Metabolomic analysis for first-trimester Down syndrome prediction

Urinary metabolomics reveals potential biomarkers for early detection of pregnancy in Mithun (Bos frontalis) cows

The present study investigated the urinary metabolic profiles of early pregnant and non-pregnant Mithun to identify potential pregnancy detection biomarkers. Urine samples were collected on days 0, 10, 18, 35 and 45 of gestation from pregnant (n = 6) and on days 0, 10 and 18 from non-pregnant (n = 6) Mithun. Urinary metabolites were assessed using proton nuclear magnetic resonance (1H NMR) spectroscopy and identified 270 metabolites. Statistical analyses demonstrated pronounced distinctions in metabolite profiles between pregnant and non-pregnant samples. Twenty-five metabolites that could discriminate between pregnant and non-pregnant Mithun based on Variable Importance in Projection (VIP) scores >1 were identified. Upon further examination of six metabolites (kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine and leucine) identified with high VIP scores, ROC curve analyses demonstrated their significant predictive potential, with AUC values ranging between 0.50 and 0.85. Additionally, a combined panel of top 25 metabolites yielded an AUC value of 0.85. Pathway analysis identified seven potential metabolic pathway modulations during early gestation, with particular emphasis on phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan pathway and pathways involved in the metabolism of various amino acids. In conclusion, kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine, and leucine show promise as non-invasive urinary biomarkers for early pregnancy detection in Mithun. SIGNIFICANCE: This study presents the first report on the metabolic profile of urine from early pregnant and non-pregnant Mithun (Bos frontalis). The metabolites like kynurenine and its derivatives (kynurenate, 3-hydroxykynurenine and quinolinate), tyrosine and leucine were documented signature urinary metabolites associated with early pregnancy in Mithun. The identified combination of metabolites holds promise as predictive biomarkers for non-invasive urinary-based early pregnancy diagnostics in Mithun. In addition, this study identified changes in metabolic pathways that involve phenylalanine, tyrosine, tryptophan and related amino acids and biomarkers identified were either precursors or products within these metabolic pathways.

Metabolomic Profiling in Mouse Model of Menopause-Associated Asthma

Menopause-associated asthma impacts a subset of women, tends to be more severe, and is less responsive to current treatments. We recently developed a model of menopause-associated asthma using 4-Vinylcyclohexene Diepoxide (VCD) and house dust mites (HDM). The goal of this study was to uncover potential biomarkers and drivers of menopause-onset asthma by assessing serum and bronchoalveolar lavage fluid (BALF) samples from mice with and without menopause and HDM challenge by large-scale targeted metabolomics. Female mice were treated with VCD/HDM to model menopause-associated asthma, and serum and BALF samples were processed for large-scale targeted metabolomic assessment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine metabolites of potential biological significance. We identified over 50 individual metabolites, impacting 46 metabolic pathways, in the serum and BALF that were significantly different across the four study groups. In particular, glutamate, GABA, phosphocreatine, and pyroglutamic acid, which are involved in glutamate/glutamine, glutathione, and arginine and proline metabolisms, were significantly impacted in the menopausal HDM-challenged mice. Additionally, several metabolites had significant correlations with total airway resistance including glutamic acid, histamine, uridine, cytosine, cytidine, and acetamide. Using metabolic profiling, we identified metabolites and metabolic pathways that may aid in discriminating potential biomarkers for and drivers of menopause-associated asthma.

Metabolomics in Prenatal Medicine: A Review

Pregnancy is a complicated and insidious state with various aspects to consider, including the well-being of the mother and child. Developing better non-invasive tests that cover a broader range of disorders with lower false-positive rates is a fundamental necessity in the prenatal medicine field, and, in this sense, the application of metabolomics could be extremely useful. Metabolomics measures and analyses the products of cellular biochemistry. As a biomarker discovery tool, the integrated holistic approach of metabolomics can yield new diagnostic or therapeutic approaches. In this review, we identify and summarize prenatal metabolomics studies and identify themes and controversies. We conducted a comprehensive search of PubMed and Google Scholar for all publications through January 2020 using combinations of the following keywords: nuclear magnetic resonance, mass spectrometry, metabolic profiling, prenatal diagnosis, pregnancy, chromosomal or aneuploidy, pre-eclampsia, fetal growth restriction, pre-term labor, and congenital defect. Metabolite detection with high throughput systems aided by advanced bioinformatics and network analysis allowed for the identification of new potential prenatal biomarkers and therapeutic targets. We took into consideration the scientific papers issued between the years 2000-2020, thus observing that the larger number of them were mainly published in the last 10 years. Initial small metabolomics studies in perinatology suggest that previously unidentified biochemical pathways and predictive biomarkers may be clinically useful. Although the scientific community is considering metabolomics with increasing attention for the study of prenatal medicine as well, more in-depth studies would be useful in order to advance toward the clinic world as the obtained results appear to be still preliminary. Employing metabolomics approaches to understand fetal and perinatal pathophysiology requires further research with larger sample sizes and rigorous testing of pilot studies using various omics and traditional hypothesis-driven experimental approaches.

