In-depth mass spectrometry analysis of rhGH administration altered energy metabolism and steroidogenesis

Growth hormone, as a proteohormone, is primarily known of its dramatic effect on longitudinal growth. Recombinant DNA technology has provided a safe, abundant and comparatively cheap supply of human GH for growth hormone-deficient individuals. However, many healthy subjects, especially athletics, administrate GH for enhanced athletic performance or strength. A better and more comprehensive understanding of rhGH effect in healthy individuals is urgent and essential. In this study, we recruited 14 healthy young male and injected rhGH once. Untargeted LC-MS metabolomics profiling of serum and urine was performed before and after the rhGH injection. The GH-induced dysregulation of energy related pathways, such as amino acid metabolism, nucleotide metabolism, glycolysis and TCA cycle, was revealed. Moreover, individuals supplemented with micro-doses of rhGH exhibited significantly changed urinary steroidal profiles, suggesting a role of rhGH in both energy metabolism and steroidogenesis. We expect that our results will be helpful to provide new evidence on the effects of rhGH injection and provide potential biomarkers for rhGH administration.

Determination of bile acids in serum of pigs exposed to polychlorinated biphenyls by liquid chromatography-mass spectrometry

Exposure to polychlorinated biphenyls (PCBs) has been linked to dyslipidemia. Under acute exposure to PCBs, it has been observed that the secretion of bile acids (BAs) can be impacted, limiting (indirectly) lipid absorption in the gut. In this context, two non-targeted metabolomics studies on pig serum have recently suggested that BA concentrations may fluctuate under exposure to current non-dioxin-like (NDL)-PCB levels in food, reflecting the acute effects of such chronic exposure. The objective of this research is to implement a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for BA analysis in order to validate the findings of previous metabolomics studies, in which BA levels in serum samples from pigs exposed to environmental doses of NDL-PCBs were highlighted to be affected. The proposed LC-MS method involves the use of a C18-pentafluorophenyl LC column, which is not usually selected for the separation of BAs, but shows better performance for the separation of isomers than typical C18 columns. This LC-MS method shows excellent analytical performance such as low limits of detection (LODs) (≤1 ng/mL for most BAs) and good linearity (R2 > 0.994), while no matrix effect was observed. A total of 13 BAs have been quantified, while further BA isomers could be detected and semi-quantified. The application of this targeted LC-MS method confirmed previous findings, suggesting that exposure to low doses of NDL-PCBs decreases the concentration of BAs (i.e., glycochenodeoxycholic acid, hyodeoxycholic acid and taurochenodeoxycholic acid) while the effect on the precursors (cholic acid and chenodeoxycholic acid) is less pronounced.

Deeper insights into the effects of low dietary levels of polychlorinated biphenyls on pig metabolism using gas chromatography-high resolution mass spectrometry metabolomics

Polychlorinated biphenyls (PCBs) are a class of contaminants of great concern, linked to the development of many chronic diseases. Adverse effects of PCBs have been documented in humans after accidental and massive exposure. However, little is known about the effect of chronic exposure to low-dose PCB mixtures, and studies regarding scattered lifetime exposures to non-dioxin-like (NDL)-PCBs are especially missing. In this work, serum samples from pigs chronically exposed through their diet during 22 days to Aroclor 1260 (i.e. a commercially available mixture of NDL-PCBs) underwent a metabolomics analysis using gas chromatography-high resolution mass spectrometry (GC-HRMS), with the objective to investigate the effect of exposure to low doses of NDL-PCBs (few ng/kg body weight (b.w.) per day). The study showed that the serum profiles of 84 metabolites are significantly altered by the administration of Aroclor 1260, of which 40 could be identified at level 1. The aggregate interpretation of the results of this study, together with the outcome of a previous one involving LC-HRMS profiling, provided a substantial and concise overview of the effect of low dose exposure to NDL-PCBs, reflecting the hepatotoxic and neurotoxic effects already reported in literature at higher and longer exposures. These results are intended to contribute to the debate on the current toxicological reference values for these substances.

