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

From infection to infertility: a review of the role of human papillomavirus-induced oxidative stress on reproductive health and infertility

Infertility has emerged as a significant global health concern, affecting nearby 8-12% of couples in reproductive age worldwide. Increasing evidence suggests a potential link between human papillomavirus (HPV) and infertility in both men and women. Some research indicate that HPV can infect various components of semen, potentially affecting sperm quality by decreasing motility, viability, and increasing DNA fragmentation, all of which may contribute to male infertility. The virus can attach to the equatorial region of the sperm head, enabling infected sperm to transmit the virus to the oocyte or placenta. Consequently, HPV potentially induces apoptosis in trophoblastic cells and disrupts their adhesion to endometrial cells, which raises the risk of miscarriage. HPV may also affect ovarian reserve by causing chronic inflammation, which can impair granulosa cell function and lower serum anti-Müllerian hormone (AMH) levels. Besides, HPV-related immune responses also contribute to infertility by producing anti-sperm antibodies (ASAs), which cause sperm clumping, reduce motility through cervical mucus, activate the complement system that damages sperm in the female reproductive tract and interfere with sperm-egg interactions. Moreover, HPV infection has been linked to reduced success rates in assisted reproductive technologies (ART), potentially disrupting critical processes such as the acrosome reaction, sperm-oocyte interaction, and fusion. One potential mechanism through which HPV contributes to infertility is oxidative stress (OS). Triggered OS can negatively impact sperm quality and cause damage to the female reproductive system, ultimately contributing to infertility. Despite these associations, the precise mechanisms and the strength of the relationship remain uncertain. Thus, this review seeks to investigate the potential impact of HPV on infertility, particularly its effects on the reproductive system through OS. A clearer understanding of these processes could inform future health strategies for addressing HPV-related infertility.

Critical factors influencing live birth rates in fresh embryo transfer for IVF: insights from cluster ensemble algorithms

Infertility has emerged as a significant global health concern. Assisted reproductive technology (ART) assists numerous infertile couples in conceiving, yet some experience repeated, unsuccessful cycles. This study aims to identify the pivotal clinical factors influencing the success of fresh embryo transfer of in vitro fertilization (IVF). We introduce a novel Non-negative Matrix Factorization (NMF)-based Ensemble algorithm (NMFE). By combining feature matrices from NMF, accelerated multiplicative updates for non-negative matrix factorization (AMU-NMF), and the generalized deep learning clustering (GDLC) algorithm. NMFE exhibits superior accuracy and reliability in analyzing the in vitro fertilization and embryo transfer (IVF-ET) dataset. The dataset comprises 2238 cycles and 85 independent clinical features, categorized into 13 categories based on feature correlation. Subsequently, the NMFE model was trained and reached convergence. Then the features of 13 categories were sequentially masked to analyze their individual effects on IVF-ET live births. The NMFE analysis highlights the significant influence of therapeutic interventions, Embryo transfer outcomes, and ovarian response assessment on live births of IVF-ET. Therapeutic interventions, including ovarian stimulation protocols, ovulation stimulation drugs, and pre-and intra-stimulation cycle acupuncture play prominent roles. However, their impacts on the IVF-ET model are reduced, suggesting a potential synergistic effect when combined. Conversely, factors like basic information, diagnosis, and obstetric history have a lesser influence. The NMFE algorithm demonstrates promising potential in assessing the influence of clinical features on live births in IVF fresh embryo transfer.

Identification of important genes related to ferroptosis in early missed abortion based on WGCNA

Early missed abortion is defined as a pregnancy of ≤ 12 weeks in which there is a cessation of life in the developing embryo or fetus, leading to its retention within the uterine cavity without being spontaneously expelled promptly. This condition is commonly observed and significantly impacts human reproductive health. This study aimed to identify key genes related to ferroptosis that could serve as novel biomarkers for early missed abortion. Findings from gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicate a correlation between iron- DEFRGS in key modules and the p53 signaling, mitophagy-animal, and protein digestion and absorption pathways. An analysis of the protein-protein interaction (PPI) network was conducted on DEFRGs, identifying five central genes (TP53, EZH2, TIMP1, SLC3A2, and GABARAPL2) using STRING and Cytohubba ROC curves. The expression of pivotal genes in both the missed-abortion and control groups was verified by RT-qPCR. CIBERSORT analysis revealed a notable increase in the infiltration levels of CD8 + T lymphocytes and M2 macrophages among individuals in the early missed abortion group. Additionally, a ceRNA network was constructed to predict interactions between mRNA, miRNA, and lncRNA of the central genes. However, the interacting miRNAs predicted for SLC3A2 in the miRanda, miRDB, and TargetScan databases were limited to hsa-miR-661 and hsa-miR-4311, with no interacting lncRNAs found in the spongeScan database. This research has identified novel genes that could be targeted for the early detection and management of missed abortions.

