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Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network

  • Authors:
    • Jun-Qiang Cao
    • Cai-Xia Li
    • Ru-Yi Wang
    • Jin-Jin Chen
    • Shu-Mei Ma
    • Wen-Ying Wang
    • Li-Jun Meng
  • View Affiliations / Copyright

    Affiliations: Department of Cardiology, Binzhou City Center Hospital, Binzhou, Shandong 251700, P.R. China, Departments of Anesthesiology, Binzhou City Center Hospital, Binzhou, Shandong 251700, P.R. China
    Copyright: © Cao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Pages: 3391-3398
    |
    Published online on: March 6, 2019
       https://doi.org/10.3892/etm.2019.7351
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Abstract

Metabolites are the final products of cellular regulation processes, their level is the ultimate response of biological systems to environmental and genetic changes. Therefore, the identification of key metabolites is required for the diagnosis and therapy of diseases. In this study, atherosclerosis-related gene expression profile information was extracted from ArrayExpress database (GEOD-57691), and analyzed with limma package. Furthermore, we constructed an intricate multi-omics network involved in genes, phenotypes, metabolites and their associations. To identify the prioritization of atherosclerosis-related metabolites, the relation score of each metabolite in the composite network was computed with the random walk with restart (RWR) method. The top 50 metabolites and top 100 genes were chosen based on the score in the weighted composite network. Consequently, several key metabolites that were ranked in the top 5 of relation score or degree greater than 70 were confirmed. Particularly, metabolites Tretinoin and Estraderm not only have high relation scores, but also contain more degrees. Moreover, we obtained 24 co-expression genes that may be regarded as the targets of atherosclerosis therapy. Therefore, identification of metabolite prioritizations by the composite network integrated the information of genes, phenotypes and metabolites may be available to diagnose atherosclerosis, and can provide the potential therapeutic strategies for atherosclerosis.
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Copy and paste a formatted citation
Spandidos Publications style
Cao J, Li C, Wang R, Chen J, Ma S, Wang W and Meng L: Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network . Exp Ther Med 17: 3391-3398, 2019.
APA
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., & Meng, L. (2019). Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network . Experimental and Therapeutic Medicine, 17, 3391-3398. https://doi.org/10.3892/etm.2019.7351
MLA
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., Meng, L."Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network ". Experimental and Therapeutic Medicine 17.5 (2019): 3391-3398.
Chicago
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., Meng, L."Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network ". Experimental and Therapeutic Medicine 17, no. 5 (2019): 3391-3398. https://doi.org/10.3892/etm.2019.7351
Copy and paste a formatted citation
x
Spandidos Publications style
Cao J, Li C, Wang R, Chen J, Ma S, Wang W and Meng L: Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network . Exp Ther Med 17: 3391-3398, 2019.
APA
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., & Meng, L. (2019). Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network . Experimental and Therapeutic Medicine, 17, 3391-3398. https://doi.org/10.3892/etm.2019.7351
MLA
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., Meng, L."Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network ". Experimental and Therapeutic Medicine 17.5 (2019): 3391-3398.
Chicago
Cao, J., Li, C., Wang, R., Chen, J., Ma, S., Wang, W., Meng, L."Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network ". Experimental and Therapeutic Medicine 17, no. 5 (2019): 3391-3398. https://doi.org/10.3892/etm.2019.7351
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