Alzheimer's disease: a clinical update on diagnosis and treatment

Alzheimer's disease (AD) is the leading cause of dementia, characterized by progressive cognitive and functional decline. As the population ages, the prevalence of AD is expected to increase significantly, imposing a growing burden on patients, caregivers, and healthcare systems. Advances in our understanding of AD pathophysiology and biomarker-based diagnosis have redefined clinical practice, introducing challenges in early detection, accurate diagnosis, and effective treatment.

Current AD diagnostic frameworks incorporate clinical assessment alongside biomarkers of amyloid and tau pathology, cerebrovascular contributions, and neurodegeneration. Imaging modalities and fluid biomarker analyses enable more precise diagnosis, although accessibility remains limited in many settings. Recent therapeutic advancements in the form of anti-amyloid monoclonal antibodies offer disease-modifying potential but are accompanied by implementation challenges, such as patient selection, monitoring for adverse events, and cost considerations.

Integrating biomarker testing into routine clinical practice requires a careful review of individual risks and benefits for each patient, balancing diagnostic accuracy with practical considerations like testing consequences, test availability, pretest probability, and patient preferences. Shared decision-making is pivotal when discussing treatment options, weighing potential clinical benefits against risks and the overall burden of care.

Enhancing the delivery of anti-amyloid antibodies and advancing research into tau-targeted therapies represent promising therapeutic avenues. Incorporating scalable, non-invasive biomarkers, e.g., plasma-based biomarkers, into clinical practice has the potential to transform diagnostic workflows, provided they are applied in appropriate clinical contexts. Bridging the gap between research innovations and real-world implementation will require coordinated, multidisciplinary collaboration across healthcare systems.