Literature DB >> 29302021

Long Non-Coding RNAs Serve as Diagnostic Biomarkers of Preeclampsia and Modulate Migration and Invasiveness of Trophoblast Cells.

Xiucui Luo1, Xiaoqiong Li2.   

Abstract

BACKGROUND Long non-coding RNAs (lncRNAs) have emerged as crucial regulators of tumor progression. However, the effects of lncRNAs in preeclampsia are not entirely clear. The aim of this study was to demonstrate the potential of lncRNAs to serve as biomarkers in preeclampsia. MATERIAL AND METHODS The RNA expression levels of lncRNAs (NR_027457, BC030099, AF037219, NR_024178, AF085938, G43016, G36948, NR_029420, NR_024015, AK002210, NR_026643, and AL049277) in the serum of patients with preeclampsia and in the serum of normal controls were measured by qRT-PCR. The area under the curve (AUC), the optimal cut-off values, the specificity, and the sensitivity of NR_027457, AF085938, G36948, and AK002210 were analyzed by receiver operating characteristic (ROC) curve analysis. We designed RNA interference species to suppress NR_027457 and G36948 and identified the roles of NR_027457 and G36948 in the functions of a trophoblast cell line (HTR-8/SVneo). RESULTS The qRT-PCR results indicated that NR_027457 and AF085938 were significantly up-regulated, whereas G36948 and AK002210 were significantly down-regulated in preeclampsia. We found that NR_027457, AF085938, G36948, and AK002210 had potential diagnostic value for the detection of preeclampsia. Furthermore, the levels of NR_027457, AF085938, G36948, and AK002210 in the serum of patients were significantly different before vs. after surgery. The silencing of NR_027457 inhibited the proliferation, migration, and invasion abilities of HTR-8/SVneo cells, while the silencing of G36948 promoted the proliferation, migration, and invasion abilities of HTR-8/SVneo cells. CONCLUSIONS NR_027457, AF085938, G36948, and AK002210 can serve as potential diagnostic biomarkers in preeclampsia, and NR_027457 and G36948 might be involved in the pathogenesis of preeclampsia.

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Year:  2018        PMID: 29302021      PMCID: PMC5766055          DOI: 10.12659/msm.907808

Source DB:  PubMed          Journal:  Med Sci Monit        ISSN: 1234-1010


Background

Preeclampsia, which is characterized by high blood pressure and proteinuria, is a pregnancy-specific disease that can cause a series of problems to both mother and fetus [1,2]. Without proper and timely prevention, it may progress to a worse stage known as eclampsia, which is accompanied by seizures and other severe impairments, including the development of hemolysis, elevated liver enzymes, and low platelet (HELLP) syndrome, hemorrhagic or ischemic stroke, liver damage and dysfunction, kidney injury, and acute respiratory distress syndrome (ARDS) [3-5]. Preeclampsia usually occurs 20 weeks after the beginning of pregnancy, and it can be subdivided into 2 types: that which occurs before 34 weeks of gestation is termed early onset preeclampsia, and late onset preeclampsia, which occurs from ≥34 weeks to delivery [6,7]. Preeclampsia involves multiple risk factors, such as hypertension in pregnancy, diabetes, autoimmune disorders, and previous preeclampsia [8, 9]. The identification of pregnant women at risk for preeclampsia provides an opportunity for its prevention [10]. Unfortunately, most proposed primary prevention agents, including oral antioxidants, dietary, aspirin, and activity restrictions, lack proven efficacy [11-15]. In addition, preeclampsia is a multi-system disease that is associated with adverse maternal and fetal outcomes; therefore, to avoid morbidity and mortality, we cannot misdiagnose true patients with preeclampsia according to the clinical diagnostic criteria. Research by the International Society for the Study of Hypertension in Pregnancy (ISSHP) has also found that the lack of a consensus is the major reason for the controversy regarding the counselling, management, and documentation of pregnancy outcomes [16]. Therefore, preeclampsia has been defined as both hypertension and proteinuria (defined as ≥300 mg per 24 h or a spot urine protein/creatinine ratio of ≥30 mg/mmol) [16,17]. Many studies have been published on the functions and mechanisms of preeclampsia [18-20]. A greater understanding of the genetic and molecular pathways involved in the pathogenesis of preeclampsia is essential and may provide future targets for therapeutic action. Reliable biomarkers for prediction and diagnosis would contribute to maternal health, and several promising markers have been suggested, including PlGF, PP13, endothelin-1, plasma-P-selectin, and PAPP-A [21-23]. Although preeclampsia can be diagnosed through the measurement of blood pressure and proteinuria as well as by other biochemical or biophysical markers, the expression of lncRNAs (long non-coding RNAs) and the roles they play in preeclampsia are unclear. LncRNA is defined as a non-protein coding transcript that is longer than 200 nucleotides and that functions as a regulator of gene expression; lncRNAs have vital effects on imprinting control, cell differentiation, immune responses, human diseases, and other biological processes [24,25]. An advantage to targeting lncRNAs over messenger RNAs (mRNAs) is that targeting a single lncRNA has the potential to affect multiple downstream pathways and therefore can amplify the effect of a single target [26]. Targeting multiple pathways may also lead to unwanted adverse effects, so the functions of lncRNAs should be completely characterized before they are used as therapeutic targets. Many different methods are currently being developed to silence lncRNAs in cancer, including siRNAs, antisense transcripts, and aptamers, which have potentially to be adapted for use in the treatment of preeclampsia [24,27]. Thus, we attempted to seek potential and valid lncRNAs to serve as biomarkers for the efficient and precise prediction and diagnosis of preeclampsia. Beyond that, we investigated the impact of alterations in candidate lncRNAs on cell function when their expression deviated from the normal level. The experimental results indicated that NR_027457, AF085938, G36948, and AK002210 may be potential predictive and diagnostic biomarkers for preeclampsia. Moreover, the expression changes in these lncRNAs would cause cell functional disorders.

