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Sleep and Breathing

, Volume 23, Issue 1, pp 259–267 | Cite as

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

  • Xiandong Gu
  • Wei Yang
  • Xuming Luo
  • Xiongbiao Wang
  • Jihong Tang
  • Zhuying CaiEmail author
Sleep Breathing Physiology and Disorders • Original 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.

Keywords

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

Notes

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).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

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

Informed consent

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

References

  1. 1.
    Azagracalero E, Espinarescalona E, Barreramora JM, Llamascarreras JM, Solanoreina E (2012) Obstructive sleep apnea syndrome (OSAS). Review of the literature. Medicina Oral Patología Oral Y Cirugía Bucal 17:e925–e929CrossRefGoogle Scholar
  2. 2.
    Spicuzza L, Caruso D, Maria GD (2015) Obstructive sleep apnoea syndrome and its management. Therapeutic Advances in Chronic Disease 6:273–285CrossRefGoogle Scholar
  3. 3.
    A Q PD, DK O MS, JE H PS (2014) Diagnosis of obstructive sleep apnea in adults: a clinical practice guideline from the American College of Physicians. Ann Intern Med 161:210–220CrossRefGoogle Scholar
  4. 4.
    Bratton DJ, Gaisl T, Wons AM, Kohler M (2015) CPAP vs mandibular advancement devices and blood pressure in patients with obstructive sleep apnea: a systematic review and meta-analysis. Jama 314:2280–2293CrossRefGoogle Scholar
  5. 5.
    Iftikhar IH, Kline CE, Youngstedt SD (2014) Effects of exercise training on sleep apnea: a meta-analysis. Lung 192:175–184CrossRefGoogle Scholar
  6. 6.
    Gaisl T, Bratton DJ, Kohler M (2015) The impact of obstructive sleep apnoea on the aorta. Eur Respir J 46:532–544CrossRefGoogle Scholar
  7. 7.
    Yaggi HK, Concato J, Kernan WN, Lichtman JH, Brass LM, Mohsenin V (2006) Obstructive sleep apnea as a risk factor for stroke and death. China Prescription Drug 353:2034–2041Google Scholar
  8. 8.
    PE P TY, M P JS (2000) Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 342:1378CrossRefGoogle Scholar
  9. 9.
    Lavie P (2000) Obstructive sleep apnoea syndrome as a risk factor for hypertension: population study. Bmj 320:479–482CrossRefGoogle Scholar
  10. 10.
    Schröder CM, O’Hara R (2005) Depression and obstructive sleep apnea (OSA). Ann General Psychiatry 4:1–8CrossRefGoogle Scholar
  11. 11.
    Kent BD, Mcnicholas WT, Ryan S (2015) Insulin resistance, glucose intolerance and diabetes mellitus in obstructive sleep apnoea. Journal of Thoracic Disease 7:1343Google Scholar
  12. 12.
    Wise J (2016) Women with sleeping problems may be more likely to develop diabetes. Bmj 352:i548CrossRefGoogle Scholar
  13. 13.
    Punjabi NM (2008) The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc 5:136–143CrossRefGoogle Scholar
  14. 14.
    Stanke-Labesque F, Pépin JL, Jouvencel TD, Arnaud C, Baguet JP, Petri MH et al (2012) Leukotriene B4 pathway activation and atherosclerosis in obstructive sleep apnea. J Lipid Res 53:1944–1951CrossRefGoogle Scholar
  15. 15.
    AK H, H G, S T, G C, T H, D W et al (2006) Activation of nuclear factor kappaB in obstructive sleep apnea: a pathway leading to systemic inflammation. Sleep & breathing—Schlaf & Atmung 10:43CrossRefGoogle Scholar
  16. 16.
    Williams A, Scharf SM (2007) Obstructive sleep apnea, cardiovascular disease, and inflammation—is NF-κB the key? Sleep and Breathing 11:69–76CrossRefGoogle Scholar
  17. 17.
    Schulz R, Hummel C, Heinemann S, Seeger W, Grimminger F (2002) Serum levels of vascular endothelial growth factor are elevated in patients with obstructive sleep apnea and severe nighttime hypoxia. Am J Respir Crit Care Med 165:67–70CrossRefGoogle Scholar
  18. 18.
    G Z, F S, P F, R H, L K, D P et al (2005) NADPH oxidase mediates hypersomnolence and brain oxidative injury in a murine model of sleep apnea. Am J Respir Crit Care Med 172:921CrossRefGoogle Scholar
  19. 19.
    Gharib SA, Hayes AL, Rosen MJ, Patel SR (2013) A pathway-based analysis on the effects of obstructive sleep apnea in modulating visceral fat transcriptome. Sleep 36:23–30Google Scholar
  20. 20.
    Carvalho BS, Irizarry RA (2010) A framework for oligonucleotide microarray preprocessing. Bioinformatics 26:2363–2367.  https://doi.org/10.1093/bioinformatics/btq431 CrossRefGoogle Scholar
  21. 21.
    Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, Smyth GK (2015) Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43:e47CrossRefGoogle Scholar
  22. 22.
    Huang DW, Sherman BT, Tan Q, Kir J, Liu D, Bryant D et al (2007) DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res 35:169–175CrossRefGoogle Scholar
  23. 23.
    Consortium TGO (2015) Gene ontology consortium: going forward. Nucleic Acids Res 43:1049–1056CrossRefGoogle Scholar
  24. 24.
    Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M (2015) KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res 44:D457–D462CrossRefGoogle Scholar
