Investigation of the roles of trace elements during hepatitis C virus infection using protein-protein interactions and a shortest path algorithm

• Published in: Biochimica et biophysica acta Vol. 1860; no. 11; pp. 2756 - 2768
• Main Authors: Zhu, LiuCun, Chen, XiJia, Kong, Xiangyin, Cai, Yu-Dong
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.11.2016
• Subjects: Algorithms; Carcinoma, Hepatocellular - etiology; Carcinoma, Hepatocellular - genetics; Carcinoma, Hepatocellular - metabolism; genes; genetics; HCV; Hepacivirus - pathogenicity; hepatitis C; Hepatitis C - complications; Hepatitis C - genetics; Hepatitis C - metabolism; Hepatitis C virus; hepatoma; Host-Pathogen Interactions - genetics; human health; Humans; inflammation; liver; Liver - metabolism; Liver Cirrhosis - etiology; Liver Cirrhosis - genetics; Liver Cirrhosis - metabolism; Liver Neoplasms - etiology; Liver Neoplasms - genetics; Liver Neoplasms - metabolism; pathogenesis; pathogens; Permutation test; Protein Interaction Maps - genetics; Protein-protein interaction; protein-protein interactions; Shortest path algorithm; Trace element; trace elements; Trace Elements - adverse effects; Trace Elements - metabolism; Trace element; HCV; Protein-protein interaction; Permutation test; Shortest path algorithm
• ISSN: 0304-4165; 0006-3002; 1872-8006
• DOI: 10.1016/j.bbagen.2016.05.018

Hepatitis is a type of infectious disease that induces inflammation of the liver without pinpointing a particular pathogen or pathogenesis. Type C hepatitis, as a type of hepatitis, has been reported to induce cirrhosis and hepatocellular carcinoma within a very short amount of time. It is a great threat to human health. Some studies have revealed that trace elements are associated with infection with and immune rejection against hepatitis C virus (HCV). However, the mechanism underlying this phenomenon is still unclear. In this study, we aimed to expand our knowledge of this phenomenon by designing a computational method to identify genes that may be related to both HCV and trace element metabolic processes. The searching procedure included three stages. First, a shortest path algorithm was applied to a large network, constructed by protein-protein interactions, to identify potential genes of interest. Second, a permutation test was executed to exclude false discoveries. Finally, some rules based on the betweenness and associations between candidate genes and HCV and trace elements were built to select core genes among the remaining genes. 12 lists of genes, corresponding to 12 types of trace elements, were obtained. These genes are deemed to be associated with HCV infection and trace elements metabolism. The analyses indicate that some genes may be related to both HCV and trace element metabolic processes, further confirming the associations between HCV and trace elements. The method was further tested on another set of HCV genes, the results indicate that this method is quite robustness. The newly found genes may partially reveal unknown mechanisms between HCV infection and trace element metabolism. This article is part of a Special Issue entitled “System Genetics” Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. •Trace elements are reported to be associated with hepatitis C virus (HCV).•A method was designed to identify genes related to both HCV and trace elements.•Several novel genes were produced by our method.•Extensive analyses on the identified genes suggest the utility of the method.