Lipid imbalance and inflammatory oxylipin cascade at the maternal-fetal interface in recurrent spontaneous abortion

Background

Recurrent spontaneous abortion (RSA) is intricately linked to metabolic dysregulation at the maternal-fetal interface during early gestation. Abnormal levels of essential fatty acids and downstream oxylipins in decidua and chorionic villi have been identified as potential risk factors for RSA. Oxylipins have been linked to excessive inflammation, which might disrupt maternal-fetal immune tolerance, potentially contributing to RSA. Nonetheless, the exact fatty acid-oxylipin metabolic pathway at the matrernal-fetal interface in RSA occurrence remains unknown. Therefore, this research aimed to explore the effect of essential fatty acids, their transport, and downstream oxylipins at the maternal-fetal interface on RSA pathogenesis.

Methods

Plasma, chorionic villus, and decidual tissue samples from the first trimester were collected from healthy pregnant women undergoing elective pregnancy terminations, as well as from patients experiencing spontaneous abortion. The concentrations of essential fatty acids and their downstream oxylipins in the villi and decidua were quantified using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS). The expression of enzymes related to metabolic pathways was investigated by q-PCR. The ratios of M1/M2 macrophages were assessed by flow cytometry (FCM).

Results

This study found elevated concentrations of omega-6 fatty acids, encompassing arachidonic acid (AA), linoleic acid (LA), and dihomo-gamma-linolenic acid (DGLA) in maternal plasma and chorionic villi, whereas lower concentrations were observed in the decidua, than in samples from normal pregnancies. Further analysis revealed that the transport of these fatty acids was dysregulated at the maternal-fetal interface in RSA women, possibly due to the aberrant expression of the fatty acid translocase (FAT/CD36). In addition, this study revealed that RSA patients displayed higher levels of downstream oxylipins, such as prostaglandin F2a (PGF2a), prostaglandin E2 (PGE2), and leukotriene B4 (LTB4) in chorionic villi and decidua. These compounds may contribute to M1 inflammatory macrophage polarization in RSA, thereby forming a highly inflammatory environment and influencing immunomodulation at the maternal-fetal interface.

Conclusion

The study revealed alterations in omega-6 fatty acids, CD36 transport, and AA downstream oxylipins in RSA, which in turn promote M1 macrophage polarization. Thus, this research has established a foundation for identifying potential biomarkers for, and providing novel insights into, the diagnosis and pathophysiology of RSA.

Epigenetic Biomarkers in Thrombophilia-Related Pregnancy Complications: Mechanisms, Diagnostic Potential, and Therapeutic Implications: A Narrative Review

Pregnancy complications associated with thrombophilia represent significant risks for maternal and fetal health, leading to adverse outcomes such as pre-eclampsia, recurrent pregnancy loss, and intra-uterine growth restriction (IUGR). They are caused by disruptions in key physiological processes, including the coagulation cascade, trophoblast invasion, angiogenesis, and immune control. Recent advancements in epigenetics have revealed that non-coding RNAs, especially microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and extracellular vesicles (EVs) carrying these RNAs, play crucial roles in the regulation of these biological processes. This review aims to identify the epigenetic biomarkers that are the best candidates for evaluating thrombophilia-related pregnancy complications and for assessing the efficacy of anticoagulant and antiaggregant therapies. We emphasize their potential integration into personalized treatment plans, aiming to improve the risk assessment and therapy strategies for thrombophilic pregnancies. Future research should focus on validating these epigenetic biomarkers and establishing standardized protocols to enable their integration into clinical practice, paving the way for a precision medicine approach in obstetric care.

Delineation of Partial Chromosomal Abnormalities in Early Pregnancy Losses

Pregnancy loss (PL), particularly early pregnancy loss (EPL), is a prevalent reproductive complication, with approximately 15% of confirmed pregnancies affected. Chromosomal abnormalities are implicated in more than half of EPLs, with trisomies being the most prevalent. Partial abnormalities, including segmental deletions, duplications, and unbalanced translocations, are detected in up to 10% of EPL cases. This study focuses on the precise characterization of partial chromosomal abnormalities, previously identified by Quantitative fluorescent polymerase chain reaction (QF-PCR) and multiplex ligation probe amplification (MLPA) analyses. By employing an array comparative genomic hybridization (aCGH), we analyzed 20 EPL samples, identifying 32 partial chromosomal abnormalities, including 18 deletions and 14 duplications, with an average size of 33.2 Mb. Notably, two abnormalities previously undetected by QF-PCR and MLPA were revealed (deletions in 7q36, and 1p36.32p36.31regions), emphasizing the necessity of high-resolution genomic tools. Chromosomes 1, 18, and 13 emerged as frequently involved, aligning with previous associations with recurrent pregnancy loss. Recurrent abnormalities were identified in six chromosomal regions, with chromosome 1p36.33-p36.32 exhibiting the highest frequency. Gene Ontology (GO) enrichment analysis of recurrent regions highlighted disruptions in critical biological processes, including molecular binding, enzymatic activity, and cellular development. Many genes in these regions are linked to multisystem syndromes, suggesting their involvement in early embryonic development and pregnancy viability. Our findings underscore the complexity of EPL's genetic landscape, demonstrating that large CNVs, may disrupt multiple genes critical for development. Although, subtelo-meric MLPA reliably detects telomeric partial chromosomal abnormalities in EPLs, aCGH is essential for detection and precise characterization of all CNVs, thus enhancing diagnostic and counseling strategies in affected couples.

