title: Deciphering early development of complex diseases by progressive module network.
abstract: There is no effective cure nowadays for many complex diseases, and thus it is crucial to detect and further treat diseases in earlier stages. Generally, the development and progression of complex diseases include three stages: normal stage, pre-disease stage, and disease stage. For diagnosis and treatment, it is necessary to reveal dynamical organizations of molecular modules during the early development of the disease from the pre-disease stage to the disease stage. Thus, we develop a new framework, i.e. we identify the modules presenting at the pre-disease stage (pre-disease module) based on dynamical network biomarkers (DNBs), detect the modules observed at the advanced stage (disease-responsive module) by cross-tissue gene expression analysis, and finally find the modules related to early development (progressive module) by progressive module network (PMN). As an application example, we used this new method to analyze the gene expression data for NOD mouse model of Type 1 diabetes mellitus (T1DM). After the comprehensive comparison with the previously reported milestone molecules, we found by PMN: (1) the critical transition point was identified and confirmed by the tissue-specific modules or DNBs relevant to the pre-disease stage, which is considered as an earlier event during disease development and progression; (2) several key tissues-common modules related to the disease stage were significantly enriched on known T1DM associated genes with the rewired association networks, which are marks of later events during T1DM development and progression; (3) the tissue-specific modules associated with early development revealed several common essential progressive genes, and a few of pathways representing the effect of environmental factors during the early T1DM development. Totally, we developed a new method to detect the critical stage and the key modules during the disease occurrence and progression, and show that the pre-disease modules can serve as warning signals for the pre-disease state (e.g. T1DM early diagnosis) whereas the progressive modules can be used as the therapy targets for the disease state (e.g. advanced T1DM), which were also validated by experimental data.
authors.affiliation: Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zeng
authors.affiliation: Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Computer, Wuhan University, Wuhan 430072, China.
authors.forename: Chuan-chao
authors.initials: CC
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors.forename: Wanwei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: School of Sciences, South China University of Technology, Guangzhou 510640, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Liu
authors.affiliation: School of Computer, Wuhan University, Wuhan 430072, China. Electronic address: liujuan@whu.edu.cn.
authors.forename: Juan
authors.initials: J
authors.lastname: Liu
authors.affiliation: Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Collaborative Research Center for Innovative Mathematical Modelling, Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan. Electronic address: lnchen@sibs.ac.cn.
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
mesh_terms: D000818:Animals; D003920:Diabetes Mellitus / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D018450:Disease Progression; D042241:Early Diagnosis; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D016688:Mice, Inbred NOD; D008962:Models, Theoretical; D011379:Prognosis
keywords: Disease development and progression; Disease diagnosis and prognosis; Disease therapy; Dynamical network biomarker; Progressive module network; Type 1 diabetes mellitus