Amniotic Fluid and Maternal Serum Metabolic Signatures in the

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Amniotic fluid and maternal serum metabolic signatures in the 2nd trimester associated with pre-term delivery Christina Virgiliou, Helen G. Gika, Michael Witting, Anna A. Bletsou, Apostolos Athanasiadis, Menelaos Zafrakas, Nikolaos S. Thomaidis, Nikolaos Raikos, Georgios Makrydimas, and Georgios A. Theodoridis J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00845 • Publication Date (Web): 09 Jan 2017 Downloaded from http://pubs.acs.org on January 17, 2017

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Journal of Proteome Research

Amniotic fluid and maternal serum metabolic signatures in the 2nd trimester associated with pre-term delivery Christina Virgiliou1, Helen G. Gika2 , Michael Witting3, Anna A. Bletsou4, Apostolos Athanasiadis5, Menelaos Zafrakas6, Nikolaos S. Thomaidis4, Nikolaos Raikos2, Georgios Makridimas7, Georgios A. Theodoridis1*

1Department 2School

of Chemistry, Aristotle University Thessaloniki, 541 24 Thessaloniki, Greece

of Medicine, Aristotle University Thessaloniki, 541 24 Thessaloniki, Greece

3Helmholtz

Zentrum München, Research Unit Analytical BioGeoChemistry, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany

4Department

of Chemistry, University of Athens, Panepistimiopolis Zographou Athens15771 Greece

51st Department of Obstetrics and Gynaecology, Aristotle University Medical School, Papageorgiou General Hospital, Thessaloniki

6 Research Laboratory for Mastology, Gynecology and Obstetrics, School of Health and Medical Care, Alexander Technological Institute of Thessaloniki, 57400 Thessaloniki, Greece 7 School

of Medicine, University of Ioannina, Greece

*Corresponding author email address: [email protected] tel: 0030-2310997718

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Abstract Pre-term delivery (PTD) represents a major health problem which occurs in one in ten births. The hypothesis of the present study was that the metabolic profile of different biological fluids, obtained from pregnant women during the 2nd trimester of gestation, could allow useful correlations with pregnancy outcome. Holistic and targeted metabolomics approaches were applied for the complementary assessment of the metabolic content of prospectively collected amniotic fluid (AF) and paired maternal blood serum samples from 35 women who delivered preterm (between 29weeks+0days and 36weeks +5 days gestation) and 35 women delivered at term. The results revealed trends relating the metabolic content of the analysed samples with preterm delivery. Untargeted and targeted profiling showed differentiations in certain key metabolites in the biological fluids of the two study groups. In amniotic fluid, intermediate metabolites involved in energy metabolism (pyruvic acid, glutamic acid and glutamine) were found to contribute to the classification of the two groups. In maternal serum, increased levels of lipids and alterations of key end-point metabolites were observed in cases of preterm delivery. Overall, the metabolic content of second trimester amniotic fluid and maternal blood serum show potential for the identification of biomarkers related to fetal growth and preterm delivery.

Keywords: Pre-term delivery; amniotic fluid; maternal serum; metabolomics; targeted profiling; untargeted/holistic profiling; biomarker discovery


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1. Introduction Pre-term birth represents a major public health problem. According to the Word Health Organization (WHO), each year an estimated 15 million babies world-wide are born prematurely and this number seems to be rising. Prematurity complications are the main cause of death among children under 5 years of age being responsible for nearly 1 million deaths in 2013. The etiology of preterm birth, defined as delivery before 37 weeks of pregnancy is yet largely unknown as it can be initiated by multiple pathophysiologic processes including infection, systematic inflammation, activation of fetal hypothalamic-pituitary-adrenal axis, decidual hemorrhage, pathologic distension of the uterus and immunologically mediated processes1-2. On everyday clinical practice, fetal growth and pregnancy progress are monitored by ultrasound measurements. However, this approach has certain restrictions with limited potential for diagnostic and/or prognostic purposes in various clinical scenarios3. Although several biomarker studies related to preterm delivery (PTD) have been conducted, the lack of knowledge on the molecular mechanisms and biochemistry related to the PTD results to limited number of markers for early diagnosis and prevention of preterm labor 4 . Metabolomics offer a good perspective in this endeavor. The examination of the metabolic content of a sample through an omics approach provides a picture of the response of the organism to pathophysiological stimuli. Thus, an organism’s metabolic fingerprint may serve as an excellent probe for its phenotype, providing molecular signatures in certain disease states and/or under physiological conditions.



