People living with HIV display increased anti-apolipoprotein A1 auto-antibodies, inflammation, and kynurenine metabolites: a case-control study.

Objective: This study aimed to study the relationship between auto-antibodies against apolipoprotein A1 (anti-apoA1 IgG), human immunodeficiency virus (HIV) infection, anti-retroviral therapy (ART), and the tryptophan pathways in HIV-related cardiovascular disease. Design: This case-control study conducted in South Africa consisted of control volunteers (n = 50), people living with HIV (PLWH) on ART (n = 50), and untreated PLWH (n = 44). Cardiovascular risk scores were determined, vascular measures were performed, and an extensive biochemical characterisation (routine, metabolomic, and inflammatory systemic profiles) was performed. Methods: Anti-apoA1 IgG levels were assessed by an in-house ELISA. Inflammatory biomarkers were measured with the Meso Scale Discovery® platform, and kynurenine pathway metabolites were assessed using targeted metabolomic profiling conducted by liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS). Results: Cardiovascular risk scores and vascular measures exhibited similarities across the three groups, while important differences were observed in systemic inflammatory and tryptophan pathways. Anti-apoA1 IgG seropositivity rates were 15%, 40%, and 70% in control volunteers, PLWH ART-treated, and PLWH ART-naïve, respectively. Circulating anti-apoA1 IgG levels were significantly negatively associated with CD4+ cell counts and positively associated with viremia and pro-inflammatory biomarkers (IFNγ, TNFα, MIPα, ICAM-1, VCAM-1). While circulating anti-apoA1 IgG levels were associated with increased levels of kynurenine in both control volunteers and PLWH, the kynurenine/tryptophan ratio was significantly increased in PLWH ART-treated. Conclusion: HIV infection increases the humoral response against apoA1, which is associated with established HIV severity criteria and kynurenine pathway activation.

Randomly controlled drivers using minimally invasive sampling: assessment of drug prevalence in Western Switzerland over two time periods.

BACKGROUND: According to the World Health Organization, road traffic injuries lead to 1.3 million deaths each year and represent the leading cause of death for young adults under 30 years old. The use of psychoactive substances, including alcohol, drugs and pharmaceuticals, is a well-known risk factor for road traffic injuries. Our study aims to assess the prevalence of substances consumed by drivers in western Switzerland. Such studies are pivotal to improving prevention and developing public awareness campaigns. METHODS: To assess the prevalence of psychoactive substances among drivers, roadside controls were performed in collaboration with local police, using their classical sampling procedures to detect drivers under the influence of drugs or alcohol over two time periods (P1: 2006-2008, P2: 2017-2020). When impaired driving was not suspected by the police, minimally invasive sampling strategies (i.e., oral fluids during P1 and dried blood spots during P2) were performed on volunteer drivers after a road safety survey. A posteriori analyses and statistical interpretation were then performed. RESULTS: Among the 1605 drivers included in the study, 1048 volunteers provided an oral fluid sample, while 299 provided a dried blood spot sample. The percentage of drivers testing positive for at least one substance that can impact driving abilities was stable over time, with a rate of 10.5% positivity measured over both periods. Considering the different categories of substances, a slight variation was observed between both periods, with 7.6 and 6.3% of pharmaceuticals and 3.6 and 4.9% of illicit drugs for P1 and P2, respectively. Regarding the consumption of illicit drugs, the highest percentage of positivity was measured in biological fluids of drivers under the age of 35, during nights and week-ends, periods which are considered particularly prone to fatal accidents for this age group. Disturbingly, the road safety survey highlighted that drivers' perception of the risk of getting positively controlled while driving after drug consumption is low (3.3 on a 1-to-10 scale, N = 299). CONCLUSION: The number of positive cases measured in voluntary drivers who passed the preliminary police check demonstrates the importance of systematic biofluid sampling strategies regarding driving under the influence of psychoactive substances. Although the number of fatal road accidents globally has decreased over time, the results of this study reveal the need for both better prevention and deterrent processes that could potentially reduce the risk of fatal road accidents associated with drug consumption.