Role of Immune Inflammation in Recurrent Spontaneous Abortions

Objective

This study aimed to investigate the role of immune inflammation in recurrent spontaneous abortions (RSA).

Methods

In this study, decidua tissues from 12 patients were collected. These included six individuals with RSA in the RSA group and six in the control group. The differences in gene and metabolite expression in the decidua of the placenta between normal pregnancies and patients with RSA were compared using transcriptomic and metabolomic analyses. The differentially expressed genes and metabolites were further analyzed through functional enrichment analysis using high-throughput sequencing technology.

Results

There was a significant upregulation of genes associated with immunity and inflammation in the RSA group compared to the control group. The TNF signaling pathway was upregulated in the RSA group. Inflammatory mediators were expressed at higher levels in the RSA group, and arachidonic acid metabolism was the most significant differential metabolite set. The regulation of inflammatory mediators of transient receptor potential (TRP) channels were enriched in RSA cases. The integrated analysis of the data further suggests that the immune-inflammatory response might be an important factor in RSA. The expression levels of genes related to inflammation and hypoxia in tissues from patients with RSA were verified using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and this revealed that the expression of MARK10 and TNFAIP3 genes was significantly upregulated in samples from RSA patients compared to normal tissues.

Conclusion

The findings suggest a strong association between immune-related inflammation and RSA. Addressing metabolic and inflammatory aspects in patients with RSA may potentially help enhance pregnancy outcomes.

Alloimmune Causes of Recurrent Pregnancy Loss: Cellular Mechanisms and Overview of Therapeutic Approaches

Recurrent pregnancy loss (RPL) is a complex early pregnancy complication affecting 1-2% of couples and is often linked to immune dysfunction. Aberrations in T and B cell subpopulations, as well as natural killer (NK) cell activity, are particularly influential, with studies showing that abnormal NK cell activation and imbalances in T and B cell subtypes contribute to immune-mediated miscarriage risk. Successful pregnancy requires a tightly regulated balance between pro-inflammatory and anti-inflammatory immune responses. In the early stages, inflammation supports processes such as trophoblast invasion and spiral artery remodeling, but this must be tempered to prevent immune rejection of the fetus. In this review, we explore the underlying immune mechanisms of RPL, focusing on how dysregulated T, B, and NK cell function disrupts maternal tolerance. Specifically, we discuss the essential role of uterine NK cells in the early stages of vascular remodeling in the decidua and regulate the depth of invasion by extravillous trophoblasts. Furthermore, we focus on the delicate Treg dynamics that enable the maintenance of optimal immune homeostasis, where the balance, and not only the quantity of Tregs, is crucial for fostering maternal-fetal tolerance. Other T cell subpopulations, such as Th1, Th2, and Th17 cells, also contribute to immune imbalance, with Th1 and Th17 cells promoting inflammation and potentially harming fetal tolerance, while Th2 cells support immune tolerance. Finally, we show how changes in B cell subpopulations and their functions have been associated with adverse pregnancy outcomes. We further discuss current therapeutic strategies aimed at correcting these immune imbalances, including intravenous immunoglobulin (IVIg), glucocorticoids, and TNF-α inhibitors, examining their efficacy, challenges, and potential side effects. By highlighting both the therapeutic benefits and limitations of these interventions, we aim to offer a balanced perspective on clinical applications for women facing immune-related causes of RPL.