Material and Methods

Patients and samples

Samples from patients who were diagnosed with preeclampsia were collected between 2011 and 2016 from the Lianyungang Maternal and Children’s Hospital; control samples were obtained from normal controls (pregnant women who were completely healthy) and were also provided by Lianyungang Maternal and Children’s Hospital. The patient data were fully recorded, and the samples were processed according to standard protocols. The exclusion criteria were as follows: patients with diabetes, chronic nephritis, chronic hypertension, heart diseases, autoimmune diseases, multiple pregnancies, thrombophilic conditions, vaginal delivery, fetal malformations, and HELLP syndrome. The clinical characteristics assessed at enrollment are shown in Table 1. The blood samples were centrifuged for 15 min at 3000×g at 4°C, and then the serum was collected and stored at −80°C. All protocols used in this study were accepted by the patients and were approved by the Ethics Review Board of Lianyungang Maternal and Children’s Hospital.
Table 1

The clinical characteristics assessed at enrollment.

CharacteristicPreeclampsia (n=81)No Preeclampsia (n=81)P-value
Age (years)
 ≤3557 (70.37%)59 (72.84%)0.43
 >3524 (29.63%)22 (27.16%)
BMI at enrollment26.9±1.48 (22.8–31.7)24.2±1.12 (21.4–28.6)<0.001
Blood pressure
 Systolic113±4.81 (108–119)110±2.07 (101–114)<0.001
 Diastolic69±4.74 (62–73)66±4.43 (61–70)<0.001
Proteinuria2.7±0.85 (0.3–6.4)0.12±0.05 (0–0.3)<0.001
Gestational age (years)33.2±2.69 (27–38)33.3±1.88 (26–38)0.78
Previous pregnancy15 (19.75%)19 (23.46%)0.28

RNA extraction and quantitative real-time PCR (qPCR)

Total RNA was isolated using TRIzol reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The cDNA was synthesized using Oligod (T)18 primer, and the synthesis was catalyzed by PrimeScript® RT reagent Kit (Perfect Real Time) (TaKaRa, Japan). The primers used in the qPCR experiments are shown in Table 2. The reaction mixture contained 10 μL of 2×SYBR Premix Ex Taq™ (TaKaRa, Japan), 0.4 μL of 50×ROX Reference Dye II, 0.5 μL of 10 μM forward and reverse primers, 2 μL of template cDNA and ddH2O in a final volume of 20 μL. The qPCR reaction was performed with a denaturation step of 10 min at 95°C; followed by 35 cycles at 95°C (10 s), 60°C (40 s), 72°C (30 s), and a final step at 72°C for 10 min. The relative lncRNA expression levels were calculated using the 2−ΔΔCt method [28].
Table 2

The primer sequences of the related lncRNAs.

