The Placental Innate Immune System Is Altered in Early-Onset Preeclampsia, but Not in Late-Onset Preeclampsia

Current Evidence of Maternal Infection With Chlamydia trachomatis and Preeclampsia Risk

Chlamydia trachomatis is the most common bacterial sexually transmitted infection (STI) in the United States. Ascending C. trachomatis can cause pelvic inflammatory disease (PID), potentially leading to subsequent infertility, ectopic pregnancy, and adverse pregnancy outcomes. There is growing evidence implicating infections (e.g., COVID-19, cytomegalovirus) in preeclampsia etiology, a maternal hypertensive disorder and leading cause of maternal morbidity and mortality. However, few studies have investigated the impact of STIs on preeclampsia risk. In this review, we provide an overview of the potential association between C. trachomatis and preeclampsia and identify future research needs through a critical evaluation of epidemiologic, in vitro, and in vivo studies. Unfortunately, current methodological limitations such as lower-quality study designs, selection bias, confounding bias, and variations in chlamydia diagnostic methods inhibit our understanding of the impact of C. trachomatis on preeclampsia. In addition, bench-side approaches such as animal models and in vitro studies have not elucidated the mechanisms linking C. trachomatis to preeclampsia. Understanding the biological pathways that could be disrupted by chlamydia is important as it may ultimately guide the development and use of novel therapeutics to augment standard antibiotic therapy to reduce pathology.

Integration of Immune Responses and Transcriptomic Signatures Reveals the Efficacy of Maternal Genetic Vaccination in a Pregnant Model and Its Neonates

Maternal vaccination is essential for safeguarding both mother and foetus from infectious diseases. This study investigated the immunogenicity and efficacy of a maternal ORF-B2L genetic vaccine in a pregnant rat model, focusing on maternal-neonatal immune modulation, placental and neonatal spleen transcriptomics and the underlying mechanisms contributing to neonatal immune development. Female rats received intramuscular injections of either a gene vaccine (GV) containing 200 μg of recombinant ORF-B2L DNA and 50 μg of a subunit protein or an empty plasmid as a control. Results showed significantly higher levels of specific anti-B2L antibodies and Th1 and Th2 cytokine levels in both maternal and neonatal sera from the GV group compared to the control group (p < 0.05). Transcriptome analysis identified 1295 differentially expressed genes (DEGs) in the placenta and 998 DEGs in the neonatal spleen, with upregulated pathways associated with immune cell recruitment, cytokine signalling and hormone regulation in the GV group. Notably, upregulated DEGs such as TLR4, ESR1 and various cytokine/chemokine-related genes in the placenta suggest enhanced immune regulation and foetal protection. In the neonatal spleen, increased expression of IL-1β, IL-6, IL-10 and CD69 indicates enhanced T and B cell development and pathogen defence. The upregulation of IL-1β suggests a Th1 response, while elevated IL-10 indicates a potential Th2-biased immunity, reflecting a balanced Th1/Th2 response that is crucial for effective adaptive immunity. Overall, maternal ORF-B2L genetic vaccination induces a robust immune response, enhancing maternal-foetal protection and shaping neonatal immune responses, offering valuable insights for optimizing maternal vaccination strategies.

Prediction Models for Late-Onset Preeclampsia: A Study Based on Logistic Regression, Support Vector Machine, and Extreme Gradient Boosting Models

Background: Preeclampsia, affecting 2-4% of pregnancies worldwide, poses a substantial risk to maternal health. Late-onset preeclampsia, in particular, has a high incidence among preeclampsia cases. However, existing prediction models are limited in terms of the early detection capabilities and often rely on costly and less accessible indicators, making them less applicable in resource-limited settings. Objective: To develop and evaluate prediction models for late-onset preeclampsia using general information, maternal risk factors, and laboratory indicators from early gestation (6-13 weeks). Methods: A dataset of 2000 pregnancies, including 110 late-onset preeclampsia cases, was analyzed. General information and maternal risk factors were collected from the hospital information system. Relevant laboratory indicators between 6 and 13 weeks of gestation were examined. Logistic regression was used as the baseline model to assess the predictive performance of the support vector machine and extreme gradient boosting models for late-onset preeclampsia. Results: The logistic regression model, only considering general information and risk factors, identified 19.1% of cases, with a false positive rate of 0.4%. When selecting 15 factors encompassing general information, risk factors, and laboratory indicators, the false positive rate increased to 0.7% and the detection rate improved to 27.3%. The support vector machine model, only considering general information and risk factors, achieved a detection rate of 27.3%, with a false positive rate of 0.0%. After including all the laboratory indicators, the false positive rate increased to 7.7% but the detection rate significantly improved to 54.5%. The extreme gradient boosting model, only considering general information and risk factors, achieved a detection rate of 31.6%, with a false positive rate of 1.5%. After including all the laboratory indicators, the false positive rate remained at 0.7% but the detection rate increased to 52.6%. Additionally, after adding the laboratory indicators, the areas under the ROC curve for the logistic regression, support vector machine, and extreme gradient boosting models were 0.877, 0.839, and 0.842, respectively. Conclusion: Compared with the logistic regression model, both the support vector machine and extreme gradient boosting models significantly improved the detection rates for late-onset preeclampsia. However, the support vector machine model had a comparatively higher false positive rate. Notably, the logistic regression and extreme gradient boosting models exhibited high negative predictive values of 99.3%, underscoring their effectiveness in accurately identifying pregnant women less likely to develop late-onset preeclampsia. Additionally, logistic regression showed the highest areas under the ROC curve, suggesting that the traditional model has unique advantages in relation to prediction.

