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Issue 1, 2016
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Identification of potential COPD genes based on multi-omics data at the functional level

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Abstract

Chronic obstructive pulmonary disease (COPD) is a complex disease, which involves dysfunctions in multi-omics. The changes in biological processes, such as adhesion junction, signaling transduction, transcriptional regulation, and cell proliferation, will lead to the occurrence of COPD. A novel systematic approach MMMG (Methylation–MicroRNA–MRNA–GO) was proposed to identify potential COPD genes by integrating function information with a methylation profile, a microRNA expression profile and an mRNA expression profile. 8 co-functional classes and 102 potential COPD genes were identified. These genes displayed a high performance in classifying COPD patients and normal samples, revealed COPD-related pathways, and have been confirmed to be associated with COPD by Matthews correlation coefficient (MCC)-values, literature, an independent data set, and pathways. The MMMG method that analyzed multi-omics data at the functional level could effectively identify potential COPD genes. These potential COPD genes would provide in-depth insights into understanding the complexity of COPD genome landscapes, improve the early diagnostics, and guide new efforts to develop therapeutics in the future.

Graphical abstract: Identification of potential COPD genes based on multi-omics data at the functional level

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Publication details

The article was received on 26 Aug 2015, accepted on 02 Nov 2015 and first published on 03 Nov 2015


Article type: Paper
DOI: 10.1039/C5MB00577A
Mol. BioSyst., 2016,12, 191-204

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    Identification of potential COPD genes based on multi-omics data at the functional level

    Z. Liu, W. Li, J. Lv, R. Xie, H. Huang, Y. Li, Y. He, J. Jiang, B. Chen, S. Guo and L. Chen, Mol. BioSyst., 2016, 12, 191
    DOI: 10.1039/C5MB00577A

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