imputomics: web server and R package for missing values imputation in metabolomics data.

MOTIVATION: Missing values are commonly observed in metabolomics data from mass spectrometry. Imputing them is crucial because it assures data completeness, increases the statistical power of analyses, prevents inaccurate results, and improves the quality of exploratory analysis, statistical modeling, and machine learning. Numerous Missing Value Imputation Algorithms (MVIAs) employ heuristics or statistical models to replace missing information with estimates. In the context of metabolomics data, we identified 52 MVIAs implemented across 70 R functions. Nevertheless, the usage of those 52 established methods poses challenges due to package dependency issues, lack of documentation, and their instability. RESULTS: Our R package, 'imputomics', provides a convenient wrapper around 41 (plus random imputation as a baseline model) out of 52 MVIAs in the form of a command-line tool and a web application. In addition, we propose a novel functionality for selecting MVIAs recommended for metabolomics data with the best performance or execution time. AVAILABILITY AND IMPLEMENTATION: 'imputomics' is freely available as an R package (github.com/BioGenies/imputomics) and a Shiny web application (biogenies.info/imputomics-ws). The documentation is available at biogenies.info/imputomics.

A single extraction 96-well method for LC-MS/MS quantification of urinary eicosanoids, steroids and drugs.

Urinary eicosanoid concentrations reflect inflammatory processes in multiple diseases and have been used as biomarkers of disease as well as suggested for patient stratification in precision medicine. However, implementation of urinary eicosanoid profiling in large-scale analyses is restricted due to sample preparation limits. Here we demonstrate a single solid-phase extraction of 300 µL urine in 96-well-format for prostaglandins, thromboxanes, isoprostanes, cysteinyl-leukotriene E4 and the linoleic acid-derived dihydroxy-octadecenoic acids (9,10- and 12,13-DiHOME). A simultaneous screening protocol was also developed for cortisol/cortisone and 7 exogenous steroids as well as 3 cyclooxygenase inhibitors. Satisfactory performance for quantification of eicosanoids with an appropriate internal standard was demonstrated for intra-plate analyses (CV = 8.5-15.1%) as well as for inter-plate (n = 35) from multiple studies (CV = 22.1-34.9%). Storage stability was evaluated at - 20 °C, and polar tetranors evidenced a 50% decrease after 5 months, while the remaining eicosanoids evidenced no significant degradation. All eicosanoids were stable over 3.5-years in urine stored at - 80 °C. This method will facilitate the implementation of urinary eicosanoid quantification in large-scale screening.

Simultaneous Comparison of Aqueous Humor and Serum Metabolic Profiles of Diabetic and Nondiabetic Patients Undergoing Cataract Surgery-A Targeted and Quantitative Metabolomics Study.

The aim of this study was to compare the aqueous humor (AH) and serum concentrations of metabolites in diabetic (n = 36) and nondiabetic (n = 36) senior adults undergoing cataract surgery. Blood samples were collected before surgery and AH during surgery. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomic and lipidomic analyses of samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites targeted by the kit, 41 and 133 were detected in >80% of AH and serum samples, respectively. Statistical analysis performed to indicate metabolites differentiating diabetic and nondiabetic patients showed 8 and 20 significant metabolites in AH and serum, respectively. Pathway analysis performed for significant metabolites revealed that galactose metabolism is mostly affected in the AH, while arginine biosynthesis is mostly affected in the serum. Among metabolites that differentiate diabetic and nondiabetic patients, arginine was the only metabolite common to both serum and AH samples, as well as the only one with a decreased concentration in both body fluids of diabetic patients. Concentrations of the rest were elevated in AH and lowered in serum. This may suggest different mechanisms of diabetes-related dysregulation of the local metabolism in the eye in comparison to systemic changes observed in the blood.

Elevated level of lysophosphatidic acid among patients with HNF1B mutations and its role in RCAD syndrome: a multiomic study.

