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Prenatal Sildenafil and Fetal-placental Programming in Human Pregnancies Complicated by Fetal Growth Restriction: A Retrospective Gene Expression Analysis

Published onSep 26, 2023
Prenatal Sildenafil and Fetal-placental Programming in Human Pregnancies Complicated by Fetal Growth Restriction: A Retrospective Gene Expression Analysis
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Abstract

Objective: Fetal growth restricted (FGR) offspring are more susceptible to develop cardiovascular and renal disease. The potential therapeutic value of sildenafil to improve fetal growth has recently been evaluated in several randomized clinical trials. Here we investigate whether administration of sildenafil during pregnancies complicated by FGR influences fetal-placental programming profiles, especially related to cardiorenal development and disease.

Methods: We collected human umbilical vein endothelial cells (HUVECs) and placental tissue within the Dutch STRIDER trial, in which sildenafil versus placebo treatment were randomly assigned to pregnancies complicated by severe early-onset FGR. Differential expression of genes of these samples were studied by whole genome RNA-sequencing. In addition, we performed gene set enrichment analysis focused on cardiovascular and renal gene sets to examine differentially expressed gene sets related to cardiorenal development and health.

Results: Our study showed similar gene expression profiles between treatment groups in HUVECs (n=12 sildenafil; n=8 placebo) and placentas (n=13 per group). Prenatal sildenafil exposure did not change cardiovascular or renal programming in pregnancies complicated by FGR. In placental tissue, prenatal sildenafil altered a few gene sets involved with the nitric oxide pathway potentially reflecting the mechanism of action of sildenafil. Prenatal sildenafil also upregulated gene sets related to immune pathways in placental tissue.

Conclusions: Overall, our study showed that sildenafil has the potential to alter placental (but not fetal) expression of gene sets related to immune pathways and did not support (in)direct reprogramming of cardiovascular or renal health in human pregnancies complicated by FGR.

Keywords: fetal growth restriction, sildenafil, developmental programming, RNA-sequencing, gene set enrichment analysis, human umbilical cord vein endothelial cells, placenta

Graphical abstract

Take-home Message

Fetal growth restriction (FGR) predisposes to cardiorenal diseases later in life. Prenatal administration of sildenafil showed beneficial effects on cardiovascular health in animal FGR offspring. However, this study did not support the potency of sildenafil to reprogram the cardiorenal health in human pregnancies complicated by FGR.

Original Purpose

The adverse in utero environment resulting in fetal growth restriction (FGR) predisposes the offspring to develop cardio-renal disease beyond the fetal developmental phase by altered epigenetic programming. Interest grew in prenatal administration of sildenafil after several animal studies showed improved fetal growth and long-term cardiovascular function.

An international STRIDER consortium emerged to evaluate the therapeutic potency of sildenafil to improve fetal growth in pregnancies complicated by FGR. In our sub-study (of the Dutch STRIDER trial) we aimed to study whether prenatal sildenafil influences developmental programming of cardiorenal health by examining whole genome RNA-sequencing and gene set enrichment analysis in human umbilical vein endothelial cells and placental tissue. We hypothesized that prenatal sildenafil alters fetal-placental programming profiles especially related to cardiorenal development and disease.

The interim-analysis of the Dutch STRIDER trial showed futility in combination with potentially increased mortality and morbidity in neonates. Hereafter all trials and inevitably our substudy were halted. This made our sub-study the first and last to investigate whether prenatal sildenafil administration in pregnancies complicated by FGR could influence fetal-placental programming of cardiorenal health.

Our study does not support the use of prenatal sildenafil for cardiorenal reprogramming. This is contrary to several animal studies, which may be suggestive of interspecies differences. Our results might be reassuring considering the negative clinical results of the STRIDER study and highlight the need for tissue collection from complicated pregnancies in humans to study developmental programming on a molecular or genetic level.

Introduction

Fetal growth restriction (FGR) describes the inability of the fetus to reach its intrinsic growth potential. Early-onset FGR is most commonly caused by maternal vascular malperfusion resulting in placental insufficiency; a reduced uteroplacental blood flow impairs oxygen and nutrient supply towards the fetus (Burton & Jauniaux, 2018). Multiple lines of evidence suggest that exposure to this unfavorable intrauterine environment results in fetal adaptations, impaired maturation of organ development, and triggers developmental programming of cardiorenal diseases later in life (Barker, 2006; Sundrani et al., 2017; Chen & Zhang, 2012; Henriksen & Clausen, 2002). FGR offspring, and their future generations, are more susceptible to develop cardiovascular and renal disease, including hypertension, ischemic heart disease, chronic kidney disease and end-stage renal disease in adulthood (Malhotra et al., 2019; White et al., 2009; Gjerde et al., 2020; Kooiman et al., 2020; Demicheva & Crispi, 2014; Dötsch et al., 2016; Sehgal et al., 2020; Nüsken et al., 2020). Adverse developmental programming might underlie this increased risk (Sehgal et al., 2020; Nüsken et al., 2020). A recent study showed altered gene expression and gene sets related to cardiovascular health and renal development in human umbilical vein endothelial cells (HUVECs) between placental insufficiency-induced FGR and control (Terstappen et al., 2020).

Mitigation of the detrimental developmental programming of cardiorenal disease following FGR in pregnancy is desirable (Paauw et al., 2016). Several animal studies provided proof-of-concept of in utero interventions to diminish adverse developmental programming, also known as reprogamming. For instance administration of nitric oxide (NO) stimulating agents during pregnancy improved cardiovascular outcomes alongside altered epigenetics and gene expression in fetuses or offspring of FGR models in rat, guinea pig or chicken (Herrera et al., 2017; Itani et al., 2017; Man et al., 2020; Wu et al., 2015).

Sildenafil is one of these potential candiates to improve fetal growth and reprogram cardiorenal disease. Prenatal administration of this phosphodiesterase-5 showed beneficial effects on cardiovascular function in FGR models in rats, mice, and chickens (Itani et al., 2017; Mills et al., 2018; Terstappen et al., 2019). This might be a result of indirect influence on developmental programming, via improved fetal growth by uteroplacental blood flow by NO induced relaxation of the placental vascular bed on both the maternal and fetal side (Krause et al., 2011; Wareing et al., 2006). In addition, the long-term benefit might also result from direct protection of developmental programming, since improvements in long-term cardiovascular function were also observed in a chick embryo model (without the presence of a placenta) of FGR after administration of sildenafil (Itani et al., 2017). While several animal and small-scaled human studies indeed showed improved fetal growth in the sildenafil-treated group (Paauw et al., 2017; Von Dadelszen et al., 2011), a series of randomized clinical trials (Sildenafil TheRapy In Dismal Prognosis Early-onset Fetal Growth Restriction [STRIDER]) designed within an international network did not show increased birth weight in pregnancies complicated with severe early-onset FGR following sildenafil compared to placebo (Pels et al., 2020; Sharp et al., 2018; Groom et al., 2019). These human data make indirect influence on developmental programming less likely; nevertheless, prenatal sildenafil could still directly influence developmental programming.

We collected HUVECs and placental tissue as a sub-study within the Dutch STRIDER trial to study whether sildenafil influences programming by regulation of fetal and placental gene expression. Hereby we aimed to address potential mechanisms underlying the effects of sildenafil on cardiovascular and renal programming in severe early-onset FGR offspring. Our approach involved whole genome RNA-sequencing to map differential expression per gene and gene set enrichment analysis focussed on cardiovascular and renal development, function and health.

