Excess fibronectin 1 participates in pathogenesis of pre-eclampsia by promoting apoptosis and autophagy in vascular endothelial cells

Unique motif Sequences for early diagnosis of preeclampsia

Preeclampsia (PE) is a disease that significantly impacts both maternal and infant health with its prevalence varying across different ethnicities. Current diagnostic methods for PE typically identify the condition after 20 weeks of gestation, often when the disease has already manifested and reached an advanced stage. The situation underscores the urgent need for early biomarkers capable of effective screening and diagnosis. Our review addresses this challenge by utilizing bioinformatics approaches as an alternative method prior to preclinical and clinical studies. Specifically, we focus on FRAGmentomics-based Methylation Analysis (FRAGMA), targeting the CGCGCGG sequence motif for methylation studies in cell-free DNA (cfDNA). Since cfDNA is largely derived from the placenta, the FRAGMA approach is particularly promising, given that the primary pathophysiology of PE originates in the placenta, and methylation patterns are unique to specific tissues. In the previous research, we identified 66 genes containing this sequence motif that are implicated in the pathophysiology of PE, and only six genes - FN1, ITGA2, ITGA5, ITGB1, ITGB3, and VWF - show potential as early detection biomarkers for PE. These genes still require further investigation to confirm their utility as biomarkers for PE in the future studies.

Multi-omics analysis of placental metabolomics and transcriptomics datasets reveals comprehensive insights into the pathophysiology of preeclampsia

Preeclampsia, a life-threatening pregnancy complication, remains a major global health concern. Understanding the complex molecular mechanisms underlying this disorder is crucial for improving both diagnostics and therapeutic strategies. In this study, a multi-omics approach based on NMR metabolomics and RNA-seq transcriptomics analyses was conducted to analyze placental tissue samples obtained from patients with preeclampsia and healthy controls. Metabolomics data analysis results indicated alterations in several metabolite levels including lactate, myo-inositol, glutamate, glutamine, valine, leucine, isoleucine, creatinine, alanine, taurine, choline, phosphocholine, glycerophosphocholine, ethanolamine, and dihydroxyacetone. These alterations cause significant disruptions in the Krebs cycle, energy, lipid, and amino acid metabolisms. Concurrently, transcriptomics data analysis identified 10 upregulated and 37 downregulated genes (|log2FC= > 1 and padj < 0.05) in preeclampsia patients. Identified genes were linked to critical roles such as vasoconstriction, angiogenesis, inflammation, hormonal balance, oxidative stress, and collagen integrity. Multi-omics data analysis revealed the association of certain metabolites with several other genes. A gene interaction network formed by these genes resulted in a lower protein-protein interaction enrichment value (p-value < 1e-16) compared to the network formed with the differentially expressed genes (p-value = 0.0183) which suggests the importance of considering multiple omics levels for a comprehensive understanding of the disease.

Characterizing the Ovarian Cytogenetic Dynamics of Sichuan Bream (Sinibrama taeniatus) During Vitellogenesis at a Single-Cell Resolution

Vitellogenesis in fish represents a critical phase of oogenesis, significantly influencing the nutritional provisioning for oocyte maturation and subsequent offspring development. However, research on the physiological mechanisms governing vitellogenesis at the single-cell level remains limited. In this study, we performed single-nucleus RNA sequencing (snRNA-seq) on the ovaries of Sichuan bream (Sinibrama taeniatus). We first identified six distinct cell types (germ cells, follicular cells, immune cells, stromal cells, endothelial cells, and epithelial cells) in the ovaries based on typical functional marker genes. Subsequently, we reconstructed the developmental trajectory of germ cells using pseudotime analysis, which describes the transcriptional dynamics of germ cells at various developmental stages. Additionally, we identified transcription factors (TFs) specific to germ cells that exhibit high activity at each developmental stage. Furthermore, we analyzed the genetic functional heterogeneity of germ cells and follicular cells at different developmental stages to elucidate their contributions to vitellogenesis. Finally, cell interaction analysis revealed that germ cells communicate with somatic cells or with each other via multiple receptors and ligands to regulate growth, development, and yolk acquisition. These findings enhance our understanding of the physiological mechanisms underlying vitellogenesis in fish, providing a theoretical foundation for regulating ovarian development in farmed fish.