Prediction Models for Late-Onset Preeclampsia: A Study Based on Logistic Regression, Support Vector Machine, and Extreme Gradient Boosting Models

Background: Preeclampsia, affecting 2–4% of pregnancies worldwide, poses a substantial risk to maternal health. Late-onset preeclampsia, in particular, has a high incidence among preeclampsia cases. However, existing prediction models are limited in terms of the early detection capabilities and often rely on costly and less accessible indicators, making them less applicable in resource-limited settings. Objective: To develop and evaluate prediction models for late-onset preeclampsia using general information, maternal risk factors, and laboratory indicators from early gestation (6–13 weeks). Methods: A dataset of 2000 pregnancies, including 110 late-onset preeclampsia cases, was analyzed. General information and maternal risk factors were collected from the hospital information system. Relevant laboratory indicators between 6 and 13 weeks of gestation were examined. Logistic regression was used as the baseline model to assess the predictive performance of the support vector machine and extreme gradient boosting models for late-onset preeclampsia. Results: The logistic regression model, only considering general information and risk factors, identified 19.1% of cases, with a false positive rate of 0.4%. When selecting 15 factors encompassing general information, risk factors, and laboratory indicators, the false positive rate increased to 0.7% and the detection rate improved to 27.3%. The support vector machine model, only considering general information and risk factors, achieved a detection rate of 27.3%, with a false positive rate of 0.0%. After including all the laboratory indicators, the false positive rate increased to 7.7% but the detection rate significantly improved to 54.5%. The extreme gradient boosting model, only considering general information and risk factors, achieved a detection rate of 31.6%, with a false positive rate of 1.5%. After including all the laboratory indicators, the false positive rate remained at 0.7% but the detection rate increased to 52.6%. Additionally, after adding the laboratory indicators, the areas under the ROC curve for the logistic regression, support vector machine, and extreme gradient boosting models were 0.877, 0.839, and 0.842, respectively. Conclusion: Compared with the logistic regression model, both the support vector machine and extreme gradient boosting models significantly improved the detection rates for late-onset preeclampsia. However, the support vector machine model had a comparatively higher false positive rate. Notably, the logistic regression and extreme gradient boosting models exhibited high negative predictive values of 99.3%, underscoring their effectiveness in accurately identifying pregnant women less likely to develop late-onset preeclampsia. Additionally, logistic regression showed the highest areas under the ROC curve, suggesting that the traditional model has unique advantages in relation to prediction.

Early prediction of preeclampsia using the first trimester vaginal microbiome

Preeclampsia is a severe obstetrical syndrome which contributes to 10-15% of all maternal deaths. Although the mechanisms underlying systemic damage in preeclampsia-such as impaired placentation, endothelial dysfunction, and immune dysregulation-are well studied, the initial triggers of the condition remain largely unknown. Furthermore, although the pathogenesis of preeclampsia begins early in pregnancy, there are no early diagnostics for this life-threatening syndrome, which is typically diagnosed much later, after systemic damage has already manifested. Here, we performed deep metagenomic sequencing and multiplex immunoassays of vaginal samples collected during the first trimester from 124 pregnant individuals, including 62 who developed preeclampsia with severe features. We identified multiple significant associations between vaginal immune factors, microbes, clinical factors, and the early pathogenesis of preeclampsia. These associations vary with BMI, and stratification revealed strong associations between preeclampsia and Bifidobacterium spp., Prevotella timonensis, and Sneathia vaginalis. Finally, we developed machine learning models that predict the development of preeclampsia using this first trimester data, collected ~5.7 months prior to clinical diagnosis, with an auROC of 0.78. We validated our models using data from an independent cohort (MOMS-PI), achieving an auROC of 0.80. Our findings highlight robust associations among the vaginal microbiome, local host immunity, and early pathogenic processes of preeclampsia, paving the way for early detection, prevention and intervention for this devastating condition.

Evaluation of outcomes and risk factors for recurrent preeclampsia in a subsequent pregnancy

PURPOSE

The aim was to evaluate the pregnancy outcomes and identify risk factors for recurrent preeclampsia (PE).

METHODS

Retrospective analysis of patients discharged with PE between January 1, 2010, and January 1, 2023, from two tertiary referral hospitals. They were classified into recurrent and non-recurrent groups based on the presence of PE in subsequent pregnancies.

