Dynamical network biomarkers: Theory and applications

Kazuyuki Aihara; Rui Liu; Keiichi Koizumi; Xiaoping Liu; Luonan Chen

doi:10.1016/j.gene.2021.145997

Dynamical network biomarkers: Theory and applications

Gene. 2022 Jan 15:808:145997. doi: 10.1016/j.gene.2021.145997. Epub 2021 Oct 6.

Authors

Kazuyuki Aihara¹, Rui Liu², Keiichi Koizumi³, Xiaoping Liu⁴, Luonan Chen⁵

Affiliations

¹ International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan. Electronic address: kaihara@g.ecc.u-tokyo.ac.jp.
² School of Mathematics, South China University of Technology, Guangzhou 510640, China; Pazhou Lab, Guangzhou 510330, China.
³ Division of Kampo Diagnostics, Institute of Natural Medicine, University of Toyama, Toyama, Japan; Laboratory of Drug Discovery and Development for Pre-disease, Section of Host Defences, Division of Bioscience, Institute of Natural Medicine, University of Toyama, Toyama, Japan.
⁴ Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China; Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China.
⁵ Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China; Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China; State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China. Electronic address: lnchen@sibcb.ac.cn.

PMID: 34626720
DOI: 10.1016/j.gene.2021.145997

Abstract

This paper reviews theory of DNB (Dynamical Network Biomarkers) and its applications including both modern medicine and traditional medicine. We show that omics data such as gene/protein expression profiles can be effectively used to detect pre-disease states before critical transitions from healthy states to disease states by using the DNB theory. The DNB theory with big biological data is expected to lead to ultra-early precision and preventive medicine.

Keywords: Bifurcation; Disease state; Dynamical network biomarker; Early warning signals; Healthy state; Pre-disease state; Tipping point; Ultra-early medicine.

Publication types

Review

MeSH terms

Algorithms
Biomarkers / analysis
Biomarkers / metabolism
Disease / genetics*
Disease Progression*
Gene Expression Profiling / methods
Gene Regulatory Networks / genetics*
Genomics / methods
Humans
Proteomics / methods
Time Factors

Substances

Biomarkers