Methods

Study population

For this substudy, women with a pregnancy complicated by severe early-onset FGR most likely based on placental insufficiency and participating in the Dutch STRIDER were recruited from the University Medical Center Utrecht (UMCU) and the Academic Medical Center (AMC) in Amsterdam from 09-07-2016 to 30-10-2017. In the Dutch STRIDER study, women were randomized to either prenatal administration of placebo or sildenafil at a dose of 25mg three times per day (Pels et al., 2020; Pels et al., 2017). The study population was selected based on low biometric parameters for gestational age and signs of placental insufficiency; inclusion and exclusion criteria have been described in detail previously (Pels et al., 2020; Pels et al., 2017). For this sub-study, we excluded cases in whom the offspring was diagnosed with a congenital disorder after birth.

The Dutch STRIDER trial (Clincial trial.gov identifier NCT02277132) was approved by the medical ethical committee of the AMC on 02-07-2014; protocol number 2014-131. The UMCU approved the study on 14-09-2015; protocol number 15-510/G-C. Prior to delivery, the STRIDER participants in this sub-study gave additional written informed consent for placental research (amendment approved on 29-01-2016, updated on 05-09-2017). The Dutch STRIDER study was halted mid-term because the interim-analysis showed futility in combination with potentially increased risk of mortality and persistent pulmonary hypertension (PPHN) in neonates.

Clinical data

Clinical data has been derived from the Dutch STRIDER database and patient records. The maternal medication was noted, including the start and duration of administration of the allocated drug. Unblinding of treatment allocation was done after all methods below were executed. Exact percentiles for weight and head circumference at birth were determined with Intergrowth-21st (Anderson et al., 2016). Neonatal survival during hospital admission and cases of PPHN were registered.

HUVECs isolation and RNA isolation

Directly after placental delivery, the umbilical cord was stored in phosphate-buffered saline (PBS) solution (pH 7.2) at 4°C. HUVECs isolation occurred as previously described, preferably within 12 hours, but always within 24 hours after placental delivery (Hartman et al., 2020). We collected umbilical cords in both UMCU and AMC. Cannulation of the umbilical vein at one end allowed access for further processing. After washing with sterile PBS (pH 7.4; Gibco by Life Technologies, Grand Island, NY) the umbilical cord was clamped at both sides to incubate with accutase (0.02 µg/ml DNase; Innovative cell technologies Inc, San Diego, CA) for 5 minutes in 37°C sterile PBS to detach the endothelial cells. The detached HUVECs in accutase were flushed out of the umbilical vein with endothelial cell growth medium-2 (97% EGM-2; basal medium and SingleQuots supplement [1.9% FBS, 0.04% hydrocortisone, 0.4% hFGF-B2, 0.1% vascular endothelial growth factor, 0.1% R3-IGF-1, 0.1% ascorbic acid, 0.1% hEGF, 0.1% GA-1000, 0.1% heparin], Lonza Bioscience, Walkersville, MD) and centrifuged for 5 minutes at 330g at room temperature. The pellet was resuspended in 600 μl RA1 lysis buffer (Macherey-Nagel, Düren, Germany) and 6 μl 1M DTT and stored at -80°C until RNA isolation.

RNA was isolated using NucleoSpin RNA® (Macherey-Nagel), with RNA elution in 40 μl nuclease-free water. RNA concentration was quantified using Qubit RNA HS assay and Qubit fluorometer (ThermoFisher).

RNA isolation of placental tissue

Biopsies (4 by 4 mm) were taken from the middle of five cotyledons per placenta directly after birth and only in AMC. RNAlater stabilization solution (ThermoFisher Scientific) was used to freeze the (unrinsed) placental biopsies in liquid nitrogen and stored at -80°C until RNA isolation.

Frozen placenta samples were homogenized with a Tissuelyzer LT (Qiagen, Venlo, the Netherlands) in lysis buffer. Total RNA was isolated with the allprepRNA mini kit (Qiagen), following the manufacturer’s protocol. RNA quality and quantity were characterized by a Nanodrop 2000c (Thermo Scientific, Pittsburgh, PA, USA). RNA was stored at -80°C until further analysis.

RNA-sequencing of HUVECs and placental tissue

Samples with a measurable amount (minimal concentration 41.4 ng/µl in placental samples and 2.1 ng/µl in HUVEC samples) of RNA were selected for RNA sequencing. Polyadenylated mRNA was isolated using Poly(A) beads (NEXTflex). Sequencing libraries were prepared by using the Rapid Directional RNA-seq kit (NEXTflex). The library was sequenced at the Utrecht Sequencing Facility (USEQ) on a Nextseq500 platform (Illumina) using a single-end 75-base pair high-output run. Reads were aligned to the human reference genome (GRCh37) using STAR version 2.4.2a. Read groups were added to the BAM files with Picard’s AddOrReplaceReadGroups (v1.98). The BAM files were sorted with Sambamba v0.4.5, and transcript abundances were quantified with HTSeq-count version 0.6.1p117 using the union mode.

Gene set analysis

Gene set enrichment testing was performed on the hallmark (H), canonical pathway (C2-CP) and GO term (C5) gene set collections from the Molecular Signatures Database (version 7.1) (Wu & Smyth, 2012; Liberzon et al., 2016). Only gene sets with relation to renal or cardiovascular development or pathologies, or Nitric Oxide (NO) signaling were selected from the GO term gene sets (Table S1). Gene sets with less than five genes in the set of selected genes (based on expression, see above) were excluded from the analysis, eventually resulting in 2,167 included gene sets

Statistical analysis

Clinical data

IBM SPSS Statistics 25 for Windows (version 25, UBM Corp, Armonk, NY) was used for statistical analysis. Parametric data tested with independent t-test are presented as mean ± SD, non-parametric data tested with Mann-Whitney are presented as median (minimum-maximum), and nominal data tested with Fisher exact are presented as n (%). A two-sided p-value of below 0.05 was considered statistically significant.

Differential expression of genes

Read counts per gene, per sample, were analyzed for global expression differences using R (version 3.5.3). Genes were selected with an expression of one count per million reads (CPM) in at least 8 samples (n=13,760 genes selected). Read counts were Trimmed Mean of M-values (TMM)-normalized using the calcNormFactors function from the edgeR package (version 3.24.3) (Robinson et al., 2010). TMM-normalized counts were used to assess global transcriptional profile differences of all samples by Principal Comonent Analysis (PCA) (ten components). Ten Principal components (PC) were analyzed in the PCA analysis, values from each PC were checked for correlation to sample characteristics by the Mann-Whitney U test implemented in the scipy package (version 0.19.0) in python (version 2.7.10). Low-quality samples were identified and removed when passing any of these conditions: 1) number of reads were less than 1,000,000, 2) number of non-zero genes were less than 10,000, or 3) a combination of number of non-zero genes between 10,000-12,000 and being a visible outlier on one of the PCA components. HUVECs and placental tissue were analyzed separately.