RESULTS

Among 519 women who had a subsequent pregnancy after a history of PE, 153 developed recurrent PE while 366 did not. The recurrent cases included 81 preterm PE, of which 41 were early-onset PE (EOPE). Recurrent PE correlated significantly with prior EOPE, HELLP syndrome, placental abruption, and stillbirth, as well as with current chronic hypertension (CH) and type 2 diabetes. The recurrent group showed a 5.8-fold higher risk of preterm birth (PTB) compared to the non-recurrent group (50.7% vs. 8.7%). Notably, 58.1% of the PTBs in the non-recurrent group were spontaneous. Logistic regression identified previous EOPE (aOR: 4.22 [95% CI: 2.50-7.13]) and current CH (aOR: 1.86 [95% CI: 1.09-3.18]) as independent contributors for recurrent PE. Furthermore, recurrent preterm PE shared the same risk factors: previous EOPE (aOR: 5.27 [95% CI: 2.82-9.85]) and current CH (aOR: 2.99 [95% CI: 1.57-5.71]). The morbidity of CH in subsequent pregnancy peaked at 31.9% when women with a history of EOPE delivered within three years.

CONCLUSION

Previous EOPE and current CH were sequentially crucial risk factors for the development of PE and preterm PE during the next pregnancy. This may clarify risk stratification in prenatal management for women with a history of PE.

Development and validation of preeclampsia predictive models using key genes from bioinformatics and machine learning approaches

Background

Preeclampsia (PE) poses significant diagnostic and therapeutic challenges. This study aims to identify novel genes for potential diagnostic and therapeutic targets, illuminating the immune mechanisms involved.

Methods

Three GEO datasets were analyzed, merging two for training set, and using the third for external validation. Intersection analysis of differentially expressed genes (DEGs) and WGCNA highlighted candidate genes. These were further refined through LASSO, SVM-RFE, and RF algorithms to identify diagnostic hub genes. Diagnostic efficacy was assessed using ROC curves. A predictive nomogram and fully Connected Neural Network (FCNN) were developed for PE prediction. ssGSEA and correlation analysis were employed to investigate the immune landscape. Further validation was provided by qRT-PCR on human placental samples.

Result

Five biomarkers were identified with validation AUCs: CGB5 (0.663, 95% CI: 0.577-0.750), LEP (0.850, 95% CI: 0.792-0.908), LRRC1 (0.797, 95% CI: 0.728-0.867), PAPPA2 (0.839, 95% CI: 0.775-0.902), and SLC20A1 (0.811, 95% CI: 0.742-0.880), all of which are involved in key biological processes. The nomogram showed strong predictive power (C-index 0.873), while FCNN achieved an optimal AUC of 0.911 (95% CI: 0.732-1.000) in five-fold cross-validation. Immune infiltration analysis revealed the importance of T cell subsets, neutrophils, and NK cells in PE, linking these genes to immune mechanisms underlying PE pathogenesis.

Conclusion

CGB5, LEP, LRRC1, PAPPA2, and SLC20A1 are validated as key diagnostic biomarkers for PE. Nomogram and FCNN could credibly predict PE. Their association with immune infiltration underscores the crucial role of immune responses in PE pathogenesis.

Effect of low-molecular-weight heparin calcium combined with magnesium sulfate and labetalol on coagulation, vascular endothelial function and pregnancy outcome in early-onset severe preeclampsia

OBJECTIVE

This paper was aimed at unveiling the effect of low-molecular-weight heparin calcium (LMWH) combined with magnesium sulfate and labetalol on coagulation, vascular endothelial function, and pregnancy outcome in early-onset severe preeclampsia (EOSP).

METHODS

Pregnant women with EOSP were divided into the control group and the study group, each with 62 cases. Patients in the control group were treated with labetalol and magnesium sulfate, and those in the study group were treated with LMWH in combination with the control grou Blood pressure (systolic blood pressure [SBP] and diastolic blood pressure [DBP]), 24-h urine protein, coagulation indices [D-dimer (D-D), plasma fibrinogen (Fg), prothrombin time (PT), activated partial thromboplastin time (APTT), and prothrombin time (TT)], endothelial function [endothelin (ET-1) and nitric oxide (NO)], oxidative stress indices [oxidized low-density lipoproteins (ox-LDL), lipid peroxidation (LPO), superoxide dismutase (SOD), and malondialdehyde (MDA)], pregnancy outcome, and adverse effects occurred in the two groups were compared.

RESULTS

After treatment, lower SBP, DBP, and 24-h urine protein levels; lower Fg and D-D levels; higher PT, APPT, and TT levels; higher NO levels; lower ET-1 levels; lower ox-LDL, MDA, and LPO levels; higher SOD levels; and lower incidence of adverse pregnancy and adverse reactions were noted in the study group in contrast to the control group.

CONCLUSION

EOSP patients given with LMWH combined with magnesium sulfate and labetalol can effectively reduce the patient's blood pressure and urinary protein level; improve coagulation function, oxidative stress, and vascular endothelial function indices; reduce the adverse pregnancy outcomes; and improve the safety of treatment.

