A computationally inferred regulatory heart aging model including post-transcriptional regulations

Cardiovascular diseases are one of the leading causes of death in most developed countries and aging is a dominant risk factor for their development. Among the different factors, miRNAs have been identified as relevant players in the development of cardiac pathologies and their ability to influence gene networks suggests them as potential therapeutic targets or diagnostic markers. This paper presents a computational study that applies data fusion techniques coupled with network analysis theory to identify a regulatory model able to represent the relationship between key genes and miRNAs involved in cardiac senescence processes. The model has been validated through an extensive literature analysis that was able to connect 94% of the identified genes and miRNAs with cardiac senescence related studies.