Unraveling the mechanistic complexity of Alzheimer's disease through systems biology

Jennifer L Rollo; Nahid Banihashemi; Fatemeh Vafaee; John W Crawford; Zdenka Kuncic; R M Damian Holsinger

doi:10.1016/j.jalz.2015.10.010

Unraveling the mechanistic complexity of Alzheimer's disease through systems biology

Alzheimers Dement. 2016 Jun;12(6):708-18. doi: 10.1016/j.jalz.2015.10.010. Epub 2015 Dec 17.

Authors

Jennifer L Rollo¹, Nahid Banihashemi², Fatemeh Vafaee³, John W Crawford⁴, Zdenka Kuncic⁵, R M Damian Holsinger⁶

Affiliations

¹ Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; Laboratory of Molecular Neuroscience, Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia; Department of Molecular Neuroscience, Institute of Neurology, University College of London, London, UK. Electronic address: [email protected].
² Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia.
³ Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; School of Mathematics and Statistics, University of Sydney, Sydney, NSW, Australia.
⁴ Rothamsted Research, Harpenden, UK.
⁵ Charles Perkins Centre, The University of Sydney, Sydney, NSW, Australia; School of Physics, The University of Sydney, Sydney, NSW, Australia.
⁶ Laboratory of Molecular Neuroscience, Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia; Discipline of Biomedical Science, School of Medical Sciences, Sydney Medical School, The University of Sydney, Lidcombe, NSW, Australia.

PMID: 26703952
DOI: 10.1016/j.jalz.2015.10.010

Abstract

Alzheimer's disease (AD) is a complex, multifactorial disease that has reached global epidemic proportions. The challenge remains to fully identify its underlying molecular mechanisms that will enable development of accurate diagnostic tools and therapeutics. Conventional experimental approaches that target individual or small sets of genes or proteins may overlook important parts of the regulatory network, which limits the opportunity of identifying multitarget interventions. Our perspective is that a more complete insight into potential treatment options for AD will only be made possible through studying the disease as a system. We propose an integrative systems biology approach that we argue has been largely untapped in AD research. We present key publications to demonstrate the value of this approach and discuss the potential to intensify research efforts in AD through transdisciplinary collaboration. We highlight challenges and opportunities for significant breakthroughs that could be made if a systems biology approach is fully exploited.

Keywords: Complex systems; Computational modeling; Holistic; Integrative; Risk genes; Transdisciplinary research.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Alzheimer Disease / diagnosis*
Alzheimer Disease / genetics
Computer Simulation
Humans
Models, Biological*
Protein Interaction Maps
Systems Biology / methods*