ArticleBMC pregnancy and childbirth2022
Identification of key genes in pathogenesis of placental insufficiency intrauterine growth restriction.
Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Genetics and Stillbirth.Clinics in perinatology · 2026Review
- Promoter landscape of maternal plasma DNA reveals predictive signatures of fetal growth restriction.Human genomics · 2026Article
- Use of a Maternal Genetic Risk Score to Derive and Test a Genetically Customized Fetal Growth Curve.O&G open · 2025Article
- Using transcriptomic signatures to elucidate individual and mixture effects of inorganic arsenic and manganese in human placental trophoblast HTR-8/SVneo cells.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Human cord plasma proteomic analysis reveals sexually dimorphic proteins associated with intrauterine growth restriction.Proteomics · 2024Article
- Association between TGFβ1 Levels in Cord Blood and Weight Progress in the First Year of Life.Biomedicines · 2023Article
- The Update of Fetal Growth Restriction Associated with Biomarkers.Maternal-fetal medicine (Wolters Kluwer Health, Inc.) · 2022Review
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntrauterine growth restriction (IUGR) is defined as a fetus that fails to achieve its genetically determined growth potential. The exact molecular mechanisms of placental insufficiency IUGR pathogenesis are a little known. Our goal was to identify key genes and gene co-expression modules related to placental insufficiency IUGR.
methodsWe used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis to examine the IUGR dataset GSE114691 from NCBI Gene Expression Omnibus. Core modules and hub nodes of the protein-protein interaction network were identified. A gene network was constructed and genes were classified by WGCNA into different modules. The validation of potential key genes was carried out using additional datasets (GSE12216 and GSE24129).
resultsWe identified in GSE114691 539 down regulated genes and 751 up regulated genes in placental tissues characteristic of placental insufficiency IUGR compared with non-IUGR, and defined 76 genes as hub nodes in the protein-protein interaction network. Genes in the key modules of the WGCNA network were most closely associated with placental insufficiency IUGR and significantly enriched in biological process such as cellular metabolic process and macromolecule metabolic process. We identified as key genes TGFB1, LEP, ENG, ITGA5, STAT5A, LYN, GATA3, FPR1, TGFB2, CEBPB, KLF4, FLT1, and PNPLA2. The RNA expression levels of ENG and LEP, as biomarkers, were validated.
conclusionA holistic gene expression profile of placental insufficiency IUGR has been generated and the key genes ENG and LEP has potential to serve as circulating diagnosis biomarkers and therapeutic targets for placental insufficiency IUGR.
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