The virus causing COVID-19 can invade the brain, raising concern over long-term impacts on thinking abilities. We aim to identify long-term impacts on these cognitive abilities in those who have had COVID-19, and pinpoint factors that predict long-term outcomes. Adults positive for COVID-19 and those with no evidence of infection, are completing a series of cognitive and psychological tests in a current study. The proposed project will follow these individuals over time, with one and three-year follow-ups to examine changes in cognition across time. We will examine group differences in cognition, mental health, and other factors at each time point, determine if one or more cognitive profiles (clusters) characterize COVID-19 positive individuals, examine changes in these profiles across time, and test a screening measure to detect these cognitive difficulties. Findings will inform clinicians (e.g. neurologists, rehabilitation specialists) on trajectory of recovery of function and inform healthcare service provision in BC. Results will help ensure long-term impacts of infection are appropriately addressed, so those affected can efficiently resume complex activities requiring cognitive effort (e.g. employment, academic pursuits).
Program: Scholar
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.
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.
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.
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.
Optimal pregnancy and postpartum health for everyone
After childbirth, mothers are at risk of death and disease. Patient engagement can improve the relevance and impact of research in this area; however, patient partners often do not reflect the diversity of the community. This limits the research and its results. This is especially important in BC, which is the most ethnically diverse province in Canada. The proposed research project aims to answer the following three questions: 1) How can we improve the diversity of patient partners in pregnancy and postpartum-related research? 2) Is a mobile application appropriate and acceptable for self-screening of postpartum complications? 3) What is the frequency, timing, and factors associated with postpartum complications and hospital readmissions in BC? The proposed research will promote equitable representation of pregnant and postpartum individuals in research, improving our understanding of their health and health concerns. It will be a core component of my portfolio of patient-oriented maternal health research in BC and globally.
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.
Using high-throughput experiments and machine learning to understand the role of non-coding mutations in cancer
Cancer is caused by mutations in the DNA that cause a patient’s cells to grow out of control. Some of these cancer-causing mutations change how genes are regulated; that is, which genes are turned on or off in the cell. Essentially all cancers have activated the TERT gene because TERT is essential for cancer growth. We understand TERT regulation better than most genes, but even here we cannot predict how mutations alter TERT expression. Overall, we do not understand which genes or mutations can promote cancer via altered gene regulation. Our work aims to learn the code that cancer cells use to interpret regulatory mutations. We will make many artificial mutations in large scale, and measure how much each mutation affects the amount of gene made. We will model how the cells interpret these mutations using a computer, and apply the model to find new cancer mutations. We will these computer models to discover how often mutations alter gene regulation in cancer, and highlight genes whose regulation is important in particular cancers. In the long-term, our work will allow us to better diagnose and treat cancer by showing how a particular patient’s tumor’s mutations alter gene regulation and cancer growth.
Light and drug delivery coupled with biomaterials to improve motor function after spinal cord injury in animal models
Spinal cord injury (SCI) is a debilitating condition with no available cure directly affecting ~80,000 Canadians. The major challenges to overcome include: i) the limited spontaneous regeneration of nerve fibers (axons) after the injury; ii) scar tissue formation at the injury site (lesion), which inhibits the growth of axons; and iii) the difficulty in guiding axons to grow across the lesion. The present work proposes a novel solution that combines optical stimulation technology and biomaterials to promote axonal growth, inhibit the formation of scar tissue using targeted drug delivery, and guide growing axons across the lesion. My team has developed fully implantable multifunctional neural probes for the delivery of both light and drugs to the spinal cord injury site as well as biomaterials to guide the growth to axons across the lesion. The MSFHR Scholar Program would support our work to integrate these strategies and create a therapy that helps us understand the combined effects of light stimulation, drug delivery, and axon guidance on motor function recovery after SCI in animal models. The outcomes will support treatment development for SCI based on a better mechanistic understanding of regeneration.
Towards a mathematical theory of development
New technologies like single-cell RNA sequencing can observe biological processes at unprecedented resolution. One of the most exciting prospects associated with this new trove of data is the possibility of studying temporal processes, such as differentiation and development. How are cell types stabilized? How do they destabilize in diseases like cancer and with age? However, it is not currently possible to record dynamic changes in gene expression, because current measurement technologies are destructive. A number of recent efforts have tackled this by collecting snap-shots of single cell expression profiles along a time-course and then computationally inferring trajectories from the static snap-shots. We argue that this inference problem is easier with more data, and the right way to measure the “size” of a data set is really the number of time-points, not the number of cells. We propose to collect the first single cell RNA-seq time-course with more than one thousand distinct temporal snapshots, and we develop a novel mathematical and conceptual framework to analyze the data. This tremendous temporal resolution will give us unprecedented statistical power to discover the genetic forces controlling development.