Noise in multiple sclerosis: unwanted and necessary

Area of Science:

• Cell biology
• Nonlinear dynamics
• Genetics

Background:

• Deterministic models are insufficient for explaining multiple sclerosis (MS) etiology.
• Stochastic phenomena (random events) are increasingly recognized as potential contributors to MS pathogenesis.
• The sources and mechanisms of stochasticity in disease development remain largely unexplored.

Purpose of the Study:

• To explore the role of stochastic phenomena in the context of multiple sclerosis (MS) pathogenesis.
• To propose a framework for incorporating nondeterministic processes into disease biology.
• To highlight the significance of stochastic gene expression in phenotypic variation.

Main Methods:

• Drawing analogies between nonlinear physics and cell biology to explain the impact of small-scale perturbations.
• Reviewing evidence on stochastic gene expression as a driver of phenotypic variation.
• Describing novel methodologies for studying stochastic phenomena in patients.

Main Results:

• Small-scale random perturbations in biological systems can influence large-scale phenomena, including cell function.
• Stochastic gene expression, or "noise," is a significant contributor to phenotypic variation.
• New methods enable unprecedented study of these phenomena in MS patients.

Conclusions:

• Stochastic processes are crucial for a comprehensive understanding of multiple sclerosis (MS) pathogenesis.
• Investigating gene expression noise in MS patients can reveal new therapeutic targets.
• A framework incorporating stochasticity is needed to advance MS research and treatment.