Differential gene expression analysis was performed with the edgeR package (version 3.24.3) in R (version 3.5.3, R Core team, Auckland, New Zealand). Gene expression was modeled using the glmQLFit function in EdgeR (Robinson et al., 2010), to a model that included treatment group variables, as well as factors to capture mode of delivery (caesarean section vs spontaneous delivery), sex (male vs female), and gestational stage (preterm vs term) related gene expression variation. Differential gene expression was determined between treatment groups (sildenafil vs placebo) and the differential expression statistics were obtained using the glmQLFTest functionality in edgeR. False Discovery Rates (FDR) were determined using the Benjamini-Hochberg method to adjust for multiple testing and were considered significant when below 0.1 (in combination with unadjusted p-value <0.05; (Benjamini & Hochberg, 1995).

Differential expression of gene sets

Gene set enrichment testing was performed with Correlation Adjusted MEan Rank (CAMERA), using the same linear model and contrasts as in the differential gene expression analysis (see above), and FDR were determined using the Benjamini-Hochberg method to adjust for multiple testing, which were considered significantly different when below 0.1 (Benjamini & Hochberg, 1995). When a module showed ≥ 50% overlap with higher ranking gene sets we only selected the more significant gene set. Heatmap for the gene sets related to the cardiovascular, renal and nitric oxide pathway were created.

Results

Sample inclusion

We collected umbilical cords from 14 sildenafil-treated and 10 placebo-treated births. Two sildenafil-treated and one placebo-treated sample did not yield enough RNA to perform RNA-sequencing. Therefore 12 sildenafil and 9 placebo HUVECs samples were used for RNA-sequencing. From the HUVECs samples, we excluded 1 low-quality run from the placebo group that was also an outlier in the RNA-seq data. Therefore, we proceeded with analyzing 12 sildenafil-treated versus 8 placebo-treated HUVEC samples.

We collected 16 sildenafil-treated and 18 placebo-treated placental biopsies. The RNA concentration of one placebo sample was too low to perform RNA-sequencing and thereby excluded. We also excluded one placental tissue sample in the placebo group based on postnatal detection of congenital disorders (Silver Russell syndrome). This resulted in 16 sildenafil versus 16 placebo-treated placental samples for RNA-sequencing. In these results, we identified three low-quality samples outliers in both the sildenafil and placebo group. Thus, we proceeded with 13 sildenafil-treated and 13 placebo-treated placenta samples for analysis.

Study characteristics

Patient characteristics are presented in Table 1. Birth weight did not differ between groups. Neonatal survival during hospital admission was approximately 20% higher in the sildenafil group compared to the placebo group (not significantly different). Only sildenafil-exposed neonates suffered from PPHN during admission (n=3 in HUVECs samples and n=2 in the placental tissue samples).

Differential expression of genes

Principal component analysis (PCA) plots did not reveal clear clustering of sildenafil versus placebo in HUVECs (Figure 1A) or placental tissue (Figure 1B). The heatmaps supported that the gene expression between samples were similar (Figure S1). Multidimensional scaling (MDS) plots of HUVECs material showed clustering in prematurity as potential modifier, but not in the treatment group, delivery route, or sex (Figure S2). MDS plots of placental material showed no clustering in the treatment group, sex, prematurity or delivery route as potential modifiers (Figure S3). All of the study characteristics were tested for association for all of the first 10 PCs. Gestational stage was associated with PC2 and PC5 in HUVECs and PC8 in placenta, delivery route was associated with PC2 and PC5 in HUVECs and PC1 and PC10 in placenta, and sex was associated with PC3 in HUVECs and PC8 in placenta (Table S2). Therefore, differences in expression due to mode of delivery, gestationagal stage, and sex were accounted for in the modeling of gene expression.

The analysis of differential expression of genes, including genes involved in the NO pathway or related to cardiovascular or renal development or function, did not show any significant differences between the treatment groups, neither in HUVECs samples (Table S3) nor in placenta samples (Table S4).

Differential expression of gene sets

Gene set enrichment analysis did not show any differences between treatment groups in HUVECs samples (Table S5). However, in placental samples 90 gene sets were upregulated in sildenafil-treated compared to placebo-treated (Table S6). The selection of only the highest-ranking gene set module (overlapping modules excluded) resulted in 64 upregulated gene sets and 5 downregulated gene sets. These gene sets mostly involved immune pathways, and three gene sets were related to the NO pathway and one to cardiovascular disease (Table 2). Heatmaps were made for the top ten gene sets related to immune pathways (Figure S4), and the four gene sets related to the NO pathway and cardiovascular disease (Figure S5). This was done to study the extent of up- and downregulation for the distinct genes in these gene sets in each sample and were ordered per duration of treatment. From this analysis, most genes were up- and downregulated in accordance with the differential gene set analysis results for immunity, but this did not apply for gene sets related to the NO pathway and cardiovascular disease. None of the heatmaps showed ascending or descending expression levels correlating to duration of treatment.

The adverse in utero environment resulting in fetal growth restriction (FGR) predisposes the offspring to develop cardio-renal disease beyond the fetal developmental phase by altered epigenetic programming. Interest grew in prenatal administration of sildenafil after several animal studies showed improved fetal growth and long-term cardiovascular function.

Discussion

This sub-study within the Dutch STRIDER trial evaluated whether prenatal sildenafil administration during pregnancies complicated by severe early-onset FGR influenced gene modules, with specific focus on cardiovascular and renal programming. The RNA expression in collected HUVECs and placental tissue did not differ between the sildenafil or placebo group. Gene set enrichment analysis also showed no differences in gene sets related to cardiovascular and renal health in HUVECs, but three gene sets involved in the NO-pathway and one in cardiovascular health were possibly different in placenta samples. Additionally, we observed an upregulation of several gene sets related to immune pathways in the sildenafil-exposed placental samples.

The results of the three STRIDER trials in UK, New-Zealand and the Netherlands suggested that prenatal sildenafil does not have an indirect programming effect via placental function improvements since they observed no beneficial effects on pregnancy outcomes, such as birth weight, prolongation of pregnancy, or perinatal morbidity or mortality (Groom et al., 2019; Sharp et al., 2018; Pels et al., 2020). Complementary to this, the results from this current sub-study showed no direct cardiovascular or renal programming following prenatal sildenafil exposure. The low sample size due to the mid-term halt of the study and only collecting samples in part of the participating centers due to logistics might both have limited detection of beneficial effects. Alternatively, our lack of clear results regarding cardiovascular and renal programming might be a result of interspecies differences, since several animal studies did report a reprogramming potential of prenatal administration of NO-stimulating agents (sildenafil, pentaerythritol tetranitrate, N-acetely cysteine) in animal models for placental insufficiency (Herrera et al., 2017; Itani et al., 2017; Wu et al., 2015). However, a recent study showed that prenatal sildenafil reprogrammed salt-sensitvive hypertension in rat FGR offspring, but had not affected renal function nor did they find differences in targeted RNA-seq data in renal tissue (Turbeville et al., 2020). These conflicting results might plead for the use of tissue collected from complicated pregnancies (such as FGR) in humans to study developmental programming on a molecular level rather than the use of animal tissue.

Upregulated gene sets involved with NO pathway

We observed upregulation of three gene sets related to the NO pathway (response to vascular endothelial growth factor stimuli, leukocyte adhesion to vascular endothelial cells, and negative regulation of the NO metabolic process) in placental tissues in the sildenafil group compared with the placebo group. These gene sets might reflect the mechanism of action of sildenafil. Preclinical studies report conflicting results, with some showing altered expression of metabolites in the NO-pathway after sildenafil exposure in fetal cardiac or lung tissue (Itani et al., 2017)(Shue et al., 2014), while others did not find these differences in expression in spite of beneficial functional effects (George et al., 2013). However, while these gene sets were significantly different in our study, the heatmaps of these gene sets showed that the differences of the individual genes were minimal and independent of duration of sildenafil intake. Therefore, these inconclusive results did not lead to a clear insight regarding the mechanism of action of sildenafil.

The Dutch STRIDER trial showed a potentially increased risk of PPHN in neonates (Pels et al., 2020). The gene set of increased leukocyte adhesion to vascular endothelial cells combined with our gene set’s result on immune pathways might suggest that this pathway is involved in the increased PPHN risk (Rafikov et al., 2019; Kuebler et al., 2018; El Chami & Hassoun, 2012; Kobayashi et al., 2004). However, this was not observed in HUVECs representing the fetal profile. To gain better insight into underlying mechanisms involved with the potentially increased risk of PPHN in the Dutch STRIDER trial requires follow-up studies that were beyond the scope of this study.

Upregulated gene sets involved in the immune pathway

Interestingly, sildenafil administration resulted in the upregulation of several gene sets involved in immune or inflammation pathways and, additionally, longer sildenafil intake correlated with higher expression of genes related to these pathways. Pregnancies complicated by placental insufficiency syndromes show an increased placental release of pro-inflammatory cytokines, such as TNF-α and IL-6 and therefore targeting inflammation has been of therapeutic interest (George & Granger, 2011; Oyston et al., 2015; Kniotek & Boguska, 2017). Sildenafil might exert an anti-inflammatory response by inhibition of TNF-α and IL1β release and stimulation of IL-10 release (Ribaudo et al., 2016; Kniotek & Boguska, 2017). Indeed, prenatal sildenafil reduced TNF-α levels in maternal plasma and placenta in the rat model for preeclampsia and FGR (Gillis et al., 2016) and reduced placental TNF-α and IL1β in the mice model for pregnancy loss. Administration of a different NO stimulating agent during healthy pregnancy lowered placental expression of IL1β and IL18 in sows (Luo et al., 2019). Our study showed only significant upregulation of the IL-10 signaling and pathway, but not TNF- α or IL1β. We speculate that most of the significantly upregulated gene sets promote protection to auto-immunity and innate immunity, which is necessary for embryonal implantation and placentation. This could potentially contribute to reducing pregnancy loss after prenatal sildenafil treatment when used earlier in pregnancy (Luna et al., 2015).

Strengths and limitations

To our knowledge, this is the first study examining the effect of prenatal sildenafil administration during human pregnancies complicated by early-onset FGR on programming. One major strength is that we used two different types of tissue - with placenta representing maternal profile and HUVECs representing fetal profile - collected from a well-defined randomized controlled trial with severe early-onset FGR.

We acknowledge some limitations. This was a sub-study in which we collected samples from live births from the Dutch STRIDER trial and therefore does not fully represent the clinical pregnancy outcomes. We attempted to minimize samples bias selection by using all the samples available, even if they were not paired. Because of the halt of the Dutch STRIDER study and because women were only recruited for this substudy in 2 of the 11 recruiting centers, this study is limited by a relatively low sample size. However, it also made the analysis of these samples unique and valuable. We used native HUVECs without prior selective culturing to be as close as possible to the in situ situation. Despite extensive washing, HUVEC samples might therefore have been contaminated with a few other fetal blood cells.

Conclusion and future perspectives

FGR is associated with the developmental programming of cardiovascular and renal diseases later in life. Currently, no therapy exists to improve fetal growth or prevent these detrimental long-term consequences. Administration of PDE-5 inhibitors such as sildenafil during pregnancy showed beneficial effects on cardiovascular health in animal FGR offspring. However, our study in human pregnancies complicated by severe early-onset FGR did not show an effect of prenatal sildenafil administration on cardiovascular or renal programming. Future research is needed to understand whether an interspecies difference underlies these discrepancies or other differences in study design (such as dose) between animal and human studies. In order to progress, elucidation of (direct or indirect) underlying mechanisms and safety studies are of paramount importance in the evaluation of any new potential intervention.

List of abbreviations

CAMERA, Correlation Adjusted MEan RAnk; CPM, count per million reads; EGM, endothelial cell growth medium; FDR, False Discovery Rates; FGR, fetal growth restriction; GA, gestational age; GSEA, gene set enrichment analysis; HELLP, Hemolysis, Elevated Liver enzymes and Low Platelet syndrome; HUVECs, human umbilical vein endothelial cells; IL1β, Interleukin 1β; MDS, Multidimensional scaling; MgSO4, magnesium sulfate; NO, nitric oxide; PC, principle components; PCA, principal components analysis; PBS, phosphate-buffered saline; PPHN, persistent pulmonary hypertension; STRIDER, Sildenafil TheRapy In Dismal Prognosis Early-onset Fetal Growth Restriction; TMM, Trimmed mean of M-values; TNF-α, Tumor necrosis factor; VEGF, vascular endothelial growth factor.

Ethics approval and consent to participate

The Dutch STRIDER trial (Clincial trial.gov identifier NCT02277132) was approved by the medical ethical committee of the AMC on 02-07-2014; protocol number 2014-131. The UMCU approved the study on 14-09-2015; protocol number 15-510/G-C. Prior to delivery, the STRIDER participants in this sub-study gave additional written informed consent for placental research (amendment approved on 29-01-2016, updated on 05-09-2017).

Conflict of interest

None declared.

Availability of data and materials

The datasets generated and/or analyzed during the current study are not publicly available due to the Dutch privacy law to protect participants, but are partly and always coded available from the corresponding author on request. All data generated or analyzed during this study are included in this published article and its supplementary information files.

Figure Legends

Figure 1

Principal component analysis (PCA) plots of A) human umbilical vein endothelial cells (HUVECs) and of B) placenta.PC1 versus PC2 does not show clustering in treatment group sildenafil (blue) vs. placebo (red) in HUVECs or placental tissue.

Tables

Table 1: Maternal and neonatal characteristics

 

HUVECs

Placenta

 

Sildenafil

(n=12)

Placebo

(n=8)

p-value

Sildenafil

(n=13)

Placebo (n=13)

p-value

Maternal characteristics during pregnancy

Age, years

35±6

31±3

0.19

34±6

33±6

0.66

(pre-pregnancy) BMI, kg/m3

23±3

24±6

0.74

24±4#

26±7#

0.29

Preeclampsia/HELLP, %

8 (67)

3 (38)

0.36

6 (46)

5 (39)

1.00

Smoking, %

1 (8)

0 (0)

1.00

1 (8)

2 (15)

1.00

Maternal medication during pregnancy

Antihypertensive drugs, %

8 (67)

2 (25)

0.17

6 (46)

4 (31)

0.69

Antenatal steroids, %

9 (75)

7 (88)

0.62

8 (62)

7 (54)

1.00

MgSO4, %

2 (18)#

0 (0)

0.49

2 (15)

0 (0)

0.48

GA start allocated drug, weeks

25.0±2.0

24.5±2.2#

0.64

24.0±2.5

25.0±2.4

0.33

Duration allocated drug, days

30.6±20.1

44.3±20.1#

0.17

25.4±18.5

24.7±17.8

0.92

Delivery

Caesarean section, %

9 (75)

6 (75)

1.00

8 (62)

6 (46)

0.70

Apgar at 5 min

8 (3-10)