Noninvasive screening for congenital heart defects using a serum metabolomics approach

OBJECTIVE

Heart anomalies represent nearly one-third of all congenital anomalies. They are currently diagnosed using ultrasound. However, there is a strong need for a more accurate and less operator-dependent screening method. Here we report a metabolomics characterization of maternal serum in order to describe a metabolomic fingerprint representative of heart congenital anomalies.

METHODS

Metabolomic profiles were obtained from serum of 350 mothers (280 controls and 70 cases). Nine classification models were built and optimized. An ensemble model was built based on the results from the individual models.

RESULTS

The ensemble machine learning model correctly classified all cases and controls. Malonic, 3-hydroxybutyric and methyl glutaric acid, urea, androstenedione, fructose, tocopherol, leucine, and putrescine were determined as the most relevant metabolites in class separation.

CONCLUSION

The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal heart anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the revelation of the associated metabolites and their respective biochemical pathways allows a better understanding of the overall pathophysiology of affected pregnancies.

Steroid profile analysis by liquid chromatography-tandem mass spectrometry in second-trimester pregnant women for trisomy 21 screening

BACKGROUND

Trisomy 21 is a serious chromosome abnormality. The conventional Down's screening test is the most widely used for trisomy 21 screening. However, this method could lead to a higher false positive rate. Therefore, we aim to analyze steroid profile in second-trimester pregnant women and identify novel serum biomarkers of trisomy 21.

METHODS

We employed an LC-MS/MS method to measure the steroid profile. The concentrations and product-to-substrate ratios in 71 second-trimester pregnant women were determined and statistically analyzed to identify novel biomarkers for trisomy 21 screening.

RESULTS

We found that there were significant differences in levels of E3, 11-deoxycortisol, and 11-deoxycortisol /17-hydroxyprogesterone between two groups. The OPLS-DA plots revealed obvious separation between two groups. Combining VIP analysis (VIP > 1.0) with volcano plot (P < 0.05 and fold change >1.2 or < 0.83), 11-deoxycortisol was identified as a novel biomarker for trisomy 21. After controlling for confounders, we found 11-deoxycortisol was associated with trisomy 21 (adjusted P = 0.009), and the fully adjusted OR (95 % CI) was 0.098 (0.016-0.593) in highest quartile versus lowest quartile of 11-deoxycortisol (P = 0.011).

CONCLUSIONS

Steroid profile analysis for the first time showed that steroid hormones perturbations occurred in pregnant women carrying a fetus affected by trisomy 21 and decreased 11-deoxycortisol levels were associated with trisomy 21.

Association of Oxidative Stress on Pregnancy

The pathophysiological mechanism underlying pregnancy complications such as congenital malformations, miscarriage, preeclampsia, or fetal growth restriction is not entirely known. However, the negative impact of the mother's body oxidative imbalance on the fetus and the course of gestation is increasingly discussed. This article is an integrative review of some original studies and review papers on the effects of oxidative stress on the adverse pregnancy outcomes mainly birth defects in fetuses. A systematic search for English language articles published from 2010 until 2020 was made, using MEDLINE data. Additionally, we analyzed the Cochrane and Scopus databases, discussions with experts, and a review of bibliography of articles from scientifically relevant and valuable sources. The main purposes are to assess the contribution of the existing literature of associations of oxidative stress on the etiology of the abovementioned conditions and to identify relevant information and outline existing knowledge. Furthermore, the authors aim to find any gaps in the research, thereby providing grounds for our own research. The key search terms were "oxidative stress in pregnancy," "oxidative stress and congenital malformations," and "oxidative stress and adverse pregnancy outcomes." Studies have confirmed that oxidative stress has a significant impact on pregnancy and is involved in the pathomechanism of adverse pregnancy outcomes.

GC-MS analysis of seven metabolites for the screening of pregnant women with Down Syndrome fetuses

Down Syndrome is a genetic disorder caused by the presence of all or part of a third copy of chromosome 21. Metabolomics is identification and quantification of small-molecule metabolites (molecular weight <1000 Da) in tissues, cells and physiological fluids within a certain period time. Metabolites are intermediate products of various types of biochemical reactions that participate in bonding metabolic pathways. In this study, metabolites such as 2-Hydroxybutyric acid, 3-Hydroxybutyric acid, β-Hydroxyisovaleric acid, Uracil, Glutamic acid, Maltose and Melezitose were chosen as the possible determinants/markers for the prenatal screening of Down Syndrome. Quantitative analysis of the metabolites conducted by GCMS method using 5 % phenyl / 95 % dimethylpolysiloxane (30 m ×0.25 mm, 0.25 μm film thickness) capillary column. The oven temperature was held constant at 60 °C for 1 min and ramped at 10 °C /min to 200 °C then ramped at 30 °C/min to 320 °C and hold for 6 min before cool-down, as helium mobile phase and flow rate of 2.8 mL/min and adding Myristic acid-d27 as an internal standard. Our method was validated by parameters of system suitability, stability, linearity, sensitivity, accuracy, precision, selectivity, robustness and ruggedness. The developed and validated method was applied to plasma samples taken from pregnant women with Down Syndrome (study group) and euploid fetuses (healthy group). The levels of these seven metabolites are statistically different (p < 0.05 for all) between the groups. It can be concluded that these relevant metabolites might be used for the prenatal screening of Down Syndrome.

