Identifying placental metabolic biomarkers of preterm birth using nuclear magnetic resonance of intact tissue samples

Maternal plasma extracellular vesicles tsRNA as potential biomarkers for assessing preterm labor risk

BACKGROUND

Spontaneous preterm labor (PTL) accounts for approximately 70% of preterm births, posing significant risks to both maternal and neonatal health. Current predictive biomarkers lack sufficient reliability, underscoring the need for non-invasive and dependable indicators. Emerging research indicates that tRNA-derived small RNAs (tsRNAs) are involved in various diseases; however, their potential association with PTL remains underexplored.

METHODS

Bioinformatics analyses of public GEO datasets (PRJNA415953 and PRJNA428989) were conducted to identify tsRNAs associated with PTL. Validation was performed using plasma extracellular vesicles samples collected at 12 weeks of gestation from PTL patients (n = 45) and healthy controls (n = 38). Functional assays were used to assess the impact of tsRNA1 (tRNA-Gly-GCC-5p-tRF-921) on extravillous trophoblast (EVT) function, including apoptosis, migration, invasion, and endothelial-like tube formation in HTR8/SVneo cells. Transcriptomic sequencing was conducted to identify tsRNA1-mediated pathways, and DNA methylation patterns were predicted based on the transcriptomic data. Statistical significance was determined using Student's t-test.

RESULTS

Two tsRNAs, tsRNA1 and tsRNA3 (tRNA-Gly-GCC-5p-tR-half-368), were significantly upregulated in PTL patient samples compared to controls. Overexpression of tsRNA1 impaired EVT function, increased apoptosis, and altered DNA methylation profiles, implicating its critical role in PTL mechanisms.

CONCLUSIONS

This study identifies tsRNA1 as a key regulator of EVT dysfunction and placental pathology in PTL. The findings provide novel insights into the mechanistic role of tsRNAs in PTL and highlight tsRNA1 as a promising biomarker for early risk stratification and prediction of the condition.

CLINICAL TRIAL NUMBER

Not applicable.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of the placenta in neurodevelopment and in the onset of neuropsychiatric disorders. Recently, mQTL and iQTL maps have proven useful in understanding relationships between SNPs and GWAS that are not captured by eQTL. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation. We construct a public placental cis-mQTL database including 214,830 CpG sites calculated in 368 fetal placenta DNA samples from the INMA project, and run cell type-, gestational age- and sex-imQTL models. We combine these data with summary statistics of GWAS on ten neuropsychiatric disorders using summary-based Mendelian randomization and colocalization. We also evaluate the influence of identified DNA methylation sites on placental gene expression in the RICHS cohort. We find that placental cis-mQTLs are enriched in placenta-specific active chromatin regions, and establish that part of the genetic burden for schizophrenia, bipolar disorder, and major depressive disorder confers risk through placental DNA methylation. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, the involvement of cell type-imQTLs, and the correlation of identified DNA methylation sites with the expression levels of relevant genes in the placenta.

Angelica sinensis polysaccharide as potential protectants against recurrent spontaneous abortion: focus on autophagy regulation

Introduction

Recurrent spontaneous abortion (RSA) represents a significant clinical challenge, with its underlying mechanisms yet to be fully elucidated. Despite advances in understanding, the precise pathophysiology driving RSA remains unclear. Angelica sinensis, a traditional herbal remedy, is frequently used as an adjunctive treatment for miscarriage. However, it remains uncertain whether its primary active component, Angelica sinensis polysaccharide (ASP), plays a definitive role in its therapeutic effects. The specific function and mechanism of ASP in the context of RSA require further investigation.

Methods

In this study, we sought to evaluate autophagy levels at the maternal-fetal interface in RSA patients and in an RSA mouse model treated with ASP, complemented by a comprehensive metabolomic analysis. Autophagy flux in the decidua was compared between eight RSA patients and eight healthy pregnant women. Additionally, changes in autophagy flux were assessed in an RSA mouse model following ASP treatment, with embryos and placental tissues collected for subsequent metabolomic profiling.

Results

Our results revealed a significant reduction in Beclin 1 protein levels in the decidua of RSA patients compared to the normal pregnancy group. Conversely, ASP treatment in the RSA mouse model restored autophagy-related protein expression, including ATG7, ATG16L, and Beclin 1, to levels higher than those observed in the untreated RSA group. Metabolomic analyses further identified significant changes in phosphatidylethanolamine levels between ASP-treated and control groups, with differential metabolites enriched in pathways related to glycolysis/gluconeogenesis, glycerolipid metabolism, and glycine, serine, and threonine metabolism. Functional assays revealed that ASP enhances trophoblast cell proliferation, migration, and invasion.