Identification of Biomarkers and Mechanisms Associated with Apoptosis in Recurrent Pregnancy Loss

In this study, we employed bioinformatics techniques to identify genes associated with apoptosis in recurrent pregnancy loss (RPL). We retrieved the RPL expression profile datasets GSE165004 and GSE73025 from the Gene Expression Omnibus (GEO) database. We also obtained data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway of Apoptosis (hsa04210) to identify apoptosis-related genes. In addition, we performed Friends analysis to explore the interactions between differential apoptosis genes and other genes in the functional pathway. We identified six differentially expressed genes related to apoptosis, including CTSZ, BCL2, PIK3CD, KRAS, GADD45G, and CASP8, with GADD45G as the most gene. Functional fertility analysis revealed that differentially expressed genes primarily regulated protein stability, cell number homeostasis, myeloid cell homeostasis, hematopoietic progenitor cell differentiation, lytic vacuole and lysosome functions, vacuolar and lysosomal membranes, transmembrane transporter binding, protein domain-specific binding, G-protein beta-subunit binding, phospholipid binding, and were involved in pathways such as Rap1 signaling, regulation of actin cytoskeleton, and NOD-like receptor signaling. KRAS exhibited the highest mutation rate in RPL-related cancer CESC. There was also a positive correlation between differentially expressed genes and B cell memory, CD4 memory resting T cells, follicular helper T cells, naïve B cells, and resting dendritic cells. We identified six differentially expressed genes related to apoptosis in RPL, with GADD45G as the most important. NOD-like receptor signaling pathway and regulation of actin cytoskeleton could be therapeutic targets for RPL.

High Prevalence of Anti-Prothrombin IgM and IgG Autoantibodies in Women With Unexplained Recurrent Pregnancy Loss

To investigate the association between anti-prothrombin IgM and IgG antibodies and recurrent pregnancy loss (RPL) in a cohort of Lebanese women, and their impact on pregnancy outcomes. This was a retrospective case-control study involving 207 women with RPL and 179 age-matched multiparous controls. Quantitative sandwich ELISA assayed anti-prothrombin IgM and IgG antibodies. Univariate and multivariate logistic regression were employed to assess the risk imparted by anti-prothrombin antibodies, while ROC analysis was used to determine their sensitivity and specificity. Our study revealed that women with RPL had significantly higher serum levels of anti-prothrombin IgM and IgG than controls. Univariate regression analysis demonstrated that elevated anti-prothrombin IgM (OR = 1.13; 95% CI = 1.07, 1.19; P < 0.001) and IgG (OR = 1.05; 95% CI = 1.03, 1.08; P < 0.001) were associated with increased RPL risk. Multivariate analysis confirmed these findings, indicating that anti-prothrombin IgM (aOR = 1.13; 95% CI = 1.05, 1.20; P < 0.001) and IgG (aOR = 1.08; 95% CI = 1.05, 1.11; P < 0.001) are independent risk factors. ROC analysis yielded an AUC of 0.720 for IgM and 0.649 for IgG, underscoring their predictive value and offering hope for improved risk assessment and management of RPL. Elevated levels of anti-prothrombin IgM and IgG are significantly associated with RPL, suggesting an autoimmune component to pregnancy loss. These findings highlight the importance of screening for these antibodies in women with unexplained RPL to guide management and therapeutic strategies.

Shared diagnostic genes and potential mechanisms between polycystic ovary syndrome and recurrent miscarriage revealed by integrated transcriptomics analysis and machine learning

Objective

More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear.

Methods

Based on the GEO database, we downloaded the PCOS (GSE10946, GSE6798 and GSE137684) and RSA (GSE165004, GSE26787 and GSE22490) datasets and performed differential analysis, weighted gene co-expression network (WGCNA), functional enrichment, and machine learning, respectively, on the datasets of the two diseases, Nomogram and integrated bioinformatics analysis such as immune infiltration analysis. Finally, the reliability of the diagnostic gene was verified by external verification and collection of human specimens.

Results

In this study, PCOS and RSA datasets were obtained from Gene Expression Omnibus (GEO) database, and a total of 23 shared genes were obtained by differential analysis and WGCNA analysis. GO results showed that the shared genes were mainly enriched in the functions of lipid catabolism and cell cycle transition (G1/S). DO enrichment revealed that shared genes are mainly involved in ovarian diseases, lipid metabolism disorders and psychological disorders. KEGG analysis showed significant enrichment of Regulation of lipolysis in adipocytes, Prolactin signaling pathway, FoxO signaling pathway, Hippo signaling pathway and other pathways. A diagnostic gene FAM166 B was obtained by machine learning and Nomogram screening, which mainly played an important role in Cellular component. GSEA analysis revealed that FAM166B may be involved in the development of PCOS and RSA by regulating the cell cycle, amino acid metabolism, lipid metabolism, and carbohydrate metabolism. CIBERSORT analysis showed that the high expression of FAM166 B was closely related to the imbalance of multiple immune cells. Further verification by qPCR suggested that FAM166 B could be used as a common marker of PCOS and RSA.

Conclusions

In summary, this study identified FAM166B as a common biomarker for PCOS and RSA, and conducted in-depth research and analysis of this gene, providing new data for basic experimental research and early prognosis, diagnosis and treatment of clinical diseases.