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So far, a limited number of studies have been applied with the use of high- throughput technologies in this setting. These studies have reported the metabolic profiling of maternal biological matrices, namely placental membranes, amniotic fluid (AF), urine and cervicovaginal secretions in order to identify markers related to PTD.5,6,7,8,9,10 Based on these, alteration in hepatic metabolites involving xenobiotic detoxification and CoA metabolism was revealed in cases of PTD through global metabolic profiling of AF5. Earlier Romero et al 9studied the human amniotic fluid metabolome by LC-MS and found that it contains products of the intermediate metabolism of mammalian cells and xenobiotic compounds which could provide identification of patients with high risk of PTD. The authors reported also correlation in the concentration of certain aminoacids in AF with cases of PTD with intraamniotic infection and/or inflammation. In another study10 alterations in amino acid fluxes through the placenta and a possible tendency for hyperglycemia was observed through AF metabolic profiling probably affecting pre-PTD fetuses. In this study Maitre et al. report early (i.e. at the end of first trimester) differences in urinary metabolic phenotypes in pregnant women with PTD and fetal growth restriction. Urinary acetate, tyrosine, formate, trimethylamine, lysine and glycoprotein were associated with increased risk of negative birth outcomes. In the present study, the metabolome of maternal serum and amniotic fluid at the second trimester was investigated in women who delivered either prematurely or at term, by using Ultra High Performance Liquid Chromatography coupled to Mass Spectrometry (UHPLC-MS) in both reversed phase and hydrophilic interaction separation modes. The study was part of the EmbryoMetabolomics project11. The key objective of this project was to investigate the potential of metabolomics approaches on the assessment of pregnancy outcome. In particular the metabolic profile signatures of 2nd 4 ACS Paragon Plus Environment

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trimester AF and maternal serum samples were studied in order to identify markers or concentration patterns able to characterize PTD and subsequently focus on specific assays for diagnostic and/or prognostic purposes. The present study provides new knowledge on the correlation of serum and amniotic fluid metabolic profiles to fetal growth and premature delivery. 2. Materials and Methods 2.1 Reagents and Materials LC/MS grade Acetonitrile (ACN) was obtained from Carlo Erba (Van de Remil, France). Distilled Water (18.2MΩ) for chromatographic separation was purified in Milli-Q device (Millipore Merck Darmstadt, Germany). Ammonium formate was purchased from Sigma Aldrich (Gillingham, Dorset, UK). For serum lipid profiling method, ACN, isopropanol, methanol, formic acid and ammonium formate were obtained from Sigma Aldrich (Sigma-Aldrich GmbH, Taufkirchen, Germany).The standards were of analytical or higher grade and for this study were obtained from various vendors. 2.2 Amniotic fluid and maternal serum samples AF and serum samples were collected from women at the second trimester of their pregnancy in the University General Hospital of Ioannina. The study was conducted in the frame of the Embryometabolomics project 11. More than 100 women were enrolled in the study, however due to limited number of pre-term delivery cases 70 were analysed for the current study. Inclusion criteria were based on individual characteristics (age, weight, etc) and obstetrical history. AF was collected by a Fetal Medicine Specialist during ultrasound guided amniocentesis scheduled between the 14th and the 23rd week of pregnancy. Blood samples were also collected in the same visit. The outcomes of pregnancies were followed and recorded. 5 ACS Paragon Plus Environment


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There were 35 preterm deliveries (between 29 weeks + 0 days and 36 weeks +5 days gestation) and 35 term deliveries (between 38 and 40 weeks gestation) paired based on the age of the mother and the gestational week when amniocentesis was performed. Selection criteria of control samples were based on participants’ characteristics data of preterm delivery cases. Both study groups contained subjects with same age and weight range while with regards to clinical records both groups contained subjects with clear clinical history in order to avoid ambiguous data interpretation. (Information on the study population is given Table 1). All AF and maternal serum samples, were frozen directly after collection at -80oC, All procedures have been performed according to the EU and local legislations and have been authorized by the Bioethical Committees of the Aristotle University of Thessaloniki and the University General Hospital of Ioannina.