INTRODUCTION: Patients with hepatocyte nuclear factor-1 beta (HNF1B) mutations present a variable phenotype with two main symptoms: maturity onset diabetes of the young (MODY) and polycystic kidney disease (PKD). OBJECTIVES: Identification of serum metabolites specific for HNF1Bmut and evaluation of their role in disease pathogenesis. METHODS: We recruited patients with HNF1Bmut (N = 10), HNF1Amut (N = 10), PKD: non-dialyzed and dialyzed (N = 8 and N = 13); and healthy controls (N = 12). Serum fingerprinting was performed by LC-QTOF-MS. Selected metabolite was validated by ELISA (enzyme-linked immunosorbent assay) measurements and then biologically connected with HNF1B by in silico analysis. HepG2 were stimulated with lysophosphatidic acid (LPA) and HNF1B gene was knocked down (kd) by small interfering RNA. Transcriptomic analysis with microarrays and western blot measurements were performed. RESULTS: Serum levels of six metabolites including: arachidonic acid, hydroxyeicosatetraenoic acid, linoleamide and three LPA (18:1, 18:2 and 20:4), had AUC (the area under the curve) > 0.9 (HNF1Bmut vs comparative groups). The increased level of LPA was confirmed by ELISA measurements. In HepG2HNF1Bkd cells LPA stimulation lead to downregulation of many pathways associated with cell cycle, lipid metabolism, and upregulation of steroid hormone metabolism and Wnt signaling. Also, increased intracellular protein level of autotaxin was detected in the cells. GSK-3alpha/beta protein level and its phosphorylated ratio were differentially affected by LPA stimulation in HNF1Bkd and control cells. CONCLUSIONS: LPA is elevated in sera of patients with HNF1Bmut. LPA contributes to the pathogenesis of HNF1B-MODY by affecting Wnt/GSK-3 signaling.

Applications of Metabolomics in Calcium Metabolism Disorders in Humans.

The pathogenesis of the disorders of calcium metabolism is not fully understood. This review discusses the studies in which metabolomics was applied in this area. Indeed, metabolomics could play an essential role in discovering biomarkers and elucidating pathological mechanisms. Despite the limited bibliography, the present review highlights the potential of metabolomics in identifying the biomarkers of some of the most common endocrine disorders, such as primary hyperparathyroidism (PHPT), secondary hyperparathyroidism (SHPT), calcium deficiency, osteoporosis and vitamin D supplementation. Metabolites related to above-mentioned diseorders were grouped into specific classes and mapped into metabolic pathways. Furthermore, disturbed metabolic pathways can open up new directions for the in-depth exploration of the basic mechanisms of these diseases at the molecular level.

A Preliminary Study Showing the Impact of Genetic and Dietary Factors on GC-MS-Based Plasma Metabolome of Patients with and without PROX1-Genetic Predisposition to T2DM up to 5 Years Prior to Prediabetes Appearance.

Risk factors for type 2 diabetes mellitus (T2DM) consist of a combination of an unhealthy, imbalanced diet and genetic factors that may interact with each other. Single nucleotide polymorphism (SNP) in the prospero homeobox 1 (PROX1) gene is a strong genetic susceptibility factor for this metabolic disorder and impaired ß-cell function. As the role of this gene in T2DM development remains unclear, novel approaches are needed to advance the understanding of the mechanisms of T2DM development. Therefore, in this study, for the first time, postprandial changes in plasma metabolites were analysed by GC-MS in nondiabetic men with different PROX1 genotypes up to 5 years prior to prediabetes appearance. Eighteen contestants (12 with high risk (HR) and 6 with low risk (LR) genotype) participated in high-carbohydrate (HC) and normo-carbohydrate (NC) meal-challenge tests. Our study concluded that both meal-challenge tests provoked changes in 15 plasma metabolites (amino acids, carbohydrates, fatty acids and others) in HR, but not LR genotype carriers. Postprandial changes in the levels of some of the detected metabolites may be a source of potential specific early disturbances possibly associated with the future development of T2DM. Thus, accurate determination of these metabolites can be important for the early diagnosis of this metabolic disease.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine.

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the "omics sciences", could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Metabolomics Reveal Altered Postprandial Lipid Metabolism After a High-Carbohydrate Meal in Men at High Genetic Risk of Diabetes.