8 (6-10)

0.88

6 (0-9)

8 (0-10)

0.29

Neonatal characteristics

Male gender, %

7 (58)

5 (63)

1.00

8 (62)

6 (46)

0.70

GA at birth, weeks

30.8±4.3

32.2±3.7

0.45

27.8±1.9

29.4±4.1

0.21

Birth weight, gram

795

 (430-2528)

852

(580-2282)

0.64

520

(280-1005)

770

(315-2385)

0.23

Birth weight, percentile

3.6

(<0.01-16.7)

1.0

 (<0.01-4.7)

0.22

0.1

(<0.01-13.3)

0.7

(<0.01-8.0)

0.19

      - <3rd percentile

6 (50)

2 (25)

0.37

8 (62)

8 (62)

1.00

Survival, %

8 (67)

7 (88)

0.60

5 (42)

8 (62)

0.43

PPHN, %

3 (25)

0 (0)

0.24

2 (15)

0 (0)

0.48

Data expressed as mean±SD, median (min-max), and n(%), which were respectively tested with independent t-test, Mann-Whitney, or Fisher exact. Magnesium sulfate (MgSO4) was based on the maternal indication. # represents missing data of maximal one patient per group and therefore, the percentages are calculated based on the number of observations/measurements. GA, gestational age; HELLP, Hemolysis, Elevated Liver enzymes and Low Platelet syndrome; HUVECs, human umbilical vein endothelial cells; p, percentile; PPHN, persistent pulmonary hypertension.

Table 2: Significantly different gene sets related to cardiovascular development or NO pathway between in vivo sildenafil and placebo treated placental tissue samples

Gene set name

Up or down

p-value

FDR

Brief description

GO_CELLULAR_RESPONSE_TO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_STIMULUS

Up

0.0013

0.0437

Any process that results in a change in state or activity of a cell (movement, secretion, enzyme production, gene expression) as a result of a VEGF stimulus

GO_LEUKOCYTE_ADHESION_TO_VASCULAR_ENDOTHELIAL_CELL

Up

0.0031

0.0848

The attachment of a leukocyte to vascular endothelial cell via adhesion molecules

GO_NEGATIVE_REGULATION_OF_NITRIC_OXIDE_METABOLIC_PROCESS

Up

0.0031

0.0848

Any process that stops, prevents or reduces the frequency, rate or extent of nitric oxide metabolic process

BIOCARTA_AMI_PATHWAY

Up

0.0036

0.0945

Acute myocardial infarction is the condition of irreversible necrosis of the heart muscle that results from prolonged ischemia

Ordered according to lowest false discovery rate (FDR). VEGF, vascular endothelial growth factor.

Supplementary materials

Table S1: Overview of the gene-sets related to cardiovascular and renal health and the NO-pathway

Gene-sets involved with cardiovascular development, function, and health

KEGG_CARDIAC_MUSCLE_CONTRACTION

REACTOME_PLATELET_ACTIVATION_SIGNALING_AND_AGGREGATION

BIOCARTA_GCR_PATHWAY

BIOCARTA_NO1_PATHWAY

KEGG_VASCULAR_SMOOTH_MUSCLE_CONTRACTION

BIOCARTA_CARDIACEGF_PATHWAY

KEGG_ARRHYTHMOGENIC_RIGHT_VENTRICULAR_CARDIOMYOPATHY_ARVC

BIOCARTA_P53HYPOXIA_PATHWAY

BIOCARTA_NFAT_PATHWAY

BIOCARTA_HIF_PATHWAY

KEGG_HYPERTROPHIC_CARDIOMYOPATHY_HCM; KEGG_DILATED_CARDIOMYOPATHY

REACTOME_CELL_SURFACE_INTERACTIONS_AT_THE_VASCULAR_WALL

KEGG_VEGF_SIGNALING_PATHWAY

BIOCARTA_PAR1_PATHWAY

BIOCARTA_PLATELETAPP_PATHWAY

BIOCARTA_PGC1A_PATHWAY

BIOCARTA_ALK_PATHWAY

BIOCARTA_AMI_PATHWAY

HALLMARK_ANGIOGENESIS

REACTOME_ENOS_ACTIVATION_AND_REGULATION

REACTOME_HEMOSTASIS

REACTOME_VEGF_LIGAND_RECEPTOR_INTERACTIONS

REACTOME_REGULATION_OF_HYPOXIA_INDUCIBLE_FACTOR_HIF_BY_OXYGEN

BIOCARTA_VEGF_PATHWAY

BIOCARTA_HIF_PATHWAY

PID_ENDOTHELIN_PATHWAY

PID_HIF1_TFPATHWAY

PID_HIF1A_PATHWAY

PID_HIF2PATHWAY

PID_VEGF_VEGFR_PATHWAY

PID_VEGFR1_2_PATHWAY

PID_VEGFR1_PATHWAY

PID_THROMBIN_PAR1_PATHWAY

PID_THROMBIN_PAR4_PATHWAY

REACTOME_FORMATION_OF_FIBRIN_CLOT_CLOTTING_CASCADE 

REACTOME_SIGNALING_BY_VEGF

REACTOME_METABOLISM_OF_LIPIDS

BIOCARTA_LDL_PATHWAY

HALLMARK_FATTY_ACID_METABOLISM

GO_ATRIAL_CARDIAC_MUSCLE_TISSUE_DEVELOPMELOPMENT

GO_ATRIOVENTRICULAR_CANAL_DEVELOPMENT

GO_BRANCHING_INVOLVED_IN_BLOOD_VESSEL_MORPHOGENESIS

GO_CARDIAC_ATRIUM_DEVELOPMENT

GO_CARDIAC_CELL_DEVELOPMENT

GO_CARDIAC_CELL_FATE_COMMITMENT

GO_CARDIAC_CHAMBER_DEVELOPMENT

GO_CARDIAC_CHAMBER_FORMATION

GO_CARDIAC_CHAMBER_MORPHOGENESIS

GO_CARDIAC_CONDUCTION_SYSTEM_DEVELOPMENT

GO_CARDIAC_EPITHELIAL_TO_MESENCHYMAL_TRANSITION

GO_CARDIAC_LEFT_VENTRICLE_MORPHOGENESIS

GO_CARDIAC_MUSCLE_CELL_CARDIAC_MUSCLE_CELL_ADHESION

GO_CARDIAC_MUSCLE_CELL_CONTRACTION

GO_CARDIAC_MUSCLE_CELL_DIFFERENTIATION

GO_CARDIAC_MUSCLE_CELL_MYOBLAST_DIFFERENTIATION

GO_CARDIAC_MUSCLE_CELL_PROLIFERATION

GO_CARDIAC_MUSCLE_CONTRACTION

GO_CARDIAC_MUSCLE_FIBER_DEVELOPMENT

GO_CARDIAC_MUSCLE_MYOBLAST_PROLIFERATION

GO_CARDIAC_MUSCLE_TISSUE_DEVELOPMENT

GO_CARDIAC_MUSCLE_TISSUE_MORPHOGENESIS

GO_CARDIAC_MUSCLE_TISSUE_REGENERATION

GO_CARDIAC_MYOFIBRIL

GO_CARDIAC_SEPTUM_DEVELOPMENT

GO_CARDIAC_NEURAL_CREST_CELL_DEVELOPMENT_INVOLVED_IN_OUTFLOW_TRACT_MORPHOGENESIS

GO_CARDIAC_NEURAL_CREST_CELL_DIFFERENTIATION_INVOLVED_IN_HEART_DEVELOPMENT

GO_CARDIAC_PACEMAKER_CELL_DIFFERENTIATION

GO_CARDIAC_RIGHT_VENTRICLE_MORPHOGENESIS

GO_CARDIAC_SEPTUM_MORPHOGENESIS

GO_CARDIAC_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_CARDIAC_VENTRICLE_DEVELOPMENT

GO_CARDIAC_VENTRICLE_FORMATION

GO_CARDIAC_VENTRICLE_MORPHOGENESIS

GO_CARDIOBLAST_DIFFERENTIATION

GO_CARDIOBLAST_PROLIFERATION

GO_CARDIOCYTE_DIFFERENTIATION

GO_CARDIOVASCULAR_SYSTEM_DEVELOPMENT

GO_CELLULAR_RESPONSE_TO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_STIMULUS

