Abstract
<jats:p>Alzheimer’s disease (AD) represents one of the most complex and pressing challenges of modern medicine, particularly in the context of global population aging. Despite major advances in molecular biology, neuroimaging, and digital health, Alzheimer’s disease remains largely diagnosed at a symptomatic stage, when neurodegeneration is already advanced and therapeutic options are limited. Recent large-scale population studies using blood-based biomarkers reveal that biological Alzheimer’s disease pathology is far more prevalent than clinically diagnosed dementia, highlighting a long and actionable preclinical phase for prevention and early intervention. This chapter adopts a lifespan and longevity-medicine perspective, integrating classical pathophysiological mechanisms with emerging concepts in brain resilience, stress biology, intrinsic capacity, and preventive medicine. We review current and emerging diagnostic tools – including fluid, imaging, digital, and AI-supported biomarkers – key mechanisms of disease pathogenesis, and multimodal therapeutic strategies. Particular emphasis is placed on the transition from symptom-based diagnosis to biology-based staging, early intervention, and personalized, adaptive care pathways. We address the “digital health paradox,” emphasizing that effective deployment of digital biomarkers requires objective assessment of digital competence rather than reliance on patient self-report, given documented discrepancies in older populations. Finally, we propose a Seniors-Oriented Technology Acceptance Model (STAM) and co-creation strategies to support age-inclusive, ethically governed, and scalable clinical implementation. Together, these approaches aim to preserve brain healthspan, delay disease progression, and translate geroscience principles into routine clinical practice.</jats:p>