Heart attack and stroke are the leading causes of death in Canada. These lethal events are caused by diseased cells accumulated on the wall of the blood vessels, leading to narrowing of the arteries. Although diseased cells can be removed naturally, this process is inhibited by inflammation. Recently, anti-inflammatory drugs are being actively developed to reduce heart attacks, but we lack methods to assess their effectiveness before testing in patients. This problem led to the failure of several clinical trials and serious side effects due to non-specific inhibition of the immune system. We will use models that closely mimic the conditions of patients and apply a thorough “onsite inventory” of diseased arteries to: 1) understand how inflammation inhibits the removal of diseased cells; 2) see if current drug candidates can neutralize these adverse effects in diseased arteries; and 3) explore and develop markers that can find patients who will benefit from the drug candidates. This study will provide evidence to guide the design of more specific anti-inflammatory drugs and their application to the right patients. It will minimize side effects and allow more patients to be properly treated to prevent heart attacks and strokes.
Research Pillar: Biomedical Research
Cost-efficient approach for phenotyping cells in large cohorts and relating them with COPD clinical outcomes
In Canada, over 2 million people suffer from COPD, costing over $1.5 billion per year in direct expenditures. However, no existing therapy can reverse COPD’s disease progress. Alveolar macrophages (AMs) are the lungs’ dominant immune cells and perform critical functions, including fighting infection and tissue repair. Single-cell genomics technology can characterize AM phenotypes and reveal their roles in COPD. However, validating the relation between AM phenotypes and COPD clinical outcomes requires many patients, making the unscalable single-cell technology impractical to study such large cohorts. This issue motivated me to develop a cost-efficient approach to discover cell-phenotype biomarkers, using both high-resolution single-cell and low-cost bulk genomic technologies. I will develop novel statistical methods and software tools for this novel approach. The key deliverables are: 1) an experiment protocol, novel statistical methods, and the first software pipeline for cost-efficient deep-phenotyping of large clinical cohorts, to discover biomarkers for ANY diseases; 2) novel AM phenotype biomarkers as drug targets of immunotherapy for COPD or a genomics diagnostic test (medical device) to guide personalized COPD treatment.
The links between nutrient sensing, cell intrinsic metabolism and T cell function in immune-related diseases
Our focus is on the cellular fuels and building blocks that change immune cell functions. Our immune system normally defends us against infections. In a healthy person, T cells (a type of immune cell) recognize infected or cancerous cells and remove them from the body. Normally, immune cells know the difference between healthy and infected or cancerous tissues. When this recognition is lost, it can lead to the development of attack of healthy tissues by immune cells (autoimmunity), the growth of cancer, or to persistent infections. This dysfunction of the immune system can lead to devastating diseases in children. My research aims to better understand how this happens. By comparing the way that biological fuels (sugars, fats and other building blocks) are used by immune cells from healthy people and patients with immune system associated diseases, we will define the cellular the pathways that maintain health or cause disease. This will allow us to target and “dial down” pathways that are driving cells to attack our tissues, or turn these pathways on to help immune cells fight persistent infections and cancerous cells. Ultimately, we hope to help develop new treatments.
Developing sensors for rapid detection of biomarker proteins for Alzheimer’s disease
Dementia is a growing health challenge that affects over 500,000 Canadians today, which is estimated to grow to 900,000 by 2030. Alzheimer’s disease, the most common form of dementia, is characterized by protein misfolding in the brain. This process can start over a decade before the occurrence of significant cognitive decline making it possible to diagnose at an early stage when treatment strategies are most effective. Biomarkers are measurable indicators that help determine if a person may have or be at risk of developing a disease. Researchers have identified phosphorylated tau (p-tau) proteins and small proteins called cytokines to be promising biomarkers for Alzheimer’s disease. To detect these biomarkers in blood samples, very sensitive detection methods are needed but existing methods have drawbacks such as being expensive and time consuming, and need to be performed in a laboratory, limiting their availability to Canadians. We have developed a new sensor that can detect proteins at ultra-low concentrations using a simple and rapid test. Our goal is to make a rapid and easy-to-use tool that can be used by clinicians to help diagnose Alzheimer’s disease and patients for personalized health monitoring.
Examining motor imagery-related brain function in health and after stroke to leverage its prescription
Many stroke survivors (~85 percent) in Canada experience long-term impairments in arm and hand function. To aid recovery, motor imagery (the mental rehearsal of movement) shows promise as an adjunct therapy. Yet, its effectiveness is varied. We think this is due to a lack of basic knowledge about how motor imagery works. Motor imagery is thought to work similarly to physical therapy, whereby repetitive physical practice drives changes in brain function necessary for learning and recovery. However, we do not know a lot about how motor imagery drives changes in brain function. Using a blended approach not yet taken, we will examine changes in both brain function and behaviour driven by motor imagery. Importantly, we will examine how changes in brain function are altered and can be optimized after stroke, to improve its effectiveness. Findings will provide new information about how motor imagery should be applied to maximize learning and recovery, directly informing its use and prescription in stroke rehabilitation. Overall, this research represents a critical step in improving interventions for stroke recovery, leading to improved daily function and better quality of life for Canadians living with stroke.