Effects of Bailing capsule on diabetic nephropathy based on UPLC-MS urine metabolomics

Diabetic nephropathy (DN) is one of the most common microvascular diabetes complications and has become a threat to human health. Bailing capsules (BLCs), containing fermentation products of Cordyceps sinensis, have been commonly used for treatment of renal dysfunction, such as DN. However, mechanisms underlying the protective effects of BLC remain largely obscure and await more investigation. In this study, UPLC-MS-based comprehensive metabolomics along with pattern recognition was applied to explore the urine metabolic alteration of DN as well as therapeutic mechanisms of BLC. Nineteen differentially expressed endogenous metabolites were identified related to DN, which were involved in the perturbations of tyrosine metabolism, tryptophan metabolism, glycine metabolism, purine metabolism, glutamine metabolism, phenylalanine metabolism, histidine metabolism and TCA cycle metabolism pathways. After drug intervention, most of the biomarkers exhibited a certain extent towards normal levels (P < 0.05), which indicated that BLC was an effective drug for treating DN and might play its therapeutic role by retrieving abnormal metabolism pathways. The data obtained in this research may pave the way for further exploration of DN and provide key clues to understand the protective effect of BLC.

UPLC-MS-based metabolomics along with pattern recognition was applied to explore the metabolic alteration of diabetic nephropathy and therapeutic mechanisms of Bailing capsule.

Metabolomics analysis of children with autism, idiopathic-developmental delays, and Down syndrome

Although developmental delays affect learning, language, and behavior, some evidence suggests the presence of disturbances in metabolism are associated with psychiatric disorders. Here, the plasma metabolic phenotype of children with autism spectrum disorder (ASD, n = 167), idiopathic-developmental delay (i-DD, n = 51), and Down syndrome (DS, n = 31), as compared to typically developed (TD, n = 193) controls was investigated in a subset of children from the case-control Childhood Autism Risk from Genetics and the Environment (CHARGE) Study. Metabolome profiles were obtained using nuclear magnetic resonance spectroscopy and analyzed in an untargeted manner. Forty-nine metabolites were identified and quantified in each sample that included amino acids, organic acids, sugars, and other compounds. Multiple linear regression analysis revealed significant associations between 11 plasma metabolites and neurodevelopmental outcome. Despite the varied origins of these developmental disabilities, we observed similar perturbation in one-carbon metabolism pathways among DS and ASD cases. Similarities were also observed in the DS and i-DD cases in the energy-related tricarboxylic acid cycle. Other metabolites and pathways were uniquely associated with DS or ASD. By comparing metabolic signatures between these conditions, the current study expands on extant literature demonstrating metabolic alterations associated with developmental disabilities and provides a better understanding of overlapping vs specific biological perturbations associated with these disorders.

Metabolomic study of the protective effect of Gandi capsule for diabetic nephropathy

Diabetic nephropathy (DN) is the one of the leading causes of end-stage renal disease (ESRD) in clinical. However, it is still lack of accurate biomarkers and effective methods for diagnosing and curing DN. Therefore, there is an urgent need to develop a definite strategy for the identification of reliable and versatile biomarkers for risk assessment of DN and search for therapeutic approaches that can effectively attenuate DN progression. Treatment with Gandi capsule (GDC) not only decreased the levels of urinary albumin excretion, but also increased the levels of estimated glomerular filtration rate (eGFR), indicating that it produces a renal protective effect on diabetic nephropathy. Based on metabolomics investigation including UHPLC-MS analysis and multivariate statistical analysis, sixteen disordered metabolites were screened out and considered as potential biomarkers corresponding to DN, which were mostly improved and partially returned to normalcy in GDC treatment group. Therefore, it was suggested that GDC was a promising therapeutic agent against DN. The underlying mechanisms of GDC attenuating the development of DN may be improving abnormal metabolic disorders by retrieving the imbalance of glycine metabolism, tryptophan metabolism, valine, leucine and isoleucine degradation, purine metabolism, nitrotoluene degradation, phenylalanine metabolism, fatty acid metabolism, tyrosine metabolism and bile acid metabolism pathways. The data obtained in this study may provide key clues to enhance our understanding of the metabolic mechanism of DN and shed new insights into the therapeutic mechanism of GDC.

MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis

We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.

Prenatal circulating microRNA signatures of foetal Down syndrome

The altered expression pattern of miRNAs might potentially reflect anomalies related to foetal chromosomal aberrations. The aim of the study was to determine the expression level of miRNAs in plasma of pregnant women with foetal Down syndrome (DS). Out of 198 amniocentesis performed at 15-18 weeks of gestation, within a group of 12 patients with foetal DS and 12 patients with uncomplicated pregnancies, who delivered healthy newborns at term, we examined the expression level of 800 miRNAs using the NanoString technology. Our study revealed that there are 6 miRNAs were upregulated (hsa-miR-15a, hsa-let-7d, hsa-miR-142, hsa-miR-23a, hsa-miR-199, hsa-miR-191) and 7 were downregulated (hsa-miR-1290, hsa-miR-1915, hsa-miR30e, hsa-miR-1260, hsa-miR-483, hsa-miR-548, hsa-miR-590) in plasma samples of women with foetal DS syndrome. The genes regulated by identified miRNAs are involved in central nervous system development, congenital abnormalities and heart defects. The results of the present study yielded information on DS-specific miRNA expression signature, which can further help to design a panel of miRNAs as a non-invasive test for DS diagnosis. We believe that identified miRNAs may attend in the pathogenesis of DS and would potentially make a significant role for the future preventive therapies.

Integrative metabolomics reveals unique metabolic traits in Guillain-Barré Syndrome and its variants

Guillain-Barré syndrome (GBS) is an acute fatal progressive disease caused by autoimmune mechanism mainly affecting peripheral nervous system. Although the syndrome is clinically sub-classified into several variants, specific biomarker and exact pathomechanism of each subtypes are not well elucidated yet. In current study, integrative metabolomic and lipidomic profiles were acquisitioned from cerebrospinal fluid samples of 86 GBS from three variants and 20 disease controls. And the data were systematically compared to our previous result on inflammatory demyelination disorders of central nervous system (IDDs) and healthy controls. Primary metabolite profiles revealed unique metabolic traits in which 9 and 7 compounds were specifically changed in GBS and IDD, respectively. Next, the biomarker panel with 10 primary metabolites showed a fairly good discrimination power among 3 GBS subtypes, healthy controls, and disease controls (AUCs ranged 0.849-0.999). The robustness of the biomarker panel was vigorously validated by multi-step statistical evaluation. Subsequent lipidomics revealed GBS variant-specific alteration where the significant elevations of lyso-phosphatidylcholines and sphingomyelins were unique to AIDP (acute inflammatory demyelinating polyneuropathy) and AMAN (acute motor axonal neuropathy), respectively. And metabolome-wide multivariate correlation analysis identified potential clinical association between GBS disability scale (Hughes score) and CSF lipids (monoacylglycerols, and sphingomyelins). Finally, Bayesian network analysis of covarianced structures of primary metabolites and lipids proposed metabolic hub and potential biochemical linkage associated with the pathology.

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.

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.

A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies

BACKGROUND

Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more accurate and less operator-dependent screening method.

OBJECTIVES

To perform a characterization of maternal serum in order to build a metabolomic fingerprint resulting from congenital anomalies of the central nervous system.

METHODS

This is a case-control pilot study. Metabolomic profiles were obtained from serum of 168 mothers (98 controls and 70 cases), using gas chromatography coupled to mass spectrometry. Nine machine learning and classification models were built and optimized. An ensemble model was built based on results from the individual models. All samples were randomly divided into two groups. One was used as training set, the other one for diagnostic performance assessment.

RESULTS

Ensemble machine learning model correctly classified all cases and controls. Propanoic, lactic, gluconic, benzoic, oxalic, 2-hydroxy-3-methylbutyric, acetic, lauric, myristic and stearic acid and myo-inositol and mannose were selected as the most relevant metabolites in class separation.

CONCLUSION

The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal central nervous system anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is therefore a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the details of the most relevant metabolites and their respective biochemical pathways allow better understanding of the overall pathophysiology of affected pregnancies.

Maternal plasma angiogenic and inflammatory factor profiling in foetal Down syndrome

Objective and design

Angiogenic factors are proteins that are related to certain foetal chromosomal abnormalities. The aim of this study was to determine the concentration of 60 angiogenic factors in the plasma of women with offspring possessing trisomy 21/Down syndrome (DS).

Method

After analysing karyotyping results, we selected 20 patients with foetuses possessing DS, and for the control group, we selected 28 healthy patients with uncomplicated pregnancies who delivered healthy newborns at term (i.e., 15–18 weeks of gestation). To assess the concentration of proteins in the blood plasma, we used a protein macroarray which enabled simultaneous determination of 60 angiogenic factors per sample.

Results

We observed a statistically significant increase in the concentration of these five angiogenic and inflammatory factors: TGFb1 (p = 0.039), angiostatin (p = 0.0142), I-309 (p = 0.0476), TGFb3 (p = 0.0395), and VEGF-D (p = 0.0173)—compared to concentrations in patients with healthy foetuses.

Conclusion

Our findings suggest that angiogenic factors may play role in DS pathogenesis.

General intelligence is associated with subclinical inflammation in Nepalese children: A population-based plasma proteomics study

Improving child cognition in impoverished countries is a public health priority. Yet, biological pathways and associated biomarkers of impaired cognition remain poorly understood and largely unknown, respectively. This study aimed to explore and quantify associations between functional plasma protein biomarkers and childhood intellectual test performance. We applied proteomics to quantify proteins in plasma samples of 249 rural Nepalese children, 6-8years of age who, 1year later at 7-9years of age, were administered the Universal Nonverbal Intelligence Test (UNIT). Among 751 plasma proteins quantified, 22 were associated with UNIT scores, passing a false discovery rate threshold of 5.0% (q<0.05). UNIT scores were higher by 2.3-9.2 points for every 50% increase in relative abundance of two insulin-like growth factor binding proteins (IGFBPs), six subclasses of apolipoprotein (Apo) and transthyretin, and lower by 4.0-15.3 points for each 50% increase in relative abundance of 13 proteins predominantly involved in inflammation. Among them, IGFBP-acid labile subunit, orosomucoid 1 (ORM1), Apo C-I, and pyruvate kinase isoenzymes M1/M2 jointly explained 37% of the variance in UNIT scores. After additional adjustment for height-for-age Z-score and household socio-economic status as indicators of long-term nutritional and social stress, associations with 6 proteins involved in inflammation, including ORM1, α-1-antichymotrypsin, reticulocalbin 1, and 3 components of the complement cascade, remained significant (q<0.05). Using untargeted proteomics, stable, constitutive facets of subclinical inflammation were associated with lower developmental test performance in this rural South Asian child population. Plasma proteomics may offer opportunities to identify functional, antecedent biomarkers of child cognitive development.

