Development of a blood-based test for neurodegenerative diseases

STTR Project Summary/Abstract It is estimated that every fourth to fifth death in the US is caused by a neurodegenerative disease such as Alzheimer’s, AD related diseases, or Parkinson (CDC Wonder database, 2022; Alzheimer’s Association, 2022). However, there are very few therapies or even molecular

diagnostic tools to detect these diseases, so the diagnosis of Alzheimer’s and AD-related neurodegenerative diseases relies primarily on cognitive assessments which typically only occur with onset of dementia. With no diagnostic test available for the early detection of neurodegeneration and no ability to differentiate between different neurodegenerative diseases

early on, it is unsurprising that over 43 % of primary care physicians report that they are uncomfortable diagnosing mild cognitive impairment (MCI) due to Alzheimer’s (Alzheimer’s Association, 2022). A diagnosis of ‘Alzheimer’s-type dementia’ also often serves as a placeholder to describe a syndrome of memory loss that can result from various underlying disease causes,

and which may require different therapies. Therefore, we propose to use Covalent Protein Painting (CPP), a novel platform technology that can detect, identify, and differentiate the misfolded protein aggregates that characterize AD and related neurodegenerative diseases, to develop a blood-based diagnostic test for neurodegeneration. Over 80% of primary care

physicians say they would welcome such a test, in particular if such a test could detect AD and related diseases before patients are symptomatic or only show mild symptoms because it would help them devise a therapy plan with their patient and allow them to be proactive. Better and earlier diagnostics would also lead to better therapies, because one of the reasons so many

clinical trials for neurodegenerative drugs have failed is that participants are usually treated too late, when symptoms are already apparent. Our test would allow earlier enrollment of patients in clinical trials before too much damage has been done to the brain and would enable better stratification of patient cohorts, both of which would accelerate and increase success chances of

clinical trials.