Integrating neurotransmitter receptors and multi-modal brain imaging to improve treatment selection in Parkinson’s disease

Parkinson’s affects many processes at the levels of cells, brain regions and even other organs. Consequently, despite being diagnosed with the same disease, people living with Parkinson’s may have vastly different motor and cognitive symptoms, rates of progression, and treatment responses.

At McGill University, Ahmed Khan, a PhD candidate and neuroscientist, is using brain scans and computational modelling to identify the underlying biological mechanisms behind these variations in the way different people experience Parkinson’s.

For example, imaging scans may show reductions in brain matter volume in some regions for one person compared to another, and that may correspond to different symptoms and treatment responses.

Khan wants to predict the progress of the disease, and design individual treatment plans.

“Right now, there is a generalized approach to medicine in neurodegeneration, where the same class of drugs is prescribed to most patients,” Khan says.

“This kind of model, once it’s been validated, would allow you to design personalized treatment plans for each patient based on their specific pathology and symptoms.”

Neurotransmitter receptors, which mediate a cell’s response to the brain’s main signalling molecules, are one of the pillars of this model.

Parkinson’s is associated with a deficiency of the neurotransmitter dopamine. Many other neurotransmitters are also affected, however.

Using brain scans of Parkinson’s patients taken over several years and high-resolution measurements of different types of neurotransmitter receptors from brains of deceased donors, Khan is creating a mathematical model of long-term changes to the brain over the course of Parkinson’s.

He hopes his model will illuminate the role of neurotransmitter receptors in the progression of Parkinson’s.

“My model tries to predict what’s going to happen to each patient in the future using measures from brain scans,” Khan says.

The model will measure dopamine deficiency, brain atrophy, changes in brain activity, and the integrity of white matter connections in the brain.

He will then use this computational model to evaluate which neurotransmitter receptors are most affected in each person, and how they relate to their disease symptoms, such as tremor, trouble walking, or changes in memory, thinking and reasoning.

Ultimately, Khan hopes people could receive individualized treatment to improve their symptoms, targeted to specific neurotransmitter receptors.