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Global Gene Expression Profiling in Neonatal Rat Myocardium in Response to the Anti-diabetic Drug Rosiglitazone Chao-Jen Wong 1,∗, Elliot Kleiman 1, Frank Gonzales 3, Paul Paolini 1,2, 1. Computational Science Research Center, San Diego State University, San Diego, CA, USA 2. Department of Biology, San Diego State University, San Diego, CA, USA 3. School of Public Health, San Diego State University, San Diego, CA, USA 4. Department of Medicine, University of California San Diego, La Jolla, CA, USA 5. University of California San Diego Cancer Center, La Jolla, CA, USA A recent meta-analysis on the relationship between the anti-diabetic drug rosiglitazone(Avandia) and cardiovascular death has created public concern and controversy regardingthe drug’s safety. An alternative meta-analysis approach using clinical data and continu-ity corrections concludes that the link between rosiglitazone and its risk is not statisticallysignificant [1], while RT-PCR studies suggest a possible enhancement in cardioprotectivemechanisms over a forty-eight hour time frame [2].
In this work, we utilize microarray technology to advance our understanding of the biologicalinfluences of rosiglitazone in heart cells. We have employed Illumina’s BeadChipTM technol-ogy to examine the time course gene expression of ventricular myocytes under the treatmentof the drug in neonatal rats (Rattus norvegicus). We report the general expression profilingand, most importantly, interpret the data to determine if the drug significantly affects theregulatory networks and pathways that are directly involved in the contractile response ofheart cells via the calcium signaling pathway that plays a pivotal role in regulating my-ocyte contraction. In implementing these objectives, we have: (i) identified differentiallyexpressed genes using conservative statistical analysis and bioinformatic methods that limitType I errors [3]; (ii) delineated biological processes and molecular functions that may beoverrepresented; and (iii) recognized gene expression patterns based on a subset of genesexhibiting significantly differential expression values.
Our preliminary results show that monocarboxylic acid metabolic, fatty acid metabolic,lipid metabolic, and cellular lipid metabolic processes are overrepresented by differentiallyexpressed genes under the drug treatment, as shown in Table 1. The up- and down-regulatedgenes are listed in Table 2; out of these thirty-two genes, there is no gene directly involved inthe the calcium signaling pathway, which suggests rosiglitazone does not dramatically altercardiac contractility. Further work to identify gene regulatory networks from time courseexpression data will provide a global view of transcriptional network of heart cell responsesto rosiglitazone, which may also demonstrate any connection between the drug and heartfailure.
Table 1: Biological process ontology terms overrepresented by genes differentially expressedin cardiac myocytes under the treatment of rosiglitazone. The size value represents the num-ber of genes associated with that particular biological process. The count value representsthe number of genes in a particular biological process that are significantly regulated.
[1] G. A. Diamond, L. Bax, and S. Kaul, Uncertain Effects of Rosiglitazone on the Risk for Myocardial Infarction and Cardiovascular Death, Annals of Internal Medicine 147(8),12 October 2007.
[2] R. Shah, F. Gonzales, E. Golez, D. Augustin, S. Caudillo, A. Abbott, J. Morello, P.
McDonough, P. Paolini, and H. Shubeita, The Anti-diabetic Agent Rosiglitazone Upreg-ulates SERCA2 and Enhances TNF-α and LPS-Induced NF-κβ-Dependent Transcrip-tion and TNF-α-Induced IL-6 Secretion in Ventricular Myocytes, Cellular Physiologyand Biochemistry 15:41-50, 2004.
[3] R. Gentleman, V. Carey, W. Huber, R. Irizarry, and S. Duoit, Bioinformatics and Computational Biology Solutions Using R and Bioconductor, Springer (2005).
ATP-binding cassette, sub-family A (ABC1) electron-transferring-flavoprotein dehydrogenase 2,4-dienoyl CoA reductase 1, mitochondrial sterol regulatory element binding factor 1 ectonucleoside triphosphate diphosphohydrolase 2 similar to squamous cell carcinoma antigen 2 TCDD-inducible poly(ADP-ribose) polymerase proteoglycan 4, (megakaryocyte stimulating factor) mitogen-activated protein kinase kinase 6 glycerol-3-phosphate dehydrogenase 1 (soluble) guanylate binding protein 1, interferon-inducible Table 2: Differentially expressed genes in response to rosiglitazone. The symbols represent up- and down-regulation, respectively. The symbol ∗ indicates predicted gene.

Source: http://www.icsb07.caltech.edu/proceedings/abstracts/H38.pdf