimal sample preparation, for the determination and quantification of low concentrations. A simple, highly selective and high throughput liquid chromatography tandem mass spectrometry methodology (LC-MS/MS-MS3) was developed for the determination and quantification of ∆9-tetrahydrocannabinol (THC), 11-hydroxy-∆9- tetrahydrocannabinol (THC-OH) and 11-nor-9-carboxy-∆9-tetrahydrocannabinol (THC-COOH), in blood samples. Chromatographic analysis of THC, THC-OH, and THC-COOH and their deuterated internal standards was preceded by protein precipitation (PPT) of 0.1 mL of blood samples with acetonitrile. Chromatographic separation was achieved by use of an Acquity UPLC® HHS T3 (100 mm x 2.1mm i.d., 1.8 μm) reversed-phase column, using a gradient elution of 2 mM aqueous ammonium formate, 0.1% formic acid, and methanol at a flow rate of 0.4 mL/min, with a run time of 10 minutes. For the MS/MS-MS3 analysis, a SCIEX QTRAP® 6500+ triple quadrupole linear ion trap mass spectrometer was used via electrospray ionization (ESI), operated in multiple reaction monitoring (MRM) and linear ion trap mode (MS3). The method was validated in accordance with internationally accepted criteria and guidelines, and proved to be selective and linear between 0.5-100 ng/mL (r2>0.995). The lower limits of quantification (LLOQ) corresponded to the lowest concentrations used for the calibration curves. The coefficients of variation obtained for accuracy and precision were <15%. The mean recoveries were between 88.0-117.2%, for the studied concentration levels (1 ng/mL, 5 ng/mL and 50 ng/mL). No significant interfering compounds, matrix effects or carryover were observed. The validated method provides a sensitive, efficient and robust procedure for the quantification of cannabinoids in blood, using LC-MS/MS-MS3 and a sample volume of 0.1 mL. This work is also a proof of concept for using LC-MS3 technique to determine drugs in biological samples.

Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients.

Breast cancer is the most diagnosed tumor and the leading cause of cancer death in women worldwide. Metabolomics allows the quantification of the entire set of metabolites in blood samples, making it possible to study differential metabolomics patterns related to neoadjuvant treatment in the breast cancer neoadjuvant setting. Characterizing metabolic differences in breast cancer blood samples according to their response to neoadjuvant treatment. One hundred and three plasma samples of breast cancer patients, before receiving neoadjuvant treatment, were analyzed through UPLC-MS/MS metabolomics. Then, metabolomics data were analyzed using probabilistic graphical models and biostatistics methods. Metabolomics data allowed the identification of differences between groups according to response to neoadjuvant treatment. These differences were specific to each breast cancer subtype. Patients with HER2+ tumors showed differences in metabolites related to amino acids and carbohydrates pathways between the two pathological response groups. However, patients with triple-negative tumors showed differences in metabolites related to the long-chain fatty acids pathway. Patients with Luminal B tumors showed differences in metabolites related to acylcarnitine pathways. It is possible to identify differential metabolomics patterns between complete and partial responses to neoadjuvant therapy, being this metabolomic profile specific for each breast cancer subtype.

A Comprehensive Investigation of the Potential Role of Lipoproteins and Metabolite Profile as Biomarkers of Alzheimer's Disease Compared to the Known CSF Biomarkers.

