Journal
DIAGNOSTICS
Volume 12, Issue 12, Pages -Publisher
MDPI
DOI: 10.3390/diagnostics12122975
Keywords
Alzheimer's disease (AD); diagnostic biomarkers; drug prioritization; epigenetics; network biology; multi-target drug ligands (MTDLs); disease pathways
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Funding
- Deanship of Scientific Research at Al-Zaytoonah University of Jordan
- [2020-2019/17/03]
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Alzheimer's disease is a complex neurodegenerative disease without a cure. Epigenetic factors have been found to be implicated in the disease pathogenesis and may serve as promising diagnostic biomarkers. Network biology approaches are seen as effective tools for studying the disease and discovering new treatments.
Alzheimer's disease (AD) is a polygenic multifactorial neurodegenerative disease that, after decades of research and development, is still without a cure. There are some symptomatic treatments to manage the psychological symptoms but none of these drugs can halt disease progression. Additionally, over the last few years, many anti-AD drugs failed in late stages of clinical trials and many hypotheses surfaced to explain these failures, including the lack of clear understanding of disease pathways and processes. Recently, different epigenetic factors have been implicated in AD pathogenesis; thus, they could serve as promising AD diagnostic biomarkers. Additionally, network biology approaches have been suggested as effective tools to study AD on the systems level and discover multi-target-directed ligands as novel treatments for AD. Herein, we provide a comprehensive review on Alzheimer's disease pathophysiology to provide a better understanding of disease pathogenesis hypotheses and decipher the role of genetic and epigenetic factors in disease development and progression. We also provide an overview of disease biomarkers and drug targets and suggest network biology approaches as new tools for identifying novel biomarkers and drugs. We also posit that the application of machine learning and artificial intelligence to mining Alzheimer's disease multi-omics data will facilitate drug and biomarker discovery efforts and lead to effective individualized anti-Alzheimer treatments.
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