Network-guided study of environmental factors for rare diseases
Creators: name: Ozisik, Ozan
name: Ehrhart, Friederike
name: Carta, Claudio
name: Cellai, Laura
name: Martens, Marvin
name: Mina, Eleni
name: Wolstencroft, Katherine
name: Zammit, Alan
name: Jumamurat R. Bayjanov
name: Peter A.C. 'T Hoen
name: WF-Environment EJP-RD
name: Evelo, Chris
name: Mantovani, Alberto
name: Baudot, Anaïs
Publisher: name: F1000 Research Limited
Year: 2020

description: We assembled a work focus in the European Joint Programme on Rare Diseases (EJP-RD) to study the role of environmental (non-genetic) factors in rare diseases. The goal is to widen our knowledge on the impact of different exposures, namely drugs, toxic compounds, and nutrition on rare disease etiology and pathophysiology, towards possible prevention, better diagnosis and identification of therapeutic paths.<br>To achieve this goal, we are leveraging pathways built from expert knowledge and are available for instance in the Wikipathway Rare Disease portal (http://raredisease.wikipathways.org/) and networks constructed from multi-omics datasets of rare diseases. These integrated network graphs are constructed with flexible data representation. We are developing different methodologies to use these graphs as scaffolds for further integration of data relative to environmental factors. Our protocols are based on graph-extension algorithms, in which bipartite interactions, such as drug-target interactions are added to the networks of interest. But we also develop tools to measure the overlaps or cross-overs between different graphs, as well as tools searching for active subnetworks or pathway enrichments. Overall, our algorithms are applied specifically to the study of different environmental factors:<br>Drugs: Disease-associated graphs are extended with drugs that target protein nodes in the networks, using, for instance, the CyTargetLinker Cytoscape App (http://apps.cytoscape.org/apps/cytargetlinker) when using DrugBank (https://www.drugbank.ca/) or ChEBI (https://www.ebi.ac.uk/chebi/) drug-target information. This will allow prioritizing candidate drugs targeting disease-associated processes, and explore drug repurposing opportunities.<br>Toxicology: We are developing similar graph-extension approaches to add toxic compounds and their targeted proteins, exploring datasets from ongoing toxicological platforms, such as OpenRiskNet (https://openrisknet.org/). We are also measuring the overlaps between rare disease and adverse outcome pathways using platforms such as the AOP-Wiki (https://aopwiki.org/). This is expected to reveal toxic compounds that can affect the evolution of the disease upon exposure.<br>Nutrients: Here also, the goal is to evaluate and extend disease-related graphs, in particular, metabolic networks, to leverage micronutrient-involving interaction data.<br>Overall, the work focus, by using state-of-the-art network methodologies and bioinformatics infrastructure, aims to increase the usefulness of disease-associated networks and pathways in order to better understand the cross-talk between genetic and environmental factors. Thus, to achieve better healthcare of rare diseases from prevention to diagnosis and therapy.