Mathematical modelling to help diagnose and treat Parkinson’s and Alzheimer’s
Integrating gene expression and multimodal brain imaging for identifying and comparing therapeutic needs in Parkinson's and Alzheimer's
Parkinson’s and Alzheimer’s are both progressive brain disorders that share some similar symptoms – and sometimes, people can have both diseases. That makes it hard for doctors to diagnose the illnesses and design treatment plans.
At McGill University, Quadri Adewale, a PhD candidate in neuroscience, has developed a mathematical model to help distinguish between the two diseases and lead to individual treatment plans. Adewale uses symbols to represent the results of imaging scans, such as MRIs of the brain. He includes biological information such as the amount of toxic or misshapen protein accumulations, brain wave patterns, any signs of dopamine deficiency, white matter connectivity in the brain, and whether a brain shows shrinkage.
Adewale then assigns different symbols to represent the results from a type of genetic screening, called microarray testing, which can measure the proteins expressed by large numbers of genes. This combined equation will allow researchers to examine an individual’s biological data at the functional and genetic levels simultaneously.
“By solving this equation, I can identify the genes that are important, as well as the biological factors that these genes are influencing.”
Because biological markers change over time as someone’s Parkinson’s or Alzheimer’s progresses, Adewale also has a way to incorporate those changes into his model.
Adewale has already completed his model of Alzheimer’s, and has identified genes, proteins they express and the ways those proteins influence biological factors.
Now he’s working with data from more than 200 people with Parkinson’s to identify the genes influencing the unique biological features of the condition.
Once he’s finished entering the Parkinson’s data into his model, he will compare the two results to see if there are overlapping genes.
Adewale will apply his model to each of the 200 individuals whose data he has. He hopes eventually to show how far the diseases have progressed in people, by correlating their symptoms with genes and proteins, and ranking the level of influence those genes and proteins have.
Ideally, Adewale’s model will one day enable doctors to enter the results of a patient’s brain imaging scans, genetic screening, and symptoms into an equation that could indicate which disease someone has – Alzheimer’s or Parkinson’s – or whether they have both illnesses.
“Perhaps addressing or targeting those genes that have been identified in both Alzheimer’s and Parkinson’s would open up a new treatment approach,” he says.
The modelling might also indicate what stage someone is in the disease’s progression.
That knowledge could not only lead to better diagnoses, but it could also be vital once researchers devise gene therapy treatments to treat individuals differently, Adewale says.
“If we can isolate particular genes associated with particular symptoms – then you could target individual treatment,” he says.
How your support made this research project possible
Growing up in Nigeria, Adewale heard many superstitions about why people developed progressive neurological diseases, such as Alzheimer's and Parkinson's. But as a devotee of science, he wanted to know the facts behind why the illnesses occur.
Adewale is an electrical and systems' engineer by training. He decided to pursue a PhD in neuroscience to apply his knowledge of systems to the brain – an impressive biological system in its own right.
If he can chart the brain's systems and isolate what makes them malfunction when it comes to Parkinson's and Alzheimer's, Adewale believes the knowledge will counter the superstitions that persist about the diseases.
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