Identification of dysregulated modules based on network entropy in type 1 diabetes

Type 1 diabetes is a prevalent autoimmune disease of which the underlying mechanisms remain to be elucidated. The aim of the study was to identify dysregulated modules of type 1 diabetes. After microarray data were preprocessed, 20,545 genes were obtained. By integrating gene expression data and protein-protein interactions (PPI) data, 48,778 new networks were obtained, including 7,953 genes. After simplifying networks, we obtained 24 target networks. By ranking networks with P-values, two modules with P<0.05 were identified, including the genes, CCNB1, CDC45, GINS2, NDC80, FBXO5, NCAPG and DLGAP5. Module 2 was part of module 1. The identified modules and genes may provide new insights into the underlying biological mechanisms that drive the progression of type 1 diabetes.