Lindley Darden (University of Maryland, College Park), Kunal Kundu (University of Maryland, College Park), Lipika Ray (University of Maryland, College Park), John Moult (University of Maryland, College Park)
The "big data" revolution is leading to new insights into human genetic disease mechanisms. But the many results are scattered throughout the biomedical literature and represented in many different ways, including free text and cartoons. Thus, a standard framework is needed to represent disease mechanisms. This poster presents a conceptual framework, utilizing a newly developed analysis of disease mechanisms (Darden et al.2018).
The new mechanistic philosophy of science characterizes the components of mechanisms: entities and activities. Adapting this for genetic disease mechanisms yields the categories of "substate perturbations" plus the drivers of changes from one substate perturbation to the next, called "mechanism modules" (activities or group of entities and activities). The framework shows the organized stages of a genetic disease mechanism from a beginning substate perturbation (e.g., a gene mutation or chromosomal aberration) to the disease phenotype. It depicts environmental influences as well. It aids in finding possible sites for therapeutic intervention. It shows a schema builder's view of well-established components as well as uncertainty, ignorance, and ambiguity, based on evidence from the biomedical literature. Its abstract scaffolding directs the schema builder to fill in the key components of the disease mechanism, while the unknown components serve to direct future experimental work to remove sketchiness and provide additional evidence for its components.
The poster will show progressively less abstract and more complete diagrams that represent the framework, as sketches become schemas. When a perturbation is correlated with a disease phenotype, it suggests searching for an unknown mechanism connecting them. The entire mechanism is a black box to be filled. Most abstractly and most generally, a disease mechanism is depicted by a series of substate perturbations (SSPs, rectangles) connected by lines labeled with the mechanism modules (MMs, ovals) that produce the changes from perturbation to perturbation. Optional additions include environmental inputs (cloud-like icons) and possible sites for therapeutic intervention (blue octagons). Telescoping of sets of steps into a single mechanism module increases focus on disease-relevant steps; e.g., transcription and translation telescope into the MM labeled "protein synthesis." The default organization is linear, from a beginning genetic variant to the ending disease phenotype, but it can include branches, joins, and feedback loops, as needed. Black ovals show missing components in the series of steps. The strength of evidence is indicated by color-coding, with green showing high confidence, orange medium, to red lowest. Branches labeled "and/or" show ambiguity about the path followed after a given step. Along with the general abstract diagrams, the poster will include detailed diagrams of specific disease mechanisms, such as cystic fibrosis.
In addition to providing an integrated representational framework for disease mechanisms, these visual schemas facilitate prioritization of future experiments, identification of new therapeutic targets, ease of communication between researchers, detection of epistatic interactions between multiple schemas in complex trait diseases, and personalized therapy choice.