Metabolomic alteration induced by psychotropic drugs: Short-term metabolite profile as a predictor of weight gain evolution.

Psychotropic drugs can induce strong metabolic adverse effects, potentially increasing morbidity and/or mortality of patients. Metabolomic profiling, by studying the levels of numerous metabolic intermediates and products in the blood, allows a more detailed examination of metabolism dysfunctions. We aimed to identify blood metabolomic markers associated with weight gain in psychiatric patients. Sixty-two patients starting a treatment known to induce weight gain were recruited. Two hundred and six selected metabolites implicated in various pathways were analyzed in plasma, at baseline and after 1 month of treatment. Additionally, 15 metabolites of the kynurenine pathway were quantified. This latter analysis was repeated in a confirmatory cohort of 24 patients. Among the 206 metabolites, a plasma metabolomic fingerprint after 1 month of treatment embedded 19 compounds from different chemical classes (amino acids, acylcarnitines, carboxylic acids, catecholamines, nucleosides, pyridine, and tetrapyrrole) potentially involved in metabolic disruption and inflammation processes. The predictive potential of such early metabolite changes on 3 months of weight evolution was then explored using a linear mixed-effects model. Of these 19 metabolites, short-term modifications of kynurenine, hexanoylcarnitine, and biliverdin, as well as kynurenine/tryptophan ratio at 1 month, were associated with 3 months weight evolution. Alterations of the kynurenine pathway were confirmed by quantification, in both exploratory and confirmatory cohorts. Our metabolomic study suggests a specific metabolic dysregulation after 1 month of treatment with psychotropic drugs known to induce weight gain. The identified metabolomic signature could contribute in the future to the prediction of weight gain in patients treated with psychotropic drugs.

Sphingosine-1-phosphate as a key player of insulin secretion induced by high-density lipoprotein treatment.

Beta cell failure is one of the most important features of type 2 diabetes mellitus (T2DM). High-density lipoprotein (HDL) has been proposed to improve ß-cell function. However, the mechanisms involved in this process are still poorly understood. The aim of this study was to investigate the contribution of sphingosine-1-phosphate (S1P) in the impact of HDL treatment on insulin secretion by pancreatic ß-cells and to determine its mechanisms. Primary cultures of ß-cells isolated from rat were treated with or without HDL in the presence or absence of S1P pathway inhibitors and insulin secretion response was analyzed. The S1P content of HDL (HDL-S1P) isolated from T2DM patients was analyzed and correlated to the HDL-induced insulin secretion. The expression of genes involved in the biosynthesis of the insulin was also evaluated. HDL as well as S1P treatment enhanced glucose-stimulated insulin secretion (GSIS). In HDL isolated from T2DM patients, while HDL-S1P was strongly correlated to its pro-secretory capacity (r = 0.633, p = 0.005), HDL-cholesterol and apolipoprotein AI levels were not. HDL-induced GSIS was blocked by the S1P1/3 antagonist but not by the S1P2 antagonist, and was also accompanied by increased intracellular S1P in ß-cells. We also observed that HDL improved GSIS without significant changes in expression levels of insulin biosynthesis genes. Our present study highlights the importance HDL-S1P in GSIS in T2DM patients and demonstrates that HDL induces insulin secretion by a process involving both intra- and extra-cellular sources of S1P independently of an effect on insulin biosynthesis genes.

DBnorm as an R package for the comparison and selection of appropriate statistical methods for batch effect correction in metabolomic studies.

As a powerful phenotyping technology, metabolomics provides new opportunities in biomarker discovery through metabolome-wide association studies (MWAS) and the identification of metabolites having a regulatory effect in various biological processes. While mass spectrometry-based (MS) metabolomics assays are endowed with high throughput and sensitivity, MWAS are doomed to long-term data acquisition generating an overtime-analytical signal drift that can hinder the uncovering of real biologically relevant changes. We developed "dbnorm", a package in the R environment, which allows for an easy comparison of the model performance of advanced statistical tools commonly used in metabolomics to remove batch effects from large metabolomics datasets. "dbnorm" integrates advanced statistical tools to inspect the dataset structure not only at the macroscopic (sample batches) scale, but also at the microscopic (metabolic features) level. To compare the model performance on data correction, "dbnorm" assigns a score that help users identify the best fitting model for each dataset. In this study, we applied "dbnorm" to two large-scale metabolomics datasets as a proof of concept. We demonstrate that "dbnorm" allows for the accurate selection of the most appropriate statistical tool to efficiently remove the overtime signal drift and to focus on the relevant biological components of complex datasets.

