Placental expression of lysophosphatidic acid receptors in normal pregnancy and preeclampsia

Circ_0007611 modulates the miR-34c-5p/LPAR2 cascade to suppress proliferation and enhance apoptosis of HTR-8/SVneo cells

INTRODUCTION

The aberrant biological behaviors of trophoblast cells actively take part in the pathogenesis of preeclampsia (PE). Herein, we defined the action of the circular RNA (circRNA) circ_0007611 on trophoblast cell apoptosis and growth to understand its role in PE.

METHODS

Expression of circ_0007611, miR-34c-5p and lysophosphatidic acid receptor 2 (LPAR2) mRNA was analyzed by qPCR. LPAR2 protein was determined by western blotting. Cell proliferation was analyzed by EdU assay. We assessed apoptosis through flow cytometry and analysis of caspase3 activity and apoptosis-related marker proteins. The binding of miR-34c-5p and circ_0007611 or LPAR2 was verified by dual-luciferase and pull-down assays.

RESULTS

Circ_0007611 and LPAR2 levels were augmented, while miR-34c-5p was diminished in blood samples of PE. Circ_0007611 deficiency repressed cell apoptosis and enhanced the growth of HTR-8/SVneo cells. Circ_0007611 interacted with miR-34c-5p, and miR-34c-5p depletion reversed circ_0007611 deficiency-induced HTR-8/SVneo cell apoptotic inhibition and growth enhancement. MiR-34c-5p targeted LPAR2, and circ_0007611 affected LPAR2 expression via miR-34c-5p competition. Circ_0007611 deficiency-induced HHTR-8/SVneo cell apoptotic inhibition and growth enhancement were also counteracted by LPAR2 overexpression.

DISCUSSION

Circ_0007611 modulates the miR-34c-5p/LPAR2 cascade to enhance apoptosis and inhibit proliferation in HTR-8/SVneo cells, thereby contributing to the progression of PE.

Upregulation of autotaxin by oxidative stress via Nrf2 activation: A novel insight into the compensation mechanism in preeclamptic placenta

The response of autotaxin (ATX)-lysophosphatidic acid (LPA) signaling system to placental oxidative stress (OS) and its significance to preeclampsia were investigated. For this purpose, oxidative stress index (OSI) and ATX levels were measured in the serum of pregnant women with preeclampsia. The expression levels of ATX and LPA receptors were assessed in trophoblast cells under high OS and glucose deprivation/re-oxygenation (OGD/R) conditions, with particular emphasis on the antioxidative nuclear factor erythroid 2-related factor 2 (NRF2) pathway. The influence of ATX-LPA signaling on cell migration was also evaluated using the wound healing assay. ATX concentrations and OSI in the serum were found to be elevated in preeclamptic women. The serum ATX levels were also positively correlated with OSI. Trophoblast cells responded to OS by increasing ATX mRNA expression concomitantly with intranuclear translocation of Nrf2, whereas inhibition of Nrf2 activation reverted this effect. The ATX-LPA signaling pathway facilitated trophoblast cell motility after Nrf2 activation. In conclusion, OS accumulation in preeclamptic placenta may activate the ATX-LPA system in trophoblasts via the Nrf2 pathway to sustain trophoblast functionality.

Serum protein profile analysis via label-free quantitation proteomics in patients with early-onset preeclampsia

BACKGROUND

Preeclampsia (PE) is a serious pregnancy complication, resulting in potentially life-threatening conditions for both mother and foetus. It is worth noting that early-onset PE has become a great challenge for clinicians due to its complex manifestation, rapid progression and serious complications. This study aims to investigate differential serum proteome profiles in patients with early-onset PE.

METHODS

Each serum sample was separated using a nanoliter flow rate Easy-nLC chromatography system. Then the samples were analysed by mass spectrometry. Bioinformatics analyses were conducted to analyse the functional categories or signal transduction pathways for differentially abundant proteins. Key proteins identified by mass spectrometry were verified by ELISA.

RESULTS

We found 30 and 34 proteins were upregulated and downregulated in early-onset PE patients (n = 3) vs controls (n = 3), respectively. Functional enrichment analysis revealed differentially expressed proteins related to the immune response and regulation of peptidase activity. ELISA confirmed that there were lower CSH1 levels and higher LPA concentrations in the serum samples of early-onset PE patients (n = 22) than in healthy controls (n = 19) (p < 0.05 for CSH1 and p < 0.001 for LPA).

CONCLUSIONS

This study revealed the critical features of serum proteins in early-onset PE patients. LPA and CSH1 may serve as biomarkers for early-onset PE diagnosis and therapy.

Expression of lysophosphatidic acid receptors in the rat uterus: cellular distribution of protein and gestation-associated changes in gene expression

Though lysophosphatidic acid (LPA) shows a variety of regulatory roles in reproduction, its action mechanisms in the gestational organs are still largely unknown. We here characterized cellular distribution of its six kinds of specific receptors (LPA1-6) in rat uteri by immunohistochemistry and quantitatively analyzed changes in Lpar1-6 mRNAs expression throughout pregnancy. Among LPA1-6, evident expression of LPA3, LPA4, and LPA6 was immunologically detected and less expression of immunoreactive LPA1 and LPA2 was also found. Luminal and glandular epithelial cells, stromal cells, and myometrial cells are sites of positive immunoreactions, and they are all likely to express three or more subtypes. All of Lpar1-6 mRNAs were expressed, and their alterations were variable depending on subtypes and gestational age. The present information suggests that diverse actions of LPA in the uterus involve varied expression of LPA receptors dependent on tissue/cell types, receptor subtype(s), and organ reproductive states and helps to understand uterine biology of LPA.

G-Protein Coupled Receptor Dysregulation May Play Roles in Severe Preeclampsia-A Weighted Gene Correlation Network Analysis of Placental Gene Expression Profile

Preeclampsia is one of the major hypertensive diseases of pregnancy. Genetic factors contribute to abnormal placentation. The inadequate transformation of cytotrophoblasts causes failure of maternal spiral arteries’ remodeling and results in narrow, atherotic-prone vessels, leading to relative placental ischemia. This study aims to explore the possibility of identifying dysregulated gene networks that may offer a potential target in the possible prevention of preeclampsia. We performed a weighted gene correlated network analysis (WGCNA) on a subset of gene expression profiles of placental tissues from severe preeclamptic pregnancies. We identified a gene module (number of genes = 402, GS = 0.35, p = 0.02) enriched for several G-protein-coupled receptor (GPCR)-related genes with significant protein–protein molecular interaction (number of genes = 38, FDR = 0.0007) that may play key roles in preeclampsia. Some genes are noted to play key roles in preeclampsia, including LPAR4/5, CRLR, NPY, TACR1/2, and SFRP4/5, whose functions generally relate to angiogenesis and vasodilation or vasoconstriction. Other upregulated genes, including olfactory and orexigenic genes, serve limited functions in the disease pathogenesis. Altogether, this study shows the utility of WGCNA in exploring possible new gene targets, and additionally reinforces the feasibility of targeting GPCRs that may offer intervention against development and disease progression among severe preeclampsia patients.

Potential genetic biomarkers predict adverse pregnancy outcome during early and mid-pregnancy in women with systemic lupus erythematosus

BACKGROUND

Effectively predicting the risk of adverse pregnancy outcome (APO) in women with systemic lupus erythematosus (SLE) during early and mid-pregnancy is a challenge. This study was aimed to identify potential markers for early prediction of APO risk in women with SLE.

METHODS

The GSE108497 gene expression dataset containing 120 samples (36 patients, 84 controls) was downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis (WGCNA) was performed, and differentially expressed genes (DEGs) were screened to define candidate APO marker genes. Next, three individual machine learning methods, random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator, were combined to identify feature genes from the APO candidate set. The predictive performance of feature genes for APO risk was assessed using area under the receiver operating characteristic curve (AUC) and calibration curves. The potential functions of these feature genes were finally analyzed by conventional gene set enrichment analysis and CIBERSORT algorithm analysis.

RESULTS

We identified 321 significantly up-regulated genes and 307 down-regulated genes between patients and controls, along with 181 potential functionally associated genes in the WGCNA analysis. By integrating these results, we revealed 70 APO candidate genes. Three feature genes, SEZ6, NRAD1, and LPAR4, were identified by machine learning methods. Of these, SEZ6 (AUC = 0.753) showed the highest in-sample predictive performance for APO risk in pregnant women with SLE, followed by NRAD1 (AUC = 0.694) and LPAR4 (AUC = 0.654). After performing leave-one-out cross validation, corresponding AUCs for SEZ6, NRAD1, and LPAR4 were 0.731, 0.668, and 0.626, respectively. Moreover, CIBERSORT analysis showed a positive correlation between regulatory T cell levels and SEZ6 expression (P < 0.01), along with a negative correlation between M2 macrophages levels and LPAR4 expression (P < 0.01).

CONCLUSIONS

Our preliminary findings suggested that SEZ6, NRAD1, and LPAR4 might represent the useful genetic biomarkers for predicting APO risk during early and mid-pregnancy in women with SLE, and enhanced our understanding of the origins of pregnancy complications in pregnant women with SLE. However, further validation was required.

Comprehensive transcriptome mining identified the gene expression signature and differentially regulated pathways of the late-onset preeclampsia

Preeclampsia (PE) is categorized as a pregnancy-related hypertensive disorder and is a serious concern in pregnancies. Several factors, including genetic factors (placenta gene expression, and imprinting), oxidative stress, the inaccurate immune response of the mother, and the environmental factors are responsible for PE development, but still, the exact mechanism of the pathogenesis has remained unknown. The main aim of the present study is to identify the gene expression signature in placenta tissue, to unveil disease etiology mechanisms. The GEO, PubMed, and ArrayExpress databases have selected to identify gene expression datasets on placenta samples of both preeclampsia and the normotensive controls. A comprehensive gene expression meta-analysis of fourteen publicly available microarray data of preeclampsia disease has performed to identify gene expression signature and responsible biological pathways and processes. Using two different meta-analysis pipeline (in-house and INMEX) we have identified a total of 1234 differentially expressed genes (DEGs) with in-house method, including 713 overexpressed and 356 under-expressed genes whereas 272 DEGs (131 over and 141 under-expressed) have identified with INMEX, across PEs and healthy controls. Comprehensive functional enrichment and pathway analysis was performed by EnrichR library, whic revealed "Asparagine N-linked glycosylation Homo sapiens", "Nef and signal transduction", "Hemostasis", and "immune system" among the most enriched terms. The present study sets out to explain a novel database of candidate genetic markers and biological pathways that play a critical role in PE development, which might aid in the identification of diagnostic, prognostic, and therapeutic informative molecules.

The transcriptome-wide association search for genes and genetic variants which associate with BMI and gestational weight gain in women with type 1 diabetes

BACKGROUND

Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes; however, the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG.

METHODS

We have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1 Mb around identified loci) with the mentioned phenotypes.

RESULTS

In Analysis 1 we have found 175 BMI associated genes and 19 variants (p < 10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p = 3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p < 10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p = 9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR < 0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort.

CONCLUSIONS

Here, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.

Prediction of preeclampsia risk in first time pregnant women: Metabolite biomarkers for a clinical test

Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality. Accurate prediction of preeclampsia risk would enable more effective, risk-based prenatal care pathways. Current risk assessment algorithms depend on clinical risk factors largely unavailable for first-time pregnant women. Delivering accurate preeclampsia risk assessment to this cohort of women, therefore requires for novel biomarkers. Here, we evaluated the relevance of metabolite biomarker candidates for their selection into a prototype rapid, quantitative Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) based clinical screening assay. First, a library of targeted LC-MS/MS assays for metabolite biomarker candidates was developed, using a medium-throughput translational metabolomics workflow, to verify biomarker potential in the Screening-for-Pregnancy-Endpoints (SCOPE, European branch) study. A variable pre-selection step was followed by the development of multivariable prediction models for pre-defined clinical use cases, i.e., prediction of preterm preeclampsia risk and of any preeclampsia risk. Within a large set of metabolite biomarker candidates, we confirmed the potential of dilinoleoyl-glycerol and heptadecanoyl-2-hydroxy-sn-glycero-3-phosphocholine to effectively complement Placental Growth Factor, an established preeclampsia biomarker, for the prediction of preeclampsia risk in first-time pregnancies without overt risk factors. These metabolites will be considered for integration in a prototype rapid, quantitative LC-MS/MS assay, and subsequent validation in an independent cohort.

Signalling by lysophosphatidate and its health implications

Extracellular lysophosphatidate (LPA) signalling is regulated by the balance of LPA formation by autotaxin (ATX) versus LPA degradation by lipid phosphate phosphatases (LPP) and by the relative expressions of six G-protein-coupled LPA receptors. These receptors increase cell proliferation, migration, survival and angiogenesis. Acute inflammation produced by tissue damage stimulates ATX production and LPA signalling as a component of wound healing. If inflammation does not resolve, LPA signalling becomes maladaptive in conditions including arthritis, neurologic pain, obesity and cancers. Furthermore, LPA signalling through LPA1 receptors promotes fibrosis in skin, liver, kidneys and lungs. LPA also promotes the spread of tumours to other organs (metastasis) and the pro-survival properties of LPA explain why LPA counteracts the effects of chemotherapeutic agents and radiotherapy. ATX is secreted in response to radiation-induced DNA damage during cancer treatments and this together with increased LPA1 receptor expression leads to radiation-induced fibrosis. The anti-inflammatory agent, dexamethasone, decreases levels of inflammatory cytokines/chemokines. This is linked to a coordinated decrease in the production of ATX and LPA1/2 receptors and increased LPA degradation through LPP1. These effects explain why dexamethasone attenuates radiation-induced fibrosis. Increased LPA signalling is also associated with cardiovascular disease including atherosclerosis and deranged LPA signalling is associated with pregnancy complications including preeclampsia and intrahepatic cholestasis of pregnancy. LPA contributes to chronic inflammation because it stimulates the secretion of inflammatory cytokines/chemokines, which increase further ATX production and LPA signalling. Attenuating maladaptive LPA signalling provides a novel means of treating inflammatory diseases that underlie so many important medical conditions.