Abstract
Virtually any stressor that alters the cellular homeostatic state may result in an inflammatory response. As a critical component of innate immunity, inflammasomes play a prominent role in the inflammatory response. The information on inflammasome biology is rapidly growing, thus creating the need for structuring it into a model that can help visualize and enhance the understanding of underlying biological processes. Causal biological network (CBN) models provide predictive power for novel disease mechanisms and treatment outcomes. We assembled the available literature information on inflammasome activation into the CBN model and scored it with publicly available transcriptomic datasets that address viral infection of the lungs, osteo- and rheumatoid arthritis, psoriasis, and aging. The scoring inferred pathway activation leading to NLRP3 inflammasome activation in these diverse conditions, demonstrating that the CBN model provides a platform for interpreting transcriptomic data in the context of inflammasome activation.
Highlights
Inflammasome activation has been linked to viral, bacterial, and fungal infections [4,5,6] and autoinflammatory and autoimmune diseases such as gout and rheumatoid arthritis [7,8,9], as well as to other diverse conditions such as Alzheimer’s disease, atherosclerosis, aging, or obesity [10,11,12,13,14]
We assembled the available literature information on inflammasome activation into the Causal biological network (CBN) model and scored it with publicly available transcriptomic datasets that address viral infection of the lungs, osteo- and rheumatoid arthritis, psoriasis, and aging. e scoring inferred pathway activation leading to NLRP3 inflammasome activation in these diverse conditions, demonstrating that the CBN model provides a platform for interpreting transcriptomic data in the context of inflammasome activation
We curated scientific literature related to inflammasome activation from 55 research articles and compiled a network model with 297 nodes and 455 edges, which can be used to score the pathology of infections, diseases, treatments, and other conditions. e network model is centered on NLRP3 inflammasome activation, as it is the most studied and best characterized inflammasome
Summary
Inflammasome activation has been linked to viral, bacterial, and fungal infections [4,5,6] and autoinflammatory and autoimmune diseases such as gout and rheumatoid arthritis [7,8,9], as well as to other diverse conditions such as Alzheimer’s disease, atherosclerosis, aging, or obesity [10,11,12,13,14]. Compilation of the involved pathways in a network representation is a step toward comprehensive understanding of a system response Such a network approach is a valuable tool in network medicine, which takes into account how the regulated molecules interact with each other and how information flows along the multiple pathways that constitute a given biological process or pathology [26, 27]. From the RNA expression values in transcriptomic datasets, the activity levels of their regulating factors can be extrapolated and used to score the entities of network models [28] Such an approach creates a powerful explorative tool by combining literature-derived network models with billions of data points that are publicly available. Such an approach creates a powerful explorative tool by combining literature-derived network models with billions of data points that are publicly available. is methodology conforms to the 21st century paradigm for medical research, which shifts the research from animal tests to assessments in cells and tissues in the context of systems biology with the use of in silico tools [29, 30]
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