Chitosan Film as a Replacement for Conventional Sulphur Dioxide Treatment of White Wines: A 1H NMR Metabolomic Study.

Chitosan-genipin (Ch-Ge) films have been proposed for the replacement of sulfur dioxide (SO2) in white wines preservation to circumvent the adverse health consequences caused by SO2 intake. To assess the effects of different-sized Ch-Ge films (25 and 100 cm2) on wine composition compared to SO2-treated and untreated wines, nuclear magnetic resonance metabolomics was applied. Relative to SO2, 100 cm2 films induced significant changes in the levels of organic acids, sugars, amino acids, 5-hydroxymethylfurfural, among other compounds, while 25 cm2 films appeared to induce only small variations. The observed metabolite variations were proposed to arise from the mitigation of fermentative processes, electrostatic interactions between acids and the positively charged films and the promotion of Maillard and Strecker reactions. Qualitative sensory analysis showed that wines maintained overall appropriate sensory characteristics, with 100 cm2 film treated wines showing slightly higher attributes. Based on these results, the possibility of using Ch-Ge films as a replacement for SO2 treatment is discussed.

The role of NAD metabolism in neuronal differentiation.

BACKGROUND: Nicotinamide adenine dinucleotide (NAD) metabolism is involved in redox and non-redox reactions that regulate several processes including differentiation of cells of different origins. Here, the role of NAD metabolism in neuronal differentiation, which remains elusive so far, was investigated. MATERIAL AND METHODS: A protein-protein interaction network between neurotrophin signaling and NAD metabolic pathways was built. Expression of NAD biosynthetic enzymes in SH-SY5Y cells during retinoic acid (RA)/brain derived neurotrophic factor (BDNF) differentiation, was evaluated. The effects of NAD biosynthetic enzymes QPRT and NAPRT inhibition in neurite outgrowth, cell viability, NAD availability and histone deacetylase (HDAC) activity, were analyzed in RA- and BDNF-differentiated cells. RESULTS: Bioinformatics analysis revealed the interaction between NAD biosynthetic enzyme NMNAT1 and NTRK2, a receptor activated by RA/BDNF sequential treatment. Differences were found in the expression of NAD biosynthetic enzymes during neuronal differentiation, namely, increased QPRT gene expression along the course of RA/BDNF treatment and NAPRT protein expression after a 5-day treatment with RA. QPRT inhibition in BDNF-differentiated SH-SY5Y cells resulted in less neuritic length per cell, decreased expression of the neuronal marker ß-III Tubulin and also decreased NAD+ levels and HDAC activity. NAPRT inhibition had no effect in neuritic length per cell, NAD+ levels and HDAC activity. Of note, NAD supplementation along with RA, but not with BDNF, resulted in considerable cell death. CONCLUSIONS: Taken together, our results show the involvement of NAD metabolism in neuronal differentiation, specifically, the importance of QPRT-mediated NAD biosynthesis in BDNF-associated SH-SY5Y differentiation and suggest additional roles for NAPRT beyond NAD production in RA-differentiated cells.

The Long-Term Culture of Human Fibroblasts Reveals a Spectroscopic Signature of Senescence.

Aging is a complex process which leads to progressive loss of fitness/capability/ability, increasing susceptibility to disease and, ultimately, death. Regardless of the organism, there are some features common to aging, namely, the loss of proteostasis and cell senescence. Mammalian cell lines have been used as models to study the aging process, in particular, cell senescence. Thus, the aim of this study was to characterize the senescence-associated metabolic profile of a long-term culture of human fibroblasts using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopy. We sub-cultivated fibroblasts from a newborn donor from passage 4 to passage 17 and the results showed deep changes in the spectroscopic profile of cells over time. Late passage cells were characterized by a decrease in the length of fatty acid chains, triglycerides and cholesterol and an increase in lipid unsaturation. We also found an increase in the content of intermolecular ß-sheets, possibly indicating an increase in protein aggregation levels in cells of later passages. Metabolic profiling by NMR showed increased levels of extracellular lactate, phosphocholine and glycine in cells at later passages. This study suggests that spectroscopy approaches can be successfully used to study changes concomitant with cell senescence and validate the use of human fibroblasts as a model to monitor the aging process.

Endo- and Exometabolome Crosstalk in Mesenchymal Stem Cells Undergoing Osteogenic Differentiation.

