The innate immune system, unlike the adaptive immune system, does not first require exposure to a foreign substance before immunity can be developed. Natural killer (NK) cells—a subset of white blood cells—make up a major part of the innate immune system. NK cells are considered a first line of defence in the body as they can recognize and destroy cells that have been altered, such as in the case of virus-infected or tumour cells and also foreign cells. This recognition is through the interaction of receptors on the surface of NK cells, with the receptor molecules called MHC class-1, expressed on the surface of target cells. The absence or alteration of numbers of MHC class-1 on abnormal target cells results in their destruction by NK cells. In both humans and mice, there is great variability in the number and combination of receptors on individual NK cells. Furthermore, it has recently become evident that the receptor repertoire of NK cells can change in response to various stimuli. Building on her previous MSFHR-funded work, Arefeh Rouhi is studying the mechanisms that control these variations among NK cells. Understanding how NK receptors are controlled is critical to the interpretation of how the repertoire is modified in response to infection and tumour cells, and the response of NK cells to mismatched bone-marrow grafts. Ultimately, this knowledge may lead to the development of methods to use the body’s own immune system to protect against infections and malignancy.
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Cluster Analysis for High-Dimensionality Population Health Data
Population health research seeks to develop a better understanding of how social, cultural, environmental, occupational and economic factors determine health status. While most population health research focuses on specific hypotheses, understanding the bigger picture can yield insights on a larger scale. How socio-economic factors influence or correlate with health status, how diseases group together in constellations, and how these relate to health services usage, medication usage and health-driven outcomes are all important questions. Cluster analysis (CA) is a class of statistical techniques that can be applied to data that exhibit natural patterns. However, current CA methods are poorly suited to broad population health data, which may contain hundreds of variables with many dimensions. The result is that patterns between classes of variables can be lost in the statistical “noise.” Eric Sayre is developing a new method of CA called Cluster Analysis for High-Dimensionality Data (CAHDD), which provides a means for filtering statistical noise, and allowing important patterns to emerge from the data. By applying CAHDD to Canadian population health data, Eric’s research seeks to answer big-picture questions about socio-economic factors and health status. CAHDD will be available for other health researchers to interpret population health data, leading to significant advances in our understanding of the determinants of health status in our population.
Antagonism of the p75 Neurotrophin Receptor promotes neurotrophin-mediated neural regeneration and plasticity within the injured spinal cord
Functional recovery following spinal cord injury is extremely limited, leaving individuals with limited mobility, autonomic dysfunction, and chronic pain. The lack of significant recovery following this type of injury reflects the failure of mature nerve fibres (axons) to regenerate and the incapacity of uninjured nerves to undergo compensatory growth (plasticity). Regeneration and plasticity are governed by a balance between growth-promoting and growth-prohibiting factors within the injured spinal cord. Neurotrophic factors and myelin-associated inhibitory proteins (MAlPs) both influence axonal growth through axonal receptor complexes that include the p75 neurotrophin receptor (p75NTR). MAIPs suppress axonal growth through p75NTR; neurotrophic factors augment axonal growth partly by inhibiting p75NTR. Angela Scott has found in past research that both the regeneration of injured axons and the plasticity of spared axons can be improved with the antagonism of p75NTR. Her current research explores the role of p75NTR following spinal cord injury. By determining the functional significance and clinical relevance of p75NTR antagonism, her work may lead to clinically relevant therapeutic treatments that improve functional recovery for people with spinal cord injuries.
Computational methods for array CGH analysis for improved diagnosis of human cancers
Chromosomal instability is a hallmark of tumour cells in human cancer. Regions of chromosomal instability can have various forms including single point mutations, rearrangements, whole chromosome loss or duplication, or chromosomal segments containing DNA copy number change. The alterations change the expression of cellular constituents and eventually result in cells that do not function normally. Finding regions of chromosomal instability provides important locations in the human genome that are both symptomatic and diagnostic markers of various cancers. Recently developed techniques called array comparative genomic hybridization (aCGH) have allowed scientists an unprecedented high degree of resolution to detect regions of chromosomal instability in cancer patients. The experiments produce both a high volume of data and noisy signals that are not cleanly interpretable. Therefore, robust computational techniques must be developed that can automatically identify regions of chromosomal instability. Sohrab Shah is developing computational methods and statistical models that, given aCGH data for one or more patients, can accurately and reliably detect chromosomal aberrations. His research will first evaluate this method on standard data sets where the location of the aberrations are known, and then apply the method to three large scale genomic studies to discover chromosomal locations affected in lung, brain and lymphoma tumours. He will also assess the diagnostic utility of chromosomal alterations that are recurrent across patients and develop prototype diagnostic tests that may ultimately be put into clinical practice.
ACK family tyrosine kinase may participate in the control of dorsal closure through negative regulation of Egfr
The Rho family of small GTPases in the fruit fly Drosophila are key controllers of cell shape and cell movement through their participation in signalling networks that control a variety of cellular processes. These proteins function as molecular “switches”, turning on or off the particular steps in the signal pathways to control cell shape or cell movement. The study of these molecules provides us with important medical insight since disturbance of their signalling has been implicated in a variety of disorders including cancer and a number of inherited conditions, such as mental retardation, deafness and facial deformities. These proteins have also been shown to be key regulators in wound healing. The activated Cdc42 kinases (ACKs) are proteins shown to be effectors for the Rho GTPases Cdc42, and are linked to the regulation of Drosophila Dorsal Closure (DC). DC is a well-known animal model system for studying wound healing. Previous studies have demonstrated Drosophila activated Cdc42 kinase (DACK) functions in controlling cell shape change and movement of epidermal cells during DC. Weiping Shen is using the DC as a model system to assemble signalling networks controlling the movement and shape of cells. The learning gained from these signalling pathways will shed light on their roles in human development and disease. By developing a better understanding of the mechanisms that allow signals to translate into physical movements, this research could lead ultimately to solving many genetic and developmental puzzles related to human diseases.
