Implications of cardiac extracellular matrix remodeling and computational frameworks to improve the knowledge discovery post-myocardial infarction.

摘要

Myocardial infarction is a significant cause of mortality and morbidity. Commonly known as heart attack, myocardial infarction is defined as myocardial cell death due to prolonged ischemia. While the events occurring immediately before and after myocardial infarction have been well studied, the effects of myocardial infarction on long-term survival still remain elusive. Although a large amount of research results has been deposited into numerous databases, valuable knowledge is hidden and trapped in different schemas. To this end, it is necessary to integrate data from different resources to develop a global view of myocardial infarction to coordinate future research efforts for improvement of long-term survival following myocardial infarction. The objectives of this study were to 1) examine the current knowledge of extracellular matrix remodeling following myocardial infarction, 2) establish the first knowledge map and predict protein expressions related to the post-myocardial infarction response, and 3) establish a systemic analysis approach to integrate biological processes and pathways to predict potential involvement of proteins in pathways. To fulfill these aims, we have developed a software package to computationally review all PubMed abstracts on myocardial infarction with text mining and extract experimentally confirmed protein-protein-interaction using data mining from public databases. The literature reviewed yielded important extracellular matrix proteins, contributing to the initial set of proteins for the construction of myocardial infarction-specific protein-protein-interaction network. Analysis of the myocardial infarction specific protein network demonstrated the overrepresentation of proteins involved in transcriptional activity, inflammatory response and extracellular matrix remodeling. We further mapped proteins in the myocardial infarction specific protein network into their functional groups to establish the first knowledge map on myocardial infarction. The knowledge map coupled the molecular interactions, cellular responses, biological processes, and pathways, providing a major step towards enhancing our understanding of molecular interactions specific to myocardial infarction. To further extend static property represented by the knowledge map into temporal regulation implicated by biological pathways and pathways, we proposed a Boolean analysis to compare similarities and differences among biological processes and pathways. Such analysis has led to the first logic circuit integrating biological processed into pathways and the corresponding functional interaction network for biological processes and pathways. This functional interaction network delivered an intuitive way to identify biological properties of pathways, allowing researchers and scientists to explore critical routes in the progress of myocardial infarction. In summary, this novel research has provided a systemic approach which links molecular interactions related to myocardial infarction to broad biological processes, maps molecule into specific pathways, and sheds light on temporal progression of myocardial infarction. This approach and the computational package can be easily applied to study other diseases and will provide a foundation for selecting variables and structures of mathematical models for precision disease progression.