This paper describes, for the first time to our knowledge, a lipidome and exometabolome characterization of osteogenic differentiation for human adipose tissue stem cells (hAMSCs) using nuclear magnetic resonance (NMR) spectroscopy. The holistic nature of NMR enabled the time-course evolution of cholesterol, mono- and polyunsaturated fatty acids (including ω-6 and ω-3 fatty acids), several phospholipids (phosphatidylcholine, phosphatidylethanolamine, sphingomyelins, and plasmalogens), and mono- and triglycerides to be followed. Lipid changes occurred almost exclusively between days 1 and 7, followed by a tendency for lipidome stabilization after day 7. On average, phospholipids and longer and more unsaturated fatty acids increased up to day 7, probably related to plasma membrane fluidity. Articulation of lipidome changes with previously reported polar endometabolome profiling and with exometabolome changes reported here in the same cells, enabled important correlations to be established during hAMSC osteogenic differentiation. Our results supported hypotheses related to the dynamics of membrane remodelling, anti-oxidative mechanisms, protein synthesis, and energy metabolism. Importantly, the observation of specific up-taken or excreted metabolites paves the way for the identification of potential osteoinductive metabolites useful for optimized osteogenic protocols.

NMR Metabolomics Assessment of Osteogenic Differentiation of Adipose-Tissue-Derived Mesenchymal Stem Cells.

This Article presents, for the first time to our knowledge, an untargeted nuclear magnetic resonance (NMR) metabolomic characterization of the polar intracellular metabolic adaptations of human adipose-derived mesenchymal stem cells during osteogenic differentiation. The use of mesenchymal stem cells (MSCs) for bone regeneration is a promising alternative to conventional bone grafts, and untargeted metabolomics may unveil novel metabolic information on the osteogenic differentiation of MSCs, allowing their behavior to be understood and monitored/guided toward effective therapies. Our results unveiled statistically relevant changes in the levels of just over 30 identified metabolites, illustrating a highly dynamic process with significant variations throughout the whole 21-day period of osteogenic differentiation, mainly involving amino acid metabolism and protein synthesis; energy metabolism and the roles of glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation; cell membrane metabolism; nucleotide metabolism (including the specific involvement of O-glycosylation intermediates and NAD+); and metabolic players in protective antioxidative mechanisms (such as glutathione and specific amino acids). Different metabolic stages are proposed and are supported by putative biochemical explanations for the metabolite changes observed. This work lays the groundwork for the use of untargeted NMR metabolomics to find potential metabolic markers of osteogenic differentiation efficacy.

FTIR Spectroscopy as a Tool to Study Age-Related Changes in Cardiac and Skeletal Muscle of Female C57BL/6J Mice.

Studying aging is important to further understand the molecular mechanisms underlying this physiological process and, ideally, to identify a panel of aging biomarkers. Animals, in particular mice, are often used in aging studies, since they mimic important features of human aging, age quickly, and are easy to manipulate. The present work describes the use of Fourier Transform Infrared (FTIR) spectroscopy to identify an age-related spectroscopic profile of the cardiac and skeletal muscle tissues of C57BL/6J female mice. We acquired ATR-FTIR spectra of cardiac and skeletal muscle at four different ages: 6; 12; 17 and 24 months (10 samples at each age) and analyzed the data using multivariate statistical tools (PCA and PLS) and peak intensity analyses. The results suggest deep changes in protein secondary structure in 24-month-old mice compared to both tissues in 6-month-old mice. Oligomeric structures decreased with age in both tissues, while intermolecular ß-sheet structures increased with aging in cardiac muscle but not in skeletal muscle. Despite FTIR spectroscopy being unable to identify the proteins responsible for these conformational changes, this study gives insights into the potential of FTIR to monitor the aging process and identify an age-specific spectroscopic signature.

The Potential of Metabolomics in the Diagnosis of Thyroid Cancer.

Thyroid cancer is the most common endocrine system malignancy. However, there is still a lack of reliable and specific markers for the detection and staging of this disease. Fine needle aspiration biopsy is the current gold standard for diagnosis of thyroid cancer, but drawbacks to this technique include indeterminate results or an inability to discriminate different carcinomas, thereby requiring additional surgical procedures to obtain a final diagnosis. It is, therefore, necessary to seek more reliable markers to complement and improve current methods. "Omics" approaches have gained much attention in the last decade in the field of biomarker discovery for diagnostic and prognostic characterisation of various pathophysiological conditions. Metabolomics, in particular, has the potential to identify molecular markers of thyroid cancer and identify novel metabolic profiles of the disease, which can, in turn, help in the classification of pathological conditions and lead to a more personalised therapy, assisting in the diagnosis and in the prediction of cancer behaviour. This review considers the current results in thyroid cancer biomarker research with a focus on metabolomics.