BACKGROUND: The transcription factor 7-like 2 (TCF7L2) gene confers one of the strongest genetic predispositions to type 2 diabetes, but diabetes development can be modified by diet. OBJECTIVE: The aim of our study was to evaluate postprandial metabolic alterations in healthy men with a high genetic risk of diabetes, after two meals with varying macronutrient content. METHODS: The study was conducted in 21 homozygous nondiabetic men carrying the high-risk (HR, n = 8, age: 31.2 ± 6.3 y, body mass index (BMI, kg/m2) 28.5 ± 8.1) or low-risk (LR, n = 13, age: 35.2 ± 10.3 y, BMI: 28.1 ± 6.4) genotypes at the rs7901695 locus. During two meal challenge test visits subjects received standardized isocaloric (450 kcal) liquid meals: high-carbohydrate (HC, carbohydrates: 89% of energy) and normo-carbohydrate (NC, carbohydrates: 45% of energy). Fasting (0 min) and postprandial (30, 60, 120, 180 min) plasma samples were analyzed for metabolite profiles through untargeted metabolomics. Metabolic fingerprinting was performed on an ultra-high-performance liquid chromatography (UHPLC) system connected to an iFunnel quadrupole-time-of-flight (Q-TOF) mass spectrometer. RESULTS: In HR-genotype men, after the intake of an HC-meal, we noted a significantly lower area under the curves (AUCs) of postprandial plasma concentrations of most of the phospholipids (-37% to -53%, variable importance in the projection (VIP) = 1.2-1.5), lysophospholipids (-29% to -86%, VIP = 1.1-2.6), sphingolipids (-32% to -47%, VIP = 1.1-1.3), as well as arachidonic (-36%, VIP = 1.4) and oleic (-63%, VIP = 1.3) acids, their metabolites: keto- and hydoxy-fatty acids (-38% to -78%, VIP = 1.3-2.5), leukotrienes (-65% to -83%, VIP = 1.4-2.2), uric acid (-59%, VIP = 1.5), and pyroglutamic acid (-65%, VIP = 1.8). The AUCs of postprandial sphingosine concentrations were higher (125-832%, VIP = 1.9-3.2) after the NC-meal, AUCs of acylcarnitines were lower (-21% to -61%, VIP = 1.1-2.4), and AUCs of fatty acid amides were higher (51-508%, VIP = 1.7-3.1) after the intake of both meals. CONCLUSIONS: In nondiabetic men carrying the TCF7L2 HR genotype, subtle but detectable modifications in intermediate lipid metabolism are induced by an HC-meal. This trial was registered at www.clinicaltrials.gov as NCT03792685.

The MC4R genetic variants are associated with lower visceral fat accumulation and higher postprandial relative increase in carbohydrate utilization in humans.

PURPOSE: The interactions between lifestyle and genetic factors play an important role in obesity development. Mutations in melanocortin-4-receptor (MC4R) gene are one of the most common cause of monogenic obesity, however, the functional effects of polymorphic variants near MC4R gene in general populations remain uncertain. The aim of our study was to analyze whether the common single nucleotide polymorphisms (SNPs) of MC4R gene influence the food preferences, physical activity, body fat content and distribution, as well as fasting and postprandial energy expenditure and substrates utilization. METHODS: We genotyped previously identified MC4R SNPs: rs17782313, rs633265, rs1350341, rs12970134 in 927 subjects, who underwent anthropometric, total body fat content, visceral (VAT) and subcutaneous adipose tissue (SAT) measurements, and daily physical activity and dietary intake analysis. In randomly selected 47 subjects the energy expenditure, carbohydrate and lipid utilizations were evaluated in fasting state and after high-carbohydrate and control meals intake. RESULTS: We found the significant associations between studied SNPs of MC4R gene and VAT and VAT/SAT ratio. Moreover, the GG genotype carriers of rs1350341, who had the lowest VAT accumulation (p = 0.012), presented higher relative increase in postprandial carbohydrate utilization (p = 0.013, p = 0.024). CONCLUSIONS: We have observed that common SNPs of the MC4R gene influence the body fat content and distribution, as well as relative increase in postprandial carbohydrate utilization. We believe that our study may help to understand better the impact of MC4R gene on obesity development, and to help to provide personalized prevention/treatment strategies to fight against obesity and its metabolic consequences.

