Exposure disease model
The following figure depicts the three part progression of a proposed Exposure-disease model. Here you can see the upper ExO schema (Figure 1A), our adaptable exposure-disease model (Figure 1B), and an application of our model using an instance level example of chlorpyrifos residue ingestion on an apple (Figure 1C). Chlorpyrifos, an organophosphorus insecticide, is a common agricultural chemical used for production of produce and other crops within the US and beyond [1]. Chlorpyrifos has faced criticism previously for its potential impact on the human nervous system, and particularly for the risks it may post to children’s neurological development [2]. Based on reported literature of chlorpyrifos mechanisms, our model can be used to identify exposure sources, mechanisms, and associations with presenting disease and phenotypes. As seen in this figure, ExO describes an ‘exposure stimulus’ as ‘an agent, stimulus, activity, or event that causes stress or tension on an organism and interacts with an exposure_receptor during an exposure event’. A ‘exposure receptor’ is defined as ‘an entity (e.g., a human, human population, or a human organ) that interacts with an exposure stimulus during an exposure event’. An ‘exposure outcome’ is defined as ‘entity that results from the interaction between an exposure_receptor and an exposure stimulus during an exposure event’, and represents the negative or positive outcomes of having been exposed to the stimulus. It is important to recognize that it is the axioms encoded within the model that connect exposure information to a variety of knowledge that then allows the potential inference of a candidate stimulus or a predicted outcome in response to one.
Figure 1. Defining and populating the exposure semantic framework. All figure panels contain consistent model variables: the exposure event in green, the entity stimulating the exposure in blue, the organism or entity being exposed in yellow, and the resulting outcomes in purple. Within Figure 1C, an instance level exposure is included in a red panel to display the proposed integration of knowledge with data. Figure 1A. ExO upper ontology: ExO includes the central ‘exposure event’ as well as associated ‘exposure stimulus’, ‘exposure receptor’, and ‘exposure outcome’ elements. Granular exposures (e.g. exposure to chlorpyrifos) are modeled in ECTO, but leverage the upper ExO ontology. In ECTO, each element can be annotated with associated metadata. Figure 1B. Exposure-disease model: Utilizing ECTO ‘exposure event’ classes, our model can include a variety of exposure stimuli, mediums, routes, and outcomes due to the inherent ExO upper level modeling. Solid edges include direct relationships which can be modeled as a part of an exposure event, with dashed lines representing inferred relationships that are derived from the known direct relationships. This exposure-disease model offers a precomposed template for which to map documented relationships from the literature in order to support computational assessment of environmental health research findings. Figure 1C. Chlorpyrifos exposure instance example: The adaptable exposure-disease model can be used to coordinate instance level data with ontology knowledge, resulting in a translatable schema for environmental exposures. This example provides a multilayer exposure process for an individual who ingests an apple after it is exposed to chlorpyrifos, coordinated with the known phenotype and disease presentation in the individual. Documented relationships are seen with solid lines and inferred relationships are seen in dashed lines.
By documenting not only food items that are the mediums for the exposure to chlorpyrifos, but also including the mechanism of action, known phenotypes, and disease states, our example model of chlorpyrifos exposure offers access points in which further information can be inferred. For example, if another chemical served as an acetylcholinesterase inhibitor within humans, by inclusion of that chemical exposure and known regulatory activity, one could infer that the second chemical exposure may also be related to cognitive disorders, or that the chemicals composition may be similar to chlorpyrifos.
To view a prototype branch that includes the logical axioms within Figure 1C, please see the following link. https://github.com/EnvironmentOntology/environmental-exposure-ontology/tree/ICBO_prototype
References:
- Chlorpyrifos. [cited 30 Apr 2021]. Available: https://www.panna.org/resources/chlorpyrifos-facts
- Burke RD, Todd SW, Lumsden E, Mullins RJ, Mamczarz J, Fawcett WP, et al. Developmental neurotoxicity of the organophosphorus insecticide chlorpyrifos: from clinical findings to preclinical models and potential mechanisms. J Neurochem. 2017;142 Suppl 2: 162–177.