While cerebrospinal fluid (CSF) core biomarkers have been considered diagnostic biomarkers for a long time, special attention has been recently dedicated to lipoproteins and metabolites that could be potentially associated with Alzheimer's disease (AD) neurodegeneration. Herein, we aimed to investigate the relationship between the levels of CSF core biomarkers including Aβ-42, TAU, and P-TAU and plasma lipoproteins and metabolites of patients with AD from the baseline cohort of the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Using the ADNI database, fourteen subclasses of lipoproteins as well as a number of lipids and fatty acids and low-molecular metabolites including amino acids, ketone bodies, and glycolysis-related metabolites in blood samples were measured as potential noninvasive markers, and their association with the CSF core biomarkers was statistically investigated controlling for age and gender. A total number of 251 AD subjects were included, among whom 71 subjects were negative for the Apo-E ε4 allele and 150 were positive. There was no significant difference between the two groups regarding cognitive assessments, CSF core biomarkers, and lipoproteins and metabolites except the level of Aβ-42 (p < 0.001) and phenylalanine (p = 0.049), which were higher in the negative group. CSF TAU and P-TAU were significantly correlated with medium and small HDL in the negative group, and with extremely large VLDL in the positive group. Our results also indicated significant correlations of metabolites including unsaturated fatty acids, glycerol, and leucine with CSF core biomarkers. Based on our findings, a number of lipoproteins and metabolites were associated with CSF core biomarkers of AD. These correlations showed some differences in Apo-E ε4 positive and negative groups, which reminds the role of Apo-E gene status in the pathophysiology of AD development. However, further research is warranted to explore the exact association of lipoproteins and other metabolites with AD core biomarkers and pathology.

Detection of Carbamazepine and Its Metabolites in Blood Samples by LC-MS/MS.

To establish a method for the detection of carbamazepine and its metabolites 10,11-dihydro-10,11-epoxycarbamazepine and 10,11-dihydro-10-hydroxycarbamazepine in blood samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The blood samples were treated with 1-butyl-3-methylimidazolium hexafluorophosphate as an extraction solvent. The samples were extracted by ultrasound-assisted extraction and separated by ZORBAX Eclipse Plus C18, 95Å column. The mobile phase A aqueous solution containing 0.1% formic acid and 10 mmol/L ammonium acetate, and mobile phase B mixed organic solvent containing acetonitrile/methanol (Vacetonitrile∶Vmethanol=2∶3) were used for gradient elution at the flow rate of 1.00 mL/min. An electrospray ion source in positive mode was used for detection in the multiple reaction monitoring. The linearities of carbamazepine and its metabolites 10,11-dihydro-10,11-epoxycarbamazepine and 10,11-dihydro-10-hydroxycarbamazepine in blood samples were good within the corresponding range, with correlation coefficients (r) greater than 0.995 6. The limits of detection were 3.00, 0.40 and 1.30 ng/mL, respectively. The limit of quantitation were 8.00, 1.00 and 5.00 ng/mL, respectively. The extraction recoveries ranged from 76.00% to 106.44%. The relative standard deviations of the intra-day and inter-day precisions were less than 16%. Carbamazepine and its main metabolite 10,11-dihydro-10,11-epoxycarbamazepine were detected in blood samples of death cases with a mass concentration of 2.71 μg/mL and 252.14 ng/mL, respectively. This method has high sensitivity and good selectivity, which is suitable for the detection of carbamazepine and its metabolites in blood samples, and can be used for carbamazepine-related forensic identifications.

Optimization of a GC-MS method for the profiling of microbiota-dependent metabolites in blood samples: An application to type 2 diabetes and prediabetes.

Changes in serum or plasma metabolome may reflect gut microbiota dysbiosis, which is also known to occur in patients with prediabetes and type 2 diabetes (T2DM). Thus, developing a robust method for the analysis of microbiota-dependent metabolites (MDMs) is an important issue. Gas chromatography with mass spectrometry (GC–MS) is a powerful approach enabling detection of a wide range of MDMs in biofluid samples with good repeatability and reproducibility, but requires selection of a suitable solvents and conditions. For this reason, we conducted for the first time the study in which, we demonstrated an optimisation of samples preparation steps for the measurement of 75 MDMs in two matrices. Different solvents or mixtures of solvents for MDMs extraction, various concentrations and volumes of derivatizing reagents as well as temperature programs at methoxymation and silylation step, were tested. The stability, repeatability and reproducibility of the 75 MDMs measurement were assessed by determining the relative standard deviation (RSD). Finally, we used the developed method to analyse serum samples from 18 prediabetic (PreDiab group) and 24 T2DM patients (T2DM group) from our 1000PLUS cohort. The study groups were homogeneous and did not differ in age and body mass index. To select statistically significant metabolites, T2DM vs. PreDiab comparison was performed using multivariate statistics. Our experiment revealed changes in 18 MDMs belonging to different classes of compounds, and seven of them, based on the SVM classification model, were selected as a panel of potential biomarkers, able to distinguish between patients with T2DM and prediabetes.

