Mathematical and computational approaches in understanding the immunobiology of granulomatous diseases. Issue 12 (December 2018) - Magombedze, Gesham; Marino, Simeone
Abstract: A granuloma is a physical pathological structure that manifests when the host mounts an immune response to fend off pathogens/infections, immunological aberrations, irritants, inflammations and other foreign particles. It is an amalgamation of immune cells (lymphocytes, phagocytes (mostly macrophages and their derivatives) plasma cells, neutrophils and eosinophils), pathogens or foreign particles or irritants, fibroblasts, epithelioid cells and multi-nucleated giant cells. This well-organized dynamic structure form after an ingested pathogen or particle finds its way into tissues. The host will then mount a response to prevent the pathogen from replicating or the foreign particle from propagating inflammation. Multiple granulomas can form upon infection/invasion in a single host. The ensemble of these structures dictates the state of disease manifestation and end points, such as rapid, fulminant infections, chronic persistent states (both symptomatic and asymptomatic) or sterilization where the infection gets cleared and cure is established. Studying granuloma formation and how it shapes immune responses is an enigma, mainly because they develop at remote locations, which makes the acquisition of relevant biological readouts a nightmare. Therefore, researchers are resorting to the use of computational inference techniques as a gateway to gain more insights. Mathematical and computational modeling approaches have been used to elucidate the mechanisms driving granuloma formation, function of granulomas, and disease progression in these granulomatous diseases. However, the use of mathematical modeling to elaborately explain non-tuberculosis infections is still primal. The goals of this review are i) to review existing modeling studies describing the initiation, progression and development of different granulomatous diseases, and ii) to suggest how existing modeling approaches can be exploited to understand the immunobiology of granulomatous non-TB infections. Highlights: Immuno-biology for granulomatous diseases. Balance between arms of immune responses (Th1 and Th2) and the evolution. Application of mathematical/computational modeling to study biological systems. Mathematical modeling in the study of granulomatous diseases. Understanding the link between human microbiome and granulomatous diseases.