GO_ENDOCARDIAL_CUSHION_DEVELOPMENT

GO_EPITHELIAL_TO_MESENCHYMAL_TRANSITION_INVOLVED_IN_ENDOCARDIAL_CUSHION_FORMATION

GO_HEART_FORMATION

GO_HIS_PURKINJE_SYSTEM_DEVELOPMENT

GO_INTERCALATED_DISC

GO_LEUKOCYTE_ADHESION_TO_VASCULAR_ENDOTHELIAL_CELL

GO_MUSCLE_HYPERTROPHY

GO_NEGATIVE_REGULATION_OF_CARDIAC_MUSCLE_ADAPTATION

GO_NEGATIVE_REGULATION_OF_CARDIAC_MUSCLE_CELL_PROLIFERATION

GO_NEGATIVE_REGULATION_OF_CARDIAC_MUSCLE_CONTRACTION

GO_NEGATIVE_REGULATION_OF_CARDIAC_MUSCLE_TISSUE_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_CARDIAC_MUSCLE_TISSUE_GROWTH

GO_NEGATIVE_REGULATION_OF_CARDIOCYTE_DIFFERENTIATION

GO_NEGATIVE_REGULATION_OF_CELL_GROWTH_INVOLVED_IN_CARDIAC_MUSCLE_CELL_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_CELLULAR_RESPONSE_TO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_STIMULUS

GO_NEGATIVE_REGULATION_OF_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_APOPTOTIC_PROCESS

GO_NEGATIVE_REGULATION_OF_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_MIGRATION

GO_NEGATIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_CELL_PROLIFERATION

GO_NEGATIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_SIGNALING_PATHWAY

GO_NEGATIVE_REGULATION_OF_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_NEGATIVE_REGULATION_OF_VASCULAR_SMOOTH_MUSCLE_CELL_PROLIFERATION

GO_PHYSIOLOGICAL_CARDIAC_MUSCLE_HYPERTROPHY

GO_POSITIVE_REGULATION_OF_CARDIAC_MUSCLE_ADAPTATION

GO_POSITIVE_REGULATION_OF_CARDIAC_MUSCLE_CELL_DIFFERENTIATION

GO_POSITIVE_REGULATION_OF_CARDIAC_MUSCLE_CELL_PROLIFERATION

GO_POSITIVE_REGULATION_OF_CARDIAC_MUSCLE_TISSUE_DEVELOPMENT

GO_POSITIVE_REGULATION_OF_CARDIAC_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_POSITIVE_REGULATION_OF_CARDIOBLAST_DIFFERENTIATION

GO_POSITIVE_REGULATION_OF_CARDIOCYTE_DIFFERENTIATION

GO_POSITIVE_REGULATION_OF_CELL_GROWTH_INVOLVED_IN_CARDIAC_MUSCLE_CELL_DEVELOPMENT

GO_POSITIVE_REGULATION_OF_CELL_MIGRATION_BY_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_SIGNALING_PATHWAY

GO_POSITIVE_REGULATION_OF_ENDOTHELIAL_CELL_CHEMOTAXIS_BY_VEGF_ACTIVATED_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_SIGNALING_PATHWAY

GO_POSITIVE_REGULATION_OF_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_APOPTOTIC_PROCESS

GO_POSITIVE_REGULATION_OF_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_MIGRATION

GO_POSITIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_CELL_PROLIFERATION

GO_POSITIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_PRODUCTION

GO_POSITIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_SIGNALING_PATHWAY

GO_POSITIVE_REGULATION_OF_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_SIGNALING_PATHWAY

GO_POSITIVE_REGULATION_OF_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_POSITIVE_REGULATION_OF_VASCULAR_SMOOTH_MUSCLE_CELL_PROLIFERATION

GO_PURKINJE_MYOCYTE_TO_VENTRICULAR_CARDIAC_MUSCLE_CELL_SIGNALING

GO_REGULATION_OF_CARDIAC_EPITHELIAL_TO_MESENCHYMAL_TRANSITION

GO_REGULATION_OF_CARDIAC_MUSCLE_ADAPTATION

GO_REGULATION_OF_CARDIAC_MUSCLE_CELL_DIFFERENTIATION

GO_REGULATION_OF_CARDIAC_MUSCLE_TISSUE_DEVELOPMENT

GO_REGULATION_OF_CARDIAC_MUSCLE_TISSUE_REGENERATION

GO_REGULATION_OF_CARDIAC_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_REGULATION_OF_CARDIOBLAST_DIFFERENTIATION

GO_REGULATION_OF_CARDIOCYTE_DIFFERENTIATON

GO_REGULATION_OF_CELL_GROWTH_INVOLVED_IN_CARDIAC_MUSCLE_CELL_DEVELOPMENT

GO_REGULATION_OF_CELLULAR_RESPONSE_TO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_STIMULUS

GO_REGULATION_OF_HEART_RATE_BY_CARDIAC_CONDUCTION

GO_STRIATED_MUSCLE_CELL_DIFFERENTIATION

GO_STRIATED_MUSCLE_CELL_PROLIFERATION

GO_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_APOPTOTIC_PROCESS

GO_VASCULAR_ASSOCIATED_SMOOTH_MUSCLE_CELL_MIGRATION

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_ACTIVATED_RECEPTOR_ACTIVITY

