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The clinical blood metabogram (CBM) was developed to match a tailored analysis of the blood metabolome to the time, cost, and reproducibility constraints of clinical laboratory testing. By analyzing the main blood metabolite groups, CBM offers clinically relevant information about the intake of low-molecular substances into the organism, humoral regulation, liver function, amino acid level, and the lipid and carbohydrate metabolism. The purpose of this work was to investigate the relevance of using the CBM in patients with diabetes mellitus. For this, a CBM was obtained for 18 healthy individuals, 12 individuals with prediabetes, and 64 individuals with type 2 diabetes mellitus, separated into groups according to fasting blood glucose and oral glucose tolerance tests. The results showed that the CBM reveals diabetes-associated metabolic alterations in the blood, including changes in the levels of carbohydrates, ketone bodies, eicosanoids, phospholipids, and amino acids, which are consistent with the scientific data available to date. The CBM enabled the separation of diabetic patients according to their metabolic metabotypes, providing both a general overview of their metabolic alterations and detailing their individual metabolic characteristics. It was concluded that the CBM is a precise and clinically applicable test for assessing an individual's metabolic status in diabetes mellitus for diagnostic and treatment purposes. [ABSTRACT FROM AUTHOR]

In metabolomics, a large number of small molecules can be detected in a single run. However, metabolomic data do not include the absolute concentrations of each metabolite. Generally, mass spectrometry analyses provide metabolite concentrations that are derived from mass peak intensities, and the peak intensities are strictly dependent on the type of mass spectrometer used, as well as the technical characteristics, options and protocols applied. To convert mass peak intensities to actual concentrations, calibration curves have to be generated for each metabolite, and this represents a significant challenge depending on the number of metabolites that are detected and involved in metabolome-based diagnostics. To overcome this limitation, and to facilitate the development of diagnostic tests based on metabolomics, mass peak intensities may be expressed in quintiles. The present study demonstrates the advantage of this approach. The examples of diagnostic signatures, which were designed in accordance to this approach, are provided for lung and prostate cancer (leading causes of mortality due to cancer in developed countries) and impaired glucose tolerance (which precedes type 2 diabetes, the most common endocrinology disease worldwide). [ABSTRACT FROM AUTHOR]

The goal of this study was to evaluate the capacity for mass spectrometry of blood plasma to diagnose impaired glucose tolerance (IGT). For this study, blood plasma samples from control subjects (n = 30) and patients with IGT (n = 20) were treated with methanol and low molecular weight fraction were then analyzed by direct infusion mass spectrometry. A total of 51 metabolite ions strongly associated with IGT were detected. The area under a receiver operating characteristic (ROC) curve (AUC) for diagnosing IGT that was based on an analysis of all these metabolites was 0.93 (accuracy 90%, specificity 90%, and sensitivity 90%). The associated reproducibility was 85%. The metabolites identified were also consistent with risk factors previously associated with the development of diabetes. Thus, direct infusion mass spectrometry of blood plasma metabolites represents a rapid, single-step, and reproducible method for the analysis of metabolites. Moreover, this method has the potential to serve as a prototype for clinical analyses that could replace the currently used glucose tolerance test with a more patient-friendly assay. [ABSTRACT FROM AUTHOR]

In metabolomics, mass spectrometry is used to detect a large number of low-molecular substances in a single analysis. Such a capacity could have direct application in disease diagnostics. However, it is challenging because of the analysis complexity, and the search for a way to simplify it while maintaining the diagnostic capability is an urgent task. It has been proposed to use the metabolomic signature without complex data processing (mass peak detection, alignment, normalization, and identification of substances, as well as any complex statistical analysis) to make the analysis more simple and rapid. Methods: A label-free approach was implemented in the metabolomic signature, which makes the measurement of the actual or conditional concentrations unnecessary, uses only mass peak relations, and minimizes mass spectra processing. The approach was tested on the diagnosis of impaired glucose tolerance (IGT). Results: The label-free metabolic signature demonstrated a diagnostic accuracy for IGT equal to 88% (specificity 85%, sensitivity 90%, and area under receiver operating characteristic curve (AUC) of 0.91), which is considered to be a good quality for diagnostics. Conclusions: It is possible to compile label-free signatures for diseases that allow for diagnosing the disease in situ, i.e., right at the mass spectrometer without complex data processing. This achievement makes all mass spectrometers potentially versatile diagnostic devices and accelerates the introduction of metabolomics into medicine. [ABSTRACT FROM AUTHOR]