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Introduction to Alzheimer's Disease and Biomarkers
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Author(s): Kanika Gupta (Shri R.K. Patni Girls' College, Kishangarh, India)
Copyright: 2025
Pages: 28
Source title:
Deep Generative Models for Integrative Analysis of Alzheimer's Biomarkers
Source Author(s)/Editor(s): Abhishek Kumar (Chandigarh University, India), S. Rakesh Kumar (GITAM University (Deemed), India), N. Gayathri (GITAM University (Deemed), India), R. Srivel (Adhiparasakthi Engineering College, India)and Dhaya C. (Adhiparasakthi Engineering College, India)
DOI: 10.4018/979-8-3693-6442-0.ch004
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Abstract
Alzheimer's disease, the leading cause of dementia affecting 50-60% of cases globally, manifests initially with cognitive impairments and progresses with neurodegeneration, brain inflammation, and atrophy. Early diagnosis and treatment rely on identifying biomarkers, which can be invasive or non-invasive, categorized as diagnostic, prognostic, predictive, pharmacodynamic/response, susceptibility/risk, monitoring, and safety biomarkers. They include amyloid Aβ plaques, Brain derived Neurotrophic factor (BDNF), pro-NGF, tau protein (t-protein) neurofibrillary tangles, apolipoprotein, and novel markers in CSF, blood, urine, and lipid profiles. Challenges encompass lumbar puncture, multifactorial progression, early biomarker inexplicability, and pathophysiological understanding gaps.Advancement of Theranostics approach is explained in AD patients. Later in this study, we analyzed these biomarkers using integrative approaches of deep generative models focusing on detecting anomalies in brain structure, biological functions, abnormal metabolite concentrations, and misfolded proteins.
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