The genomic response of skeletal muscle to methylprednisolone using microarrays: Tailoring data mining to the structure of the pharmacogenomic time series

Pharmacogenomics

Volumn 5, Issue 5, 2004, Pages 525-552

  Almon, Richard R ^a   DuBois, Debra C ^a   Piel, William H ^a   Jusko, William J ^a  

^a UNIVERSITY AT BUFFALO   (United States)

Author keywords

Corticosteriods; Data mining; Expression profiling; Gene chips; Methylprednisolone; Microarrays; Modeling; Pharmacodynamics; Skeletal muscle; Time series

Indexed keywords

METHYLPREDNISOLONE;

ANALYTIC METHOD; ANIMAL TISSUE; ARTICLE; CONTROLLED STUDY; DNA MICROARRAY; DRUG RESPONSE; GENE EXPRESSION; GENE PROBE; HIGH THROUGHPUT SCREENING; HYPOTHESIS; INFORMATION PROCESSING; MALE; NONHUMAN; NUCLEOTIDE SEQUENCE; PHARMACODYNAMICS; PHARMACOGENOMICS; RAT; SAMPLE SIZE; SKELETAL MUSCLE; TIME SERIES ANALYSIS; UNINDEXED SEQUENCE;

ADRENALECTOMY; ANIMALS; MALE; METHYLPREDNISOLONE; MUSCLE, SKELETAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PHARMACOGENETICS; RATS; RATS, WISTAR; RNA, COMPLEMENTARY; TIME FACTORS;

EID: 3543069887     PISSN: 14622416     EISSN: None     Source Type: Journal    
DOI: 10.1517/14622416.5.5.525     Document Type: Article

References (36)

