TREM-1 amplifies trophoblastic inflammation via activating NF-κB pathway during preeclampsia

NFĸB and its inhibitors in preeclampsia: mechanisms and potential interventions

Preeclampsia (PE), which affects between 2 and 15% of pregnancies, is one of the most often reported prenatal problems. It is defined as gestational hypertension beyond 20 weeks of pregnancy, along with widespread edema or proteinuria and specific types of organ damage. PE is characterized by increased levels and activation of nuclear factor kappa B (NF-κB) in the mother's blood and placental cells. This factor controls over 400 genes linked to inflammatory, apoptotic, angiogenesis, and cellular responses to hypoxia and oxidative stress. In the final stages of physiological pregnancy, NF-κB levels need to be lowered to favor maternal immunosuppressive events and continue gestation to prevent hypoxia and inflammation, which are advantageous for implantation. Pharmacotherapy is thought to be a potential treatment for PE by downregulating NF-κB activation. NF-κB activity has been discovered to be regulated by several medications used for both prevention and treatment of PE. However, in order to guarantee treatment safety and effectiveness, additional creativity is desperately required. This article provides an overview of the current understanding of the defined function of NF-κB in PE progression. According to their effect on the cellular control of NF-κB pathways, newly proposed compounds for preventing and treating PE have also been emphasized.

Inhibition of BCAT1 expression improves recurrent miscarriage by regulating cellular dysfunction and inflammation of trophoblasts

Sustained or chronic inflammation in the placenta can result in placental insufficiency, leading to adverse reproductive outcomes such as pregnancy loss. Branched-chain amino acid transaminase 1 (BCAT1) expresses in the placenta and is involved in the pathological inflammatory response, but its role in recurrent miscarriage (RM) has not been fully investigated. In the present study, we delved into the effects of BCAT1 on trophoblast inflammation induced by lipopolysaccharide (LPS) and a mouse model of pregnancy loss induced by LPS. In vitro, after the HTR-8/SVneo cells were treated with LPS and BCATc inhibitor 2 (a selective BCAT inhibitor), the cell apoptosis was verified by TUNEL assay, and the activity of caspase-3 and caspase-9 was detected. Real-time PCR, enzyme-linked immunosorbent assay (ELISA), and immunofluorescence (IF) were used to determine the expression of inflammatory cytokines (TNF-α, IL-6, and IL-1β) and inflammasomes (NLRP3 and ASC) in LPS-treated trophoblast cells. Western blot analysis was performed to verify the expression of phospho-IκBα (p-IκBα) in cells and NF-κB p65 in the nuclei. IF staining was used to detect the nuclear translocation of NF-κB p65. The DNA binding activity of NF-κB was detected by an electrophoretic mobility shift assay (EMSA). The results demonstrated that inhibition of BCAT1 reduced trophoblast apoptosis, suppressed the release of proinflammatory cytokines, and prevented NLRP3 inflammasome activation in response to LPS. Additionally, BCAT1 inhibition blocked the activation of the NF-κB pathway in trophoblasts. This study highlights the potential therapeutic role of targeting BCAT1 in preventing adverse reproductive outcomes associated with chronic placental inflammation.

Integrated transcriptomic analysis and machine learning for characterizing diagnostic biomarkers and immune cell infiltration in fetal growth restriction

Background

Fetal growth restriction (FGR) occurs in 10% of pregnancies worldwide. Placenta dysfunction, as one of the most common causes of FGR, is associated with various poor perinatal outcomes. The main objectives of this study were to screen potential diagnostic biomarkers for FGR and to evaluate the function of immune cell infiltration in the process of FGR.

Methods

Firstly, differential expression genes (DEGs) were identified in two Gene Expression Omnibus (GEO) datasets, and gene set enrichment analysis was performed. Diagnosis-related key genes were identified by using three machine learning algorithms (least absolute shrinkage and selection operator, random forest, and support vector machine model), and the nomogram was then developed. The receiver operating characteristic curve, calibration curve, and decision curve analysis curve were used to verify the validity of the diagnostic model. Using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), the characteristics of immune cell infiltration in placental tissue of FGR were evaluated and the candidate key immune cells of FGR were screened. In addition, this study also validated the diagnostic efficacy of TREM1 in the real world and explored associations between TREM1 and various clinical features.

Results

By overlapping the genes selected by three machine learning algorithms, four key genes were identified from 290 DEGs, and the diagnostic model based on the key genes showed good predictive performance (AUC = 0.971). The analysis of immune cell infiltration indicated that a variety of immune cells may be involved in the development of FGR, and nine candidate key immune cells of FGR were screened. Results from real-world data further validated TREM1 as an effective diagnostic biomarker (AUC = 0.894) and TREM1 expression was associated with increased uterine artery PI (UtA-PI) (p-value = 0.029).

Conclusion

Four candidate hub genes (SCD, SPINK1, TREM1, and HIST1H2BB) were identified, and the nomogram was constructed for FGR diagnosis. TREM1 was not only associated with a variety of key immune cells but also correlated with increased UtA-PI. The results of this study could provide some new clues for future research on the prediction and treatment of FGR.