Relationship between fat embolism and endothelial glycocalyx

Fat embolism (FE) is acknowledged as one of the significant causes of sudden death following traumatic injury. To clarify the relevance of vascular endothelial glycocalyx (EGC) damage and FE, temporal changes in the mRNA levels of inflammatory cytokines associated with EGC components were investigated in an experimental fat embolization rat model. Nine-week-old rats were used as FE models through triolein injection (TO) and femoral fracture (FX), and physiological saline was administered to the control group. RT-qPCR and fat staining were performed. The target genes were Il6, Il10, Tnf, Elane, Sdc1, Sdcbp, Vcan, Hyal1, Fn1, and CD14. Notably, FE was detected in 100% and 5.6% of the TO and FX groups, respectively, using fat staining. Bimodal peaks in the mRNA expression levels of Sdc1, Tnf, Elane, IL6, and IL10 were observed 4 and 20 h after treatment in both groups. In the TO group, mRNA expression peaked at 4 h and then declined to the lowest level at 16 h. The incidence of fat emboli due to trauma was consistent with that reported in previous studies. Bimodal mRNA peaks may correspond to FE progression, in which physical obstructions are followed by biochemical reactions. The fluctuation in Sdc1 expression suggests that the initial peak resulted from physical EGC damage. The subsequent peak could be because of EGC damage caused by the secretion of inflammatory cytokines induced by oleic acid from lipid droplet decomposition. These results suggest that EGC disorders caused by lipid droplets may induce lung damage during FE.

Identification of Autophagy-Related Genes Involved in Intervertebral Disc Degeneration by Microarray Data Analysis

BACKGROUND

Nucleus pulposus cells survive in a hypoxic, acidic, nutrient-poor, and hypotonic microenvironment. Consequently, they maintain low proliferation and undergo autophagy to protect themselves from cellular stress. Therefore, we aimed to identify autophagy-related biomarkers involved in intervertebral disc degeneration pathogenesis.

METHODS

Autophagy-related differentially expressed genes were derived from the intersection between the public GSE147383 microarray data set to identify differentially expressed genes and online databases to identify autophagy-related genes. Furthermore, we assessed their biological functions with gene annotation and enrichment analysis in the Metscape portal. Then, the STRING database and Cytoscape software allowed inferring a protein-protein interaction (PPI) network and identifying hub genes. In addition, to predict transcription factors that may regulate the hub genes, we used the GeneMANIA website. Finally, the competing endogenous RNA prediction tools and Cytoscape were also used to construct an mRNA-miRNA-lncRNA network.

RESULTS

A total of 123 autophagy-related differentially expressed genes were identified, they were mainly involved in phosphoinositide 3-kinase-Akt signaling, autophagy animal, and apoptosis pathways. Nine were identified as hub genes (PTEN, MYC, CTNNB1, JUN, BECN1, ERBB2, FOXO3, ATM, and FN1) and 36 transcription factors were associated with them. Finally, an autophagy-associated competing endogenous RNA network was constructed based on the 9 hub genes.

CONCLUSIONS

Nine hub genes were identified and a network of competing endogenous RNA associated with autophagy was established. They can be used as autophagy-related biomarkers of intervertebral disc degeneration and for further exploration.

Generation and characterisation of scalable and stable human pluripotent stem cell-derived microvascular-like endothelial cells for cardiac applications

Coronary microvascular disease (CMD) and its progression towards major adverse coronary events pose a significant health challenge. Accurate in vitro investigation of CMD requires a robust cell model that faithfully represents the cells within the cardiac microvasculature. Human pluripotent stem cell-derived endothelial cells (hPSC-ECs) offer great potential; however, they are traditionally derived via differentiation protocols that are not readily scalable and are not specified towards the microvasculature. Here, we report the development and comprehensive characterisation of a scalable 3D protocol enabling the generation of phenotypically stable cardiac hPSC-microvascular-like ECs (hPSC-CMVECs) and cardiac pericyte-like cells. These were derived by growing vascular organoids within 3D stirred tank bioreactors and subjecting the emerging 3D hPSC-ECs to high-concentration VEGF-A treatment (3DV). Not only did this promote phenotypic stability of the 3DV hPSC-ECs; single cell-RNA sequencing (scRNA-seq) revealed the pronounced expression of cardiac endothelial- and microvascular-associated genes. Further, the generated mural cells attained from the vascular organoid exhibited markers characteristic of cardiac pericytes. Thus, we present a suitable cell model for investigating the cardiac microvasculature as well as the endothelial-dependent and -independent mechanisms of CMD. Moreover, owing to their phenotypic stability, cardiac specificity, and high angiogenic potential, the cells described within would also be well suited for cardiac tissue engineering applications.