Brief Communication: Maternal Plasma Autoantibodies Screening in Fetal Down Syndrome

Imbalance in the metabolites levels which can potentially be related to certain fetal chromosomal abnormalities can stimulate mother's immune response to produce autoantibodies directed against proteins. The aim of the study was to determine the concentration of 9000 autoantibodies in maternal plasma to detect fetal Down syndrome. Method. We performed 190 amniocenteses and found 10 patients with confirmed fetal Down syndrome (15th–18th weeks of gestation). For the purpose of our control we chose 11 women without confirmed chromosomal aberration. To assess the expression of autoantibodies in the blood plasma, we used a protein microarray, which allows for simultaneous determination of 9000 proteins per sample. Results. We revealed 213 statistically significant autoantibodies, whose expression decreased or increased in the study group with fetal Down syndrome. The second step was to create a classifier of Down syndrome pregnancy, which includes 14 antibodies. The predictive value of the classifier (specificity and sensitivity) is 100%, classification errors, 0%, cross-validation errors, 0%. Conclusion. Our findings suggest that the autoantibodies may play a role in the pathophysiology of Down syndrome pregnancy. Defining their potential as biochemical markers of Down syndrome pregnancy requires further investigation on larger group of patients.

Impact of fetal chromosomal disorders on maternal blood metabolome: toward new biomarkers?

OBJECTIVE

This study aimed at determining the relationship between fetal chromosomal disorders (CDs), including trisomy 21 (T21), and on first- and second-trimester maternal blood plasma, to identify the time-course metabolic adaptations to the conditions and the possible new plasma biomarkers. Furthermore, a definition of a joint circulatory (plasma) and excretory (urine) metabolic description of second-trimester CDs was sought.

STUDY DESIGN

Plasma was obtained for 119 pregnant women: 74 controls and 45 CD cases, including 22 T21 cases. Plasma and lipid extracts (for T21 only) were analyzed by nuclear magnetic resonance spectroscopy, and data were handled by variable selection and multivariate analysis. Correlation analysis was used on a concatenated plasma/urine matrix descriptive of second-trimester CD, based on previously obtained urine data.

RESULTS

CD cases were accompanied by enhanced lipid β-oxidation (increased ketone bodies) and underutilization of glucose, pyruvate, and citrate. Lower circulating high-density lipoprotein levels were noted, along with changes in the proline and methanol in the first trimester, and also the urea, creatinine, acetate, and low-density lipoprotein plus very low-density lipoprotein in the second trimester and the different urea and creatinine levels, suggesting fetal renal dysfunction. In terms of plasma composition, T21 cases were indistinguishable from other CDs in the first trimester, whereas in the second trimester, increased methanol and albumin may be T21 specific. Furthermore, first-trimester lipid extracts of T21 showed decreased levels of 18:2 fatty acids, whereas in the second trimester, lower levels of 20:4 and 22:6 fatty acids were noted, possibly indicative of inflammation mechanisms. In both trimesters, high classification rates for CDs (88-89%) and T21 (85-92%) generally relied on variable selection of nuclear magnetic resonance data. Plasma/urine correlations confirmed most metabolic deviations and unveiled possible new ones regarding low-density lipoprotein plus very low-density lipoprotein, sugar, and gut-microflora metabolisms.

CONCLUSION

This work partially confirmed previously reported data on first-trimester T21 and provided additional information on time-course metabolic changes accompanying CD and T21, in particular regarding plasma lipid composition. These results demonstrate the potential of plasma metabolomics in monitoring and characterizing CD cases; however, validation in larger cohorts is desirable.

Advances in revealing the molecular targets downstream of oxidative stress-induced proapoptotic kinase signaling in diabetic embryopathy

Preexisting maternal diabetes is a high-risk factor of diabetic embryopathy, such as neural tube defects and congenital heart defects. Maternal diabetes significantly increases the production of reactive oxygen species, resulting in oxidative stress and diabetic embryopathy. Multiple cellular and metabolic factors contribute to these processes. Forkhead box O (FoxO)-3a has been demonstrated as a key transcription factor in the signaling transduction pathways responsible for maternal diabetes-induced birth defects. Apoptosis signal-regulating kinase 1 (ASK1) activated by oxidative stress stimulates nuclear translocation of FoxO3a, resulting in the overexpression of tumor necrosis factor receptor 1-associated death domain protein, which, in turn, leads to caspase-8 activation and apoptosis. Maternal diabetes-activated c-Jun N-terminal kinase (JNK)-1/2, downstream effectors of ASK1, can be blocked by superoxide dismutase-1 overexpression, suggesting that oxidative stress is responsible for JNK1/2 signaling activation. Deletion of JNK1/2 significantly suppressed the activity of FoxO3a. These observations indicate that maternal diabetes-induced oxidative stress stimulates the activation of ASK1, JNK1/2, FoxO3a, tumor necrosis factor receptor 1-associated death domain protein, caspase-8 cleavage, and finally, apoptosis and diabetic embryopathy.

