Next Article in Journal
Defining the Skeletal Myogenic Lineage in Human Pluripotent Stem Cell-Derived Teratomas
Next Article in Special Issue
The Role of Matrix-Bound Extracellular Vesicles in the Regulation of Endochondral Bone Formation
Previous Article in Journal
Code Red in the Supply Center: The Impact of Immune Activation on Hematopoiesis
Previous Article in Special Issue
miR-150-5p and let-7b-5p in Blood Myeloid Extracellular Vesicles Track Cognitive Symptoms in Patients with Multiple Sclerosis
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

The Role of Non-Coding RNAs in the Human Placenta

Milena Žarković
Franziska Hufsky
Udo R. Markert
3,‡ and
Manja Marz
RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, Leutragraben 1, 07743 Jena, Germany
European Virus Bioinformatics Center, Leutragraben 1, 07743 Jena, Germany
Placenta Lab, Department of Obstetrics, University Hospital Jena, Am Klinikum 1, 07747 Jena, Germany
FLI Leibniz Institute for Age Research, Beutenbergstraße 11, 07745 Jena, Germany
Aging Research Center (ARC), 07745 Jena, Germany
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
These authors contributed equally to this work.
Cells 2022, 11(9), 1588;
Submission received: 8 March 2022 / Revised: 1 May 2022 / Accepted: 3 May 2022 / Published: 9 May 2022
(This article belongs to the Special Issue Extracellular Vesicle-Associated Non-Coding RNAs)


Non-coding RNAs (ncRNAs) play a central and regulatory role in almost all cells, organs, and species, which has been broadly recognized since the human ENCODE project and several other genome projects. Nevertheless, a small fraction of ncRNAs have been identified, and in the placenta they have been investigated very marginally. To date, most examples of ncRNAs which have been identified to be specific for fetal tissues, including placenta, are members of the group of microRNAs (miRNAs). Due to their quantity, it can be expected that the fairly larger group of other ncRNAs exerts far stronger effects than miRNAs. The syncytiotrophoblast of fetal origin forms the interface between fetus and mother, and releases permanently extracellular vesicles (EVs) into the maternal circulation which contain fetal proteins and RNA, including ncRNA, for communication with neighboring and distant maternal cells. Disorders of ncRNA in placental tissue, especially in trophoblast cells, and in EVs seem to be involved in pregnancy disorders, potentially as a cause or consequence. This review summarizes the current knowledge on placental ncRNA, their transport in EVs, and their involvement and pregnancy pathologies, as well as their potential for novel diagnostic tools.

1. Introduction

The placenta forms the connection and the barrier between the mother and her fetus. It is one of the organs with the highest variability between different species. It differs in shape, size, number and layers between fetal and maternal blood. Moreover, the hormonal regulation of each trimester of pregnancy and the respective sources of hormones are almost unique in each species. Consequently, these differences include the uniqueness of pathologies in different species as reviewed for mice by Schmidt et al. [1]. Therefore, in this review we focus on the human placenta. It may be assumed that the underlying regulation of placentation occurs on a molecular level, which includes specific proteins and their respective specific gene expression control. A great part of this control acts post-transcriptionally through interactions on the RNA level, mainly via non-coding RNA (ncRNA)-induced RNA degradation and inhibition of translation. The cellular interface between mother and fetus is built by different subtypes of trophoblast cells, which are of fetal origin. The functions of the different trophoblast subtypes are manifold and include two-directional transport of water and a broad spectrum of molecules, hormone production, anchoring of the fetus in the uterus, immunoregulation, angiogenesis and others. Trophoblast cells, and mainly the syncytiotrophoblast, are able to produce different types of extracellular vesicles and release them into the maternal circulation. Trophoblast-derived extracellular vesicles contain cytoplasm components from their cells of origin, including proteins and RNA, and transport them to distant targets [2]. This complex system of factors and their balance seems to be susceptible to disorders that may lead to pregnancy pathologies, but it can be expected that yet unknown or uninvestigated factors are also involved. These may include ncRNAs in trophoblast cells and trophoblast-derived extracellular vesicles which seem to be indispensable for the molecular regulation of normal pregnancies, while their dysregulation may lead to the development of pregnancy-related diseases [3].
From the pilot project of ENCODE, we know that less than 3% of the human genome codes for proteins [4,5]. The remaining 97% are divided into 45% repetitive elements (SINEs, LINEs, transposons), 26% introns and other unique non-coding DNA [6]. The question of their meaning has been raised and is only being answered slowly. By now, we know that at least 80% of the human genome has a function [5]. Some ncRNAs are known to be located intergenically, within introns, in 5 /3 UTRs, antisense to protein-coding genes or just adjacent to them [7] (Figure 1). Most studies on placental ncRNAs focus on microRNA and long ncRNAs, while studies on ncRNAs of a length in between are comparatively scarce.
miRNAs are 19–25 nt single-stranded RNAs, belonging to the class of small ncRNAs, which mediate the post-transcriptional gene silencing of target RNA transcripts. This gene regulation takes place by binding to mRNA and degrading the transcript or blocking the translation. It is estimated that miRNAs govern the translation of 30–90% of protein-coding genes [8,9]. miRNAs can also be imported back into the nucleus to alter DNA methylation at promoters. Deregulated miRNAs have been associated with all kinds of human diseases.
LncRNAs can act as sponges to inhibit miRNA function by isolating them from their target mRNAs. LncRNAs can further interact with proteins in the cytoplasm and also enter the nucleus to interact with chromatin and regulate gene expression.
The third group of ncRNAs, circular RNAs, are generated from exon regions of protein-coding genes by 5 -3 splicing and are proposed to function as sponges blocking miRNA activity. CircRNAs are relatively unexplored in the placenta but are likely to be of importance [10].
During the last decade, microRNAs (miRNAs, 22 nt), as regulators of various cell processes, received major attention. However, according to Rfam 14.6 (July 2021) 4070 RNA families are discovered. About one quarter (1067) are known to exist in humans, covering 16,421 genomic regions ( (accessed on 17 January 2022)) [11]. Additionally, the existence of long non-coding RNAs (lncRNAs, >200 nt) containing introns themselves is estimated in humans by GENCODE 7 to 9640 loci [12]. Our knowledge about lncRNAs is limited and only a few general computer programs for their identification are developed, see the section below.
Transcriptome analysis is increasingly used to investigate placental development. Thus, not much is known about ncRNA expression in the human placenta, their functions in placental development, and their role in healthy pregnancies, as well as pathologies ranging from preeclampsia and gestational diabetes mellitus to preterm labor [10]. The number of reports focusing on miRNAs is rapidly increasing (see Morales Prieto and Markert [13], Morales-Prieto et al. [14] for a review) and also placental lncRNAs are brought into focus [15,16,17]. Additionally, the number of studies on placental ncRNAs of a length between miRNAs and lncRNAs has increased during recent years. Here, we focus on a summary of ncRNAs with a known function.
Initially, the principal function of ncRNA was expected to be intracellular regulation. More recently, many studies have demonstrated that ncRNA can be transported via extracellular vesicles which can be incorporated by distant cells of different types where they exert regulative effects [18]. These regulatory functions may be involved in physiological as well as pathological processes [19,20,21].
In this review, we summarize relevant current knowledge on ncRNA and their potential role in the human placenta in healthy and pathological pregnancies.

2. Prediction and Identification of ncRNAs

In silico identification of ncRNAs is still a huge challenge. The function of ncRNAs is mainly characterized by their secondary structure rather than by their sequence. Gene identification tools based on sequence homology fail for ncRNAs. Therefore, almost all ncRNA-related computational tools rely on compensatory mutation analysis or covariance models, retaining the secondary structure. The vast majority of ncRNAs are not assigned to a function yet. Whereas many ncRNA classes can be nowadays solidly predicted by secondary structure homology, a de novo detection of ncRNAs in silico is still a bioinformatical challenge. Only a few tools have been developed (Table 1), which, however, are usually restricted by disadvantages, such as high false-positive rates. Therefore, due to their diverse and fast-evolving sequence they are identified most efficiently by a combined ex or in vivo/in silico approach, including sequencing the transcriptome and the usage of established bioinformatical tools with tissue/organ/organism-specific features, such as considering specific promoters, terminators, or transcription signatures.

2.1. Identification of miRNAs as Marker Genes

Finding reliable miRNAs as biomarkers and their corresponding targets is a non-trivial task. Potential targets are scored differently by predictive computational tools and miRNA expression and miRNA:target interactions can be tissue- or context-specific but are mostly neglected in databases. Therefore, understanding the limitations of target identification is very relevant.
The identification of miRNAs and corresponding target genes can be divided into three steps: First, miRNAs of interest are selected based on information from the literature, experimental studies (e.g., high-throughput) or from databases (Figure 2 left). Second, target genes are predicted using various in silico tools for each miRNA (Figure 2 center). Third, a comparison of these possible target genes with genes known to be involved in the disease of interest (Figure 2 bottom panel) completes the computational prediction of miRNAs and their targets. While in silico predictions are fast, inexpensive, and provide a wealth of possible gene connections, predictions can be false-positive. To reduce this risk, as many prediction tools as possible are often combined (Figure 2 right).
In addition, the initial identification of possible marker miRNAs may be biased by a number of factors, e.g., the age of the pregnant women, that may influence miRNA expression levels.
The miRBase database is a searchable database of published miRNA sequences and annotation [35,36]. The Human microRNA Disease Database (HMDD v.3.2, March 2019) is a database that curated experiment-supported evidence for human miRNA and disease associations, and currently contains 1206 miRNA genes in 893 diseases [37,38] ( (accessed on 17 January 2022)), including 156 entries for preeclampsia-related miRNAs.

2.2. Non-Coding RNA Target Prediction

The prediction of the ncRNA function is a widely unsolved problem. Non-coding RNAs may interact with other RNA molecules, DNA, or with proteins [39]. The latter one in particular is computationally not explored yet. Interactions with DNA are commonly predicted as interactions with RNAs, just with the slightly different exclusion of GT/UG basepairs. If a specific region of the ncRNA is known to be functional, a vague prediction of its target is possible. However, if this region is smaller than 20 nt (such as for miRNAs), the prediction in general usually comes with a lot of false-positive target candidates. Target prediction of miRNAs, however, has been investigated intensively in the last decade. The prediction of targets in an evolutionary context based on multi-sequence alignments has been described as most reliable [40]. Combined results of predicted and experimentally verified targets can be accessed by various databases (e.g., mirbase). However, a general approach for ncRNA target prediction still needs to be developed.

3. MicroRNAs and MicroRNA Clusters in Placenta

Although first described in 1993 [41], only during the last decade have miRNAs emerged as primary epigenetic regulators which have an important role in placental development and function [42]. miRNAs in pregnancy and their complications have been reviewed by Cai et al. [43], Hayder et al. [44], Xu et al. [45]. The role of miRNAs in preimplantation embryo development and the actions of endometrial miRNAs on implantation have been reviewed by Liu et al. [46].
Placental miRNAs have been analyzed in full tissue and in isolated trophoblast cells. As the placenta contains numerous cell types, the results are only partly congruent [47,48,49,50]. In our own studies, we have detected 762 miRNAs in trophoblast cells isolated from the first and third trimester placenta, whereof 382 miRNAs are expressed at relevant levels (Ct < 35 ). When comparing first and third-trimester, 31 miRNAs were up-regulated and 14 miRNAs were down-regulated more than 100-fold [50]. Several miRNAs that are highly expressed in total placenta tissue homogenisate are also highly expressed in isolated trophoblast cells, e.g., miR-21, miR-24, miR-30b, miR-30c, miR-191 and miR-199a [48]. Other placental miRNAs may derive from fibroblasts, immune cells, or endothelial cells. Generally placenta-tissue specific miRNAs can be identified.

3.1. miRNA Clusters C14MC, C19MC and miR-371-3 in Trophoblast Cells

A large number of miRNAs is expressed in clusters which almost exclusively appear in trophoblast cells. The two most prominent ones are the largest human miRNA clusters chromosome 14 miRNA cluster (C14MC) and chromosome 19 miRNA cluster (C19MC), supplemented by the miR-371-3 cluster. All of them underly a specific expression kinetic during the course of pregnancy [50]. The functions of each individual miRNA of these clusters are controversially discussed. It may be expected that the coordinated interaction of all members of these clusters will be more powerful than individual members, but analyses of whole cluster functions are still scarce. For more detailed and summarized information refer to [51,52,53,54].
C14MC is located at the DLK1-DIO3 genomic region on chromosome 14 and contains at least 54 different miRNAs [55]. Although a few species divergences have been observed, this cluster is widely conserved among placental mammals. Nonetheless, for several C14MC members no orthologs have been detected in mice (hsa-miR-300, -329-2, -432, -487a, -541, -654, -655, -656, -889, -1185-1, and -1185-2, 376a-2) [56] and vice versa (murine miR-679, -666 and -667) [57]. C14MC members are strongly expressed in the primary first-trimester trophoblast cells and in the immortalized first-trimester extravillous trophoblast-derived cell line HTR-8/SVneo which is a frequently used but also controversially discussed model [50], which has a comparatively stable karyotype, but numerous dissimilarities with primary trophoblast cells [58,59]. The expression of C14MC members decreases towards the third- trimester and they are almost absent in JEG-3 choriocarcinoma cells and their derivates which are still more common models [50,59]. miRNAs of C14CM region are involved mostly in the pathogenesis of cancer [55].
Both, C19MC and the miR-371-3 cluster, are encoded on chromosome 19. They are predominantly expressed in the placenta but also in stem cells [14]. C19MC and C14MC are imprinted in the placenta [60,61]. C19MC consists of at least 46 miRNA genes which are mostly, but not completely conserved among primates but not in other species [14,56]. Members of this cluster are strongly expressed in human placenta tissue where they derive mainly from third-trimester trophoblast cells (less from first-trimester trophoblast) and in JEG-3 cells [47,48,49]. They may also be expressed by other placental cells such as mesenchymal stem cells [62]. C19MC miRNAs are involved in several functions: (1) they regulate implantation through inhibition of epithelial-to-mesenchymal transition [63]; (2) villous stroma and trophoblast cells release EVs containing C19MC and other miRNAs into the maternal circulation [48,49]; (3) their circulation very early in pregnancy suggests a role in the establishment of the maternal–fetal interface [64]; (4) upregulation of C19MC miRNAs is a characteristic phenomenon of preterm birth [65]; (5) C19MC miRNAs are described to be involved in antiviral protection [66]; (6) several C19MC miRNAs may trigger cancer development such as hsa-miR-520c-3p in breast cancer or hsa-miR-519d in hepatocellular carcinoma [67].
The miR-371-3 cluster (including miR-371, -372, and -373) is expressed in primary trophoblast cells, JEG-3 cells, and their hybrids, but not in immortalized HTR-8/SVneo Mice have homologous cluster miR-290-296 to the human miR-371-3 cluster [68]. miRNAs of miR371-3 cluster region act as oncogenes or tumor suppressor when up or down-regulated [69].

3.2. Placental MicroRNAs in Pregnancy Pathologies

Placental miRNA may be associated with pregnancy pathologies being involved in their pathomechanism or expressed consequently. For almost all pregnancy diseases, specific miRNA patterns have been described, but sometimes controversially (summarized in [3,70]). miRNAs regulate the proliferation [18,71,72,73], migration [72,74,75,76,77], invasion [18,71,73,74,75,76,77,78,79,80,81,82,83,84] and apoptosis [78,85,86,87] of trophoblast cells and are involved in the development of placental vasculature and spiral artery remodeling [88,89,90].

3.2.1. miRNA and Preeclampsia

In particular, for preeclampsia (PE), the role of miRNAs has emerged over the last five years. Several very comprehensive reviews have been produced [91,92,93,94,95]. However, it is still unclear how miRNAs affect the development and outcome of the disease [96]. In Table 2, we name just a few of the most important miRNAs. miRNAs have been described to be potential biomarkers for onset prediction and development of preeclampsia [96,97].

3.2.2. Gestational Diabetes Mellitus

Poirier et al. [118] reviewed the role of miRNAs in the development of gestational diabetes mellitus (GDM), Iljas et al. [119] with regard to intracellular and extracellular miRNAs and [120] with regard to the role of miR-143 for mitochondrial function and glucose metabolism. Interestingly, the up-regulation of miR-98 in the placental tissue in human GDM is linked to the global DNA methylation via targeting methyl CpG binding protein 2 (MECP2) [121]. Furthermore, placental miRNAs have been shown to potentially contribute to the pathogenesis of GDM through altering trophoblast migration [122], invasion [123,124], and apoptosis [125]. Some miRNAs, such as miR-96-5p and miR-132, can be used as diagnostic biomarkers for GDM [126,127].

3.2.3. Miscarriage

Four human miRNAs were found to be upregulated in tissue samples from early pregnancy loss and all the affected target genes are involved in its pathogenesis [42]. Up-regulation of miR-365 may contribute to recurrent miscarriage by decreasing Serum/glucocorticoid-regulated kinase 1 (SGK1) expression [128]. miRNAs are involved in the pathogenesis of pregnancy loss by the inhibition of trophoblast proliferation [129], migration and invasion [130], as well as by promotion of trophoblast [131,132] and decidual [133] apoptosis, and promotion of immune intolerance [134,135]. The down-regulation of miR-324-3p and KISS1/kisspeptins can serve as biomarker for ectopic pregnancy at early gestational ages [136].

