Embryonic Hypotaurine Levels Contribute to Strain-Dependent Susceptibility in Mouse Models of Valproate-Induced Neural Tube Defects

Epigenetic regulation by TET1 in gene-environmental interactions influencing susceptibility to congenital malformations

The etiology of neural tube defects (NTDs) involves complex gene-environmental interactions. Folic acid (FA) prevents NTDs, but the mechanisms remain poorly understood and at least 30% of human NTDs resist the beneficial effects of FA supplementation. Here, we identify the DNA demethylase TET1 as a nexus of folate-dependent one-carbon metabolism and genetic risk factors post-neural tube closure. We determine that cranial NTDs in Tet1 -/- embryos occur at two to three times higher penetrance in genetically heterogeneous than in homogeneous genetic backgrounds, suggesting a strong impact of genetic modifiers on phenotypic expression. Quantitative trait locus mapping identified a strong NTD risk locus in the 129S6 strain, which harbors missense and modifier variants at genes implicated in intracellular endocytic trafficking and developmental signaling. NTDs across Tet1 -/- strains are resistant to FA supplementation. However, both excess and depleted maternal FA diets modify the impact of Tet1 loss on offspring DNA methylation primarily at neurodevelopmental loci. FA deficiency reveals susceptibility to NTD and other structural brain defects due to haploinsufficiency of Tet1. In contrast, excess FA in Tet1 -/- embryos drives promoter DNA hypermethylation and reduced expression of multiple membrane solute transporters, including a FA transporter, accompanied by loss of phospholipid metabolites. Overall, our study unravels interactions between modified maternal FA status, Tet1 gene dosage and genetic backgrounds that impact neurotransmitter functions, cellular methylation and individual susceptibilities to congenital malformations, further implicating that epigenetic dysregulation may underlie NTDs resistant to FA supplementation.

Melatonin alleviates valproic acid-induced neural tube defects by modulating Src/PI3K/ERK signaling and oxidative stress

Neural tube defects (NTDs) represent a developmental disorder of the nervous system that can lead to significant disability in children and impose substantial social burdens. Valproic acid (VPA), a widely prescribed first-line antiepileptic drug for epilepsy and various neurological conditions, has been associated with a 4-fold increase in the risk of NTDs when used during pregnancy. Consequently, urgent efforts are required to identify innovative prevention and treatment approaches for VPA-induced NTDs. Studies have demonstrated that the disruption in the delicate balance between cell proliferation and apoptosis is a crucial factor contributing to NTDs induced by VPA. Encouragingly, our current data reveal that melatonin (MT) significantly inhibits apoptosis while promoting the restoration of neuroepithelial cell proliferation impaired by VPA. Moreover, further investigations demonstrate that MT substantially reduces the incidence of neural tube malformations resulted from VPA exposure, primarily by suppressing apoptosis through the modulation of intracellular reactive oxygen species levels. In addition, the Src/PI3K/ERK signaling pathway appears to play a pivotal role in VPA-induced NTDs, with significant inhibition observed in the affected samples. Notably, MT treatment successfully reinstates Src/PI3K/ERK signaling, thereby offering a potential underlying mechanism for the protective effects of MT against VPA-induced NTDs. In summary, our current study substantiates the considerable protective potential of MT in mitigating VPA-triggered NTDs, thereby offering valuable strategies for the clinical management of VPA-related birth defects.

Gene-environment interactions underlying the etiology of neural tube defects

Neural tube defects (NTDs) consist of severe structural malformations of the brain and spinal cord and are the second most common structural birth defect in humans, accounting for approximately 2700 affected pregnancies every year in the United States. These numbers are highly significant, considering that birth defects remain a leading cause of infant mortality in the United States, affecting approximately 120,000 babies born annually. Survivors of these congenital malformations face long-term disability and lifelong challenges imposed by severe physical burdens compromising the afflicted individual's overall quality of life. Clearly, birth defects, and especially NTDs remain a global public health challenge, and the source of significant financial repercussions for healthcare systems worldwide. In order to better understand the role gene-environment interactions play in the etiology of NTDs, this chapter provides an overview of NTD phenotypes and their embryonic origins, discusses the genetic landscape of NTDs as it is currently understood, with a focus on experimental models that best illustrate how environmental factors modulate individual susceptibility to these birth defects. As folic acid interventions have proven to be effective in reducing the prevalence of NTDs, the chapter ends with a discussion on the impact that maternal dietary status has on NTD prevalence from a population perspective.