Validation of a simple and quick method for determination of psychoactive substances, drugs and their metabolites from human blood by LC-MS/MS

The development of the black market, and thus the increase in the number of available psychoactive substances, forces laboratories to take measures to prevent poisoning and deaths caused by the use of, inter alia, new psychoactive substances (NPS). It is important to selectively determine psychoactive substances and their metabolites in blood samples in the shortest possible time, which will allow medical services to act timely. Bearing in mind the above, the aim of our study was to develop an analytical method that would enable the unequivocal identification of over 500 psychoactive substances in blood samples with one analysis. The techniques selected for this purpose were liquid–liquid extraction (LLE) and liquid chromatography coupled with mass spectrometry (LC-MS/MS). Acetonitrile with ammonium formate and formic acid was used for the extraction. The best column was found to be the Kinetex C18 column (Phenomenex, 3.0 × 100 mm; 2.6 µm). MRM pair monitoring mode was used (two pairs for each analyte). 522 psychoactive substances and their metabolites have been validated, and only 2 out of 522 failed to meet the validation criteria recommended by SWGTOX (CV: ± 20 % and BIAS ± 20 %). The developed method enables the quantitative analysis of 520 psychoactive substances during a 30-minute run. Limits of quantification (LOQ) range from 1 to 200 ng/mL. The developed method was introduced into the routine toxicological analysis of blood samples. It also offers opportunities for further development in line with the needs of toxicology.

LC-MS/MS-MS3 for determination and quantification of Δ9-tetrahydrocannabinol and metabolites in blood samples

Due to the high prevalence of cannabinoids in forensic toxicology, it is crucial to have an efficient method that allows the use of a small sample amount and that requires a minimal sample preparation, for the determination and quantification of low concentrations. A simple, highly selective and high throughput liquid chromatography tandem mass spectrometry method (LC-MS/MS-MS3) was developed for the determination and quantification of Δ9-tetrahydrocannabinol (THC), 11-hydroxy-Δ9-THC (THC-OH) and 11-nor-Δ9-THC-9-carboxylic acid (THC-COOH) in blood samples. Chromatographic analysis was preceded by a protein precipitation of 0.1 mL of blood samples with acetonitrile, then THC, THC-OH, THC-COOH and deuterated internal standards were separated on an Acquity UPLC® HSS T3 (100 mm × 2.1 mm i.d., 1.8 mm) reversed-phase column using a gradient elution with 2 mM aqueous ammonium formate (0.1% formic acid) and methanol, at a flow rate of 0.4 mL/min, and with a run time of 10 min. For MS/MS-MS3 analysis, a SCIEX QTRAP® 6500+ linear ion trap triple quadrupole mass spectrometer was used via electrospray ionization (ESI), operated in multiple reaction mode (MRM) and linear ion trap mode (MS3). The method was validated in accordance with international accepted criteria and guidelines. The method was selective and linear between 0.5–100 ng/mL (r2 > 0.995). The lower limits of quantification (LLOQ) corresponded to the lowest concentrations used for the calibration curves. The coefficients of variation obtained for accuracy and precision were less than 15%. The mean recoveries were between 88.0–101.4% for the studied concentration levels (1 ng/mL, 5 ng/mL and 50 ng/mL). No significant interfering compounds, matrix effects or carryover were observed. The validated method provides a sensitive, efficient and robust procedure for the quantitation of cannabinoids in blood using LC–MS/MS-MS3 and a sample volume of 0.1 mL. This work is also a proof of concept for using LC-MS3 technique to determine drugs in biological samples.