Identification and validation of oxidative stress-related diagnostic markers for recurrent pregnancy loss: insights from machine learning and molecular analysis

It has been recognized that oxidative stress (OS) is implicated in the etiology of recurrent pregnancy loss (RPL), yet the biomarkers reflecting oxidative stress in association with RPL remain scarce. The dataset GSE165004 was retrieved from the Gene Expression Omnibus (GEO) database. From the GeneCards database, a compendium of 789 genes related to oxidative stress-related genes (OSRGs) was compiled. By intersecting differentially expressed genes (DEGs) in normal and RPL samples with OSRGs, differentially expressed OSRGs (DE-OSRGs) were identified. In addition, four machine learning algorithms were employed for the selection of diagnostic markers for RPL. The Receiver Operating Characteristic (ROC) curves for these genes were generated and a predictive nomogram for the diagnostic markers was established. The functions and pathways associated with the diagnostic markers were elucidated, and the correlations between immune cells and diagnostic markers were examined. Potential therapeutics targeting the diagnostic markers were proposed based on data from the Comparative Toxicogenomics Database and ClinicalTrials.gov. The candidate biomarker genes from the four models were further validated in RPL tissue samples using RT-PCR and immunohistochemistry. A set of 20 DE-OSRGs was identified, with 4 genes (KRAS, C2orf69, CYP17A1, and UCP3) being recognized by machine learning algorithms as diagnostic markers exhibiting robust diagnostic capabilities. The nomogram constructed demonstrated favorable predictive accuracy. Pathways including ribosome, peroxisome, Parkinson's disease, oxidative phosphorylation, Huntington's disease, and Alzheimer's disease were co-enriched by KRAS, C2orf69, and CYP17A1. Cell chemotaxis terms were commonly enriched by all four diagnostic markers. Significant differences in the abundance of five cell types, namely eosinophils, monocytes, natural killer cells, regulatory T cells, and T follicular helper cells, were observed between normal and RPL samples. A total of 180 drugs were predicted to target the diagnostic markers, including C544151, D014635, and CYP17A1. In the validation cohort of RPL patients, the LASSO model demonstrated superiority over other models. The expression levels of KRAS, C2orf69, and CYP17A1 were significantly reduced in RPL, while UCP3 levels were elevated, indicating their suitability as molecular markers for RPL. Four oxidative stress-related diagnostic markers (KRAS, C2orf69, CYP17A1, and UCP3) have been proposed to diagnose and potentially treat RPL.

Syncytiotrophoblast Markers Are Downregulated in Placentas from Idiopathic Stillbirths

The trophoblast cells are responsible for the transfer of nutrients between the mother and the foetus and play a major role in placental endocrine function by producing and releasing large amounts of hormones and growth factors. Syncytiotrophoblast cells (STB), formed by the fusion of mononuclear cytotrophoblasts (CTB), constitute the interface between the foetus and the mother and are essential for all of these functions. We performed transcriptome analysis of human placental samples from two control groups-live births (LB), and stillbirths (SB) with a clinically recognised cause-and from our study group, idiopathic stillbirths (iSB). We identified 1172 DEGs in iSB, when comparing with the LB group; however, when we compared iSB with the SB group, only 15 and 12 genes were down- and upregulated in iSB, respectively. An assessment of these DEGs identified 15 commonly downregulated genes in iSB. Among these, several syncytiotrophoblast markers, like genes from the PSG and CSH families, as well as ALPP, KISS1, and CRH, were significantly downregulated in placental samples from iSB. The transcriptome analysis revealed underlying differences at a molecular level involving the syncytiotrophoblast. This suggests that defects in the syncytial layer may underlie unexplained stillbirths, therefore offering insights to improve clinical obstetrics practice.

Clinical Relevance of Vaginal and Endometrial Microbiome Investigation in Women with Repeated Implantation Failure and Recurrent Pregnancy Loss

Recent studies have investigated if and how the vaginal and endometrial microbiome might affect endometrial receptivity and reproductive health. Although there is no consensus on the existence of a core uterine microbiome yet, evidence shows that the dominance of Lactobacillus spp. in the female reproductive tract is generally associated with eubiosis and improved chances of successful implantation and an ongoing pregnancy. Conversely, vaginal and endometrial dysbiosis can cause local inflammation and an increase of pro-inflammatory cytokines, compromising the integrity and receptivity of the endometrial mucosa and potentially hampering successful embryonic implantation. This review provides a critical appraisal of the influence of the vaginal and endometrial microbiome as parts of the female reproductive tract on fertility outcomes, focusing on repeated implantation failure (RIF) and recurrent pregnancy loss (RPL). It seems that RIF as well as RPL are both associated with an increase in microbiome diversity and a loss of Lactobacillus dominance in the lower female reproductive system.