1. Almon RR, DuBois DC: Fiber-type discrimination in disuse and glucocorticoid-induced atrophy. Med. Sci. Sports Exerc. 22, 304-311 (1990).
2. McKay LI, DuBois DC, Sun YN, Almon RR, Jusko WJ: Corticosteroid effects in skeletal muscle: gene induction/receptor autoregulation. Muscle Nerve 20, 1318-1320 (1997).
3. Sun YN, McKay LI, DuBois DC, Jusko WJ, Almon RR: Pharmacokinetic/pharmacodynamic models for corticosteroid receptor down-regulation and glutamine synthetase induction in rat skeletal muscle by a receptor/gene-mediated mechanism. J. Pharmacol. Exp. ther. 288, 270-278 (1999).
4. Reynolds RM, Walker BR: Human insulin resistance: the role of glucocorticoids. Diabetes Obes. Metab. 5, 5-12 (2003).
5. Selyatitskaya VG, Kuzminova OI, Odintsov SV: Development of insulin resistance in experimental animals during long-term glucocorticoid treatment. Bull. Exp. Biol. Med. 133, 339-341 (2002).
6. Wald JA, Farr RS: Abnormal liver-function tests associated with long-term systemic corticosteroid use in subjects with asthma. J. Allergy clin. Immunol. 88, 277-278 (1991).
7. Eisenstein A: Effects of adrenal cortical hormones on carbohydrate, protein, and fat metabolism. Am. J. Clin. Nutr. 26, 113-120 (1973).
8. Tomono S, Ohyama Y, Uchiyama T: Insulin resistance induced by drugs, inflammation and stress. Jpn. J. Clin. Med. 60, 632-636 (2002).
9. Bialas MC, Routledge PA: Adverse effects of corticosteroids. Adverse Drug React. Toxicol. Rev. 17, 227-235 (1998).
10. Sun YN, DuBois DC, Almon RR, Jusko WJ: Fourth-generation model for corticosteroid pharmacodynamics: a model for methylprednisolone effects on receptor/gene-mediated glucocorticoid receptor down-regulation and tyrosine aminotransferase induction in rat liver. J. Pharmacokinet. Biopharm. 26, 289-317 (1998).
11. Almon RR, DuBois DC, Brandenburg EH et al.: Pharmacodynamics and pharmacogenomics of diverse receptor-mediated effeccs of methylprednisolone in rats using microarray analysis. J. Pharmacokinet. Pharmacodyn. 29, 103-129 (2002).
12. Barbera M, Fierabracci V, Novelli M et al.: Dexamethasone-induced insulin resistance and pancreatic adaptive response in aging rats are not modified by oral vanadyl sulfate treatment. Eur. J. Endo. 145, 799-806 (2001).
13. Jin JY, DuBois DC, Jusko WJ, Almon RR: Modeling of corticosteroid pharmacogenomics in rat liver using gene microarrays. J. Pharmacol. Exp. Ther. 307, 93-109 (2003).
14. Klaassen CD: Induction of metallothionein by adrenocortical steroids. Toxicology 20, 275-279 (1981).
15. Ramakrishnan R, DuBois DC, Almon RR, Pyszczynski NA, Jusko WJ: Fifth-generation model for corticosteroid pharmacodynamics: application to steady-state receptor down-regulation and enzyme induction patterns during seven-day continuous infusion of methylprednisolone in rats. J. Pharmacokinet. Pharmacodyn. 29, 1-24 (2002).
16. Ramakrishnan R, DuBois DC, Almon RR, Pyszczynski NA, Jusko WJ: Pharmacodynamics and pharmacogenomics of methylprednisolone during 7-day infusions in rats. J. Pharmacol. Exp. Ther. 300, 245-256 (2002).
17. Sun YN, DuBois DC, Almon RR, Pyszczynski NA, Jusko, WJ: Dose-dependence and repeated-dose studies for receptor/gene-mediated pharmacodynamics of methylprednisolone on glucocorticoid receptor down-regulation and tyrosine aminotransferase induction in rat liver. J. Pharmacokinet. Biopharm. 26, 619-648 (1998).
18. Garlatti M, Aggerbeck M, Bouguet J, Barouki R: Contribution of a nuclear factor 1 binding site to the glucocorticoid regulation of the cytosolic aspartate aminotransferase gene promoter. J. Biol. Chem. 271, 32629-32634 (1996).
19. Long W, Wei L, Barrett EJ: Dexamethasone inhibits the stimulation of muscle protein synthesis and PHAS-I and p70 S6-kinase phosphorylation. Am. J. Physiol. Endocrinol. Metab. 280, E570-E575 (2001).
20. Makkinje A, Quinn DA, Chen A et al.: Gene 33/Mig-6, a transcriptionally inducible adapter protein that binds GTP-Cdc42 and activates SAPK/JNK. A potential marker transcript for chronic pathologic conditions, such as diabetic nephropathy. Possible role in the response to persistent stress. J. Biol. Chem. 275, 17838-17847 (2000).
21. Masters JN, Cotman SL, Osterburg HH, Nichols NR, Finch CE: Modulation of a novel RNA in brain neurons by glucocorticoid and mineralocorticoid receptors. Neuroendocrinology 63, 28-38 (1996).
22. Takiguchi M, Mori M: Transcriptional regulation of genes for ornithine cycle enzymes. Biochem. J. 312, 649-659 (1985).
23. Bodine SC, Latres E, Baumhueter S et al.: Identification of ubiquitin ligases required for skeletal muscle atrophy. Science 294, 1704-1708 (2001).
24. Son C, Hosoda K, Matsuda J et al.: Up-regulation of uncoupling protein 3 gene expression by fatty acids and agonists for PPARs in L6 myotubes. Endocrinology 142, 4189-4194 (2001).
25. Sugden MC, Orfali KA, Holness MJ: The pyruvate dehydrogenase complex: nutrient control and the pathogenesis of insulin resistance. J. Nutr. 125, 1746S-1752S (1995).
26. Sugden MC, Holness MJ: Therapeutic potential of the mammalian pyruvate dehydrogenase kinases in the prevention of hyperglycaemia. Curr. Drug Targets Immune Endocr. Metab. Disord. 2, 151-165 (2002).
27. Almon RR, Chen J, Snyder G, DuBois DC, Jusko WJ, Hoffman EP: In vivo multi-tissue corticosteroid microarray time series available online at Public Expression Profile Resource (PEPR). Pharmacogenomics 4, 791-799 (2003).
28. Cojocaru G, Friedman N, Krupsky M et al.: Transcriptional profiling of non-small cell lung cancer using oligonucleotide microarrays. Chest 121, 44S (2002).
29. Friedman N, Kaminski N: Statistical methods for analyzing gene expression data for cancer research. Ernst Schering Res. Found. Workshop 109-131 (2002).
30. Kaminski N: Microarray analysis of idiopathic pulmonary fibrosis. Am. J. Respir. Cell Mol. Biol. 29, S32-S36 (2003).
31. Lock C, Hermans G, Pedotti R et al.: Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis. Nat. Med. 8, 500-508 (2002).
32. Morgan KT, Ni H, Brown HR et al.: Application of cDNA microarray technology to in vitro toxicology and the selection of genes for a real-time RT-PCR-based screen for oxidative stress in Hep-G2 cells. Toxicol. Pathol. 30, 435-451 (2002).
33. Rhodes DR, Barrette TR, Rubin MA, Ghosh D, Chinnaiyan AM: Meta-analysis of microarrays: interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer Res. 62, 4427-4433 (2002).
34. Tumour Analysis Best Practices Working Group: Expression profiling - best practices for data generation and interpretation in clinical trials. Nat. Rev. Genet. 5, 229-237 (2004).
35. Seo J, Bakay M, Chen Y, Himler S, Shneiderman B, Hoffman E: Optimizing signal/noise ratios in expression profiling, project-specific algorithm selection and detection p value weighting in affymetrix microarrays. Bioinformatics (2004) (In Press).
36. Eisen MB, Spellman PT, Brown PO, Botstein D: Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863-14868 (1998).