3.2.4. Other Pathologies

In trisomy 21 placentas, seven miRNAs have been verified as upregulated. Three of these miRNAs are located on chromosome 21 [137]. Further, there is evidence that birthweight is regulated by placenta-derived miRNAs [138]. Placental miR-21 and miR-143 are important in the development of macrosomia (fetal overgrowth, birth weight ≥ 4000 g) [139]. Kennedy et al. [140] showed that placental miRNAs can regulate adipokines and affect the birthweight. miR-16-5p, miR-103-3p, and miR-27b-3p can be detected in blood and serve as an early biomarker for fetal growth restriction [141]. Moreover, there is a specific placental miRNA profile in maternal obesity. Some of the affected miRNAs may serve as predictors of lower birth weight and increased postnatal weight gain [142]. The expression of vascular cell adhesion molecule 1 (VCAM-1), the target of miR-590-3p, is reduced in intrahepatic cholestasis in pregnancy [143]. In placenta accreta, miR-29a/b/c and miR-125a inhibit apoptosis of intermediate trophoblast cells at the implantation site by targeting myeloid cell leukemia-1 (MCL1) [144,145]. Two miRNAs (hsa-miR-490-3p and hsa-miR-133a-3p) investigated by Yang et al. [146] showed positive correlation to operation-related blood volume loss. Chen et al. [147] discovered four miRNAs (miR-139-3p, miR-196a-5p, miR-518a-3p, and miR-671-3p) that, together with clinical parameters, can be used for non-invasive prenatal screening of placenta accreta spectrum disorders. In obstetric antiphospholipid syndrome, antiphospholipid antibody-induced up-regulation of trophoblast miR-146a-3p is mediated by Toll-like receptor 4, and miR-146a-3p in turn drives the cells to secrete interleukin-8 by activating the RNA sensor, Toll-like receptor 8 [148].

4. Long Non-Coding RNAs in Placenta

The involvement of lncRNAs in the development and function of trophoblast cells and the human placenta has been reviewed by McAninch et al. [149]. Later, a study characterized the lncRNA expression profile in human term placenta and detected the expression of 4463 isoforms from 2899 annotated lncRNA loci, plus 990 putative lncRNA transcripts from 607 intergenic regions [150]. Interestingly, the antisense promoter region of L1PA2, a LINE-1 subfamily, appears to act as a promoter for lncRNAs with placenta-specific expression [151].
The Igf2/H19 gene cluster appears to be the most intensively investigated (reviewed by Nordin et al. [152]). H19 large intergenic ncRNA is not only the most prominent lncRNA in the placenta, but also one of the most highly abundant and conserved transcripts in mammalian development, being expressed in both embryonic and extra-embryonic cell lineages. Its expression is conserved in mice and humans [153]. Maternally expressed H19 is located approximately 130kb downstream of Insulin Like Growth Factor 2 (IGF2) gene, and encodes for an ncRNA which downregulates cellular proliferation [154,155]. H19 is a precursor for miR-675, which targets IGF1R, and thus stalls placental growth during late gestation [156] and also has role in fetal growth restriction [157]. Thus, a certain methylation pattern of H19 exon 1 is closely related to PE and trophoblast abnormalities [158]. H19 is up-regulated in PE, reduces cell viability and promotes autophagy and invasion in trophoblast cells, along with activation of the PI3K/AKT/mTOR pathways [159]. In murine placentas obtained after in vitro fertilization and embryo culture, levels of H19 and IGF2 mRNA are altered, but embryos are phenotypically normal, potentially due to a compensatory process capable of correcting placenta dysfunction [160]. Furthermore, after in vitro fertilization in humans, placental H19 and IGF2 expression is disturbed which may be associated with a loss of imprinting on the paternal allele. H19 and IGF2 expression seem to be negatively correlated [161]. In mice, the expression of IGF2 and H19 was found to be decreased in alcohol-exposed placentas, while, conversely, the expression of H19 was significantly increased in alcohol-exposed embryos [162]. Further, lower expression levels of H19 [157] and differential DNA methylation defects of H19/IGF2 are associated with congenital growth disorders [163]. H19 alters trophoblast cell migration and invasion by regulating T β R3 in placentas with fetal growth restriction [164]. Molar tissues show significant differences in allelic distribution of IGF2 and H19 from normal placenta tissues [165]. The expression of IGF2 is significantly higher in gestational diabetes mellitus, while the expression of H19 is significantly lower in GDM [166].

Long Non-CODING RNAs in Pathologies

The potential role of lncRNAs in the pathogenesis of PE has been discussed in [167,168,169]. Li et al. [170] identified 78 lncRNAs differentially expressed in GDM and Wu et al. [171] 329 lncRNAs in placenta accreta spectrum disorders. Several lncRNAs are differentially expressed in the placenta of macrosomic fetuses, and may contribute to the pathogenesis [172]. However, specific lncRNAs have been examined in detail (see Table 3).

5. Circular RNAs in Placenta

CircRNAs exert their effects by acting as miRNA sponges. CircRNAs in the context of reproduction have been reviewed by Quan and Li [202]. Maass et al. [203] presented a map of human circular RNAs in clinically relevant tissues, including the placenta. A total of 227 circRNAs were found to be significantly up-regulated and 255 circRNAs significantly down-regulated in gestational diabetes mellitus (GDM) and play potential roles in its pathogenesis [204]. Further, circRNAs potentially involved in GDM have been described [204,205]. CircRNAs are also found differentially expressed in preeclampsia [206,207,208,209,210]. Qian et al. [210] described 143 up-regulated and 158 down-regulated circRNAs in PE placental tissues, many of them possessing miR-17 binding sites. The pathomechanism of circRNAs in PE includes sponging miRNAs [211], regulation of trophoblast cells [212], proliferation [213,214], migration [215,216], invasion [217,218,219] epithelial-mesenchymal transition [220] and angiogenesis regulation of vascular endothelial cells [221]. Some circRNA can serve as potential therapeutic targets [222] and biomarkers for PE [223,224] as they can be detected in the blood of pregnant women (see below). Dysregulation of trophoblastic circRNAs is further related with fetal growth restriction [225,226,227], fetal macrosomia [228], and recurrent spontaneous abortion [229].

6. Circulating Non-Coding RNAs in Maternal Serum/Plasma

Human serum and plasma contain various classes of RNA molecules which have considerable potential as stable and reliable, minimally invasive, easily accessible biomarkers [3,230,231]. In blood, circulating miRNAs exist in a vesicle-free form associated with ribonucleoprotein complexes [232,233,234,235] or are enclosed in extracellular vesicles [236]. Their concentration and pattern change dynamically in the placenta [50] and blood during the course of pregnancy [237].
In the blood of pregnant women, the RNA of male fetoplacental origin has been identified by detecting a Y chromosome-specific protein-coding RNA [238]. Circulating microRNAs in blood have been implicated in cell-to-cell communication and provide useful biological information about communication between mother, fetus, and placenta [237]. Their expected function is a transmission of signals from the placenta to distant organs and cells, where they might bind to specific surface receptors. The fetal contribution to the RNA pool in maternal plasma is 3.7% in early pregnancy, increasing to 11.28% in late pregnancy [239].
Non-invasive blood tests that provide information about fetal development and pregnancy pathologies have the potential to revolutionize prenatal care. Most of the circulating placenta-derived miRNAs in maternal serum have trophoblast origin and may reflect the status of the placenta. Whitehead et al. [240] discussed the potential of circulating placental RNAs to non-invasively predict pregnancy complications. Therefore, they might serve as novel biomarkers for a wide panel of pregnancy disorders such as preeclampsia, intrauterine growth restriction, and imminent abortion [3]. They can be used to predict gestational age (with comparable accuracy to ultrasound but at substantially lower cost), risk of preterm delivery [241], gynecological diseases, as well as the outcome of in vitro fertilization [242,243] and early [42] or recurrent miscarriage [244].

Free RNAs and Pathologies

The circulating lncRNAs XLOC_014172 and RP11-230G5.2 serve as a fingerprint for GDM [245] and GDM associated with the risk of macrosomia [246]. Maternal pre-pregnancy overweight, which can lead to different pregnancy complications, is associated with circulating miRNAs in early-mid pregnancy that have also been associated with adipogenesis [247]. Low vitamin B12 levels during pregnancy alter adipose-derived circulating miRNAs, which may mediate an adipogenic and insulin-resistant phenotype, leading to obesity [248]. Maternal fasting seems not to affect circulating placenta-specific transcripts [249]. Gardiner et al. [250] found 55 miRNAs in serum significantly altered through alcohol use during pregnancy. Circulating RNAs can predict infant growth deficits after prenatal alcohol intake [251].
Significantly higher levels of miRNA-200b and miRNA-429 were found in the sera of anovulatory women [252]. In the plasma of patients who later developed PE, 25 small ncRNAs have been identified which are differentially expressed, some of which indicate early-onset PE [253,254] and the severity of the disease [255]. Jung et al. [256] have found circulating RNA involved in the pathogenesis of PE in amniotic fluid. Five significantly differentially regulated circulating lncRNAs have been identified in the plasma of pregnant women with typical fetal congenital heart defects [257]. Moreover, other cell-free RNAs and circulating proteins seem to be potential biomarkers for this disease [258]. A unique circulating placental transcriptome is detectable in maternal blood in pregnancies destined to develop late-onset fetal growth restriction [259]. Carbone et al. [260] have reviewed and discussed the usefulness of circulating RNAs in diagnostics in pregnancy. See also Table 4.

7. Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-enclosed packages that ensure the stability of RNA through separation from RNases in the circulation [263]. They are formed by a variety of cell types leading to unique molecular compositions. EVs modulate vascular homeostasis, facilitate immunotolerance, transport regulatory miRNA to target cells, and may stimulate immunity to tumor cells [264,265]. The largest fraction of EVs detectable in the serum of pregnant women is derived from the syncytiotrophoblast (Figure 3) [266,267,268]. It includes exosomes, microvesicles, apoptotic bodies, and syncytial nuclear aggregates for intensive and efficient feto-maternal communication [267,269,270].
Syncytial knots, the classical term for syncytial nuclear aggregates of approximately 2 μ m diameter (macro EVs) have been detected in the human lung and have been under morphological investigation since the late 19th century [271]. During the last decade, modern methods have allowed more refined analyses of EVs. Microvesicles are 50–1000 nm in size and passively released from the syncytiotrophoblast membrane while exosomes, 30–100 nm, are actively secreted through a fusion of intracellular multivesicular bodies with the plasma membrane. Placenta-derived microvesicles and exosomes are characterized through their membrane expression of placental alkaline phosphatase (PLAP) [272]. This property can be used for quantification [2].
Syncytiotrophoblast EVs circulate through the maternal organism which enables the trophoblast to communicate with cells in distant regions of the body. Their number increases with progressing gestation [267]. Microvesicles and exosomes have different biological functions, cargos and modes of production, reviewed in [273]. The complex cargos consist of bioactive mediators, such as proteins, DNA, mRNA transcripts, miRNAs, other ncRNA, and lipids [270]. Numerous studies have investigated the EV composition (reviewed for example by Chamley et al. [274] and Tong et al. [267]), but the exact mechanisms of interaction with cells are widely unknown. Exosomes secreted by the blastocyst seem to influence the gene expression and receptivity of endometrial cells to prepare and control implantation [275]. Further reviews about EVs during pregnancy can be found [276,277].

EVs in Pregnancy Pathologies

Syncytiotrophoblast EVs contribute to maternal tolerance towards the fetus, and their dysregulation may lead to pathologies such as PE [19]. Throughout pregnancy, in presymptomatic women who develop PE, the concentration of total exosomes and placenta-derived exosomes in maternal plasma is significantly elevated [261]. In PE, the level of total exosomal miRNA is increased [278] and EVs have a unique miRNA profile [279]. The level of hsa-miR-210 is elevated in women with PE, and even more in the severe form [278]. Exosomal miR-15a-5p promotes the progression of PE [262]. miR-141 is abnormally expressed in PE placentas and elevated levels of miR141 can be transferred from trophoblast to immune cells by release and internalization of EVs [18,280]. However, the influence of EVs on immune cells needs further investigation (reviewed by Redman and Sargent [281] and Delorme-Axford et al. [282]). Their elevated number and altered miRNA content damage endothelial cells, resulting in endothelial dysfunction and disturbed angiogenesis (reviewed in [70,270,283,284]). The uptake of syncytiotrophoblast EVs into primary human coronary artery endothelial cells has been demonstrated, as well as the transfer of placenta-specific miRNAs into their endoplasmic reticulum and mitochondria which causes endothelial damage and oxidative and endoplasmic reticulum stress [285]. Placenta-associated exosomal miR-155 in serum from patients with PE suppresses endothelial nitric oxide synthase expression in endothelial cells [286]. In a human ex vivo placenta perfusion model of PE induced through hemoglobin, syncytiotrophoblast EVs show an altered miRNA content, in particular of the placenta specific mir-517a and mir-517b, members of the chromosome 19 miRNA cluster [287]. Further, the number of exosomes is higher in trophoblast cells cultured under 1% compared to 8% oxygen. Exosomes from trophoblast cells cultured at 8% oxygen increase endothelial cell migration, whilst exosomes cultured at 1% oxygen decrease it [288].
The extrusion of EVs by the placenta is also significantly increased in GDM [289]. Gillet et al. [290] identified 10 miRNAs up-regulated in GDM influencing trophoblast proliferation and differentiation, insulin secretion and regulation, and glucose transport. Nair et al. [291] showed that exosomal circular RNAs can affect skeletal muscle insulin sensitivity. Fallen et al. [292] identified a number of miRNAs in EVs that can be used as biomarkers for preterm labor that may reflect the pathological changes of the placenta. Decidual macrophage-derived miR-153-3p, as a regulator of trophoblast functions, is involved in recurrent spontaneous abortion [293]. Furthermore, infections, such as malaria or HIV, can lead to changes in trophoblast EV composition as recently demonstrated [19]. Trophoblastic exosomes exhibit the highest antiviral activity, containing trophoblastic miRNAs expressed from the chromosome 19 miRNA cluster (C19MC) [282,294]. It has been shown that miRNA transfected into trophoblastic cell lines are expressed at different levels into their microvesicles and exosomes. They can be transferred to T cells and influence their behavior [18]. Rice et al. [295] found that the trafficking of EVs is bi-directional: macrophage- (but not monocyte)-derived EVs induce the release of pro-inflammatory cytokines by the placenta. See also Table 4.

8. Conclusions

The human placenta, and especially trophoblast cells, express huge amounts of all classes of ncRNAs. They seem to be involved in the physiological development of the organ, but also in the differentiation and regulation of trophoblasts and other cells. NcRNAs function inside their cells of origin, but also, they seem to be actively and selectively released via different kinds of EVs. These vehicles can be incorporated by different cell types in the placenta or in distant organs where they can influence the behavior of recipient cells. The formation and uptake of EVs can be affected by pregnancy-related pathologies or independent diseases. Thereby, they may be involved in the respective pathomechanism and lead to local and distant symptoms. NcRNAs circulating in the maternal bloodstream have a great potential for non-invasive diagnostics beginning from very early pregnancy potentially leading to the development of novel early treatment strategies.

Author Contributions

Literature search, M.Ž., F.H., U.R.M. and M.M.; writing, M.Ž., F.H., U.R.M. and M.M. All authors have read and agreed to the published version of the manuscript.


