title: Network and Pathway-Based Analyses of Genes Associated with Parkinson's Disease.
abstract: Parkinson's disease (PD) is a major neurodegenerative disease influenced by both genetic and environmental factors. Although previous studies have provided insights into the significant impacts of genetic factors on PD, the molecular mechanism underlying PD remains largely unclear. Under such situation, a comprehensive analysis focusing on biological function and interactions of PD-related genes will provide us valuable information to understand the pathogenesis of PD. In the current study, by reviewing the literatures deposited in PUBMED, we identified 242 genes genetically associated with PD, referred to as PD-related genes gene set (PDgset). Functional analysis revealed that biological processes and biochemical pathways related to neurodevelopment, metabolism, and immune system were enriched in PDgset. Then, pathway crosstalk analysis indicated that the enriched pathways could be grouped into two modules, with one module consisted of pathways mainly involved in neuronal signaling and another in immune response. Further, based on a global human interactome, we found that PDgset tended to have more moderate degree compared with cancer-related genes. Moreover, PD-specific molecular network was inferred using Steiner minimal tree algorithm and some potential related genes associated with PD were identified. In summary, by using network- and pathway-based methods to explore pathogenetic mechanism underlying PD, results from our work may have important implications for understanding the molecular mechanism underlying PD. Also, the framework proposed in our current work can be used to infer pathological molecular network and genes related to a specific disease.
authors.affiliation: School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
authors.forename: Yanshi
authors.initials: Y
authors.lastname: Hu
authors.affiliation: School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
authors.forename: Zhenhua
authors.initials: Z
authors.lastname: Pan
authors.affiliation: School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Hu
authors.affiliation: School of Computer Science and Technology, Tianjin University, Tianjin, 300072, China. lzhang@tju.edu.cn.
authors.forename: Lei
authors.initials: L
authors.lastname: Zhang
authors.affiliation: School of Biomedical Engineering, Tianjin Medical University, Tianjin, 300070, China. wangju@tmu.edu.cn.
authors.forename: Ju
authors.identifier: 0000-0002-6514-0923
authors.initials: J
authors.lastname: Wang
mesh_terms: D030541:Databases, Genetic; D053263:Gene Regulatory Networks; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D010300:Parkinson Disease / Q000235:genetics*; D015398:Signal Transduction / Q000235:genetics
keywords: Functional enrichment analysis; Network analysis; Parkinson’s disease; Pathway crosstalk