GeneSequence of primers (5′-3′)
NR_027457F: GTCCTTTGCAGCAACATGGAR: TTCAACCCATGCACCTCTCT
BC030099F: CAGCTGAGCGGGACATTTACR: GGTCTGAAAGGATGGAGGCT
AF037219F: TGAAGCTGTTGAGGGAGGAGR: CCCTCCACCTTCTTTCCCAT
NR_024178F: ACAGGCTAGGAGAGAAGGGAR: CTTAAGCATCTTCACGGCCC
AF085938F: GAGCAACACAAGCAGCATCTR: TGAGAGGATATTGTGGCCGA
G43016F: TCAGTAATGCTCTAGTCCAGGGR: ACAGGTTGCTTGGTCTCAC
G36948F: AGACCTACCCTCGACCCAGR: TGGGAGTTCTGCTGGATTCA
NR_029420F: GAGACCTTGGCCAAACACAGR: TTGTCAGCTTTCTTGTGGGC
NR_024015F: CGCCCATTCTGCTCTTCTTCR: GGAGGTTTCAGAGATGGGCT
AK002210F: CTACCCCAGCTCGCATCATAR: TGACTTCGATCTGCCCACTT
NR_026643F: CTGGTACTGGGATTTGGGGTR: TGCTGACCTGGACAAGAGAG
AL049277F: AGCCTTTCCACTCCCAACTTR: TCTCCCCAGACTTGCCAAAC
GAPDHF: TATGATGATATCAAGAGGGTAGTR: TGTATCCAAACTCATTGTCATAC

Cell culture and siRNA transfection

The human immortalized first trimester trophoblast cell line HTR8/SVneo was used in the Transwell assay as previously depicted [29]. Briefly, HTR8/SVneo cells were cultured in RPMI 1640 medium (Gibco, Thermo Fisher Scientific, USA) with 10% fetal bovine serum (Gibco, Thermo Fisher Scientific, USA) and were maintained in a humid atmosphere at 5% CO2 and 37°C. The cells were incubated in serum-free RPMI 1640 medium for different time intervals for serum starvation. Torin1 stimulation was performed by incubating the cells in fresh medium containing different concentrations of Torin1 for 24 h. Transfection of small interfering RNA (siRNA) was performed using Lipofectamine 2000 (Thermo Fisher Scientific, USA) according to the manufacturer’s instructions.

Cell proliferation assay

An MTT assay was performed to evaluate the effects of si-lncRNA as previously reported [30]. Briefly, the cells were harvested with trypsin and seeded at a concentration of 2×105 cells/well in a 24-well plate. Then, 20 μl of MTT reagent was added to each well, and the cells were incubated at 37°C for 4 h, followed by the addition of 150 μl dimethylsulfoxide (DMSO). The absorbance was determined sequentially at 48 h using a microplate reader at 490 nm (Sunrise™; Tecan Group Ltd., Männedorf, Switzerland).

Cell migration and invasion assay

A Transwell assay was performed to examine the invasion and migration abilities of cells transfected with si-NR_027457, si-AF085938, si-G36948, or si-AK002210. For the invasion assay, 2×105 cells were suspended in 200 μl medium and then plated into the upper chamber of the Transwell plate (8 μm pore size; Corning Inc.; NY, USA), which was coated with Matrigel. Then, 0.5 ml medium supplemented with 10% FBS was added to the lower chamber. After incubation at 37°C for 24 h, a portion of cells remained on the surface of the upper membrane; these cells were removed with a cotton swab, and the cells on the surface of the reverse membrane were stained with crystal violet. The stained cells were examined by confocal microscopy, and the numbers of cells were calculated in at least 5 random images, including the upper, lower, left, right, and middle areas of each image. The general manipulation steps of the migration assay were the same as those described above but without Matrigel.

Statistical analysis

All statistical analysis was performed with SPSS version 19.0 (SPSS Inc, Chicago, IL, USA). The t test was used to detect variations in the data between patients and normal controls. Receiver operating characteristic (ROC) curves were generated to estimate the utility of each parameter as a tool for predicting preeclampsia, and the area under the ROC curves and the related parameters were also calculated in order to analyze the diagnostic points. The log-rank test was used to analyze survival, and the Kaplan-Meier method was used to plot the survival curves. In all analyses, p-value<0.05 was considered statistically significant.

Results

The expression levels of 12 lncRNAs in the serum of patients with preeclampsia

This study first determined the genome-wide lncRNA expression patterns in placentas derived from patients with preeclampsia using a Human LncRNA Microarray [27]. The results showed that clusters of lncRNAs were aberrantly expressed in placentas from patients with preeclampsia. Simultaneously, this study also demonstrated that LOC391533, LOC284100, and CEACAMP8 might contribute to the underlying mechanism of preeclampsia. In our study, we randomly selected relatively distinct lncRNAs, such as NR_027457, BC030099, AF037219, NR_024178, AF085938, G43016, G36948, NR_029420, NR_024015, AK002210, NR_026643, and AL049277. In this research, serum samples from all 81 patients with preeclampsia were obtained, and the expression levels of 12 various lncRNAs were detected by qRT-PCR according to the method described in a previous study. Compared with the normal controls, 4 lncRNAs were found to be differentially expressed in the serum samples of patients with preeclampsia; these lncRNAs were NR_027457, AF085938, G36948, and AK002210. The qRT-PCR results indicated that NR_027457 and AF085938 were significantly up-regulated, while G36948 and AK002210 were significantly down-regulated, and no significant difference was observed in the remainder of the lncRNAs that were tested (Figure 1A–1C).
Figure 1

The expression levels of 12 different lncRNAs in the serum samples of patients with preeclampsia were examined by qRT-PCR. (A–C) In all, 81 serum samples were collected from patients with preeclampsia and from normal controls. The statistical results for the expression levels of lncRNA were demonstrated in healthy controls and in patients with preeclampsia, and each lncRNA is presented in an individual plot. The X axis shows the categories, the Y axis represents the relative expression levels of the lncRNAs (2−ΔΔCt), and ns indicates no significance (* P<0.05, ** P<0.01, *** P<0.001).

The correlation between the expression levels of 4 lncRNAs and preeclampsia

The differential expression of the lncRNAs NR_027457, AF085938, G36948, and AK002210 was verified by qRT-PCR, suggesting that they may have potential value as diagnostic markers of preeclampsia; moreover, the results clearly confirmed this via the ROC curves and the area under the ROC curves (AUC) of NR_027457, AF085938, G36948, and AK002210 (Figure 2A). Among these, the AUCs of AF085938 (AUC=0.7673, P<0.001), G36948 (AUC=0.7956, P<0.001), and AK002210 (AUC=0.7575, P<0.001) were larger than 0.75, which indicated that the performance of these 3 lncRNAs can be considered “fair” in the prediction of preeclampsia (Figure 2A). However, the results of NR_027457 (AUC=0.5633, P=0.164) were not as good as those for the previously mentioned 3 lncRNAs (Figure 2A). In addition, the Kaplan-Meier analysis showed that patients with higher expression of NR_027457 and AF085938 would be more likely to experience preeclampsia at an earlier time than patients who expressed lower levels; patients with lower expression of G36948 and AK002210 would also be more likely to experience preeclampsia at an earlier time than patients with higher levels. In summary, patients with high expression levels of NR_027457 and AF085938 are more likely to relapse than patients with low expression levels of NR_027457 and AF085938; patients with low expression levels of G36948 and AK002210 are more likely to relapse than those patients with high expression levels of G36948 and AK002210. Therefore, NR_027457, AF085938, G36948 and AK002210 indicate a good prognosis and have the potential to be valid markers for the prediction of preeclampsia (Figure 2B).
Figure 2

The good prognostic effects of NR_027457, AF085938, G36948, and AK002210 in patients with preeclampsia. (A) The ROC curve for the 4 lncRNAs in their ability to predict preeclampsia. (B) Kaplan-Meier curve for the same lncRNAs in patients with a high or a low expression level of a particular lncRNA.

The effects of lncRNA NR_027457, AF085938, G36948, and AK002210 knockdown on cell proliferation

The patient-derived serum samples were tested, and the results showed that the lncRNAs NR_027457, AF085938, G36948, and AK002210 had high potential to be valid markers for the prediction of preeclampsia. For further research and for the validation of the availability of selecting these lncRNAs as markers, in vitro experiments were conducted. SVneo cells were transfected with the synthesized interfering oligonucleotide sequences si-NR_027457, si-AF085938, si-G36948, and si-AK002210 or with the corresponding control siRNA. As the results showed, the expression of all 4 lncRNAs in SVneo cells transfected with siRNAs was dramatically decreased compared with the control groups transfected with the negative control (si-NC) (Figure 3A). The results of the MTT assay showed that the proliferation rate of si-NR_027457- and si-AF085938-transfected cells was significantly inhibited, which suggests that the silencing of NR_027457 and AF085938 suppressed the proliferation of SVneo cells. In contrast, the proliferation rate of si-G36948- and si-AK002210-transfected cells was significantly promoted, which suggests that the silencing of G36948 and AK002210 promotes the proliferation of SVneo cells (Figure 3B). In summary, NR_027457, AF085938, G36948, and AK002210 play roles in cell proliferation.
Figure 3

The silencing of NR_027457, AF085938, G36948, and AK002210 affected the proliferation abilities of SVneo cells. SVneo cells were transfected with negative control siRNAs (si-NC), NR_027457 siRNAs (si-NR_027457), AF085938 siRNAs (si-AF085938), G36948 siRNAs (si-G36948), or AK002210 siRNAs (si-AK002210). (A) The expression levels of NR_027457, AF085938, G36948 and AK002210 were detected by qRT-PCR assays (** P<0.01, *** P<0.001). (B) The proliferation abilities were measured by MTT assay in treated SVneo cells (* P<0.05, ** P<0.01, *** P<0.001).

The effects of lncRNA NR_027457, AF085938, G36948, and AK002210 knockdown on cell invasion and migration

To explore the effects of NR_027457, AF085938, G36948, and AK002210 on the invasion and migration abilities of the cells, a Transwell assay was performed using SVneo cells transfected with si-NR_027457, si-AF085938, si-G36948, and si-AK002210 or with the negative control siRNA. The results showed that the knockdown of NR_027457 and AF085938 significantly suppressed the cell migration and invasion abilities in vitro (Figure 4A, 4B), while the silencing of G36948 and AK002210 in SVneo cells significantly promoted the cell migration and invasion abilities (Figure 4C, 4D). These results suggest that NR_027457, AF085938, G36948, and AK002210 act as important regulators in the SVneo cell line.
Figure 4

The results of the Transwell assays revealed that the silencing of NR_027457, AF085938, G36948, and AK002210 suppressed the cell migration and invasion capabilities in vitro. Images obtained from the Transwell assay illustrate the migratory and invasive abilities of treated cells compared with those of cells treated with si-control; the statistical results are shown alongside the images. (A) The result of si-NR_027457 and the corresponding control. (B) The result of si-AF085938 and the corresponding control. (C) The result of si-G36948 and the corresponding control. (D) The result of si-AK002210 and the corresponding control (* P<0.05, ** P<0.01, *** P<0.001).

Discussion

Previous studies on the prediction, diagnosis, and treatment of preeclampsia have mainly concentrated on physiological and biochemical indexes [24,31-33]. However, no single biomarker can be regarded as a standard and valid diagnostic marker [34,35]. Some new predictive markers and therapeutics have been explored, and angiogenic factors, including soluble fms-like tyrosine kinase 1, an endogenous vascular endothelial growth factor inhibitor, have been implicated [36-39]. We attempted and managed to solve this problem by other approaches using lncRNAs as new diagnostic targets. LncRNAs have been demonstrated to be reliable biomarkers and are commonly used as biomarkers for the prediction and diagnosis of cancers [24,40,41]. To investigate the roles of lncRNAs in preeclampsia, above all, we explored numerous prior studies of lncRNA and preeclampsia to find some clues. The research by X He et al. provided a series of lncRNAs that were up-regulated or down-regulated in patients who were clinically diagnosed with preeclampsia by microarray [27]. From those lncRNAs, we selected NR_027457, BC030099, AF037219, NR_024178, AF085938, G43016, G36948, NR_029420, NR_024015, AK002210, NR_026643, and AL049277 as our research objects. To confirm the different expression levels of these lncRNAs, serum samples were collected from patients with preeclampsia and from healthy controls and were tested by qRT-PCR. The results showed that the expression levels of NR_027457, AF085938, G36948, and AK002210 in the serum derived from patients with preeclampsia deviated from their normal expression levels, in accordance with a previous study [27]. Then, the data were further analyzed using the ROC curve and Kaplan-Meier analysis. As we expected, the AUC of these 4 lncRNAs were all larger than 0.5, and the AUC of AF085938, G36948, and AK002210 were even larger than 0.75 according to the ROC curves. Moreover, the significant potential of these lncRNAs to be diagnostic markers of preeclampsia was also shown by the Kaplan-Meier analysis. Since most diseases involve the dysfunction of cells, and preeclampsia is no exception, we sought to determine the roles of these 4 lncRNAs in cells that may be affected in preeclamptic patients by performing in vitro cell experiments (MTT analysis and Transwell assay). The expression of these 4 lncRNAs was knocked down in vitro by transfection of si-lncRNAs. The results showed that in the siRNA-transfected cells, the capacity of the cells to proliferate, migrate, and invade was remarkably affected. A large number of studies have drawn similar conclusions, and the lncRNA SPRY4-IT1 was demonstrated to modulate proliferation, migration, apoptosis, and network formation in the trophoblast cell line HTR-8SV/neo [42]. The lncRNA MEG3 was found to promote apoptosis and suppress the migration of trophoblast cells [43]. The lncRNA CCAT1 promotes colon cancer cell proliferation and invasion [44]. All these results indicate that NR_027457, AF085938, G36948, and AK002210 can be selected as biomarkers for the diagnosis of preeclampsia. Although the results were promising, some issues still need to be resolved. In vitro experiments have demonstrated that these 4 lncRNAs play roles in cell proliferation, migration, and invasion, but no in vivo data were obtained; therefore, the mechanism is still unclear. In addition, the number of included patients was too small, and more data are required to validate the conclusion of this study. Still, this research may provide a new perspective and a useful reference in the diagnosis of preeclampsia.

