ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025
Transcript Changes of Placental Tissue in Gestational Diabetes Mellitus Based on Transcriptome Sequencing.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
- Observational
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6 authors.
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Abstract
Purpose: This study aims to identify key genes that may be involved in the pathogenesis of gestational diabetes mellitus and to preliminarily elucidate the underlying mechanisms. Methods: High-throughput transcriptome sequencing was employed to identify Differentially expressed genes (DEGs) in placental tissue samples of GDM and normal pregnant women. Functional and pathway analyses of these DEGs were conducted using bioinformatics databases. Significant DEGs were validated through real-time quantitative PCR in conjunction with relevant literature. Results: In comparison to the normal pregnancy group, 435 DEGs were identified in the GDM group, comprising 128 upregulated and 307 downregulated genes. GO enrichment analysis revealed that DEGs were primarily associated with biological processes, such as cellular processes, biological regulation, regulation of biological processes, and response to stimuli. Cell component enrichment analysis indicated their association with cellular anatomical entities and protein-containing complexes. Molecular function enrichment analysis highlighted their roles in binding and catalytic activities. KEGG pathway enrichment analysis indicated the involvement of DEGs in signalling pathways related to PI3K-Akt signaling pathway and ECM-receptor interaction. qRT-PCR validation of five randomly selected DEGs confirmed consistent expression trends with RNA-Seq quantification. Conclusion: YWHAB, LEP, CCL21, PAPPA2, and SFN may be potential biological markers for the diagnosis of GDM, involved in the occurrence and development of GDM, and have certain value for disease prediction and diagnosis.
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