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Placenta 30 (2009) 424–433

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Placenta

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Differential Placental Gene Expression in Severe Preeclampsia

V. Sitras a,*,1, R.H. Paulssen b,1, H. Grønaas c,2, J. Leirvik c, T.A. Hanssen d, Å. Vårtun a, G. Acharya a

a Department of Obstetrics and Gynecology, University Hospital of Northern Norway and Institute of Clinical Medicine, University of Tromsø, PO Box 24, N-9038 Tromsø, Norwayb Laboratory of Molecular Medical Research, Institute of Clinical Medicine, University of Tromsø, N-9037, Norwayc Department of Medical Genetics, University Hospital of Northern Norway, N-9038, Norwayd Department of Pathology, University Hospital of Northern Norway, N-9038, Norway

a r t i c l e i n f o

Article history:Accepted 28 January 2009

Keywords:Gene expressionMicroarraysPlacentaSevere preeclampsia

* Corresponding author. Tel.: þ47 776 26 000; fax:E-mail address: vasilis.sitras@unn.no (V. Sitras).

1 These authors contributed equally to this work.2 Present address: WesternGeco, Oslo Technology

N-1372 Asker, Norway.

0143-4004/$ – see front matter � 2009 Elsevier Ltd.doi:10.1016/j.placenta.2009.01.012

a b s t r a c t

We investigated the global placental gene expression profile in severe preeclampsia. Twenty-one womenwere randomly selected from 50 participants with uncomplicated pregnancies to match 21 patients withsevere preeclampsia. A 30 K Human Genome Survey Microarray v.2.0 (Applied Biosystems) was used toevaluate the gene expression profile. After RNA isolation, five preeclamptic placentas were excluded dueto poor RNA quality. The series composed of 37 hybridizations in a one-channel detection system ofchemiluminescence emitted by the microarrays. An empirical Bayes analysis was applied to finddifferentially expressed genes. In preeclamptic placentas 213 genes were significantly (fold-change� 2and p� 0.01) up-regulated and 82 were down-regulated, compared with normal placentas. Leptin (40fold), laeverin (10 fold), different isoforms of b-hCG (3–6 fold), endoglin (4 fold), FLT1 (3 fold) and FLT4 (2fold) were up-regulated. PDGFD was down-regulated (2 fold). Several differentially expressed genes wereassociated with Alzheimer disease, angiogenesis, Notch-, TGFb- and VEGF-signalling pathways. Sixteengenes best discriminated preeclamptic from normal placentas. Comparison between early- (<34 weeks)and late-onset preeclampsia showed 168 differentially expressed genes with oxidative stress, inflam-mation, and endothelin signalling pathways mainly involved in early-onset disease. Validation of themicroarray results was performed by RT-PCR, quantitative urine hCG measurement and placentalhistopathologic examination. In summary, placental gene expression is altered in preeclampsia and weprovide a comprehensive list of the differentially expressed genes. Placental gene expression is differentbetween early- and late-onset preeclampsia, suggesting differences in pathophysiology.

� 2009 Elsevier Ltd. All rights reserved.

1. Introduction

Preeclampsia is a clinical syndrome defined as new-onsethypertension and proteinuria after 20 weeks gestation in a previ-ously normotensive woman [1]. It affects 3–8% of all pregnanciesand is a major cause of maternal and perinatal morbidity andmortality world-wide. Preeclampsia occurs only in the presence ofplacenta and its resolution begins after delivery. Therefore, theplacenta must play a primary role in its etiology. Moreover,placental gene expression reflects the feto–maternal interactionand seems to control the maternal phenotype [2]. Furthermore,a high recurrence risk of severe preeclampsia in subsequent preg-nancies and a clear familial predisposition indicate that there is

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a genetic component involved [3]. However, large genetic linkagestudies have failed to demonstrate clear inheritance pattern [4]suggesting that a variety of genes may predispose to preeclampsiain different populations.

Gene expression profile of first trimester [5] and term [6] humanplacentas has been previously reported. There are no studiesinvestigating gene expression changes throughout gestationbecause of obvious difficulties of obtaining placental sampleslongitudinally. Gene expression profile is consistently altered inpreeclamptic placentas, as reported in a recent review of sixteenstudies that used microarrays [7]. However, the results have beeninconsistent regarding which genes are differentially expressed,possibly due to small sample size, matching variability, differentmaternal ethnicity, different types of microarray chips and plat-forms used and indirect comparison design (i.e. pooling mRNAfrom multiple individuals to one single sample).

The clinical management of preeclampsia depends on theseverity of the maternal syndrome and the degree of fetal compro-mise. There are differences between early- and late-onsetpreeclampsia regarding clinical presentation and outcome [8].

V. Sitras et al. / Placenta 30 (2009) 424–433 425

Histopathological examination of placenta also shows differentmorphological characteristics depending on the timing of disease-onset [9]. However, whether these differences are a reflection ofdifferential placental gene expression is not known. The aims of ourstudy were:

a) To provide a comprehensive list of differentially expressedplacental genes in severe preeclampsia in comparison tonormal controls using genome-wide microarrays and a directcomparison design.

b) To investigate whether early- and late-onset preeclampsia havedifferent placental gene expression profiles.

2. Materials and methods

2.1. Study population

We recruited 50 healthy women with uncomplicated pregnancies and 21women with severe preeclampsia to our study. All participants were Caucasian.Severe preeclampsia was defined as blood pressure (BP) of at least 160 mmHg(systolic) and/or 110 mmHg (diastolic), with proteinuria �2þ on dipstick, measuredon at least two occasions 6 h apart while the patient was on bed rest, or hemolysis,elevated liver enzymes and low platelet (HELLP) syndrome, after the 20th week ofgestation. Women with pre-existing chronic hypertension, renal disease, lupuserythematosus, diabetes, and gestational hypertension without proteinuria wereexcluded. The study was approved by the Regional Committee for Medical ResearchEthics and informed written consent was obtained from all the participants. All theparticipants had a physical examination and ultrasonography�72 h before delivery.The outcome of pregnancy and information on the neonates were prospectivelyrecorded. Umbilical cord blood samples were collected immediately after birth andanalysed for acid-base status.

