Early Detection of Alzheimer’s Disease
Biological and Technological Advances
- 1st Edition - March 26, 2025
- Imprint: Academic Press
- Editor: Dennis Chan
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 2 4 0 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 2 4 1 - 6
Early Detection of Alzheimer’s Disease: Biological and Technological Advances aims to introduce to a wide audience the high global priority problem of detecting AD prior to dement… Read more
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Request a sales quoteEarly Detection of Alzheimer’s Disease: Biological and Technological Advances aims to introduce to a wide audience the high global priority problem of detecting AD prior to dementia onset. According to the Alzheimer’s Association, 5.8 million Americans are living with Alzheimer’s and care costs will cost the nation approximately $290 billion (2019 Alzheimer’s Disease Facts and Figures). With the failure of recent AD drug trials, many hypothesize that by the time symptoms appear, it is too late to be treated. Early detection can offer benefits such as more choice of medications, ability to participate in clinical trials, more time for family and for care planning. This book outlines potential solutions to the above problem using opportunities arising from the technology revolution, advances in neuroscience, and molecular biology. Most importantly, it discusses a paradigm shift from a reactive to a proactive diagnostic approach, aiming to detect disease before occurrence of symptoms. Topics covered include the use of sensing technologies (e.g. smartphones, smartwatches, Internet of Things) to detect early disease-related changes, the application of data science (machine learning/AI) to extract otherwise invisible disease features from these datasets and the potential to personalize diagnosis based on tracking changes in individual behaviours. Advances in blood-based biomarkers, brain imaging, and the potential for early diagnosis to aid interventions (lifestyle, dietary, pharmacological) to delay future development of dementia are also discussed.
- Outlines the importance of early diagnosis of Alzheimer’s Disease
- Helps readers understand the limitations of current clinical approaches and the need for a paradigmatic shift in diagnostic practice
- Discusses the potential role of technology in clinical practice using machine learning and artificial intelligence and the potential to personize diagnosis and treatment
Neuroscientists, neurologists, psychiatrists and nurse practitioners focused on AD
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- Chapter 1. Introduction
- Chapter 2. A century of Alzheimer's disease: Merging neuropathology with in vivo biomarkers
- Overview
- The modern beginning of “Alzheimer's disease”
- The era of clinical-pathological correlation
- The rise of genetics and the molecular biology of AD
- Challenges to the status quo
- The advent of biomarkers
- The research framework and a biological definition of AD
- Challenges to the research framework
- With a view to the future
- Chapter 3. Early Alzheimer’s disease: Clinical overview
- Alzheimer's disease pathology
- Early Alzheimer’s disease pathology
- Amyloid-beta
- Tau
- Co-pathology
- The syndrome of mild cognitive impairment
- Subjective cognitive decline
- Mild behavioral impairment
- Sub-classification mild cognitive impairment
- Conversion to dementia
- Management of mild cognitive impairment
- Clinical assessment
- Treatment
- Pharmacological
- Non-pharmacological
- Chapter 4. The need for early diagnosis—Clinical, societal and health economic drivers
- Epidemiology of dementia
- The aging population – prevalence and incidence of dementia and dementia subtypes
- Global time trends and inequalities in dementia prevalence and incidence
- Risk factors
- Dementia costs
- Access to diagnosis
- Future perspectives
- Conclusion
- Chapter 5. An overview of current diagnostic strategies
- Clinical assessment
- Neuropsychological testing
- Screening tools
- Cognitive domains testing
- Functional assessment instruments
- Diagnostic tools to support clinical diagnosis
- Cerebrospinal fluid
- Magnetic Resonance Imaging
- Positron emission tomography imaging
- Conclusions
- Novel approaches to diagnosis
- Chapter 6a. Opportunities arising from the tech revolution
- Introduction
- Digital testing
- App-based active testing
- Passive sensing
- Big data
- Machine learning
- Personalized diagnostics
- Risks associated with usage of digital tools
- Conclusions
- Chapter 6b. Advances in imaging
- Neurodegeneration and MRI
- Reserve and resilience
- Brain reserve
- Cognitive reserve
- Structural traits
- Synaptic dysfunction
- Cerebrovascular imaging
- Time of flight (TOF) imaging
- Perfusion and permeability imaging
- Glymphatic imaging
- Perivascular spaces
- Inferior frontal sulcal hyperintensities
- White matter hyperintensities
- Summary
- Chapter 6c. Advances in fluid-based biomarkers
- Introduction
- Fluid biomarkers for Aβ pathology
- Biomarkers for tau pathology
- Fluid biomarkers for neurodegeneration
- From research tools to clinical implementation
- Limitations of fluid-based biomarkers
- Biomarkers for AD—how can they be used in the most effective manner now that we have approved disease-modifying therapies?