Changing of ATP and Its Metabolites in Blood Samples for Post Mortem Interval: In Vitro Study

Background: Postmortem interval (PMI) is an important in forensic practice. Many studies in blood and tissue ofanimals have revealed correlation between adenosine triphosphate (ATP) level and PMI. In this study aimed toexplore the correlation between human blood ATP and its metabolites level and PMI in vitro model.Methods: Ten milliliter of venous blood samples were collected form four healthy men and contained in EDTAtube. One milliliter of the blood sample was divided at 0, 1, 2, 4, 8, 12 and 24 h, respectively. The blood sampleswere extracted and measured ATP, adenosine diphosphate (ADP) and adenosine monophosphate (AMP) level byHigh performance liquid chromatography- diode array. Energy charge value was calculated to predict charge ofATP metabolites.Results: The blood ATP, ADP and AMP levels increased in the first hour. The blood ATP, ADP and AMP levelsdid not obviously change before 12 hour. The blood ATP level trended to decrease but the blood ADP and AMPlevels trended to increase after 24 hour. Energy Charge was not change in first 12 hour but trended to decreaseafter 24 hour.Conclusion: The blood ATP level and its metabolites changed after 12 hour and apply for the PMI investigation.

Oleamide as analyte protectant in GC analysis of THC and its metabolites in blood

Methods for the analysis of cannabinoids in bio-matrices are continually being developed, to achieve a proper sensitivity required for their detection and accuracy in their quantification. The presented paper shows that the analytical sensitivity of GC–MS to THC and its metabolites in blood samples can be significantly increase by oleamide (OLA) addition to the examined sample, which evokes the matrix effect of transient character. The magnitude of signal increment resulting from oleamide presence in the examined sample is the greatest for THC metabolites and depends on oleamide concentration in the examined sample. The use of transient matrix effect to increase the sensitivity of the analysis can be applied not only in QuEChERS procedure, which is applied in the described experiments, but also in other blood sample preparation methods. Evoking the transient matrix effect by means of OLA in the experimental analytical quantitation of THC and its metabolites in blood allowed to lower limit of detection (LOD) approximately by 20.5%, 87.6% and 90.1% in the case of THC, THC-OH and THC-COOH, respectively.

Matching Drug Metabolites from Non-Targeted Metabolomics to Self-Reported Medication in the Qatar Biobank Study.

Modern metabolomics platforms are able to identify many drug-related metabolites in blood samples. Applied to population-based biobank studies, the detection of drug metabolites can then be used as a proxy for medication use or serve as a validation tool for questionnaire-based health assessments. However, it is not clear how well detection of drug metabolites in blood samples matches information on self-reported medication provided by study participants. Here, we curate free-text responses to a drug-usage questionnaire from 6000 participants of the Qatar Biobank (QBB) using standardized WHO Anatomical Therapeutic Chemical (ATC) Classification System codes and compare the occurrence of these ATC terms to the detection of drug-related metabolites in matching blood plasma samples from 2807 QBB participants for which we collected non-targeted metabolomics data. We found that the detection of 22 drug-related metabolites significantly associated with the self-reported use of the corresponding medication. Good agreement of self-reported medication with non-targeted metabolomics was observed, with self-reported drugs and their metabolites being detected in a same blood sample in 79.4% of the cases. On the other hand, only 29.5% of detected drug metabolites matched to self-reported medication. Possible explanations for differences include under-reporting of over-the-counter medications from the study participants, such as paracetamol, misannotation of low abundance metabolites, such as metformin, and inability of the current methods to detect them. Taken together, our study provides a broad real-world view of what to expect from large non-targeted metabolomics measurements in population-based biobank studies and indicates areas where further improvements can be made.

Occurrence of Zearalenone and Its Metabolites in the Blood of High-Yielding Dairy Cows at Selected Collection Sites in Various Disease States.