Untargeted metabolomics: an overview of its usefulness and future potential in prenatal diagnosis.

INTRODUCTION: Metabolomics opens up new avenues for biomarker discovery in different branches of medicine, including perinatology. Chromosomal aberration, preterm delivery (PTD), congenital heart defects, spina bifida, chorioamnionitis, and low birth weight are the main perinatal pathologies. Investigations using untargeted metabolomics have found the candidate metabolites for diagnostic biomarkers. Areas covered: This review describes areas of prenatal diagnosis in which untargeted metabolomics has been used. Data on the disease, type of sample, techniques used, number of samples used in the study, and metabolites obtained including the sign of their regulation are summarized. Expert commentary: Untargeted metabolomics is a powerful tool which can shed a new light on prenatal diagnostics. It helps to discover affected metabolic pathways what may help to reveal disease pathogenesis and propose potential biomarkers. Among others, glycerol and 2- and 3-hydroxybutyrate were proposed as markers of chromosomal aberration. Serum metabolic signature of PTD was characterized by increased lipids and decreased levels of hypoxanthine, tryptophane, and pyroglutamic acid. Lower level lipids and vitamin D3 metabolites together with increased bilirubin level in maternal serum were associated with macrosomia. However, to give a real value to those assays and allow their clinical application multicenter, large cohort validation studies are necessary.

An exploratory LC-MS-based metabolomics study reveals differences in aqueous humor composition between diabetic and non-diabetic patients with cataract.

Cataract is the leading cause of blindness worldwide. Epidemiological studies revealed up to a fivefold increased prevalence of cataracts in diabetic subjects. Metabolomics is nowadays frequently implemented to understand pathophysiological processes responsible for disease occurrence and progression. It has also been used recently to study the metabolic composition of aqueous humor (AH). AH is a transparent fluid which fills the anterior and posterior chambers of the eye. It supplies nutrients and removes metabolic waste from avascular tissues in the eye. The aim of this study was to use metabolomics to compare the AH of diabetic and non-diabetic patients undergoing cataract surgery. Several antioxidants (methyltetrahydrofolic acid, taurine, niacinamide, xanthine, and uric acid) were found decreased (-22 to -61%, p-value 0.05-0.003) in AH of diabetics. Also amino acids (AA) and derivatives were found decreased (-21 to -36%, p-value 0.05-0.01) while glycosylated AA increased (+75-98%, p-value 0.03-0.009) in this group of patients. Metformin was detected in AH of people taking this drug. To our knowledge, this is the first metabolomics study aiming to assess differences in AH composition between diabetic and non-diabetic patients with cataract. An increased oxidative stress and perturbations in amino acid metabolism in AH may be responsible for earlier cataract onset in diabetic patients.

Maternal plasma metabolic fingerprint indicative for fetal Down syndrome.

OBJECTIVE: The objective of the study was to perform maternal plasma metabolic fingerprinting to evaluate differences in plasma metabolites between healthy and Down syndrome (DS) pregnancies and to indicate novel non-invasive markers for DS prenatal diagnostics. METHODS: This was a case-control study of pregnancies between 15th and 18th gestational week. LC-MS-based metabolic fingerprinting of plasma samples was performed. RESULTS: Levels of five metabolites were significantly lower in the plasma of DS pregnancies. The majority of the statistically significant metabolites may be connected with fetal brain and central nervous system development (eg, fatty acid amides). According to the receiver operating characteristic (ROC), the combination of linoleamide and piperine has the highest diagnostic potential: area under the curve (AUC) = 0.878, sensitivity of 100%, and specificity of 73.3%. CONCLUSIONS: The study indicates disturbances in maternal metabolic pathways evoked by fetal DS. Novel potential maternal plasma metabolomic markers for non-invasive prenatal diagnostics of fetal DS are proposed.

