How do large networks of proteins change in the brains of people with Alzheimer’s or Parkinson’s disease?
Nicholas Seyfried, Ph.D.
Atlanta, GA - United States
Although Alzheimer’s and Parkinson’s are considered to be distinct diseases, there is increasing evidence that they may share some common mechanisms. Furthermore, many patients have overlapping brain changes and clinical symptoms. For example, some patients who have Parkinson’s disease also have amyloid plaques in the brain and impaired cognitive function often associated with Alzheimer’s disease.
Scientists around the world are working to identify characteristics that define Alzheimer’s and Parkinson’s, and which allow the two diseases to be distinguished. There is also a need to better understand if some of the earliest brain changes associated with neurodegenerative diseases share a common molecular mechanism. If so these similarities and differences may identify key targets for the development of new therapeutics.
Nicholas Seyfried, Ph.D., and colleagues have proposed a novel approach to exploring the similarities and differences between Alzheimer’s and Parkinson’s. Their approach, known as proteomic network analysis, involves the use of advanced computational methods to identify relationships among large numbers of proteins and biological pathways. Specifically, Dr. Seyfried and colleagues will analyze changes in large numbers of proteins in the brain tissue and cerebrospinal fluid of people with Alzheimer’s or Parkinson’s. Instead of focusing on single proteins, the network analysis will identify complex patterns of protein changes, including those that are shared by the two diseases, as well as those that are unique.
This novel approach could lead to the identification of changes in proteins networks that may serve as biomarkers to indicate the presence of disease in the brain at the earliest stages. A better understanding of these early mechanisms could inform the development of targeted drug therapies. In both Alzheimer’s and Parkinson’s disease, early detection could allow for future treatments to be administered before significant brain damage has occurred.
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