Evolutionary Analysis of the Mammalian IL-17 Cytokine Family Suggests Conserved Roles in Female Fertility

PROBLEM

The interleukin-17 (IL-17) family includes pro-inflammatory cytokines IL-17A-F with important roles in mucosal defence, barrier integrity and tissue regeneration. IL-17A can be dysregulated in fertility complications, including pre-eclampsia, endometriosis and miscarriage. Because mammalian subclasses (eutherian, metatherian, and prototherian) have different related reproductive strategies, IL-17 genes and proteins were investigated in the three mammalian classes to explore their involvement in female fertility.

METHOD OF STUDY

Gene and protein sequences for IL-17s are found in eutherian, metatherian and prototherian mammals. Through synteny and multiple sequence protein alignment, the relationships among mammalian IL-17s were inferred. Publicly available datasets of early pregnancy stages and female fertility in therian mammals were collected and analysed to retrieve information on IL-17 expression.

RESULTS

Synteny mapping and phylogenetic analyses allowed the classification of mammalian IL-17 family orthologs of human IL-17. Despite differences in their primary amino acid sequence, metatherian and prototherian IL-17s share the same tertiary structure as human IL-17s, suggesting similar functions. The analysis of available datasets for female fertility in therian mammals shows up-regulation of IL-17A and IL-17D during placentation. IL-17B and IL-17D are also found to be over-expressed in human fertility complication datasets, such as endometriosis or recurrent implantation failure.

CONCLUSIONS

The conservation of the IL-17 gene and protein across mammals suggests similar functions in all the analysed species. Despite significant differences, the upregulation of IL-17 expression is associated with the establishment of pregnancy in eutherian and metatherian mammals. The dysregulation of IL-17s in human reproductive disorders suggests them as a potential therapeutic target.

Differential proteomics of circulating extracellular vesicles of placental origin isolated from women with early-onset preeclampsia reveal aberrant innate immune and hemostasis processes

PROBLEM

Early-onset preeclampsia (EOPE) is a severe gestational hypertensive disorder with significant feto-maternal morbidity and mortality due to uteroplacental insufficiency. Circulating extracellular vesicles of placental origin (EV-P) are known to be involved in the pathophysiology of EOPE and might serve as an ideal reservoir for its specific biomarkers. Therefore, we aimed to characterize and perform comparative proteomics of circulating EV-P from healthy pregnant and EOPE women before delivery.

METHOD OF STUDY

The EV-P from both groups were isolated using immunoaffinity and were characterized using transmission electron microscopy, dynamic light scattering, nanoparticle tracking analysis, and immunoblotting. Following IgG albumin depletion, the pooled proteins that were isolated from EV-P of both groups were subjected to quantitative TMT proteomics.

RESULTS

Circulating term EV-P isolated from both groups revealed ∼150 nm spherical vesicles containing CD9 and CD63 along with placental PLAP and HLA-G proteins. Additionally, the concentration of EOPE-derived EV-P was significantly increased. A total of 208 proteins were identified, with 26 among them being differentially abundant in EV-P of EOPE women. This study linked the pathophysiology of EOPE to 19 known and seven novel proteins associated with innate immune responses such as complement and TLR signaling along with hemostasis and oxygen homeostasis.

CONCLUSION

The theory suggesting circulating EVs of placental origin could mimic molecular information from the parent organ-"the placenta"-is strengthened by this study. The findings pave the way for possible discovery of novel prognostic and predictive biomarkers as well as provide insight into the mechanisms driving the pathogenesis of EOPE.

Novel insights into the complex interplay of immune dysregulation and inflammatory biomarkers in preeclampsia and fetal growth restriction: A two-step Mendelian randomization analysis

Background

The relationship between genetic immune dysregulation and the occurrence of preeclampsia (PE) or PE with fetal growth restriction (PE with FGR) has yielded inconsistent findings, and the underlying mediators of this association remain elusive. We aimed to explore the causal impact of genetic immune dysregulation on the risk of PE or PE with FGR and to elucidate the role of specific transcriptomes in mediating this relationship.

Methods

A two-step Mendelian randomization (MR) analysis was performed to explore the link between immune dysregulation and PE or PE with FGR, as well as to identify potential inflammatory biomarkers that act as mediators. GWAS summary data for outcomes were obtained from the FinnGen dataset. The analyses encompassed five systemic immune-associated diseases, four chronic genital inflammatory diseases, and thirty-one inflammatory biomarkers. Summary-data-based MR (SMR) and HEIDI analysis were conducted to test whether the effect size of single nucleotide polymorphisms (SNPs) on outcomes was mediated by the expression of immune-associated genes.

Results

The primary univariable analysis revealed a significant positive correlation between systemic lupus erythematosus (SLE), type 1 diabetes (T1D), type 2 diabetes (T2D), and rheumatoid arthritis (RA) with the risk of PE or PE with FGR. Surprisingly, a counterintuitive finding showed a significant negative association between endometriosis of pelvic peritoneum (EMoP) and the risk of PE with FGR. None of the inflammatory factors had a causal relationship with PE or PE with FGR. However, there was a significant association between lymphocyte count and the risk of PE with FGR. Within the lymphocyte subset, both the proportion of Natural Killer (NK) cells and absolute counts of naïve CD4+ T cells demonstrated significant effects on the risk of PE with FGR. Two-step MR analysis underscored the genetically predicted lymphocyte count as a significant mediator between T1D and PE with FGR. Additionally, SMR analysis indicated the potential involvement of SH2B3 in the occurrence of PE with FGR.

