Protein structural biomarkers to predict PD motor progression.
Main applicant: Prof. Dr. Paola Picotti
Affiliation(s): ETH Zurich (CH)
Abstract: : Parkinson’s disease (PD) is the second most prevalent neurodegenerative brain disease, becoming more common with the aging of our society. People affected by PD vary widely in prognosis, rate of progression and response to treatment. The ability to predict these differences at the time of diagnosis would significantly improve our ability to give the best care to patients. To date, there are no reliable ways to predict how a person diagnosed with PD will progress. In recent work, we have used our cutting-edge technology to compare the structures (i.e., shapes) of thousands of proteins between the cerebrospinal fluid (CSF) of Parkinson’s patients and healthy individuals. We found that about 100 proteins had different structures in Parkinson’s and healthy CSF. This was a major discovery since nobody had made such a comparison or found such structural changes before. It showed that looking at protein structures can be a powerful way to diagnose Parkinsons’ disease. Now, in this new project, we will apply the same approach to try to discover biomarkers predicting the rate of motor or cognitive decline during disease progression in PD. Such biomarkers would guide physicians in the selection of the best personalized treatment or disease management, help decide which patients to include in clinical studies for testing new treatments, and possibly help us understand the underlying reasons for faster or slower progression.
Related Publications: Biomarkers in Parkinson’s disease: Advances and strategies.