Driving Under the Influence of Drugs: A Single Parallel Monitoring-Based Quantification Approach on Whole Blood.

Driving under the influence of psychoactive substances is a major cause of motor vehicle crashes. The identification and quantification of substances most frequently involved in impaired-driving cases in a single analytic procedure could be an important asset in forensic toxicology. In this study, a highly sensitive and selective liquid chromatography (LC) approach hyphenated with Orbitrap high-resolution mass spectrometry (HRMS) was developed for the quantification of the main drugs present in the context of driving under the influence of drugs (DUID) using 100 µL of whole blood. This procedure involves a simple sample preparation and benefit from the selectivity brought by parallel reaction monitoring (PRM) allowing to solve most DUID cases using a single multi-analyte injection. The method was fully validated for the quantification of the major classes of psychoactive substances associated with impaired-driving (cannabinoids, cocaine and its metabolites, amphetamines, opiates and opioids, and the major benzodiazepines and z-drugs). The validation guidelines set by the "Société Française des Sciences et des Techniques Pharmaceutiques" (SFSTP) were respected for 22 psychoactive substances using 15 internal standards. Trueness was measured to be between 95.3 and 107.6% for all the tested concentrations. Precision represented by repeatability and intermediate precision was lower than 12% while recovery (RE) and matrix effect (ME) ranged from 49 to 105% and from -51 to 3%, respectively. The validated procedure provides an efficient approach for the simultaneous and simple quantification of the major drugs associated with impaired driving benefiting from the selectivity of PRM.

Liquid chromatography-high resolution mass spectrometry for broad-spectrum drug screening of dried blood spot as microsampling procedure.

BACKGROUND: Hyphenation of liquid chromatography (LC) with high-resolution mass spectrometry (HRMS) offers the potential to develop broad-spectrum screening procedures from low volumes of biological matrices. In parallel, dried blood spot (DBS) has become a valuable tool in the bioanalysis landscape to overcome conventional blood collection issues. Herein, we demonstrated the applicability of DBS as micro-sampling procedure for broad-spectrum toxicological screening. METHODS: A method was developed on a HRMS system in data dependant acquisition (DDA) mode using an extensive inclusion list to promote collection of relevant data. 104 real toxicology cases were analysed, and the results were cross-validated with one published and one commercial screening procedures. Quantitative MRM analyses were also performed on identified substances on a triple quadrupole instrument as a complementary confirmation procedure. RESULTS: The method showed limits of identification (LOIs) in appropriateness with therapeutic ranges for all the classes of interest. Applying the three screening approaches on 104 real cases, 271 identifications were performed including 14 and 6 classes of prescribed and illicit drugs, respectively. Among the detected substances, 23% were only detected by the proposed method. Based on confirmatory analyses, we demonstrated that the use of blood micro-samples did not impair the sensitivity allowing more identifications in the low concentration ranges. CONCLUSION: A LC-HRMS assay was successfully developed for toxicological screening of blood microsamples demonstrating a high identification power at low concentration ranges. The validation procedure and the analysis of real cases demonstrated the potential of this assay by supplementing screening approaches of reference.

XCMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules.

We report XCMS-MRM and METLIN-MRM ( http://xcmsonline-mrm.scripps.edu/ and http://metlin.scripps.edu/ ), a cloud-based data-analysis platform and a public multiple-reaction monitoring (MRM) transition repository for small-molecule quantitative tandem mass spectrometry. This platform provides MRM transitions for more than 15,500 molecules and facilitates data sharing across different instruments and laboratories.

Beneficial Effects of Human Mesenchymal Stromal Cells on Porcine Hepatocyte Viability and Albumin Secretion.

