RESUMEN
Identifying molecular connections between developmental processes and disease can lead to new hypotheses about health risks at all stages of life. Here we introduce a new approach to identifying significant connections between gene sets and disease genes, and apply it to several gene sets related to human development. To overcome the limits of incomplete and imperfect information linking genes to disease, we pool genes within disease subtrees in the MeSH taxonomy, and we demonstrate that such pooling improves the power and accuracy of our approach. Significance is assessed through permutation. We created a web-based visualization tool to facilitate multi-scale exploration of this large collection of significant connections (http://gda.cs.tufts.edu/development). High-level analysis of the results reveals expected connections between tissue-specific developmental processes and diseases linked to those tissues, and widespread connections to developmental disorders and cancers. Yet interesting new hypotheses may be derived from examining the unexpected connections. We highlight and discuss the implications of three such connections, linking dementia with bone development, polycystic ovary syndrome with cardiovascular development, and retinopathy of prematurity with lung development. Our results provide additional evidence that TGFB lays a key role in the early pathogenesis of polycystic ovary syndrome. Our evidence also suggests that the VEGF pathway and downstream NFKB signaling may explain the complex relationship between bronchopulmonary dysplasia and retinopathy of prematurity, and may form a bridge between two currently-competing hypotheses about the molecular origins of bronchopulmonary dysplasia. Further data exploration and similar queries about other gene sets may generate a variety of new information about the molecular relationships between additional diseases.
Asunto(s)
Mapeo Cromosómico/métodos , Regulación del Desarrollo de la Expresión Génica/genética , Predisposición Genética a la Enfermedad/genética , Estudio de Asociación del Genoma Completo/métodos , Modelos Genéticos , Proteoma/genética , Animales , Simulación por Computador , Marcadores Genéticos/genética , HumanosRESUMEN
MDSVis (Multidimensional Scaling Visualization) lets analysts explore the simulation space of agent-based models, finding similar patterns at an aggregated level and finding the dominant factors affecting agent behavior. SocialVis lets analysts narrow their analysis to a single simulation run, exploring relationships between time steps and geographic regions.