Metabolomics is a powerful tool for identifying both known and new disease-related perturbations in metabolic pathways. In preclinical drug testing, it has a high potential for early identification of drug off-target effects. Recent advances in high-precision high-throughput mass spectrometry have brought the metabolomic field to a point where quantitative, targeted, metabolomic measurements with ready-to-use kits allow for the automated in-house screening for hundreds of different metabolites in large sets of biological samples. Today, the field of metabolomics is, arguably, at a point where transcriptomics was about 5 yr ago. This being so, the field has a strong need for adapted bioinformatics tools and methods. In this paper we describe a systematic analysis of a targeted quantitative characterization of more than 800 metabolites in blood plasma samples from healthy and diabetic mice under rosiglitazone treatment. We show that known and new metabolic phenotypes of diabetes and medication can be recovered in a statistically objective manner. We find that concentrations of methylglutaryl carnitine are oppositely impacted by rosiglitazone treatment of both healthy and diabetic mice. Analyzing ratios between metabolite concentrations dramatically reduces the noise in the data set, allowing for the discovery of new potential biomarkers of diabetes, such as the N-hydroxyacyloylsphingosyl-phosphocholines SM(OH)28:0 and SM(OH)26:0. Using a hierarchical clustering technique on partial eta(2) values, we identify functionally related groups of metabolites, indicating a diabetes-related shift from lysophosphatidylcholine to phosphatidylcholine levels. The bioinformatics data analysis approach introduced here can be readily generalized to other drug testing scenarios and other medical disorders.

In the past few years, high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) has matured to a true alternative to antibody-based immunoassays in routine therapeutic drug monitoring. In transplantation medicine, mass spectrometry-based assessment of immunosuppressant drug levels is considered a gold standard diagnostic procedure. We describe a fast state-of-the-art routine online solid-phase extraction (SPE) HPLC-MS/MS analysis platform that allows monitoring of cyclosporine A, tacrolimus, sirolimus and everolimus from 50-microl aliquots of EDTA whole blood specimens within 3.4 min total analysis time. Sample purification is done by offline protein precipitation followed by two automated chromatographic separation steps. Mass spectrometry-based analyte quantification relies on selected reaction monitoring experiments. The assay underwent complete validation and performance evaluation studies and performs very well in several international proficiency testing schemes. In daily routine, it allows reporting of about 75 patient sample results per work shift with a typical total individual sample turnaround time of less than 3 h.

Unprecedented demands are now placed on clinicians for early diagnosis as we enter into an era of advancing treatment opportunities for the mucopolysaccharidoses (MPS). Biochemical monitoring of any therapeutic avenue will also be prerequisite. To this end, we aimed to identify a range of urinary oligosaccharides that could be used to identify and characterize patients with MPS. We analyzed 94 urine samples from 68 patients with MPS and 26 control individuals for oligosaccharides derived from glycosaminoglycans using electrospray ionization-tandem mass spectrometry. The oligosaccharide profile for each patient group was compared with that of the control group. The Mann-Whitney U test was used to measure the difference between each patient group and the controls for each analyte. Urine samples from patients before and at successive times after bone marrow transplantation were also evaluated. A number of oligosaccharides were identified in the urine of each MPS subtype, and for each of these, specific oligosaccharide profiles were formulated. These profiles enabled the identification of all 68 patients and their subtypes with the exception of MPS IIIB and IIIC. Selected oligosaccharides were used to assess three individuals after a bone marrow transplant, and, in each case, a substantial reduction in the level of diagnostic oligosaccharides, posttransplantation, was observed. The identification and measurement of glycosaminoglycan-derived oligosaccharides in urine provides a sensitive and specific screen for the early identification of individuals with MPS. The resulting oligosaccharide profiles not only characterize subtype but also provide a disease-specific fingerprint for the biochemical monitoring of current and proposed therapies. The mucopolysaccharidoses (MPS) are a group of inherited lysosomal storage disorders characterized by a deficiency in one of the lysosomal enzymes required to degrade glycosaminoglycans (GAG). There are 11 known enzyme deficiencies that give rise to seven distinct types of MPS, with a combined incidence of~1 in 16,000 (1). In all MPS subtypes, partially degraded GAG accumulate in the lysosomes of affected cells and/or are excreted in the urine. The lysosomal storage of GAG leads to the chronic and progressive deterioration of cells, tissues, and organs (2). The MPS share many clinical manifestations, including organomegaly, abnormal facial features, and dysostosis multiplex. Impaired hearing, vision, and joint mobility, as well as abnormal airway and cardiovascular function, are common, although there is wide clinical heterogeneity within each enzyme deficiency. Profound mental retardation is characteristic of the severe forms of MPS I, II, and VII and all subtypes of MPS III. Similar and severe skeletal and joint abnormalities are present in MPS I, II, VI, and VII, whereas MPS IV develops different skeletal pathology.The clinical management for MPS is changing, as new treatment options, such as enzyme replacement therapy, that will complement and replace bone marrow transplantatio...

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The small amount of 20 microL sample volume used in this assay and the demonstrated application to various sample types makes it an ideal routine analysis method for fatty acid metabolites. The resulting values for LOX-derived metabolites in diabetes mellitus type 2 samples support earlier findings about the role of lipid oxidation products in diabetes.