Display options
Share it on

Gene Regul Syst Bio. 2014 Mar 10;8:75-87. doi: 10.4137/GRSB.S13134. eCollection 2014.

Tissue-specific gene expression and regulation in liver and muscle following chronic corticosteroid administration.

Gene regulation and systems biology

Tung T Nguyen, Richard R Almon, Debra C Dubois, Siddharth Sukumaran, William J Jusko, Ioannis P Androulakis

Affiliations

  1. BioMaPS Institute for Quantitative Biology, Rutgers University, Piscataway, NJ, USA.
  2. Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA. ; Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA. ; New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, NY, USA.
  3. Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY, USA. ; Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.
  4. Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA.
  5. Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY, USA. ; New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, NY, USA.
  6. Biomedical Engineering Department, Rutgers University, Piscataway, NJ, USA. ; Chemical and Biochemical Engineering Department, Rutgers University, Piscataway, NJ, USA.

PMID: 24653645 PMCID: PMC3956809 DOI: 10.4137/GRSB.S13134

Abstract

Although corticosteroids (CSs) affect gene expression in multiple tissues, the array of genes that are regulated by these catabolic steroids is diverse, highly tissue specific, and depends on their functions in the tissue. Liver has many important functions in performing and regulating diverse metabolic processes. Muscle, in addition to its mechanical role, is critical in maintaining systemic energy homeostasis and accounts for about 80% of insulin-directed glucose disposal. Consequently, a better understanding of CS pharmacogenomic effects in these tissues would provide valuable information regarding the tissue-specificity of transcriptional dynamics, and would provide insights into the underlying molecular mechanisms of action for both beneficial and detrimental effects. We performed an integrated analysis of transcriptional data from liver and muscle in response to methylprednisolone (MPL) infusion, which included clustering and functional annotation of clustered gene groups, promoter extraction and putative transcription factor (TF) identification, and finally, regulatory closeness (RC) identification. This analysis allowed the identification of critical transcriptional responses and CS-responsive functions in liver and muscle during chronic MPL administration, the prediction of putative transcriptional regulators relevant to transcriptional responses of CS-affected genes which are also potential secondary bio-signals altering expression levels of target-genes, and the exploration of the tissue-specificity and biological significance of gene expression patterns, CS-responsive functions, and transcriptional regulation. The analysis provided an integrated description of the genomic and functional effects of chronic MPL infusion in liver and muscle.

Keywords: corticosteroids; gene expression; gene regulation; glucocorticoids; liver; muscle; promoter analysis

References

  1. Adverse Drug React Toxicol Rev. 1996 Nov;15(4):203-6 - PubMed
  2. OMICS. 2009 Jun;13(3):219-37 - PubMed
  3. BMC Bioinformatics. 2010 Oct 14;11:515 - PubMed
  4. Mol Endocrinol. 1988 Dec;2(12):1256-64 - PubMed
  5. Environ Health Perspect. 2003 Nov;111(15):1819-26 - PubMed
  6. Cancer Res. 1989 Apr 15;49(8 Suppl):2295s-2302s - PubMed
  7. Adv Intern Med. 2000;45:317-49 - PubMed
  8. Pharmacol Ther. 2002 Oct;96(1):23-43 - PubMed
  9. PLoS One. 2008 Apr 02;3(4):e1880 - PubMed
  10. Nature. 2001 Dec 13;414(6865):799-806 - PubMed
  11. Crit Rev Eukaryot Gene Expr. 1993;3(2):63-88 - PubMed
  12. Endocrinology. 2007 May;148(5):2209-25 - PubMed
  13. Int Urol Nephrol. 1996;28(3):419-30 - PubMed
  14. Physiol Genomics. 2011 Apr 27;43(8):457-60 - PubMed
  15. PLoS One. 2011;6(5):e18889 - PubMed
  16. PLoS Genet. 2006 Oct 20;2(10):e172 - PubMed
  17. Mol Biol Evol. 2005 Oct;22(10):2113-8 - PubMed
  18. Methods. 2003 Dec;31(4):282-9 - PubMed
  19. AAPS J. 2005 Aug 18;7(1):E156-94 - PubMed
  20. Pharmacogenomics. 2004 Jul;5(5):525-52 - PubMed
  21. Proc Natl Acad Sci U S A. 2008 Dec 30;105(52):20870-5 - PubMed
  22. Adverse Drug React Toxicol Rev. 1998 Nov;17(4):227-35 - PubMed
  23. J Pharmacokinet Biopharm. 1998 Dec;26(6):619-48 - PubMed
  24. Bioinformatics. 2005 Jul 1;21(13):2933-42 - PubMed
  25. BMC Bioinformatics. 2008 Jun 09;9:271 - PubMed
  26. J Pharmacokinet Pharmacodyn. 2002 Apr;29(2):103-29 - PubMed
  27. N Engl J Med. 2005 Oct 20;353(16):1711-23 - PubMed
  28. Genome Res. 2004 Jan;14(1):54-61 - PubMed
  29. BMC Bioinformatics. 2010 May 26;11:279 - PubMed
  30. Physiol Genomics. 2007 Aug 20;30(3):282-99 - PubMed
  31. BMC Genomics. 2005 May 09;6:68 - PubMed
  32. BioData Min. 2008 Sep 19;1(1):8 - PubMed
  33. Science. 1969 Jul 25;165(3891):349-57 - PubMed
  34. J Pharmacokinet Pharmacodyn. 2002 Feb;29(1):1-24 - PubMed
  35. BMC Genomics. 2010 Dec 02;11 Suppl 4:S23 - PubMed
  36. J Pharmacokinet Biopharm. 1998 Jun;26(3):289-317 - PubMed
  37. J Pharmacol Exp Ther. 2002 Jan;300(1):245-56 - PubMed
  38. Eur Respir J. 2006 Feb;27(2):413-26 - PubMed
  39. BMC Biol. 2008 Nov 12;6:49 - PubMed

Publication Types

Grant support