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_BINDING

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_PRODUCTION

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_2_BINDING

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_BINDING

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_RECEPTOR_SIGNALING_PATHWAY

GO_VASCULAR_ENDOTHELIAL_GROWTH_FACTOR_SIGNALING_PATHWAY

GO_VASCULAR_SMOOTH_MUSCLE_CELL_DEVELOPMENT

GO_VASCULAR_SMOOTH_MUSCLE_CELL_DIFFERENTIATION

GO_VASCULAR_SMOOTH_MUSCLE_CONTRACTION

GO_VENTRICULAR_CARDIAC_MUSCLE_CELL_DEVELOPMENT

GO_VENTRICULAR_CARDIAC_MUSCLE_CELL_DIFFERENTIATION

GO_VENTRICULAR_CARDIAC_MUSCLE_CELL_MEMBRANE_REPOLARIZATION

GO_VENTRICULAR_CARDIAC_MUSCLE_TISSUE_DEVELOPMENT

GO_VENTRICULAR_COMPACT_MYOCARDIUM_MORPHOGENESIS

GO_VENTRICULAR_TRABECULA_MYOCARDIUM_MORPHOGENESIS

GO_POSITIVE_REGULATION_OF_BLOOD_CIRCULATION

GO_POSITIVE_REGULATION_OF_BLOOD_PRESSURE

GO_POSITIVE_REGULATION_OF_BLOOD_PRESSURE_BY_EPINEPHRINE_NOREPINEPHRINE

GO_POSITIVE_REGULATION_OF_BLOOD_VESSEL_DIAMETER

GO_POSITIVE_REGULATION_OF_BLOOD_VESSEL_ENDOTHELIAL_CELL_MIGRATION

GO_POSITIVE_REGULATION_OF_BLOOD_VESSEL_ENDOTHELIAL_CELL_PROLIFERATION_INVOLVED_IN_SPROUTING_ANGIOGENESIS

GO_POSITIVE_REGULATION_OF_BLOOD_VESSEL_REMODELING

GO_POSITIVE_REGULATION_OF_CELL_MIGRATION_INVOLVED_IN_SPROUTING_ANGIOGENESIS

GO_POSITIVE_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_REGULATION_OF_BLOOD_CIRCULATION

GO_REGULATION_OF_BLOOD_PRESSURE

GO_REGULATION_OF_BLOOD_VESSEL_REMODELING

GO_REGULATION_OF_CELL_MIGRATION_INVOLVED_IN_SPROUTING_ANGIOGENESIS

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOODD_PRESSURE_BY_CIRCULATORY_RENIN_ANGIOTENSIN

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_BY_ENDOTHELIN

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_BY_NOREPINEPHRINE_EPINEPHRINE

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_BY_RENIN_ANGIOTENSIN

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_BY_VASOPRESSIN

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_MEDIATED_BY_A_CHEMICAL_SIGNAL

GO_REGULATION_OF_VASOCONSTRICTION

GO_RENAL_CONTROL_OF_PERIPHERAL_VASCULAR_RESISTANCE_INVOLVED_IN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_RENAL_RESPONSE_TO_BLOOD_FLOW_INVOLVED_IN_CIRCULATORY_RENIN_ANGIOTENSIN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_SPROUTING_ANGIOGENESIS

GO_VASCULOGENESIS

GO_VENOUS_BLOOD_VESSEL_MORPHOGENESIS

GO_VENTRICULAR_CARDIAC_MUSCLE_CELL_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_BLOOD_CIRCULATION

GO_NEGATIVE_REGULATION_OF_BLOOD_PRESSURE

GO_NEGATIVE_REGULATION_OF_BLOOD_VESSEL_ENDOTHELIAL_CELL_PROLIFERATION_INVOLVED_IN_SPROUTING_ANGIOGENESIS

GO_NEGATIVE_REGULATION_OF_BLOOD_VESSEL_ENDOTHELIAL_CELL_MIGRATION

GO_NEGATIVE_REGULATION_OF_BLOOD_VESSEL_DIAMETER

GO_OUTFLOW_TRACT_MORPHOGENESIS

GO_CELLULAR_LIPID_METABOLIC_PROCESS

GO_CELLULAR_LIPID_METABOLIC_PROCESS

GO_REGULATION_OF_LIPID_METABOLIC_PROCESS

Gene-sets involved in renal development, function, and health

KEGG_ALDOSTERONE_REGULATED_SODIUM_REABSORPTION

KEGG_VASOPRESSIN_REGULATED_WATER_REABSORPTION

KEGG_ALDOSTERONE_REGULATED_SODIUM_REABSORPTION

BIOCARTA_EPONFKB_PATHWAY

BIOCARTA_EPONFKB_PATHWAY

BIOCARTA_RAS_PATHWAY

KEGG_RENIN_ANGIOTENSIN_SYSTEM

KEGG_PROXIMAL_TUBULE_BICARBONATE_RECLAMATION

REACTOME_REGULATION_OF_WATER_BALANCE_BY_RENAL_AQUAPORINS

BIOCARTA_EPO_PATHWAY

BIOCARTA_ACE2_PATHWAY

PID_EPO_PATHWAY

PID_RAS_PATHWAY

GO_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_CELL_MIGRATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_EPITHELIAL_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_EPITHELIAL_TUBE_MORPHOGENESIS

GO_GLOMERULAR_MESANGIAL_CELL_DEVELOPMENT

GO_GLOMERULAR_MESANGIAL_CELL_DIFFERENTIATION

GO_GLOMERULAR_MESANGIUM_DEVELOPMENT

GO_KIDNEY_EPITHELIUM_DEVELOPMENT

GO_KIDNEY_MESENCHYME_DEVELOPMENT

GO_KIDNEY_MORPHOGENESIS

GO_MESANGIAL_CELL_DEVELOPMENT

GO_MESENCHYMAL_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_METANEPHRIC_GLOMERULAR_MESANGIUM_DEVELOPMENT

GO_METANEPHRIC_RENAL_VESICLE_MORPHOGENESIS

GO_METANEPHROS_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_CELL_PROLIFERATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_EPITHELIAL_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_NEGATIVE_REGULATION_OF_KIDNEY_DEVELOPMENT

GO_PATTERN_SPECIFICATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_POSITIVE_REGULATION_OF_CELL_PROLIFERATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_POSITIVE_REGULATION_OF_EPITHELIAL_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_POSITIVE_REGULATION_OF_KIDNEY_DEVELOPMENT

GO_PRONEPHROS_DEVELOPMENT

GO_PROXIMAL_DISTAL_PATTERN_FORMATION_INVOLVED_IN_NEPHRON_DEVELOPMENT

GO_REGULATION_OF_CELL_PROLIFERATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_REGULATION_OF_EPITHELIAL_CELL_DIFFERENTIATION_INVOLVED_IN_KIDNEY_DEVELOPMENT

GO_REGULATION_OF_GLOMERULAR_FILTRATION

GO_REGULATION_OF_KIDNEY_DEVELOPMENT

GO_REGULATION_OF_RENAL_SYSTEM_PROCESS

GO_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE_BY_VASOPRESSIN

GO_RENAL_ABSORPTION

GO_RENAL_CONTROL_OF_PERIPHERAL_VASCULAR_RESISTANCE_INVOLVED_IN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_RENAL_FILTRATION

GO_RENAL_SODIUM_ION_TRANSPORT

GO_RENAL_SYSTEM_DEVELOPMENT

GO_RENAL_SYSTEM_PROCESS

GO_RENAL_SYSTEM_PROCESS_INVOLVED_IN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_RENAL_SYSTEM_VASCULATURE_DEVELOPMENT

GO_RENAL_SYSTEM_VASCULATURE_MORPHOGENESIS

GO_RENAL_TUBULE_DEVELOPMENT

GO_RENAL_VESICLE_DEVELOPMENT

GO_RENAL_VESICLE_FORMATION

GO_RENAL_WATER_HOMEOSTASIS

GO_RENAL_WATER_TRANSPORT

GO_RENAL_SYSTEM_PROCESS_INVOLVED_IN_REGULATION_OF_BLOOD_VOLUME

GO_RENAL_SYSTEM_PROCESS_INVOLVED_IN_REGULATION_OF_SYSTEMIC ARTERIAL_BLOOD_PRESSURE

GO_RENAL_RESPONSE_TO_BLOOD_FLOW_INVOLVED_IN_CIRCULATORY_RENIN_ANGIOTENSIN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