We thank the DFG, German Research Foundation (MA1550/12-1, MA5082/9-1) and the Landesprogramm ProDigital (DigLeben-5575/10-9) for financial support.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Schmidt, A.; Morales-Prieto, D.M.; Pastuschek, J.; Froehlich, K.; Markert, U.R. Only humans have human placentas: Molecular differences between mice and humans. J. Reprod. Immunol. 2015, 108, 65–71. [Google Scholar] [CrossRef] [PubMed]
  2. Göhner, C.; Weber, M.; Tannetta, D.S.; Groten, T.; Plösch, T.; Faas, M.M.; Scherjon, S.A.; Schleußner, E.; Markert, U.R.; Fitzgerald, J.S. A New Enzyme-linked Sorbent Assay (ELSA) to Quantify Syncytiotrophoblast Extracellular Vesicles in Biological Fluids. Am. J. Reprod. Immunol. 2015, 73, 582–588. [Google Scholar] [CrossRef] [PubMed]
  3. Morales-Prieto, D.M.; Ospina-Prieto, S.; Schmidt, A.; Chaiwangyen, W.; Markert, U.R. Elsevier Trophoblast Research Award Lecture: Origin, evolution and future of placenta miRNAs. Placenta 2014, 35, S39–S45. [Google Scholar] [CrossRef] [PubMed]
  4. ENCODE Project Consortium; Birney, E.; Stamatoyannopoulos, J.A.; Dutta, A.; Guigó, R.; Gingeras, T.R.; Margulies, E.H.; Weng, Z.; Snyder, M.; Dermitzakis, E.T.; et al. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 2007, 447, 799–816. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 2012, 489, 57–74. [Google Scholar] [CrossRef]
  6. Gregory, T.R. Synergy between sequence and size in large-scale genomics. Nat. Rev. Genet. 2005, 6, 699–708. [Google Scholar] [CrossRef]
  7. Kung, J.T.Y.; Colognori, D.; Lee, J.T. Long Noncoding RNAs: Past, Present, and Future. Genetics 2013, 193, 651–669. [Google Scholar] [CrossRef] [Green Version]
  8. Chang, T.C.; Mendell, J.T. microRNAs in vertebrate physiology and human disease. Annu. Rev. Genom. Hum. Genet. 2007, 8, 215–239. [Google Scholar] [CrossRef] [Green Version]
  9. Esteller, M. Non-coding RNAs in human disease. Nat. Rev. Genet. 2011, 12, 861–874. [Google Scholar] [CrossRef]
  10. Cox, B.; Leavey, K.; Nosi, U.; Wong, F.; Kingdom, J. Placental transcriptome in development and pathology: Expression, function, and methods of analysis. Am. J. Obstet. Gynecol. 2015, 213, S138–S151. [Google Scholar] [CrossRef]
  11. Kalvari, I.; Nawrocki, E.P.; Ontiveros-Palacios, N.; Argasinska, J.; Lamkiewicz, K.; Marz, M.; Griffiths-Jones, S.; Toffano-Nioche, C.; Gautheret, D.; Weinberg, Z.; et al. Rfam 14: Expanded coverage of metagenomic, viral and microRNA families. Nucleic Acids Res. 2021, 49, D192–D200. [Google Scholar] [CrossRef] [PubMed]
  12. Harrow, J.; Frankish, A.; Gonzalez, J.M.; Tapanari, E.; Diekhans, M.; Kokocinski, F.; Aken, B.L.; Barrell, D.; Zadissa, A.; Searle, S.; et al. GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res. 2012, 22, 1760–1774. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Morales Prieto, D.M.; Markert, U.R. MicroRNAs in pregnancy. J. Reprod. Immunol. 2011, 88, 106–111. [Google Scholar] [CrossRef] [PubMed]
  14. Morales-Prieto, D.M.; Ospina-Prieto, S.; Chaiwangyen, W.; Schoenleben, M.; Markert, U.R. Pregnancy-associated miRNA-clusters. J. Reprod. Immunol. 2013, 97, 51–61. [Google Scholar] [CrossRef] [PubMed]
  15. He, X.; He, Y.; Xi, B.; Zheng, J.; Zeng, X.; Cai, Q.; OuYang, Y.; Wang, C.; Zhou, X.; Huang, H.; et al. LncRNAs expression in preeclampsia placenta reveals the potential role of lncRNAs contributing to preeclampsia pathogenesis. PLoS ONE 2013, 8, e81437. [Google Scholar]
  16. Zou, Y.; Jiang, Z.; Yu, X.; Sun, M.; Zhang, Y.; Zuo, Q.; Zhou, J.; Yang, N.; Han, P.; Ge, Z.; et al. Upregulation of long noncoding RNA SPRY4-IT1 modulates proliferation, migration, apoptosis, and network formation in trophoblast cells HTR-8SV/neo. PLoS ONE 2013, 8, e79598. [Google Scholar] [CrossRef] [Green Version]
  17. Wang, E.C.; Wang, A.Z. Nanoparticles and their applications in cell and molecular biology. Integr. Biol. 2014, 6, 9–26. [Google Scholar] [CrossRef] [Green Version]
  18. Ospina-Prieto, S.; Chaiwangyen, W.; Herrmann, J.; Groten, T.; Schleussner, E.; Markert, U.R.; Morales-Prieto, D.M. MicroRNA-141 is upregulated in preeclamptic placentae and regulates trophoblast invasion and intercellular communication. Transl. Res. 2016, 172, 61–72. [Google Scholar] [CrossRef]
  19. Moro, L.; Bardají, A.; Macete, E.; Barrios, D.; Morales-Prieto, D.M.; España, C.; Mandomando, I.; Sigaúque, B.; Dobaño, C.; Markert, U.R.; et al. Placental Microparticles and microRNAs in Pregnant Women with Plasmodium falciparum or HIV Infection. PLoS ONE 2016, 11, e0146361. [Google Scholar] [CrossRef]
  20. Gezer, U.; Özgür, E.; Cetinkaya, M.; Isin, M.; Dalay, N. Long non-coding RNAs with low expression levels in cells are enriched in secreted exosomes. Cell Biol. Int. 2014, 38, 1076–1079. [Google Scholar] [CrossRef]
  21. Takahashi, K.; Yan, I.K.; Wood, J.; Haga, H.; Patel, T. Involvement of extracellular vesicle long noncoding RNA (linc-VLDLR) in tumor cell responses to chemotherapy. Mol. Cancer Res. 2014, 12, 1377–1387. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Gruber, A.R.; Findeiß, S.; Washietl, S.; Hofacker, I.L.; Stadler, P.F. RNAz 2.0: Improved noncoding RNA detection. In Biocomputing 2010; World Scientific: Singapore, 2010; pp. 69–79. [Google Scholar]
  23. Rivas, E.; Eddy, S.R. Noncoding RNA gene detection using comparative sequence analysis. BMC Bioinform. 2001, 2, 1–19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Camargo, A.P.; Sourkov, V.; Pereira, G.A.G.; Carazzolle, M.F. RNAsamba: Neural network-based assessment of the protein-coding potential of RNA sequences. NAR Genom. Bioinform. 2020, 2, lqz024. [Google Scholar] [CrossRef] [Green Version]
  25. Wucher, V.; Legeai, F.; Hedan, B.; Rizk, G.; Lagoutte, L.; Leeb, T.; Jagannathan, V.; Cadieu, E.; David, A.; Lohi, H.; et al. FEELnc: A tool for long non-coding RNA annotation and its application to the dog transcriptome. Nucleic Acids Res. 2017, 45, e57. [Google Scholar] [CrossRef] [Green Version]
  26. Wang, G.; Yin, H.; Li, B.; Yu, C.; Wang, F.; Xu, X.; Cao, J.; Bao, Y.; Wang, L.; Abbasi, A.A.; et al. Characterization and identification of long non-coding RNAs based on feature relationship. Bioinformatics 2019, 35, 2949–2956. [Google Scholar] [CrossRef]
  27. Wang, L.; Park, H.J.; Dasari, S.; Wang, S.; Kocher, J.P.; Li, W. CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model. Nucleic Acids Res. 2013, 41, e74. [Google Scholar] [CrossRef]
  28. Hu, L.; Xu, Z.; Hu, B.; Lu, Z.J. COME: A robust coding potential calculation tool for lncRNA identification and characterization based on multiple features. Nucleic Acids Res. 2017, 45, e2. [Google Scholar] [CrossRef]
  29. Li, A.; Zhang, J.; Zhou, Z. PLEK: A tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme. BMC Bioinform. 2014, 15, 1–10. [Google Scholar] [CrossRef] [Green Version]
  30. Lin, M.F.; Jungreis, I.; Kellis, M. PhyloCSF: A comparative genomics method to distinguish protein coding and non-coding regions. Bioinformatics 2011, 27, i275–i282. [Google Scholar] [CrossRef] [PubMed]
  31. Sun, L.; Liu, H.; Zhang, L.; Meng, J. lncRScan-SVM: A tool for predicting long non-coding RNAs using support vector machine. PLoS ONE 2015, 10, e0139654. [Google Scholar] [CrossRef]
  32. Chen, J.; Shishkin, A.A.; Zhu, X.; Kadri, S.; Maza, I.; Guttman, M.; Hanna, J.H.; Regev, A.; Garber, M. Evolutionary analysis across mammals reveals distinct classes of long non-coding RNAs. Genome Biol. 2016, 17, 1–17. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Sun, L.; Luo, H.; Bu, D.; Zhao, G.; Yu, K.; Zhang, C.; Liu, Y.; Chen, R.; Zhao, Y. Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic Acids Res. 2013, 41, e166. [Google Scholar] [CrossRef] [PubMed]
  34. Simopoulos, C.M.; Weretilnyk, E.A.; Golding, G.B. Prediction of plant lncRNA by ensemble machine learning classifiers. BMC Genom. 2018, 19, 1–11. [Google Scholar] [CrossRef] [Green Version]
  35. Kozomara, A.; Griffiths-Jones, S. miRBase: Integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res. 2011, 39, D152–D157. [Google Scholar] [CrossRef] [Green Version]
  36. Kozomara, A.; Griffiths-Jones, S. miRBase: Annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014, 42, D68–D73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Lu, M.; Zhang, Q.; Deng, M.; Miao, J.; Guo, Y.; Gao, W.; Cui, Q. An analysis of human microRNA and disease associations. PLoS ONE 2008, 3, e3420. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Huang, Z.; Shi, J.; Gao, Y.; Cui, C.; Zhang, S.; Li, J.; Zhou, Y.; Cui, Q. HMDD v3. 0: A database for experimentally supported human microRNA–disease associations. Nucleic Acids Res. 2019, 47, D1013–D1017. [Google Scholar] [CrossRef] [Green Version]
  39. Costa, F.F. Non-coding RNAs: New players in eukaryotic biology. Gene 2005, 357, 83–94. [Google Scholar] [CrossRef]
  40. Chatzou, M.; Magis, C.; Chang, J.M.; Kemena, C.; Bussotti, G.; Erb, I.; Notredame, C. Multiple sequence alignment modeling: Methods and applications. Brief. Bioinform. 2016, 17, 1009–1023. [Google Scholar] [CrossRef] [Green Version]
  41. Lee, R.; Feinbaum, R.; Ambros, V. The C. Elegans Heterochronic Gene Lin-4 Encodes Small RNAs Antisense Complementarity to Lin-14. Cell 1993, 75, 843–854. [Google Scholar] [CrossRef]
  42. Hosseini, M.K.; Gunel, T.; Gumusoglu, E.; Benian, A.; Aydinli, K. MicroRNA expression profiling in placenta and maternal plasma in early pregnancy loss. Mol. Med. Rep. 2018, 17, 4941–4952. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Cai, M.; Kolluru, G.K.; Ahmed, A. Small Molecule, Big Prospects: MicroRNA in Pregnancy and Its Complications. J. Pregnancy 2017, 2017, 6972732. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Hayder, H.; O’Brien, J.; Nadeem, U.; Peng, C. MicroRNAs: Crucial regulators of placental development. Reproduction 2018, 155, R259–R271. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Xu, P.; Ma, Y.; Wu, H.; Wang, Y.L. Placenta-Derived MicroRNAs in the Pathophysiology of Human Pregnancy. Front. Cell Dev. Biol. 2021, 9, 540. [Google Scholar] [CrossRef]
  46. Liu, W.; Niu, Z.; Li, Q.; Pang, R.T.K.; Chiu, P.C.N.; Yeung, W.S.B. MicroRNA and Embryo Implantation. Am. J. Reprod. Immunol. 2016, 75, 263–271. [Google Scholar] [CrossRef]
  47. Liang, Y.; Ridzon, D.; Wong, L.; Chen, C. Characterization of microRNA expression profiles in normal human tissues. BMC Genom. 2007, 8, 166. [Google Scholar] [CrossRef] [Green Version]
  48. Luo, S.S.; Ishibashi, O.; Ishikawa, G.; Ishikawa, T.; Katayama, A.; Mishima, T.; Takizawa, T.; Shigihara, T.; Goto, T.; Izumi, A.; et al. Human villous trophoblasts express and secrete placenta-specific microRNAs into maternal circulation via exosomes. Biol. Reprod. 2009, 81, 717–729. [Google Scholar] [CrossRef] [Green Version]
  49. Donker, R.; Mouillet, J.; Chu, T.; Hubel, C.; Stolz, D.; Morelli, A.; Sadovsky, Y. The expression profile of C19MC microRNAs in primary human trophoblast cells and exosomes. Mol. Hum. Reprod. 2012, 18, 417–424. [Google Scholar] [CrossRef] [Green Version]
  50. Morales-Prieto, D.M.; Chaiwangyen, W.; Ospina-Prieto, S.; Schneider, U.; Herrmann, J.; Gruhn, B.; Markert, U.R. MicroRNA expression profiles of trophoblastic cells. Placenta 2012, 33, 725–734. [Google Scholar] [CrossRef]
  51. Légaré, C.; Clément, A.A.; Desgagné, V.; Thibeault, K.; White, F.; Guay, S.P.; Arsenault, B.J.; Scott, M.S.; Jacques, P.É.; Perron, P.; et al. Human plasma pregnancy-associated miRNAs and their temporal variation within the first trimester of pregnancy. Reprod. Biol. Endocrinol. 2022, 20, 1–13. [Google Scholar] [CrossRef]
  52. Morales-Prieto, D.M.; Favaro, R.R.; Markert, U.R. Placental miRNAs in feto-maternal communication mediated by extracellular vesicles. Placenta 2020, 102, 27–33. [Google Scholar] [CrossRef] [PubMed]
  53. Mouillet, J.F.; Goff, J.; Sadovsky, E.; Sun, H.; Parks, T.; Chu, T.; Sadovsky, Y. Transgenic expression of human C19MC miRNAs impacts placental morphogenesis. Placenta 2020, 101, 208–214. [Google Scholar] [CrossRef] [PubMed]
  54. Paquette, A.G.; Chu, T.; Wu, X.; Wang, K.; Price, N.D.; Sadovsky, Y. Distinct communication patterns of trophoblastic miRNA among the maternal-placental-fetal compartments. Placenta 2018, 72, 28–35. [Google Scholar] [CrossRef]
  55. Benetatos, L.; Hatzimichael, E.; Londin, E.; Vartholomatos, G.; Loher, P.; Rigoutsos, I.; Briasoulis, E. The microRNAs within the DLK1-DIO3 genomic region: Involvement in disease pathogenesis. Cell. Mol. Life Sci. 2013, 70, 795–814. [Google Scholar] [CrossRef]
  56. Hu, H.Y.; He, L.; Fominykh, K.; Yan, Z.; Guo, S.; Zhang, X.; Taylor, M.S.; Tang, L.; Li, J.; Liu, J.; et al. Evolution of the human-specific microRNA miR-941. Nat. Commun. 2012, 3, 1145. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Glazov, E.A.; McWilliam, S.; Barris, W.C.; Dalrymple, B.P. Origin, evolution, and biological role of miRNA cluster in DLK-DIO3 genomic region in placental mammals. Mol. Biol. Evol. 2008, 25, 939–948. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Weber, M.; Weise, A.; Vasheghani, F.; Göhner, C.; Fitzgerald, J.S.; Liehr, T.; Markert, U.R. Cytogenomics of six human trophoblastic cell lines. Placenta 2021, 103, 72–75. [Google Scholar] [CrossRef]
  59. Pastuschek, J.; Nonn, O.; Gutiérrez-Samudio, R.N.; Murrieta-Coxca, J.M.; Müller, J.; Sanft, J.; Huppertz, B.; Markert, U.R.; Groten, T.; Morales-Prieto, D.M. Molecular characteristics of established trophoblast-derived cell lines. Placenta 2021, 108, 122–133. [Google Scholar] [CrossRef]
  60. Noguer-Dance, M.; Abu-Amero, S.; Al-Khtib, M.; Lefèvre, A.; Coullin, P.; Moore, G.E.; Cavaillé, J. The primate-specific microRNA gene cluster (C19MC) is imprinted in the placenta. Hum. Mol. Genet. 2010, 19, 3566–3582. [Google Scholar] [CrossRef] [Green Version]
  61. Malnou, E.C.; Umlauf, D.; Mouysset, M.; Cavaillé, J. Imprinted microRNA gene clusters in the evolution, development, and functions of mammalian placenta. Front. Genet. 2019, 9, 706. [Google Scholar] [CrossRef]
  62. Flor, I.; Neumann, A.; Freter, C.; Helmke, B.M.; Langenbuch, M.; Rippe, V.; Bullerdiek, J. Abundant expression and hemimethylation of C19MC in cell cultures from placenta-derived stromal cells. Biochem. Biophys. Res. Commun. 2012, 422, 411–416. [Google Scholar] [CrossRef] [PubMed]
  63. Mong, E.F.; Yang, Y.; Akat, K.M.; Canfield, J.; VanWye, J.; Lockhart, J.; Tsibris, J.C.; Schatz, F.; Lockwood, C.J.; Tuschl, T.; et al. Chromosome 19 microRNA cluster enhances cell reprogramming by inhibiting epithelial-to-mesenchymal transition. Sci. Rep. 2020, 10, 1–13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Dumont, T.M.F.; Mouillet, J.F.; Bayer, A.; Gardner, C.L.; Klimstra, W.B.; Wolf, D.G.; Yagel, S.; Balmir, F.; Binstock, A.; Sanfilippo, J.S.; et al. The expression level of C19MC miRNAs in early pregnancy and in response to viral infection. Placenta 2017, 53, 23–29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Hromadnikova, I.; Kotlabova, K.; Ivankova, K.; Krofta, L. Expression profile of C19MC microRNAs in placental tissue of patients with preterm prelabor rupture of membranes and spontaneous preterm birth. Mol. Med. Rep. 2017, 16, 3849–3862. [Google Scholar] [CrossRef]