Zearalenone (ZEN) and its metabolites, alpha-zearalenol (α-ZEL) and beta-zearalenol (β-ZEL), are ubiquitous in plant materials used as feed components in dairy cattle diets. The aim of this study was to confirm the occurrence of ZEN and its selected metabolites in blood samples collected from different sites in the hepatic portal system (posthepatic–external jugular vein EJV; prehepatic–abdominal subcutaneous vein ASV and median caudal vein MCV) of dairy cows diagnosed with mastitis, ovarian cysts and pyometra. The presence of mycotoxins in the blood plasma was determined with the use of combined separation methods involving immunoaffinity columns, a liquid chromatography system and a mass spectrometry system. The parent compound was detected in all samples collected from diseased cows, whereas α-ZEL and β-ZEL were not identified in any samples, or their concentrations were below the limit of detection (LOD). Zearalenone levels were highest in cows with pyometra, where the percentage share of average ZEN concentrations reached 44%. Blood sampling sites were arranged in the following ascending order based on ZEN concentrations: EJV (10.53 pg/mL, 44.07% of the samples collected from this site), ASV (14.20 pg/mL, 49.59% of the samples) and MCV (26.67 pg/mL, 67.35% of the samples). The results of the study indicate that blood samples for toxicological analyses should be collected from the MCV (prehepatic vessel) of clinically healthy cows and/or cows with subclinical ZEN mycotoxicosis. This sampling site increases the probability of correct diagnosis of subclinical ZEN mycotoxicosis.

Successful Multiorgan Donation From a Brain-dead Donor Following Liquid Nicotine Voluntary Intoxication: A Case Report.

Successful Multiorgan Donation From a Brain-dead Donor Following Liquid Nicotine Voluntary Intoxication: A Case Report.

Profiles of neonicotinoid insecticides and characteristic metabolites in paired urine and blood samples: Partitioning between urine and blood and implications for human exposure

Neonicotinoid insecticides (NEOs) are widely used for pest control worldwide. However, only a few studies have analyzed NEOs and their metabolites in blood samples, and no study has measured the concentrations of NEOs and their metabolites in paired urine and blood samples. In this study, six NEOs and three characteristic metabolites were detected in 196 paired urine and blood samples collected from young adults from China. The NEOs and their metabolites were widely detected in paired urine (67%–91%) and blood (64%–97%) samples, and the median levels ranged within 0.01–1.15 ng/mL in urine and 0.08–0.80 ng/mL in blood. Olefin-imidacloprid (Of-IMI) and 1-methyl-3-(tetrahydro-3-furylmethyl) urea (UF) were the most abundant target compounds in the urine (32.4%) and blood (26.4%) samples, respectively. Gender-related differences were observed in the concentrations of most NEOs and their metabolites in the urine and blood samples. The partitioning of target analytes between blood and urine (NEOs-B/NEOs-U ratios) was also calculated in this study. The B/U ratios of most NEOs and their metabolites were below 1, and positive correlations were observed between urine and blood in most levels of NEOs and their metabolites. This finding indicates that urinary levels are good predictors of human exposure to NEOs and their metabolites. The estimated daily intake (EDI) and the imidacloprid-equivalent (IMIeq) levels of NEOs and their metabolites in 196 young adults were also determined. The median EDI values (ng/kg bw/day) of ΣNEOs (sum of NEOs and their metabolites) and IMIeq in females (194.9 and 458.2) were slightly higher than (p > 0.05) those in males (157.1 and 439.7). This finding shows young adults are extensively exposed to NEOs and their metabolites. To our knowledge, this study is the first to report about NEOs and their metabolites in paired samples of urine and blood in China.

Is pain temporary and glory forever? Detection of tramadol using dried blood spot in cycling competitions.

Tramadol is a synthetic opioid drug used in the treatment of chronic and acute pain. An abnormal prevalence of its misuse in elite sport to overcome pain resulting from prolonged physical effort was recently reported. However, besides its antinociceptive effects, tramadol consumption is associated with negative effects such as numbness, confusion, and reduced alertness. This fact prompted the Union Cycliste Internationale to ban the use of tramadol in cycling competitions. Herein, we present the development of a dried blood spot (DBS) sample collection and preparation method followed by a liquid-chromatography mass spectrometry (LC-MS) analysis to rapidly determine the presence of tramadol and its two main metabolites in blood samples. The detection window of each analyte was evaluated and the analysis of performance on various MS platforms (HRMS and MS/MS) was assessed. Tramadol and its two main metabolites were detected up to 12 h after the intake of a single dose of 50 mg of tramadol in positive controls. In professional cycling competitions, 711 DBS samples collected from 361 different riders were analysed using the developed methodology, but all returned negative results (absence of parent and both metabolite compounds). In the context of professional cycling, we illustrate a valid method bringing together the easiness of collection and minimal sample preparation required by DBS, yet affording the performance standards of MS determination. The proposed method to detect tramadol and its metabolites was successfully implemented in cycling races with a probable strong deterrent effect.

