Parkinson’s disease (PD) is a complex, age-related disorder for which there are currently no biomarkers available to diagnose or predict the onset of disease. However, growing evidence suggests that brain inflammation and autoimmunity are associated with PD and could thus serve as clinically relevant biomarkers. We recently found that PINK1 and Parkin, proteins that are disabled in early-onset PD, actively repress the processes that lead to the targeting of cellular mitochondria by the immune system. When PINK1 and Parkin are absent, immune cells inappropriately recognize and destroy these vital cell structures — damage that is associated with Parkinson's disease.
Based on our preliminary data, we propose to test the hypothesis that activation of an autoimmune response directed against mitochondria, and the production of immune cells that target these structures, can serve as biomarkers to monitor disease onset and progression in PD.
We propose that autoimmune recognition of mitochondria can be exploited as potential biomarker, particularly during early stages of Parkinson's. We will identify mitochondria-specific immune cells in people with PD by exposing blood samples to mitochondrial proteins and assessing their immunoreactivity. In addition, we will catalogue the repertoire of reactive immune cells to establish an autoimmune profile associated with PD. Together, these findings will produce a unique dataset that will fully describe the immune response involved in mitochondrial autoimmunity in individuals with PD.
Impact on Diagnosis/Treatment of Parkinson’s Disease:
The ability to monitor the engagement of mitochondria-specific autoimmune mechanisms will open new avenues for the treatment of PD, which had not previously been linked to autoimmunity. Furthermore, our results hold the promise to better categorize people with PD and identify those that will most likely benefit from treatments.
Next Steps for Development:
We will recruit independent cohorts to validate the autoimmune signature we identify and to evaluate whether our results can be used as a biomarker to reliably identify individuals with Parkinson's.