Monitoring plasma protein aggregation during aging using conformation-specific antibodies and FTIR spectroscopy.

The loss of proteostasis during aging has been well described using different models, however little is known with respect to protein aggregation levels in biofluids with aging. Therefore, the aim of this study was to assess the pattern of age-related protein aggregation in human plasma using two distinct approaches: analysis with conformation-specific antibodies and FTIR spectroscopy. The latter has been widely used in biomedical research to study protein conformational changes in health and disease. Samples from a primary care based-cohort from the Aveiro region, Portugal, were used for slot-blot analyses followed by immunodetection with conformation-specific antibodies and for the acquisition of FTIR spectra. Immunoblot analyses revealed an age-dependent evolution of the protein conformational profile in human plasma, towards a decrease in prefibrillar oligomers and an increase in fibrillar structures. This finding was also supported by PLS-R multivariate analysis of FTIR data, where a positive correlation between the age of the donors and secondary structure of plasma proteins could be observed. Samples from younger donors are characterized by antiparallel ß-sheet-containing structures while intermolecular ß-sheets characterized older samples. Exclusion of age-associated co-morbidities improved the correlation between protein conformational profiles and aging. The results reveal structural changes in human plasma proteins from middle to old age, confirming the age-associated changes in protein aggregation, and support the applicability of FTIR as a reliable approach to study proteostasis during aging.

NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma.

Lung tumour subtyping, particularly the distinction between adenocarcinoma (AdC) and squamous cell carcinoma (SqCC), is a critical diagnostic requirement. In this work, the metabolic signatures of lung carcinomas were investigated through (1)H NMR metabolomics, with a view to provide additional criteria for improved diagnosis and treatment planning. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (NMR) spectroscopy was used to analyse matched tumour and adjacent control tissues from 56 patients undergoing surgical excision of primary lung carcinomas. Multivariate modeling allowed tumour and control tissues to be discriminated with high accuracy (97% classification rate), mainly due to significant differences in the levels of 13 metabolites. Notably, the magnitude of those differences were clearly distinct for AdC and SqCC: major alterations in AdC were related to phospholipid metabolism (increased phosphocholine, glycerophosphocholine and phosphoethanolamine, together with decreased acetate) and protein catabolism (increased peptide moieties), whereas SqCC had stronger glycolytic and glutaminolytic profiles (negatively correlated variations in glucose and lactate and positively correlated increases in glutamate and alanine). Other tumour metabolic features were increased creatine, glutathione, taurine and uridine nucleotides, the first two being especially prominent in SqCC and the latter in AdC. Furthermore, multivariate analysis of AdC and SqCC profiles allowed their discrimination with a 94% classification rate, thus showing great potential for aiding lung tumours subtyping. Overall, this study has provided new, clear evidence of distinct metabolic signatures for lung AdC and SqCC, which can potentially impact on diagnosis and provide important leads for future research on novel therapeutic targets or imaging tracers.

Following healthy pregnancy by NMR metabolomics of plasma and correlation to urine.

This work presents the first NMR metabolomics study of maternal plasma during pregnancy, including correlation between plasma and urine metabolites. The expected decrease in circulating amino acids early in pregnancy was confirmed with six amino acids being identified as required by the fetus in larger extents. Newly observed changes in citrate, lactate, and dimethyl sulfone suggested early adjustments in energy and gut microflora metabolisms. Alterations in creatine levels were also noted, in addition to creatinine variations reflecting alterations in glomerular filtration rate. Regarding plasma macromolecules, HDL and LDL+VLDL levels were confirmed to increase throughout pregnancy, although at different rates and accompanied by increases in fatty acid chain length and degree of unsaturation. Correlation studies suggested (a) an inverse relationship between lipoproteins (HDL and LDL+VLDL) and albumin, with a possible direct correlation to excreted (unassigned) pregnancy markers resonating at δ 0.55 and δ 0.63, (b) a direct link between LDL+VLDL and N-acetyl-glycoproteins, together with excreted marker at δ 0.55, and (c) correlation of plasma albumin with particular circulating and excreted metabolites. These results have unveiled specific lipoprotein/protein metabolic aspects of pregnancy with impact on the excreted metabolome and, therefore, provide an interesting lead for the further understanding of pregnancy metabolism.