  25. 25.
    Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, Lin J, Minguez P, Bork P, von Mering C, Jensen LJ (2013) STRING v9. 1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 41:D808–D815CrossRefGoogle Scholar
  26. 26.
    Saito R, Smoot ME, Ono K, Ruscheinski J, Wang P-L, Lotia S, Pico AR, Bader GD, Ideker T (2012) A travel guide to cytoscape plugins. Nat Methods 9:1069–1076CrossRefGoogle Scholar
  27. 27.
    Tang Y, Li M, Wang J, Pan Y, Wu F-X (2015) CytoNCA: a cytoscape plugin for centrality analysis and evaluation of protein interaction networks. BioSystems 127:67–72.  https://doi.org/10.1016/j.biosystems.2014.11.005 CrossRefGoogle Scholar
  28. 28.
    Bandettini WP, Kellman P, Mancini C, Booker OJ, Vasu S, Leung SW, Wilson JR, Shanbhag SM, Chen MY, Arai AE (2012) MultiContrast Delayed Enhancement (MCODE) improves detection of subendocardial myocardial infarction by late gadolinium enhancement cardiovascular magnetic resonance: a clinical validation study. J Cardiovasc Magn Reson 14:83.  https://doi.org/10.1186/1532-429X-14-83 CrossRefGoogle Scholar
  29. 29.
    Janky Rs VA, Imrichová H, Van de Sande B, Standaert L, Christiaens V et al (2014) iRegulon: from a gene list to a gene regulatory network using large motif and track collections. PLoS Comput Biol 10:e1003731.  https://doi.org/10.1371/journal.pcbi.1003731 CrossRefGoogle Scholar
  30. 30.
    S Ö, T Ö, Acar M, Erbek SS, Köseoğlu S, Göktürk G et al (2016) Association of interleukin-10 gene promoter polymorphisms with obstructive sleep apnea. Sleep Breath 20:855–866CrossRefGoogle Scholar
  31. 31.
    Su MS, Li X, Xu K, Zheng JS (2017) Association of T lymphocyte immune imbalance and IL-10 gene polymorphism with the risk of obstructive sleep apnea in children with obesity. Sleep Breath:1–9Google Scholar
  32. 32.
    Zhu HF, Zhang DH, Xing HY (2011) Expression of interleukin 10 in patients with obstructive sleep apnea hyponea syndrome. Journal of Clinical Pulmonary MedicineGoogle Scholar
  33. 33.
    Jiang H, Cao H, Wang P, Liu W, Cao F, Chen J (2015) Tumour necrosis factor-α/interleukin-10 ratio in patients with obstructive sleep apnoea hypopnoea syndrome. J Laryngol Otol 129:73–78CrossRefGoogle Scholar
  34. 34.
    Leoncabrera S, Aranalechuga Y, Esquedaleón E, Teránpérez G, Gonzalezchavez A, Escobedo G et al (2015) Reduced systemic levels of IL-10 are associated with the severity of obstructive sleep apnea and insulin resistance in morbidly obese humans. Mediat Inflamm 2015:493409Google Scholar
  35. 35.
    Zhao YN, Liu WQ, Wang HY (2013) Effect of grape seed proanthocyanidin on phosphorylated p38MAPK and IL-1β in hippocampus in a rat model of obstructive sleep apnea hypoxia. Journal of Apoplexy & Nervous DiseasesGoogle Scholar
  36. 36.
    Wang Y, Hai B, Niu X, Ai L, Cao Y, Li R, Li Y (2017) Chronic intermittent hypoxia disturbs insulin secretion and causes pancreatic injury via the MAPK signaling pathway. Biochemistry and cell biology—Biochimie et biologie cellulaire 95:415–420CrossRefGoogle Scholar
  37. 37.
    Guo X, Shang J, Deng Y, Yuan X, Zhu D, Liu H (2015) Alterations in left ventricular function during intermittent hypoxia: possible involvement of O-GlcNAc protein and MAPK signaling. Int J Mol Med 36:150–158CrossRefGoogle Scholar
  38. 38.
    Kang HH, Kim IK, Lee HI, Joo H, Lim JU, Lee J et al (2017) Chronic intermittent hypoxia induces liver fibrosis in mice with diet-induced obesity via TLR4/MyD88/MAPK/NF-kB signaling pathways. Biochemical & Biophysical Research Communications 490:349–355CrossRefGoogle Scholar
  39. 39.
    Takahashi K, Chin K, Nakamura H, Morita S, Sumi K, Oga T et al (2008) Plasma thioredoxin, a novel oxidative stress marker, in patients with obstructive sleep apnea before and after nasal continuous positive airway pressure. Antioxid Redox Signal 10:715–726CrossRefGoogle Scholar
  40. 40.
    Guo Q, Wang Y, Li QY, Li M, Wan HY (2013) Levels of thioredoxin are related to the severity of obstructive sleep apnea: based on oxidative stress concept. Sleep Breath 17:311–316CrossRefGoogle Scholar
  41. 41.
    Serra A, Maiolino L, Cocuzza S, Di LM, Campione G, Licciardello L et al (2017) Assessment of oxidative stress markers and hearing thresholds in patients with obstructive sleep apnea-hypopnoea treated with cysteine and superoxide dismutase therapy. Acta Biomed 87:253–258Google Scholar
  42. 42.
    Lira AB, Cf DSR (2016) Evaluation of oxidative stress markers in obstructive sleep apnea syndrome and additional antioxidant therapy: a review article. Sleep Breath 20:1–6CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Xiandong Gu
    • 1
  • Wei Yang
    • 1
  • Xuming Luo
    • 1
  • Xiongbiao Wang
    • 1
  • Jihong Tang
    • 1
  • Zhuying Cai
    • 1
    Email author
  1. 1.Department of Respiratory Medicine, Putuo HospitalShanghai University of Traditional Chinese MedicineShanghaiChina

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