In-and-Out Molecular Changes Linked to the Type 2 Diabetes Remission after Bariatric Surgery: An Influence of Gut Microbes on Mitochondria Metabolism.

Different kinds of gastrointestinal tract modulations known as "bariatric surgery" are actually the most effective treatment for obesity and associated co-morbidities, such as type 2 diabetes (T2DM). The potential causes of those effects have yet to be explained. In our study, we focused on molecular changes evoked by laparoscopic sleeve gastrectomy leading to T2DM remission. Two complementary metabolomics techniques, namely, liquid chromatography coupled with mass spectrometry (LC-MS) and gas chromatography mass spectrometry (GC-MS), were used to study those effects in a group of 20 obese patients with T2DM selected from a cohort of 372 obese individuals who underwent bariatric surgery and did not receive anti-diabetic treatment afterward. Modified levels of carnitines, lipids, amino acids (including BCAA) and α- and ß-hydroxybutyric acids were detected. Presented alterations suggest a major role of mitochondria activity in T2DM remission process. Moreover, some of the observed metabolites suggest that changes in gut microbiota composition may also correlate with the tempo of diabetes recovery. Additional analyses confirmed a relationship between biochemical and clinical parameters and the aforementioned metabolites, thereby, highlighting a role of mitochondria and microbes. Our data suggests that there is a previously undescribed relationship between mitochondria and gut microbiota, which changes after the bariatric surgery. More investigations are needed to confirm and explore the observed findings.

Serum Metabolic Fingerprinting Identified Putatively Annotated Sphinganine Isomer as a Biomarker of Wolfram Syndrome.

Wolfram syndrome (WFS) is an example of a rare neurodegenerative disease with coexisting endocrine symptoms including diabetes mellitus as the first clinical symptom. Treatment of WFS is still only symptomatic and associated with poor prognosis. Potential markers of disease progression that could be useful for possible intervention trials are not available. Metabolomics has potential to identify such markers. In the present study, serum fingerprinting by LC-QTOF-MS was performed in patients with WFS (n = 13) and in patients with T1D (n = 27). On the basis of the obtained results, aminoheptadecanediol (17:0 sphinganine isomer) (+50%, p = 0.02), as the most discriminatory metabolite, was selected for validation. The 17:0 sphinganine isomer level was determined using the LC-QQQ method in the samples from WFS patients at two time points and compared with samples obtained from patients with T1D (n = 24) and healthy controls (n = 24). Validation analysis showed higher 17:0 sphinganine isomer level in patients with WFS compared to patients with T1D (p = 0.0097) and control group (p < 0.0001) with progressive reduction of its level after two-year follow-up period. Patients with WFS show a unique serum metabolic fingerprint, differentiating them from patients with T1D. Sphinganine derivate seems to be a marker of the ongoing process of neurodegeneration in WFS patients.

Development of LC-QTOF-MS method for human lung tissue fingerprinting. A preliminary application to nonsmall cell lung cancer.

The major histologic subtypes of non-small cell lung cancer (NSCLC) include adenocarcinoma (ADC), squamous cell lung carcinoma (SCC), and large-cell carcinoma (LCC). Clinical trials of targeted agents and newer chemotherapy agents yielded differences in outcomes according to histologic subgroups providing a rationale for histology-based treatment in NSCLC. Currently, NSCLC subtyping is performed based on histopathological examinations and immunohistochemistry. However available methods leave about 10% of NSCLC cases as not otherwise specified. The purpose of this study was development of an LC-QTOF-MS method for human lung tissue metabolic fingerprinting that could discriminate NSCLC histological subtypes and propose biomarkers candidates that could support proper NSCLC diagnosis. Metabolites were extracted with acetonitrile or methanol/ethanol and different chromatographic conditions were tested. In the final method 10 mg of lung tissue was homogenized with 50% methanol and metabolites were extracted with acetonitrile. Metabolites were separated on C8-RP and HILIC columns. About 3500 and 2000 of metabolic features (in both ion modes) were detected with good repeatability (CV < 20%) by RP and HILIC methods, respectively. Lung tumor and control tissue samples obtained from NSCLC patients were analyzed with developed methodology. Acylcarnitines, fatty acids, phospholipids, and amino acids were found more abundant in tumor as compared to control tissue. Acylcarnitines, lysophospholipids, creatinine, creatine, and alanine were identified as potential targets enabling classification of NSCLC subtypes.

