Aging-US: Alzheimer’s disease as a systems network disorder
11-13-2020Aging-US recently published "Alzheimer’s disease as a systems network disorder: chronic stress/dyshomeostasis, innate immunity, and genetics" which reported that ineffective results of clinical trials of over 200 anti-Alzheimer's drug candidates, with a 99.6% attrition rate, suggest that the current paradigm of Alzheimer's disease may be incomplete, necessitating exploration of alternative and complementary frameworks.
Results of this analysis suggest that Alzheimer’s may not be a brain disease but a progressive system-level network disorder, which is driven by chronic network stress and dyshomeostasis.
The latter can be caused by various endogenous and exogenous factors, such as chronic inflammatory conditions, infections, vascular dysfunction, head trauma, environmental toxicity, and immune disorders.
Whether originating in the brain or on the periphery, chronic stress, toxicity, and inflammation are communicated to the central nervous system via humoral and neural routes, preferentially targeting high-centrality regulatory nodes and circuits of the nervous system, and eventually manifesting as a neurodegenerative CNS disease.
In this report, the Aging-US authors outline an alternative perspective on AD as a systems network disorder and discuss biochemical and genetic evidence suggesting the central role of chronic tissue injury/dyshomeostasis, innate immune reactivity, and inflammation in the etiopathobiology of Alzheimer’s disease.
"The Aging-US authors outline an alternative perspective on AD as a systems network disorder"
Dr. Alexei Kurakinn and Dr. Dale E. Bredesen said, "Alzheimer’s disease has become a global epidemic, rapidly advancing in the last decade to become the 5th leading cause of death globally and the 3rd leading cause of death in high-income countries."
In brief, a multimodal clinical profile of a patient is used by a human expert to generate a representative set of terms that characterize the disease configuration of the patient.
The generated set serves as a query to search research literature and databases for information blocks with highest densities of query terms. Selected and rank-ordered blocks of information are analyzed by an expert to identify a parsimonious set of concepts that interconnect cliques of search terms. The identified concepts are then used as new or additional query terms in the next iteration to identify higher level connectors, until all search terms become assimilated within a parsimoniously interconnected network.
Figure 2. The network of genetic polymorphisms associated with Alzheimer’s disease. Most of the genetic polymorphisms associated with Alzheimer’s disease can be broadly assigned to a small number of overlapping functional groups and interconnected via such terms as tissue damage and repair, innate immune activation, inflammation, wound clearance, and detoxification, without specifying whether these processes occur in the CNS or on the periphery.
Analysis of the generated disease network by a human expert allows for formulation of de novo hypotheses.
Although searches are non-exhaustive and hypothesis generation is inevitably biased by idiosyncratic expertise and choices of human expert, the relative worth of a generated hypothesis is measured in terms of its practical utility by testing hypothesis’ predictions empirically and/or in silico.
The implications of the proposed systemic nature of Alzheimer’s disease for treatment and prevention of cognitive decline are briefly discussed.
The Kurakinn/Bredesen Research Team concluded in their Aging-US Research Paper that the promising results of an integrative, systemic, precision medicine approach to treating Alzheimer’s disease suggests that evaluating and addressing the individual organism as a whole rather than focusing exclusively on an apparently failing part may represent a promising strategy to approach other complex chronic multifactorial disorders, which warrants further exploration and development.
Full Text - https://doi.org/10.18632/aging.103883
Correspondence to: Alexei Kurakin email: akurakin@mednet.ucla.edu and Dale E. Bredesen email: dbredesen@mednet.ucla.edu
Keywords: Alzheimer’s disease, neurodegeneration, complex chronic disorder, network biology, systems biology
About Aging-US:
Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.
Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed Central, Web of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).
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