2.2. Ultrasonography

Ultrasonography was performed using an Acuson Sequoia 512 (Mountainview,CA, USA) system with a 2.5–6 MHz curvilinear transducer. After a survey of fetalanatomy, biometry was performed to assess fetal growth. Blood flow velocitywaveforms were obtained using Doppler from the middle cerebral artery, umbilicalartery at a free-loop of the cord and maternal uterine arteries. Pulsatility index (PI)was calculated from the blood velocity waveforms as: PI¼ (peak systolic veloc-ity� end diastolic velocity)/time-averaged maximum velocity. Umbilical vein anduterine artery time-averaged intensity weighted mean velocities and diameters weremeasured and the volume blood flow was calculated as described previously [10].

2.3. Placental sample collection and conservation

Placental samples were obtained immediately after delivery by two designatedpersons. Chorionic tissue was dissected from a standardised location - approxi-mately 2 cm beside the umbilical cord insertion, from the middle layer of placentamidway between maternal and fetal surfaces - in order to reduce the bias related tothe physiological difference in gene expression within the same placenta dependingon the sampling site [11]. Placental samples were collected from macroscopicallynormal areas excluding sites of infarction, haemorrhage and fibrin deposition. Thecollected specimen (w2 cm3) was transferred to a Petri dish and washed withphysiological saline to remove any contamination with maternal blood and amnioticfluid. Each tissue sample was cut in two pieces and transferred to tubes containing1.5 ml RNAlater solution (RNA stabilization reagent, Qiagen GmbH, Germany), andstored at �70 �C until RNA isolation, microarray and real-time polymerase chainreaction (RT-PCR) were performed.

2.4. Placental morphology

All placentas were immersed in 4% formalin and sent for histopathologicexamination. A single pathologist examined the preeclamptic placentas according toour standard laboratory procedure without prior knowledge of clinical status. Fivesections were sampled from the umbilical cord, membranes, central portion ofplacenta, tangential section from basal plate and transmural central section,respectively. All sections were evaluated for inflammation and graded as describedpreviously [12] in standard hematoxylin and eosin stained slides. They were alsoevaluated for any evidence of atherosclerosis, thrombosis or infarction.

2.5. RNA isolation and quality/quantity control

Disruption and homogenization of tissue specimens were performed inlysis buffer using the MagNa Lyser Instrument (Roche Applied Science,

Germany), according to the manufacturer’s instructions. Isolation of total RNAwas performed using the MagNa Pure Compact RNA isolation kit and the MagNaPure Compact Instrument (Roche Applied Science, Germany). RNA was quan-tified by measuring absorbance at 260 nm, and RNA purity was determined bythe ratios OD260 nm/280 nm and OD230 nm/280 nm using the NanoDropinstrument (NanoDrop� ND-1000, Wilmington, USA). The RNA integrity wasdetermined by electrophoresis using the Agilent 2100 Bioanalyser (Matriks,Norway). Only samples with RNA Integrity Number (RIN) >7.2 were used formicroarray.

2.6. Microarray experimental design

Twenty-one out of 50 normal placentas were randomly selected to match with21 preeclamptic placentas, accounting for parity. Parity was taken into account,because epidemiological studies suggest that the risk of preeclampsia is at leasttwice as high in first pregnancies compared with later pregnancies [13]. Fivepreeclamptic placentas were excluded because of poor RNA quality, leaving 16preeclamptic placentas for microarray experiments. Thus, a total of 37 hybridiza-tions were performed, applying a direct comparison design.

2.7. Microarray procedures

Total RNA samples were processed into digoxigenin (DIG) - labelled cRNA usingthe Applied Biosystems Chemiluminescent NanoAmp� RT-IVT Labeling Kit. Thelabelled DIG-cRNA (10 mg per microarray) was then injected into each microarrayhybridization chamber. Following hybridization at 55 �C for 16 h, the unboundmaterial was washed from the microarrays. Features that retained bound DIG-labelled cRNA were visualized using the Applied Biosystems ChemiluminescenceDetection Kit. Anti-DIG alkaline phosphatase was used to hydrolyse a chem-iluminescence substrate to generate light at 458 nm which was detected by theApplied Biosystems 1700 Chemiluminescent Microarray Analyzer. The HumanGenome Survey Microarray v.2.0 (Applied Biosystems) with 32,878 probes for theinterrogation of 29,098 genes was used for microarray analysis.

2.8. Image and data analysis

The features were extracted from the arrays using the ABI1700 software.Normalization was carried out using quantile normalization, which forces all theslides to have the same intensity distribution. Spots on the arrays with less thanexcellent signal and with expression values missing for �25% of the samples in thepreeclampsia group or �35% in the control group were filtered out. For thepurpose of finding differentially expressed genes, we applied an empirical Bayesanalysis [14] using the LIMMA package [15]. This involves using a t-statistic whosestandard error component has been pooled across all other gene standard errorestimates. This gives more degrees of freedom with which to make statisticalinference, and produces more stable standard error estimates. The data wereanalysed using an ANOVA two-component linear model accounting forpreeclampsia versus normal and nulliparity versus multiparity. We further usedthe same method in order to identify potential differentially expressed genesbetween early- and late-onset preeclampsia. The cut-off time point of early-versus late-onset preeclampsia was 34 weeks gestation. The prior guess of theproportion of differentially expressed genes was set to 0.01. A two-fold-change inexpression of any gene was considered significant, if the difference in fluorescenceintensity between the samples reached a p-value of <0.01. A hierarchical clusteranalysis was conducted on the 300 most differentially expressed genes. Thedistance metric was Euclidian and complete linkage was used. A PredictiveAnalysis of Microarrays (PAM) [16] was conducted in order to investigate whetherany set of genes provides predictive power between the groups (preeclampsiaversus normal).

