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Unraveling the mechanistic complexity of Alzheimer's disease through systems biology
Author(s) -
Rollo Jennifer L.,
Banihashemi Nahid,
Vafaee Fatemeh,
Crawford John W.,
Kuncic Zdenka,
Holsinger R.M. Damian
Publication year - 2016
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2015.10.010
Subject(s) - systems biology , disease , perspective (graphical) , computational biology , key (lock) , value (mathematics) , data science , biology , computer science , neuroscience , risk analysis (engineering) , medicine , artificial intelligence , ecology , pathology , machine learning
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.