Politano Gianfranco, Logrand Federica, Brancaccio Mara, Di Carlo Stefano
Politecnico di Torino, Control and Computer Engineering Department, Torino, Italy.
Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy.
Methods. 2017 Jul 15;124:57-68. doi: 10.1016/j.ymeth.2017.06.002. Epub 2017 Jun 8.
In most developed countries, cardiovascular diseases are among the top causes of death and their development has been shown closely related to aging. In this context, because of their ability to pervasively influence gene networks, miRs have been found as possible key players in the development of cardiac pathologies, suggesting their potential role as therapeutic targets or diagnostic markers. Based on these assumptions, we hereby present 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 miRs involved in cardiac senescence processes. The proposed model has been validated through an extensive literature analysis, which confirmed that 94% of the identified genes and miRs are related with cardiac senescence. Furthermore, two relevant genes of the model have been also validated by Western blot experiments on heart samples from young and old mice, confirming in vitro their ectopic expression in aged hearts. The pure computationally inferred model presented in the paper is therefore a good candidate to represent the relationship between key genes and miRs involved in cardiac senescence processes, and represents a reliable selection of genes and miRs for further studies, in order to elucidate and better detail their involvement in cardiac aging.
在大多数发达国家，心血管疾病是主要死因之一，且其发展已被证明与衰老密切相关。在此背景下，由于微小RNA（miRs）能够广泛影响基因网络，它们被发现可能是心脏疾病发展的关键因素，这表明它们作为治疗靶点或诊断标志物具有潜在作用。基于这些假设，我们在此展示一项计算研究，该研究应用数据融合技术并结合网络分析理论，以识别一个能够代表参与心脏衰老过程的关键基因和miRs之间关系的调控模型。所提出的模型已通过广泛的文献分析得到验证，该分析证实所识别的基因和miRs中有94%与心脏衰老相关。此外，该模型的两个相关基因也已通过对年轻和老年小鼠心脏样本的蛋白质免疫印迹实验得到验证，在体外证实了它们在老年心脏中的异位表达。因此，本文中提出的纯计算推断模型是一个很好的候选模型，可用于代表参与心脏衰老过程的关键基因和miRs之间的关系，并且为进一步研究提供了可靠的基因和miRs选择，以便阐明并更详细地了解它们在心脏衰老中的作用。
