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pmid:36046382

Exploring Key Genes and Pathways of Cardiac Hypertrophy Based on Bioinformatics.

Zhenzhen Zhang · Chunxiao Wang

Disease markers · 2022 doi:10.1155/2022/2081590

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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Exploring Key Genes and Pathways of Cardiac Hypertrophy Based on Bioinformatics.
doi
10.1155/2022/2081590
pmid
36046382
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[0]
Zhenzhen Zhang
[1]
Chunxiao Wang
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Disease markers
year
2022
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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The DEGs of GSE1621 and GSE18801 were analyzed using the online tool GEO2R. The screening criteria for DEGs were adjusted P value < 0.05 and |Log2 fold change (LogFC)| >1.5.
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sections[4] "2.2. Identification of DEGs" paragraph 2
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The DEGs of GSE1621 and GSE18801 were analyzed using the online tool GEO2R. The screening criteria for DEGs were adjusted P value < 0.05 and |Log2 fold change (LogFC)| >1.5.
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The intersection analysis identified 38 co-DEGs between GSE1621 and GSE18801, comprising 17 upregulated and 21 downregulated genes.
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sections[8] "3.1. Identification of DEGs" paragraph 2
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38 co-DEGs, including 17 upregulated genes (Figure 2(c)) and 21 downregulated genes (Figure 2(d)), were obtained by taking the intersection from DEGs of GSE1621 and GSE18801.
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The intersection analysis identified 38 co-DEGs between GSE1621 and GSE18801, comprising 17 upregulated and 21 downregulated genes.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36046382", "kind": "science-record", "revision": 4, "content_hash": "sha256:5a440f1d7a199f6ed4f6da28ea543d678d75249512ede7592ef8b72d17fa5d7a", "created_at": "2026-11-01T18:15:13Z", "updated_at": "2026-11-01T22:07:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploring Key Genes and Pathways of Cardiac Hypertrophy Based on Bioinformatics.", "doi": "10.1155/2022/2081590", "pmid": "36046382", "authors": ["Zhenzhen Zhang", "Chunxiao Wang"], "journal": "Disease markers", "year": 2022, "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.\nMethods: 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.\nResults: 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.\nConclusions: 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.", "claims": [{"id": "claim-method", "statement": "The DEGs of GSE1621 and GSE18801 were analyzed using the online tool GEO2R. 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