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Acetaminophen (APAP) is one of the most common antipyretic and analgesic drugs. Despite various precautions patients use APAP in amounts exceeding acceptable daily doses. APAP overdosing contributes to APAP intoxication, which leads to acute liver injury or necessity of exigent liver transplantation. Biomarkers that can be helpful in early diagnosis of liver injury during APAP overdosing are studied worldwide. This review presents recent reports on new potential biomarkers and their prospective application in clinical practice.

Objective. To profile maternal plasma metabolome in spontaneous preterm birth. Method. In this retrospective case-control study, we have examined plasma of patient with preterm birth (between 22 and 36 weeks of pregnancy (n=57)), with threatened preterm labor (between 23 and 36 weeks of pregnancy (n=49)), and with term delivery (n=25). Plasma samples were analysed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) in positive and negative polarity modes. Results. We found 168 differentially expressed metabolites that were significantly distinct between study groups. We determined 51 metabolites using publicly available databases that could be subdivided into one of the five groups: amino acids, fatty acids, lipids, hormones, and bile acids. PLS-DA models, verified by SVM classification accuracy, differentiated preterm birth and term delivery groups. Conclusions. Maternal plasma metabolites are different between term and preterm parturitions. Part of them may be related with preterm labor, while others may be affected by gestational age or the beginning of labor. Metabolite profile can classify preterm or term delivery groups raising the potential of metabolome as a biomarker to identify high-risk pregnancies. Metabolomic studies are also a tool to detect individual compounds that may be further tested in targeted researches.

Abdominal aortic aneurysm (AAA) is an important health problem, both because of AAA rupture and death and because of increased cardiovascular mortality. Identification of new biomarkers of AAA may suggest novel pathological mechanisms and targets for new medical treatments to slow AAA progression. Metabolic changes in AAA patients were mainly related to carbohydrate and lipid metabolism and many of these changes can be associated with a situation of insulin resistance (which can be related to metabolic syndrome) together with altered amino acid metabolism. For the first time, metabolites that can be associated with differential metabolism by the gut microflora of AAA patients have also been found. Moreover, aminomalonic acid in plasma has been shown to be the metabolite with the biggest difference between patients suffering from large aneurysm (>5 cm) and controls.

Metabolite fingerprinting (metabolomics/metabonomics) is perfectly suited for assessing the biological response following acute coronary syndrome (ACS) as relevant information can be identified in both the change and the absence of change in metabolite concentrations as time progresses post syndrome. During this study the metabolic pattern of plasma from patients at time points 0, four days, two months and six months after the onset of ACS were compared to controls using a non-targeted approach with gas chromatography mass spectrometry (GC-MS). Fatty acid profiles of the sample set were also analysed in a targeted way. The methods were employed with the aim to identify specific biomarkers, which vary with time. Using the non-targeted approach 27 statistically significant metabolites of interest were found: glucose, fructose, myoinositol, pyruvate, lactate, oxalate, citrate, isocitrate, succinate, malate, valine, alanine, serine, glycine, cysteine, threonine, aspartate, tryptophan, tyrosine, 4-hydroxyproline, 2-hydroxybutyrate, 2-aminobutyrate, 2,3,4-trihydroxybutyrate, 3-hydroxybutyrate, creatinine and aminomalonate. In addition, the targeted analysis of 21 fatty acids revealed patients within the group ACS at day 0 had the highest values for all 21. After 4 days, values decreased and were maintained at a lower level during the 6 months. Whereas the overall fatty acid profile did not change, different patterns of concentration trajectories over time were identified, which can reflect the underlying metabolic alterations as a result of the initial ACS, interestingly these levels had not fully reverted six months later.

Propolis is a resin that is collected by honeybees from various plant sources. Due to its pharmacological properties, it is used in commercial production of nutritional supplements in pharmaceutical industry. In this study, gas chromatography–mass spectrometry was applied for quality control analysis of the three commercial specimens containing aqueous-alcoholic extracts of bee propolis. More than 230 constituents were detected in analyzed products, including flavonoids, chalcones, cinnamic acids and their esters, phenylpropenoid glycerides, and phenylpropenoid sesquiterpenoids. An allergenic benzyl cinnamate ester was also identified in all tested samples. This analytical method allows to evaluate biological activity and potential allergenic components of bee glue simultaneously. Studies on chemical composition of propolis samples may provide new approach to quality and safety control analysis in production of propolis supplementary specimens.

Abdominal aortic aneurysm (AAA) is a permanent and localized aortic dilation, defined as aortic diameter ≥3 cm. It is an asymptomatic but potentially fatal condition because progressive enlargement of the abdominal aorta is spontaneously evolving towards rupture. Biomarkers may help to explain pathological processes of AAA expansion, and allow us to find novel therapeutic strategies or to determine the efficiency of current therapies. Metabolomics seems to be a good approach to find biomarkers of AAA. In this study, plasma samples of patients with large AAA, small AAA, and controls were fingerprinted with LC-QTOF-MS. Statistical analysis was used to compare metabolic fingerprints and select metabolites that showed a significant change. Results presented here reveal that LC-QTOF-MS based fingerprinting of plasma from AAA patients is a very good technique to distinguish small AAA, large AAA, and controls. With the use of validated PLS-DA models it was possible to classify patients according to the disease stage and predict properly the stage of additional AAA patients. Identified metabolites indicate a role for sphingolipids, lysophospholipids, cholesterol metabolites, and acylcarnitines in the development and progression of AAA. Moreover, guanidinosuccinic acid, which mimics nitric oxide in terms of its vasodilatory action, was found as a strong marker of large AAA, The paper has been supported by Comunidad Autónoma de Madrid (CAM) (S2006/GEN-0247), the European Community Fighting Aneurysmal Disease (FAD) project (FP-7, HEALTH F2-2008-200647), the Spanish Ministerio de Ciencia y Tecnología (SAF2010/21852 and CTQ2008-03779), Ministerio de Sanidad y Consumo, Instituto de Salud Carlos III, Redes Red Temática de Investigación Cooperativa en Enfermedades Cardiovasculares (RECAVA) (RD06/0014/0035), European Aeronautic Defence and Space Company - Construcciones Aeronáuticas Sociedad Anónima (EADSCASA), and EUS2008-03565

The plasma of patients with stable carotid atherosclerosis (n = 9), and healthy subjects (n = 10) have been fingerprinted with both GC-MS and (1)H NMR. Principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) have been applied to the profiles from each technique both separately and in combination. These techniques complement each other and enable a clearer picture of the biological samples to be interpreted not only for classification purposes, but also more importantly to define the metabolic state of patients with carotid atherosclerosis. The results showed at least 24 metabolites that were significantly modified in the group of atherosclerotic patients by this nontargeted procedure. Most of the changes can be associated to alterations of the metabolism characteristics of insulin resistance that can be strongly related to the metabolic syndrome. In addition, correlations among variables accounting for the classification show amino acids as variables whose changes showed a high degree of correlation. GC-MS and (1)H NMR fingerprints can provide complementary information in the identification of altered metabolic pathways in patients with carotid atherosclerosis. Moreover, correlations among the results with both techniques, instead of a single study, can provide a deeper insight into the patient state.