A Metabolomics Approach to Screening for Autism Risk in the Children's Autism Metabolome Project.

Autism spectrum disorder (ASD) is biologically and behaviorally heterogeneous. Delayed diagnosis of ASD is common and problematic. The complexity of ASD and the low sensitivity of available screening tools are key factors in delayed diagnosis. Identification of biomarkers that reduce complexity through stratification into reliable subpopulations can assist in earlier diagnosis, provide insight into the biology of ASD, and potentially suggest targeted interventions. Quantitative metabolomic analysis was performed on plasma samples from 708 fasting children, aged 18 to 48 months, enrolled in the Children's Autism Metabolome Project (CAMP). The primary goal was to identify alterations in metabolism helpful in stratifying ASD subjects into subpopulations with shared metabolic phenotypes (i.e., metabotypes). Metabotypes associated with ASD were identified in a discovery set of 357 subjects. The reproducibility of the metabotypes was validated in an independent replication set of 351 CAMP subjects. Thirty‐four candidate metabotypes that differentiated subsets of ASD from typically developing participants were identified with sensitivity of at least 5% and specificity greater than 95%. The 34 metabotypes formed six metabolic clusters based on ratios of either lactate or pyruvate, succinate, glycine, ornithine, 4‐hydroxyproline, or α‐ketoglutarate with other metabolites. Optimization of a subset of new and previously defined metabotypes into a screening battery resulted in 53% sensitivity (95% confidence interval [CI], 48%–57%) and 91% specificity (95% CI, 86%–94%). Thus, our metabolomic screening tool detects more than 50% of the autistic participants in the CAMP study. Further development of this metabolomic screening approach may facilitate earlier referral and diagnosis of ASD and, ultimately, more targeted treatments.Lay SummaryAnalysis of a selected set of metabolites in blood samples from children with autism and typically developing children identified reproducible differences in the metabolism of about half of the children with autism. Testing for these differences in blood samples can be used to help screen children as young as 18 months for risk of autism that, in turn, can facilitate earlier diagnoses. In addition, differences may lead to biological insights that produce more precise treatment options. We are exploring other blood‐based molecules to determine if still a higher percentage of children with autism can be detected using this strategy. Autism Res 2020, 13: 1270–1285. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals LLC.

Evaluation of Synthetic Cannabinoid Metabolites in Human Blood in the Absence of Parent Compounds: A Stability Assessment.

Synthetic cannabinoids represent a chemically diverse class of novel psychoactive substances (NPS) responsible for large analytical and interpretative challenges for forensic toxicologists. Between 2016 and 2019, the three most prevalent synthetic cannabinoids in the United States were MMB-FUBINACA (FUB-AMB), 5F-MDMB-PINACA (5F-ADB) and 5F-MDMB-PICA, based on results from seized drug and toxicology testing. In 2018, accurate determination of synthetic cannabinoid positivity was brought into question as it was determined that the metabolites of these drug species were present in the absence of parent compounds in forensically relevant blood samples. During this study, the stability of MMB-FUBINACA, 5F-MDMB-PINACA and 5F-MDMB-PICA was evaluated, as well as the characterization of breakdown products. A liquid-liquid extraction method was assessed for recovery of basic parent compounds and acidic metabolites and deemed fit for use in this study. Analysis was performed by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) using a SCIEX TripleTOF® 5600+. All three synthetic cannabinoids were found to be unstable when stored in blood at either room temperature or refrigerated; all analytes were considerably more stable when stored in the freezer. All three synthetic cannabinoids degraded to their respective butanoic acid metabolites: MMB-FUBINACA 3-methylbutanoic acid, 5F-MDMB-PINACA 3,3-dimethylbutanoic acid and 5F-MDMB-PICA 3,3-dimethylbutanoic acid. All three of these metabolites were studied and determined to be stable in blood at all storage conditions. Considering these results, our laboratory continued testing for synthetic cannabinoid metabolites in blood samples and found 83 positives (21%) for only a synthetic cannabinoid metabolite. A case report is presented herein where 5F-MDMB-PINACA 3,3-dimethylbutanoic acid was identified in the absence of 5F-MDMB-PINACA. Forensic toxicologists should be aware of the results of this study as they directly impact analytical consideration for test development and implementation, as well as interpretation of findings.