Curcumin ameliorates high glucose-induced neural tube defects by suppressing cellular stress and apoptosis

OBJECTIVE

Curcumin is a naturally occurring polyphenol present in the roots of the Curcuma longa plant (turmeric), which possesses antioxidant, antitumorigenic, and antiinflammatory properties. Here, we test whether curcumin treatment reduces high glucose-induced neural tube defects (NTDs), and if this occurs via blocking cellular stress and caspase activation.

STUDY DESIGN

Embryonic day 8.5 mouse embryos were collected for use in whole-embryo culture under normal (100 mg/dL) or high (300 mg/dL) glucose conditions, with or without curcumin treatment. After 24 hours in culture, protein levels of oxidative stress makers, nitrosative stress makers, endoplasmic reticulum (ER) stress makers, cleaved caspase 3 and 8, and the level of lipid peroxides were determined in the embryos. After 36 hours in culture, embryos were examined for evidence of NTD formation.

RESULTS

Although 10 μmol/L of curcumin did not significantly reduce the rate of NTDs caused by high glucose, 20 μmol/L of curcumin significantly ameliorated high glucose-induced NTD formation. Curcumin suppressed oxidative stress in embryos cultured under high glucose conditions. Treatment reduced the levels of the lipid peroxidation marker, 4-hydroxynonenal, nitrotyrosine-modified protein, and lipid peroxides. Curcumin also blocked ER stress by inhibiting phosphorylated protein kinase RNA-like ER kinase, phosphorylated inositol-requiring protein-1α (p-IRE1α), phosphorylated eukaryotic initiation factor 2α (p-eIF2α), C/EBP-homologous protein, binding immunoglobulin protein, and x-box binding protein 1 messenger RNA splicing. Additionally, curcumin abolished caspase 3 and caspase 8 cleavage in embryos cultured under high glucose conditions.

CONCLUSION

Curcumin reduces high glucose-induced NTD formation by blocking cellular stress and caspase activation, suggesting that curcumin supplements could reduce the negative effects of diabetes on the embryo. Further investigation will be needed to determine if the experimental findings can translate into clinical settings.

Maternal plasma and amniotic fluid sphingolipids profiling in fetal Down syndrome

Introduction

Sphingolipids can be potentially involved in the formation of the central and peripheral nervous systems, which are particularly connected with the pathogenesis of Down syndrome. The aim of the study was to determine the concentration of selected sphingolipids in the plasma and amniotic fluid of pregnant patients with fetal Down syndrome.

Material and Methods

Out of 190 amniocentesis we had 10 patients with confirmed Down syndrome. For the purpose of our control we chose 14 women without confirmed chromosomal aberration. To assess the concentration of 11 sphingolipids in the blood plasma and amniotic fluid we used an ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometry (UHPLC/MS/MS).

Results

We showed a significant increase in the concentration of 2 ceramides, C22-Cer and C24:1-Cer, in the plasma of women with fetal Down syndrome. Furthermore we showed a decrease in the concentration of 7 ceramides—C16-Cer, C18-Cer, C18:1-Cer, C20-Cer, C22-Cer, C24:1-Cer, and C24-Cer—in the amniotic fluid of women with fetal Down syndrome. We created ROC curves for all significant sphingolipids in maternal plasma, which set the threshold values and allowed for predicting the likelihood of Down syndrome in the fetus with specific sensitivity and specificity. We demonstrated a significantly higher risk of Down syndrome when the plasma concentration of C22-Cer > 12.66 ng/100ul (sens. 0.9, sp. 0.79, P value = 0.0007) and C24:1-Cer > 33,19 ng/100ul (sens. 0.6, sp. 0.86, P value = 0.0194).

Conclusion

On the basis of our findings, it seems that the sphingolipids may play a role in the pathogenesis of Down syndrome. Defining their potential as biochemical markers of Down syndrome requires further investigation on a larger group of patients.

Oxidative stress is responsible for maternal diabetes-impaired transforming growth factor beta signaling in the developing mouse heart

OBJECTIVE

Oxidative stress plays a causal role in diabetic embryopathy. Maternal diabetes induces heart defects and impaired transforming growth factor beta (TGFβ) signaling, which is essential for cardiogenesis. We hypothesize that mitigating oxidative stress through superoxide dismutase 1 (SOD1) overexpression in transgenic (Tg) mice reverses maternal hyperglycemia-impaired TGFβ signaling and its downstream effectors.

