A biomedical knowledge graphing system to propose mechanistic hypotheses for real-world environmental health observations: cohort study and computer application



Knowledge graphs are a common form of knowledge representation in biomedicine and many other fields. We have developed an open system based on biomedical knowledge graphs called Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ROBOKOP consists of both a front-end user interface and a back-end knowledge graph. The ROBOKOP user interface allows users to ask questions and explore response subgraphs. Users can also ask questions via a direct Cypher query of the underlying knowledge graph, which currently contains around 6 million nodes or biomedical entities and 140 million edges or predicates describing the relationship between the nodes, taken from more of 30 organized data sources.


Our goal was to apply ROBOKOP to survey data on workplace exposures and immune-mediated diseases from the Environmental Polymorphism Registry (EPR) of the National Institute of Environmental Health Sciences.

Methods :

We analyzed data from the EPR survey and identified 45 associations between workplace chemical exposures and immune-mediated illnesses, as reported by study participants (n = 4574), with 20 significant associations at P <.05 after correcting for the false discovery rate. we then used robokop to validate associations by determining whether plausible connections exist within knowledge graph and propose biological mechanisms that could explain them serve as hypotheses further testing. highlight following three exemplary associations: carbon monoxide-multiple sclerosis ammonia-asthma isopropanol allergic disease.>


ROBOKOP successfully returned response sets for three queries that were posed in the context of the driving examples. The response sets included potential intermediary genes, as well as supporting evidence that could explain the associations observed.


We demonstrate the actual application of ROBOKOP to generate mechanistic hypotheses for associations between workplace chemical exposures and immune-mediated diseases. We expect ROBOKOP to find wide application in many biomedical fields and other scientific disciplines due to its generalizability, speed of discovery and generation of mechanistic hypotheses, and open nature.

Key words:

data mining; Discovery; generalizability; immune mediated disease; knowledge graph; representation of knowledge; open science.

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