Foot-Ankle Stability (FASt) solutions for lifelong mobility
“You need to improve your stability” is one of the most common pieces of advice offered by clinicians after an individual experiences a fall resulting in an injury. Despite this common advice, researchers are still trying to determine how to best keep a person stable as they age. Recent work has shown that foot and ankle structures may play a critical role in maintaining stability, but how this is accomplished varies from person to person, and may change as people age. In the game “Jenga”, players are required to remove blocks from within the stack and place them on the top of the structure; the blocks at the bottom are more difficult to remove than those closer to the top, as smaller movements at the base can cause the structure to collapse. Feet and ankles are much the same: If there are foot and ankle issues, the lack of stability at a person’s base can create small movement that ultimately contribute to a fall. My research will help researchers and clinicians fundamentally understand the importance of the foot and ankle to movements that are important for mobility (e.g. walking) and use this knowledge to create digital health solutions and assistive technologies aimed at maintaining mobility throughout the lifecycle.
Immunomodulatory effects of endogenous retroviruses in infection and inflammation
Infectious diseases and chronic inflammatory diseases plague human health and account for roughly 60 percent of deaths worldwide. Basic and translational research that reveal new mechanisms of immune modulation during viral infection and chronic inflammatory diseases are therefore critical to lower health burden. Genetic and environmental factors influence immune responses, but we are far from achieving a comprehensive understanding of mechanisms that underlie protective responses and unwanted excessive inflammation. Endogenous retroviruses (ERVs) are viral sequences that are major components of all human genomes, yet ERVs have been largely overlooked in the context of infectious diseases and chronic inflammation. Dr. Maria Tokuyama will develop a highly innovative and rigorous research program to identify novel interactions between ERVs and the immune system and determine interactions that boost antiviral responses in the context of viral infection and those that promote excessive inflammation in the context of chronic inflammatory diseases. This research will expand our knowledge of the underlying mechanisms of disease and will lead to health and economic benefits for Canadians.
Post-transcriptional regulation of hematopoietic stem cell function during normal and malignant hematopoiesis
In 2016, there were approximately 22,510 Canadians living with leukemia and an estimated 2,900 Canadians died from leukemia. Acute myeloid leukemia (AML) is one of the most common types of leukemia in adults. About 30 percent of AML patients eventually relapse after treatment and suffer from very poor overall survival at this stage. It is postulated that leukemia stem cells (LSCs), a small population of leukemia cells characterized with regenerative ability, mediate resistance and relapse after therapy. My work sought to uncover the largely unknown role of the processes that control protein generation in maintaining blood stem cells and how it contributes to transformation of leukemia stem cells in cancer. This research program aims to identify new factors, which can serve as targetable molecules and pathways to specifically eliminate leukemia cells while sparing normal cells. The work will provide the scientific foundation for future developments of therapy targeting these pathways as a novel strategy in eradicating leukemia stem cells to improve outcomes in AML patients.
Self reactivity as a driver of extranodal diffuse large B-cell lymphoma transformation and survival
Lymphoma is a form of cancer that affects immune cells called lymphocytes, a type of white blood cell. There are many subtypes of lymphocytes and lymphomas. Diffuse large B-cell lymphomas (DLBCL) develop from B lymphocytes (B-cells) and are the most common subtype of non-Hodgkin lymphoma. About one third of DLBCL extend beyond the lymph nodes (“extranodal DLBCL”), and invade vital organs such as the kidneys, lungs, and brain, with an often-fatal outcome. Our ability to predict which patients will develop extranodal DLBCL is limited, and we also lack disease-specific treatments, partly due to an incomplete understanding of how and when these tumors originate. Interestingly, recent evidence suggests extranodal DLBCL share features with autoimmune disorders — conditions in which lymphocytes abnormally react against organs in our bodies, instead of external foes. In this study, we will investigate the relationship between the origin and progression of these diseases, in an effort to better understand how B-cells transform into cancerous cells, disseminate, and expand. Our work could help identify patients at high risk of developing extranodal DLBCL, and unveil key tumor dependencies to be leveraged as specific therapeutic targets.
Fine-scale mapping of high dimensional brain imaging genetics
Brain imaging genetics looks at how differences in genes (the part of our DNA that makes us who we are) affect our brains. The connections between different parts of the brain, and the way the brain develops are all influenced by genes. Usually, when scientists look for genetic effects in the brain, they look for really broad characteristics such as the the sizes, or thicknesses of the different parts of the brain. This is useful for giving us a big picture about what’s happening, but it hasn’t led to any deep understanding of genetic neurodegenerative diseases (instead, it provides more of a description rather than an understanding). The main tool for measuring the brain in humans is magnetic resonance imaging (MRI). The MRI produces a three dimensional picture of the brain. The “pixels” of the picture are known as voxels (as they are volumetric). There are many voxels in each MRI picture, and the complexity and size of the picture is the reason scientists have so far only looked at broad effects. By using modern machine learning and statistical techniques, the challenge of looking for genetic effects at the level of the voxel can be overcome.