Bioinformatics identification and validation of maternal blood biomarkers and immune cell infiltration in preeclampsia: An observational study

Preeclampsia (PE) is a pregnancy complication characterized by placental dysfunction. However, the relationship between maternal blood markers and PE is unclear. It is helpful to improve the diagnosis and treatment of PE using new biomarkers related to PE in the blood. Three PE-related microarray datasets were obtained from the Gene Expression Synthesis database. The limma software package was used to identify differentially expressed genes (DEGs) between PE and control groups. Least absolute shrinkage and selection operator regression, support vector machine, random forest, and multivariate logistic regression analyses were used to determine key diagnostic biomarkers, which were verified using clinical samples. Subsequently, functional enrichment analysis was performed. In addition, the datasets were combined for immune cell infiltration analysis and to determine their relationships with core diagnostic biomarkers. The diagnostic performance of key genes was evaluated using the receiver operating characteristic (ROC) curve, C-index, and GiViTi calibration band. Genes with potential clinical applications were evaluated using decision curve analysis (DCA). Seventeen DEGs were identified, and 6 key genes (FN1, MYADM, CA6, PADI4, SLC4A10, and PPP4R1L) were obtained using 3 types of machine learning methods and logistic regression. High diagnostic performance was found for PE through evaluation of the ROC, C-index, GiViti calibration band, and DCA. The 2 types of immune cells (M0 macrophages and activated mast cells) were significantly different between patients with PE and controls. All of these genes except SLC4A10 showed significant differences in expression levels between the 2 groups using quantitative reverse transcription-polymerase chain reaction. This model used 6 maternal blood markers to predict the occurrence of PE. The findings may stimulate ideas for the treatment and prevention of PE.

Preeclampsia in mice carrying fetuses with APOL1 risk variants

African-American women have a maternal mortality rate approximately three times higher than European-American women. This is partially due to hypertensive disorders of pregnancy, including preeclampsia. Fetal APOL1 high-risk genotype increases preeclampsia risk, although mechanisms remain elusive. We characterized two mouse models to investigate whether fetal-origin APOL1 induces preeclampsia and which cell types contribute. We in vitro fertilized mice with sperm from two transgenic mouse lines: APOL1 transgenic mice carrying human genomic locus constructs from bacterial artificial chromosomes (BAC) containing the APOL1 gene, mimicking expression and function of human APOL1 (BAC/APOL1 mice) and albumin promoter APOL1 transgenic mice expressing APOL1 in liver and plasma (Alb/APOL1 mice). Dams carrying either BAC/APOL1-G1 or Alb/APOL1-G1 fetuses had elevated systolic blood pressure, while dams carrying BAC/APOL1-G0 or Alb/APOL1-G0 fetuses did not. BAC/APOL1-G1 and Alb/APOL1-G1 fetuses weighed less than littermates, indicating intrauterine growth restriction. Single-nucleus RNA-seq of APOL1-G1 placentas showed increased expression of osteopontin/Spp1, most prominently in vascular endothelial cells with robust APOL1 expression. Cell-cell interaction analysis indicated pro-inflammatory signaling between placental cells and maternal monocytes. These models show that fetal origin APOL1-G1 causes preeclampsia, inducing pro-inflammatory response in placenta and maternal monocytes. The APOL1-G1 variant poses a multi-generational problem, causing effects in mothers and offspring.

Research Progress on Extracellular Matrix Involved in the Development of Preeclampsia

Preeclampsia (PE) is a serious pregnancy complication, and its primary clinical manifestations are gestational hypertension and proteinuria. Trophoblasts are responsible for the basic functions of the placenta during placental development; recent studies have revealed that placental "shallow implantation" caused by the decreased invasiveness of placental trophoblasts plays a crucial role in PE pathogenesis. The interaction between the cells and the extracellular matrix (ECM) plays a crucial role in trophoblast proliferation, differentiation, and invasion. Abnormal ECM function can result in insufficient migration and invasion of placental trophoblasts, thus participating in PE. This article summarizes the recent studies on the involvement of ECM components, including small leucine-rich proteoglycans, syndecans, glypicans, laminins, fibronectin, collagen, and hyaluronic acid, in the development of PE. ECM plays various roles in PE development, most notably by controlling the activities of trophoblasts. The ECM is structurally stable and can serve as a biological diagnostic marker and therapeutic target for PE.

