title: The implications of relationships between human diseases and metabolic subpathways.
abstract: One of the challenging problems in the etiology of diseases is to explore the relationships between initiation and progression of diseases and abnormalities in local regions of metabolic pathways. To gain insight into such relationships, we applied the "k-clique" subpathway identification method to all disease-related gene sets. For each disease, the disease risk regions of metabolic pathways were then identified and considered as subpathways associated with the disease. We finally built a disease-metabolic subpathway network (DMSPN). Through analyses based on network biology, we found that a few subpathways, such as that of cytochrome P450, were highly connected with many diseases, and most belonged to fundamental metabolisms, suggesting that abnormalities of fundamental metabolic processes tend to cause more types of diseases. According to the categories of diseases and subpathways, we tested the clustering phenomenon of diseases and metabolic subpathways in the DMSPN. The results showed that both disease nodes and subpathway nodes displayed slight clustering phenomenon. We also tested correlations between network topology and genes within disease-related metabolic subpathways, and found that within a disease-related subpathway in the DMSPN, the ratio of disease genes and the ratio of tissue-specific genes significantly increased as the number of diseases caused by the subpathway increased. Surprisingly, the ratio of essential genes significantly decreased and the ratio of housekeeping genes remained relatively unchanged. Furthermore, the coexpression levels between disease genes and other types of genes were calculated for each subpathway in the DMSPN. The results indicated that those genes intensely influenced by disease genes, including essential genes and tissue-specific genes, might be significantly associated with the disease diversity of subpathways, suggesting that different kinds of genes within a disease-related subpathway may play significantly differential roles on the diversity of diseases caused by the corresponding subpathway.
authors.affiliation: Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, and College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. lixia@hrbmu.edu.cn
authors.forename: Xia
authors.initials: X
authors.lastname: Li
authors.forename: Chunquan
authors.initials: C
authors.lastname: Li
authors.forename: Desi
authors.initials: D
authors.lastname: Shang
authors.forename: Jing
authors.initials: J
authors.lastname: Li
authors.forename: Junwei
authors.initials: J
authors.lastname: Han
authors.forename: Yingbo
authors.initials: Y
authors.lastname: Miao
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.forename: Qianghu
authors.initials: Q
authors.lastname: Wang
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.forename: Chao
authors.initials: C
authors.lastname: Wu
authors.forename: Yunpeng
authors.initials: Y
authors.lastname: Zhang
authors.forename: Xiang
authors.initials: X
authors.lastname: Li
authors.forename: Qianlan
authors.initials: Q
authors.lastname: Yao
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D004194:Disease / Q000235:genetics; D006801:Humans; D053858:Metabolic Networks and Pathways; D012306:Risk