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Metabolomics and lipidomics are pivotal in understanding phenotypic variations beyond genomics. However, quantification and comparability of mass spectrometry (MS)-derived data are challenging. Standardised assays can enhance data comparability, enabling applications in multi-center epidemiological and clinical studies. Here we evaluated the performance and reproducibility of the MxP ® Quant 500 kit across 14 laboratories. The kit allows quantification of 634 different metabolites from 26 compound classes using triple quadrupole MS. Each laboratory analysed twelve samples, including human plasma and serum, lipaemic plasma, NIST SRM 1950, and mouse and rat plasma, in triplicates. 505 out of the 634 metabolites were measurable above the limit of detection in all laboratories, while eight metabolites were undetectable in our study. Out of the 505 metabolites, 412 were observed in both human and rodent samples. Overall, the kit exhibited high reproducibility with a median coefficient of variation (CV) of 14.3 %. CVs in NIST SRM 1950 reference plasma were below 25 % and 10 % for 494 and 138 metabolites, respectively. To facilitate further inspection of reproducibility for any compound, we provide detailed results from the in-depth evaluation of reproducibility across concentration ranges using Deming regression. Interlaboratory reproducibility was similar across sample types, with some species-, matrix-, and phenotype-specific differences due to variations in concentration ranges. Comparisons with previous studies on the performance of MS-based kits (including the AbsoluteIDQ p180 and the Lipidyzer) revealed good concordance of reproducibility results and measured absolute concentrations in NIST SRM 1950 for most metabolites, making the MxP ® Quant 500 kit a relevant tool to apply metabolomics and lipidomics in multi-center studies., Competing Interests: DECLARATION OF INTERESTS G.K. is co-inventor (through Helmholtz Zentrum München) on patents regarding applications of metabolomics in diseases of the central nervous system and holds equity in Chymia LLC. A.L., T.H.P and T.K. were employed at biocrates life sciences ag at the time the experiment was conducted and/or at the time this manuscript was being written. K.C. is currently an AstraZeneca employee.

Schizophrenia (SCZ) is a neuropsychiatric disorder, caused by a combination of genetic and environmental factors. The etiology behind the disorder remains elusive although it is hypothesized to be associated with the aberrant response to neurotransmitters, such as dopamine and glutamate. Therefore, investigating the link between dysregulated metabolites and distorted neurodevelopment holds promise to offer valuable insights into the underlying mechanism of this complex disorder. In this study, we aimed to explore a presumed correlation between the transcriptome and the metabolome in a SCZ model based on patient-derived induced pluripotent stem cells (iPSCs). For this, iPSCs were differentiated towards cortical neurons and samples were collected longitudinally at various developmental stages, reflecting neuroepithelial-like cells, radial glia, young and mature neurons. The samples were analyzed by both RNA-sequencing and targeted metabolomics and the two modalities were used to construct integrative networks in silico. This multi-omics analysis revealed significant perturbations in the polyamine and gamma-aminobutyric acid (GABA) biosynthetic pathways during rosette maturation in SCZ lines. We particularly observed the downregulation of the glutamate decarboxylase encoding genes GAD1 and GAD2, as well as their protein product GAD65/67 and their biochemical product GABA in SCZ samples. Inhibition of ornithine decarboxylase resulted in further decrease of GABA levels suggesting a compensatory activation of the ornithine/putrescine pathway as an alternative route for GABA production. These findings indicate an imbalance of cortical excitatory/inhibitory dynamics occurring during early neurodevelopmental stages in SCZ. Our study supports the hypothesis of disruption of inhibitory circuits to be causative for SCZ and establishes a novel in silico approach that enables for integrative correlation of metabolic and transcriptomic data of psychiatric disease models., (© 2024. The Author(s).)

The mechanisms connecting environmental conditions to plasticity in biological aging trajectories are fundamental to understanding individual variation in functional traits and life history. Recent findings suggest that telomere biology is especially dynamic during early life stages and has long-term consequences for subsequent reproduction and survival. However, our current understanding is mostly derived from studies investigating ecological and anthropogenic factors separately, leaving the effects of complex environmental interactions unresolved. American alligators (Alligator mississippiensis) are long-lived apex predators that rely on incubation temperature during a discrete period during development and endocrine cues to determine sex, making them especially vulnerable to current climatic variability and exposure to anthropogenic contaminants interfering with hormone function. Here, we combine field studies with a factorial design to understand how the developmental environment, along with intrinsic biological variation contribute to persistent telomere variation. We found that exposure to a common endocrine disrupting contaminant, DDE, affects telomere length, but that the directionality is highly dependent upon incubation temperature. Variation in hatchling growth, underlies a strong clutch effect. We also assess concentrations of a panel of glucocorticoid hormones and find that contaminant exposure elicits an increase in circulating glucocorticoids. Consistent with emerging evidence linking stress and aging trajectories, GC levels also appear to trend with shorter telomere length. Thus, we add support for a mechanistic link between contaminants and glucocorticoid signalling, which interacts with ecological aspects of the developmental environment to alter telomere dynamics., (© 2021 John Wiley & Sons Ltd.)

