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Background: The incidence of many diseases increases with age and leads to multimorbidity, characterized by the presence of multiple diseases in old age. This phenomenon is closely related to systemic metabolic changes; the most suitable way to study it is through metabolomics. The use of accumulated metabolomic data to characterize this phenomenon at the system level may provide additional insight into the nature and strength of aging–disease relationships. Methods: For this purpose, metabolic changes associated with human aging and metabolic alterations under different pathological conditions were compared. To do this, the published results of metabolomic studies on human aging were compared with data on metabolite alterations collected in the human metabolome database through metabolite set enrichment analysis (MSEA) and combinatorial analysis. Results: It was found that human aging and pathological conditions involve the set of the same metabolic pathways with a probability of 99.96%. These data show the high identity of the aging process and the development of diseases at the metabolic level and allow to identify the set of metabolic pathways reflecting age-related changes closely associated with health. Based on these pathways, a metapathway was compiled, changes in which are simultaneously associated with health and age. Conclusions: The knowledge about the strength of the convergence of aging and pathological conditions has been supplemented by the rigor evidence at the metabolome level, which also made it possible to outline the age and health-relevant place in the human metabolism. [ABSTRACT FROM AUTHOR]

Simple Summary: Renal cell carcinoma (RCC) is one of the most common cancer types. However, the lack of clinical symptoms and validated biomarkers for early stage RCC prevent timely disease diagnosis. The study was focused on revealing potential low molecular biomarkers for early-stage RCC. The untargeted direct injection mass spectrometry-based metabolite profiling of blood plasma samples from non-cancer volunteers (control) and RCC patients (early stages of clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chrRCC), and advanced stages of ccRCC) was performed. A set of metabolites with diagnostic power for the early stages of ccRCC was detected. Early diagnostics significantly improves the survival of patients with renal cell carcinoma (RCC), which is the prevailing type of adult kidney cancer. However, the absence of clinically obvious symptoms and effective screening strategies at the early stages result to disease progression and survival rate reducing. The study was focused on revealing of potential low molecular biomarkers for early-stage RCC. The untargeted direct injection mass spectrometry-based metabolite profiling of blood plasma samples from 51 non-cancer volunteers (control) and 78 patients with different RCC subtypes and stages (early stages of clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chrRCC) and advanced stages of ccRCC) was performed. Comparative analysis of the blood plasma metabolites between the control and cancer groups provided the detection of metabolites associated with different tumor stages. The designed model based on the revealed metabolites demonstrated high diagnostic power and accuracy. Overall, using the metabolomics approach the study revealed the metabolites demonstrating a high value for design of plasma-based test to improve early ccRCC diagnosis. [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]

A laboratory-developed test (LDT) is a type of in vitro diagnostic test that is developed and used within a single laboratory. The holistic metabolomic LDT integrating the currently available data on human metabolic pathways, changes in the concentrations of low-molecular-weight compounds in the human blood during diseases and other conditions, and their prevalent location in the body was developed. That is, the LDT uses all of the accumulated metabolic data relevant for disease diagnosis and high-resolution mass spectrometry with data processing by in-house software. In this study, the LDT was applied to diagnose early-stage Parkinson's disease (PD), which currently lacks available laboratory tests. The use of the LDT for blood plasma samples confirmed its ability for such diagnostics with 73% accuracy. The diagnosis was based on relevant data, such as the detection of overrepresented metabolite sets associated with PD and other neurodegenerative diseases. Additionally, the ability of the LDT to detect normal composition of low-molecular-weight compounds in blood was demonstrated, thus providing a definition of healthy at the molecular level. This LDT approach as a screening tool can be used for the further widespread testing for other diseases, since 'omics' tests, to which the metabolomic LDT belongs, cover a variety of them. [ABSTRACT FROM AUTHOR]

The dried blood spot (DBS) sampling has a lot of advantages in comparison with the "standard" venous blood collecting, such as small collection volume, painless and easy sample collection with minimal training required, stable and transportable at ambient temperatures, etc. The aim of this study was to determine the comparability of four different types of DBS sampling (HemaSpot™-HF Blood Collection Device, Whatman® 903 Protein Saver Snap Apart Card, card ImmunoHealth™, and glass fiber strip ImmunoHealth™) for analysis of the global metabolites profile. All the samples were collected from the same person at the same time and stored at room temperature for four weeks in order to exclude all possible deviations deriving from biological variances and to evaluate sample storage stability. Metabolome profiling by direct injection of a deproteinized capillary blood DBS sample into an electrospray ion source of a hybrid quadrupole time-of-flight mass spectrometer was used. Differences in the metabolomics profile were found between the different DBS collection materials, especially for ImmunoHealth™ card and ImmunoHealth™ glass fiber strip. However, our results indicate that the analytical performance of all tested DBS sampling materials showed consistent results overall detected metabolites and no dramatic changes between them in the metabolic composition during the storage time. [ABSTRACT FROM AUTHOR]