2.9. Gene annotations and pathway analysis

We used Protein ANalysis THrough Evolutionary Relationships (PANTHER)which is a freely available, comprehensive software system for relating genesequence to specific molecular functions, biological processes and pathways (http://www.pantherdb.org/).

Additionally, we applied two novel methods in order to find weak but coordi-nated shifts in gene expression that could result in a significant up- or down-regulation of a pathway. Namely, the Gene Set Enrichment Analysis (GSEA) [17] thatuses the whole raw data file consisting of the normalised ratios per gene per array(18,800 genes), irrespective of their fold-change and the Mann–Whitney U-test [18]that uses the mean ratio of all differentially expressed genes.

2.10. Database submission of microarray data

The microarray data were prepared according to minimum information abouta microarray experiment (MIAME) recommendations and deposited in the GeneExpression Omnibus (GEO) database: http://www.ncbi.nlm.nih.gov/geo/. The GEOaccession number for the platform is GSE10588.

V. Sitras et al. / Placenta 30 (2009) 424–433426

2.11. Validation of microarray results by RT-PCR

The expression of 16 selected genes was validated by RT-PCR. Total RNA frompreeclamptic and healthy placentas was reverse transcribed using High-CapacitycDNA Reverse Transcription Kit (Applied Biosystems, Part Number 4368814) asdescribed by the manufacturer’s protocol. TaqMan RT-PCR amplification was per-formed with an ABI HT7900 Instrument (Applied Biosystems) using the TaqMan�

Gene Expression Assays (Applied Biosystems, USA). Thermal cycling conditions wereas follows: denaturation for 20 s at 95 �C, then 40 cycles PCR with denaturation for1 s at 95 �C. Annealing and extension for 20 s at 60 �C (total run time was approx-imately 27 min). Sample volume used was 20 ml. The following AB Assay IDs indicatethe unique primers used for RT-PCR and can be found at www.appliedbiosystems.com: PPIA, Hs99999904_m1; LEP, Hs00174877_m1; FLJ90650, Hs01060574_m1;FLT1, Hs00176573_m1; PDGFD, Hs00937332_m1; COX17, Hs00705436_s1; BRSK2,Hs00908883_g1; LHB, Hs00751207_s1; METT5D1, Hs00541457_m1; INHA,Hs00171410_m1; CYP1B1, Hs00164383_m1; PAPPA2, Hs00395734_m1; COL17A1,Hs00166711_m1; CRLF1, Hs00191064_m1; PLA2G4A, Hs00233352_m1; PTGS2,Hs00153133_m1 and ADCY2, Hs00392729_m1. Cyclophilin A was used as referencegene. Samples for each experiment were run in triplicate and averaged for finalquantification. The fold inductions were calculated as described previously [19].

2.12. Quantitative urine human chorionic gonadotropin (hCG) measurement

Urinary samples were collected from the mother before delivery and storedat �70 �C until further analysis. We measured urinary hCG concentration in41 normal pregnancies and 18 pregnancies affected by severe preeclampsia byan automated electrochemiluminescence immunoassay method using intacthCGþ b-subunit kit (Modular E170 Analyser, Roche Diagnostics) which has previouslybeen validated [20].

2.13. Leptin immunofluorescence

Tissue sections were fixed in formalin and embedded in paraffin blocksaccording to standard procedures. Glass slides were cleaned with 95% ethanol,treated with subbing solution and airdried. 4–6 micron thick tissue sections werecut and applied to slides. Slides were deparaffinized in xylene using three changes5 min each. Sections were hydrated gradually through graded alcohols (100%ethanol twice for 10 min each, then 95% ethanol twice for 10 min each). Slides werethen washed in deionised water for 1 min with stirring and excess liquid aspiratedfrom slides.

Antigen unmasking was performed using heat treatment. Slides were placed ina prewarmed solution of 10 mM sodium citrate buffer, pH 6.0 for 5 min. This stepwas repeated once. Slides were let to cool down at room temperature in the bufferfor 20 min before they were washed in deionised water three times for 2 min eachand excess liquid was aspirated from slides.

Table 1Phenotype of the study population, hemodynamic parameters and pregnancy outcome. Vvariables. Differences in mean and proportions among groups were assessed using Stud

Maternal age (years)Nulliparous n (%)Body Mass Index at first antenatal visit (kg/m2)Body Mass Index before delivery (kg/m2)Mean arterial pressure before delivery (mmHg)Proteinuria (g/l)Uterine artery pulsatility index (mean of the left and right side)Uterine artery protodiastolic notchingTotal uterine artery volume blood flow (ml/min)Middle cerebral artery pulsatility indexUmbilical artery pulsatility indexUmbilical vein volume blood flow normalised for birthweight (ml/min/kg)Gestational age at delivery (days)Caesarean sectionBirthweight (g)Birthweight� 10 percentilePlacental weight (g)5 min APGAR scoreArterial cord blood pHArterial cord blood Base ExcessVenous cord blood pHVenous cord blood Base Excess

a Seven nulliparous preeclamptic women [3 (43%) with early- and 4 (57%) with late-ononset preeclampsia].

b Five women who had early-onset preeclampsia were delivered by caesarean section asection).

