Systems-based medicine approaches to understand and treat complex diseases. The example of multiple sclerosis.
Systems medicine is an emerging concept that acknowledges the complexity of a multitude of non-linear interactions among molecular and physiological variables. Under this new paradigm, rather than a collection of symptoms, diseases are seen as the product of deviations from a robust steady state compatible with life. This concept requires the incorporation of mathematics and physics to the more classical arsenal of physiology and molecular biology with which physicians are trained today. This review explores the diverse types of information that can be accumulated towards the understanding of multiple sclerosis (MS), a complex autoimmune disease that targets the central nervous system (CNS). The challenge of data integration and modeling of dynamical systems is discussed in the context of disease susceptibility and response to treatment. A theoretical framework that supports the use of combination therapy is also presented.
Baranzini
Sergio E
SE
Department of Neurology, School of Medicine, University of California, San Francisco, 513 Parnassus Avenue Room S-256, San Francisco, CA 94143-0435, USA. sebaran@cgl.ucsf.edu
D000818:Animals; D019295:Computational Biology / Q000379:methods / Q000639:trends; D020022:Genetic Predisposition to Disease; D006801:Humans; D008962:Models, Theoretical; D009103:Multiple Sclerosis / Q000503:physiopathology*; D049490:Systems Biology / Q000379:methods / Q000639:trends