Different Lengths of Gestational Exposure to Secondhand Smoke or e-Cigarette Vapor Induce the Development of Placental Disease Symptoms

Exposure to cigarette smoke is known to induce disease during pregnancy. Recent evidence showed that exposure to secondhand smoke (SHS) negatively impacts fetal and placental weights, leading to the development of intrauterine growth restriction (IUGR). Electronic cigarettes (eCigs) represent a phenomenon that has recently emerged, and their use is also steadily rising. Even so, the effects of SHS or eCigs during gestation remain limited. In the present study, we wanted to characterize the effects of SHS or eCig exposure at two different important gestational points during mouse pregnancy. C57/Bl6 mice were exposed to SHS or eCigs via a nose-only delivery system for 4 days (from 14.5 to 17.5 gestational days (dGA) or for 6 days (from 12.5 dGA to 17.5 dGA)). At the time of necropsy (18.5 dGA), placental and fetal weights were recorded, maternal blood pressure was determined, and a dipstick test to measure proteinuria was performed. Placental tissues were collected, and inflammatory molecules in the placenta were identified. Treatment with SHS showed the following: (1) a significant decrease in placental and fetal weights following four days of exposure, (2) higher systolic and diastolic blood pressure following six days of exposure, and (3) increased proteinuria after six days of exposure. Treatment with eCigs showed the following: (1) a significant decrease in placental weight and fetal weight following four or six days of exposure, (2) higher systolic and diastolic blood pressure following six days of exposure, and (3) increased proteinuria after six days of exposure. We also observed different inflammatory markers associated with the development of IUGR or PE. We conclude that the detrimental effects of SHS or eCig treatment coincide with the length of maternal exposure. These results could be beneficial in understanding the long-term effects of SHS or eCig exposure in the development of placental diseases.

The NFκB Signaling Pathway Is Involved in the Pathophysiological Process of Preeclampsia

The high prevalence of preeclampsia (PE) is a major cause of maternal and fetal mortality and affects the long-term prognosis of both mother and baby. Termination of pregnancy is currently the only effective treatment for PE, so there is an urgent need for research into its pathogenesis and the development of new therapeutic approaches. The NFκB family of transcription factors has an essential role in inflammation and innate immunity. In this review, we summarize the role of NFκB in normal and preeclampsia pregnancies, the role of NFκB in existing treatment strategies, and potential NFκB treatment strategies.

Placenta autophagy is closely associated with preeclampsia

The pathogenesis of preeclampsia (PE) is complex and placental internal homeostasis is regulated by cellular autophagy. However, there are fewer studies related to the role of placental autophagy in the pathogenesis of PE. The GSE75010 and GSE10588 datasets were downloaded from the gene expression omnibus (GEO) database. In the GSE75010 (test cohort), 103 differentially expressed genes (DEGs) were screened using "Limma" package, and 281 PE characteristic genes were screened by weighted gene coexpression network analysis (WGCNA). Combined with the autophagy gene set, a total of 5 autophagy-related hub genes were obtained. Three biomarkers (HK2, PLOD2, and TREM1) were then further screened by random forest(RF) model and least absolute shrinkage and selection operator(LASSO) algorithm as diagnostic of PE. In the unsupervised consensus clustering analysis, HK2, PLOD2, and TREM1 may be synergistically involved in hypoxia-induced autophagy and hypoxia-inducible factor 1(HIF-1) signaling pathway to induce PE. In addition, we constructed and evaluated a nomogram model for PE diagnosis using these three key diagnostic biomarkers, and the results showed that the model had significantly excellent predictive power (AUC values of GSE75010 and GSE10588 datasets were 0.869 and 0.876, respectively). In terms of immune infiltration, a higher proportion of T cells CD8, and a lower proportion of Macrophages M2 were found in PE placentas compared to normal tissue, and high expression of HK2, PLOD2, and TREM1 were accompanied by low levels of Macrophages M2 infiltration. HK2, PLOD2, and TREM1 may be associated with the development of pre-eclampsia, and their mechanisms of action in preeclampsia need to be further investigated.

Prediction of Differentially Expressed Genes and a Diagnostic Signature of Preeclampsia via Integrated Bioinformatics Analysis

Background

Preeclampsia (PE), which has a high incidence rate worldwide, is a potentially dangerous syndrome to pregnant women and newborns. However, the exact mechanism of its pathogenesis is still unclear. In this study, we used bioinformatics analysis to identify hub genes, establish a logistic model, and study immune cell infiltration to clarify the physiopathogenesis of PE.

Methods

We downloaded the GSE75010 and GSE10588 datasets from the GEO database and performed weighted gene coexpression network analysis (WGCNA) as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The online search tool for the retrieval of interacting genes and Cytoscape software were used to identify hub genes, which were then used to establish a logistic model. We also analyzed immune cell infiltration. Finally, we verified the expression of the genes included in the predictive model via RT-PCR.

Results

A total of 100 and 212 differently expressed genes were identified in the GSE75010 and GSE10588 datasets, respectively, and after overlapping with WGCNA results, 17 genes were identified. KEGG and GO analyses further indicated the involvement of these genes in bioprocesses, such as gonadotropin secretion, immune cell infiltration, and the SMAD and MAPK pathways. Additionally, protein-protein interaction network analysis identified 10 hub genes, six (FLT1, FLNB, FSTL3, INHA, TREM1, and SLCO4A1) of which were used to establish a logistic model for PE. RT-PCR analysis also confirmed that, except FSTL3, these genes were upregulated in PE. Our results also indicated that macrophages played the most important role in immune cell infiltration in PE.

Conclusion

This study identified 10 hub genes in PE and used 6 of them to establish a logistic model and also analyzed immune cell infiltration. These findings may enhance the understanding of PE and enable the identification of potential therapeutic targets for PE.