Q&A Walter Swardfager

We are pleased to have Walter Swardfager on our scientific advisory board. Walter holds a Canada Research Chair in Clinical Pharmacology of Cognitive Neurovascular Disorders. He is an Associate Professor and Associate Chair of Clinical Sciences in the Department of Pharmacology and Toxicology at the University of Toronto, and a Scientist at Sunnybrook Research Institute. He has a deep understanding of dementia and current research strategies and is at the forefront of prevention research.

We recently posed a few questions to Walter to introduce him to the i-Forget community.

How did you get into neurobiology?

My interest in pharmacology started from a curiosity about how our brains process thoughts and feelings. I wanted to know how those processes differed in people with mental health conditions. However, the enormous complexity and diversity of those conditions and how we conceptualize and measure them made them difficult to map onto the underlying biochemistry, which was my main interest as a pharmacologist. My colleagues in neurology had instrumentation that made it easier to map brain changes seen in mental illness and brain aging onto biochemical processes, which led me into the dementia field.

What does your lab work on?

We primarily study how the risk factors for dementia translate into changes in the brain. Understanding this dynamic can help us find ways to break the connections between early underlying causes and the brain changes that set up cognitive decline before it becomes irreversible. 

We have a particular interest in vascular risk factors like diabetes and hypertension and how they affect the brain’s smallest blood vessels, which are important for maintaining brain function as we age. We have shown that some of the newer diabetes medications are associated with reduced dementia risk in people with diabetes.

In general, where is the dementia research field going, and are there any short- to medium-term goals expected?

We’re at a point where we understand some causes of dementia well enough to manipulate them with drugs but not well enough yet to make people well. We know that misfolded proteins like amyloid, tau, alpha-synuclein, progranulin and TDP43 accumulate in the brain, and we can now remove amyloid.

At the same time, the field is undergoing a revolution in biomarker research, which makes it possible to determine who has Alzheimer's disease (specifically, amyloid and tau) versus other kinds of dementia involving other misfolded proteins. In the near term, we expect to see further refinement of amyloid-lowering therapies, used in combination with practical biomarkers that allow us to target them to the right people. 

In the longer term, progress in structural biology offers new ideas about targeting other proteins that cause dementia. This has resulted in a pipeline of new candidate drugs to test, including small-molecule drugs and additional antibody immunotherapies. However, I think more significant benefits will come when we know what causes these proteins to accumulate in the first place and when we learn to manipulate those processes for better outcomes. We are starting to identify viable drug targets for processes such as neuroinflammation and cell metabolism.

Using biomarkers in clinical studies may help us to understand how the risk factors contribute to early pathological processes. This, in combination with a person’s genetic risk profile, should take some of the guesswork out of which early interventions or preventative therapies might mitigate an individual's most significant risks for dementia and keep them well longer.

How does the i-Forget research funding model compare to what is commonly seen in academic research?

Funding research through a charitable organization that will become self-sustaining through donations and by making its data commercially available to researchers is new and interesting.  Building a community around research participants and enabling them to learn about their health and dementia risk is also uncommon in more traditional academic research models.  

This innovative model couldn’t come at a better time when research costs and dollars are scarce. I think it's a win-win.

What interests you most about the i-Forget data set, and what could be the lasting legacy of the study?

The dataset's structure is interesting, and it could become part of i-Forget’s legacy. It could help identify genetic and environmental features in the gut microbiota, helping researchers spot potentially “modifiable" signals involved in dementia and potentially other conditions. The evolution of analytical methods, such as artificial intelligence and machine learning is allowing us to seek answers to more nuanced research questions that incorporate more complex datasets like i-Forget.