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February-2018 Volume 15 Issue 2

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Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis

  • Authors:
    • Qiang Zhao
    • Ke Wu
    • Nannan Li
    • Zhengmei Li
    • Fenglin Jin
  • View Affiliations / Copyright

    Affiliations: Department of Cardiology, The Affiliated Hospital of Taishan Medical University of Shandong Province, Tai'an, Shandong 271000, P.R. China, Department of Cardiology, Central Hospital of Tai'an of Shandong Province, Tai'an, Shandong 271000, P.R. China, Department of Respiration Medicine, Central Hospital of Tai'an of Shandong Province, Tai'an, Shandong 271000, P.R. China, Department of Radiology, Taishan Medical University of Shandong Province, Tai'an, Shandong 271000, P.R. China
    Copyright: © Zhao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 1456-1464
    |
    Published online on: November 28, 2017
       https://doi.org/10.3892/etm.2017.5580
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Abstract

Myocardial infarction (MI) is a heart disease with high morbidity and mortality rates, thus it is critical to identify genes that serve roles during its pathogenesis. The objective of the present study was to identify potentially relevant genes during the progression of the disease. Blood samples from patients with MI and normal controls (n=3/group) were obtained, the RNA was extracted and cDNA libraries were established. RNA sequencing (RNA‑seq) was performed on a HiSeq 2500 platform and fragments per kilobase of exon per million fragments mapped was utilized to calculate the gene expression value following preprocessing of the RNA‑seq data. Electronic validation of several identified differentially expressed genes (DEGs) was performed on a Gene Expression Omnibus (GEO) dataset GSE59867 (390 cases and 46 healthy controls). Functional enrichment and protein‑protein interaction network analysis was conducted for DEGs. A total of 977 DEGs, including 817 upregulated and 160 downregulated genes were identified in patients with MI. These DEGs were significantly enriched for ‘positive regulation of the immune system process,’ ‘inflammatory response,’ ‘regulation of I‑kappaB‑kinase/NF‑kappaB signaling’ and ‘TNF signaling pathway’. A protein‑protein interaction network of the top 40 DEGs was used to identify high degree genes, including interferon induced protein with tetratricopeptide repeats 3 (IFIT3), MX dynamin like GTPase 1 (MX1), major histocompatibility complex, class II, DQ α1 (HLA‑DQA1), RAR related orphan receptor A (RORA), prostaglandin D2 synthase (PTGDS), cysteine rich protein 2 (CRIP2), collagen type VI α 2 chain (COL6A2) and S100 calcium binding protein P (S100P). The results of validation in the GEO dataset were consistent with the sequencing analysis. A total of eight genes, including IFIT3, MX1, HLA‑DQA1, RORA, PTGDS, CRIP2, COL6A2 and S100P may therefore be considered as potentially relevant genes in the pathology of MI.

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Copy and paste a formatted citation
Spandidos Publications style
Zhao Q, Wu K, Li N, Li Z and Jin F: Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis. Exp Ther Med 15: 1456-1464, 2018.
APA
Zhao, Q., Wu, K., Li, N., Li, Z., & Jin, F. (2018). Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis. Experimental and Therapeutic Medicine, 15, 1456-1464. https://doi.org/10.3892/etm.2017.5580
MLA
Zhao, Q., Wu, K., Li, N., Li, Z., Jin, F."Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis". Experimental and Therapeutic Medicine 15.2 (2018): 1456-1464.
Chicago
Zhao, Q., Wu, K., Li, N., Li, Z., Jin, F."Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis". Experimental and Therapeutic Medicine 15, no. 2 (2018): 1456-1464. https://doi.org/10.3892/etm.2017.5580
Copy and paste a formatted citation
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Spandidos Publications style
Zhao Q, Wu K, Li N, Li Z and Jin F: Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis. Exp Ther Med 15: 1456-1464, 2018.
APA
Zhao, Q., Wu, K., Li, N., Li, Z., & Jin, F. (2018). Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis. Experimental and Therapeutic Medicine, 15, 1456-1464. https://doi.org/10.3892/etm.2017.5580
MLA
Zhao, Q., Wu, K., Li, N., Li, Z., Jin, F."Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis". Experimental and Therapeutic Medicine 15.2 (2018): 1456-1464.
Chicago
Zhao, Q., Wu, K., Li, N., Li, Z., Jin, F."Identification of potentially relevant genes for myocardial infarction using RNA sequencing data analysis". Experimental and Therapeutic Medicine 15, no. 2 (2018): 1456-1464. https://doi.org/10.3892/etm.2017.5580
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