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). We found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption., (Copyright © 2022 Elsevier B.V. All rights reserved.)

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.

Alzheimer's disease (AD) is the most common cause of dementia. The mechanism of disease development and progression is not well understood, but increasing evidence suggests multifactorial etiology, with a number of genetic, environmental, and aging-related factors. There is a growing body of evidence that metabolic defects may contribute to this complex disease. To interrogate the relationship between system level metabolites and disease susceptibility and progression, the AD Metabolomics Consortium (ADMC) in partnership with AD Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for patients in the ADNI1 cohort. We used the Biocrates Bile Acids platform to evaluate the association of metabolic levels with disease risk and progression. We detail the quantitative metabolomics data generated on the baseline samples from ADNI1 and ADNIGO/2 (370 cognitively normal, 887 mild cognitive impairment, and 305 AD). Similar to our previous reports on ADNI1, we present the tools for data quality control and initial analysis. This data descriptor represents the third in a series of comprehensive metabolomics datasets from the ADMC on the ADNI.

In recent years, metabolites have attracted substantial attention as promising novel biomarkers of various diseases. However, breast cancer plasma metabolite studies are still in their infancy. Here, we investigated the potential of metabolites to serve as minimally invasive, early detection markers of primary breast cancer. We profiled metabolites extracted from the plasma of primary breast cancer patients and healthy controls using tandem mass spectrometry (UHPLC-MS/MS and FIA-MS/MS). Two metabolites were found to be upregulated, while 16 metabolites were downregulated in primary breast cancer patients compared to healthy controls in both the training and validation cohorts. A panel of seven metabolites was selected by LASSO regression analysis. This panel could differentiate primary breast cancer patients from healthy controls, with an AUC of 0.87 (95% CI: 0.81 ~ 0.92) in the training cohort and an AUC of 0.80 (95% CI: 0.71 ~ 0.87) in the validation cohort. These significantly differentiated metabolites are mainly involved in the amino acid metabolism and breast cancer cell growth pathways. In conclusion, using a metabolomics approach, we identified metabolites that have potential value for development of a multimarker blood-based test to complement and improve early breast cancer detection. The panel identified herein might be part of a prescreening tool, especially for younger women or for closely observing women with certain risks, to facilitate decision making regarding which individuals should undergo further diagnostic tests. In the future, the combination of metabolites and other blood-based molecular marker sets, such as DNA methylation, microRNA, and cell-free DNA mutation markers, will be an attractive option., (© 2018 UICC.)

Introduction: Increasing evidence suggests a role for the gut microbiome in central nervous system disorders and a specific role for the gut-brain axis in neurodegeneration. Bile acids (BAs), products of cholesterol metabolism and clearance, are produced in the liver and are further metabolized by gut bacteria. They have major regulatory and signaling functions and seem dysregulated in Alzheimer's disease (AD)., Methods: Serum levels of 15 primary and secondary BAs and their conjugated forms were measured in 1464 subjects including 370 cognitively normal older adults, 284 with early mild cognitive impairment, 505 with late mild cognitive impairment, and 305 AD cases enrolled in the AD Neuroimaging Initiative. We assessed associations of BA profiles including selected ratios with diagnosis, cognition, and AD-related genetic variants, adjusting for confounders and multiple testing., Results: In AD compared to cognitively normal older adults, we observed significantly lower serum concentrations of a primary BA (cholic acid [CA]) and increased levels of the bacterially produced, secondary BA, deoxycholic acid, and its glycine and taurine conjugated forms. An increased ratio of deoxycholic acid:CA, which reflects 7α-dehydroxylation of CA by gut bacteria, strongly associated with cognitive decline, a finding replicated in serum and brain samples in the Rush Religious Orders and Memory and Aging Project. Several genetic variants in immune response-related genes implicated in AD showed associations with BA profiles., Discussion: We report for the first time an association between altered BA profile, genetic variants implicated in AD, and cognitive changes in disease using a large multicenter study. These findings warrant further investigation of gut dysbiosis and possible role of gut-liver-brain axis in the pathogenesis of AD., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The adrenocorticotropic hormone (ACTH) stimulation test is a widely used diagnostic tool to assess the adrenal gland function. Beyond that the ACTH test can be used in stress research to induce a biochemical stress response under standardized conditions. To study the impact of the stress response on protein metabolism, time-course plasma amino acid profiling in healthy individuals was performed with high performance liquid chromatography tandem-mass spectrometry (HPLC-MS/MS)., Methods: A set of 39 samples (pre/post 30´ and 60´ IV-ACTH) from 13 healthy individuals (age range 26 - 58, 3 female and 10 male) was investigated. Plasma amino acids were quantified by LC-MS/MS using the AbsoluteIDQ® p180 Kit (Biocrates Life Science, Innsbruck, Austria) including 19 biogenic amino acids, ornithine, and citrulline., Results: Statistically significant decreases were observed for 11 proteinogenic amino acids (alanine, asparagine, isoleucine, leucine, tyrosine, phenylalanine, tryptophan, valine, methionine, aspartate, and threonine). The amino acids alanine, asparagine, and isoleucine showed markedly pronounced relative changes with short-term reduction of median inter-individual plasma concentrations of up to 25%., Conclusions: Amino acid profiling with LC-MS/MS revealed highly dynamic plasma alterations upon application of exogenous corticotropin as a stress model. Our findings provide novel insights into the biochemical stress response and improve our understanding of short-term metabolic consequences. Further studies should elucidate the impact of corticotropin mediated stress responses on amino acid catabolism.