  66. Bayer, A.; Lennemann, N.J.; Ouyang, Y.; Sadovsky, E.; Sheridan, M.A.; Roberts, R.M.; Coyne, C.B.; Sadovsky, Y. Chromosome 19 microRNAs exert antiviral activity independent from type III interferon signaling. Placenta 2018, 61, 33–38. [Google Scholar] [CrossRef]
  67. Flor, I.; Bullerdiek, J. The dark side of a success story: MicroRNAs of the C19MC cluster in human tumours. J. Pathol. 2012, 227, 270–274. [Google Scholar] [CrossRef]
  68. Wu, S.; Aksoy, M.; Shi, J.; Houbaviy, H.B. Evolution of the miR-290–295/miR-371–373 cluster family seed repertoire. PLoS ONE 2014, 9, e108519. [Google Scholar] [CrossRef]
  69. Shah, J.A.; Khattak, S.; Rauf, M.A.; Cai, Y.; Jin, J. Potential Biomarkers of miR-371–373 Gene Cluster in Tumorigenesis. Life 2021, 11, 984. [Google Scholar] [CrossRef]
  70. Escudero, C.A.; Herlitz, K.; Troncoso, F.; Acurio, J.; Aguayo, C.; Roberts, J.M.; Truong, G.; Duncombe, G.; Rice, G.; Salomon, C. Role of extracellular vesicles and microRNAs on dysfunctional angiogenesis during preeclamptic pregnancies. Front. Physiol. 2016, 7, 98. [Google Scholar] [CrossRef] [Green Version]
  71. Dai, X.; Cai, Y. Down-regulation of microRNA let-7d inhibits the proliferation and invasion of trophoblast cells in preeclampsia. J. Cell Biochem. 2018, 119, 1141–1151. [Google Scholar] [CrossRef]
  72. Lu, T.M.; Lu, W.; Zhao, L.J. MicroRNA-137 Affects Proliferation and Migration of Placenta Trophoblast Cells in Preeclampsia by Targeting ERRα. Reprod. Sci. 2017, 24, 85–96. [Google Scholar] [CrossRef] [PubMed]
  73. Wang, F.; Yan, J. MicroRNA-454 is involved in regulating trophoblast cell proliferation, apoptosis, and invasion in preeclampsia by modulating the expression of ephrin receptor B4. Biomed. Pharmacother. 2018, 107, 746–753. [Google Scholar] [CrossRef]
  74. Wu, L.; Song, W.Y.; Xie, Y.; Hu, L.L.; Hou, X.M.; Wang, R.; Gao, Y.; Zhang, J.N.; Zhang, L.; Li, W.W.; et al. miR-181a-5p suppresses invasion and migration of HTR-8/SVneo cells by directly targeting IGF2BP2. Cell Death Dis. 2018, 9, 16. [Google Scholar] [CrossRef]
  75. Gao, Y.; She, R.; Wang, Q.; Li, Y.; Zhang, H. Up-regulation of miR-299 suppressed the invasion and migration of HTR-8/SVneo trophoblast cells partly via targeting HDAC2 in pre-eclampsia. Biomed. Pharmacother. 2018, 97, 1222–1228. [Google Scholar] [CrossRef] [PubMed]
  76. Pan, Q.; Niu, H.; Cheng, L.; Li, X.; Zhang, Q.; Ning, Y. Invasion of trophoblast cell lines is inhibited by miR-93 via MMP-2. Placenta 2017, 53, 48–53. [Google Scholar] [CrossRef] [PubMed]
  77. Jiang, L.; Long, A.; Tan, L.; Hong, M.; Wu, J.; Cai, L.; Li, Q. Elevated microRNA-520g in pre-eclampsia inhibits migration and invasion of trophoblasts. Placenta 2017, 51, 70–75. [Google Scholar] [CrossRef]
  78. Niu, Z.R.; Han, T.; Sun, X.L.; Luan, L.X.; Gou, W.L.; Zhu, X.M. MicroRNA-30a-3p is overexpressed in the placentas of patients with preeclampsia and affects trophoblast invasion and apoptosis by its effects on IGF-1. Am. J. Obstet. Gynecol. 2018, 218, 249.e1–249.e12. [Google Scholar] [CrossRef]
  79. Zou, A.X.; Chen, B.; Li, Q.X.; Liang, Y.C. MiR-134 inhibits infiltration of trophoblast cells in placenta of patients with preeclampsia by decreasing ITGB1 expression. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 2199–2206. [Google Scholar] [CrossRef]
  80. Gao, T.; Deng, M.; Wang, Q. miRNA-320a inhibits trophoblast cell invasion by targeting estrogen-related receptor-gamma. J. Obstet. Gynaecol. Res. 2018, 44, 756–763. [Google Scholar] [CrossRef]
  81. Fang, M.; Du, H.; Han, B.; Xia, G.; Shi, X.; Zhang, F.; Fu, Q.; Zhang, T. Hypoxia-inducible microRNA-218 inhibits trophoblast invasion by targeting LASP1: Implications for preeclampsia development. Int. J. Biochem. Cell Biol. 2017, 87, 95–103. [Google Scholar] [CrossRef]
  82. Wu, H.; Wang, H.; Liu, M.; Bai, Y.; Li, Y.X.; Ji, L.; Peng, C.; Yu, Y.; Wang, Y.L. MiR-195 participates in the placental disorder of preeclampsia via targeting activin receptor type-2B in trophoblastic cells. J. Hypertens. 2016, 34, 1371–1379. [Google Scholar] [CrossRef] [PubMed]
  83. Yang, M.; Chen, Y.; Chen, L.; Wang, K.; Pan, T.; Liu, X.; Xu, W. miR-15b-AGO2 play a critical role in HTR8/SVneo invasion and in a model of angiogenesis defects related to inflammation. Placenta 2016, 41, 62–73. [Google Scholar] [CrossRef] [PubMed]
  84. Zhang, M.; Li, P.; Mao, X.; Zhang, H. Regulatory mechanism of miR-525-5p in over-invasion of trophoblast. J. Obstet. Gynaecol. Res. 2021, 47, 679–688. [Google Scholar] [CrossRef] [PubMed]
  85. Dong, X.; Yang, L.; Wang, H. miR-520 promotes DNA-damage-induced trophoblast cell apoptosis by targeting PARP1 in recurrent spontaneous abortion (RSA). Gynecol. Endocrinol. 2017, 33, 274–278. [Google Scholar] [CrossRef] [PubMed]
  86. Ding, G.C.; Chen, M.; Wang, Y.X.; Rui, C.; Xu, W.; Ding, H.J.; Shi, Z.H. MicroRNA-128a-induced apoptosis in HTR-8/SVneo trophoblast cells contributes to pre-eclampsia. Biomed. Pharmacother. 2016, 81, 63–70. [Google Scholar] [CrossRef]
  87. Guo, M.; Zhao, X.; Yuan, X.; Li, P. Elevated microRNA-34a contributes to trophoblast cell apoptosis in preeclampsia by targeting BCL-2. J. Hum. Hypertens. 2017, 31, 815–820. [Google Scholar] [CrossRef]
  88. Zhang, Y.; Pan, X.; Yu, X.; Li, L.; Qu, H.; Li, S. MicroRNA-590-3p inhibits trophoblast-dependent maternal spiral artery remodeling by repressing low-density lipoprotein receptor-related protein 6. Mol. Genet. Genom. Med. 2018, 6, 1124–1133. [Google Scholar] [CrossRef] [Green Version]
  89. Brkić, J.; Dunk, C.; O’Brien, J.; Fu, G.; Nadeem, L.; Wang, Y.l.; Rosman, D.; Salem, M.; Shynlova, O.; Yougbaré, I.; et al. MicroRNA-218-5p promotes endovascular trophoblast differentiation and spiral artery remodeling. Mol. Ther. 2018, 26, 2189–2205. [Google Scholar] [CrossRef] [Green Version]
  90. Hayder, H.; Fu, G.; Nadeem, L.; O’Brien, J.A.; Lye, S.J.; Peng, C. Overexpression of miR-210-3p Impairs Extravillous Trophoblast Functions Associated with Uterine Spiral Artery Remodeling. Int. J. Mol. Sci. 2021, 22, 3961. [Google Scholar] [CrossRef]
  91. Bounds, K.R.; Chiasson, V.L.; Pan, L.J.; Gupta, S.; Chatterjee, P. MicroRNAs: New Players in the Pathobiology of Preeclampsia. Front. Cardiovasc. Med. 2017, 4, 60. [Google Scholar] [CrossRef] [Green Version]
  92. Hemmatzadeh, M.; Shomali, N.; Yousefzadeh, Y.; Mohammadi, H.; Ghasemzadeh, A.; Yousefi, M. MicroRNAs: Small molecules with a large impact on pre-eclampsia. J. Cell. Physiol. 2020, 235, 3235–3248. [Google Scholar] [CrossRef] [PubMed]
  93. Jairajpuri, D.S.; Almawi, W.Y. MicroRNA expression pattern in pre-eclampsia (Review). Mol. Med. Rep. 2016, 13, 2351–2358. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Lv, Y.; Lu, C.; Ji, X.; Miao, Z.; Long, W.; Ding, H.; Lv, M. Roles of microRNAs in preeclampsia. J. Cell. Physiol. 2019, 234, 1052–1061. [Google Scholar] [CrossRef] [PubMed]
  95. Skalis, G.; Katsi, V.; Miliou, A.; Georgiopoulos, G.; Papazachou, O.; Vamvakou, G.; Nihoyannopoulos, P.; Tousoulis, D.; Makris, T. MicroRNAs in preeclampsia. MicroRNA 2019, 8, 28–35. [Google Scholar] [CrossRef]
  96. Lagana, A.S.; Vitale, S.G.; Sapia, F.; Valenti, G.; Corrado, F.; Padula, F.; Rapisarda, A.M.C.; D’Anna, R. miRNA expression for early diagnosis of preeclampsia onset: Hope or hype? J. Matern. Fetal Neonatal Med. 2018, 31, 817–821. [Google Scholar] [CrossRef]
  97. Hornakova, A.; Kolkova, Z.; Holubekova, V.; Loderer, D.; Lasabova, Z.; Biringer, K.; Halasova, E. Diagnostic Potential of MicroRNAs as Biomarkers in the Detection of Preeclampsia. Genet. Test. Mol. Biomark. 2020, 24, 321–327. [Google Scholar] [CrossRef] [PubMed]
  98. Wang, W.; Feng, L.; Zhang, H.; Hachy, S.; Satohisa, S.; Laurent, L.C.; Parast, M.; Zheng, J.; Chen, D.b. Preeclampsia up-regulates angiogenesis-associated microRNA (ie., miR-17,-20a, and-20b) that target ephrin-B2 and EPHB4 in human placenta. J. Clin. Endocrinol. Metab. 2012, 97, E1051–E1059. [Google Scholar] [CrossRef] [Green Version]
  99. Zhang, S.; Kan, X.; Liu, P.; Yin, L.; Li, Q.; Xu, H. MiR-20b is implicated in preeclampsia progression via the regulation of myeloid cell leukemin-1. J. Biol. Regul. Homeost. Agents 2020, 34, 1709–1717. [Google Scholar] [PubMed]
  100. Shao, X.; Liu, Y.; Liu, M.; Wang, Y.; Yan, L.; Wang, H.; Ma, L.; Li, Y.X.; Zhao, Y.; Wang, Y.L. Testosterone Represses Estrogen Signaling by Upregulating miR-22: A Mechanism for Imbalanced Steroid Hormone Production in Preeclampsia. Hypertension 2017, 69, 721–730. [Google Scholar] [CrossRef]
  101. Rezaei, M.; Eskandari, F.; Mohammadpour-Gharehbagh, A.; Harati-Sadegh, M.; Teimoori, B.; Salimi, S. Hypomethylation of the miRNA-34a gene promoter is associated with Severe Preeclampsia. Clin. Exp. Hypertens. 2018, 41, 118–122. [Google Scholar] [CrossRef]
  102. Liu, J.; Zhang, L.; Zhang, F.; Luan, T.; Yin, Z.; Rui, C.; Ding, H. Influence of miR-34a on preeclampsia through the Notch signaling pathway. Eur. Rev. Med. Pharmacol. Sci. 2019, 23, 923–931. [Google Scholar] [PubMed]
  103. Xue, F.; Yang, J.; Li, Q.; Zhou, H. Down-regulation of microRNA-34a-5p promotes trophoblast cell migration and invasion via targetting Smad4. Biosci. Rep. 2019, 39, BSR20181631. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Huang, X.; Wu, L.; Zhang, G.; Tang, R.; Zhou, X. Elevated MicroRNA-181a-5p contributes to trophoblast dysfunction and preeclampsia. Reprod. Sci. 2019, 26, 1121–1129. [Google Scholar] [CrossRef] [PubMed]
  105. Wu, D.; Shi, L.; Hong, L.; Chen, X.; Cen, H. MiR-135a-5p promotes the migration and invasion of trophoblast cells in preeclampsia by targeting β-TrCP. Placenta 2020, 99, 63–69. [Google Scholar] [CrossRef]
  106. Wu, D.; Chen, X.; Wang, L.; Chen, F.; Cen, H.; Shi, L. Hypoxia-induced microRNA-141 regulates trophoblast apoptosis, invasion, and vascularization by blocking CXCL12β/CXCR2/4 signal transduction. Biomed. Pharmacother. 2019, 116, 108836. [Google Scholar] [CrossRef]
  107. Wang, Y.; Cheng, K.; Zhou, W.; Liu, H.; Yang, T.; Hou, P.; Li, X. miR-141-5p regulate ATF2 via effecting MAPK1/ERK2 signaling to promote preeclampsia. Biomed. Pharmacother. 2019, 115, 108953. [Google Scholar] [CrossRef]
  108. Xiao, J.; Tao, T.; Yin, Y.; Zhao, L.; Yang, L.; Hu, L. miR-144 may regulate the proliferation, migration and invasion of trophoblastic cells through targeting PTEN in preeclampsia. Biomed. Pharmacother. 2017, 94, 341–353. [Google Scholar] [CrossRef]
  109. Hu, S.; Li, J.; Tong, M.; Li, Q.; Chen, Y.; Lu, H.; Wang, Y.; Min, L. MicroRNA-144-3p may participate in the pathogenesis of preeclampsia by targeting Cox-2. Mol. Med. Rep. 2019, 19, 4655–4662. [Google Scholar] [CrossRef] [Green Version]
  110. Gunel, T.; Kamali, N.; Hosseini, M.K.; Gumusoglu, E.; Benian, A.; Aydinli, K. Regulatory effect of miR-195 in the placental dysfunction of preeclampsia. J. Matern. Fetal Neonatal Med. 2020, 33, 901–908. [Google Scholar] [CrossRef]
  111. Hu, T.X.; Wang, G.; Guo, X.J.; Sun, Q.Q.; He, P.; Gu, H.; Huang, Y.; Gao, L.; Ni, X. MiR 20a,-20b and -200c are involved in hydrogen sulfide stimulation of VEGF production in human placental trophoblasts. Placenta 2016, 39, 101–110. [Google Scholar] [CrossRef]
  112. Liu, F.; Wu, K.; Wu, W.; Chen, Y.; Wu, H.; Wang, H.; Zhang, W. miR-203 contributes to pre-eclampsia via inhibition of VEGFA expression. Mol. Med. Rep. 2018, 17, 5627–5634. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Xie, N.; Jia, Z.; Li, L. miR-320a upregulation contributes to the development of preeclampsia by inhibiting the growth and invasion of trophoblast cells by targeting interleukin 4. Mol. Med. Rep. 2019, 20, 3256–3264. [Google Scholar] [CrossRef] [PubMed]
  114. Shi, Z.; She, K.; Li, H.; Yuan, X.; Han, X.; Wang, Y. MicroRNA-454 contributes to sustaining the proliferation and invasion of trophoblast cells through inhibiting Nodal/ALK7 signaling in pre-eclampsia. Chem. Biol. Interact. 2019, 298, 8–14. [Google Scholar] [CrossRef] [PubMed]
  115. Liu, Z.; Zhao, X.; Shan, H.; Gao, H.; Wang, P. microRNA-520c-3p suppresses NLRP3 inflammasome activation and inflammatory cascade in preeclampsia by downregulating NLRP3. Inflamm. Res. 2019, 68, 643–654. [Google Scholar] [CrossRef] [PubMed]
  116. Gao, X.; Li, H.; Wei, J.X. MiR-4421 regulates the progression of preeclampsia by regulating CYP11B2. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 1533–1540. [Google Scholar] [CrossRef]
  117. Licini, C.; Avellini, C.; Picchiassi, E.; Mensà, E.; Fantone, S.; Ramini, D.; Tersigni, C.; Tossetta, G.; Castellucci, C.; Tarquini, F.; et al. Pre-eclampsia predictive ability of maternal miR-125b: A clinical and experimental study. Transl. Res. 2021, 228, 13–27. [Google Scholar] [CrossRef]
  118. Poirier, C.; Desgagné, V.; Guérin, R.; Bouchard, L. MicroRNAs in Pregnancy and Gestational Diabetes Mellitus: Emerging Role in Maternal Metabolic Regulation. Curr. Diab. Rep. 2017, 17, 35. [Google Scholar] [CrossRef]
  119. Iljas, J.D.; Guanzon, D.; Elfeky, O.; Rice, G.E.; Salomon, C. Review: Bio-compartmentalization of microRNAs in exosomes during gestational diabetes mellitus. Placenta 2017, 54, 76–82. [Google Scholar] [CrossRef] [Green Version]
  120. Muralimanoharan, S.; Maloyan, A.; Myatt, L. Mitochondrial function and glucose metabolism in the placenta with gestational diabetes mellitus: Role of miR-143. Clin. Sci. 2016, 130, 931–941. [Google Scholar] [CrossRef] [Green Version]
  121. Cao, J.L.; Zhang, L.; Li, J.; Tian, S.; Lv, X.D.; Wang, X.Q.; Su, X.; Li, Y.; Hu, Y.; Ma, X.; et al. Up-regulation of miR-98 and unraveling regulatory mechanisms in gestational diabetes mellitus. Sci. Rep. 2016, 6, 32268. [Google Scholar] [CrossRef] [Green Version]
  122. Peng, H.Y.; Li, M.Q.; Li, H.P. miR-137 restricts the viability and migration of HTR-8/SVneo cells by downregulating FNDC5 in gestational diabetes mellitus. Curr. Mol. Med. 2019, 19, 494–505. [Google Scholar] [CrossRef] [PubMed]
  123. Sun, D.G.; Tian, S.; Zhang, L.; Hu, Y.; Guan, C.Y.; Ma, X.; Xia, H.F. The miRNA-29b is downregulated in placenta during gestational diabetes mellitus and may alter placenta development by regulating trophoblast migration and invasion through a HIF3A-dependent mechanism. Front. Endocrinol. 2020, 11, 169. [Google Scholar] [CrossRef] [PubMed]
  124. Zhang, L.; Li, K.; Tian, S.; Wang, X.Q.; Li, J.H.; Dong, Y.C.; Xia, H.F.; Ma, X. Down-regulation of microRNA-30d-5p is associated with gestational diabetes mellitus by targeting RAB8A. J. Diabetes Its Complicat. 2021, 35, 107959. [Google Scholar] [CrossRef]
  125. Wen, J.; Bai, X. miR-520h Inhibits cell survival by targeting mTOR in gestational diabetes mellitus. Acta Biochim. Pol. 2021, 68, 65–70. [Google Scholar] [CrossRef] [PubMed]
  126. Yu, X.; Liu, Z.; Fang, J.; Qi, H. miR-96-5p: A potential diagnostic marker for gestational diabetes mellitus. Medicine 2021, 100, e25808. [Google Scholar] [CrossRef]
  127. Zhou, X.; Xiang, C.; Zheng, X. miR-132 serves as a diagnostic biomarker in gestational diabetes mellitus and its regulatory effect on trophoblast cell viability. Diagn. Pathol. 2019, 14, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  128. Zhao, W.; Shen, W.W.; Cao, X.M.; Ding, W.Y.; Yan, L.P.; Gao, L.J.; Li, X.L.; Zhong, T.Y. Novel mechanism of miRNA-365-regulated trophoblast apoptosis in recurrent miscarriage. J. Cell. Mol. Med. 2017, 21, 2412–2425. [Google Scholar] [CrossRef] [Green Version]