Slides were incubated with 500 ml 10% normal goat blocking serum (Santa CruzBiotechnology, Inc, USA) in 1� phosphate buffered saline (PBS) for 20 min at roomtemperature. Suction was used to remove reagents (drying of specimens was avoi-ded between steps) before slides were washed in 1� PBS two times for 2 min each.Primary antibody for leptin 2.5 mg/ml (Ob (A-20) Santa Cruz Biotechnology, Inc, USA)in PBS with 1.5% normal blocking serum was incubated for 60 min. PBS only wasused to test the specificity of the primary antibody (negative control). Slides werewashed with three changes of PBS for 5 min each and then incubated for 45 min atroom temperature with secondary goat anti-rabbit IgG-FITC 2.5 mg/ml (Santa CruzBiotechnology, Inc, USA) in PBS with 1.5% normal blocking serum. Slides werewashed with three changes of PBS for 2 min each before they were airdried andcounterstained with DAPI (40 ,6-diamidino-2-phenylindole) II (Vysis, Abbott Diag-nostics, USA).

Images were obtained using a CytoVision (Applied Imaging, San Jose, CA, USA)digital system equipped with a charged-coupled device (CCD) camera (Cohu Inc.,San Diego, USA).

3. Results

RNA samples from 16 out of 21 preeclamptic placentas passedthe quality criteria and were used for microarrays. All placentascollected from uncomplicated pregnancies yield RNA of goodquality. The phenotype of the study population including clinicaland hemodynamic data, and pregnancy outcome are presented inTable 1. Preeclamptic women had an average mean arterial pressureof 132 mmHg and proteinuria of 5 g in a 24-h urine specimen.Preeclamptic women were not significantly different in terms ofage, parity and body mass index (BMI) compared to their controls.However, they had significantly higher mean uterine artery PI andreduced uterine artery volume blood flow, but the fetal circulationwas not compromised as indicated by normal cerebro-placentalratio (middle cerebral PI/umbilical artery PI) and normalisedumbilical vein volume blood flow. Eleven out of sixteenpreeclamptic women were delivered prematurely (at <37 weeks)by Caesarean section before the onset of labour and among them 3had HELLP syndrome. Among controls, eight women were deliv-ered by caesarean section and the remaining 13 had a vaginaldelivery. The number of small for gestational age babies wassignificantly higher and placental weight lower amongpreeclamptic women compared to controls. Two preeclampticwomen had growth restricted fetuses (defined as birthweight

alues are expressed as mean� SD for continuous variables and n (%) for categoricalent’s t-test and chi-square test, respectively.

Preeclampsia (n¼ 16) Healthy controls (n¼ 21) p-value

30.5� 5.2 30.2� 4.8 0.97 (44%)a 9 (43%) 125.9� 4.8 24.8� 5.3 0.531.2� 5.8 29.8� 4.2 0.5132� 10 89� 8 <0.00013.93� 2.5 – –1.37� 0.70 0.74� 0.30 0.0027 (44%) 1 (5%) 0.004458� 383 905� 572 0.031.50� 0.41 1.27� 0.30 0.0721.17� 0.36 0.78� 0.18 0.00184.6� 47.5 66.2� 31.4 0.2238� 25 277� 9 <0.000111 (69%)b 8 (38%) 0.0652181� 998 3653� 619 0.0007 (44%) 3 (14%) 0.046445� 183 648� 154 0.0018–10 9–10 0.17.26� 0.07 7.26� 0.03 0.9�2.3� 3.8 �2.4� 1.9 0.97.30� 0.05 7.33� 0.04 0.1�2.00� 3.6 �2.23� 5.9 0.9

set preeclampsia] and nine multiparous [2 (22%) with early- and 7 (78%) with late-

nd 11 women had late-onset preeclampsia (5 delivered vaginally and 6 by caesarean

Table 2Genes up-regulated in placentas obtained from women with severe preeclampsiacompared to controls, with fold-change �2.0 and p� 0.01. They are clustered interms of biological processes and subdivided into the indicated subgroups.

Genesymbol

Gene name Foldinduction

1. Cell proliferation and differentiationBHLHB2 Basic helix-loop-helix domain containing, class B, 2 3.0EPHB3 EPH receptor B3 2.0FLT4 fms-related tyrosine kinase 4 2.4FLT1 fms-related tyrosine kinase 1 2.6GPR126 Protein-coupled receptor 126 2.1INHBA Inhibin, beta A (activin A, activin AB alpha polypeptide) 2.3MLF2 Myeloid leukaemia factor 2 2.4NDRG1 N-myc downstream regulated gene 1 2.7PAPPA2 Pregnancy-associated plasma protein-A (pappalysin 2) 2.9

2. Immunity and defenceAPS Adaptor protein with pleckstrin homology and src

homology 2 domains2.2

ARHGAP26 Rho GTPase activating protein 26 2.2GRN Granulin 2.0G6PC3 Glucose 6 phosphatase, catalytic, 3 2.6NOTCH3 Notch homolog 3 (drosophila) 2.4PVRL4 Poliovirus receptor-related 4 2.5

3. Cell structureKRT19 Keratin, type I cytoskeletal 2.3MFAP5 Microfibrillar associated protein 5 2.3PDLIM4 PDZ and LIM domain 4 2.6PLEC1 Plectin 1, intermediate filament binding protein 500 kDa 3.2FLNB Filamin B 2.2

4. Lipid metabolismABCA12 ATP-binding cassette, sub-family A (ABC1), member 12 2.3CYP26A1 Cytochrome P450, family 26, sub-family A, polypeptide 1 3.0PNPLA2 Patatin-like phospholipase domain containing 2 2.5OSBPL9 Oxysterol binding protein-like 9 2.7OXCT2 3-Oxoacid CoA transferase 2 2.5

5. TransportABCA12 ATP-binding cassette, sub-family A (ABC1), member 12 2.3BIN2 Bridging integrator 2 2.4RAMP2 Receptor (calcitonin) activity modifying protein 2 2.4SLC11A1 Solute carrier family 11, member 1 2.4SLC2A5 Solute carrier family 2 (facilitated glucose/fructose

transporter), member 52.2

SLCO4A1 Solute carrier organic anion transporter family,member 4A1

3.4

STN2 Stonin 2 2.9UCP2 Uncoupling protein 2 (mitochondrial, proton carrier) 2.3VPS52 Vacuolar protein sorting 52 (yeast) 2.0