2.3 Sample preparation Samples were allowed to thaw in room temperature prior to analysis. For both AF and maternal serum a fraction of 50 μl was mixed with 150 μl of ACN. The diluted samples were then vortex mixed (5 min) and centrifuged for 15 min (14000 g) to remove proteins or particulates. Supernatants were transferred to LC/MS vials and loaded on the autosampler tray maintained at 10oC for the duration of the analysis. Quality Control (QC) samples were prepared for the untargeted analysis by mixing equal volumes of all samples of the dataset each time. The same procedure was followed for all LC-MS analyses performed. 2.4 UHPLC-MS analysis


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AF and the paired maternal serum samples from 70 gestations were analysed by complementary methods both with RP and HILIC chromatography. 2.4.1 UHPLC- TOF MS untargeted profiling Two different untargeted profiling methods were applied. For maternal serum samples a lipid profiling UHPLC- TOF-MS method was applied, while for a subset of the amniotic fluid samples comprising the extreme cases (n=27) a method for profiling the components of medium polarity and unpolars was applied by UHPLC- TOF-MS. For lipid profiling of maternal serum a generic acetonitrile (AcN)/isopropanol (iProH) gradient was applied on a Cortecs C18 column (1.6μm, 150 mm × 2.1 mm, Waters GmbH, Eschborn, Germany) using a Waters Acquity UPLC (Waters GmbH, Eschborn, Germany). More specifically solvent A consisted of 60% ACN and 40% water and solvent B of 90% iPrOH and 10%ACN, both with 10 mM ammonium formate and 0.1% formic acid. Gradient programme and other chromatographic parameters were set based on a previous study by Witting et al. where the optimization of a UHPLC-TOF MS approach for in depth lipidomic profiling is described 12 MS-data was collected on an UHR-TOF/MS (Bruker Daltonics, Bremen, Germany) operated in positive and negative ionisation mode (+ESI, -ESI) in two separate experiments; parameters were set as follows: capillary +4500 V or -4000 V, end plate offset set at -500V, dry gas flow 8 l/min, dry gas temperature 200oC, nebuliser gas pressure 2 bar, mass range 100- 1500 m/z and applied spectra rate at 2Hz. For individual recalibration of each chromatogram 1:4 diluted Low Concentration Tune Mix (Agilent, Waldbronn, Germany) was injected before each run between 0.1 and 0.3 min. For profiling of AF a Waters Acquity HSS T3 C18 column (2.1mm x 100mmm, 1.8μm) at 40oC was used on an Ultimate 3000 RSLC (Dionex, Sunnyvale CA, USA) using a binary 7 ACS Paragon Plus Environment


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solvent system consisting of solvent A (0.1% formic acid in water) and B (0.1% formic acid in AcN). Gradient elution profile started with an isocratic step of 1 min at 2% B, then increased to 50% B in 10 min and finally to 100% B over the next 5 min followed by 2.5 min equilibration prior to the next injection Mobile phase flow rate was 0.2 ml/min and a 5 μL sample volume was injected into the system. TOF MS data were acquired by a Bruker Maxis Impact (Bruker Daltonics,) time of flight mass spectrometer (QTOF) in both +ESI and -ESI. Scan rate was set at 2Hz over a mass range of 90-1000 m/z. The. capillary voltage was set at 2500 V and -4500 V, the end plate offset potential was set at ±500 V, the nebulizer gas pressure at 2 bar and the dry gas flow rate 10 l/min at a temperature of 350oC. External calibration was daily performed with sodium formate solution. The sodium formate calibration mixture consisted of 10mM sodium formate in a mixture of water/isopropanol (1:1 v/v). The theoretical exact masses of calibration ions with formulas Na(NaCOOH)1-14 in the range of 50-1000 Da were used for mass recalibration. Samples were internally recalibrated using the calibrant segment in the beginning (0.10.25 min) of each chromatogram. Along each run a QC sample was analyzed every 10 samples to monitor the quality of the acquired data. 13-14