GO_RENAL_CONTROL_OF_PERIPHERAL_VASCULAR_RESISTANCE_INVOLVED_IN_REGULATION_OF_SYSTEMIC_ARTERIAL_BLOOD_PRESSURE

Gene-sets involved with the NO-pathway

REACTOME_NITRIC_OXIDE_STIMULATES_GUANYLATE_CYCLASE

BIOCARTA_NOS1_PATHWAY

BIOCARTA_NO1_PATHWAY

REACTOME_CGMP_EFFECTS

REACTOME_ENOS_ACTIVATION_AND_REGULATION

REACTOME_METABOLISM_OF_NITRIC_OXIDE_ENOS_ACTIVATION_AND_REGULATION

GO_NITRIC_OXIDE_MEDIATED_SIGNAL_TRANSDUCTION

GO_NITRIC_OXIDE_SYNTHASE_BINDING

GO_POSITIVE_REGULATION_OF_NITRIC_OXIDE_SYNTHASE_ACTIVITY

GO_CELLULAR_RESPONSE_TO_NITRIC_OXIDE

GO_NEGATIVE_REGULATION_OF_NITRIC_OXIDE_METABOLIC_PROCESS

GO_NITRIC_OXIDE_MEDIATED_SIGNAL_TRANSDUCTION

GO_NITRIC_OXIDE_SYNTHASE_BIOSYNTHETIC_PROCESS

GO_NITRIC_OXIDE_SYNTHASE_REGULATOR_ACTIVITY

GO_POSITIVE_REGULATION_OF_NITRIC_OXIDE_MEDIATED_SIGNAL_TRANSDUCTION

GO_POSITIVE_REGULATION_OF_NITRIC_OXIDE_METABOLIC_PROCESS

GO_REGULATION_OF_NITRIC_OXIDE_BIOSYNTHETIC_PROCESS

GO_RESPONSE_TO_NITRIC_OXIDE

These gene-sets were selected from the pre-built gene-sets in homo sapiens in the Molecular Signature database (MsigDB, v7.1), in the hallmark (H) and canonical pathways of curated (C2) collection - containing  BioCarta, KEGG, PID, Reactome gene sets – and all gene-sets involved in cardiovascular, renal or NO-pathway of the GO gene-sets (C5) searched for with the terms ‘cardial OR cardiac OR cardio* OR vascular OR blood pressure’,  ‘kidney OR renal’, ‘nitric oxide‘(Liberzon et al., 2015; Subramanian et al., 2005).

Table S2: Per principal component best correlated modulator

 

HUVECs

 

Placenta

 

 

PC

Modulator

Ranksum

p-value

Modulator

Ranksum

p-value

PC1

Gestational Stage

-1.1490

0.25

Delivery route

2.5717

0.01

 

Delivery route

1.0911

0.28

Treatment group

-0.9487

0.34

 

Sex

-0.6172

0.54

Gestational Stage

0.7698

0.44

 

Treatment group

0.2315

0.83

Sex 

0.1029

0.92

PC2

Gestational Stage

2.0207

0.04

Gestational Stage

-1.1547

0.25

 

Delivery route

-1.9640

0.049

Delivery route

-0.6172

0.54

 

Treatment group

1.1573

0.25

Treatment group

0.2821

0.78

 

Sex

-0.5401

0.59

Sex

0.2057

0.84

PC3

Sex

2.2374

0.03

Treatment group

1.9231

0.05

 

Gestational Stage

-1.2283

0.22

Sex

1.1316

0.26

 

Delivery route

1.0911

0.28

Delivery route

0.7715

0.44

 

Treatment group

0.1543

Gestational Stage

-0.2887

0.77

PC4

Gestational Stage

1.4660

0.14

Delivery route

-1.5944

0.11

 

Delivery route

-0.9165

0.36

Sex

-1.0801

0.28

 

Sex

-0.6172

0.54

Gestational Stage

-0.4811

0.63

 

Treatment group

-0.2315

0.82

Treatment group

-0.3846

0.70

PC5

Gestational Stage

-2.4169

0.02

Sex

-1.8516

0.06

 

Delivery route

2.0512

0.04

Gestational Stage

-1.7321

0.08

 

Treatment group

1.4659

0.14

Delivery route

1.5430

0.12

 

Sex

0.6943

0.49

Treatment group

0.8974

0.37

PC6

Delivery route

-0.9165

0.36

Gestational Stage

-1.9245

0.05

 

Treatment group

0.6172

0.54

Sex

0.0896

0.09

 

Sex

0.5891

0.59

Treatment group

-0.6923

0.69

 

Gestational Stage

-0.1981

0.84

Delivery route

0.3086

0.76

PC7

Delivery route

0.3055

0.76

Gestational Stage

-1.2509

0.21

 

Treatment group

-0.2315

0.82

Treatment group

0.8974

0.37

Gestational Stage

-0.1981

0.84

Sex

0.3819

0.38

 

Sex

-0.0772

0.94

Delivery route

0.3600

0.72

PC8

Sex

1.0801

0.28

Sex

2.1088

0.03

 

Delivery route

-0.9165

0.36

Gestational Stage

2.0207

0.04

 

Gestational Stage

-0.9113

0.36

Delivery route

-1.6973

0.09

 

Treatment group

-0.2315

0.82

Treatment group

-0.1282

0.90

PC9

Delivery route

1.0911

0.28

Sex

1.9545

0.05

 

Treatment group

0.3858

0.70

Delivery route

-0.5143

0.61

 

Gestational Stage

0.1981

0.84

Gestational Stage

-0.2887

0.77

 

Sex

-0.0772

0.94

Treatment group

-0.1282

0.90

PC10

Sex

1.8516

0.06

Delivery route

2.6232

0.01

 

Treatment group

1.5430

0.12

Gestational Stage

-1.6358

0.10

 

Delivery route

-1.1784

0.24

Sex

-0.7201

0.47

 

Gestational Stage

-0.3566

0.72

Treatment group

0.2820

0.78

Expanded results

 Figure S1: Correlation heatmaps of A) HUVECs and B) placental tissue samples

Figure S2: Multidimensional scaling (MDS) plots of HUVECs samples

The MDS plots of A) treatment group with Sildenafil (SIL) vs placebo (CTRL), B) mode of delivery with caesarian section (CS) vs spontaneous delivery (SP), C) gestational age at birth with preterm (<37 weeks) vs term (>37 weeks) and D) sex with female (F) vs male (M). Clustering was only visuable for preterm vs term.

 

Figure S3: Multidimensional scaling (MDS) plots of STRIDER placental tissue samples

No clustering was shown in the MDS plots of A) treatment group with Sildenafil (SIL) vs placebo (CTRL), B) mode of delivery with caesarian section (CS) vs spontaneous delivery (SP), C) gestational age at birth with preterm (<37 weeks) vs term (>37 weeks) and D) sex with female (F) vs male (M).

 

Figure S4: Top ten significant differential expressed gene sets related to immune or inflammatory pathways in placental tissue

The samples are ordered per group by duration of treatment. From left to right, from longest duration of treatment to the shortest duration of treatment. CS, caesarean section; SP, spontaneous delivery.


 

Figure S5: Four significant differential expressed gene sets related to the nitric oxide pathway or cardiovascular disease in placental tissue

The samples are ordered per group by duration of treatment. From left to right, from longest duration of treatment to the shortest duration of treatment. CS, caesarean section; SP, spontaneous delivery.

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