A systematic review of Alzheimer's disease: exploring genetic and environmental risk factors, biomarkers, and future pharmacotherapy for cognitive decline and neurodegeneration
DOI:
https://doi.org/10.69857/joapr.v13i3.929Keywords:
Cholinergic neurodegeneration, Memory impairment, Synaptic dysfunction, Tau protein aggregation, Amyloid-beta pathology, NeuroinflammationAbstract
Background: Alzheimer's disease (AD) is the most prevalent form of dementia, affecting millions globally through progressive cognitive decline caused by neurodegeneration in cholinergic brain regions. Aging is the primary risk factor, but metabolic, genetic, and environmental influences, including inflammation and vascular dysfunction, significantly contribute to disease onset and progression. Methodology: This comprehensive review evaluates diagnostic methods, biomarkers, and genetic and environmental risk factors associated with AD, focusing on recent advancements (2022–2025). The study selection process prioritized clinical trials, systematic reviews, and meta-analyses related to AD pathophysiology, diagnostics, and therapeutic interventions while excluding research with ambiguous findings or lacking methodological rigor. A PRISMA flowchart illustrates the study selection process, ensuring transparency. Pharmaceutical and non-pharmacological interventions, along with multi-target therapeutic strategies, were critically analyzed. Results and Discussion: AD pathology is driven by amyloid-beta plaques and tau tangles, leading to synaptic dysfunction and neurodegeneration. Current treatments, including acetylcholinesterase inhibitors and NMDA receptor antagonists, offer symptomatic relief but are ineffective in halting disease progression. Emerging therapies such as monoclonal antibodies (Lecanemab, Donanemab), tau inhibitors, and neuroinflammation modulators show potential in slowing cognitive decline and preserving neuronal health. Advances in biomarker-based diagnostics (e.g., p-tau217) and AI-powered precision medicine have improved early detection and personalized treatment strategies, though challenges in cost, accessibility, and regulatory approval persist. Conclusion: A multisystem approach combining pharmacotherapy, biomarker-driven diagnostics, and AI-assisted personalized medicine is essential to optimize AD treatment effectiveness. Future research should focus on developing innovative, multidisciplinary treatment strategies to enhance patient outcomes and quality of life.
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