  129. Liu, H.N.; Tang, X.M.; Wang, X.Q.; Gao, J.; Li, N.; Wang, Y.Y.; Xia, H.F. MiR-93 inhibits trophoblast cell proliferation and promotes cell apoptosis by targeting BCL2L2 in recurrent spontaneous abortion. Reprod. Sci. 2020, 27, 152–162. [Google Scholar] [CrossRef]
  130. Ding, J.; Cheng, Y.; Zhang, Y.; Liao, S.; Yin, T.; Yang, J. The miR-27a-3p/USP25 axis participates in the pathogenesis of recurrent miscarriage by inhibiting trophoblast migration and invasion. J. Cell. Physiol. 2019, 234, 19951–19963. [Google Scholar] [CrossRef] [PubMed]
  131. Tang, H.; Pan, L.; Xiong, Y.; Wang, L.; Cui, Y.; Liu, J.; Tang, L. Down-regulation of the Sp1 transcription factor by an increase of microRNA-4497 in human placenta is associated with early recurrent miscarriage. Reprod. Biol. Endocrinol. 2021, 19, 1–12. [Google Scholar] [CrossRef]
  132. Du, E.; Cao, Y.; Feng, C.; Lu, J.; Yang, H.; Zhang, Y. The Possible Involvement of miR-37la-5p Regulating XIAP in the Pathogenesis of Recurrent Pregnancy Loss. Reprod. Sci. 2019, 26, 1468–1475. [Google Scholar] [CrossRef] [PubMed]
  133. Hong, L.; Yu, T.; Xu, H.; Hou, N.; Cheng, Q.; Lai, L.; Wang, Q.; Sheng, J.; Huang, H. Down-regulation of miR-378a-3p induces decidual cell apoptosis: A possible mechanism for early pregnancy loss. Hum. Reprod. 2018, 33, 11–22. [Google Scholar] [CrossRef] [PubMed]
  134. Ye, H.X.; Li, L.; Dong, Y.J.; Li, P.H.; Su, Q.; Guo, Y.H.; Lu, Y.R.; Zhong, Y.; Jia, Y.; Cheng, J.Q. miR-146a-5p improves the decidual cytokine microenvironment by regulating the toll-like receptor signaling pathway in unexplained spontaneous abortion. Int. Immunopharmacol. 2020, 89, 107066. [Google Scholar] [CrossRef] [PubMed]
  135. Zhao, L.; Li, J.; Huang, S. Patients with unexplained recurrent spontaneous abortion show decreased levels of microrna-146a-5p in the deciduae. Ann. Clin. Lab. Sci. 2018, 48, 177–182. [Google Scholar]
  136. Romero-Ruiz, A.; Avendaño, M.S.; Dominguez, F.; Lozoya, T.; Molina-Abril, H.; Sangiao-Alvarellos, S.; Gurrea, M.; Lara-Chica, M.; Fernandez-Sanchez, M.; Torres-Jimenez, E.; et al. Deregulation of miR-324/KISS1/kisspeptin in early ectopic pregnancy: Mechanistic findings with clinical and diagnostic implications. Am. J. Obstet. Gynecol. 2019, 220, 480.e1–480.e17. [Google Scholar] [CrossRef] [Green Version]
  137. Svobodová, I.; Korabečná, M.; Calda, P.; Břešťák, M.; Pazourková, E.; Pospíšilová, V.; Krkavcová, M.; Novotná, M.; Hořínek, A. Differentially expressed miRNAs in trisomy 21 placentas. Prenat. Diagn. 2016, 36, 775–784. [Google Scholar] [CrossRef]
  138. Rahman, M.L.; Liang, L.; Valeri, L.; Su, L.; Zhu, Z.; Gao, S.; Mostofa, G.; Qamruzzaman, Q.; Hauser, R.; Baccarelli, A.; et al. Regulation of birthweight by placenta-derived miRNAs: Evidence from an arsenic-exposed birth cohort in Bangladesh. Epigenetics 2018, 13, 573–590. [Google Scholar] [CrossRef]
  139. Zhang, J.T.; Cai, Q.Y.; Ji, S.S.; Zhang, H.X.; Wang, Y.H.; Yan, H.T.; Yang, X.J. Decreased miR-143 and increased miR-21 placental expression levels are associated with macrosomia. Mol. Med. Rep. 2016, 13, 3273–3280. [Google Scholar] [CrossRef]
  140. Kennedy, E.M.; Hermetz, K.; Burt, A.; Everson, T.M.; Deyssenroth, M.; Hao, K.; Chen, J.; Karagas, M.R.; Pei, D.; Koestler, D.C.; et al. Placental microRNA expression associates with birthweight through control of adipokines: Results from two independent cohorts. Epigenetics 2021, 16, 770–782. [Google Scholar] [CrossRef]
  141. Tagliaferri, S.; Cepparulo, P.; Vinciguerra, A.; Campanile, M.; Esposito, G.; Maruotti, G.M.; Zullo, F.; Annunziato, L.; Pignataro, G. miR-16-5p, miR-103-3p, and miR-27b-3p as Early Peripheral Biomarkers of Fetal Growth Restriction. Front. Pediatr. 2021, 9, 156. [Google Scholar] [CrossRef]
  142. Carreras-Badosa, G.; Bonmatí, A.; Ortega, F.J.; Mercader, J.M.; Guindo-Martínez, M.; Torrents, D.; Prats-Puig, A.; Martinez-Calcerrada, J.M.; de Zegher, F.; Ibáñez, L.; et al. Dysregulation of Placental miRNA in Maternal Obesity Is Associated with Pre- and Postnatal Growth. J. Clin. Endocrinol. Metab. 2017, 102, 2584–2594. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  143. Qin, X.; Ni, X.; Mao, X.; Ying, H.; Du, Q. Cholestatic pregnancy is associated with reduced VCAM1 expression in vascular endothelial cell of placenta. Reprod. Toxicol. 2017, 74, 23–31. [Google Scholar] [CrossRef] [PubMed]
  144. Gu, Y.; Bian, Y.; Xu, X.; Wang, X.; Zuo, C.; Meng, J.; Li, H.; Zhao, S.; Ning, Y.; Cao, Y.; et al. Downregulation of miR-29a/b/c in placenta accreta inhibits apoptosis of implantation site intermediate trophoblast cells by targeting MCL1. Placenta 2016, 48, 13–19. [Google Scholar] [CrossRef] [PubMed]
  145. Gu, Y.; Meng, J.; Zuo, C.; Wang, S.; Li, H.; Zhao, S.; Huang, T.; Wang, X.; Yan, J. Downregulation of MicroRNA-125a in Placenta Accreta Spectrum Disorders Contributes Antiapoptosis of Implantation Site Intermediate Trophoblasts by Targeting MCLI. Reprod. Sci. 2019, 26, 1582–1589. [Google Scholar] [CrossRef] [PubMed]
  146. Yang, T.; Li, N.; Hou, R.; Qiao, C.; Liu, C. Development and validation of a four-microRNA signature for placenta accreta spectrum: An integrated competing endogenous RNA network analysis. Ann. Transl. Med. 2020, 8, 919. [Google Scholar] [CrossRef]
  147. Chen, S.; Pang, D.; Li, Y.; Zhou, J.; Liu, Y.; Yang, S.; Liang, K.; Yu, B. Serum miRNA biomarker discovery for placenta accreta spectrum. Placenta 2020, 101, 215–220. [Google Scholar] [CrossRef]
  148. Gysler, S.M.; Mulla, M.J.; Guerra, M.; Brosens, J.J.; Salmon, J.E.; Chamley, L.W.; Abrahams, V.M. Antiphospholipid antibody-induced miR-146a-3p drives trophoblast interleukin-8 secretion through activation of Toll-like receptor 8. Mol. Hum. Reprod. 2016, 22, 465–474. [Google Scholar] [CrossRef] [Green Version]
  149. McAninch, D.; Roberts, C.T.; Bianco-Miotto, T. Mechanistic Insight into Long Noncoding RNAs and the Placenta. Int. J. Mol. Sci. 2017, 18, 1371. [Google Scholar] [CrossRef] [Green Version]
  150. Majewska, M.; Lipka, A.; Paukszto, L.; Jastrzebski, J.P.; Gowkielewicz, M.; Jozwik, M.; Majewski, M.K. Preliminary [RNA]-Seq Analysis of Long Non-Coding [RNA]s Expressed in Human Term Placenta. Int. J. Mol. Sci. 2018, 19, 1894. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  151. Chishima, T.; Iwakiri, J.; Hamada, M. Identification of Transposable Elements Contributing to Tissue-Specific Expression of Long Non-Coding RNAs. Genes 2018, 9, 23. [Google Scholar] [CrossRef] [Green Version]
  152. Nordin, M.; Bergman, D.; Halje, M.; Engström, W.; Ward, A. Epigenetic regulation of the Igf2/H19 gene cluster. Cell Prolif. 2014, 47, 189–199. [Google Scholar] [CrossRef]
  153. Yu, L.; Chen, M.; Zhao, D.; Yi, P.; Lu, L.; Han, J.; Zheng, X.; Zhou, Y.; Li, L. The H19 gene imprinting in normal pregnancy and pre-eclampsia. Placenta 2009, 30, 443–447. [Google Scholar] [CrossRef] [PubMed]
  154. Gabory, A.; Ripoche, M.A.; Yoshimizu, T.; Dandolo, L. The H19 gene: Regulation and function of a non-coding RNA. Cytogenet. Genome Res. 2006, 113, 188–193. [Google Scholar] [CrossRef] [PubMed]
  155. Gabory, A.; Jammes, H.; Dandolo, L. The H19 locus: Role of an imprinted non-coding RNA in growth and development. Bioessays 2010, 32, 473–480. [Google Scholar] [CrossRef] [PubMed]
  156. Keniry, A.; Oxley, D.; Monnier, P.; Kyba, M.; Dandolo, L.; Smits, G.; Reik, W. The H19 lincRNA is a developmental reservoir of miR-675 that suppresses growth and Igf1r. Nat. Cell Biol. 2012, 14, 659–665. [Google Scholar] [CrossRef]
  157. Tsunoda, Y.; Kudo, M.; Wada, R.; Ishino, K.; Kure, S.; Sakatani, T.; Takeshita, T.; Naito, Z. Expression level of long noncoding RNA H19 of normotensive placentas in late pregnancy relates to the fetal growth restriction. J. Obstet. Gynaecol. Res. 2020, 46, 1025–1034. [Google Scholar] [CrossRef]
  158. Lu, L.; Hou, Z.; Li, L.; Yang, Y.; Wang, X.; Zhang, B.; Ren, M.; Zhao, D.; Miao, Z.; Yu, L.; et al. Methylation pattern of H19 exon 1 is closely related to preeclampsia and trophoblast abnormalities. Int. J. Mol. Med. 2014, 34, 765–771. [Google Scholar] [CrossRef] [Green Version]
  159. Xu, J.; Xia, Y.; Zhang, H.; Guo, H.; Feng, K.; Zhang, C. Overexpression of long non-coding RNA H19 promotes invasion and autophagy via the PI3K/AKT/mTOR pathways in trophoblast cells. Biomed. Pharmacother. 2018, 101, 691–697. [Google Scholar] [CrossRef]
  160. Fauque, P.; Ripoche, M.A.; Tost, J.; Journot, L.; Gabory, A.; Busato, F.; Le Digarcher, A.; Mondon, F.; Gut, I.; Jouannet, P.; et al. Modulation of imprinted gene network in placenta results in normal development of in vitro manipulated mouse embryos. Hum. Mol. Genet. 2010, 19, 1779–1790. [Google Scholar] [CrossRef] [Green Version]
  161. Sakian, S.; Louie, K.; Wong, E.C.; Havelock, J.; Kashyap, S.; Rowe, T.; Taylor, B.; Ma, S. Altered gene expression of H19 and IGF2 in placentas from ART pregnancies. Placenta 2015, 36, 1100–1105. [Google Scholar] [CrossRef]
  162. Marjonen, H.; Toivonen, M.; Lahti, L.; Kaminen-Ahola, N. Early prenatal alcohol exposure alters imprinted gene expression in placenta and embryo in a mouse model. PLoS ONE 2018, 13, e0197461. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Freschi, A.; Hur, S.K.; Valente, F.M.; Ideraabdullah, F.Y.; Sparago, A.; Gentile, M.T.; Oneglia, A.; Di Nucci, D.; Colucci-D’Amato, L.; Thorvaldsen, J.L.; et al. Tissue-specific and mosaic imprinting defects underlie opposite congenital growth disorders in mice. PLoS Genet. 2018, 14, e1007243. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  164. Zuckerwise, L.; Li, J.; Lu, L.; Men, Y.; Geng, T.; Buhimschi, C.S.; Buhimschi, I.A.; Bukowski, R.; Guller, S.; Paidas, M.; et al. H19 long noncoding RNA alters trophoblast cell migration and invasion by regulating TβR3 in placentae with fetal growth restriction. Oncotarget 2016, 7, 38398–38407. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Piyamongkol, W.; Suprasert, P. Allelic Characterization of IGF2 and H19 Gene Polymorphisms in Molar Tissues. Asian Pac. J. Cancer Prev. 2016, 17, 4405–4408. [Google Scholar] [PubMed]
  166. Su, R.; Wang, C.; Feng, H.; Lin, L.; Liu, X.; Wei, Y.; Yang, H. Alteration in Expression and Methylation of IGF2/H19 in Placenta and Umbilical Cord Blood Are Associated with Macrosomia Exposed to Intrauterine Hyperglycemia. PLoS ONE 2016, 11, e0148399. [Google Scholar] [CrossRef] [PubMed]
  167. Song, X.; Luo, X.; Gao, Q.; Wang, Y.; Gao, Q.; Long, W. Dysregulation of LncRNAs in Placenta and Pathogenesis of Preeclampsia. Curr. Drug Targets 2017, 18, 1165–1170. [Google Scholar] [CrossRef]
  168. Moradi, M.T.; Rahimi, Z.; Vaisi-Raygani, A. New insight into the role of long non-coding RNAs in the pathogenesis of preeclampsia. Hypertens. Pregnancy 2019, 38, 41–51. [Google Scholar] [CrossRef]
  169. Yang, X.; Meng, T. Long noncoding RNA in preeclampsia: Transcriptional noise or innovative indicators? BioMed Res. Int. 2019, 2019, 5437621. [Google Scholar] [CrossRef]
  170. Li, T.; Hu, D.; Gong, Y. Identification of potential lncRNAs and co-expressed mRNAs in gestational diabetes mellitus by RNA sequencing. J. Matern. Fetal Neonatal Med. 2021, 1–15. [Google Scholar] [CrossRef]
  171. Wu, K.; Liu, F.; Wu, W.; Chen, Y.; Wu, H.; Zhang, W. Long non-coding RNA HOX transcript antisense RNA (HOTAIR) suppresses the angiogenesis of human placentation by inhibiting vascular endothelial growth factor A expression. Reprod. Fertil. Dev. 2019, 31, 377–385. [Google Scholar] [CrossRef]
  172. Song, G.Y.; Na, Q.; Wang, D.; Qiao, C. Microarray expression profile of lncRNAs and mRNAs in the placenta of non-diabetic macrosomia. J. Dev. Orig. Health Dis. 2018, 9, 191–197. [Google Scholar] [CrossRef] [PubMed]
  173. Chen, H.; Meng, T.; Liu, X.; Sun, M.; Tong, C.; Liu, J.; Wang, H.; Du, J. Long non-coding RNA MALAT-1 is downregulated in preeclampsia and regulates proliferation, apoptosis, migration and invasion of JEG-3 trophoblast cells. Int. J. Clin. Exp. Path. 2015, 8, 12718. [Google Scholar]
  174. Feng, C.; Cheng, L.; Jin, J.; Liu, X.; Wang, F. Long non-coding RNA MALAT1 regulates trophoblast functions through VEGF/VEGFR1 signaling pathway. Arch. Gynecol. Obstet. 2021, 304, 873–882. [Google Scholar] [CrossRef] [PubMed]
  175. Li, Q.; Wang, T.; Huang, S.; Zuo, Q.; Jiang, Z.; Yang, N.; Sun, L. LncRNA MALAT1 affects the migration and invasion of trophoblast cells by regulating FOS expression in early-onset preeclampsia. Pregnancy Hypertens. 2020, 21, 50–57. [Google Scholar] [CrossRef] [PubMed]
  176. Wu, H.Y.; Wang, X.H.; Liu, K.; Zhang, J.L. LncRNA MALAT1 regulates trophoblast cells migration and invasion via miR-206/IGF-1 axis. Cell Cycle 2020, 19, 39–52. [Google Scholar] [CrossRef] [PubMed]
  177. Wu, D.; Xu, Y.; Zou, Y.; Zuo, Q.; Huang, S.; Wang, S.; Lu, X.; He, X.; Wang, J.; Wang, T.; et al. Long Noncoding RNA 00473 Is Involved in Preeclampsia by LSD1 Binding-Regulated TFPI2 Transcription in Trophoblast Cells. Mol. Ther. Nucleic Acids 2018, 12, 381–392. [Google Scholar] [CrossRef] [Green Version]
  178. Liang, X.H.; Deng, W.B.; Liu, Y.F.; Liang, Y.X.; Fan, Z.M.; Gu, X.W.; Liu, J.L.; Sha, A.G.; Diao, H.L.; Yang, Z.M. Non-coding RNA LINC00473 mediates decidualization of human endometrial stromal cells in response to cAMP signaling. Sci. Rep. 2016, 6, 22744. [Google Scholar] [CrossRef] [Green Version]
  179. Chi, Z.; Gao, Q.; Sun, Y.; Zhou, F.; Wang, H.; Shu, X.; Zhang, M. LINC00473 downregulation facilitates trophoblast cell migration and invasion via the miR-15a-5p/LITAF axis in pre-eclampsia. Environ. Toxicol. 2021, 36, 1618–1627. [Google Scholar] [CrossRef]
  180. Liu, C.; Li, H.; Zhang, Y.; Ding, H. Long intergenic noncoding RNA 00473 promoting migration and invasion of trophoblastic cell line HTR-8/SVneo via regulating miR-424-5p-mediated wnt3a/β-catenin signaling pathway. J. Obstet. Gynaecol. Res. 2021, 47, 3034–3046. [Google Scholar] [CrossRef]
  181. Jiao, S.; Wang, S.Y.; Huang, Y. LncRNA PRNCR1 promoted the progression of eclampsia by regulating the MAPK signal pathway. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 3635–3642. [Google Scholar] [CrossRef]
  182. Li, J.L.; Li, R.; Gao, Y.; Guo, W.C.; Shi, P.X.; Li, M. LncRNA CCAT1 promotes the progression of preeclampsia by regulating CDK4. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 1216–1223. [Google Scholar] [CrossRef] [PubMed]
  183. Yu, L.; Kuang, L.Y.; He, F.; Du, L.L.; Li, Q.L.; Sun, W.; Zhou, Y.M.; Li, X.M.; Li, X.Y.; Chen, D.J. The Role and Molecular Mechanism of Long Nocoding RNA-MEG3 in the Pathogenesis of Preeclampsia. Reprod. Sci. 2018, 25, 1619–1628. [Google Scholar] [CrossRef]
  184. Xu, Y.; Ge, Z.; Zhang, E.; Zuo, Q.; Huang, S.; Yang, N.; Wu, D.; Zhang, Y.; Chen, Y.; Xu, H.; et al. The lncRNA TUG1 modulates proliferation in trophoblast cells via epigenetic suppression of RND3. Cell Death Dis. 2017, 8, e3104. [Google Scholar] [CrossRef] [PubMed]