Second trimester maternal urine for the diagnosis of trisomy 21 and prediction of poor pregnancy outcomes.

Given the recognized lack of prenatal clinical methods for the early diagnosis of preterm delivery, intrauterine growth restriction, preeclampsia and gestational diabetes mellitus, and the continuing need for optimized diagnosis methods for specific chromosomal disorders (e.g., trisomy 21) and fetal malformations, this work sought specific metabolic signatures of these conditions in second trimester maternal urine, using (1)H Nuclear Magnetic Resonance ((1)H NMR) metabolomics. Several variable importance to the projection (VIP)- and b-coefficient-based variable selection methods were tested, both individually and through their intersection, and the resulting data sets were analyzed by partial least-squares discriminant analysis (PLS-DA) and submitted to Monte Carlo cross validation (MCCV) and permutation tests to evaluate model predictive power. The NMR data subsets produced significantly improved PLS-DA models for all conditions except for pre-premature rupture of membranes. Specific urinary metabolic signatures were unveiled for central nervous system malformations, trisomy 21, preterm delivery, gestational diabetes, intrauterine growth restriction and preeclampsia, and biochemical interpretations were proposed. This work demonstrated, for the first time, the value of maternal urine profiling as a complementary means of prenatal diagnostics and early prediction of several poor pregnancy outcomes.

Mid-infrared (MIR) metabolic fingerprinting of amniotic fluid: a possible avenue for early diagnosis of prenatal disorders?

This work describes a mid-infrared (MIR) metabolic profiling study of 2nd trimester amniotic fluid in relation to selected prenatal disorders, with results focusing on fetal malformations (FM), preterm delivery (PTD) and premature rupture of membranes (PROM), the latter two conditions occurring later in pregnancy. Partial least squares-discriminant analysis (PLS-DA) models were obtained for FM and pre-PTD subject groups, supported by Monte Carlo Cross Validation (MCCV), and identified specific MIR profile changes. For pre-PROM subjects, minor changes were noted. MIR interpretation was assisted by intra- (MIR/MIR) and inter- (MIR/NMR) domain statistical correlation analysis, the results unveiling possible biomarker MIR signatures for FM and pre-PTD subjects. Biofluid MIR metabolic profiling holds enticing possibilities as a low cost, easy to use, rapid method and the results presented have shown its sensitivity to clinically diagnosed conditions such as FM, and to the pre-clinical stages of PTD. Specific improvement needs are discussed, namely regarding sample numbers and experimental reproducibility.

Following healthy pregnancy by nuclear magnetic resonance (NMR) metabolic profiling of human urine.

In this work, untargeted NMR metabonomics was employed to evaluate the effects of pregnancy on the metabolite composition of maternal urine, thus establishing a control excretory trajectory for healthy pregnancies. Urine was collected for independent groups of healthy nonpregnant and pregnant women (in first, second, third trimesters) and multivariate analysis performed on the corresponding NMR spectra. Models were validated through Monte Carlo Cross Validation and permutation tests and metabolite correlations measured through Statistical Total Correlation Spectroscopy. The levels of 21 metabolites were found to change significantly throughout pregnancy, with variations observed for the first time to our knowledge for choline, creatinine, 4-deoxyerythronic acid, 4-deoxythreonic acid, furoylglycine, guanidoacetate, 3-hydroxybutyrate, and lactate. Results confirmed increased aminoaciduria across pregnancy and suggested (a) a particular involvement of isoleucine and threonine in lipid oxidation/ketone body synthesis, (b) a relation of excreted choline, taurine, and guanidoacetate to methionine metabolism and urea cycle regulation, and (c) a possible relationship of furoylglycine and creatinine to pregnancy, based on a tandem study of nonfasting confounding effects. Results demonstrate the usefulness of untargeted metabonomics in finding biomarker metabolic signatures for healthy pregnancies, against which disease-related deviations may be confronted in future studies, as a base for improved diagnostics and prediction.

UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers.