Future opportunities for the Athlete Biological Passport

The Athlete Biological Passport (ABP) was introduced to complement the direct anti-doping approach by indirectly outlining the possible use of prohibited substances or methods in sports. The ABP proved its effectiveness, at least through a deterrent effect, even though the matrices used for longitudinal monitoring (urine and blood) are subject to many intrinsic (e.g., genetic) and extrinsic (e.g., environmental conditions) confounding factors. In that context, new and more specific biomarkers are currently under development to enhance both the sensitivity and the specificity of the ABP. Multiple strategies are presently being explored to improve this longitudinal monitoring, with the development of the current modules, the investigation of new strategies, or the screening of new types of doping. Nevertheless, due to the variability induced by indirect biomarkers, the consideration of confounding factors should continuously support this research. Beyond tremendous advances in analytical sensitivity, machine learning-based approaches seem inevitable to facilitate an expert interpretation of numerous biological profiles and promote anti-doping efforts. This perspective article highlights the current innovations of the Athlete Biological Passport that seem the most promising. Through different research axes, this short manuscript provides an opportunity to bring together approaches that are more widely exploited (e.g., omics strategies) and others in the early stages of investigation (e.g., artificial intelligence) seeking to develop the ABP.

Metabolomics and lipidomics to identify biomarkers of effect related to exposure to non-dioxin-like polychlorinated biphenyls in pigs

Recent epidemiological studies show that current levels of exposure to polychlorinated biphenyls (PCBs) remain of great concern, as there is still a link between such exposures and the development of chronic environmental diseases. In this sense, most studies have focused on the health effects caused by exposure to dioxin-like PCBs (DL-PCBs), although chemical exposure to non-dioxin-like PCB (NDL-PCB) congeners is more significant. In addition, adverse effects of PCBs have been documented in humans after accidental and massive exposure, but little is known about the effect of chronic exposure to low-dose PCB mixtures. In this work, exposure to Aroclor 1260 (i.e. a commercially available mixture of PCBs consisting primarily of NDL-PCB congeners) in pigs is investigated as new evidence in the risk assessment of NDL-PCBs. This animal model has been selected due to the similarities with human metabolism and to support previous toxicological studies carried out with more frequently used animal models. Dietary exposure doses in the order of few ng/kg body weight (b.w.) per day were applied. As expected, exposure to Aroclor 1260 led to the bioaccumulation of NDL-PCBs in perirenal fat of pigs. Metabolomics and lipidomics have been applied to reveal biomarkers of effect related to Aroclor 1260 exposure, and by extension to NDL-PCB exposure, for 21 days. In the metabolomics analysis, 33 metabolites have been identified (level 1 and 2) as significantly altered by the Aroclor 1260 administration, while in the lipidomics analysis, 39 metabolites were putatively annotated (level 3) and associated with NDL-PCB exposure. These biomarkers are mainly related to the alteration of fatty acid metabolism, glycerophospholipid metabolism and tryptophan-kynurenine pathway.

Metabolomics in clinical and forensic toxicology, sports anti-doping and veterinary residues

Metabolomics is a multidisciplinary field providing workflows for complementary approaches to conventional analytical determinations. It allows for the study of metabolically related groups of compounds or even the study of novel pathways within the biological system. The procedural stages of metabolomics; experimental design, sample preparation, analytical determinations, data processing and statistical analysis, compound identification and validation strategies are explored in this review. The selected approach will depend on the type of study being conducted. Experimental design influences the whole metabolomics workflow and thus needs to be properly assessed to ensure sufficient sample size, minimal introduced and biological variation and appropriate statistical power. Sample preparation needs to be simple, yet potentially global in order to detect as many compounds as possible. Analytical determinations need to be optimised either for the list of targeted compounds or a universal approach. Data processing and statistical analysis approaches vary widely and need to be better harmonised for review and interpretation. This includes validation strategies that are currently deficient in many presented workflows. Common compound identification approaches have been explored in this review. Metabolomics applications are discussed for clinical and forensic toxicology, human and equine sports anti-doping and veterinary residues.

