Aim: To find the molecular interact network specific for different diabetic microangiopathy complications that will direct us to research the mechanism involved in the pathological process of those complications. At present, the plentiful multiomics data of microvascular complications allow us to construct multidimentional regulator network for different microvascular complications from a integrated system perspective. In this study, we introduced hierarchical Bayesian Mode, drivenRN, to decode multi-regulation that form inner regulatory networks in different microvascular complications by combining multi-regulator and transcriptional kinetics into one single model framework, drivenRN can naturally integrate gene expression data and regulator-binding signals in order to identify the hidden driven networks and to detect the key function gene signature. Our study finds out the specific driven networks related to diabetic nephropathy, diabetic retinopathy and diabetic feet respectively. These complication specific driven networks not only offer a new kind biomarker for susceptible patients’ identification but also help us to research the pathological process of microvascular complications systematically. Then offer potential therapy targets and forewarning mechanisms for clinical practice.
Figure 1. The Specific Driven Networks for Different Microvascular Complications of Diabetes Mellitus.
Y. Chen: None. H. Li: None. D. Guan: None.
National Key Research and Development Program of China (2017YFA0105803); National Natural Science Foundation of China (81770826); Sun Yat-sen University (2015015); Science and Technology Plan Projects of Guangdong Province (2016A050502010); Key Special Projects of Medical and Health Collaborative Innovation of Guangzhou City (201604020016); Special Scientific Research Project of Guangzhou City (2060404)