Integrated Proteomic and N-Glycoproteomic Profiling of Placental Tissues of Patients with Preeclampsia

Background

Preeclampsia (PE) is a multi-system disorder of pregnancy that poses a serious threat to maternal and perinatal health worldwide. This study aims to evaluate the global alterations of protein expression and N-glycosylations that are crucial for PE pathogenesis. Here, tandem mass tag labeling combined with LC-MS/MS was employed to determine the global expression of all proteins and intact glycopeptide in placentas from three healthy pregnant women, three patients with early-onset severe PE, and three patients with late-onset severe PE.

Results

A total of 2260 proteins were quantified across 9 placental tissues, of which 37 and 23 were differentially expressed in the early-onset and late-onset PE groups, compared to the controls. A total of 789 glycopeptides were accurately quantified, which were derived from 204 glycosylated sites in 159 glycoproteins and were modified by 59 N-Linked glycans. A total of 123 differently expressed glycopeptides, which were from 47 glycoproteins were identified among three groups. Through a combined analysis of proteomic and glycoproteomic data, it was found that the changes in 10 glycoproteins were caused by the difference in glycosylation level but not in the protein abundance level.

Conclusion

This is the first study to conduct an integrated proteomic and glycoproteomic characterization of placental tissues of PE patients. Our findings suggest that glycosylation modification may affect the molecular function of proteins through changes in the glycosylation structure or the occupancy of glycosylation, which will provide new insights to help elucidating the pathogenic mechanism of PE.

Single-Cell Atlas of the Chinese Tongue Sole (Cynoglossus semilaevis) Ovary Reveals Transcriptional Programs of Oogenesis in Fish

Oogenesis is a highly orchestrated process that depends on regulation by autocrine/paracrine hormones and growth factors. However, many details of the molecular mechanisms that regulate fish oogenesis remain elusive. Here, we performed a single-cell RNA sequencing (scRNA-seq) analysis of the molecular signatures of distinct ovarian cell categories in adult Chinese tongue sole (Cynoglossus semilaevis). We characterized the successive stepwise development of three germ cell subtypes. Notably, we identified the cellular composition of fish follicle walls, including four granulosa cell types and one theca cell type, and we proposed important transcription factors (TFs) showing high activity in the regulation of cell identity. Moreover, we found that the extensive niche–germline bidirectional communications regulate fish oogenesis, whereas ovulation in fish is accompanied by the coordination of simultaneous and tightly sequential processes across different granulosa cells. Additionally, a systems biology analysis of the homologous genes shared by Chinese tongue sole and macaques revealed remarkably conserved biological processes in germ cells and granulosa cells across vertebrates. Our results provide key insights into the cell-type-specific mechanisms underlying fish oogenesis at a single-cell resolution, which offers important clues for exploring fish breeding mechanisms and the evolution of vertebrate reproductive systems.

Screening of the Key Genes and Signalling Pathways for Diabetic Nephropathy Using Bioinformatics Analysis

BACKGROUND

This study aimed to identify biological markers for diabetic nephropathy (DN) and explore their underlying mechanisms.

METHODS

Four datasets, GSE30528, GSE47183, GSE104948, and GSE96804, were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the "limma" package, and the "RobustRankAggreg" package was used to screen the overlapping DEGs. The hub genes were identified using cytoHubba of Cytoscape. Logistic regression analysis was used to further analyse the hub genes, followed by receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. Correlation analysis and enrichment analysis of the hub genes were performed to identify the potential functions of the hub genes involved in DN.

RESULTS

In total, 55 DEGs, including 38 upregulated and 17 downregulated genes, were identified from the three datasets. Four hub genes (FN1, CD44, C1QB, and C1QA) were screened out by the "UpSetR" package, and FN1 was identified as a key gene for DN by logistic regression analysis. Correlation analysis and enrichment analysis showed that FN1 was positively correlated with four genes (COL6A3, COL1A2, THBS2, and CD44) and with the development of DN through the extracellular matrix (ECM)-receptor interaction pathway.

CONCLUSIONS

We identified four candidate genes: FN1, C1QA, C1QB, and CD44. On further investigating the biological functions of FN1, we showed that FN1 was positively correlated with THBS2, COL1A2, COL6A3, and CD44 and involved in the development of DN through the ECM-receptor interaction pathway. THBS2, COL1A2, COL6A3, and CD44 may be novel biomarkers and target therapeutic candidates for DN.