A disease-gene-drug connectivity website

Published 10/29/2015 11:17:42 PM  |  Last update 3/13/2019 01:20:55 AM

Human chromosome 21 (HSA21) encodes approximately 160 classical protein coding genes, five microRNAs and an additional >350 genes of unassigned function (Sturgeon et al., 2010). Over expression of these genes, as in Down syndrome, will result in complex perturbations of multiple processes involved in neurological development and function.

While several recent reports have shown pharmacological rescue of learning and memory deficits in a popular mouse model of DS (the Ts65Dn), this model is trisomic for fewer than 100 HSA21 proteins. Development of safe and effective pharmacotherapies for the cognitive deficits in DS requires an understanding of pathway perturbations in a full trisomy HSA21. We developed a Human Genes - Drugs - Pathways database and a system of web interfaces to allow queries against the database online. Data in the database are combined from popular bioinformatics repositories, including NCBI, UniProt and GO for the list of genes, molecules and biological annotations; BIND, HPRD, BioGRID and IntAct for physical protein-protein interactions; KEGG, Reactome, BioCarta and PID for curated pathways of known biological processes. Using the website, we developed a systems neuroscience, pathway-based approach, not only to understand non-HSA21 molecular abnormalities observed in DS and mouse models, but also to predict additional abnormalities and potential responses of these systems to drug treatments. The subset of pathways relevant to intellectual disability (ID) in DS are termed DS-ID pathways and are defined as those pathways with components and/or interacting proteins that include HSA21 proteins and one or more ID proteins, proteins known to be involved in ID from mutation analysis in human subjects. Pathway component data have been obtained from the curated pathway databases and ID proteins have been identified from the Online Mendelian Inheritance in Man database (OMIM) and the literature. Pathways were then extended by adding primary interaction data obtained from the curated protein interaction databases, filtered for co-expression and common cellular compartment. Extended pathways were scored based on the proportion of their components and interactions that are HSA21 and ID proteins. Inspection of the resulting set of DS-ID pathways showed the following: (i) few pathways include HSA21 proteins as components; rather DS-ID pathways are heavily impacted by interactions with HSA21 proteins; (ii) perturbations in nerve growth factor (NGF) and Sonic Hedgehog (SHH) signaling, observed in the Ts65Dn, are predicted from pathway associations of ID and HSA21 components and interactions; (iii) perturbations of similar significance are predicted in glucocorticoid, interferon, insulin and ErbB signaling, and apoptosis pathways;. (iv) a small number of HSA21 proteins, including APP, TIAM1, ITSN1, SUMO3, ITGB2 and S100B, impact a large number of pathways; and (v) the majority of pathways, including those listed above, are influenced by proteins mapping throughout HSA21 and include those whose orthologs are not trisomic in the Ts65Dn, emphasizing the likelihood that the molecular basis of drug responses in the Ts65Dn will be different in human DS. All pathway data are available and searchable by pathway, protein or interaction protein name at bioc.tinyray.com (this was primarily hosted at gfuncpathdb.ucdenver.edu/iddrc/hsa21gdpw/home.htm). Any difficult experience or concern regarding the following issues with the website: biological data retrieval, development of data analysis methods, development of computational web model and Implementation of the web model and data analysis methods, should be directed by email to Thanh Le. Thank you for reading this article.


  • Xiaolu Sturgeon, Thanh Le, Md. Mahiuddin Ahmed and Katheleen Gardiner, 2012, Pathways to cognitive deficits in Down syndrome.
  • Thanh Le (2013) A Machine Learning approach for Gene Expression analysis and applications.
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