Conclusions

Our findings provided substantial evidence of the underlying causal relationship between immune dysregulation and PE or PE with FGR and some of these diseases proved to accelerate immune cells disorders and then contribute to the risk of incident PE or PE with FGR.

Data-driven insights can transform women's reproductive health

This perspective explores the transformative potential of data-driven insights to understand and address women's reproductive health conditions. Historically, clinical studies often excluded women, hindering comprehensive research into conditions such as adverse pregnancy outcomes and endometriosis. Recent advances in technology (e.g., next-generation sequencing techniques, electronic medical records (EMRs), computational power) provide unprecedented opportunities for research in women's reproductive health. Studies of molecular data, including large-scale meta-analyses, provide valuable insights into conditions like preterm birth and preeclampsia. Moreover, EMRs and other clinical data sources enable researchers to study populations of individuals, uncovering trends and associations in women's reproductive health conditions. Despite these advancements, challenges such as data completeness, accuracy, and representation persist. We emphasize the importance of holistic approaches, greater inclusion, and refining and expanding on how we leverage data and computational integrative approaches for discoveries so that we can benefit not only women's reproductive health but overall human health.

Differences in Cardiometabolic Proteins in Pregnancy Prioritize Relevant Targets of Preeclampsia

BACKGROUND

Preeclampsia is a hypertensive disorder of pregnancy characterized by widespread vascular inflammation. It occurs frequently in pregnancy, often without known risk factors, and has high rates of maternal and fetal morbidity and mortality. Identification of biomarkers that predict preeclampsia and its cardiovascular sequelae before clinical onset, or even before pregnancy, is a critical unmet need for the prevention of adverse pregnancy outcomes.

METHODS

We explored differences in cardiovascular proteomics (Olink Explore 384) in 256 diverse pregnant persons across 2 centers (26% Hispanic, 21% Black).

RESULTS

We identified significant differences in plasma abundance of markers associated with angiogenesis, blood pressure, cell adhesion, inflammation, and metabolism between individuals delivering with preeclampsia and controls, some of which have not been widely described previously and are not represented in the preeclampsia placental transcriptome. While we observed a broadly similar pattern in early (<34 weeks) versus late (≥34 weeks) preeclampsia, several proteins related to hemodynamic stress, hemostasis, and immune response appeared to be more highly dysregulated in early preeclampsia relative to late preeclampsia.

CONCLUSIONS

These results demonstrate the value of performing targeted proteomics using a panel of cardiovascular biomarkers to identify biomarkers relevant to preeclampsia pathophysiology and highlight the need for larger multiomic studies to define modifiable pathways of surveillance and intervention upstream to preeclampsia diagnosis.

Comparison of immune-related gene signatures and immune infiltration features in early- and late-onset preeclampsia

BACKGROUND

Preeclampsia, a severe pregnancy syndrome, is widely accepted divided into early- and late-onset preeclampsia (EOPE and LOPE) based on the onset time of preeclampsia, with distinct pathophysiological origins. However, the molecular mechanism especially immune-related mechanisms for EOPE and LOPE is currently obscure. In the present study, we focused on placental immune alterations between EOPE and LOPE and search for immune-related biomarkers that could potentially serve as potential therapeutic targets through bioinformatic analysis.

METHODS

The gene expression profiling data was obtained from the Gene Expression Omnibus database. ESTIMATE algorithm and Gene Set Enrichment Analysis were employed to evaluate the immune status. The intersection of differentially expressed genes in GSE74341 series and immune-related genes set screened differentially expressed immune-related genes. Protein-protein interaction network and random forest were used to identify hub genes with a validation by a quantitative real-time PCR. Kyoto Encyclopedia of Genes and Genomes pathways, Gene Ontology and gene set variation analysis were utilized to conduct biological function and pathway enrichment analyses. Single-sample gene set enrichment analysis and CIBERSORTx tools were employed to calculate the immune cell infiltration score. Correlation analyses were evaluated by Pearson correlation analysis. Hub genes-miRNA network was performed by the NetworkAnalyst online tool.

RESULTS

Immune score and stromal score were all lower in EOPE samples. The immune system-related gene set was significantly downregulated in EOPE compared to LOPE samples. Four hub differentially expressed immune-related genes (IL15, GZMB, IL1B and CXCL12) were identified based on a protein-protein interaction network and random forest. Quantitative real-time polymerase chain reaction validated the lower expression levels of four hub genes in EOPE compared to LOPE samples. Immune cell infiltration analysis found that innate and adaptive immune cells were apparent lacking in EOPE samples compared to LOPE samples. Cytokine-cytokine receptor, para-inflammation, major histocompatibility complex class I and T cell co-stimulation pathways were significantly deficient and highly correlated with hub genes. We constructed a hub genes-miRNA regulatory network, revealing the correlation between hub genes and hsa-miR-374a-5p, hsa-miR-203a-3p, hsa-miR-128-3p, hsa-miR-155-3p, hsa-miR-129-2-3p and hsa-miR-7-5p.