Glycolysis: A fork in the path of normal and pathological pregnancy

Glucose metabolism is vital to the survival of living organisms. Since the discovery of the Warburg effect in the 1920s, glycolysis has become a major research area in the field of metabolism. Glycolysis has been extensively studied in the field of cancer and is considered as a promising therapeutic target. However, research on the role of glycolysis in pregnancy is limited. Recent evidence suggests that blastocysts, trophoblasts, decidua, and tumors all acquire metabolic energy at specific stages in a highly similar manner. Glycolysis, carefully controlled throughout pregnancy, maintains a dynamic and coordinated state, so as to maintain the homeostasis of the maternal-fetal interface and ensure normal gestation. In the present review, we investigate metabolic remodeling and the selective propensity of the embryo and placenta for glycolysis. We then address dysregulated glycolysis that occurs in the cellular interactive network at the maternal-fetal interface in miscarriage, preeclampsia, fetal growth restriction, and gestational diabetes mellitus. We provide new insights into the field of maternal-fetal medicine from a metabolic perspective, thus revealing the mystery of human pregnancy.

Relationship between air pollutants and spontaneous abortion in a coal resource valley city: a retrospective cohort study

OBJECTIVE

Pollutants in the atmosphere have been linked to poor pregnancy outcomes in women. However, such investigations are scarce in metropolitan northern China. The major exposure window of air pollution affecting pregnant women is also unknown.

METHODS

For the analysis, this retrospective cohort study enrolled 6960 pregnant women recorded at Tongchuan People's Hospital from January 2018 to December 2019. Pollutant concentration values from the nearest monitoring station to the pregnant women were used to estimate exposure doses for each exposure window. Logistic regression models were created to investigate the connection between pollutants and spontaneous abortion while controlling for confounding factors.

RESULTS

PM2.5 was a risk factor for spontaneous abortion in T3 (30-60 days before the first day of the last menstrual period [LMP]), (OR: 1.305, 95% CI: 1.143-1.490) and T4 (60-90 days before the first day of the LMP),(OR: 1.450, 95% CI: 1.239-1.696) after controlling for covariates. In the same window, PM10 was a risk factor (OR: 1.308, 95% CI: 1.140-1.500), (OR: 1.386, 95% CI: 1.184-1.621). In T2 (30 days before the first day of the LMP), T3, and T4, SO2 was a risk factor for spontaneous abortion (OR: 1.185, 95% CI: 1.025-1.371), (OR: 1.219, 95% CI: 1.071-1.396), (OR: 1.202, 95% CI: 1.040-1.389). In T3 and T4, NO2 was a risk factor (OR: 1.171, 95% CI: 1.019- 1.346), (OR: 1.443, 95% CI: 1.259-1.655). In T1 (from the first day of the LMP to the date of abortion), O3 was found to be a risk factor (OR: 1.366, 95% CI: 1.226-1.521).

CONCLUSION

Exposure to high levels of air pollutants before and during pregnancy may be a risk factor for spontaneous abortion in pregnant women. This study further illustrates the importance of reducing air pollution emissions.

Role of the HLA-G regulatory region polymorphisms in idiopathic recurrent spontaneous abortions (RSA)

PROBLEM

HLA-G polymorphisms have a functional impact on its expression and may cause a breakdown of maternal tolerance towards the semi-allogenic fetus, resulting in recurrent spontaneous abortions (RSA). This study reports on the association of HLA-G regulatory region polymorphisms with idiopathic RSA.

METHODS

Seventy-five couples with ≥2 spontaneous abortions were recruited in comparison to 75 healthy couples who had normal pregnancies. About 5 mL of blood samples were collected from all the participants, and DNA was extracted. Screening of HLA-G 5'-upstream regulatory region (5'-URR) was done by direct sequencing in 50 each of RSA and healthy couples, respectively. The 14 bp deletion/insertion polymorphism in the 3'-untranslated region (3'-UTR) was genotyped in 75 each of RSA and healthy couples, respectively, by PCR amplification of HLA-G exon 8. MedCalc, GraphPad Prism, Haploview, PLINK, and multifactor dimensionality reduction were used to analyze the data.

RESULTS

HLA-G screening revealed the presence of -762C/T, -725C/G, -716T/G, -689A/G, -486C/A, and -477C/G single nucleotide polymorphisms (SNPs) in the 5'-URR. At positions -762 and -477, the frequency of CC homozygotes was significantly higher in controls compared to the patients. The 14 bp deletion/insertion polymorphism in the 3'-UTR showed an association with RSA with the heterozygous genotype being significantly higher in RSA compared to controls.

CONCLUSIONS

The study indicates a protective role of the CC genotypes of the two HLA-G 5'-URR polymorphisms, -762C/T and -477C/G, against RSA. It also suggests that women with the 14 bp deletion/insertion genotype have a significantly higher risk of RSA.