We report on the first untargeted UPLC-MS study of 2nd trimester maternal urine and amniotic fluid (AF), to investigate the possible metabolic effects of fetal malformations (FM), gestational diabetes mellitus (GDM) and preterm delivery (PTD). For fetal malformations, considerable metabolite variations were identified in AF and, to a lesser extent, in urine. Using validated PLS-DA models and statistical correlations between UPLC-MS data and previously acquired NMR data, a metabolic picture of fetal hypoxia, enhanced gluconeogenesis, TCA activity and hindered kidney development affecting FM pregnancies was reinforced. Moreover, changes in carnitine, pyroglutamate and polyols were newly noted, respectively, reflecting lipid oxidation, altered placental amino acid transfer and alterations in polyol pathways. Higher excretion of conjugated products in maternal urine was seen suggesting alterations in conjugation reactions. For the pre-diagnostic GDM group, no significant changes were observed, either considering amniotic fluid or maternal urine, whereas, for the pre-PTD group, some newly observed changes were noted, namely, the decrease of particular amino acids and the increase of an hexose (possibly glucose), suggesting alteration in placental amino acid fluxes and a possible tendency for hyperglycemia. This work shows the potential of UPLC-MS for the study of fetal and maternal biofluids, particularly when used in tandem with comparable NMR data. The important roles played by sampling characteristics (e.g. group dimensions) and the specific experimental conditions chosen for MS methods are discussed.

Metabolic signatures of lung cancer in biofluids: NMR-based metabonomics of blood plasma.

In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in the patients' plasma, together with increased lactate and pyruvate and decreased levels of glucose, citrate, formate, acetate, several amino acids (alanine, glutamine, histidine, tyrosine, valine), and methanol, could be detected. These changes were found to be present at initial disease stages and could be related to known cancer biochemical hallmarks, such as enhanced glycolysis, glutaminolysis, and gluconeogenesis, together with suppressed Krebs cycle and reduced lipid catabolism, thus supporting the hypothesis of a systemic metabolic signature for lung cancer. Despite the possible confounding influence of age, smoking habits, and other uncontrolled factors, these results indicate that NMR-based metabonomics of blood plasma can be useful as a screening tool to identify suspicious cases for subsequent, more specific radiological tests, thus contributing to improved disease management.

Metabolic biomarkers of prenatal disorders: an exploratory NMR metabonomics study of second trimester maternal urine and blood plasma.

This work describes an exploratory NMR metabonomic study of second trimester maternal urine and plasma, in an attempt to characterize the metabolic changes underlying prenatal disorders and identify possible early biomarkers. Fetal malformations have the strongest metabolic impact in both biofluids, suggesting effects due to hypoxia (leading to hypoxanthine increased excretion) and a need for enhanced gluconeogenesis, with higher ketone bodies (acetone and 3-hydroxybutyric acid) production and TCA cycle demand (suggested by glucogenic amino acids and cis-aconitate overproduction). Choline and nucleotide metabolisms also seem affected and a distinct plasma lipids profile is observed for mothers with fetuses affected by central nervous system malformations. Urine from women who subsequently develop gestational diabetes mellitus exhibits higher 3-hydroxyisovalerate and 2-hydroxyisobutyrate levels, probably due to altered biotin status and amino acid and/or gut metabolisms (the latter possibly related to higher BMI values). Other urinary changes suggest choline and nucleotide metabolic alterations, whereas lower plasma betaine and TMAO levels are found. Chromosomal disorders and pre-preterm delivery groups show urinary changes in choline and, in the latter case, in 2-hydroxyisobutyrate. These results show that NMR metabonomics of maternal biofluids enables the noninvasive detection of metabolic changes associated to prenatal disorders, thus unveiling potential disorder biomarkers.

Metabolic profiling of potential probiotic or synbiotic cheeses by nuclear magnetic resonance (NMR) spectroscopy.

To assess ripening of potential probiotic cheeses (containing either Lactobacillus casei -01 or Bifidobacterium lactis B94) or synbiotic cheeses with fructooligosaccharides (FOS) or a 50:50 mix of FOS/inulin, metabolic profiles have been obtained via classical biochemical analyses and by NMR spectroscopy. The addition of prebiotics to the cheeses resulted in lower proteolysis indices, especially in those synbiotic cheeses inoculated with B. lactis B94. Among synbiotic cheeses the combination of FOS and inulin resulted in an increase in lipolytic activity. The metabolic profiles of the cheeses analyzed by NMR spectroscopy, combined with multivariate statistics, allowed profiles to be distinguished by maturation time, added probiotic bacteria, or, in the case of B. lactis B94 cheese, added prebiotic. The NMR results are in agreement with the biochemical analyses and demonstrate the potential of NMR for the study of metabolic processes in probiotic/synbiotic food matrices.