6. OthersARHGEF4 Rho guanine nucleotide exchange factor (GEF) 4 3.8BCL6 B-cell CLL/lymphoma 6 (zinc finger protein 51) 2.2BHLHB2 Basic helix-loop-helix domain containing, class B, 2 3.0BRSK2 Serine/threonine kinase 29 8.6BTN3A2 Butyrophilin, sub-family 3, member A2 8.2CBR1 Carbonyl reductase 1 3.3CGB5 Human chorionic gonadotropin, beta 5 6.4CGB7 Human chorionic gonadotropin, beta 7 6.1CGB Human chorionic gonadotropin 5.0CGB1 Human chorionic gonadotropin, beta 1 3.5C9orf86 Chromosome open reading frame 86 2.4C13orf8 Chromosome 13 open reading frame 8 2.2C19orf6 Chromosome 19 open reading frame 6 2.2CITED2 Cbp/p300-interacting transactivator, with Glu/Asp-rich

carboxy-terminal domain, 22.2

CREBL1 cAMP responsive element binding protein-like 1 2.9CST6 Cystatin E/M 3.1DIO2 Deiodinase, iodothyronine, type II 2.2DPP9 Dipetidylpeptidase 9 2.3ENG Endoglin (Osle-Rendu-Weber syndrome 1) 3.9FLJ90650 Laeverin 10.0FSTL3 Follastin-like 3 (secreted glycoprotein) 3.8GANAB Glucosidase, alpha; neutral AB 2.3

Table 2 (continued)

Genesymbol

Gene name Foldinduction

GHRH Growth hormone releasing hormone, somatoliberin 2.5GUCA2A Guanylate cyclase activator 2A (guanylin) 2.3HK2 Hexokinase 2 3.9IGSF8 Immunoglobin superfamily, member 8 4.0IL1RAP Interleukin 1 receptor accessory protein 2.4INHA Inhibin, alpha 3.0JM11 JM11 protein 2.0KLK6 Kallikrein 6 (neurosin, zyme) 2.2LDB1 LIM domain binding 1 2.8LEP Leptin 40.0LHB Luteinizing hormone beta polypeptide 4.1LIMD1 LIM domains containing 1 3.6MMP14 Matrix metallopeptidase 14 (membrane inserted) 2.8MR-1 Myofibrillogenesis regulator 1 2.0MRPL39 Mitochondrial ribosomal protein L39 4.2NEK11 NIMA (never in mitosis gene a)-related kinase 11 2.2NNAT Neuronatin 2.3NUCB1 Nucleobindin 1 2.8PCBP1 Poly(rC) binding protein 1 2.4PPL Periplakin 2.5PSG Pregnancy-specific beta 1 glycoprotein 2.2QPCT Glutaminyl-peptide cyclotransferase (glutaminyl

cyclase)3.8

RDH13 Retinol dehydrogenase 13 (all-trans and 9-cis) 2.9RNF123 Ring finger protein 123 2.3SEMA4C Semaphoring 4C 3.0SIGLEC6 Sialic acid binding IG-like lectin 6 2.1SYMPK Symplekin 2.2TAF15 TAF15 RNA polymerase II, TATA box binding

protein (TBP)-associated factor, 68 kDa3.0

TPBG Trophoblast glycoprotein 2.8TPSD1 Mast cell tryptase delta 1 2.7TREM1 Triggering receptor expressed on myeloid cells 1 5.9

7. UnclassifiedBANF1 Barrier to autointegration factor 1 2.1BTNL2 Butyrophilin-like 2 (MHC class II associated) 2.0DLST Dihydrolipoamide S-succinyltransferase 2.2EML2 Echinoderm microtubule associated protein-like 2 2.2FLJ20397 Hypothetical protein FLJ20397 13.9GRINL1A Glutamate receptor, ionotropic,

N-methyl D-aspartate-like 1A2.0

HA-1 Minor histocompatibility antigen HA-1 2.8HIG2 Hypoxia-inducible protein 2 2.1LOC283377 Hypothetical protein LOC283377 2.0MEN1 Multiple endocrine neoplasia I 2.3MGC14141 Hypothetical protein MGC14141 2.2MGC52057 Hypothetical protein MGC52057 2.2NAV2 Neuron navigator 2 2.8NCSTN Nicastrin 2.0PHYHIP Phytanoyl-CoA hydroxylase interacting protein 2.0PRDM7 PR domain containing 7 2.5SASH1 SAM and SH3 domain containing 1 2.5SPAG4 Sperm associated antigen 4 3.1TAX1BP3 Tax1 (human T cell leukaemia virus type I) binding

protein 32.5

V. Sitras et al. / Placenta 30 (2009) 424–433 427

below 10th percentile and abnormal umbilical artery Doppler).However, the neonatal outcome was not different between thegroups.

A total of 18,811 genes on the arrays passed our quality criteriaafter image analysis. In preeclamptic placentas 213 genes were up-regulated and 82 genes were down-regulated, compared to normalplacentas. Lists of up- and down-regulated genes clustered togroups of biological processes with fold-change�2 and p� 0.01 aregiven in Tables 2 and 3, respectively. The list of all 3724 differen-tially expressed genes with p� 0.01 irrespective of the fold-change,together with separate lists of up- and down-regulated genes with�2 fold-change and p� 0.01 are given in the supplementary Table1S. After supervised clustering we found 16 genes that discrimi-nated the best between our preeclamptic and normal placentas

Table 3Genes down-regulated in placentas obtained from women with severe preeclampsia compared to controls, with fold-change �2.0 and p� 0.01. They are clustered in terms ofbiological processes and subdivided into the indicated subgroups.

