title: Comparative analysis of a novel disease phenotype network based on clinical manifestations.
abstract: Systems approaches to analyzing disease phenotype networks in combination with protein functional interaction networks have great potential in illuminating disease pathophysiological mechanisms. While many genetic networks are readily available, disease phenotype networks remain largely incomplete. In this study, we built a large-scale Disease Manifestation Network (DMN) from 50,543 highly accurate disease-manifestation semantic relationships in the United Medical Language System (UMLS). Our new phenotype network contains 2305 nodes and 373,527 weighted edges to represent the disease phenotypic similarities. We first compared DMN with the networks representing genetic relationships among diseases, and demonstrated that the phenotype clustering in DMN reflects common disease genetics. Then we compared DMN with a widely-used disease phenotype network in previous gene discovery studies, called mimMiner, which was extracted from the textual descriptions in Online Mendelian Inheritance in Man (OMIM). We demonstrated that DMN contains different knowledge from the existing phenotype data source. Finally, a case study on Marfan syndrome further proved that DMN contains useful information and can provide leads to discover unknown disease causes. Integrating DMN in systems approaches with mimMiner and other data offers the opportunities to predict novel disease genetics. We made DMN publicly available at nlp/case.edu/public/data/DMN.
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, United States; Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States.
authors.forename: Yang
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, United States.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, United States; Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States.
authors.forename: Guo-Qiang
authors.initials: GQ
authors.lastname: Zhang
authors.affiliation: Division of Medical Informatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States. Electronic address: rxx@case.edu.
authors.forename: Rong
authors.initials: R
authors.lastname: Xu
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D005838:Genotype; D006801:Humans; D008382:Marfan Syndrome / Q000175:diagnosis / Q000235:genetics; D015233:Models, Statistical; D009154:Mutation; D010641:Phenotype; D015203:Reproducibility of Results; D017432:Unified Medical Language System
keywords: Disease phenotype network; Network analysis; Ontology