2.4.2 UHPLC-MS/MS targeted profiling Maternal serum and AF samples were additionally analysed by a multi-targeted method on a HILIC UHPLC/MS-MS system for the profiling of the hydrophilic constituents. A standard mixture of all metabolites was analysed in between samples as QC (details given in supplementary material). The applied method which was developed in our lab 8 ACS Paragon Plus Environment

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and described previously by Virgiliou et al

15

was adapted for the certain biological

matrices semi-quantifying a set of 108 key metabolites involved in central metabolic pathways such as amino-acids, acids, sugars, amines etc. Details on the chromatographic conditions can be found in the previous communication

15.

All other details concerning

the quantification procedure, the analytes and analytical figures of merit can be found in Supplementary material Table S1, S2. 2.5 Data pre-treatment and chemometric analysis Maternal serum lipid profiling data were processed by Genedata Expressionist for Mass Spectrometry 9.1. All chromatograms were, noise subtracted, internally recalibrated using the calibrant segment in the beginning of each run and aligned in RT direction using a pairwise alignment tree method and a m/z window of 0.1 Da. Peaks were detected using a spline-based peak detection method (retention time window:3 scans, subtraction threshold: 800, minimum m/z length 3points, minimum rt length 3 points) and grouped in isotopic clusters Chromatogram singleton filter resulted in elimination of clusters with only one member. Aligned peak list was exported as .xlsx file for further statistical analysis. AF untargeted data was processed by XCMS (free package software) after internal calibration using the software DataAnalysis 4.1 (Bruker). XCMS parameters were set after chromatogram evaluation. For peak identification in XCMS mass accuracy was set at 6 ppm for +ESI and 10 ppm for -ESI. Cent Wave algorithm was applied for peak picking. Peak width was set as follows: 6-40 sec for +ESI and 6-20 sec for -ESI data. Default values applied for m/z error (0.05) and S/N threshold (5)

16,17.

CAMERA (R-

Package) was used for grouping of related features and annotation of ion species.



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For the targeted data TargetLynx application, MassLynx Waters® version 4.1 (SCN 882) was used. Multivariate statistical analysis was performed using Simca-P v13.0 software (UMETRICS AB, Umea, Sweden). As first step, the quality of the data was evaluated by inspection of QC samples in PCA plots. Tight cluster of the QC samples in PCA models indicated satisfactory precision of the analytical system. Following this, the analysis of the test samples aimed in revealing differences with biological significance. Partial least squared discriminant analysis (PLS-DA) was used for modeling the differences between the metabolic profile of women with PTD and delivery at term, with statistical evaluation of the models. In order to increase the reliability of the models R2Y(cum) and Q2(cum) approach was applied (R2Y(cum) :total sum of variation in Y explained by the model and Q2(cum): goodness of prediction). Potential biomarker selection was based on Volcano plot (R environment, metabolomics package script), S-plot, loading plot and variable importance in the project column plot (VIP) For untargeted data, features contributing to group differentiation were identified after application of a set of criteria, starting from studying contribution S-plot with criterion the higher absolute p and p(corr) value. Only features with VIP value >1 and Bonferroni corrected p value 0.04 and p(cor)>0.6 were selected from +ESI and sixty two with p>0.05 and p(cor)>0.5 from –ESI data. Based on volcano plot (given in Figure 2c and 2d), 109 features and six features are indicated with p1 in +ESI and -ESI data respectively. These correspond to potentially interesting biomarker candidates, reflecting discrepant metabolic traits and included the above ions found by S-plot. Variables without 13 ACS Paragon Plus Environment


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significant differences (p value >0.05 and VIP60 %, 14 ACS Paragon Plus Environment

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unpublished data), quantitation was based on a standard addition curve obtained by spiking the QC pooled sample at 9 concentration levels. All relevant details on quantification are provided in Supplementary information. Precision of the analytical system within batch was assessed by statistical analysis of peak areas obtained by the analysis of QC standard mixtures which were analysed every 10 test samples (QC, n=6). It was found that all metabolites with the exception of adenosine in AF and taurine in maternal serum sample sets were within acceptable limits of RSD

Amniotic Fluid and Maternal Serum Metabolic Signatures in the

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