  185. Li, Q.; Zhang, J.; Su, D.M.; Guan, L.N.; Mu, W.H.; Yu, M.; Ma, X.; Yang, R.J. lncRNA TUG1 modulates proliferation, apoptosis, invasion, and angiogenesis via targeting miR-29b in trophoblast cells. Hum. Genom. 2019, 13, 1–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  186. Yu, Y.; Wang, L.; Gao, M.; Guan, H. Long non-coding RNA TUG 1 regulates the migration and invasion of trophoblast-like cells through sponging miR-204-5p. Clin. Exp. Pharmacol. Physiol. 2019, 46, 380–388. [Google Scholar] [CrossRef]
  187. Zhang, W.; Zhou, Y.; Ding, Y. Lnc-DC mediates the over-maturation of decidual dendritic cells and induces the increase in Th1 cells in preeclampsia. Am. J. Reprod. Immunol. 2017, 77, e12647. [Google Scholar] [CrossRef]
  188. Song, X.; Rui, C.; Meng, L.; Zhang, R.; Shen, R.; Ding, H.; Li, J.; Li, J.; Long, W. Long non-coding RNA RPAIN regulates the invasion and apoptosis of trophoblast cell lines via complement protein C1q. Oncotarget 2017, 8, 7637–7646. [Google Scholar] [CrossRef] [Green Version]
  189. Liu, X.; Chen, H.; Kong, W.; Zhang, Y.; Cao, L.; Gao, L.; Zhou, R. Down-regulated long non-coding RNA-ATB in preeclampsia and its effect on suppressing migration, proliferation, and tube formation of trophoblast cells. Placenta 2017, 49, 80–87. [Google Scholar] [CrossRef]
  190. Yin, Y.; Zhang, J.; Yu, H.; Liu, M.; Zheng, X.; Zhou, R. Effect of lncRNA-ATB/miR-651-3p/Yin Yang 1 pathway on trophoblast-endothelial cell interaction networks. J. Cell. Mol. Med. 2021, 25, 5391–5403. [Google Scholar] [CrossRef]
  191. Cao, C.; Li, J.; Li, J.; Liu, L.; Cheng, X.; Jia, R. Long Non-Coding RNA Uc.187 Is Upregulated in Preeclampsia and Modulates Proliferation, Apoptosis, and Invasion of HTR-8/SVneo Trophoblast Cells. J. Cell. Biochem. 2017, 118, 1462–1470. [Google Scholar] [CrossRef]
  192. Zuo, Q.; Huang, S.; Zou, Y.; Xu, Y.; Jiang, Z.; Zou, S.; Xu, H.; Sun, L. The Lnc RNA SPRY4-IT1 Modulates Trophoblast Cell Invasion and Migration by Affecting the Epithelial-Mesenchymal Transition. Sci. Rep. 2016, 6, 37183. [Google Scholar] [CrossRef] [PubMed]
  193. Oudejans, C.B.; Poutsma, A.; Michel, O.J.; Thulluru, H.K.; Mulders, J.; van de Vrugt, H.J.; Sistermans, E.A.; van Dijk, M. Noncoding RNA-regulated gain-of-function of STOX2 in Finnish pre-eclamptic families. Sci. Rep. 2016, 6, 32129. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  194. Brown, C.J.; Ballabio, A.; Rupert, J.L.; Lafreniere, R.G.; Grompe, M.; Tonlorenzi, R.; Willard, H.F. A gene from the region of the human X inactivation centre is expressed exclusively from the inactive X chromosome. Nature 1991, 349, 38. [Google Scholar] [CrossRef] [PubMed]
  195. Erwin, J.A.; del Rosario, B.; Payer, B.; Lee, J.T. An ex vivo model for imprinting: Mutually exclusive binding of Cdx2 and Oct4 as a switch for imprinted and random X-inactivation. Genetics 2012, 192, 857–868. [Google Scholar] [CrossRef] [Green Version]
  196. Penkala, I.; Wang, J.; Syrett, C.M.; Goetzl, L.; López, C.B.; Anguera, M.C. lncRHOXF1, a Long Noncoding RNA from the X Chromosome That Suppresses Viral Response Genes during Development of the Early Human Placenta. Mol. Cell. Biol. 2016, 36, 1764–1775. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  197. Liu, L.; Gong, Y. LncRNA-TCL6 promotes early abortion and inhibits placenta implantation via the EGFR pathway. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 7105–7112. [Google Scholar]
  198. Li, M.; Zhang, H.; Kong, Q. Long non-coding RNA IGF2-AS promotes trophoblast cell proliferation, migration, and invasion by regulating miR-520g/N-cadherin axis. J. Obstet. Gynaecol. Res. 2021, 47, 3047–3059. [Google Scholar] [CrossRef]
  199. Wang, Q.; Lu, X.; Li, C.; Zhang, W.; Lv, Y.; Wang, L.; Wu, L.; Meng, L.; Fan, Y.; Ding, H.; et al. Down-regulated long non-coding RNA PVT1 contributes to gestational diabetes mellitus and preeclampsia via regulation of human trophoblast cells. Biomed. Pharmacother. 2019, 120, 109501. [Google Scholar] [CrossRef]
  200. Gremlich, S.; Damnon, F.; Reymondin, D.; Braissant, O.; Schittny, J.; Baud, D.; Gerber, S.; Roth-Kleiner, M. The long non-coding RNA NEAT1 is increased in IUGR placentas, leading to potential new hypotheses of IUGR origin/development. Placenta 2014, 35, 44–49. [Google Scholar] [CrossRef]
  201. Xufei, F.; Xiujuan, Z.; Jianyi, L.; Liyan, Y.; Ting, Y.; Min, H. Up-regulation of LncRNA NEAT1 induces apoptosis of human placental trophoblasts. Free Radic. Res. 2020, 54, 678–686. [Google Scholar] [CrossRef]
  202. Quan, G.; Li, J. Circular RNAs: Biogenesis, expression and their potential roles in reproduction. J. Ovarian Res. 2018, 11, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  203. Maass, P.G.; Glažar, P.; Memczak, S.; Dittmar, G.; Hollfinger, I.; Schreyer, L.; Sauer, A.V.; Toka, O.; Aiuti, A.; Luft, F.C.; et al. A map of human circular RNAs in clinically relevant tissues. J. Mol. Med. 2017, 95, 1179–1189. [Google Scholar] [CrossRef] [PubMed]
  204. Yan, L.; Feng, J.; Cheng, F.; Cui, X.; Gao, L.; Chen, Y.; Wang, F.; Zhong, T.; Li, Y.; Liu, L. Circular RNA expression profiles in placental villi from women with gestational diabetes mellitus. Biochem. Biophys. Res. Commun. 2018, 498, 743–750. [Google Scholar] [CrossRef] [PubMed]
  205. Wang, H.; She, G.; Zhou, W.; Liu, K.; Miao, J.; Yu, B. Expression profile of circular RNAs in placentas of women with gestational diabetes mellitus. Endocr. J. 2019, 66, 431–441. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  206. Zhou, W.; Wang, H.; Wu, X.; Long, W.; Zheng, F.; Kong, J.; Yu, B. The profile analysis of circular RNAs in human placenta of preeclampsia. Exp. Biol. Med. 2018, 243, 1109–1117. [Google Scholar] [CrossRef] [Green Version]
  207. Bai, Y.; Rao, H.; Chen, W.; Luo, X.; Tong, C.; Qi, H. Profiles of circular RNAs in human placenta and their potential roles related to preeclampsia. Biol. Reprod. 2018, 98, 705–712. [Google Scholar] [CrossRef] [Green Version]
  208. Ou, Y.; Liu, M.; Zhu, L.; Deng, K.; Chen, M.; Chen, H.; Zhang, J. The expression profile of circRNA and its potential regulatory targets in the placentas of severe pre-eclampsia. Taiwan. J. Obstet. Gynecol. 2019, 58, 769–777. [Google Scholar] [CrossRef]
  209. Ma, B.; Zhao, H.; Gong, L.; Xiao, X.; Zhou, Q.; Lu, H.; Cui, Y.; Xu, H.; Wu, S.; Tang, Y.; et al. Differentially expressed circular RNAs and the competing endogenous RNA network associated with preeclampsia. Placenta 2021, 103, 232–241. [Google Scholar] [CrossRef]
  210. Qian, Y.; Lu, Y.; Rui, C.; Qian, Y.; Cai, M.; Jia, R. Potential Significance of Circular RNA in Human Placental Tissue for Patients with Preeclampsia. Cell. Physiol. Biochem. 2016, 39, 1380–1390. [Google Scholar] [CrossRef]
  211. Li, Z.; Zhou, X.; Gao, W.; Sun, M.; Chen, H.; Meng, T. Circular RNA VRK1 facilitates pre-eclampsia progression via sponging miR-221-3P to regulate PTEN/Akt. J. Cell. Mol. Med. 2021, 26, 1826–1841. [Google Scholar] [CrossRef]
  212. Zhang, Y.; Yang, H.; Zhang, Y.; Shi, J.; Chen, R.; Xiao, X. CircSFXN1 regulates the behaviour of trophoblasts and likely mediates preeclampsia. Placenta 2020, 101, 115–123. [Google Scholar] [CrossRef] [PubMed]
  213. Gai, S.; Sun, L.; Wang, H.; Yang, P. Circular RNA hsa_circ_0007121 regulates proliferation, migration, invasion, and epithelial–mesenchymal transition of trophoblast cells by miR-182-5p/PGF axis in preeclampsia. Open Med. 2020, 15, 1061–1071. [Google Scholar] [CrossRef] [PubMed]
  214. Zhu, H.; Niu, X.; Li, Q.; Zhao, Y.; Chen, X.; Sun, H. Circ_0085296 suppresses trophoblast cell proliferation, invasion, and migration via modulating miR-144/E-cadherin axis. Placenta 2020, 97, 18–25. [Google Scholar] [CrossRef] [PubMed]
  215. Zhou, B.; Zhang, X.; Li, T.; Xie, R.; Zhou, J.; Luo, Y.; Yang, C. CircZDHHC20 represses the proliferation, migration and invasion in trophoblast cells by miR-144/GRHL2 axis. Cancer Cell Int. 2020, 20, 1–11. [Google Scholar] [CrossRef]
  216. Tang, R.; Zhang, Z.; Han, W. CircLRRK1 targets miR-223-3p to inhibit the proliferation, migration and invasion of trophoblast cells by regulating the PI3K/AKT signaling pathway. Placenta 2021, 104, 110–118. [Google Scholar] [CrossRef] [PubMed]
  217. Ou, Y.; Zhu, L.; Wei, X.; Bai, S.; Chen, M.; Chen, H.; Zhang, J. Circular RNA circ_0111277 attenuates human trophoblast cell invasion and migration by regulating miR-494/HTRA1/Notch-1 signal pathway in pre-eclampsia. Cell Death Dis. 2020, 11, 1–14. [Google Scholar] [CrossRef]
  218. Zhang, Y.; Cao, L.; Jia, J.; Ye, L.; Wang, Y.; Zhou, B.; Zhou, R. CircHIPK3 is decreased in preeclampsia and affects migration, invasion, proliferation, and tube formation of human trophoblast cells. Placenta 2019, 85, 1–8. [Google Scholar] [CrossRef]
  219. Zhou, W.; Wang, H.; Yang, J.; Long, W.; Zhang, B.; Liu, J.; Yu, B. Down-regulated circPAPPA suppresses the proliferation and invasion of trophoblast cells via the miR-384/STAT3 pathway. Biosci. Rep. 2019, 39, BSR20191965. [Google Scholar] [CrossRef] [Green Version]
  220. Shen, X.Y.; Zheng, L.L.; Huang, J.; Kong, H.F.; Chang, Y.J.; Wang, F.; Xin, H. CircTRNC18 inhibits trophoblast cell migration and epithelial–mesenchymal transition by regulating miR-762/Grhl2 pathway in pre-eclampsia. RNA Biol. 2019, 16, 1565–1573. [Google Scholar] [CrossRef] [Green Version]
  221. Li, W.; Yu, N.; Fan, L.; Chen, S.H.; Wu, J.L. Circ_0063517 acts as ceRNA, targeting the miR-31-5p-ETBR axis to regulate angiogenesis of vascular endothelial cells in preeclampsia. Life Sci. 2020, 244, 117306. [Google Scholar] [CrossRef]
  222. Deng, N.; Lei, D.; Huang, J.; Yang, Z.; Fan, C.; Wang, S. Circular RNA expression profiling identifies hsa_circ_0011460 as a novel molecule in severe preeclampsia. Pregnancy Hypertens. 2019, 17, 216–225. [Google Scholar] [CrossRef] [PubMed]
  223. Hu, X.; Ao, J.; Li, X.; Zhang, H.; Wu, J.; Cheng, W. Competing endogenous RNA expression profiling in pre-eclampsia identifies hsa_circ_0036877 as a potential novel blood biomarker for early pre-eclampsia. Clin. Epigenet. 2018, 10, 1–12. [Google Scholar] [CrossRef] [PubMed]
  224. Zhang, Y.; Yang, H.; Zhang, Y.; Shi, J.; Chen, R. circCRAMP1L is a novel biomarker of preeclampsia risk and may play a role in preeclampsia pathogenesis via regulation of the MSP/RON axis in trophoblasts. BMC Pregnancy Childbirth 2020, 20, 1–10. [Google Scholar] [CrossRef] [PubMed]
  225. Wang, H.; Zhang, J.; Xu, Z.; Yang, J.; Xu, Y.; Liu, Y.; Li, B.; Xie, J.; Li, J. Circular RNA hsa_circ_0000848 promotes trophoblast cell migration and invasion and inhibits cell apoptosis by sponging hsa-miR-6768-5p. Front. Cell Dev. Biol. 2020, 8, 278. [Google Scholar] [CrossRef]
  226. Wang, H.; Luo, C.; Wu, X.; Zhang, J.; Xu, Z.; Liu, Y.; Li, B.; Li, J.; Xie, J. Circular RNA hsa_circ_0081343 promotes trophoblast cell migration and invasion and inhibits trophoblast apoptosis by regulating miR-210-5p/DLX3 axis. Reprod. Biol. Endocrinol. 2021, 19, 1–11. [Google Scholar] [CrossRef]
  227. Yao, P.; Hu, G.; Niu, H. Hsa_circ_0074371 Regulates Proliferation, Apoptosis, Migration, and Invasion via the miR-582-3p/LRP6 Axis in Trophoblast Cells. Biochem. Genet. 2021, 60, 267–285. [Google Scholar] [CrossRef]
  228. Wang, D.; Na, Q.; Song, G.; Wang, Y.; Wang, Y. The role of circRNA-SETD2/miR-519a/PTEN axis in fetal birth weight through regulating trophoblast proliferation. BioMed Res. Int. 2020, 2020, 9809632. [Google Scholar] [CrossRef]
  229. Li, Z.; Zhou, G.; Tao, F.; Cao, Y.; Han, W.; Li, Q. circ-ZUFSP regulates trophoblasts migration and invasion through sponging miR-203 to regulate STOX1 expression. Biochem. Biophys. Res. Commun. 2020, 531, 472–479. [Google Scholar] [CrossRef]
  230. Umu, S.U.; Langseth, H.; Bucher-Johannessen, C.; Fromm, B.; Keller, A.; Meese, E.; Lauritzen, M.; Leithaug, M.; Lyle, R.; Rounge, T.B. A comprehensive profile of circulating RNAs in human serum. RNA Biol. 2018, 15, 242–250. [Google Scholar] [CrossRef] [Green Version]
  231. Schmitz, U.; Naderi-Meshkin, H.; Gupta, S.K.; Wolkenhauer, O.; Vera, J. The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions. Brief. Bioinform. 2016, 17, 380–392. [Google Scholar] [CrossRef] [Green Version]
  232. Turchinovich, A.; Weiz, L.; Langheinz, A.; Burwinkel, B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 2011, 39, 7223–7233. [Google Scholar] [CrossRef] [PubMed]
  233. Wang, K.; Zhang, S.; Weber, J.; Baxter, D.; Galas, D.J. Export of microRNAs and microRNA-protective protein by mammalian cells. Nucleic Acids Res. 2010, 38, 7248–7259. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  234. Arroyo, J.D.; Chevillet, J.R.; Kroh, E.M.; Ruf, I.K.; Pritchard, C.C.; Gibson, D.F.; Mitchell, P.S.; Bennett, C.F.; Pogosova-Agadjanyan, E.L.; Stirewalt, D.L.; et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl. Acad. Sci. USA 2011, 108, 5003–5008. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  235. Vickers, K.C.; Palmisano, B.T.; Shoucri, B.M.; Shamburek, R.D.; Remaley, A.T. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat. Cell Biol. 2011, 13, 423–433. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  236. Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Lötvall, J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 2007, 9, 654–659. [Google Scholar] [CrossRef] [Green Version]
  237. Rodosthenous, R.S.; Burris, H.H.; Sanders, A.P.; Just, A.C.; Dereix, A.E.; Svensson, K.; Solano, M.; Téllez-Rojo, M.M.; Wright, R.O.; Baccarelli, A.A. Second trimester extracellular microRNAs in maternal blood and fetal growth: An exploratory study. Epigenetics 2017, 12, 804–810. [Google Scholar] [CrossRef] [Green Version]
  238. Poon, L.L.; Leung, T.N.; Lau, T.K.; Lo, Y.M. Presence of fetal RNA in maternal plasma. Clin. Chem. 2000, 46, 1832–1834. [Google Scholar] [CrossRef] [Green Version]
  239. Tsui, N.B.Y.; Jiang, P.; Wong, Y.F.; Leung, T.Y.; Chan, K.C.A.; Chiu, R.W.K.; Sun, H.; Lo, Y.M.D. Maternal plasma RNA sequencing for genome-wide transcriptomic profiling and identification of pregnancy-associated transcripts. Clin. Chem. 2014, 60, 954–962. [Google Scholar] [CrossRef] [Green Version]
  240. Whitehead, C.L.; Walker, S.P.; Tong, S. Measuring circulating placental RNAs to non-invasively assess the placental transcriptome and to predict pregnancy complications. Prenat. Diagn. 2016, 36, 997–1008. [Google Scholar] [CrossRef] [Green Version]
  241. Ngo, T.T.M.; Moufarrej, M.N.; Rasmussen, M.L.H.; Camunas-Soler, J.; Pan, W.; Okamoto, J.; Neff, N.F.; Liu, K.; Wong, R.J.; Downes, K.; et al. Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Science 2018, 360, 1133–1136. [Google Scholar] [CrossRef] [Green Version]
