Stratifying deeply phenotyped Parkinson’s patients with blood-based immune signatures

Parkinson’s disease is the second most common neurodegenerative disorder and the loss of dopaminergic neurons in the Substantia nigra underlies the core symptomatic presentations. The role of inflammation in the death of the dopaminergic neurons is currently unclear. We recently found that Parkinson’s patients who also carried a high genetic risk of Alzheimer’s disease developed a more severe and rapidly progressing form of Parkinson’s. As the immune system is strongly linked to the genetic risk of Alzheimer’s disease, we hypothesise that neuroinflammation is also a key driver of Parkinson’s disease progression.

This study will investigate the role of the immune system in Parkinson’s disease presentation and progression. We will take advantage of a unique and recently created large cohort of Parkinson’s patients whose symptoms have been extensively recorded over time and, importantly, have had blood gene expression measurements. By examining changes in the patient’s blood, we can get insights into what is happening in the body’s immune system during disease progression. 

We have recently developed a new mathematical method that can simplify hundreds of Parkinson’s patient’s symptoms into a small number of summarising measurements. Using this method, we will look for changes in blood molecular profiles that correlate with, or predict, changes in Parkinson’s disease symptoms. This research project has the potential to accelerate our understanding of how Parkinson’s disease manifests and progresses. It can provide insights into how the body’s immune system is responding to the disease and how this response determines progression. Most importantly, it could provide new ways to predict the progression of Parkinson’s disease and new ways to modify and slow the progression of the disease.
 

Research lead
Professor Caleb Webber
Dyddiad cychwyn
1 Ionawr 2021
UKCRC Research Activity
Aetiology
Research activity sub-code
Biological and endogenous factors