Comprehensive Peak Characterization (CPC) in Untargeted LC–MS Analysis

LC–MS-based untargeted metabolomics is heavily dependent on algorithms for automated peak detection and data preprocessing due to the complexity and size of the raw data generated. These algorithms are generally designed to be as inclusive as possible in order to minimize the number of missed peaks. This is known to result in an abundance of false positive peaks that further complicate downstream data processing and analysis. As a consequence, considerable effort is spent identifying features of interest that might represent peak detection artifacts. Here, we present the CPC algorithm, which allows automated characterization of detected peaks with subsequent filtering of low quality peaks using quality criteria familiar to analytical chemists. We provide a thorough description of the methods in addition to applying the algorithms to authentic metabolomics data. In the example presented, the algorithm removed about 35% of the peaks detected by XCMS, a majority of which exhibited a low signal-to-noise ratio. The algorithm is made available as an R-package and can be fully integrated into a standard XCMS workflow.

Metabolomics as a potential tool for the diagnosis of growth hormone deficiency (GHD): a review

Metabolomics uses several analytical tools to identify the chemical diversity of metabolites present in organisms. These metabolites are low molecular weight molecules (<1500 Da) classified as a final or intermediary product of metabolic processes. The application of this omics technology has become prominent in inferring physiological conditions through reporting on the phenotypic state; therefore, the introduction of metabolomics into clinical studies has been growing in recent years due to its efficiency in discriminating pathophysiological states. Regarding endocrine diseases, there is a great interest in verifying comprehensive and individualized physiological scenarios, in particular for growth hormone deficiency (GHD). The current GHD diagnostic tests are laborious and invasive and there is no exam with ideal reproducibility and sensitivity for diagnosis neither standard GH cut-off point. Therefore, this review was focussed on articles that applied metabolomics in the search for new biomarkers for GHD. The present work shows that the applications of metabolomics in GHD are still limited, since the little complementarily of analytical techniques, a low number of samples, GHD combined to other deficiencies, and idiopathic diagnosis shows a lack of progress. The results of the research are relevant and similar; however, their results do not provide an application for clinical practice due to the lack of multidisciplinary actions that would be needed to mediate the translation of the knowledge produced in the laboratory, if transferred to the medical setting.

Coupling Complete Blood Count and Steroidomics to Track Low Doses Administration of Recombinant Growth Hormone: An Anti-Doping Perspective

Growth Hormone (GH) under its human recombinant homologue (rhGH), may be abused by athletes to take advantage of its well-known anabolic and lipolytic properties; hence it is prohibited in sports by the World Anti-Doping Agency. Due to the rapid turnover of rhGH, anti-doping screening tests have turned to monitor two endocrine biomarkers (IGF-I and P-III-NP), but unfortunately, they show population-wise variability, limiting the identification rate of rhGH users. Previous studies have evidenced the numerous effects of GH on human physiology, especially in hematopoiesis and steroidogenesis. In this work, aiming to discover novel physiological rhGH biomarkers, we analyzed the complete blood count and the steroidomics profile of healthy, physically active, young males treated either with EPO + rhGH or EPO + placebo. The time-trends of these two physiological routes have been analyzed through geometric trajectory analysis (GTA) and OPLS-DA. Individuals supplemented with micro-doses of rhGH exhibited different leukopoietic and steroidal profiles compared to the control population, suggesting a role of the rhGH in both pathways. In the article, hypotheses on the observed differences are discussed according to the most recent literature and compared to results in animal models. The use of leukopoietic and steroidal biomarkers together with endocrine biomarkers (IGF-1 and P-III-NP) allows to correctly classify over 98% of samples with no false positives, miss-classifying only one single sample (false negative) over a total of 56; a promising result, if compared to the current rhGH detection strategies.

Annual banned-substance review: Analytical approaches in human sports drug testing 2019/2020

Analytical chemistry-based research in sports drug testing has been a dynamic endeavor for several decades, with technology-driven innovations continuously contributing to significant improvements in various regards including analytical sensitivity, comprehensiveness of target analytes, differentiation of natural/endogenous substances from structurally identical but synthetically derived compounds, assessment of alternative matrices for doping control purposes, and so forth. The resulting breadth of tools being investigated and developed by anti-doping researchers has allowed to substantially improve anti-doping programs and data interpretation in general. Additionally, these outcomes have been an extremely valuable pledge for routine doping controls during the unprecedented global health crisis that severely affected established sports drug testing strategies. In this edition of the annual banned-substance review, literature on recent developments in anti-doping published between October 2019 and September 2020 is summarized and discussed, particularly focusing on human doping controls and potential applications of new testing strategies to substances and methods of doping specified the World Anti-Doping Agency's 2020 Prohibited List.