Porcine hepatocytes transplanted during acute liver failure might support metabolic functions until the diseased liver recovers its function. Here, we isolated high numbers of viable pig hepatocytes and evaluated hepatocyte functionality after encapsulation. We further investigated whether coculture and coencapsulation of hepatocytes with human multipotent mesenchymal stromal cells (MSC) are beneficial on hepatocyte function. Livers from 10 kg pigs (n = 9) were harvested, and hepatocytes were isolated from liver suspensions for microencapsulation using alginate and poly(ethylene-glycol)- (PEG-) grafted alginate hydrogels, either alone or in combination with MSC. Viability, albumin secretion, and diazepam catabolism of hepatocytes were measured for one week. 9.2 ± 3.6 × 109 hepatocytes with 95.2 ± 3.1% viability were obtained after isolation. At day 3, free hepatocytes displayed 99% viability, whereas microencapsulation in alginate and PEG-grafted alginate decreased viability to 62% and 48%, respectively. Albumin secretion and diazepam catabolism occurred in free and microencapsulated hepatocytes. Coencapsulation of hepatocytes with MSC significantly improved viability and albumin secretion at days 4 and 8 (p < 0.05). Coculture with MSC significantly increased and prolonged albumin secretion. In conclusion, we established a protocol for isolation and microencapsulation of high numbers of viable pig hepatocytes and demonstrated that the presence of MSC is beneficial for the viability and function of porcine hepatocytes.

Quantification of ghrelin and des-acyl ghrelin in human plasma by using cubic-selected reaction-monitoring LCMS.

BACKGROUND: Ghrelin is a peptide hormone generally measured in plasma by immunoassays. LCMS/MS was investigated as an alternative method in particular for the quantification of the two forms of the peptide with improved selectivity. MATERIALS & METHODS: A LCMS assay using a cubic-selected reaction-monitoring (LCSRM(3)/MS) mode was developed for the quantification of ghrelin and des-acyl ghrelin in human plasma. RESULTS: The LCSRM(3)/MS method was found to be linear from 50-75 to 2500 pg/ml for the ghrelins using a 0.5-ml plasma sample. The accuracies and precisions at LOQ for des-acyl ghrelin (50 pg/ml) and ghrelin (75 pg/ml) were found to be better than 91 and 2%, respectively. Blood and plasma stabilization was found to be essential for good assay performance. CONCLUSION: Compared to the LCSRM/MS method the addition of an additional MS step did significantly improve the selectivity and therefore the sensitivity. The LCSRM(3)/MS method could be successfully applied for the quantification of ghrelin and des-acyl ghrelin in human plasma samples.

Peptides OFFGEL electrophoresis: a suitable pre-analytical step for complex eukaryotic samples fractionation compatible with quantitative iTRAQ labeling.

BACKGROUND: The proteomes of mammalian biological fluids, cells and tissues are complex and composed of proteins with a wide dynamic range. The effective way to overcome the complexity of these proteomes is to combine several fractionation steps. OFFGEL fractionation, recently developed by Agilent Technologies, provides the ability to pre-fractionate peptides into discrete liquid fractions and demonstrated high efficiency and repeatability necessary for the analysis of such complex proteomes. RESULTS: We evaluated OFFGEL fractionator technology to separate peptides from two complex proteomes, human secretome and human plasma, using a 24-wells device encompassing the pH range 3-10. In combination with reverse phase liquid chromatography, peptides from these two samples were separated and identified by MALDI TOF-TOF. The repartition profiles of the peptides in the different fractions were analyzed and explained by their content in charged amino acids using an algorithmic model based on the possible combinations of amino acids. We also demonstrated for the first time the compatibility of OFFGEL separation technology with the quantitative proteomic labeling technique iTRAQ allowing inclusion of this technique in complex samples comparative proteomic workflow. CONCLUSION: The reported data showed that OFFGEL system provides a highly valuable tool to fractionate peptides from complex eukaryotic proteomes (plasma and secretome) and is compatible with iTRAQ labeling quantitative studies. We therefore consider peptides OFFGEL fractionation as an effective addition to our strategy and an important system for quantitative proteomics studies.