  242. Traver, S.; Assou, S.; Scalici, E.; Haouzi, D.; Al-Edani, T.; Belloc, S.; Hamamah, S. Cell-free nucleic acids as non-invasive biomarkers of gynecological cancers, ovarian, endometrial and obstetric disorders and fetal aneuploidy. Hum. Reprod. Update 2014, 20, 905–923. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  243. Scalici, E.; Traver, S.; Mullet, T.; Molinari, N.; Ferrières, A.; Brunet, C.; Belloc, S.; Hamamah, S. Circulating microRNAs in follicular fluid, powerful tools to explore in vitro fertilization process. Sci. Rep. 2016, 6, 24976. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  244. Yang, Q.; Gu, W.W.; Gu, Y.; Yan, N.N.; Mao, Y.Y.; Zhen, X.X.; Wang, J.M.; Yang, J.; Shi, H.J.; Zhang, X.; et al. Association of the peripheral blood levels of circulating microRNAs with both recurrent miscarriage and the outcomes of embryo transfer in an in vitro fertilization process. J. Transl. Med. 2018, 16, 1–14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  245. Yoffe, L.; Polsky, A.; Gilam, A.; Raff, C.; Mecacci, F.; Ognibene, A.; Crispi, F.; Gratacós, E.; Kanety, H.; Mazaki-Tovi, S.; et al. Early diagnosis of gestational diabetes mellitus using circulating microRNAs. Eur. J. Endocrinol. 2019, 181, 565–577. [Google Scholar] [CrossRef] [PubMed]
  246. Lu, J.; Wu, J.; Zhao, Z.; Wang, J.; Chen, Z. Circulating LncRNA Serve as Fingerprint for Gestational Diabetes Mellitus Associated with Risk of Macrosomia. Cell. Physiol. Biochem. 2018, 48, 1012–1018. [Google Scholar] [CrossRef]
  247. Enquobahrie, D.A.; Wander, P.L.; Tadesse, M.G.; Qiu, C.; Holzman, C.; Williams, M.A. Maternal pre-pregnancy body mass index and circulating microRNAs in pregnancy. Obes. Res. Clin. Pract. 2017, 11, 464–474. [Google Scholar] [CrossRef]
  248. Adaikalakoteswari, A.; Vatish, M.; Alam, M.T.; Ott, S.; Kumar, S.; Saravanan, P. Low Vitamin B12 in Pregnancy Is Associated with Adipose-Derived Circulating miRs Targeting PPARγ and Insulin Resistance. J. Clin. Endocrinol. Metab. 2017, 102, 4200–4209. [Google Scholar] [CrossRef] [Green Version]
  249. MacDonald, T.M.; Kaitu’u-Lino, T.J.; Walker, S.P.; Dane, K.M.; Lockie, E.B.; Tong, S.; Whitehead, C.L.; Hui, L. Variable effect of maternal oral glucose load on circulating cell-free placental mRNAs. J. Matern. Fetal Neonatal Med. 2017, 30, 501–503. [Google Scholar] [CrossRef]
  250. Gardiner, A.S.; Gutierrez, H.L.; Luo, L.; Davies, S.; Savage, D.D.; Bakhireva, L.N.; Perrone-Bizzozero, N.I. Alcohol Use During Pregnancy is Associated with Specific Alterations in MicroRNA Levels in Maternal Serum. Alcohol. Clin. Exp. Res. 2016, 40, 826–837. [Google Scholar] [CrossRef] [Green Version]
  251. Tseng, A.M.; Mahnke, A.H.; Wells, A.B.; Salem, N.A.; Allan, A.M.; Roberts, V.H.; Newman, N.; Walter, N.A.; Kroenke, C.D.; Grant, K.A.; et al. Maternal circulating miRNAs that predict infant FASD outcomes influence placental maturation. Life Sci. Alliance 2019, 2, e201800252. [Google Scholar] [CrossRef] [Green Version]
  252. Eisenberg, I.; Nahmias, N.; Novoselsky Persky, M.; Greenfield, C.; Goldman-Wohl, D.; Hurwitz, A.; Haimov-Kochman, R.; Yagel, S.; Imbar, T. Elevated circulating micro-ribonucleic acid (miRNA)-200b and miRNA-429 levels in anovulatory women. Fertil. Steril. 2017, 107, 269–275. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  253. Yoffe, L.; Gilam, A.; Yaron, O.; Polsky, A.; Farberov, L.; Syngelaki, A.; Nicolaides, K.; Hod, M.; Shomron, N. Early Detection of Preeclampsia Using Circulating Small non-coding RNA. Sci. Rep. 2018, 8, 3401. [Google Scholar] [CrossRef] [PubMed]
  254. Munchel, S.; Rohrback, S.; Randise-Hinchliff, C.; Kinnings, S.; Deshmukh, S.; Alla, N.; Tan, C.; Kia, A.; Greene, G.; Leety, L.; et al. Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia. Sci. Transl. Med. 2020, 12, eaaz0131. [Google Scholar] [CrossRef] [PubMed]
  255. Jairajpuri, D.S.; Malalla, Z.H.; Mahmood, N.; Almawi, W.Y. Circulating microRNA expression as predictor of preeclampsia and its severity. Gene 2017, 627, 543–548. [Google Scholar] [CrossRef] [PubMed]
  256. Jung, Y.W.; Shim, J.I.; Shim, S.H.; Shin, Y.j.; Shim, S.H.; Chang, S.W.; Cha, D.H. Global gene expression analysis of cell-free RNA in amniotic fluid from women destined to develop preeclampsia. Medicine 2019, 98, e13971. [Google Scholar] [CrossRef]
  257. Gu, M.; Zheng, A.; Tu, W.; Zhao, J.; Li, L.; Li, M.; Han, S.; Hu, X.; Zhu, J.; Pan, Y.; et al. Circulating LncRNAs as Novel, Non-Invasive Biomarkers for Prenatal Detection of Fetal Congenital Heart Defects. Cell. Physiol. Biochem. 2016, 38, 1459–1471. [Google Scholar] [CrossRef]
  258. Biró, O.; Rigó, J.; Nagy, B. Noninvasive prenatal testing for congenital heart disease—Cell-free nucleic acid and protein biomarkers in maternal blood. J. Matern. Fetal Neonatal Med. 2018, 33, 1044–1050. [Google Scholar] [CrossRef] [PubMed]
  259. Whitehead, C.L.; McNamara, H.; Walker, S.P.; Alexiadis, M.; Fuller, P.J.; Vickers, D.K.; Hannan, N.J.; Hastie, R.; Tuohey, L.; Kaitu’u-Lino, T.J.; et al. Identifying late-onset fetal growth restriction by measuring circulating placental RNA in the maternal blood at 28 weeks’ gestation. Am. J. Obstet. Gynecol. 2016, 214, 521.e1–521.e8. [Google Scholar] [CrossRef]
  260. Carbone, I.F.; Conforti, A.; Picarelli, S.; Morano, D.; Alviggi, C.; Farina, A. Circulating nucleic acids in maternal plasma and serum in pregnancy complications: Are they really useful in clinical practice? a systematic review. Mol. Diagn. Ther. 2020, 24, 409–431. [Google Scholar] [CrossRef]
  261. Salomon, C.; Guanzon, D.; Scholz-Romero, K.; Longo, S.; Correa, P.; Illanes, S.E.; Rice, G.E. Placental Exosomes as Early Biomarker of Preeclampsia: Potential Role of Exosomal MicroRNAs Across Gestation. J. Clin. Endocrinol. Metab. 2017, 102, 3182–3194. [Google Scholar] [CrossRef]
  262. Wang, Y.; Du, X.; Wang, J. Transfer of miR-15a-5p by placental exosomes promotes pre-eclampsia progression by regulating PI3K/AKT signaling pathway via CDK1. Mol. Immunol. 2020, 128, 277–286. [Google Scholar] [CrossRef] [PubMed]
  263. Raposo, G.; Stoorvogel, W. Extracellular vesicles: Exosomes, microvesicles, and friends. J. Cell Biol. 2013, 200, 373–383. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  264. Ouyang, Y.; Mouillet, J.F.; Coyne, C.B.; Sadovsky, Y. Review: Placenta-specific microRNAs in exosomes—Good things come in nano-packages. Placenta 2014, 35, S69–S73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  265. Simpson, R.J.; Jensen, S.S.; Lim, J.W.E. Proteomic profiling of exosomes: Current perspectives. Proteomics 2008, 8, 4083–4099. [Google Scholar] [CrossRef]
  266. Sabapatha, A.; Gercel-Taylor, C.; Taylor, D.D. Specific isolation of placenta-derived exosomes from the circulation of pregnant women and their immunoregulatory consequences. Am. J. Reprod. Immunol. 2006, 56, 345–355. [Google Scholar] [CrossRef]
  267. Tong, M.; Abrahams, V.M.; Chamley, L.W. Immunological effects of placental extracellular vesicles. Immunol. Cell Biol. 2018, 96, 714–722. [Google Scholar] [CrossRef]
  268. Favaro, R.R.; Murrieta-Coxca, J.M.; Gutiérrez-Samudio, R.N.; Morales-Prieto, D.M.; Markert, U.R. Immunomodulatory properties of extracellular vesicles in the dialogue between placental and immune cells. Am. J. Reprod. Immunol. 2021, 85, e13383. [Google Scholar] [CrossRef]
  269. Tannetta, D.; Collett, G.; Vatish, M.; Redman, C.; Sargent, I. Syncytiotrophoblast extracellular vesicles—Circulating biopsies reflecting placental health. Placenta 2017, 52, 134–138. [Google Scholar] [CrossRef] [Green Version]
  270. Chiarello, D.I.; Salsoso, R.; Toledo, F.; Mate, A.; Vázquez, C.M.; Sobrevia, L. Foetoplacental communication via extracellular vesicles in normal pregnancy and preeclampsia. Mol. Asp. Med. 2018, 60, 69–80. [Google Scholar] [CrossRef]
  271. Schmorl, G. Pathologisch-Anatomische Untersuchungen über Puerperal-Eklampsie; Vogel: Munich, Germany, 1893. [Google Scholar]
  272. Kumpel, B.; King, M.J.; Sooranna, S.; Jackson, D.; Eastlake, J.; Cheng, R.; Johnson, M. Phenotype and mRNA expression of syncytiotrophoblast microparticles isolated from human placenta. Ann. N. Y. Acad. Sci. 2008, 1137, 144–147. [Google Scholar] [CrossRef]
  273. Redman, C.W.G.; Tannetta, D.S.; Dragovic, R.A.; Gardiner, C.; Southcombe, J.H.; Collett, G.P.; Sargent, I.L. Review: Does size matter? Placental debris and the pathophysiology of pre-eclampsia. Placenta 2012, 33, S48–S54. [Google Scholar] [CrossRef] [PubMed]
  274. Chamley, L.W.; Holland, O.; Chen, Q.; Viall, C.; Stone, P.; Abumaree, M. Where is the maternofetal interface? Placenta 2014, 35, S74–S80. [Google Scholar] [CrossRef] [PubMed]
  275. Homer, H.; Rice, G.E.; Salomon, C. Review: Embryo- and endometrium-derived exosomes and their potential role in assisted reproductive treatments-liquid biopsies for endometrial receptivity. Placenta 2017, 54, 89–94. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  276. Condrat, C.E.; Varlas, V.N.; Duică, F.; Antoniadis, P.; Danila, C.A.; Cretoiu, D.; Suciu, N.; Crețoiu, S.M.; Voinea, S.C. Pregnancy-Related Extracellular Vesicles Revisited. Int. J. Mol. Sci. 2021, 22, 3904. [Google Scholar] [CrossRef]
  277. Nakahara, A.; Nair, S.; Ormazabal, V.; Elfeky, O.; Garvey, C.E.; Longo, S.; Salomon, C. Circulating placental extracellular vesicles and their potential roles during pregnancy. Ochsner J. 2020, 20, 439–445. [Google Scholar] [CrossRef]
  278. Biró, O.; Alasztics, B.; Molvarec, A.; Joó, J.; Nagy, B.; Rigó, J. Various levels of circulating exosomal total-miRNA and miR-210 hypoxamiR in different forms of pregnancy hypertension. Pregnancy Hypertens. 2017, 10, 207–212. [Google Scholar] [CrossRef] [Green Version]
  279. Li, H.; Ouyang, Y.; Sadovsky, E.; Parks, W.T.; Chu, T.; Sadovsky, Y. Unique microRNA signals in plasma exosomes from pregnancies complicated by preeclampsia. Hypertension 2020, 75, 762–771. [Google Scholar] [CrossRef]
  280. Zabel, R.R.; Bär, C.; Ji, J.; Schultz, R.; Hammer, M.; Groten, T.; Schleussner, E.; Morales-Prieto, D.M.; Markert, U.R.; Favaro, R.R. Enrichment and characterization of extracellular vesicles from ex vivo one-sided human placenta perfusion. Am. J. Reprod. Immunol. 2021, 86, e13377. [Google Scholar] [CrossRef]
  281. Redman, C.W.G.; Sargent, I.L. Circulating microparticles in normal pregnancy and pre-eclampsia. Placenta 2008, 29 (Suppl. A), S73–S77. [Google Scholar] [CrossRef]
  282. Delorme-Axford, E.; Donker, R.B.; Mouillet, J.F.; Chu, T.; Bayer, A.; Ouyang, Y.; Wang, T.; Stolz, D.B.; Sarkar, S.N.; Morelli, A.E.; et al. Human placental trophoblasts confer viral resistance to recipient cells. Proc. Natl. Acad. Sci. USA 2013, 110, 12048–12053. [Google Scholar] [CrossRef] [Green Version]
  283. Schuster, J.; Cheng, S.B.; Padbury, J.; Sharma, S. Placental extracellular vesicles and pre-eclampsia. Am. J. Reprod. Immunol. 2021, 85, e13297. [Google Scholar] [CrossRef] [PubMed]
  284. Matsubara, K.; Matsubara, Y.; Uchikura, Y.; Sugiyama, T. Pathophysiology of Preeclampsia: The Role of Exosomes. Int. J. Mol. Sci. 2021, 22, 2572. [Google Scholar] [CrossRef] [PubMed]
  285. Cronqvist, T.; Tannetta, D.; Mörgelin, M.; Belting, M.; Sargent, I.; Familari, M.; Hansson, S.R. Syncytiotrophoblast derived extracellular vesicles transfer functional placental miRNAs to primary human endothelial cells. Sci. Rep. 2017, 7, 4558. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  286. Shen, L.; Li, Y.; Li, R.; Diao, Z.; Yany, M.; Wu, M.; Sun, H.; Yan, G.; Hu, Y. Placenta-associated serum exosomal miR-155 derived from patients with preeclampsia inhibits eNOS expression in human umbilical vein endothelial cells. Int. J. Mol. Med. 2018, 41, 1731–1739. [Google Scholar] [CrossRef] [Green Version]
  287. Cronqvist, T.; Saljé, K.; Familari, M.; Guller, S.; Schneider, H.; Gardiner, C.; Sargent, I.L.; Redman, C.W.; Mörgelin, M.; Åkerström, B.; et al. Syncytiotrophoblast vesicles show altered micro-RNA and haemoglobin content after ex-vivo perfusion of placentas with haemoglobin to mimic preeclampsia. PLoS ONE 2014, 9, e90020. [Google Scholar] [CrossRef]
  288. Truong, G.; Guanzon, D.; Kinhal, V.; Elfeky, O.; Lai, A.; Longo, S.; Nuzhat, Z.; Palma, C.; Scholz-Romero, K.; Menon, R.; et al. Oxygen tension regulates the miRNA profile and bioactivity of exosomes released from extravillous trophoblast cells—Liquid biopsies for monitoring complications of pregnancy. PLoS ONE 2017, 12, e0174514. [Google Scholar] [CrossRef] [Green Version]
  289. Salomon, C.; Scholz-Romero, K.; Sarker, S.; Sweeney, E.; Kobayashi, M.; Correa, P.; Longo, S.; Duncombe, G.; Mitchell, M.D.; Rice, G.E.; et al. Gestational Diabetes Mellitus Is Associated with Changes in the Concentration and Bioactivity of Placenta-Derived Exosomes in Maternal Circulation Across Gestation. Diabetes 2016, 65, 598–609. [Google Scholar] [CrossRef] [Green Version]
  290. Gillet, V.; Ouellet, A.; Stepanov, Y.; Rodosthenous, R.S.; Croft, E.K.; Brennan, K.; Abdelouahab, N.; Baccarelli, A.; Takser, L. miRNA profiles in extracellular vesicles from serum early in pregnancies complicated by gestational diabetes mellitus. J. Clin. Endocrinol. Metab. 2019, 104, 5157–5169. [Google Scholar] [CrossRef]
  291. Nair, S.; Jayabalan, N.; Guanzon, D.; Palma, C.; Scholz-Romero, K.; Elfeky, O.; Zuñiga, F.; Ormazabal, V.; Diaz, E.; Rice, G.E.; et al. Human placental exosomes in gestational diabetes mellitus carry a specific set of miRNAs associated with skeletal muscle insulin sensitivity. Clin. Sci. 2018, 132, 2451–2467. [Google Scholar] [CrossRef]
  292. Fallen, S.; Baxter, D.; Wu, X.; Kim, T.K.; Shynlova, O.; Lee, M.Y.; Scherler, K.; Lye, S.; Hood, L.; Wang, K. Extracellular vesicle RNAs reflect placenta dysfunction and are a biomarker source for preterm labour. J. Cell. Mol. Med. 2018, 22, 2760–2773. [Google Scholar] [CrossRef] [Green Version]
  293. Ying, X.; Jin, X.; Zhu, Y.; Liang, M.; Chang, X.; Zheng, L. Exosomes released from decidual macrophages deliver miR-153-3p, which inhibits trophoblastic biological behavior in unexplained recurrent spontaneous abortion. Int. Immunopharmacol. 2020, 88, 106981. [Google Scholar] [CrossRef] [PubMed]
  294. Ouyang, Y.; Bayer, A.; Chu, T.; Tyurin, V.A.; Kagan, V.E.; Morelli, A.E.; Coyne, C.B.; Sadovsky, Y. Isolation of human trophoblastic extracellular vesicles and characterization of their cargo and antiviral activity. Placenta 2016, 47, 86–95. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  295. Rice, T.F.; Donaldson, B.; Bouqueau, M.; Kampmann, B.; Holder, B. Macrophage- but not monocyte-derived extracellular vesicles induce placental pro-inflammatory responses. Placenta 2018, 69, 92–95. [Google Scholar] [CrossRef] [PubMed]
Figure 1. (A) Genomic locations of non-coding RNAs. NcRNAs can be located in 5 /3 UTRs and introns of proteins and are therewith transcribed with the protein (green). Additionally, ncRNAs exist sense and antisense in introns and exons of proteins and independent of proteins with own transcription start sites and promoter regions (red). Long non-coding RNAs usually span many kilobases and contain their own introns, located sense, antisense or independent of protein coding regions (yellow). (B) The various types of ncRNAs function in all basic cellular processes: transcription, processing, translation. They are involved in chromosome structure, DNA replication, gene regulation, genome defense and protein transport as indicated by the stars. Please note miRNA and lncRNAs are located in exosomes and microvesicles.