- Chapter 6d. Advances in cognitive testing
- Novel cognitive tests sensitive to early Alzheimer's disease
- Progression of AD pathology and the functional architecture of episodic memory and spatial navigation
- Object memory
- Feature binding and associative memory
- Spatial memory and navigation
- Comparison to current clinical standards
- Digital cognitive assessments in Alzheimer's disease
- In-clinic supervised digital cognitive assessments using tablets and personal computers
- Remote unsupervised assessments using mobile devices in the home environment
- High-frequency assessments to increase the diagnostic signal
- Repeated assessments and novel test regimes
- Practice effects
- Long-term memory and forgetting
- Need for validation of novel digital assessments
- Other approaches to infer cognitive status
- Challenges for the new approach
- Chapter 7a. Ethical challenges associated with the early detection of Alzheimer's disease
- Introduction
- Early what?
- The right to know and the consequences of early detection for the individual
- The value of knowing (and knowing what)
- The potential harms of predictive information
- The social consequences of early detection
- Stigma and discrimination
- Justice and equity considerations
- The future of early detection
- Early detection and genetic risk
- Expanding early detection and screening
- Conclusion
- Chapter 7b. Privacy
- Introduction
- Privacy issues
- Types of adversaries
- Privacy attacks and mitigation techniques
- Re-identification attack—anonymization frameworks
- Statistical inference attack
- Privacy leaks in apps
- Other privacy preserving systems
- Conclusion and future directions
- An eye to the future
- Chapter 8a(i). Clinical trials
- Introduction
- Early disease identification and the predictive value of biomarkers
- A shift from late-stage clinical presentation to early disease detection
- The Alzheimer's disease continuum
- The neuropathology of Alzheimer's disease
- Methods for investigating Alzheimer's disease pathology
- Genetics
- Conclusion
- Current drugs development and past successes/failures
- Symptomatic treatments: Past, present and future
- Cognition and everyday function
- Acetylcholinesterase inhibitors
- NMDA receptor antagonist
- α7 nicotinic receptor agonists and modulators
- MAO-B inhibitors
- 11β-HSD1 inhibitors
- Disease modifying treatments: Past, present and future
- Treatments targeting amyloid
- Treatments targeting tau
- Treatments targeting other biomarkers
- Future directions e.g., novel outcome measures
- Measuring treatment success
- Clinical meaningfulness in Alzheimer's disease outcomes
- Electronic person specific outcome measure (ePSOM) development program
- Computerized assessment methods
- Conclusion
- Clinical trials designs, considerations, major initiatives
- Randomized control trials
- Randomized control trials
- Database discoveries
- Platform trials
- Stratified medicine
- Conclusion
- Chapter 8a(ii). Non-pharmacological interventions
- Overview of risk and protective factors
- Identification of “at risk” individuals
- Non-pharmacological management strategies
- Lifestyle interventions
- Diet
- Exercise
- Multi-domain interventions
- Psychological symptoms
- Sleep
- Hearing impairment
- Cognitive training/stimulation
- Role of health and care professionals
- Conclusions
- Funding sources
- Chapter 8b. Next generation technologies for diagnosis
- Introduction
- Advancing current approaches
- Imaging
- Optical markers
- Behavioral markers
- Virtual and augmented reality markers
- Digital biomarkers
- Artificial Intelligence
- Direct brain technologies
- What do we want?
- Index
- Edition: 1
- Published: March 26, 2025
- Imprint: Academic Press
- No. of pages: 308
- Language: English
- Paperback ISBN: 9780128222409
- eBook ISBN: 9780128222416
DC
Dennis Chan
Dr. Chan, PhD MD FRCP is an academic neurologist with a special interest in the diagnosis of Alzheimer’s disease prior to the onset of dementia. He holds dual research doctorates in basic and clinical neuroscience. His NHS practice is based at Addenbrooke’s Hospital, Cambridge, where he undertakes clinics in general neurology, dementia and mild cognitive impairment. His research focuses on identifying alterations in the function of the entorhinal cortex (EC) and hippocampus in early Alzheimer's disease (AD), with the ultimate aim of diagnosing AD prior to symptom onset.
Affiliations and expertise
Consultant Neurologist, Cambridge and Peterborough NHS Foundation Trust Hononary Associate Professor, University College London, London, UKRead Early Detection of Alzheimer’s Disease on ScienceDirect