Quantification of U-47700 and its metabolites: N-desmethyl-U-47700 and N,N-didesmethyl-U-47700 in 12 autopsy blood samples employing SPE/LC\u2013ESI-MS-MS

PurposeThe paper presents a report on the comprehensive assessment of a novel synthetic opioid (NSO) termed U-47700, and its two metabolites: N-desmethyl-U-47700 and N,N-didesmethyl-U-47700 in autopsy blood samples taken from 12 cases of fatal poisonings.MethodsThe analysis of the examined samples was based on the solid-phase extraction/liquid chromatography–electrospray ionization-tandem mass spectrometry method, which was developed in the validation process. In the quantitative analytical studies, deuterium analytes analogs were used, namely U-47700-d6 and N-desmethyl-U-47700-d3.ResultsThe validation parameters of the method were determined, including the limits of quantification on the 1 ng/mL level, calibration curves range of 1–1000 ng/ml, intra-assay precisions and accuracies of 1.1–20.2% and −18.9–9%, respectively, and inter-assay precisions and accuracies of 2.9–13.0% and -11.4–3.3%, respectively. The matrix effects and the extraction efficiencies were formed at the levels of 54.0–119% and 53.0–118%, respectively. The parent substance and its metabolites in blood samples have been shown to be relatively stable under various conditions within the 21-day study. The concentration levels demonstrated in the analyzed blood samples were: U-47700 in the range of 83–24,000 ng/mL, N-desmethyl-U-47700 in the range of 2.0–7520 ng/mL and N,N-didesmethyl-U-47700 in the range of 18–1947 ng/mL.ConclusionsThe simultaneous quantification of U-47700, N-desmethyl-U-47700 and N,N-didesmethyl-U-47700 seems very useful to confirm the cause of death and to estimate antemortem interval. To our knowledge this is the first trial to measure phase I metabolites of U-47700 in authentic human blood samples.

Prospective metabolomics study identifies potential novel blood metabolites associated with pancreatic cancer risk.

Using a metabolomics approach, we systematically searched for circulating metabolite biomarkers for pancreatic cancer risk in a case-control study nested within two prospective Shanghai cohorts. Included in our study were 226 incident pancreatic cancer cases and their individually-matched controls. Untargeted mass spectrometry platforms were used to measure metabolites in blood samples collected prior to cancer diagnosis. Conditional logistic regression was performed to assess the associations of metabolites with pancreatic cancer risk. We identified 10 metabolites associated with pancreatic cancer, after accounting for multiple comparisons (the Benjamini-Hochberg false discovery rate <0.05). The majority of the identified metabolites were glycerophospholipids (ORs per SD increase: 0.44-2.32; p values: 7.2×10-4 to 1.0×10-6 ), six of which were associated with decreased risk and one with increased risk. Additionally, levels of coumarin (OR=1.96, p=3.7×10-6 ) and picolinic acid (OR=2.53, p=5.0×10-5 ) were positively associated with pancreatic cancer risk, while tetracosanoic acid was inversely associated with risk (OR=0.48, p=7.16×10-7 ). Four metabolites remained statistically significant after mutual adjustment. Our study provides novel evidence that the dysregulation of glycerophospholipids may play an important role in pancreatic cancer development.