Figure 1. (A) Genomic locations of non-coding RNAs. NcRNAs can be located in 5 /3 UTRs and introns of proteins and are therewith transcribed with the protein (green). Additionally, ncRNAs exist sense and antisense in introns and exons of proteins and independent of proteins with own transcription start sites and promoter regions (red). Long non-coding RNAs usually span many kilobases and contain their own introns, located sense, antisense or independent of protein coding regions (yellow). (B) The various types of ncRNAs function in all basic cellular processes: transcription, processing, translation. They are involved in chromosome structure, DNA replication, gene regulation, genome defense and protein transport as indicated by the stars. Please note miRNA and lncRNAs are located in exosomes and microvesicles.
Cells 11 01588 g001
Figure 2. Computational approach to detect microRNAs as potential biomarkers. miRNAs of interest can be detected experimentally and found in the literature or databases. Alternatively miRNAs can be predicted in silico and verified by transcription expression profiles. miRNA target prediction can be performed with various tools, each ranking the possible target by a score, p-value, and other criteria. Placenta-related protein genes can be obtained from databases for annotation, function or protein–protein interaction or other sources, such as own experimental data. Combining all information results in a comprehensive candidate list for miRNA and possible target genes.
Figure 2. Computational approach to detect microRNAs as potential biomarkers. miRNAs of interest can be detected experimentally and found in the literature or databases. Alternatively miRNAs can be predicted in silico and verified by transcription expression profiles. miRNA target prediction can be performed with various tools, each ranking the possible target by a score, p-value, and other criteria. Placenta-related protein genes can be obtained from databases for annotation, function or protein–protein interaction or other sources, such as own experimental data. Combining all information results in a comprehensive candidate list for miRNA and possible target genes.
Cells 11 01588 g002
Figure 3. Extracellular vesicles are released from the syncytiotrophoblast cells into the maternal blood. Microvesicles and exosomes can contain proteins, metabolites and non-coding RNAs.
Figure 3. Extracellular vesicles are released from the syncytiotrophoblast cells into the maternal blood. Microvesicles and exosomes can contain proteins, metabolites and non-coding RNAs.
Cells 11 01588 g003
Table 1. Tools for ncRNA identification. None of the existing tools for ncRNA identification have been developed specifically for the placenta. Therefore, a generic overview of tools for identification of ncRNAs is given: (a) by homology; (b) de novo; and (c) hybrid approach by including experimental work. Please note: this is a selection of available tools.
Table 1. Tools for ncRNA identification. None of the existing tools for ncRNA identification have been developed specifically for the placenta. Therefore, a generic overview of tools for identification of ncRNAs is given: (a) by homology; (b) de novo; and (c) hybrid approach by including experimental work. Please note: this is a selection of available tools.
(a) Homology-based tools for ncRNA identification
Blast/RNAcentralsequence based search
Infernal/Rfamprediction based on covariances of secondary structures
(b) Tools for de novo identification of ncRNAs
RNAzpredicting structurally conserved and thermodynamically stable RNA secondary structures in multiple sequence (genome) alignments[22]
QRNAprediction based on comparative genome sequence analysis[23]
RNAsambatool to predict the coding potential of RNA molecules from sequence information using a neural network-based that models both the whole sequence and the ORF to identify patterns that distinguish coding from non-coding transcripts[24]
FEELncalignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames[25]
LGCdiscriminating lncRNAs from protein-coding RNAs across diverse species that range from plants to mammals[26]
CPATnovel alignment-free method: recognizes coding and noncoding transcripts from a large pool of candidates[27]
COMEidentification and characterization of novel lncRNAs[28]
PLEKalgorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations[29]
PhyloCSFcomparative genomics method that analyzes a multispecies nucleotide sequence alignment to determine whether it is likely to represent a conserved protein-coding region, based on a formal statistical comparison of phylogenetic codon models[30]
(c) Identification of ncRNAs with the help of transcriptomic data
lncRScan-SVMtool for predicting the lncRNAs (classifying protein coding and lncRNA transcripts using support vector machine)[31]
slnckylncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important[32]
CNCIeffective for classifying incomplete transcripts and sense–antisense pairs (highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan)[33]
CREMAtool that can be used to rank long non-protein coding RNA predictions for use in conjunction with gene expression studies[34]
Table 2. miRNAs and their role in preeclampsia (selection). For more details see the references and for a larger overview the reviews [91,92,93,94,95].
Table 2. miRNAs and their role in preeclampsia (selection). For more details see the references and for a larger overview the reviews [91,92,93,94,95].
let-7ddown-regulation inhibits the proliferation and invasion of trophoblast cells[71]
miR-15binhibits trophoblast cell invasion and endothelial cell tube formation by suppressing the expression of argonaute 2[83]
miR-17, miR-20a, miR-20bare differentially expressed in PE, regulating EPHB4 and ephrin-B2 expression in trophoblast and endothelial cells via the same “seed” sequence[98]
mir-20bmay contribute to PE through inhibiting proliferation, invasion and migration of placental trophoblast cells by targeting MCL-1[99]
miR-22up-regulation is modulating production of androgen and estrogen and up-regulated in PE placenta[100]
miR-30a-3pexpression is significantly increased in PE and might be involved in the pathogenesis by targeting IGF-1 and regulating the invasion and apoptosis of trophoblast cells[78]
miR-34ahypo-methylation of the miR-34a promoter is associated with PE and PE severity[101]
regulates trophoblast invasion through the Notch signal transduction[102]
contributes to trophoblast cell apoptosis in PE by targeting BCL-2[87]
down-regulation miR-34a-5p improves invasion and migration of trophoblast cells by targetting SMAD4[103]
miR-93inhibits MMP-2 and reduces migration and invasion of immortalized trophoblast cells[76]
miR-128ainduces apoptosis of HTR-8/SVneo cells and thus may contribute to PE[86]
miR-181a-5pis increased in both the plasma and placenta of severe PE patients and suppresses the invasion and migration of HTR-8/SVneo cells by directly targeting IGF2BP2[74]
up-regulation induces apoptosis, and suppresses invasion in HTR-8/SVneo and JAR cells.[104]
miR-134down-regulates ITGB1 and inhibits infiltration of trophoblast cells in placenta of patients with PE[79]
miR-135a-5ppromotes migration and invasion of trophoblast cells through targeting β -TrCP[105]
miR-137reduces the proliferation and migration of trophoblast cells by targeting ERR α [72]
miR-141up-regulated in PE and regulates trophoblast (JEG-3 and HTR-8/SVneo) proliferation and invasion and intercellular communication vie EVs[18]
hypoxia-induced microRNA-141 regulates trophoblast apoptosis, invasion, and vascularization by blocking CXCL12 β /CXCR2/4 signal transduction[106]
miR-141-5p regulates ATF2 via effecting MAPK1/ERK2 signaling to promote preeclampsia[107]
miR-144may play an important role in the pathogenesis of PE through targeting PTEN in trophoblastic cells[108]
MicroRNA-144-3p may participate in the pathogenesis of preeclampsia by targeting Cox-2[109]
miR-195could promote cell invasion via directly targeting ActRIIB in trophoblast cells[82]
is suggested to regulate PE by affecting placental proliferation, apoptosis, and angiogenesis[110]
miR-200miR-200c,-20a and -20b are involved in hydrogen sulfide stimulation of VEGF in trophoblasts[111]
miR-203significantly increased in PE placenta inhibiting vascular endothelial growth factor A (VEGFA)[112]
miR-218contributes to PE by targeting LASP1 to inhibit trophoblast invasion[81]
miR-299up-regulation suppresses the invasion and migration of HTR-8/SVneo trophoblast cells partly via targeting HDAC2[75]
miR-320aoverexpression in PE placenta inhibits trophoblast cell invasion by targeting estrogen-related receptor-gamma (ERR γ ), but not migration or proliferation[80]
upregulation inhibits proliferation and invasion of trophoblast cells by targeting IL-4[113]
miR-454promotes the proliferation and invasion of trophoblast cells by inhibiting EPHB4 expression[73]
promotes the proliferation and invasion of trophoblast cells by downregulation of ALK7[114]
miR-520c-3pis suppressing inflammasome activation and inflammatory cascade by down-regulating NLRP3[115]
miR-520gis suppressing the migration and invasion of trophoblast via at least partial inhibition of MMP2 translation inhibition[77]
miR-4421is highly expressed in PE, which may promote the progression of PE by down-regulating the expression of CYP11B2[116]
miR-125binvolved in early PE development through regulation of Trop-2 expression[117]
Table 3. Long non-coding RNAs involved in pathologies. NN—no name.
Table 3. Long non-coding RNAs involved in pathologies. NN—no name.
Malat-1down-regulated in preeclampsia, regulates proliferation, apoptosis, migration and invasion of JEG-3 choriocarcinoma cells[173,174]
affects the migration and invasion of trophoblast cell by regulating FOS expression[175]
regulates trophoblast cells migration and invasion via miR-206/IGF-1 axis[176]
LOC391533, LOC284100, CEACAMP8dysregulation seems to be associated with preeclampsia[15]
linc00473down-regulated in the placenta of patients with severe PE. knockdown in trophoblast cell lines significantly inhibites cell proliferation and promotes apoptosis, whereas overexpression stimulates trophoblast proliferation. Further, linc00473 inhibited the expression of tissue factor pathway inhibitor 2 (TFPI2) through binding to lysine-specific demethylase 1 (LSD1)[177]
mediates decidualization of human endometrial stromal cells in response to cAMP signaling[178]
downregulation facilitates trophoblast cell migration and invasion via the miR-15a-5p/LITAF axis in pre-eclampsia,[179]
Linc00473 mediates regulation of Wnt/ β -catenin signaling pathway by miR-424-5p and affects invasion and migration of the trophoblastic cell line HTR-8/SVneo[180]
PRNCR1promotes the progression of PE by modulating the MAPK signaling pathway[181]
CCAT1is highly expressed in PE and can promote the progression of PE by inhibiting the expression of CDK4[182]
MEG3is lower expressed in the placenta of patients with PE, and its regulation of trophoblast cell epithelial-mesenchymal transition via the TGF- β pathway inhibitor SMAD7 may be the molecular mechanism involved in the pathogenesis of PE[183]
TUG1is modulating proliferation in trophoblast cells via epigenetic suppression of RND3[184]
is modulating proliferation, apoptosis, invasion, and angiogenesis via targeting miR-29b in trophoblast cells[185]
is regulating the migration and invasion of trophoblast-like cells through sponging miR-204-5p[186]
lnc-DCsoverexpression in dendritic cells mediates their maturation by phosphorylating STAT3 and induces the over-maturation of decidual dendritic cells in PE and leads to an increase in Th1 cells[187]
RPAINregulates the invasion and apoptosis of trophoblast cell lines via complement protein C1q[188]
ATBdown-regulated in PE placentas which was found to decrease migration, proliferation, and tube-formation of HTR-8/SVneo cells[189]
functions as a competitive endogenous RNA of miR-651-3p to regulate YY1 on progress of spiral artery remodelling[190]
uc.187is up-regulated in preeclampsia and modulates proliferation, apoptosis, and invasion of HTR-8/SVneo cells[191]
SPRY4-IT1modulates trophoblast cell invasion and migration by affecting the epithelial-mesenchymal transition[192]
up-regulation modulates proliferation, migration, apoptosis, and network formation in HTR-8SV/neo cells[16]
NNAn lncRNA within intron 3 of the STOX2 gene which seems to regulate an essential trophoblast differentiation pathway[193]
XISThas a role in X chromosome inactivation in females, a process that is paternal specific in the trophoblast and random in the fetus[194,195]
lncRHOXF1is the first example of an lncRNA from the X chromosome that regulates the host response to viral infections in human placental progenitor cells[196]
LncRNA-TCL6plays a role in early abortion by inhibiting placental implantation via the EGFR pathway[197]
LncRNaIGF2-ASplays a role in recurrent miscarriage by regulating trophoblast functions[198]
PVT1is down-regulated in GDM and PE[199]
HOTAIRplays an important role in suppressing angiogenesis of the human placenta by inhibiting the expression of VEGFA[171]
NEAT1is increased in intrauterine growth retardation (IUGR) placentas but the pathomechanism is not yet clear; up-regulation is inducing apoptosis in HTR-8/SVneo cells[200,201]
Table 4. Role of free circulating and exosomal ncRNAs in pregnancy-related diseases (selection).
Table 4. Role of free circulating and exosomal ncRNAs in pregnancy-related diseases (selection).
DiseaseCirculating ncRNACitation
Early pregnancy lossup-regulated hsa-let- 7c, hsa-miR-122 and down-regulated hsa-miR- 135a in plasma[42]
Recurrent miscarriagemiR-27a-3p, miR-29a-3p, miR-100-5p and miR-127-3p are increased and miR-486-5p decreased in plasma[244]
Fetal growth restrictionup-regulated miR-16-5p, miR-103-3p, miR-107-3p, and miR-27b-3p in plasma[141]
Fetal congenital heart defectslncRNAs ENST00000436681, ENST00000422826 are up-regulated and AA584040, AA709223 and BX478947 down-regulated in plasma[257]
Placenta accreta spectrumdown-regulated miR-139-3p, miR-196a-5p, miR-518a-3p, and miR-671-3p in serum[147]
Gestational diabetes mellitusmiR-223 and miR-23a are up-regulated in plasma[245]
Preeclampsiahsa-circ-0036877 is up-regulated in blood[223]
PreeclampsiacircCRAMP1L circulating levels are significantly lower in plasma[224]
PreeclampsiamiR-215, miR-155, miR-650, miR-210, miR-21 are up-regulated, and miR-18a, miR-19b1 down-regulated in plasma[255]
Preeclampsiahsa-miR-486-1-5p and hsa-miR-486-2-5p are up-regulated in exosomes[261]
Preeclampsiahsa-miR-210 is up-regulated in exosomes[258]
PreeclampsiamiR-15a-5p is up-regulated in exosomes[262]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Žarković, M.; Hufsky, F.; Markert, U.R.; Marz, M. The Role of Non-Coding RNAs in the Human Placenta. Cells 2022, 11, 1588.

AMA Style

Žarković M, Hufsky F, Markert UR, Marz M. The Role of Non-Coding RNAs in the Human Placenta. Cells. 2022; 11(9):1588.

Chicago/Turabian Style

Žarković, Milena, Franziska Hufsky, Udo R. Markert, and Manja Marz. 2022. "The Role of Non-Coding RNAs in the Human Placenta" Cells 11, no. 9: 1588.

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop