RNA Sequencing of Decidua Reveals Differentially Expressed Genes in Recurrent Pregnancy Loss

Possible contributions of fibrogenesis to recurrent miscarriages - A transcriptome analysis

Recurrent miscarriages (RM) generally refer to two or more consecutive pregnancy losses. The risk of miscarriages grows with its frequency of occurrences, so as the future obstetric complications or longer-term health problems for patients. Most previous researches sought to discover the etiology of RM by making comparisons between patients with RM and fertile women. Our study collected decidua tissues from patients with RM and single miscarriage (SM) for transcriptome sequencing analysis and aimed at identifying vital factors contributing to additional miscarriages after previous miscarriage. Between the RM and SM group, a total of 122 differentially expressed genes (DEGs) were detected and pathways associated with cell adhesion and ECM remodeling were particularly enriched in the RM group, which indicated abnormally activated fibrogenesis process. Particularly, the enhancement of ITGB6, EGFLAM and COL3A1 in the RM group were validated by RT-qPCR. Our study discovered that fibrogenesis, which might be caused by intrauterine manipulation, could lead to recurrent miscarriages after a previous miscarriage. Therefore, we encourage higher attention to thorough prevention and prompt remedies towards fibrotic disorders related diseases.

Identification of hub genes in placental dysfunction and recurrent pregnancy loss through transcriptome data mining: A meta-analysis

Recurrent pregnancy loss (RPL) is a condition characterized by the loss of two or more pregnancies before 20 weeks of gestation. The causes of RPL are complex and can be due to a variety of factors, including genetic, immunological, hormonal, and environmental factors. This transcriptome data mining study was done to explore the differentially expressed genes (DEGs) and related pathways responsible for pathogenesis of RPL using an Insilco approach. RNAseq datasets from the Gene Expression Omnibus (GEO) database was used to extract RNAseq datasets of RPL. Meta-analysis was done by ExpressAnalyst. The functional and pathway enrichment analysis of DEGs were performed using KEGG and BINGO plugin of Cytoscape software. Protein-protein interaction was done using STRING and hub genes were identified. A total of 91 DEGs were identified, out of which 10 were downregulated and 81 were upregulated. Pathway analysis indicated that majority of DEGs were enriched in immunological pathways (IL-17 signalling pathway, TLR-signalling pathway, autoimmune thyroid disease), angiogenic VEGF-signalling pathway and cell-cycle signalling pathways. Of these, 10 hub genes with high connectivity were selected (CXCL8, CCND1, FOS, PTGS2, CTLA4, THBS1, MMP2, KDR, and CD80). Most of these genes are involved in maintenance of immune response at maternal-fetal interface. Further, in functional enrichment analyses revealed the highest node size in regulation of biological processes followed by cellular processes, their regulation and regulation of multicellular organismal process. This in-silico transcriptomics meta-analysis findings could potentially contribute in identifying novel biomarkers and therapeutic targets for RPL, which could lead to the development of new diagnostic and therapeutic strategies for this condition.

Bulk RNA-sequencing, single-cell RNA-sequencing analysis, and experimental validation reveal iron metabolism-related genes CISD2 and CYP17A1 are potential diagnostic markers for recurrent pregnancy loss

BACKGROUND

Recurrent pregnancy loss (RPL) is associated with variable causes. Its etiology remains unexplained in about half of the cases, with no effective treatment available. Individuals with RPL have an irregular iron metabolism. In the present study, we identified key genes impacting iron metabolism that could be used for diagnosing and treating RPL.

METHODS

We obtained gene expression profiles from the Gene Expression Omnibus (GEO) database. The Molecular Signatures Database was used to identify 14 gene sets related to iron metabolism, comprising 520 iron metabolism genes. Differential analysis and a weighted gene co-expression network analysis (WGCNA) of gene expression revealed two iron metabolism-related hub genes. Reverse transcriptase-polymerase chain reaction (RT-PCR) and immunohistochemistry were used on clinical samples to confirm our results. The receiver operating characteristic (ROC) analysis and immune infiltration analysis were conducted. In addition, we analyzed the distribution of genes and performed CellChat analysis by single-cell RNA sequencing.

RESULTS

The expression of two hub genes, namely, CDGSH iron sulfur domain 2 (CISD2)and Cytochrome P450 family 17 subfamily A member 1 (CYP17A1), were reduced in RPL, as verified by both qPCR and immunohistochemistry. The Gene Ontology (GO) analysis revealed the genes predominantly engaged in autophagy and iron metabolism. The area under the curve (AUC) demonstrated better diagnostic performance for RPL using CISD2 and CYP17A1. The single-cell transcriptomic analysis of RPL demonstrated that CISD2 is expressed in the majority of cell subpopulations, whereas CYP17A1 is not. The cell cycle analysis revealed highly active natural killer (NK) cells that displayed the highest communications with other cells, including the strongest interaction with macrophages through the migratory inhibitory factor (MIF) pathway.

CONCLUSIONS

Our study suggested that CISD2 and CYP17A1 genes are involved in abnormal iron metabolism, thereby contributing to RPL. These genes could be used as potential diagnostic and therapeutic markers for RPL.

Endometrial Origins of Stillbirth (EOS), a case-control study of menstrual fluid to understand and prevent preterm stillbirth and associated adverse pregnancy outcomes: study protocol

INTRODUCTION

Current research aimed at understanding and preventing stillbirth focuses almost exclusively on the role of the placenta. The underlying origins of poor placental function leading to stillbirth, however, remain poorly understood. There is evidence demonstrating that the endometrial environment in which the embryo implants impacts not only the establishment of pregnancy but also the development of some pregnancy outcomes. Menstrual fluid has recently been applied to the study of menstrual disorders such as heavy menstrual bleeding or endometriosis, however, it has great potential in the study of adverse pregnancy outcomes. This study aims to identify differences in menstrual fluid and menstrual cycle characteristics of women who have experienced preterm stillbirth and other associated adverse pregnancy outcomes, compared with those who have not. The association between menstrual fluid composition and menstrual cycle characteristics will also be determined.

METHODS AND ANALYSIS

This is a case-control study of women who have experienced a late miscarriage, spontaneous preterm birth or preterm stillbirth or a pregnancy complicated by placental insufficiency (fetal growth restriction or pre-eclampsia), compared with those who have had a healthy term birth. Cases will be matched for maternal age, body mass index and gravidity. Participants will not currently be on hormonal therapy. Women will be provided with a menstrual cup and will collect their sample on day 2 of menstruation. Primary exposure measures include morphological and functional differences in decidualisation of the endometrium (cell types, immune cell subpopulations and protein composition secreted from the decidualised endometrium). Women will complete a menstrual history survey to capture menstrual cycle length, regularity, level of pain and heaviness of flow.

ETHICS AND DISSEMINATION

Ethics approval was obtained from Monash University Human Research Ethics Committee (27900) on 14/07/2021 and will be conducted in accordance with these conditions. Findings from this study will be disseminated through peer-reviewed publications and conference presentations.

Identification of novel biomarkers and immune infiltration features of recurrent pregnancy loss by machine learning

Recurrent pregnancy loss (RPL) is a complex reproductive disorder. The incompletely understood pathophysiology of RPL makes early detection and exact treatment difficult. The purpose of this work was to discover optimally characterized genes (OFGs) of RPL and to investigate immune cell infiltration in RPL. It will aid in better understanding the etiology of RPL and in the early detection of RPL. The RPL-related datasets were obtained from the Gene Expression Omnibus (GEO), namely GSE165004 and GSE26787. We performed functional enrichment analysis on the screened differentially expressed genes (DEGs). Three machine learning techniques are used to generate the OFGs. A CIBERSORT analysis was conducted to examine the immune infiltration in RPL patients compared with normal controls and to investigate the correlation between OFGs and immune cells. Between the RPL and control groups, 42 DEGs were discovered. These DEGs were found to be involved in cell signal transduction, cytokine receptor interactions, and immunological response, according to the functional enrichment analysis. By integrating OFGs from the LASSO, SVM-REF, and RF algorithms (AUC > 0.880), we screened for three down-regulated genes: ZNF90, TPT1P8, FGF2, and an up-regulated FAM166B. Immune infiltration study revealed that RPL samples had more monocytes (P < 0.001) and fewer T cells (P = 0.005) than controls, which may contribute to RPL pathogenesis. Additionally, all OFGs linked with various invading immune cells to varying degrees. In conclusion, ZNF90, TPT1P8, FGF2, and FAM166B are potential RPL biomarkers, offering new avenues for research into the molecular mechanisms of RPL immune modulation and early detection.

Designing Effective Multi-Target Drugs and Identifying Biomarkers in Recurrent Pregnancy Loss (RPL) Using In Vivo, In Vitro, and In Silico Approaches

Recurrent pregnancy loss (RPL) occurs in approximately 5% of women. Despite an abundance of evidence, the molecular mechanism of RPL’s pathology remains unclear. Here, we report the protective role of polo-like kinase 1 (PLK1) during RPL. We aimed to construct an RPL network utilizing GEO datasets and identified hub high-traffic genes. We also investigated whether the expressions of PLK1 were altered in the chorionic villi collected from women with RPL compared to those from healthy early pregnant women. Gene expression differences were evaluated using both pathway and gene ontology (GO) analyses. The identified genes were validated using in vivo and in vitro models. Mice with PLK1-overexpression and PLK1-knockdown in vitro models were produced by transfecting certain plasmids and si-RNA, respectively. The apoptosis in the chorionic villi, mitochondrial function, and NF-κB signaling activity was evaluated. To suppress the activation of PLK1, the PLK1 inhibitor BI2536 was administered. The HTR-8/SVneo and JEG-3 cell lines were chosen to establish an RPL model in vitro. The NF-κB signaling, Foxo signaling, PI3K/AKT, and endometrial cancer signaling pathways were identified via the RPL regulatory network. The following genes were identified: PLK1 as hub high-traffic gene and MMP2, MMP9, BAX, MFN1, MFN2, FOXO1, OPA1, COX15, BCL2, DRP1, FIS1, TRAF2, and TOP2A. Clinical samples were examined, and the results demonstrated that RPL patients had tissues with decreased PLK1 expression in comparison to women with normal pregnancies (p < 0.01). In vitro, PLK1 knockdown induced the NF-κB signaling pathway and apoptosis activation while decreasing cell invasion, migration, and proliferation (p < 0.05). Furthermore, the in vivo model proved that cell mitochondrial function and chorionic villi development are both hampered by PLK1 suppression. Our findings revealed that the PLK1/TRAF2/NF-κB axis plays a crucial role in RPL-induced chorionic villi dysfunction by regulating mitochondrial dynamics and apoptosis and might be a potential therapeutic target in the clinic.

Transcriptome-wide high-throughput m6 A sequencing of differential m6 A methylation patterns in the decidual tissues from RSA patients

Recurrent spontaneous abortion (RSA) is characterized by two or more consecutive pregnancy losses in the first trimester of pregnancy, experienced by 5% of women during their reproductive age. As a complex pathological process, the etiology of RSA remains poorly understood. Recent studies have established that gene expression changes dramatically in human endometrial stromal cells (ESCs) during decidualization. N6-methyladenosine (m⁶ A) modification is the most prevalent epigenetic modification of mRNA in eukaryotic cells and it is closely related to the occurrence and development of many pathophysiological phenomena. In this study, we first confirmed that high levels of m⁶ A mRNA methylation in decidual tissues are associated with RSA. Then, we used m⁶ A-modified RNA immunoprecipitation sequence (m⁶ A-seq) and RNA sequence (RNA-seq) to identify the differentially expressed m⁶ A methylation in decidual tissues from RSA patients and identified the key genes involved in abnormal decidualization by bioinformatics analysis. Using m⁶ A-seq, we identified a total of 2169 genes with differentially expressed m⁶ A methylation, of which 735 m⁶ A hypermethylated genes and 1434 m⁶ A hypomethylated genes were identified. Further joint analysis of m⁶ A-seq and RNA-seq revealed that 133 genes were m⁶ A modified with mRNA expression. GO and KEGG analyses indicated that these unique genes were mainly enriched in environmental information processing pathways, including the cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway. In summary, this study uncovered the transcriptome-wide m⁶ A modification pattern in decidual tissue of RSA, which provides a theoretical basis for further research into m⁶ A modification and new therapeutic strategies for RSA.

Endometrial gene expression differences in women with coronavirus disease 2019

OBJECTIVE

To study the potential effect of coronavirus disease (COVID-19) on the endometrial transcriptome of affected, symptomatic women for the detection of altered gene expression.

DESIGN

Pilot study of the endometrial transcriptomes of women manifesting COVID-19 compared with those of women without COVID-19 undergoing hysteroscopic procedures for benign gynecologic disorders using RNA sequencing.

SETTING

Hospital and university laboratories.

PATIENT(S)

Women with (n = 14) and without a COVID-19 (n = 10) diagnosis based on a nasopharyngeal swab analysis using quantitative reverse-transcription polymerase chain reaction. The endometrium of the patients with COVID-19 had previously been tested for severe acute respiratory syndrome coronavirus 2 infection, revealing the absence of the virus in this tissue.

INTERVENTION(S)

Endometrial biopsy sample collection.

MAIN OUTCOMES MEASURE(S)

Endometrial gene expression and functional analysis of symptomatic patients with COVID-19 vs. individuals without the infection.

RESULT(S)

The systemic disease COVID-19 altered endometrial gene expression in 75% of the women, with the patients exhibiting a preponderance of 163 up-regulated (e.g., UTS2, IFI6, IFIH1, and BNIP3) and 72 down-regulated genes (e.g., CPZ, CDH3, and IRF4) (false discovery rate<0.05). A total of 161 dysregulated functions (36 up-regulated and 125 down-regulated) were typically enriched in the endometria of the patients with COVID-19, including up-regulation in pathways involved in the development of immune responses to viruses and cytokine inflammation, reflecting elicitation of a COVID-19 response pathway.

CONCLUSION(S)

Coronavirus disease 2019 affects endometrial gene expression despite the absence of severe acute respiratory syndrome coronavirus 2 RNA in endometrial tissues.

Multiomics Studies Investigating Recurrent Pregnancy Loss: An Effective Tool for Mechanism Exploration

Patients with recurrent pregnancy loss (RPL) account for approximately 1%-5% of women aiming to achieve childbirth. Although studies have shown that RPL is associated with failure of endometrial decidualization, placental dysfunction, and immune microenvironment disorder at the maternal-fetal interface, the exact pathogenesis remains unknown. With the development of high-throughput technology, more studies have focused on the genomics, transcriptomics, proteomics and metabolomics of RPL, and new gene mutations and new biomarkers of RPL have been discovered, providing an opportunity to explore the pathogenesis of RPL from different biological processes. Bioinformatics analyses of these differentially expressed genes, proteins and metabolites also reflect the biological pathways involved in RPL, laying a foundation for further research. In this review, we summarize the findings of omics studies investigating decidual tissue, villous tissue and blood from patients with RPL and identify some possible limitations of current studies.

Proteomic and functional analysis of proteins related to embryonic development of decidua in patients with recurrent pregnancy loss

Recurrent pregnancy loss (RPL) is defined as the loss of two or more consecutive pregnancies before the 20 weeks of gestation. Recurrent pregnancy loss affects about 1-2% of couples trying to conceive; however, the mechanisms leading to this complication are largely unknown. Our previous studies using comparative proteomics identified 314 differentially expressed proteins (DEPs) in the placental villous. In this study, we identified 5479 proteins from a total of 34,157 peptides in decidua of patients with early recurrent pregnancy loss (Data are available via ProteomeXchange with identifier PXD023849). Further analysis identified 311 DEPs in the decidua tissue; and 159 proteins were highly expressed while 152 proteins were lowly expressed. These 311 proteins were further analyzed by using Ingenuity Pathway Analysis (IPA). The results suggested that 50 DEPs played important roles in the embryonic development. Upstream analysis of these DEPs revealed that AGT was the most important upstream regulator. Furthermore, protein - protein interaction (PPI) analysis of the embryonic development DEPs from the placental villous and decidua was performed in the STRING database. This study identified several proteins specifically associated with embryonic development in decidua of patients with early recurrent pregnancy loss. Therefore, these results provide new insights into potential biological mechanisms, that may ultimately inform recurrent pregnancy loss.