Applications of Metabolomics in Cancer Studies.

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

A Single In-Vial Dual Extraction Strategy for the Simultaneous Lipidomics and Proteomics Analysis of HDL and LDL Fractions.

A single in-vial dual extraction (IVDE) procedure for the subsequent analysis of lipids and proteins in the high-density lipoprotein (HDL) and low-density lipoprotein (LDL) fractions derived from the same biological sample is presented. On the basis of methyl-tert-butyl ether (MTBE) extraction, IVDE leads to the formation of three phases: a protein pellet at the bottom, an aqueous phase with polar compounds, and an ether phase with lipophilic compounds. After sample extraction, performed within a high-performance liquid chromatography vial insert, the ether phase was directly injected for lipid fingerprinting, while the protein pellet, after evaporation of the remaining sample, was used for proteomics analysis. Human HDL and LDL isolates were used to test the suitability of the IVDE methodology for lipid and protein analysis from a single sample in terms of data quality and matching composition to that of HDL and LDL. Subsequently, HDL and LDL fractions isolated from ApoE-KO and wild-type mice were used to validate the capacity of IVDE for revealing changes in lipid and protein abundance. Results indicate that IVDE can be successfully used for the subsequent analysis of lipids and proteins with the advantages of time saving, simplicity, and reduced sample amount.

Rapid and Reliable Identification of Phospholipids for Untargeted Metabolomics with LC-ESI-QTOF-MS/MS.

Lipids are important components of biological systems, and their role can be currently investigated by the application of untargeted, holistic approaches such as metabolomics and lipidomics. Acquired data are analyzed to find significant signals responsible for the differentiation between the investigated conditions. Subsequently, identification has to be performed to bring biological meaning to the obtained results. Lipid identification seems to be relatively easy due to the known characteristic fragments; however, the large number of structural isomers and the formation of different adducts makes it challenging and at risk of misidentification. The inspection of data, acquired for plasma samples by a standard metabolic fingerprinting method, revealed multisignal formations for phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins by the formation of ions such as [M + H](+), [M + Na](+), and [M + K](+) in positive ionization mode and [M - H](-), [M + HCOO](-), and [M + Cl](-) in negative mode. Moreover, sodium formate cluster formation was found for [M + H·HCOONa](+) and [H-H·HCOONa](-). The MS/MS spectrum obtained for each of the multi-ions revealed significant differences in the fragmentation, which were confirmed by the analysis of the samples in two independent research centers. After the inspection of an acquired spectra, a list of characteristic and diagnostic fragments was proposed that allowed for easy, quick, and robust lipid identification that provides information about the headgroup, formed adduct, and fatty acyl composition. This ensures successful identification, which is of great importance for the contextualization of data and results validation.

CE-MS-based serum fingerprinting to track evolution of type 2 diabetes mellitus.

Development of type 2 diabetes mellitus (T2DM) is preceded by insulin resistance (IR), which may evolve to impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT). IFG and IGT are considered as prediabetic states (PD). Prediabetes indicates the high risk for the future development of diabetes, it is estimated that up to 70% of prediabetics eventually develop T2DM. The risk of T2DM development is increased in overweight (OW) and obese (OB) people; however normal weight (NW) individuals also suffer from T2DM. The present study was designed to evaluate whether changes in polar metabolites induced by T2DM evolution are different between NW, overweight and obese individuals. CE-MS serum fingerprinting was performed on 197 serum samples obtained from OW, OB, and NW humans whom were IR, prediabetics, diabetics or with normal glucose homeostasis. Metabolic changes evoked by the progression of T2DM differ between obese, overweight, and normal weight subjects. Based on obtained results several metabolites can be proposed as a promising target to track T2DM evolution; BCAA in OW and NW humans, lysine in OB, while acetylcarnitine and methionine independently on body mass index. Validation of obtained results on larger population is required.