Conclusions

We demonstrated that NR_027457, AF085938, G36948, and AK002210 may serve as potential diagnostic biomarkers for preeclampsia. However, further studies are needed to validate this observation on the prognostic and therapeutic effects of NR_027457, AF085938, G36948, and AK002210 in preeclampsia, and in vivo studies are also needed. Moreover, it will be necessary to further explore the functions and mechanisms of NR_027457, AF085938, G36948, and AK002210 in preeclampsia.
  44 in total

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Review 2.  LncRNA: a link between RNA and cancer.

Authors:  Guodong Yang; Xiaozhao Lu; Lijun Yuan
Journal:  Biochim Biophys Acta       Date:  2014-08-23

Review 3.  Hypoxia and sFlt-1 in preeclampsia: the "chicken-and-egg" question.

Authors:  S Ananth Karumanchi; Yuval Bdolah
Journal:  Endocrinology       Date:  2004-11       Impact factor: 4.736

Review 4.  Predictive biomarkers of pre-eclampsia and effectiveness of preventative interventions for the disease.

Authors:  Annalisa Inversetti; Maddalena Smid; Massimo Candiani; Maurizio Ferrari; Silvia Galbiati
Journal:  Expert Opin Biol Ther       Date:  2014-04-26       Impact factor: 4.388

Review 5.  Pre-eclampsia and future cardiovascular risk among women: a review.

Authors:  Raheel Ahmed; Joseph Dunford; Roxana Mehran; Stephen Robson; Vijay Kunadian
Journal:  J Am Coll Cardiol       Date:  2014-03-05       Impact factor: 24.094

Review 6.  Immunomodulatory role of vitamin D in the pathogenesis of preeclampsia.

Authors:  Tyler A Smith; Daniel R Kirkpatrick; Oormila Kovilam; Devendra K Agrawal
Journal:  Expert Rev Clin Immunol       Date:  2015-06-22       Impact factor: 4.473

7.  Down-regulated long non-coding RNA MEG3 and its effect on promoting apoptosis and suppressing migration of trophoblast cells.

Authors:  Yuanyuan Zhang; Yanfen Zou; Wenqi Wang; Qing Zuo; Ziyan Jiang; Ming Sun; Wei De; Lizhou Sun
Journal:  J Cell Biochem       Date:  2015-04       Impact factor: 4.429

8.  Maternal morbidity associated with early-onset and late-onset preeclampsia.

Authors:  Sarka Lisonkova; Yasser Sabr; Chantal Mayer; Carmen Young; Amanda Skoll; K S Joseph
Journal:  Obstet Gynecol       Date:  2014-10       Impact factor: 7.661

9.  C-Myc-activated long noncoding RNA CCAT1 promotes colon cancer cell proliferation and invasion.

Authors:  Xiaolu He; Xueming Tan; Xiang Wang; Heiying Jin; Li Liu; Limei Ma; Hong Yu; Zhining Fan
Journal:  Tumour Biol       Date:  2014-09-04

10.  Hypoxia-Induced Activation of JAK/STAT3 Signaling Pathway Promotes Trophoblast Cell Viability and Angiogenesis in Preeclampsia.

