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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 β-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.

Due to many adverse effects of gestational diabetes mellitus (GDM) on the mother and fetus, its diagnosis is crucial. The presence of GDM can be confirmed by an abnormal fasting plasma glucose level (aFPG) and/or oral glucose tolerance test (OGTT) performed mostly between 24 and 28 gestational week. Both aFPG and abnormal glucose tolerance (aGT) are used to diagnose GDM. In comparison to measurement of FPG, OGTT is time-consuming, usually inconvenient for the patient, and very often needs to be repeated. Therefore, it is necessary to seek tests that will be helpful and convenient to diagnose GDM. For this reason, we investigated the differences in fasting serum metabolites between GDM women with abnGM and normal FPG (aGT-GDM group), with aFPG and normal glucose metabolism (aFPG-GDM group) as well as pregnant women with normal glucose tolerance (NGT) being a control group. Serum metabolites were measured by an untargeted approach using gas chromatography–mass spectrometry (GC–MS). In the discovery phase, fasting serum samples collected from 79 pregnant women (aFPG-GDM, n = 24; aGT-GDM, n = 26; NGT, n = 29) between 24 and 28 weeks of gestation (gwk) were fingerprinted. A set of metabolites (α–hydroxybutyric acid (α–HB), β–hydroxybutyric acid (β–HB), and several fatty acids) significant in aGT-GDM vs NGT but not significant in aFPG-GDM vs NGT comparison in the discovery phase was selected for validation. These metabolites were quantified by a targeted GC–MS method in a validation cohort consisted of 163 pregnant women (aFPG-GDM, n = 51; aGT-GDM, n = 44; and NGT, n = 68). Targeted analyses were also performed on the serum collected from 92 healthy women in the first trimester (8–14 gwk) who were NGT at this time, but in the second trimester (24–28 gwk) they were diagnosed with GDM. It was found that α–HB, β–HB, and several fatty acids were associated with aGT-GDM. A combination of α–HB, β–HB, and myristic acid was found highly specific and sensitive for the diagnosis of GDM manifested by aGT-GDM (AUC = 0.828) or to select women at a risk of aGT-GDM in the first trimester (AUC = 0.791). Our findings provide new potential markers of GDM and may have implications for its early diagnosis.

Adipose tissue has been the subject of research for a very long time. Many studies perform a comprehensive analysis of different types of adipose tissue with an emphasis on brown adipose tissue. Mass spectrometry-based approaches are particularly useful in the exploration not only of the metabolic composition of adipose tissue but also its function. In the presented review, a complex and critical overview of publications devoted to the analysis of adipose tissue by means of mass spectrometry was performed. Detailed investigation of analytical aspects related to either untargeted or targeted analysis of adipose tissue was performed, leading to the formation of a collection of hints at the available analytical methods. Moreover, a profound analysis of the metabolic composition of brown adipose tissue was performed. Brown adipose tissue metabolome was characterized on structural and functional levels, providing information about its exact metabolic composition but also connecting these molecules and placing them into biochemical pathways. All our work resulted in a very broad picture of the analysis of adipose tissue, starting from the analytical aspects and finishing on the current knowledge about its composition.

This paper presents, for the first time, results for chlorpyrifos (CHLP) in Polish fruits and vegetables over the course of a long period of research, 2007–2016, with toxicological aspects. The challenge of this study was to re–evaluate the impact of chlorpyrifos residues in fruit and vegetables on health risk assessed via acute and chronic exposure based on old and new, lower, established values of: Average Daily Intakes (ADIs)/Acute Reference Doses (ARfDs) and Maximum Residue Levels (MRLs). A total of 3 530 samples were collected, and CHLP in the range of 0.005–1.514 mg/kg was present in 10.2% of all samples. The MRL was exceeded in 0.7% of all samples (MRL established in 2009–2015), and recalculation yielded a much greater number of violations for the new MRL (2016), which exceeded 2.9% of all samples. Acute exposure to CHLP calculated according to the old, higher toxicological data (0.10 mg/kg bw/day), does not exceed 14% of its respective ARfDs for adults and both groups of children, but when calculated for incidental cases according to the current value (ARfD 0.005 mg/kg bw) for infants and toddlers, was above 100% of its respective ARfDs in: white cabbage (263.65% and 108.24%), broccoli (216.80% and 194.72%) and apples (153.20% and 167.70%). The chronic exposure calculated for both newly established ADI values (0.001 mg/kg bw/day and 0.100 mg/kg bw/day) appears to be relatively low for adults and children.

Diabetes mellitus, a disease of modern civilization, is considered the major mainstay of mortalities around the globe. A great number of biochemical changes have been proposed to occur at metabolic levels between perturbed glucose, amino acid, and lipid metabolism to finally diagnoe diabetes mellitus. This window period, which varies from person to person, provides us with a unique opportunity for early detection, delaying, deferral and even prevention of diabetes. The early detection of hyperglycemia and dyslipidemia is based upon the detection and identification of biomarkers originating from perturbed glucose, amino acid, and lipid metabolism. The emerging “OMICS” technologies, such as metabolomics coupled with statistical and bioinformatics tools, proved to be quite useful to study changes in physiological and biochemical processes at the metabolic level prior to an eventual diagnosis of DM. Approximately 300–400 such metabolites have been reported in the literature and are considered as predicting or risk factor-reporting metabolic biomarkers for this metabolic disorder. Most of these metabolites belong to major classes of lipids, amino acids and glucose. Therefore, this review represents a snapshot of these perturbed plasma/serum/urinary metabolic biomarkers showing a significant correlation with the future onset of diabetes and providing a foundation for novel early diagnosis and monitoring the progress of metabolic syndrome at early symptomatic stages. As most metabolites also find their origin from gut microflora, metabolism and composition of gut microflora also vary between healthy and diabetic persons, so we also summarize the early changes in the gut microbiome which can be used for the early diagnosis of diabetes.