CONCLUSIONS

The innate and adaptive immune systems were severely impaired in placentas of EOPE. Four immune-related genes (IL15, GZMB, IL1B and CXCL12) were closely correlated with immune-related pathogenesis of EOPE. The result of our study may provide a new basis for discriminating between EOPE and LOPE and acknowledging the role of the immune landscape in the eventual interference and tailored treatment of EOPE.

The effects of inflammation and acidosis on placental blood vessels reactivity

INTRODUCTION

Inflammation and acidosis are two stress stimuli that correspond to pathophysiological processes occurring in placental-mediated vascular disorders. We aimed to investigate the effects of these stimuli on placental chorionic blood vessels reactivity using the ex-vivo placental perfusion model.

METHODS

Term placentas were obtained immediately after cesarean deliveries, and selected cotyledons were cannulated and dually perfused ex-vivo. Placentas were perfused with three different protocols: culture medium (M199-controls, n = 5), culture medium with lipopolysaccharide (inflammatory stimuli) (LPS,1 μg/ml, n = 7), and acidotic culture medium (M - 199, pH: 6.9-7, n = 6). Each perfusion experiment was maintained for 180 min. Fetal perfusion pressure was continuously measured. Measurements in response to angiotensin II (AT II) at the end of the perfusion were compared between the treatment groups, including amplitude of the contraction response, relaxation factor, time to maximal constriction and the area under the pressure curve (AUC).

RESULTS

In response to ATII there was a significant difference in the amplitude of the contraction and the AUC between the treatment groups, (p = 0.049, p = 0.015, respectively). As compared with control perfused cotyledon, the inflammatory stimuli significantly increased the vasoconstriction response to ATII in fetal placental blood vessels, as expressed by increased AUC - median (IQR): 555 (235-1184) vs. 133 (118-207), respectively, p = 0.017. The time to maximal constriction and the relaxation factor did not differ between the groups.

DISCUSSION

Inflammatory stimuli but not acidosis impact fetal-placental vasculature in response to ATII, suggesting that inflammation can compromise vascular function.

Molecular Factors Involved in the Reproductive Morphophysiology of Female Domestic Cat (Felis catus)

The domestic cat (Felis catus) is considered an important model for the study of feline reproductive morphophysiology. However, although the morphological changes and clinical signs that occur during the estrous cycle and pregnancy are well known, little is known about the molecular mechanisms involved in the reproductive physiology of this animal species. Thus, this paper reviews the current knowledge about the modulation and expression profile of hormonal, immunological, redox, and growth mediators involved in the uterine, ovarian, and placental morphophysiology of domestic cats.

COVID-19. Biology, pathophysiology, and immunology: a pathologist view

Even if the SARS-CoV-2 pandemic has been declared over, several risks and clinical problems remain to be faced, including long-COVID sequelae and possible outbreaks of pathogenic variants. Intense research on COVID-19 has provided in these few years a striking amount of data covering different fields and disciplines, which can help to provide a knowledge shield against new potential infective spreads, and may also potentially be applied to other fields of medicine, including oncology and neurology. Nevertheless, areas of uncertainty still remain regarding the pathogenic mechanisms that subtend the multifaceted manifestations of the disease. To better clarify the pathogenesis of the disease, a systematic multidisciplinary evaluation of the many mechanisms involved in COVID-19 is mandatory, including clinical, physiological, radiological, immunological and pathological studies. In COVID-19 syndrome the pathological studies have been mainly performed on autopsy cases, and only a few studies are available on biopsies. Nevertheless, these studies have provided relevant information that can substantially contribute to decipher the complex scenario characterizing the different forms of COVID-19 and long-COVID-19. In this review the data provided by pathological investigations are recapitulated and discussed, in the light of different hypothesis and data provided by clinical, physiological and immunological data.

Elevated expression of glycolytic genes as a prominent feature of early-onset preeclampsia: insights from integrative transcriptomic analysis