Unraveling the Mechanisms of Clinical Drugs-Induced Neural Tube Defects Based on Network Pharmacology and Molecular Docking Analysis

Chemotherapeutic agents such as methotrexate (MTX), raltitrexed (RTX), 5-fluorouracil (5-FU), hydroxyurea (HU), and retinoic acid (RA), and valproic acid (VPA), an antiepileptic drug, all can cause malformations in the developing central nervous system (CNS), such as neural tube defects (NTDs). However, the common pathogenic mechanisms remain unclear. This study aimed to explore the mechanisms of NTDs caused by MTX, RTX, 5-FU, HU, RA, and VPA (MRFHRV), based on network pharmacology and molecular biology experiments. The MRFHRV targets were integrated with disease targets, to find the potential molecules related to MRFHRV-induced NTDs. Protein-protein interaction analysis and molecular docking were performed to analyze these common targets. Utilizing the kyoto encyclopedia of genes and genomes (KEGG) signaling pathways, we analyzed and searched the possible causative pathogenic mechanisms by crucial targets and the signaling pathway. Results showed that MRFHRV induced NTDs through several key targets (including TP53, MAPK1, HSP90AA1, ESR1, GRB2, HDAC1, EGFR, PIK3CA, RXRA, and FYN) and multiple signaling pathways such as PI3K/Akt pathway, suggesting that abnormal proliferation and differentiation could be critical pathogenic contributors in NTDs induced by MRFHRV. These results were further validated by CCK8 assay in mouse embryonic stem cells and GFAP staining in embryonic brain tissue. This study indicated that chemotherapeutic and antiepileptic agents induced NTDs might through predicted targets TP53, MAPK1, GRB2, HDAC1, EGFR, PIK3CA, RXRA, and FYN and multiple signaling pathways. More caution was required for the clinical administration for women with childbearing potential and pregnant.

Recursive Feature Elimination-based Biomarker Identification for Open Neural Tube Defects

Background: Open spina bifida (myelomeningocele) is the result of the failure of spinal cord closing completely and is the second most common and severe birth defect. Open neural tube defects are multifactorial, and the exact molecular mechanism of the pathogenesis is not clear due to disease complexity for which prenatal treatment options remain limited worldwide. Artificial intelligence techniques like machine learning tools have been increasingly used in precision diagnosis. Objective: The primary objective of this study is to identify key genes for open neural tube defects using a machine learning approach that provides additional information about myelomeningocele in order to obtain a more accurate diagnosis. Materials and Methods: Our study reports differential gene expression analysis from multiple datasets (GSE4182 and GSE101141) of amniotic fluid samples with open neural tube defects. The sample outliers in the datasets were detected using principal component analysis (PCA). We report a combination of the differential gene expression analysis with recursive feature elimination (RFE), a machine learning approach to get 4 key genes for open neural tube defects. The features selected were validated using five binary classifiers for diseased and healthy samples: Logistic Regression (LR), Decision tree classifier (DT), Support Vector Machine (SVM), Random Forest classifier (RF), and K-nearest neighbour (KNN) with 5-fold cross-validation. Results: Growth Associated Protein 43 (GAP43), Glial fibrillary acidic protein (GFAP), Repetin (RPTN), and CD44 are the important genes identified in the study. These genes are known to be involved in axon growth, astrocyte differentiation in the central nervous system, post-traumatic brain repair, neuroinflammation, and inflammation-linked neuronal injuries. These key genes represent a promising tool for further studies in the diagnosis and early detection of open neural tube defects. Conclusion: These key biomarkers help in the diagnosis and early detection of open neural tube defects, thus evaluating the progress and seriousness in diseases condition. This study strengthens previous literature sources of confirming these biomarkers linked with open NTD's. Thus, among other prenatal treatment options present until now, these biomarkers help in the early detection of open neural tube defects, which provides success in both treatment and prevention of these defects in the advanced stage.