Intercellular communication involving macrophages at the maternal-fetal interface may be a pivotal mechanism of URSA: a novel discovery from transcriptomic data

Unexplained recurrent spontaneous abortion (URSA) is a severe challenge to reproductive females worldwide, and its etiology and pathogenesis have not yet been fully clarified. Abnormal intercellular communication between macrophages (Mφ) and decidual stromal cells (DSCs) or trophoblasts has been supposed to be the key to URSA. However, the exact molecular mechanisms in the crosstalk are not yet well understood. This study aimed to explore the potential molecule mechanism that may be involved in the communication between Mφ and DSC or trophoblast cells and determine their diagnostic characteristics by using the integrated research strategy of bioinformatics analysis, machine learning and experiments. First, microarrays of decidual tissue (GSE26787, GSE165004) and placenta tissue (GSE22490) in patients with URSA, as well as microarrays involving induced decidualization (GSE94644) and macrophage polarization in vitro (GSE30595) were derived from the gene expression omnibus (GEO) database. And 721 decidua-differentially expressed genes (DEGs), 613 placenta-DEGs, 510 Mφ polarization DEGs were obtained in URSA by differential expression analysis. Then, the protein-protein interaction (PPI) network was constructed, and the hub genes were identified by CytoHubba in Cytoscape software and validated by real-time PCR assay. Subsequently, immune enrichment analysis on decidua-DEGs and placenta-DEGs by ClueGO verified their regulation effects on Mφ. Besides, functional enrichment analysis was performed on Mφ polarization DEGs and the essential module genes derived from the weighted gene co-expression network analysis (WGCNA) to uncover the biological function that were related to abnormal polarization of Mφ. Furthermore, we screened out 29, 43 and 22 secreted protein-encoding genes from DSC-DEGs, placenta-DEGs and Mφ polarization DEGs, respectively. Besides, the hub secreted-protein-encoding genes were screened by CytoHubba. Moreover, we conducted functional enrichment analysis on these genes. And spearman correlation analysis between hub secreted-protein-encoding genes from donor cells and hub genes in recipient cells was performed to further understand the molecular mechanism of intercellular communication further. Moreover, signature genes with diagnostic value were screened from secreted protein-encoding genes by machine learning and validated by immunofluorescence co-localization analysis with clinical samples. Finally, three biomarkers of DSCs (FGF9, IL1R2, NID2) and three biomarkers of Mφ (CFB, NID2, CXCL11) were obtained. In conclusion, this project provides new ideas for understanding the mechanism regulatory network of intercellular communication involving macrophages at the maternal-fetal interface of URSA. Also, it provides innovative insights for the diagnosis and treatment of URSA.

Increased levels of nerve growth factor accompany oxidative load in recurrent pregnancy loss. Machine learning applied to FT-Raman spectra study

The presented article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood serum samples in patients with diagnosed recurrent pregnancy loss (RPL) versus healthy individuals who were followed at the Gynecology department. A total of 120 participants, RPL disease (n = 60) and healthy individuals (n = 60), participated in the study. First, we investigated the effect of circulating nerve growth factor (NGF) in RPL and healthy groups. To show NGF's effect, we measured the level of oxidative loads such as Total Antioxidant Level (TAS), Total Oxidant Level (TOS), and Oxidative Stress Index (OSI) with Beckman Coulter AU system and biochemical assays. We find a correlation between oxidative load and NGF level. Oxidative load mainly causes structural changes in the blood. Therefore, we obtained Raman measurements of the participant's serum. Then we selected two Raman regions, 800 and 1800 cm^-1, and between 2700 cm^-1 and 3000 cm^-1, to see chemical changes. We noted that Raman spectra obtained for RPL and healthy women differed. The findings confirm that the imbalance between reactive oxygen species and antioxidants has important implications for the pathogenesis of RPL and that NGF levels accompany the level of oxidative load in the RPL state. Biomolecular structure and composition were determined using Raman spectroscopy and machine learning methods, and the correlation of these parameters was studied alongside machine learning technologies to advance toward clinical translation. Here we determined and validated the development of instrumentation for the Analysis of RPL patients' serum that can differentiate from control individuals with an accuracy of 100% using the Raman region corresponding to structural changes. Furthermore, this study found a correlation between traditional biochemical parameters and Raman data. This suggests that Raman spectroscopy is a sensitive tool for detecting biochemical changes in serum caused by RPL or other diseases.

Current Status and Prospects of the Single-Cell Sequencing Technologies for Revealing the Pathogenesis of Pregnancy-Associated Disorders

Single-cell RNA sequencing (scRNA-seq) is a method that focuses on the analysis of gene expression profile in individual cells. This method has been successfully applied to answer the challenging questions of the pathogenesis of multifactorial diseases and open up new possibilities in the prognosis and prevention of reproductive diseases. In this article, we have reviewed the application of scRNA-seq to the analysis of the various cell types and their gene expression changes in normal pregnancy and pregnancy complications. The main principle, advantages, and limitations of single-cell technologies and data analysis methods are described. We discuss the possibilities of using the scRNA-seq method for solving the fundamental and applied tasks related to various pregnancy-associated disorders. Finally, we provide an overview of the scRNA-seq findings for the common pregnancy-associated conditions, such as hyperglycemia in pregnancy, recurrent pregnancy loss, preterm labor, polycystic ovary syndrome, and pre-eclampsia.