Introduction: Preeclampsia (PE), a notable pregnancy-related disorder, leads to 40,000+ maternal deaths yearly. Recent research shows PE divides into early-onset (EOPE) and late-onset (LOPE) subtypes, each with distinct clinical features and outcomes. However, the molecular characteristics of various subtypes are currently subject to debate and are not consistent. Methods: We integrated transcriptomic expression data from a total of 372 placental samples across 8 publicly available databases via combat algorithm. Then, a variety of strategies including Random Forest Recursive Feature Elimination (RF-RFE), differential analysis, oposSOM, and Weighted Correlation Network Analysis were employed to identify the characteristic genes of the EOPE and LOPE subtypes. Finally, we conducted in vitro experiments on the key gene HK2 in HTR8/SVneo cells to explore its function. Results: Our results revealed a complex classification of PE placental samples, wherein EOPE manifests as a highly homogeneous sample group characterized by hypoxia and HIF1A activation. Among the core features is the upregulation of glycolysis-related genes, particularly HK2, in the placenta-an observation corroborated by independent validation data and single-cell data. Building on the pronounced correlation between HK2 and EOPE, we conducted in vitro experiments to assess the potential functional impact of HK2 on trophoblast cells. Additionally, the LOPE samples exhibit strong heterogeneity and lack distinct features, suggesting a complex molecular makeup for this subtype. Unsupervised clustering analysis indicates that LOPE likely comprises at least two distinct subtypes, linked to cell-environment interaction and cytokine and protein modification functionalities. Discussion: In summary, these findings elucidate potential mechanistic differences between the two PE subtypes, lend support to the hypothesis of classifying PE based on gestational weeks, and emphasize the potential significant role of glycolysis-related genes, especially HK2 in EOPE.

Pentoxifylline as a therapeutic option for pre-eclampsia: a study on its placental effects

BACKGROUND AND PURPOSE

Recently pentoxifylline, a non-selective phosphodiesterase inhibitor and adenosine receptor antagonist, has attracted much interest for the treatment of the increased vascular resistance and endothelial dysfunction in pre-eclampsia. We therefore investigated the placental transfer, vascular effects and anti-inflammatory actions of pentoxifylline in healthy and pre-eclamptic human placentas.

EXPERIMENTAL APPROACH

The placental transfer and metabolism of pentoxifylline were studied using ex vivo placenta perfusion experiments. In wire myography experiments with chorionic plate arteries, pentoxifyllines vasodilator properties were investigated, focusing on the cGMP and cAMP pathways and adenosine receptors. Its effects on inflammatory factors were also studied in placental explants.

KEY RESULTS

Pentoxifylline transferred from the maternal to foetal circulation, reaching identical concentrations. The placenta metabolized pentoxifylline into its active metabolite lisofylline (M1), which was released into both circulations. In healthy placentas, pentoxifylline potentiated cAMP- and cGMP-induced vasodilation, as well as causing vasodilation by adenosine A₁ antagonism and via NO synthase and PKG. Pentoxifylline also reduced inflammatory factors secretion. In pre-eclamptic placentas, we observed that its vasodilator capacity was preserved, however not via NO-PKG but likely through adenosine signalling. Pentoxifylline neither potentiated vasodilation through cAMP and cGMP, nor suppressed the release of inflammatory factors from these placentas.

CONCLUSION AND IMPLICATIONS

Pentoxifylline is transferred across and metabolized by the placenta. Its beneficial effects on the NO pathway and inflammation are not retained in pre-eclampsia, limiting its application in this disease, although it could be useful for other placenta-related disorders. Future studies might focus on selective A₁ receptor antagonists as a new treatment for pre-eclampsia.

Human Leukocyte Antigen HLA-C, HLA-G, HLA-F and HLA-E placental profiles are altered in Early Severe Preeclampsia and Preterm Birth with Chorioamnionitis

BACKGROUND

The extravillous trophoblast expresses each of the non-classical MHC class I antigens - HLA-E, F, and G and a single classical class I antigen HLA-C. We recently demonstrated dynamic expression patterns of HLA-C, G and F during early EVT invasion and placentation.

OBJECTIVE

In this study we investigate the hypothesis that the immune inflammatory mediated complications of pregnancy such as early preeclampsia and preterm labor, may show altered expression profiles of non-classical HLA.

STUDY DESIGN

Real time q-PCR, western blot and immunohistochemistry were performed on placental villous tissues and basal plate sections from term non-laboring deliveries, preterm deliveries and severe early onset preeclampsia both with and without small for gestational age neonates.

RESULTS

HLA-G is strongly and exclusively expressed by the EVT within the placental basal plate and its levels increase in pregnancies complicated by severe early onset PE with SGA neonates as compared to healthy term controls. HLA-C shows a similar profile in the EVT of PE pregnancies, but significantly decreases in the villous placenta. HLA-F protein levels are decreased in both EVT and villous placenta of severe early onset PE pregnancies both with and without SGA babies as compared to Term and PTB deliveries. HLA-E decreases in blood vessels in placentas from PE pregnancies as compared to Term and PTB deliveries. HLA-F and HLA-C are increased in the placenta of PTBs with chorioamnionitis as compared to idiopathic PTB.

CONCLUSION

Dysregulation of placental HLA expression at the maternal fetal interface may contribute to the compromised maternal tolerance in PTB with chorioamnionitis and excessive maternal systemic inflammation associated with severe early onset PE.

Inflammation in Preeclampsia: Genetic Biomarkers, Mechanisms, and Therapeutic Strategies

Objective

Preeclampsia is a common and serious complication of pregnancy, posing a threat to maternal and fetal safety due to the lack of effective biomarkers and treatment strategies. This study aimed to identify potential biomarkers that can be used to predict preeclampsia and identify the molecular mechanisms of preeclampsia pathogenesis and drug prediction at the transcriptome level.

