PMID- 23620135
OWN - NLM
STAT- MEDLINE
DCOM- 20150219
LR  - 20151119
IS  - 1477-4054 (Electronic)
IS  - 1467-5463 (Linking)
VI  - 15
IP  - 2
DP  - 2014 Mar
TI  - Detecting tissue-specific early warning signals for complex diseases based on 
      dynamical network biomarkers: study of type 2 diabetes by cross-tissue analysis.
PG  - 229-43
LID - 10.1093/bib/bbt027 [doi]
AB  - Identifying early warning signals of critical transitions during disease 
      progression is a key to achieving early diagnosis of complex diseases. By 
      exploiting rich information of high-throughput data, a novel model-free method 
      has been developed to detect early warning signals of diseases. Its theoretical 
      foundation is based on dynamical network biomarker (DNB), which is also called as 
      the driver (or leading) network of the disease because components or molecules in 
      DNB actually drive the whole system from one state (e.g. normal state) to another 
      (e.g. disease state). In this article, we first reviewed the concept and main 
      results of DNB theory, and then applied the new method to the analysis of type 2 
      diabetes mellitus (T2DM). Specifically, based on the temporal-spatial gene 
      expression data of T2DM, we identified tissue-specific DNBs corresponding to the 
      critical transitions occurring in liver, adipose and muscle during T2DM 
      development and progression. Actually, we found that there are two different 
      critical states during T2DM development characterized as responses to insulin 
      resistance and serious inflammation, respectively. Interestingly, a new 
      T2DM-associated function, i.e. steroid hormone biosynthesis, was discovered, and 
      those related genes were significantly dysregulated in liver and adipose at the 
      first critical transition during T2DM deterioration. Moreover, the dysfunction of 
      genes related to responding hormone was also detected in muscle at the similar 
      period. Based on the functional and network analysis on pathogenic molecular 
      mechanism of T2DM, we showed that most of DNB genes, in particular the core ones, 
      tended to be located at the upstream of biological pathways, which implied that 
      DNB genes act as the causal factors rather than the consequence to drive the 
      downstream molecules to change their transcriptional activities. This also 
      validated our theoretical prediction of DNB as the driver network. As shown in 
      this study, DNB can not only signal the emergence of the critical transitions for 
      early diagnosis of diseases, but can also provide the causal network of the 
      transitions for revealing molecular mechanisms of disease initiation and 
      progression at a network level.
FAU - Li, Meiyi
AU  - Li M
AD  - Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, 
      Chinese Academy of Sciences, 320 Yue-Yang Road, Shanghai 200031, China. Tel.: +86 
      21-5492-0100; Fax: +86 21-5497-2551; lnchen@sibs.ac.cn.
FAU - Zeng, Tao
AU  - Zeng T
FAU - Liu, Rui
AU  - Liu R
FAU - Chen, Luonan
AU  - Chen L
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20130425
PL  - England
TA  - Brief Bioinform
JT  - Briefings in bioinformatics
JID - 100912837
RN  - 0 (Biomarkers)
RN  - 0 (Genetic Markers)
RN  - 0 (Steroids)
SB  - IM
MH  - Algorithms
MH  - Animals
MH  - Biomarkers/*metabolism
MH  - Computational Biology/methods
MH  - Diabetes Mellitus, Type 2/*diagnosis/genetics/*metabolism
MH  - Disease Progression
MH  - Early Diagnosis
MH  - Genetic Markers
MH  - High-Throughput Screening Assays/statistics & numerical data
MH  - Humans
MH  - Models, Biological
MH  - Rats
MH  - Signal Transduction
MH  - Steroids/biosynthesis
MH  - Systems Biology
MH  - Tissue Distribution
OTO - NOTNLM
OT  - Type-2 diabetes
OT  - critical transition
OT  - disease progression
OT  - dynamical network biomarker (DNB)
OT  - leading network
OT  - multi-tissues
EDAT- 2013/04/27 06:00
MHDA- 2015/02/20 06:00
CRDT- 2013/04/27 06:00
PHST- 2013/04/27 06:00 [entrez]
PHST- 2013/04/27 06:00 [pubmed]
PHST- 2015/02/20 06:00 [medline]
AID - bbt027 [pii]
AID - 10.1093/bib/bbt027 [doi]
PST - ppublish
SO  - Brief Bioinform. 2014 Mar;15(2):229-43. doi: 10.1093/bib/bbt027. Epub 2013 Apr 
      25.