STUDY DESIGN

Day 12.5 embryonic hearts from wild-type (WT) and SOD1 overexpressing embryos of nondiabetic (ND) and diabetic mellitus (DM) dams were used for the detection of oxidative stress markers: 4-hydroxynonenal (4-HNE) and malondlaldehyde (MDA), and TGFβ1, 2, and 3, phosphor (p)-TGFβ receptor II (TβRII), p-phosphorylated mothers against decapentaplegic (Smad)2, and p-Smad3. The expression of 3 TGFβ-responsive genes was also assessed. Day 11.5 embryonic hearts were explanted and cultured ex vivo, with or without treatments of a SOD1 mimetic (Tempol; Enzo Life Science, Farmingdale, NY) or a TGFβ recombinant protein for the detection of TGFβ signaling intermediates.

RESULTS

Levels of 4-HNE and MDA were significantly increased by maternal diabetes, and SOD1 overexpression blocked the increase of these 2 oxidative stress markers. Maternal diabetes suppresses the TGFβ signaling pathway by down-regulating TGFβ1 and TGFβ3 expression. Consequently, phosphorylation of TβRII, Smad2, and Smad3, downstream effectors of TGFβ, and expression of 3 TGFβ-responsive genes were reduced by maternal diabetes, and these reductions were prevented by SOD1 overexpression. Treatment with Tempol or TGFβ recombinant protein restored high-glucose-suppressed TGFβ signaling intermediates and responsive gene expression.

CONCLUSION

Oxidative stress mediates the inhibitory effect of hyperglycemia in the developing heart. Antioxidants, TGFβ recombinant proteins, or TGFβ agonists may have potential therapeutic values in the prevention of heart defects in diabetic pregnancies.

Metabolic Profiling and Phenotyping of Central Nervous System Diseases: Metabolites Bring Insights into Brain Dysfunctions

Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.

Metabolomic profile of amniotic fluid to evaluate lung maturity: the diaphragmatic hernia lamb model

Background

Tracheal occlusion (TO) stimulates lung growth in fetuses affected with congenital diaphragmatic hernia (CDH) although the processes involved in lung maturation still remain unknown. The objective of this study was to evaluate the metabolomic profile of amniotic fluid (AF) following TO in fetal lamb model in order to obtain an indirect view of mechanisms involved in pulmonary reversal hypoplasia and biochemical maturity in response to fetal TO.

Methods

Liquid Chromatography Mass Spectrometry was performed on lamb AF samples at: age I (70 days’ gestation); age II (102 days’ gestation); age III (136 days’ gestation). CDH was induced at age I and TO at age II.

Results

Betaine, choline, creatinine were found significantly increased during gestation in the control group. The CDH group showed choline (p =0.007) and creatinine (p =0.004) decreases during pregnancy. In the TO group choline and creatinine profiles were restored.

Conclusions

Alveolar tissue and fetal global growth ameliorated after TO. Metabolomics provided useful information on biochemical details during lung maturation. Metabolomic profiling would help to identify the best time to perform TO, in order to increase survival of CDH affected patients.

PreImplantation factor (PIF*) promotes embryotrophic and neuroprotective decidual genes: effect negated by epidermal growth factor

Background

Intimate embryo-maternal interaction is paramount for pregnancy success post-implantation. The embryo follows a specific developmental timeline starting with neural system, dependent on endogenous and decidual factors. Beyond altered genetics/epigenetics, post-natal diseases may initiate at prenatal/neonatal, post-natal period, or through a continuum. Preimplantation factor (PIF) secreted by viable embryos promotes implantation and trophoblast invasion. Synthetic PIF reverses neuroinflammation in non-pregnant models. PIF targets embryo proteins that protect against oxidative stress and protein misfolding. We report of PIF’s embryotrophic role and potential to prevent developmental disorders by regulating uterine milieu at implantation and first trimester.

Methods

PIF’s effect on human implantation (human endometrial stromal cells (HESC)) and first-trimester decidua cultures (FTDC) was examined, by global gene expression (Affymetrix), disease-biomarkers ranking (GeneGo), neuro-specific genes (Ingenuity) and proteins (mass-spectrometry). PIF co-cultured epidermal growth factor (EGF) in both HESC and FTDC (Affymetrix) was evaluated.

Results

In HESC, PIF promotes neural differentiation and transmission genes (TLX2, EPHA10) while inhibiting retinoic acid receptor gene, which arrests growth. PIF promotes axon guidance and downregulates EGF-dependent neuroregulin signaling. In FTDC, PIF promotes bone morphogenetic protein pathway (SMAD1, 53-fold) and axonal guidance genes (EPH5) while inhibiting PPP2R2C, negative cell-growth regulator, involved in Alzheimer’s and amyotrophic lateral sclerosis. In HESC, PIF affects angiotensin via beta-arrestin, transforming growth factor-beta (TGF-β), notch, BMP, and wingless-int (WNT) signaling pathways that promote neurogenesis involved in childhood neurodevelopmental diseases—autism and also affected epithelial-mesenchymal transition involved in neuromuscular disorders. In FTDC, PIF upregulates neural development and hormone signaling, while downregulating genes protecting against xenobiotic response leading to connective tissue disorders.

In both HESC and FTDC, PIF affects neural development and transmission pathways. In HESC interactome, PIF promotes FUS gene, which controls genome integrity, while in FTDC, PIF upregulates STAT3 critical transcription signal. EGF abolished PIF’s effect on HESC, decreasing metalloproteinase and prolactin receptor genes, thereby interfering with decidualization, while in FTDC, EGF co-cultured with PIF reduced ZHX2, gene that regulates neural AFP secretion.