Metabolic signatures of lung cancer in biofluids: NMR-based metabonomics of urine.

In this study, ¹H NMR-based metabonomics has been applied, for the first time to our knowledge, to investigate lung cancer metabolic signatures in urine, aiming at assessing the diagnostic potential of this approach and gaining novel insights into lung cancer metabolism and systemic effects. Urine samples from lung cancer patients (n = 71) and a control healthy group (n = 54) were analyzed by high resolution ¹H NMR (500 MHz), and their spectral profiles subjected to multivariate statistics, namely, Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Orthogonal Projections to Latent Structures (OPLS)-DA. Very good discrimination between cancer and control groups was achieved by multivariate modeling of urinary profiles. By Monte Carlo Cross Validation, the classification model showed 93% sensitivity, 94% specificity and an overall classification rate of 93.5%. The possible confounding influence of other factors, namely, gender and age, have also been modeled and found to have much lower predictive power than the presence of the disease. Moreover, smoking habits were found not to have a dominating influence over class discrimination. The main metabolites contributing to this discrimination, as highlighted by multivariate analysis and confirmed by spectral integration, were hippurate and trigonelline (reduced in patients), and ß-hydroxyisovalerate, α-hydroxyisobutyrate, N-acetylglutamine, and creatinine (elevated in patients relatively to controls). These results show the valuable potential of NMR-based metabonomics for finding putative biomarkers of lung cancer in urine, collected in a minimally invasive way, which may have important diagnostic impact, provided that these metabolites are found to be specifically disease-related.

Can nuclear magnetic resonance (NMR) spectroscopy reveal different metabolic signatures for lung tumours?

This study aims to evaluate the potential of (1)H NMR spectroscopy, combined with multivariate statistics, for discriminating between tumour and non-involved (control) pulmonary parenchyma and for providing biochemical information on different histological types. Paired tissue samples from 24 primary lung tumours were directly analysed by high-resolution magic angle spinning (HRMAS) (1)H NMR spectroscopy (500 MHz), and their spectral profiles subjected to principal component analysis (PCA) and partial least squares regression discriminant analysis (PLS-DA). Tumour and adjacent control parenchyma were clearly discriminated in the PLS-DA model with a high level of sensitivity (95% of tumour samples correctly classified) and 100% specificity (no false positives). The metabolites giving rise to this separation were mainly lactate, glycerophosphocholine, phosphocholine, taurine, reduced glutathione and uridine di-phosphate (elevated in tumours) and glucose, phosphoethanolamine, acetate, lysine, methionine, glycine, myo- and scyllo-inositol (reduced in tumours compared to control tissues). Furthermore, PLS-DA of a sub-set of tumour samples allowed adenocarcinomas to be discriminated from carcinoid tumours and epidermoid carcinomas, highlighting differences in metabolite levels between these histological types, and therefore revealing valuable knowledge on the biochemistry of different types of bronchial-pulmonary carcinomas.

Impact of prenatal disorders on the metabolic profile of second trimester amniotic fluid: a nuclear magnetic resonance metabonomic study.

This paper describes a metabonomic study of prenatal disorders using nuclear magnetic resonance (NMR) spectroscopy of amniotic fluid (AF) collected in the second trimester of pregnancy, to search for metabolite markers of fetal malformations, prediagnostic gestational diabetes (GD), preterm delivery (PTD), early rupture of membranes (PROM), and chromossomopathies. Fetal malformations were found to have the highest impact on AF metabolite composition, enabling statistical validation to be achieved by several multivariate analytical tools. Results confirmed previous indications that malformed fetuses seem to suffer altered energy metabolism and kidney underdevelopment. Newly found changes (namely in α-oxoisovalerate, ascorbate, creatinine, isoleucine, serine, threonine) suggest possible additional effects on protein and nucleotide sugar biosynthesis. Prediagnostic GD subjects showed an average increase in glucose and small decreases in several amino acids along with acetate, formate, creatinine, and glycerophosphocholine. Small metabolite changes were also observed in the AF of subjects eventually undergoing PTD and PROM, whereas no relevant changes were found for chromossomopathies (for which a low number of samples was considered). The potential value of these results for biochemical insight and prediction of prenatal disorders is discussed, as well as their limitations regarding number of samples and overlap of different disorders.