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Ferroptosis-related genes in preeclampsia: integrative bioinformatics analysis, experimental validation and drug
Lidan He1, Feng Zhan2,3, Xuemei Li4
1Department of Obstetrics and Gynecology, The First Affiliated Hospital of Fujian Medical University, Fujian, 350004, China. hld2399@fjmu.edu.cn.
Insights
This study identified four ferroptosis-related genes (FRGs) as potential biomarkers for preeclampsia (PE). These findings offer new avenues for early PE diagnosis and targeted therapies.
Area of Science:
- Biochemistry
- Genetics
- Obstetrics
Background:
- Preeclampsia (PE) is a severe pregnancy complication lacking effective early diagnostic and therapeutic strategies.
- Ferroptosis, a form of regulated cell death dependent on iron, is implicated in the pathogenesis of PE.
- Identifying novel biomarkers and therapeutic targets for PE is crucial for improving maternal and fetal outcomes.
Purpose of the Study:
- To investigate ferroptosis-related genes (FRGs) in preeclampsia (PE) to identify diagnostic biomarkers and potential therapeutic targets.
- To explore the role of FRGs in PE pathogenesis using integrated bioinformatics and experimental validation.
- To establish a foundation for developing improved diagnostic tools and treatments for PE.
Main Methods:
- Bioinformatic analysis of gene expression data from public databases (GEO) to identify differentially expressed FRGs.
- Selection of hub genes using machine learning algorithms (RandomForest, LASSO) and evaluation of diagnostic potential via ROC analysis.
- Experimental validation of hub gene expression in placental tissues and hypoxic trophoblasts using immunohistochemistry, Western blot, and RT-qPCR.
Main Results:
- Identified 25 differentially expressed FRGs, with four hub genes (NDRG1, P4HA1, LDHA, IDO1) demonstrating high diagnostic efficiency (AUC=0.9182).
- Observed significant correlations between altered immune cell populations (plasma cells, CD8+ T cells, Tregs, monocytes, M2 macrophages) and hub gene expression in PE.
- Validated elevated expression of NDRG1, P4HA1, LDHA, and decreased IDO1 in PE tissues and under hypoxic conditions, supporting their role in PE pathogenesis.
Conclusions:
- Four FRGs (NDRG1, P4HA1, LDHA, IDO1) were identified as promising diagnostic biomarkers and therapeutic targets for preeclampsia (PE).
- The study provides novel insights into PE pathogenesis by integrating bioinformatics and experimental approaches.
- These findings hold potential for advancing early PE diagnosis and the development of targeted therapeutic interventions.
Introduction:
Preeclampsia (PE) is a severe pregnancy complication with limited early diagnostic and therapeutic options. Ferroptosis, an iron-dependent cell death pathway, has emerged as a potential mechanism in PE pathogenesis. This study investigated ferroptosis-related genes (FRGs) in PE to identify diagnostic biomarkers and therapeutic targets.
Methods:
Differentially expressed genes were identified from GEO databases and intersected with FRGs. Hub genes were selected using RandomForest and LASSO algorithms. Their diagnostic potential was evaluated through ROC analysis. Regulatory networks were constructed using transcription factors, microRNAs and potential drug targets. Hub gene expression was validated through immunohistochemistry, Western blot, and RT-qPCR in placental tissues and hypoxic trophoblasts.
Results:
We identified 25 ferroptosis-related differentially expressed genes enriched in ferroptosis and HIF-1 pathways. Four hub genes (NDRG1, P4HA1, LDHA, and IDO1) showed high diagnostic efficiency (AUC=0.9182). Immune cell analysis revealed altered levels of plasma cells, CD8+ T cells, Tregs, monocytes, and M2 macrophages in PE, correlating significantly with hub gene expression. We identified 84 mRNA-miRNA and 119 mRNA-TF interactions. Among 19 potential drugs, Tetrahydro-NAD showed promising targeting potential. Experimental validation confirmed elevated expression of NDRG1, P4HA1, and LDHA, and decreased IDO1 in PE tissues and hypoxic conditions.
Discussion:
This study identified four FRGs as potential PE biomarkers and therapeutic targets, providing new insights into PE pathogenesis through integrated bioinformatics and experimental validation. These findings may facilitate early PE diagnosis and treatment development.
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