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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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Related in: MedlinePlus

Transcription factor and Protein network.Circled Transcription factors are common among the pathways. The dashed line represents the demarcation between the Transcription factor regulation in nucleus and biomarker expression in extracellular matrix.
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pone-0057193-g004: Transcription factor and Protein network.Circled Transcription factors are common among the pathways. The dashed line represents the demarcation between the Transcription factor regulation in nucleus and biomarker expression in extracellular matrix.

Mentions: Based on the transcription factors identified and biomarkers analyzed we used STRING database to develop a network model (figure 4). As seen in the figure 4, the TFs PPARG, EGR1, ESRRA, CEBPB, ETS1, LMX1B and MAFB are the direct networking members with the biomarkers. Of these 7 TFs, PPARG and EGR1 are highly networked and are interfacing with the biomarkers. PPARG seems to be associated with other transcription factors like ESRRA, AHR, EGR1, TCF7L2, and CEBPB, potentially co-regulating the target biomarkers of the TFs. SimilarlyEGR1, is associated with SRF, EGR3, EGR2, PAX2, CEBPB, and MAFB transcription factors. These kinds of networks suggest the collaborative interactions between several TFs in regulating the biomarkers.


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)

Transcription factor and Protein network.Circled Transcription factors are common among the pathways. The dashed line represents the demarcation between the Transcription factor regulation in nucleus and biomarker expression in extracellular matrix.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0057193-g004: Transcription factor and Protein network.Circled Transcription factors are common among the pathways. The dashed line represents the demarcation between the Transcription factor regulation in nucleus and biomarker expression in extracellular matrix.
Mentions: Based on the transcription factors identified and biomarkers analyzed we used STRING database to develop a network model (figure 4). As seen in the figure 4, the TFs PPARG, EGR1, ESRRA, CEBPB, ETS1, LMX1B and MAFB are the direct networking members with the biomarkers. Of these 7 TFs, PPARG and EGR1 are highly networked and are interfacing with the biomarkers. PPARG seems to be associated with other transcription factors like ESRRA, AHR, EGR1, TCF7L2, and CEBPB, potentially co-regulating the target biomarkers of the TFs. SimilarlyEGR1, is associated with SRF, EGR3, EGR2, PAX2, CEBPB, and MAFB transcription factors. These kinds of networks suggest the collaborative interactions between several TFs in regulating the biomarkers.

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