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Integrative bioinformatics analysis of genomic and proteomic approaches to understand the transcriptional regulatory program in coronary artery disease pathways.

Vangala RK, Ravindran V, Ghatge M, Shanker J, Arvind P, Bindu H, Shekar M, Rao VS - PLoS ONE (2013)

Bottom Line: Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways.These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease.This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

View Article: PubMed Central - PubMed

Affiliation: Tata Proteomics and Coagulation Department, Thrombosis Research Institute, Bangalore, Karnataka, India. rajani@triindia.org.in

ABSTRACT
Patients with cardiovascular disease show a panel of differentially regulated serum biomarkers indicative of modulation of several pathways from disease onset to progression. Few of these biomarkers have been proposed for multimarker risk prediction methods. However, the underlying mechanism of the expression changes and modulation of the pathways is not yet addressed in entirety. Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways. Using the principles of systems biology we integrated the genomics and proteomics data with computational tools. We selected biomarkers from 7 different pathways based on their association with the disease and assayed 24 biomarkers along with gene expression studies and built network modules which are highly regulated by 5 core regulators PPARG, EGR1, ETV1, KLF7 and ESRRA. These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease. This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

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Identification of core transcription factors.a. Venn-diagram of the 443 Transcription factors regulating the pathways in CVD and identification of 55 core transcription factors. b. Mean expression levels of significant transcription factors obtained from microarray between cases and controls. c. Number of binding sites of 34 expressed transcription factors in the biomarkers from 7 different pathways. d. Venn-diagram of the 34 significant Transcription factors regulating the pathways in CVD and identification of 5 core transcription factors as PPARG, EGR-1, ETV-1, KLF-7, and ESRRA.
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pone-0057193-g002: Identification of core transcription factors.a. Venn-diagram of the 443 Transcription factors regulating the pathways in CVD and identification of 55 core transcription factors. b. Mean expression levels of significant transcription factors obtained from microarray between cases and controls. c. Number of binding sites of 34 expressed transcription factors in the biomarkers from 7 different pathways. d. Venn-diagram of the 34 significant Transcription factors regulating the pathways in CVD and identification of 5 core transcription factors as PPARG, EGR-1, ETV-1, KLF-7, and ESRRA.

Mentions: The 31 biomarkers selected were belonging to seven different pathways representing the pathological progression of the disease. The promoter regions of these 31 biomarkers were analyzed for TF binding sites using Genomatix software. 443 TFs were identified to be binding to the biomarker promoter regions of which 55 were common for all the 31 biomarkers (figure 2a). These 55 TFs could potentially regulate different pathways like stress, oxidative stress, inflammation, coagulation, cell adhesion, obesity and renal function. Furthermore we found that these 443 TFs belong to 124 different families and the core 55 (Table S1) were representatives of 23 TF families.


Integrative bioinformatics analysis of genomic and proteomic approaches to understand the transcriptional regulatory program in coronary artery disease pathways.

Vangala RK, Ravindran V, Ghatge M, Shanker J, Arvind P, Bindu H, Shekar M, Rao VS - PLoS ONE (2013)

Identification of core transcription factors.a. Venn-diagram of the 443 Transcription factors regulating the pathways in CVD and identification of 55 core transcription factors. b. Mean expression levels of significant transcription factors obtained from microarray between cases and controls. c. Number of binding sites of 34 expressed transcription factors in the biomarkers from 7 different pathways. d. Venn-diagram of the 34 significant Transcription factors regulating the pathways in CVD and identification of 5 core transcription factors as PPARG, EGR-1, ETV-1, KLF-7, and ESRRA.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3585295&req=5

pone-0057193-g002: Identification of core transcription factors.a. Venn-diagram of the 443 Transcription factors regulating the pathways in CVD and identification of 55 core transcription factors. b. Mean expression levels of significant transcription factors obtained from microarray between cases and controls. c. Number of binding sites of 34 expressed transcription factors in the biomarkers from 7 different pathways. d. Venn-diagram of the 34 significant Transcription factors regulating the pathways in CVD and identification of 5 core transcription factors as PPARG, EGR-1, ETV-1, KLF-7, and ESRRA.
Mentions: The 31 biomarkers selected were belonging to seven different pathways representing the pathological progression of the disease. The promoter regions of these 31 biomarkers were analyzed for TF binding sites using Genomatix software. 443 TFs were identified to be binding to the biomarker promoter regions of which 55 were common for all the 31 biomarkers (figure 2a). These 55 TFs could potentially regulate different pathways like stress, oxidative stress, inflammation, coagulation, cell adhesion, obesity and renal function. Furthermore we found that these 443 TFs belong to 124 different families and the core 55 (Table S1) were representatives of 23 TF families.

Bottom Line: Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways.These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease.This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

View Article: PubMed Central - PubMed

Affiliation: Tata Proteomics and Coagulation Department, Thrombosis Research Institute, Bangalore, Karnataka, India. rajani@triindia.org.in

ABSTRACT
Patients with cardiovascular disease show a panel of differentially regulated serum biomarkers indicative of modulation of several pathways from disease onset to progression. Few of these biomarkers have been proposed for multimarker risk prediction methods. However, the underlying mechanism of the expression changes and modulation of the pathways is not yet addressed in entirety. Our present work focuses on understanding the regulatory mechanisms at transcriptional level by identifying the core and specific transcription factors that regulate the coronary artery disease associated pathways. Using the principles of systems biology we integrated the genomics and proteomics data with computational tools. We selected biomarkers from 7 different pathways based on their association with the disease and assayed 24 biomarkers along with gene expression studies and built network modules which are highly regulated by 5 core regulators PPARG, EGR1, ETV1, KLF7 and ESRRA. These network modules in turn comprise of biomarkers from different pathways showing that the core regulatory transcription factors may work together in differential regulation of several pathways potentially leading to the disease. This kind of analysis can enhance the elucidation of mechanisms in the disease and give better strategies of developing multimarker module based risk predictions.

Show MeSH
Related in: MedlinePlus