Abstract
The conditions used to describe the presence of an immune disease are often represented by interaction graphs. These informative, but intricate structures are susceptible to perturbations at different levels. The mode in which that perturbation occurs is still of utmost importance in areas such as cell reprogramming and therapeutics models. In this sense, module identification can be useful to well characterise the global graph architecture. To help us with this identification, we perform topological overlap-related measures. Thanks to these measures, the location of highly disease-specific module regulators is possible. Such regulators can perturb other nodes, potentially causing the entire system to change behaviour or collapse. We provide a geometric framework explaining such situations in the context of inflammatory bowel diseases (IBD). IBD are severe chronic disorders of the gastrointestinal tract whose incidence is dramatically increasing worldwide. Our approach models different IBD status as Riemannian manifolds defined by the graph Laplacian of two high throughput proteome screenings. It also identifies module regulators as singularities within the manifolds (the so-called singular manifolds). Furthermore, it reinterprets the characteristic nonlinear dynamics of IBD as compensatory responses to perturbations on those singularities. Then, particular reconfigurations of the immune system could make the disease status move towards an innocuous target state.
Highlights
The conditions used to describe the presence of an immune disease are often represented by interaction graphs
The set composed by the proteins STAT1, AZU1, CD38 or NNMT in ulcerative colitis (UC) or DEFA1, IGHM, PGLYRP1 and ERAP2 in Crohn’s disease (CD) are robustly associated with the status of the disease
It is worth mentioning that those proteins more expressed in the quiescent than in the active status such as SYK or IGKV2-30 are mainly identified during the CD progression (Fig. S6)
Summary
The conditions used to describe the presence of an immune disease are often represented by interaction graphs. We lay emphasis on the behaviour of the graph Laplacians corresponding to points at or near singularities, where different transitions of disease come together This scenario enables the identification of potential drug targets in a protein-coexpression graph of IBD, accounts for the nonlinear dynamics inherent to IBD evolution and opens the door to its eventual regression to a controlled trajectory[8,9,10]. Overall, this manuscript envisages providing clinicians with useful molecular hypotheses of disease activity status prior to making any decision on the newest course of the treatment of individual patients in IBD. Our systemic approach could facilitate and accelerate drug discovery in health-care system
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