Gene symbol Gene name Fold-decrease

1. Cell proliferation and differentiationBHLHB3 Basic helix-loop-helix domain containing, class B, 3 2.4PDGFD Platelet derived growth factor D 2.3PCDH11 Protocadherin II 2.0ZNF651 Kruepel C2H2-type zing finger 2.0

2. Immunity and defenceABCC3 ATP-binding cassette, sub-family C (CFTR/MRP), member 3 2.3MARCH1 Membrane associated ring finger (C3HC4) 1 2.4

3. TransportGABRA4 Gamma-aminobutyric acid (GABA) A receptor, alpha 4 2.0SLC1A1 Solute carrier family 1 (neuronal/epithelial high affinity glutamate transporter, system Xag), member 1 2.2

4. OthersAFF3 AF4/FMR2 family, member 3 2.1ASB4 Ankyrin repeat and SOCS bvox-containing protein 4 2.0BMP5 Bone morphogenic protein 3 2.1COX17 COX17 homolog, cytochrome c oxidase assembly protein (yeast) 4.3GNPNAT1 Glucosamine-phophate N-acetyltransferase 1 3.9LEPREL1 Leprecan-like 1 2.7PRKAR1A Protein kinase, cAMP-dependent, regulatory, type 1, alpha 4.6SEMA3C Sema domain, immunoglobin domain (Ig), short basic domain, secreted, (semaphoring), 3C 2.0RGN Regucalcin (senescence marker protein-30) 2.3GPR103 G protein-coupled receptor 103 3.5ZNF598 Zinc finger protein 598 13.1

5. UnclassifiedAPOL1 Apolipoprotein L, 1 2.0FJL20032 Hypothetical protein FLJ20032 6.0IGSF6 Immunoglobin superfamily, member 6 2.1LOC168850 Hypothetical protein LOC168850 2.2PSME4 Proteasome (prosome, macropain) activator subunit 4 2.3PTCH Patched homolog (Drosophila) 13.8ZDHHC21 Zinc finger, DHHC-type containing 21 2.1

V. Sitras et al. / Placenta 30 (2009) 424–433428

(Fig. 1). Principal component analysis [21] and hierarchical clus-tering showed that placental gene expression profile of the threepatients with HELLP syndrome was similar to that of otherpreeclamptic women.

Histopathological examination of the placentas did not revealany significant morphologic differences between early- and late-onset preeclampsia. However, microarray analysis showed that inearly-onset preeclamptic placentas, 36 genes were up-regulatedand 132 genes were down-regulated compared to late-onsetpreeclamptic placentas at a significant level (p� 0.01 and �2 fold-change) (Fig. 2). A complete list of the 402 differentially expressedgenes between early- and late-onset preeclampsia with p� 0.01regardless of fold-change, together with separate lists of up- anddown-regulated genes with �2 fold-change and p� 0.01 are pre-sented in the supplementary Table 2S.

We further performed a comparison of pathways involved inpreeclamptic versus normal and early- versus late-onsetpreeclamptic placentas (Fig. 3). We compared differentiallyexpressed gene lists at different levels of significance (p� 0.01 andfold-change� 2 or p� 0.01 regardless of fold-change) in order tohave as much genetic information as possible. However, the resultwas essentially the same, with oxidative stress, inflammationmediated by chemokine and cytokine and endothelin signallingpathways mainly being involved in early-onset preeclampsia.Application of GSEA and Mann–Whitney U-test did not reveal anysignificantly (global p-value� 0.05 and FDR� 0.1) up- or down-regulated pathway.

Microarray results were validated by RT-PCR for 16 selected genesand there was a good correlation for most of them (Table 3S). Different

subtypes of hCG were up-regulated in preeclamptic placentas from3.5 to 6.4 fold. We validated this result by measuring hCG concen-tration in maternal urine. Mean concentration of urinary hCG in thecontrol group was 20,034 (95% CI: 13,121–27,687) IU/l and inpreeclamptic patients 68,271 (95% CI: 18,917–117,624) IU/l (p¼ 0.04).We found no significant correlation between urinary hCG valuesand placental weight (r¼ 0.03; p¼ 0.823). Leptin RNA was highly(40 fold) up-regulated in the preeclamptic placentas both in micro-array and RT-PCR. In order to correlate this result with leptinprotein expression levels we performed immunofluorescence inpreeclamptic and normal placentas (Fig. 4). Leptin was expressed inthe villous trophoblast and was more abundant in the preeclampticplacenta.

4. Discussion

We compared global gene expression profile of preeclampticplacentas with that of normal placentas using microarrays andfound several genes to be differentially expressed. Gene annotationusing biological process terms showed many of these genes to beassociated with cell proliferation and differentiation, cell structure,transport, immunity and defence, and lipid metabolism. Addition-ally, we found several other genes that were highly differentiallyexpressed which belonged to other biological processes or wereunclassified. Despite differences in experimental design and plat-forms used, a comparison of our results with previous microarraystudies on preeclamptic placentas shows some overlapping sets ofdifferentially expressed genes (e.g. leptin, hCG, VEGF, IGF2, MMPs)as well as some novel genes (e.g. laeverin).

Fig. 1. (A) List of the 16 genes that discriminated preeclamptic from normal placentas in our study after supervised clustering. (B) Horizontal bars indicate mean fold-change of geneexpression in preeclamptic compared to normal placentas. (C) Heat map showing the expression level of each of the 16 discriminatory genes (y-axis) for each of the preeclamptic(n¼ 16) and normal (n¼ 21) placental samples (x-axis). The color intensity represents the level of gene expression, red indicating up-regulation and green indicating down-regulation.

V. Sitras et al. / Placenta 30 (2009) 424–433 429

Fig. 2. Volcano plot showing the overall result comparing gene expression betweenearly- and late-onset preeclamptic placentas. Each spot represents a gene. The colorintensity represents the level of gene expression. Genes positioned at the two upper-lateral quadrants are both biologically and statistically differentially expressed.

