Construction and Analysis of Human Diseases and Metabolites Network - Mi, Kai; Jiang, Yanan; Chen, Jiaxin; Lv, Dongxu; Qian, Zhipeng; Sun, Hui; Shang, Desi (Frontiers in Bioengineering and Biotechnology, 2020)
One of the challenging problems in the etiology of diseases is to explore the relationships between initiation and progression of diseases and abnormalities of metabolites. To gain insights into the global relationship between diseases and metabolites, we constructed a human diseases-metabolites network (HDMN). Through analyses based on network biology, Disease score (DS), we found that metabolites associated with the same disorder tend to participate in the same cellular pathway or cascade reactions. In addition, we found the shortest distance between disease metabolites is shorter than that of all metabolites in the KEGG metabolic network. Meanwhile, we identified functional modules in the HDMN to characterize the modularity of complex diseases. The results showed that both disease and metabolite nodes displayed slight clustering phenomenon. We comprehensively estimated correlations between network topological features and metabolites within KEGG metabolic network. A significant positive correlation between the degree of metabolite and the proportion of disease metabolite was found. Also, we found that the average degree of disease metabolites is larger than that of all metabolites. Depicting a comprehensive characteristic of HDMN could provide great insights into understanding the global relationship between disease and metabolites.