Sílvia O. Diaz

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.

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.

1H NMR Based Metabonomics of Human Amniotic Fluid for the Metabolic Characterization of Fetus Malformations

An NMR-metabonomic study of malformed fetuses was carried out through human amniotic fluid (HAF) analysis. Over 70 compounds were detected in control HAF by NMR. Possible confounding variables (fetus gender and gestational and maternal ages) were shown not to induce detectable compositional trends in the control group considered. Malformed fetuses showed variations in glucose, some amino acids and organic acids and proteins. In tandem with enzymatic assays, these NMR results suggest that changes in gycolysis and gluconeogenesis as well as kidney underdevelopment occur in the malformed fetuses studied here.

NMR metabolomics of human blood and urine in disease research

This paper reviews the main applications of NMR metabolomics of blood and urine in disease research, over the last 5 years. The broad range of disease types addressed attests the increasing interest within the academic and medical communities to explore the recognised potential of metabolomics to (1) provide insight into underlying disease pathogenesis and (2) unveil new metabolic markers for disease diagnosis and follow up. Importantly, most recent studies reveal an increasing awareness of possible limitations and pitfalls of the metabolomics approach, together with efforts for improved study design and statistical validation, which are crucial requisites for the sound development of NMR metabolomics and its progress into the clinical setting.

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.

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.

Nuclear Magnetic Resonance Metabolomics of Iron Deficiency in Soybean Leaves

Iron (Fe) deficiency is an important agricultural concern that leads to lower yields and crop quality. A better understanding of the condition at the metabolome level could contribute to the design of strategies to ameliorate Fe-deficiency problems. Fe-sufficient and Fe-deficient soybean leaf extracts and whole leaves were analyzed by liquid (1)H nuclear magnetic resonance (NMR) and high-resolution magic-angle spinning NMR spectroscopy, respectively. Overall, 30 compounds were measurable and identifiable (comprising amino and organic acids, fatty acids, carbohydrates, alcohols, polyphenols, and others), along with 22 additional spin systems (still unassigned). Thus, metabolite differences between treatment conditions could be evaluated for different compound families simultaneously. Statistically relevant metabolite changes upon Fe deficiency included higher levels of alanine, asparagine/aspartate, threonine, valine, GABA, acetate, choline, ethanolamine, hypoxanthine, trigonelline, and polyphenols and lower levels of citrate, malate, ethanol, methanol, chlorogenate, and 3-methyl-2-oxovalerate. The data indicate that the main metabolic impacts of Fe deficiency in soybean include enhanced tricarboxylic acid cycle activity, enhanced activation of oxidative stress protection mechanisms and enhanced amino acid accumulation. Metabolites showing accumulation differences in Fe-starved but visually asymptomatic leaves could serve as biomarkers for early detection of Fe-deficiency stress.

Can Biofluids Metabolic Profiling Help to Improve Healthcare during Pregnancy

This paper describes a metabonomics study of 2nd trimester biofluids (amniotic fluid, maternal urine, and blood plasma), in an attempt to correlate biofluid metabolic changes with suspected/diagnosed fetal malformations (FM) and chromosomal disorders as well as with later occurring gestational diabetes mellitus (GDM), preterm delivery (PTD), and premature rupture of membranes (PROM). The global biochemical picture given by the threesome of biofluids should enable the definition of potential disease signatures and unveil potential metabolite markers for clinical use in predictive prenatal diagnostics. Results show that relatively strong metabolic disturbances accompany FM, reflected in all three biofluids and thus suggesting the involvement of both fetal and maternal metabolisms. Regarding GDM, amniotic fluid and maternal urine seem potential good media to detect early metabolic changes, and PTD subjects show small metabolite changes in the same biofluids, undergoing work being focused on plasma composition. Chromosomal disorders show an interestingly marked effect on maternal urine, whereas no statistically relevant early changes have been observed for PROM subjects. Interestingly, in the case of FM and chromosomal disorders, maternal biofluids show some sensitivity to disorder type, for example, for central nervous system malformations and trisomy 21, respectively. These results show the usefulness of biofluid metabonomics to probe overall metabolic disturbances in relation to prenatal disorders.

Newborn Urinary Metabolic Signatures of Prematurity and Other Disorders: A Case Control Study

This work assesses the urinary metabolite signature of prematurity in newborns by nuclear magnetic resonance (NMR) spectroscopy, while establishing the role of possible confounders and signature specificity, through comparison to other disorders. Gender and delivery mode are shown to impact importantly on newborn urine composition, their analysis pointing out at specific metabolite variations requiring consideration in unmatched subject groups. Premature newborns are, however, characterized by a stronger signature of varying metabolites, suggestive of disturbances in nucleotide metabolism, lung surfactants biosynthesis and renal function, along with enhancement of tricarboxylic acid (TCA) cycle activity, fatty acids oxidation, and oxidative stress. Comparison with other abnormal conditions (respiratory depression episode, large for gestational age, malformations, jaundice and premature rupture of membranes) reveals that such signature seems to be largely specific of preterm newborns, showing that NMR metabolomics can retrieve particular disorder effects, as well as general stress effects. These results provide valuable novel information on the metabolic impact of prematurity, contributing to the better understanding of its effects on the newborns state of health.

Metabolic profiling of maternal urine can aid clinical management of gestational diabetes mellitus

IntroductionThe clinical management of Gestational diabetes mellitus (GDM) would benefit from enhanced metabolic knowledge both at the time of diagnosis and during therapy.ObjectivesThis work aimed at unveiling metabolic markers of GDM and of the subjects’ response to therapy.MethodsUrine NMR metabolomics was used with a variable selection methodology to reduce uninformative variability. The NMR data was analysed by multivariate and univariate analysis methodologies.ResultsThe results showed that urine NMR metabolomics enables a metabolic signature of GDM to be identified at the time of diagnosis. This signature comprises relevant changes in 12 NMR metabolites/resonances and qualitative variations in a number of additional metabolites. The metabolite changes characterizing GDM suggest adaptations in a number of different pathways and highlight the relevance of gut microflora disturbances in relation to the disease. The impact of diet and insulin treatments on the excreted metabolome of pregnant GDM women was measured and enabled responsive and resistant metabolic pathways to be identified, as well as side-effects of treatment i.e. metabolic changes induced by treatment and previously unrelated to the disease (including changes in the gut microflora). Furthermore, treatment duration was found to be associated to urine metabolic profile, thus emphasizing the possible future use of urine metabolomics in treatment follow-up and efficacy evaluation. Finally, a possible association of a priori urinary metabolome with future treatment requirements is reported, albeit requiring demonstration in larger cohorts. This result supports the hypothesis of different metabotypes characterizing different subjects and relating to individual response to treatment.ConclusionA 12-resonance metabolic signature of GDN at the time of diagnosis was identified and the evaluation of the impact of insulin and/or diet therapies enabled responsive/resistant metabolic pathways and treatment side-effects to be identified.