Accessible biomarkers for early stage Alzheimer’s disease

Dementia affects an estimated 353,800 Australians, with up to 80% diagnosed with Alzheimer’s disease (AD). Newly developed anti-amyloid drugs are set to revolutionise the treatment of AD. These are likely to have the most significant impact at the earliest stages of disease. Therefore, there is an urgent need for early-stage biomarkers that are affordable, accessible, and scalable.

To investigate genetic risk prediction and biomarkers for early-stage Alzheimer’s disease, including the combination of traditional and digital biomarkers, which opens up opportunities for simple, accurate, and effective screening to identify early-stage AD.

The student will build on our current work in PISA (the Prospective Study of Aging, Genes, Brain, and Behaviour) in this data analysis project (dry lab). They will test the integration of genetic risk prediction, blood-based protein biomarkers, and digital biomarkers, such as online cognitive testing, speech analysis and hand movement patterns. Predictive algorithms will be developed using statistical and machine-learning approaches.

Accessible screening for early-stage Alzheimer’s disease will identify individuals suitable for more in-depth diagnostic tests, treatment, interventions and participation in clinical trials.