Network location and clustering of genetic mutations determine chronicity in a stylized model of genetic diseases

TL;DR

This paper presents a minimal network model linking genetic mutations and disease chronicity, revealing how network topology and mutation location influence disease severity and type.

Contribution

It introduces a stylized network model connecting genetic mutations, network topology, and disease chronicity, offering new insights into disease mechanisms.

Findings

Network topology affects disease severity.

Mutation location influences disease chronicity.

Model distinguishes between chronic and acute disease states.

Abstract

In a highly simplified view, a disease can be seen as the phenotype emerging from the interplay of genetic predisposition and fluctuating environmental stimuli. We formalize this situation in a minimal model, where a network (representing cellular regulation) serves as an interface between an input layer (representing environment) and an output layer (representing functional phenotype). Genetic predisposition for a disease is represented as a loss of function of some network nodes. Reduced, but non-zero, output indicates disease. The simplicity of this genetic disease model and its deep relationship to percolation theory allows us to understand the interplay between disease, network topology and the location and clusters of affected network nodes. We find that our model generates two different characteristics of diseases, which can be interpreted as chronic and acute diseases. In its stylized form, our model provides a new view on the relationship between genetic mutations and the type and severity of a disease.