V. Sitras et al. / Placenta 30 (2009) 424–433430

4.1. Angiogenetic factors

In preeclamptic pregnancies, failure of extra-villous trophoblastto invade the spiral arteries in the maternal decidua leads todefective placentation characterised by a high resistance utero-placental circulation and placental hypoperfusion. This could leadto abnormal expression of angiogenic factors [22]. We found mostof the angiogenic factors shown to be involved in the pathogenesisof preeclampsia, such as fms-related tyrosine kinase (FLT)-1 and -4and endoglin (ENG) to be up-regulated from 2.4 to 3.9 fold (Table 2).Platelet derived growth factor D (PDGFD), a recently recognisedgrowth factor which has angiogenic effects [23], was 2.3 fold down-regulated in preeclamptic placentas (Table 3). Several other differ-entially expressed genes were involved in angiogenesis, TGF-betaand VEGF-signalling pathways. These molecular mechanisms aresupported by our hemodynamic findings of increased pulsatilityand reduced volume blood flow in the uterine arteries in womenwith preeclampsia. However, there were no signs of fetal circula-tory compromise, indicated by a normal cerebro-placental ratio andweight-indexed umbilical vein volume blood flow. Similarly, therewas no significant difference in Apgar score and acid-base status ofthe neonates between the study groups despite an increasedprevalence of small for gestational age neonates among thepreeclamptic patients.

4.2. Human chorionic gonadotropin

This glycoprotein hormone secreted by trophoblast, has hetero-dimeric common subunit-a and unique subunit-b that gives biologicspecificity. Serum levels reach a peak at around 10 weeks of gesta-tion; thereafter they decline and remain at a plateau throughout thepregnancy. Like other gonadotropins, b-hCG is considered tomodulate vasculo- and angiogenesis during early gestation [24] andpromote trophoblast invasion [25]. Maternal serum concentration ofhCG is increased in severe preeclampsia [26] and the levels may behigh weeks before the clinical manifestation [27]. Although there isan association between increased second trimester serum b-hCG[28] and development of hypertensive disorders of pregnancy, it hasnot been found to be a robust predictive marker of preeclampsia inisolation [29]. In healthy human subjects, approximately 20% of

circulating hCG is excreted in urine [30]. Mid-trimester urinary hCGb-subunit core has been shown to be associated with increased riskof developing preeclampsia [31]. We found urinary b-hCG to be 3.4fold higher in preeclamptic women compared to their controls, butthe wide confidence intervals reduce its value as a sole marker ofpreeclampsia.

4.3. Leptin

Leptin was 40 fold up-regulated in preeclamptic placentas andhad a similar expression profile in early- and late-onsetpreeclampsia. It is the protein transcript of the ob/ob geneproduced by adipocytes both in adults and fetuses and is highlyexpressed in placenta. Serum leptin is elevated in pregnanciescomplicated by preeclampsia [32]. In our study, maternal BMI at thestart and the end of pregnancy was not different between groupssuggesting that leptin expression in placenta was not affected bymaternal BMI. Placental leptin ensures nutrient supply to the feto–placental unit [33] and induces trophoblast proliferation by inhib-iting apoptosis and guiding cells into the G2/M phase of the cellcycle [34]. It has been recently shown that leptin may promote theability of endothelial progenitor cells to participate in vascularremodelling [35]. Therefore, increased production of leptin by theplacenta may be a compensatory mechanism against endothelialdysfunction observed in preeclampsia.

Leptin has a stimulatory effect on hCG production in trophoblastexplants, and both leptin and hCG modulate VEGF production bythe cytotrophoblast [36]. Moreover, leptin and hCG are used toasses trophoblast viability in vitro and it has been shown that theirmRNA and transcript levels rapidly decrease in cultured tropho-blasts compared to dual perfused villous explants [37]. Interest-ingly, in the only microarray study that has so far reported on globalgene expression profile in severe preeclampsia, comparing 10preeclamptic placentas with a mixture of 3 healthy placentas thatserved as a template control, both leptin and hCG were highly up-regulated [38]. Our results of microarray and RT-PCR analysis andhemodynamic studies are in agreement with these findings andsuggest that leptin, hCG and other angiogenic factors are secretedby the poorly perfused preeclamptic placenta in order to supportadequate blood supply to the fetus.

4.4. Laeverin

It is interesting to note that laeverin, a gene encodinga membrane-bound cell-surface metallopeptidase [39], was 10 foldup-regulated in our preeclamptic placentas and was among thegenes that could predict preeclampsia in our study. Laeverin isexpressed in extra-villous trophoblast and in vitro studies indicatethat it may have a role in regulating trophoblast invasion [40].Furthermore, it shows homology to CD13/aminopeptidase N, whichcontrols endothelial cell-motility through cytoskeletal rearrange-ment leading to filopodia formation [41]. Therefore, the role oflaeverin in the pathophysiology of preeclampsia merits furtherinvestigation.

4.5. Notch: a common pathway among placental andbrain disorders

In addition to angiogenesis, apoptosis, interleukin, TGF-beta,and VEGF related pathways, which have been suggested to beinvolved in the pathogenesis of preeclampsia, we found that Notchand Alzheimer related pathways could also have a role. Notchsignalling regulates differentiation of endothelial and vascularsmooth muscle cells and branching of blood vessels [42,43]. Mousemutants in Notch pathway components exhibit absence of vascular

Fig. 3. Comparison of pathways (y-axis) between 286 differentially expressed genes in preeclamptic versus normal and 168 genes between early- versus late-onset preeclampticplacentas (�2 fold-change and p� 0.01). The x-axis was calculated as: number of genes in the pathway/number of genes in the list� 100. Pathway components and diagrams arefreely available at http://www.pantherdb.org.

