Project 456956

Twenty years ago, Citron called the lack of therapeutic options for Alzheimer's disease (AD) the "biggest unmet medical need in neurology". Today, we still do not have the necessary drugs to properly treat people. Over 170 multi-centre clinical trials have failed to find a successful treatment since 2002. However, these failures may not be because of ineffective drugs, but instead may be differences in how individual patient respond to treatment. A 'personalized-medicine' approach, where individuals are matched with a drug targeting their specific condition, may find effective therapeutics. This cannot be currently done because we have no disease mechanism(s)-associated laboratory-based biomarkers in clinical use that distinguish AD from Dementia with Lewy Bodies (DLB), Parkinson's Disease with Dementia (PDD), or patients with mixed dementias. The lack of biomarkers also precludes development of cause-directed treatment focused on metabolic factors that modulate genetic risk and environmental predisposition, notably the sex of a patient. We propose here to validate the use of profiling changes in lipid (membrane) metabolism as a means of predicting risk and discriminating neurodegenerative diseases. We seek to provide better state, rate, fate, and trait' biomarkers that enhance capacity for early diagnosis (state) and intervention, tracking disease progression (rate), predicting more accurate prognoses (fate), and identifying risk in pre-symptomatic persons for prevention (trait).