Conclusions

PIF promotes decidual trophic genes and proteins to regulate neural development. By regulating the uterine milieu, PIF may decrease embryo vulnerability to post-natal neurodevelopmental disorders. Examination of PIF-based intervention strategies used during embryogenesis to improve pregnancy prognosis and reduce post-natal vulnerability is clearly in order.

Metabolomic prediction of fetal congenital heart defect in the first trimester

OBJECTIVE

The objective of the study was to identify metabolomic markers in maternal first-trimester serum for the detection of fetal congenital heart defects (CHDs).

STUDY DESIGN

Mass spectrometry (direct injection/liquid chromatography and tandem mass spectrometry) and nuclear magnetic resonance spectrometry-based metabolomic analyses were performed between 11 weeks' and 13 weeks 6 days' gestation on maternal serum. A total of 27 CHD cases and 59 controls were compared. There were no known or suspected chromosomal or syndromic abnormalities indicated.

RESULTS

A total of 174 metabolites were identified and quantified using the 2 analytical methods. There were 14 overlapping metabolites between platforms. We identified 123 metabolites that demonstrated significant differences on a univariate analysis in maternal first-trimester serum in CHD vs normal cases. There was a significant disturbance in acylcarnitine, sphingomyelin, and other metabolite levels in CHD pregnancies. Predictive algorithms were developed for CHD detection. High sensitivity (0.929; 95% confidence interval [CI], 0.92-1.00) and specificity (0.932; 95% CI, 0.78-1.00) for CHD detection were achieved (area under the curve, 0.992; 95% CI, 0.973-1.0).

CONCLUSION

In the first such report, we demonstrated the feasibility of the use of metabolomic developing biomarkers for the first-trimester prediction of CHD. Abnormal lipid metabolism appeared to be a significant feature of CHD pregnancies.

Potential first trimester metabolomic biomarkers of abnormal birth weight in healthy pregnancies

OBJECTIVE

Macrosomia and low birth weight (LBW) can be associated with pregnancy complications and may affect the long-term health of the child. The aim of this study was to evaluate the metabolomic serum profiles of healthy pregnant women to identify early biomarkers of macrosomia and LBW and to understand mechanisms leading to abnormal fetal growth not related to mother's body mass index or presence of gestational diabetes.

METHOD

Serum samples from 770 women were collected between the 12th and 14th gestational week. Delivery samples were divided into three groups according to the infant birth weight as follows: low, <2500 g; normal, 2500-4000 g; and high >4000 g. Samples from women with any complications of pregnancy were excluded. Serum fingerprinting was performed by LC-QTOF-MS.

RESULTS

Lower levels of phospholipids, lysophospholipids, and monoacylglycerols; low vitamin D3 metabolites; and increased bilirubin level were associated with macrosomia. Because most changes involved lipids, as a concept of validation, adipocyte fatty acid-binding protein (A-FABP) levels were measured and found correlated with the studied lipids and birth weight.

CONCLUSION

Serum fingerprinting in early pregnancy can predict the risk of macrosomia. Serum levels of A-FABP and several lipids are promising prognostic markers for macrosomia in healthy pregnancies.

Metabolomic analysis for first-trimester trisomy 18 detection

OBJECTIVE

The purpose of this study was to determine whether nuclear magnetic resonance-based metabolomic markers in first-trimester maternal serum can detect fetuses with trisomy 18.

STUDY DESIGN

This was a study of pregnancies between 11 weeks and 13 weeks 6 days' gestation. We analyzed 30 cases of trisomy 18 and a total of 114 euploid cases. Nuclear magnetic resonance-based metabolomic analysis was performed. A further analysis was performed that compared 30 cases with trisomy 18 and 30 trisomy 21 (T21) cases.

RESULTS

Metabolomic markers were sensitive for trisomy 18 detection. A combination of 2-hydroxybutyrate, glycerol and maternal age had a 73.3% sensitivity and 96.6% specificity for trisomy 18 detection, with an area under the receiver operating curve: 0.92 (P < .001). Other metabolite markers, which include trimethylamine, were sensitive for distinguishing trisomy 18 from T21 cases.

CONCLUSION

This is the first report of prenatal trisomy 18 detection that has been based on metabolomic analysis. Preliminary results suggest that such markers are sensitive not only for the detection of fetal trisomy 18 but also for distinguishing this aneuploidy from T21.

Metabolic phenotyping and systems biology approaches to understanding neurological disorders

The development of high-throughput metabolic profiling and the study of the metabolome are particularly important in brain research where small molecules or metabolites play fundamental signalling roles: neurotransmitters, signalling lipids, osmolytes and even ions. Metabolic profiling has shown that metabolic perturbations in the brain go beyond alterations of neurotransmission and that variations in brain metabolic homeostasis are associated with neurological disorders. In this report, we will focus on recent developments in the field of metabolic phenotyping that have contributed to unravelling the pathophysiology of neurological diseases. Also, we will highlight the necessity of implementing systems biology approaches to integrate metabolic data and tackle the structural and functional complexity of the brain in normal and pathological conditions.