Methods

We analyzed differential expression genes (DEGs) in preeclampsia and non-preeclampsia groups in the GSE75010 dataset, cross-linking with extracted inflammatory response-related genes to obtain differentially expressed inflammation-related genes (DINRGs). Enrichment analysis and protein-protein interaction (PPI) networks were constructed to understand the functions and enrichment pathways. Machine learning models were used to identify key genes associated with preeclampsia and build a nomogram in the training set, which was validated in the validation set. The R package RcisTarget was used to predict transcription factors, and Cytoscape was used to construct miRNA-mRNA pathways, which could identify the molecular mechanisms. Then, we conducted molecular docking of the obtained key genes INHBA (inhibin subunit beta A), OPRK1 (opioid receptor kappa 1), and TPBG (trophoblast glycoprotein), as well as predicted transcription factors with drug molecules. Additionally, the CIBERSORT method explored the differences in immune cell infiltration between preeclampsia and non-preeclampsia samples based on the GSE75010 dataset.

Results

A total of 69 DINRGs associated with preeclampsia patients were screened. INHBA, OPRK1, and TPBG were the key genes based on machine learning models. A nomogram for prediction was further constructed, and the receiver operating curves (ROCs) showed good performance. Based on the transcriptome level of key genes, we proposed that RELA-miR-548K/miR-1206-TPBG may be a potential RNA regulatory pathway regulating the progression of early preeclampsia. Molecular docking suggested the effectiveness of curcumin in the treatment of preeclampsia. Additionally, regulatory T cells (Tregs) and resting mast cells were significantly different between the two groups.

Conclusion

In summary, we identified three key inflammation-associated genes, namely INHBA, OPRK1, and TPBG, which can be used as potential genetic biomarkers for preeclampsia prediction and treatment, and established a nomogram as a predictive model. Additionally, we provided insights into the mechanisms of preeclampsia development at the transcriptome level and performed corresponding drug predictions.

Network-Based Analysis Reveals Novel Biomarkers in Peripheral Blood of Patients With Preeclampsia

WGCNA is a potent systems biology approach that explains the connection of gene expression based on a microarray database, which facilitates the discovery of disease therapy targets or potential biomarkers. Preeclampsia is a kind of pregnancy-induced hypertension caused by complex factors. The disease’s pathophysiology, however, remains unknown. The focus of this research is to utilize WGCNA to identify susceptible modules and genes in the peripheral blood of preeclampsia patients. Obtain the whole gene expression data of GSE48424 preeclampsia patients and normal pregnant women from NCBI’s GEO database. WGCNA is used to construct a gene co-expression network by calculating correlation coefficients between modules and phenotypic traits, screening important modules, and filtering central genes. To identify hub genes, we performed functional enrichment analysis, pathway analysis, and protein-protein interaction (PPI) network construction on key genes in critical modules. Then, the genetic data file GSE149437 and clinical peripheral blood samples were used as a validation cohort to determine the diagnostic value of these key genes. Nine gene co-expression modules were constructed through WGCNA analysis. Among them, the blue module is significantly related to preeclampsia and is related to its clinical severity. Thirty genes have been discovered by using the intersection of the genes in the blue module and the DEGs genes as the hub genes. It was found that HDC, MS4A2, and SLC18A2 scored higher in the PPI network and were identified as hub genes. These three genes were also differentially expressed in peripheral blood validation samples. Based on the above three genes, we established the prediction model of peripheral blood markers of preeclampsia and drew the nomogram and calibration curve. The ROC curves were used in the training cohort GSE48424 and the validation cohort GSE149437 to verify the predictive value of the above model. Finally, it was confirmed in the collected clinical peripheral blood samples that MS4A2 was differentially expressed in the peripheral blood of early-onset and late-onset preeclampsia, which is of great significance. This study provides a new biomarker and prediction model for preeclampsia.

Interactions between Macrophages and Mast Cells in the Female Reproductive System

Mast cells (MCs) and macrophages (Mϕs) are innate immune cells that differentiate from early common myeloid precursors and reside in all body tissues. MCs have a unique capacity to neutralize/degrade toxic proteins, and they are hypothesized as being able to adopt two alternative polarization profiles, similar to Mϕs, with distinct or even opposite roles. Mϕs are very plastic phagocytic cells that are devoted to the elimination of senescent/anomalous endogenous entities (to maintain tissue homeostasis), and to the recognition and elimination of exogenous threats. They can adopt several functional phenotypes in response to microenvironmental cues, whose extreme profiles are the inflammatory/killing phenotype (M1) and the anti-inflammatory/healing phenotype (M2). The concomitant and abundant presence of these two cell types and the partial overlap of their defensive and homeostatic functions leads to the hypothesis that their crosstalk is necessary for the optimal coordination of their functions, both under physiological and pathological conditions. This review will examine the relationship between MCs and Mϕs in some situations of homeostatic regulation (menstrual cycle, embryo implantation), and in some inflammatory conditions in the same organs (endometriosis, preeclampsia), in order to appreciate the importance of their cross-regulation.