Blood-based biomarkers such as p-tau217, p-tau181, neurofilament light chain, and amyloid proteins are showing strong accuracy in detecting Alzheimer’s disease and related dementias years before symptoms appear. These tests could allow for earlier, more accessible diagnosis compared to brain imaging or spinal taps.

A newly developed blood test measuring MTBR-tau243 has demonstrated promise in distinguishing Alzheimer’s disease from other forms of cognitive impairment, giving clinicians a clearer tool to guide targeted therapies.

Researchers at Stanford have identified a “resilience signature” in cerebrospinal fluid, consisting of protein patterns that may predict not only who will develop dementia but also how quickly the disease will progress.

Advances in imaging technology now allow detection of living synapses on brain scans, providing insights into how neuronal connections deteriorate in early dementia.

Vascular contributions to cognitive decline are gaining attention, with studies showing how impaired blood flow and waste-clearance systems in the brain contribute to vascular dementia.

On the therapeutic front, experimental monoclonal antibodies such as posdinemab are being developed to target phosphorylated tau, while next-generation antibodies like trontinemab are engineered with “BrainShuttle” technology to cross the blood–brain barrier more effectively.

Artificial intelligence and machine learning approaches are increasingly being used to combine neuroimaging, genetic, and biomolecular data, enabling more accurate classification of dementia subtypes.

Large lifestyle-intervention trials, such as the POINTER study in the U.S., are showing that changes in diet, physical activity, and social engagement can improve cognitive performance and potentially delay the onset of dementia in at-risk populations.