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Bioinformatics analysis to reveal the key genes related to obstructive sleep apnea

Sleep and Breathing volume 23, pages 259–267 (2019)Cite this article

Abstract

Purpose

Obstructive sleep apnea (OSA) is induced by obstruction of the upper airway, which can raise multiple health risks. This study is designed to reveal the key genes involved in OSA.

Methods

GSE38792 was extracted from Gene Expression Omnibus database, including ten visceral adipose tissues from OSA patients and eight visceral adipose tissues from normal controls. Differential expression analysis was conducted using limma package, and then the functions of the differentially expressed genes (DEGs) were analyzed using DAVID database, followed by protein-protein interaction (PPI) network, and integrated regulatory network analysis was performed using Cytoscape software.

Results

A total of 368 DEGs (176 upregulated and 192 downregulated) were identified in OSA samples. Epstein-Barr virus infection (involving IL10RB, MAPK9, and MAPK10) and olfactory transduction were the main pathways separately enriched for the upregulated genes and the downregulated genes. After the PPI network was built, the top ten network nodes (such as TXN) were selected according to node degrees. Two significant PPI network modules were identified. Moreover, the integrated regulatory network was constructed.

Conclusion

IL10RB, MAPK9, MAPK10, and TXN might function in the pathogenesis of OSA.

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Funding

This work was supported by Shanghai Municipal Commission of Health and Family Planning Science and Technology innovation project on traditional Chinese medicine (No.ZYKC201703008).

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Affiliations

  1. Department of Respiratory Medicine, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, No.164, LanXi Road, Shanghai, 200063, China

    Xiandong Gu, Wei Yang, Xuming Luo, Xiongbiao Wang, Jihong Tang & Zhuying Cai

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  1. Xiandong Gu
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  2. Wei Yang
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  3. Xuming Luo
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  4. Xiongbiao Wang
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  5. Jihong Tang
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Correspondence to Zhuying Cai.

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The authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Xiandong Gu and Wei Yang are co-first authors.

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Cite this article

Gu, X., Yang, W., Luo, X. et al. Bioinformatics analysis to reveal the key genes related to obstructive sleep apnea. Sleep Breath 23, 259–267 (2019). https://doi.org/10.1007/s11325-018-1694-7

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  • DOI: https://doi.org/10.1007/s11325-018-1694-7

Keywords

  • Obstructive sleep apnea
  • Differentially expressed genes
  • Enrichment analysis
  • Protein-protein interaction network
  • Integrated regulatory network