Research Abstract


Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers

2012年3月29日 Scientific Reports 2 : 342 doi: 10.1038/srep00342


Luonan Chen1,2, Rui Liu2, Zhi-Ping Liu1, Meiyi Li1 & 合原 一幸2

  1. SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences(中国)
  2. 東京大学 生産技術研究所
Considerable evidence suggests that during the progression of complex diseases, the deteriorations are not necessarily smooth but are abrupt, and may cause a critical transition from one state to another at a tipping point. Here, we develop a model-free method to detect early-warning signals of such critical transitions, even with only a small number of samples. Specifically, we theoretically derive an index based on a dynamical network biomarker (DNB) that serves as a general early-warning signal indicating an imminent bifurcation or sudden deterioration before the critical transition occurs. Based on theoretical analyses, we show that predicting a sudden transition from small samples is achievable provided that there are a large number of measurements for each sample, e.g., high-throughput data. We employ microarray data of three diseases to demonstrate the effectiveness of our method. The relevance of DNBs with the diseases was also validated by related experimental data and functional analysis.