V. Sitras et al. / Placenta 30 (2009) 424–433 431

remodelling in the extra-embryonic yolk sac, placenta and embryo[44]. Notch pathway seems to have downstream effects via theVEGF pathway in the regulation of embryonic vascular develop-ment [45]. Furthermore, mutations in Notch pathway componentscause cerebral autosomal dominant arteriopathy with subcorticalinfarcts and leukoencephalopathy (CADASIL) which is the mostcommon type of inherited stroke and vascular dementia in humans[46]. It has recently been postulated that there are (epi) geneticsimilarities between preeclampsia and late-onset Alzheimerdisease, regarding the 10q21 region in Dutch families [2]. It isinteresting to note that several differentially expressed genes fromour study were involved in Alzheimer related pathways and manyof these overlap and interact with genes involved in the Notchpathway. Taken together these results indicate that preeclampsiaand degenerative brain disorders could share some commonpathophysiologic mechanisms.

4.6. Early- versus late-onset preeclampsia

Placentas from late-onset preeclamptic pregnancies do notappear to have significant morphological differences compared

with gestational age-matched normal placentas, however terminalvilli volume and surface area are reduced in early-onsetpreeclampsia [9]. Although it was not possible to clearly differen-tiate between early- and late-onset disease based solely onplacental morphology, our microarray and RT-PCR results showedseveral genes to be differentially expressed in early- and late-onsetpreeclampsia. Comparison between lists of differentially expressedgenes in preeclamptic versus normal and early- versus late-onsetpreeclamptic placentas indicates that different pathways mightinfluence the timing of clinical manifestation of this disease. Morespecifically, prostaglandin-endoperoxide synthase 2 (PEPTGS2) andphospholipase A2 group 4A (PLA2G4A) were up-regulated in early-compared to late-onset preeclamptic placentas (4.3 and 2.4 foldrespectively), whereas adenylate cyclase 2 (ADCY2) was 2.4 folddown-regulated. These genes are involved in endothelin andinflammation mediated by chemokine and cytokine signallingpathways. Activation of the endothelin pathway results in release ofnitric oxide and prostacyclins that affect endothelial and vascularsmooth muscle cells [47]. Inflammatory pathways control trafficand migration of immune cells. Cytokine receptor-like factor 1(CRLF1), which possibly plays an immune regulatory role during

Fig. 4. Cross-section of terminal chorionic villi (magnification 600�) showing leptinimmunofluorescence in normal (A) and preeclamptic (B) placentas, together witha negative control (C). Leptin (green color) is located in the cytoplasm of the villoustrophoblast and is more abundant in the preeclamptic placenta. Leptin is equallyexpressed in the fetal (arrow) and maternal erythrocytes (arrowhead) in both normaland preeclamptic placentas. The erythrocytes demonstrate green auto fluorescence inthe negative control.

V. Sitras et al. / Placenta 30 (2009) 424–433432

fetal development was 3.3 fold up-regulated in early- compared tolate-onset preeclampsia. Interestingly, angiogenesis, TGF beta andVEGF signalling were involved in both early- and late-onsetpreeclampsia suggesting that they may represent a common finalmechanism leading to preeclampsia but are unlikely to determinethe timing of clinical manifestation.

4.7. Limitations and strengths of the study

The factors that trigger preeclampsia probably affect the placentaearly in gestation and by examining gene expression later in preg-nancy we may only trace the molecular mechanisms that havealready occurred. Due to the cross-sectional design of our study, it isnot possible to obtain information on changes in placental geneexpression profile in preeclampsia during the course of pregnancy.However, a longitudinal study taking serial placental biopsies duringdifferent time points in gestation is ethically unacceptable. Similarly,

the use of healthy term placentas as controls may be criticisedbecause most severely preeclamptic patients were deliveredprematurely. However, placentas obtained after spontaneouspreterm delivery cannot be considered normal because of theunderlying pathological processes that lead to spontaneous pretermlabour. Furthermore, as we used a single placental sample froma standardised location, we cannot be certain that the geneexpression profile will be the same in all parts of placenta. However,we believe that this is a representative site to study placental geneexpression as it includes central villous parenchyma.

Most of the previous microarray studies on placental geneexpression in preeclampsia are confounded by the inclusion ofpatients with mild preeclampsia, small sample size, inappropriatematching and indirect design. We used stringent inclusion criteriaregarding phenotype of the study population, RNA quality, imageanalysis and data analysis. One-channel genome-wide microarraytechnology gave us the possibility to perform subgroup analysiswith regard to the timing of clinical manifestation, which is animportant factor in the prognosis and outcome of the disease. Wevalidated a relatively large number of genes by RT-PCR. These wereselected on the basis of their expression level in microarrays,previously suggested association with the pathogenesis ofpreeclampsia, or ability to predict preeclampsia in our samplesafter supervised clustering analysis.

4.8. Conclusion

Placental gene expression profile is altered in severepreeclampsia. We provide a comprehensive list of differentiallyexpressed placental genes in preeclampsia compared to normalcontrols. This may help in developing novel predictive, diagnosticand prognostic biomarkers of preeclampsia in future. In our studypopulation, 16 genes discriminated the best between preeclampticand normal placentas, among which hCG, leptin and laeverin mightbe relevant and merit further investigation. Early-onset and late-onset preeclampsia appear to have different genetic signaturessuggesting that despite sharing some common clinical featuresthey might have different pathogenesis.

5. Conflict of interestNone declared.Funding: Faculty of Medicine, University of Tromsø and NorthNorway Regional Health Authority (Funding number 721484).

Acknowledgments

Department of Medical Biochemistry University Hospital ofNorthern Norway for quantitative analysis of urine hCG. MicroarrayResource Centre Tromsø (MRCT) for performing microarrayexperiments. Mona Nystad and Chris Fenton, Department ofMedical Genetics, University Hospital of Northern Norway for lep-tin immunofluorescence and GSEA, respectively. Charles Wol-stenholme, University of Tromsø for his help with the figures.

Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi: 10.1016/j.placenta.2009.01.012.

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