Conclusion

In summary, our findings demonstrate diminished autophagy activity in RSA patients, while ASP appears to restore autophagy and regulate key metabolic pathways, including glycolysis/gluconeogenesis. These results provide new insights into the protective mechanisms of ASP in RSA, suggesting its potential as a therapeutic intervention for this condition.

Maternal Plasma miRNAs as Early Biomarkers of Moderate-to-Late-Preterm Birth

Globally, preterm birth (PTB) is a primary cause of mortality and morbidity in infants, with PTB rates increasing worldwide over the last two decades. Biomarkers for accurate early prediction of PTB before the clinical event do not currently exist. Given their roles in the development and progression of many disease states, there has been increasing interest in the utility of microRNAs (miRNAs) as early biomarkers for pregnancy-related disorders, including PTB. The present study was designed to examine potential differences in miRNA abundances in maternal plasma from mothers with infants born following a moderate to late (28-36 weeks' gestation, n = 54) spontaneous PTB (SPTB) compared to mothers with matched term infants (n = 54). Maternal plasma collected at 15 weeks' gestation were utilised from the Auckland and Adelaide cohorts from the Screening for Pregnancy Endpoints (SCOPE) study. miRNAs in plasma were quantified using the NanoString nCounter expression panel (800 miRNAs). The top four most abundant miRNAs were significantly decreased in the plasma of mothers in the SPTB group with results consistent across both cohorts and pathway analysis was undertaken to examine the biological processes linked to the dysregulated miRNAs. The top candidate miRNAs (miRs-451a, -223-3p, let-7a-5p, and -126-3p) were linked to gene pathways associated with inflammation, apoptosis, and mitochondrial biogenesis. Moreover, miRNAs were consistently less abundant in the plasma of mothers of preterm infants across both sites, suggesting potential global dysregulation in miRNA biogenesis. This was supported by a significant downregulation in expression of key genes that are involved in miRNA biogenesis (DROSHA, DICER, and AGO2) across both sites in the SPTB group. In summary, the present study has identified miRNAs in maternal plasma that may provide predictive utility as early biomarkers for the risk of later SPTB. Importantly, these observations were conserved across two independent cohorts. Further, our data provide evidence for a persistent decrease in miRNA abundance in mothers who later experienced an SPTB, which is likely to have widespread consequences for gene regulation and epigenetic processes.

Identification of key metabolism-related genes and pathways in spontaneous preterm birth: combining bioinformatic analysis and machine learning

Background

Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets.

Methods

In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the "Deseq2" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted single-sample gene set enrichment analysis to assess immune infiltration in the placenta.

Results

We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolism-related hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients.

Conclusion

Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB.

Differential impact of perfluorooctanoic acid and fluorotelomer ethoxylates on placental metabolism in mice

Poly- and perfluoroalkyl substances (PFAS) are a group of compounds with uses in industry and many consumer products. Concerns about the potential health effects of these compounds resulted in regulation by the Stockholm Convention on the use of three of the most common PFAS, including perfluorooctanoic acid (PFOA). Thousands of PFAS remain in production that are unregulated and for which their toxicity is unknown. Our group recently identified a new class of PFAS, fluorotelomer ethoxylates (FTEOs), in indoor dust and industrial wastewater. In this study, we investigated the effect of PFAS on placental metabolism by exposing healthy, pregnant CD-1 mice to PFOA or FTEOs at one of three concentrations (0 ng/L (controls), 5 ng/L, 100 ng/L) (n = 7-8/group). While PFOA is banned and PFOA concentrations in human blood are decreasing, we hypothesize that FTEOs will cause adverse pregnancy outcomes similar to PFOA, the compounds they were meant to replace. Placental tissue samples were collected at embryonic day 17.5 and 1H solid-state magic angle spinning nuclear magnetic resonance spectroscopy was used to determine the relative concentration of placental metabolites (n = 18-20/group). At the highest concentration, the relative concentrations of glucose and threonine were increased and the relative concentration of creatine was decreased in the PFOA-exposed placentas compared to controls (p < 0.05). In contrast, the relative concentrations of asparagine and lysine were decreased and the relative concentration of creatine was increased in the FTEOs-exposed placentas compared to controls (p < 0.05). Partial least squares - discriminant analysis showed the FTEOs-exposed and control groups were significantly separated (p < 0.005) and pathway analysis found four biochemical pathways were perturbed following PFOA exposure, while one pathway was altered following FTEOs exposure. Maternal exposure to PFOA and FTEOs had a significant impact on the placental metabolome, with the effect depending on the pollutant. This work motivates further studies to determine exposure levels and evaluate associations with adverse outcomes in human pregnancies.