Tryptophan (TRP) catabolism via the kynurenine pathway is considered to represent a major link between inflammation and various diseases, including neurodegenerative disorders, depression, schizophrenia, multiple sclerosis, cardiovascular disease, and cancer. The kynurenine pathway and levels of TRP and its metabolites kynurenine (KYN), kynurenic acid (KYNA) and quinolinic acid (QUIN) are well regulated under physiological conditions but may be altered as part of the activated immune response. A simple, sensitive, and specific liquid chromatography-time of flight mass spectrometry method was developed for determining levels of the four compounds in human plasma samples. The workflow involves protein precipitation with acetonitrile, chromatographic separation on a Phenomenex Luna NH2 column by applying a linear 6 min gradient of 50-5% acetonitrile in aqueous ammonium acetate solution (5 mM, pH 9.5), and mass spectrometric detection with high-resolution tandem mass spectrometry. Charcoal-treated plasma served as surrogate matrix for external standard calibration. Stable-isotope-labeled analogues were used as internal standards. The calibration ranges were 0.5-50 μg/ml for TRP, 20-1000 ng/mL for KYN und QUIN, and 1-50 ng/mL for KYNA. Validation proved fitness of the developed workflow for the intended purpose. The established method was applied to the quantification of the four targets in 100 authentic plasma samples., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Introduction: There is still a clear need for a widely available, inexpensive and reliable method to diagnose Alzheimer's disease (AD) and monitor disease progression. Liquid chromatography-mass spectrometry (LC-MS) is a powerful analytic technique with a very high sensitivity and specificity., Objectives: The aim of the present study is to measure concentrations of 20 bile acids using the novel Kit from Biocrates Life Sciences based on LC-MS technique., Methods: Twenty bile acid metabolites were quantitatively measured in plasma of 30 cognitively healthy subjects, 20 patients with mild cognitive impairment (MCI) and 30 patients suffering from AD., Results: Levels of lithocholic acid were significantly enhanced in plasma of AD patients (50 ± 6 nM, p = 0.004) compared to healthy controls (32 ± 3 nM). Lithocholic acid plasma levels of MCI patients (41 ± 4 nM) were not significantly different from healthy subjects or AD patients. Levels of glycochenodeoxycholic acid, glycodeoxycholic acid and glycolithocholic acid were significantly higher in AD patients compared to MCI patients (p < 0.05). All other cholic acid metabolites were not significantly different between healthy subjects, MCI patients and AD patients. ROC analysis shows an overall accuracy of about 66%. Discriminant analysis was used to classify patients and we found that 15/23 were correctly diagnosed. We further showed that LCA levels increased by about 3.2 fold when healthy subjects converted to AD patients within a 8-9 year follow up period. Pathway analysis linked these changes to a putative toxic cholesterol pathway., Conclusion: In conclusion, 4 bile acids may be useful to diagnose AD in plasma samples despite limitations in diagnostic accuracy., Competing Interests: Compliance with ethical standardsThe authors declare that they have no conflict of interest. TK is employed by Biocrates.The study was approved by the Ethics Committee of the Medical University of Innsbruck and was performed in accordance with the Helsinki Declaration. All subjects gave written informed consent. Data and material are available on request.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement., (Copyright © 2017 by the American Society for Biochemistry and Molecular Biology, Inc.)