Next Article in Journal
Predicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms
Previous Article in Journal
Direct Visualization of Horizontal Gene Transfer by Transformation in Live Pneumococcal Cells Using Microfluidics
Previous Article in Special Issue
A Network-Based Approach for Identification of Subtype-Specific Master Regulators in Pancreatic Ductal Adenocarcinoma
Open AccessArticle

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker

by Jing Ge 1,†, Chenxi Song 2,†, Chengming Zhang 1,3, Xiaoping Liu 1,4, Jingzhou Chen 2, Kefei Dou 2,* and Luonan Chen 1,3,5,6,*
1
Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China
2
State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases & Peking Union Medical College, Beijing 100037, China
3
Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
4
School of Mathematics and Statistics, Shandong University at Weihai, Weihai 264209, China
5
Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
6
School of Life Science and Technology, ShanghaiTech University, 100 Haike Road, Shanghai 201210, China
*
Authors to whom correspondence should be addressed.
Equally contributed to this work.
Genes 2020, 11(6), 676; https://doi.org/10.3390/genes11060676
Received: 14 April 2020 / Revised: 24 May 2020 / Accepted: 15 June 2020 / Published: 20 June 2020
(This article belongs to the Special Issue Current Advances in Network Biology for Disease Understanding)
Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as coronary atherosclerosis. Based on the l-DNB methodology, by using the metabolomics data of plasma of patients with coronary atherosclerosis at different stages, we accurately detected the early-warning signals of each patient. Moreover, we also discovered a group of dynamic network biomarkers (DNBs) which play key roles in driving the progression of the disease. Our study provides a new insight into the individualized early diagnosis of coronary atherosclerosis and may contribute to the development of personalized medicine. View Full-Text
Keywords: single-sample network; landscape dynamic network biomarkers (l-DNB); tipping point; coronary atherosclerosis; myocardial infarction single-sample network; landscape dynamic network biomarkers (l-DNB); tipping point; coronary atherosclerosis; myocardial infarction
Show Figures

Figure 1

MDPI and ACS Style

Ge, J.; Song, C.; Zhang, C.; Liu, X.; Chen, J.; Dou, K.; Chen, L. Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker. Genes 2020, 11, 676.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop