network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets基于网络的说明人类疾病相似之处揭示公共功能模块丰富的多功能药物靶点.pdfVIP

Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets 1,2,3 1,2,3 1,2,3 1,2,3 4 Silpa Suthram , Joel T. Dudley , Annie P. Chiang , Rong Chen , Trevor J. Hastie , Atul J. Butte1,2,3* 1 Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, United States of America, 2 Department of Pediatrics, Stanford University, Stanford, California, United States of America, 3 Lucile Packard Children’s Hospital, Palo Alto, California, United States of America, 4 Department of Statistics, Stanford University, Stanford, California, United States of America Abstract Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state ‘‘signature’’. These modules were significantly enriched for genes th