ArticleDisease markers2022
Exploring Key Genes and Pathways of Cardiac Hypertrophy Based on Bioinformatics.
Article in Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.Journal of translational medicine · 2026Article
- Multi-omics approach reveals CCND1, GABPA, HIF1A, and SOX6 as key regulators and prognostic markers in heart failure.Hereditas · 2025Article
- Knockdown of TGFB2 Attenuates Ischemic Heart Failure by Inhibiting Apoptosis.Cardiovascular toxicology · 2025Article
- Identification of prostate cancer bone metastasis related genes and potential therapy targets by bioinformatics and in vitro experiments.Journal of cellular and molecular medicine · 2024Article
- Comprehensive bioinformatics analysis reveals biomarkers of DNA methylation-related genes in varicose veins.Frontiers in genetics · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This research is aimed at identifying the key genes and pathways of cardiac hypertrophy using bioinformatics and at providing a new target for the identification of cardiac hypertrophy. Methods: Microarray data GSE1621 and GSE18801 were acquired from the GEO database. The DEGs of GSE1621 and GSE18801 were analyzed using the online tool GEO2R. "ggplot2" package of R software was utilized to generate the volcano plots. The top and bottom 10 genes were mapped as a heat map. GO functional annotation analysis and KEGG pathway enrichment analysis were performed separately for DEGs using the online software DAVID. Histograms were plotted using the R "ggplot2" package. The DEGs were imported into the STRING online database for constructing PPI networks and analyzing the DEG interaction relationships. Results: In the present study, 469 DEGs were screened in GSE1621 and a total of 793 DEGs were screened in GSE18801. GO analyses indicate that DEGs were mainly involved in cardiac muscle contraction, regulation of blood circulation, regulation of muscle contraction, muscle contraction, striated muscle contraction, regulation of heart contraction, regulation of striated muscle contraction, and tissue remodeling. KEGG analyses indicate that DEGs were mainly involved in Th17 cell differentiation, Th1 and Th2 cell differentiation, HIF-1 signaling pathway, pathways in cancer, hematopoietic cell lineage, Chagas disease and cell adhesion molecules, viral myocarditis, central carbon metabolism in cancer, acute myeloid leukemia, and JAK-STAT signaling pathway. Eight hub genes were screened, including Akt1, Lox, Timp1, Col1al, Spp1, Ccnd1, Mmp3, and Egfr. Conclusions: The DEGs associated with cardiac hypertrophy were screened via bioinformatics analysis, and eight hub genes were identified, including Akt1, Lox, Timp1, Col1al, Spp1, Ccnd1, Mmp3, and Egfr, which might be a new target for the identification of cardiac hypertrophy.
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