Towards reproducible research in recurrent pregnancy loss immunology: Learning from cancer microenvironment deconvolution

The most recent international guidelines regarding recurrent pregnancy loss (RPL) exclude most of the immunological tests recommended for RPL since they do not reach an evidence-based level. Comparisons for metanalysis and systematic reviews are limited by the ambiguity in terms of RPL definition, etiological and risk factors, diagnostic work-up, and treatments applied. Therefore, cohort heterogeneity, the inadequacy of numerosity, and the quality of data confirm a not standardized research quality in the RPL field, especially for immunological background, for which potential research application remains confined in a separate single biological layer. Innovative sequencing technologies and databases have proved to play a significant role in the exploration and validation of cancer research in the context of dataset quality and bioinformatics tools. In this article, we will investigate how bioinformatics tools born for large-scale cancer immunological research could revolutionize RPL immunological research but are limited by the nature of current RPL datasets.

The Progress of Research on Genetic Factors of Recurrent Pregnancy Loss

Recurrent pregnancy loss (RPL) is both mental and physical health problem affecting about 1-5% of women of childbearing age. The etiology of RPL is complex, involving chromosomal abnormalities, autoimmune diseases, metabolic disorders, and endometrial dysfunction. The causes of abortion are still unknown in more than 50% of these cases. With the development of science and technology, an increasing number of scholars focus on this field and find that genetic factors may play an essential role in unexplained RPL, such as embolism-related genes, immune factor-related genes, and chromosomal numeric, and structural variation. This review summarizes the genetic factors associated with RPL, including genetic mutations and genetic polymorphisms, chromosomal variants, and chromosomal polymorphisms. Many related genetic factors have been found to be demographically and geographically relevant, some of which can be used for risk prediction or screening for the etiology of RPL. However, it is difficult to predict and prevent RPL due to uncertain pathogenesis and highly variable clinical presentation. Therefore, the genetic factors of RPL still need plentiful research to obtain a more accurate understanding of its pathogenesis and to provide more detection means for the screening and prevention of RPL.

Prevalence and associated factors of recurrent pregnancy loss in Nigeria according to different national and international criteria (ASRM/ESHRE vs. WHO/RCOG)

Background

In low-and middle-income countries, no conclusive research explains the prevalence and associated factors of women with a history of recurrent pregnancy loss (RPL). Some authorities have recommended further scientific research on the effect of various definitions of RPL.

Objective

To assess prevalence and associated factors of RPL among pregnant women in Nigeria according to different national and international criteria: the American Society for Reproductive Medicine/ European Society for Human Reproduction and Embryology (ASRM/ESHRE; two losses) and the World Health Organization/ Royal College of Obstetricians and Gynecologists (WHO/RCOG; three consecutive losses) criteria.

Methods

This is a cross-sectional analytical study wherein, pregnant women with prior RPL were investigated. The outcome measures were prevalence and risk factors. The associations between independent variables and outcome variable were explored using bivariate and multivariable logistic regression models. The results of these analyses were reported as adjusted odds ratios (AORs) with 95% confidence intervals (95%CI). Factors associated with RPL were identified using multivariate regression models.

Result

Of the 378 pregnant women interviewed, the overall prevalence of RPL in this study was found to be 15.34% (95% confidence interval = 11.65%-19.84%). The prevalence of RPL was 15.34% (58/378; 95%CI = 11.65%-19.84%) and 5.29% (20/378; 95%CI = 3.23%-8.17) according to the ASRM and the WHO criterion respectively. Regardless of diagnostic criteria, unexplained (AOR = 23.04; 95%CI: 11.46-36.32), endocrine disturbances (AOR = 9.76; 95%CI: 1.61-63.19), uterine abnormalities (AOR = 13.57; 95%CI: 3.54-50.60), and antiphospholipid syndrome (AOR = 24.59; 95%CI: 8.45-71.04) were positively and independently associated with RPL. No significant risk factors were seen when the ASRM/ ESHRE criterion vs. WHO/RCOG criterion were compared. Advanced maternal age was significantly higher in secondary than in primary type of RPL.

Conclusion

The prevalence of RPL was 15.34% and 5.29% according to ASRM/ESHRE and WHO/RCOG criterion respectively, with secondary type predominating. No significant differences with regard to risk factors were seen according to diagnostic criteria studied, though advanced maternal age was significantly higher in secondary RPL. Further research is needed to confirm our findings and to better characterize the magnitude of differences.

Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.