Authors:  Chengfang Xu; Xuejiao Li; Peiling Guo; Jia Wang
Journal:  Med Sci Monit       Date:  2017-10-14
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  10 in total

1.  The expression profile of plasmatic exosomal lncRNAs in early-onset preeclampsia by sequencing.

Authors:  Xiaoqian Fu; Min Wu; Yue Chen; Liling Li; Hongyu Yin; Kaili Liang; Yachang Zeng
Journal:  Am J Transl Res       Date:  2022-06-15       Impact factor: 3.940

Review 2.  Epigenetics Beyond Fetal Growth Restriction: A Comprehensive Overview.

Authors:  Noemi Salmeri; Ilma Floriana Carbone; Paolo Ivo Cavoretto; Antonio Farina; Danila Morano
Journal:  Mol Diagn Ther       Date:  2022-08-26       Impact factor: 4.476

3.  Circulating lncRNA BC030099 Increases in Preeclampsia Patients.

Authors:  Yuhong Sun; Yan Hou; Nan Lv; Qian Liu; Nan Lin; Shuyu Zhao; Xiaodan Chu; Xuan Chen; Guobin Cheng; Peiling Li
Journal:  Mol Ther Nucleic Acids       Date:  2019-02-01

4.  Long Noncoding RNA VIM Antisense RNA 1 (VIM-AS1) Plays an Important Role in Development of Preeclampsia by Regulation of Epithelial Mesenchymal Transition.

Authors:  Xuehui Zhao; Xiaoying Jiang; Zongyin Liu; Mi Zhou; Juan Zhang; Xiaojing Wang; Xiaowen Li
Journal:  Med Sci Monit       Date:  2019-11-05

5.  An integrative bioinformatics analysis of microarray data for identifying hub genes as diagnostic biomarkers of preeclampsia.

Authors:  Keling Liu; Qingmei Fu; Yao Liu; Chenhong Wang
Journal:  Biosci Rep       Date:  2019-09-03       Impact factor: 3.840

6.  Placental Microarray Profiling Reveals Common mRNA and lncRNA Expression Patterns in Preeclampsia and Intrauterine Growth Restriction.

Authors:  Diana Medina-Bastidas; Mario Guzmán-Huerta; Hector Borboa-Olivares; César Ruiz-Cruz; Sandra Parra-Hernández; Arturo Flores-Pliego; Ivan Salido-Guadarrama; Lisbeth Camargo-Marín; Eliakym Arambula-Meraz; Guadalupe Estrada-Gutierrez
Journal:  Int J Mol Sci       Date:  2020-05-20       Impact factor: 5.923

7.  Increased LINC00922 in preeclampsia regulates the proliferation, invasion, and migration of placental trophoblast cells.

Authors:  Chengzhen Gao; Hui Yang; Fei Xia
Journal:  Ann Transl Med       Date:  2021-10

8.  The Gut Microbiota Dysbiosis in Preeclampsia Contributed to Trophoblast Cell Proliferation, Invasion, and Migration via lncRNA BC030099/NF-κB Pathway.

Authors:  Rong Tang; Gong Xiao; Yu Jian; Qiongjing Yuan; Chun Jiang; Wei Wang
Journal:  Mediators Inflamm       Date:  2022-06-24       Impact factor: 4.529

9.  Distinct gene expression patterns for CD14++ and CD16++ monocytes in preeclampsia.

Authors:  Vishnyakova Polina; Kuznetsova Maria; Poltavets Anastasiya; Fomina Mariia; Kiseleva Viktoriia; Muminova Kamilla; Potapova Alena; Khodzhaeva Zulfiya; Pyregov Alexey; Trofimov Dmitry; Elchaninov Andrey; Sukhikh Gennady; Fatkhudinov Timur
Journal:  Sci Rep       Date:  2022-09-14       Impact factor: 4.996

Review 10.  Roles of noncoding RNAs in preeclampsia.

Authors:  Ningxia Sun; Shiting Qin; Lu Zhang; Shiguo Liu
Journal:  Reprod Biol Endocrinol       Date:  2021-07-02       Impact factor: 5.211

  10 in total

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