ArticleFrontiers in cardiovascular medicine2022
Identification of intrinsic genes across general hypertension, hypertension with left ventricular remodeling, and uncontrolled hypertension.
Article in Frontiers in cardiovascular medicine, 2022. 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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1 citing paper in PubMed, 2 citations in OpenAlex.
- Identification of miRNA biomarkers for essential hypertension in small samples based on MPGAM.Scientific reports · 2025Article
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4 authors at 2 institutions in 1 country.
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Abstract
The purpose of the present article is to identify intrinsic genes across general hypertension (HT), hypertension with left ventricular remodeling (HT-LVR), and uncontrolled hypertension (UN-HT). In total, four microarray datasets (GSE24752, GSE75360, GSE74144, and GSE71994) were downloaded from the GEO database and were used to identify differentially expressed genes (DEGs), respectively. Furthermore, gene set enrichment analysis (GSEA) was utilized to screen for significantly enriched biological pathways across the four datasets above, respectively. Furthermore, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were applied to screen out gene modules of interest and potential biological functions, respectively. Finally, a Metascape-based multiple gene list meta-analysis was used to investigate intrinsic genes at different stages of the progression of hypertension. A total of 75 DEGs (63 upregulated genes and 12 downregulated genes, GSE24752) and 23 DEGs (2 upregulated genes and 21 downregulated genes, GSE74144) were identified. However, there were few DEGs identified in GSE75360, GSE71994, and part of the GSE74144 datasets. GSEA and functional enrichment of gene module of interest have indicated that "Heme metabolism," "TNF alpha/NFkB," and "interferon alpha response signaling," and MYC target v1/v2 were enriched significantly in different stages of hypertension progression. Significantly, findings from the multiple gene list meta-analysis suggested that
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