Improved Biostatistical Methods to Detect Gene-by-Environment Interaction in Case Control Association Studies
Complex genetic diseases are thought to result from genetic susceptibility factors acting in conjunction with environmental, lifestyle or non-genetic factors such as infectious, chemical, physical, nutritional and behavioural exposures. In the past, researchers have used the case-control study design to investigate disease associations with non-genetic factors. Recently, new genetic information in the form of Single Nucleotide Polymorphisms (SNPs) has been integrated into these population health studies in an attempt to better understand the joint effects of non-genetic and genetic risk factors. However, conventional statistical methods for this study design are not powerful enough to detect such joint effects, even for studies with very large sample sizes. Jihyung Shin is developing new biostatistical methods to more efficiently extract information from case-control data about statistical interactions between genetic and non-genetic risk factors for disease. By developing extensions of the methodology to allow for missing information on genetic risk factors in a statistically valid way, her work can accommodate the analysis of disease associations with SNP haplotypes, which are combinations of genetic variants at several nearby SNPs on the same chromosome. This type of analysis can offer improved power over analysis of single SNPs for detecting the effects of genetic factors and their interactions with non-genetic risk factors. The ability to identify interactions between genes and non-genetic factors that affect the risks of complex genetic disorders will improve our understanding of disease pathogenesis and help with the development of more effective and appropriate treatments, prevention and screening tools.
An examination of injection drug use sites: the influence of social and physical context on drug-related harms and public health interventions
Injection drug use may result in severe health consequences including increased risk of viral infections such as HIV and hepatitis C, soft tissue infections, and drug overdose. Recently, with increasing attention being paid to the impact of environment on individual and public health, intervention efforts for injection drug users (IDUs) have moved beyond the modification of individual behaviour and focused on modifying the environments in which people use injection drugs. One recent and controversial example of this involves medically supervised injection facilities, where IDUs can inject pre-obtained illicit drugs under the supervision of health care professionals. William Small is studying and comparing three types of injecting settings in the Downtown Eastside: private injecting spaces (such as homes), public injecting spaces (such as alleys), and Vancouver’s supervised injecting facility. He is examining how the social and physical context of each setting influences the ability of injection drug users to employ HIV-prevention measures and safer injection practices. The findings of this research will build important knowledge about the health and HIV vulnerabilities of IDUs in the Downtown Eastside. Also, this research will provide information on the impact of current interventions, which may inform future interventions for addressing injection drug use.
Pharmacogenetics of Mycophenolate in Thoracic Transplant Recipients: Role of UDP-Glucuronosyltransferase Genetic Polymorphisms
Thoracic (heart and/or lung) transplantation is an effective but aggressive measure for treatment of end-stage heart and lung diseases. However, rejection of the transplanted organ remains a major problem and frequently leads to organ loss and death. All transplant recipients take immunosuppressants (drugs that prevent rejection), yet over-immunosuppression exposes them to undesirable infections and other side effects. Mycophenolic acid (MPA) is an effective immunosuppressant commonly used in transplantation. However, tailoring MPA therapy is challenging due to the wide variability and unpredictability in treatment responsiveness and side effects among patients. Genetic makeup and metabolism of MPA have a significant bearing on drug responsiveness. While many studies provide better understanding of MPA in kidney transplant recipients, information on the thoracic transplant population is scarce. Lillian Ting’s research is exploring the role of genetics in determining treatment responses. The ultimate goal is to individualize regimens, even before treatment begins, for each patient in order to obtain optimal treatment response and minimal toxicity. The results from Lillian’s study will add valuable knowledge to transplantation management. It will be directly incorporated into patient care, improving patient survival and quality of life after transplantation.
Effect of cholesterol on prohormone processing in pancreatic beta cells in Type 2 Diabetes Mellitus
Type 2 diabetes mellitus is a devastating chronic disease affecting close to two million Canadians. The disease is characterized by a loss of insulin action in tissues such as muscle and a loss of insulin secretion by the islet beta cells of the pancreas. The number of beta cells within the pancreas – an important determinant of the amount of insulin secreted – is decreased in persons with type 2 diabetes. This supports the idea that the progressive loss of insulin secretion in this disease is due to a loss of functional beta cells. The loss of beta cells is associated with the formation of toxic islet amyloid deposits, consisting primarily of the beta cell peptide islet amyloid polypeptide (IAPP or amylin). Although the mechanism underlying islet amyloid formation is not known, impaired processing of the IAPP precursor, proIAPP, has been proposed to be an important initiating event. In type 2 diabetes, elevated glucose and free fatty acids can cause beta cell dysfunction, which raises the question whether elevated cholesterol induces beta cell dysfunction in this disease. Zainisha Vasanji’s research is aimed at determining whether exposure of beta cells to elevated cholesterol is the trigger for the chain of events that lead to islet amyloid formation in type 2 diabetes. Zainisha’s study may help delineate the cause of the beta cell defect in type 2 diabetes and may lead to new therapies to prevent the progressive loss of insulin secretion in this disease.
New RNAs Phenotypes from Old by Random Recombination and Selection
The emergence of new viral species or strains by evolution is viewed as a great potential danger to human health. Besides mutation, recombination (shuffling of genes) plays an important role in the evolution of viruses – such as HIV or Hepatitis E. There is significant concern that more dangerous viral strains or species may evolve through recombination. However, the complexity of virus-host systems makes the study of this process very difficult. Using a new method she developed, Qing (Sunny) Wang is using ribozymes (specific functional RNAs) as a model for studying the mechanisms of random recombination in viruses. She hopes that this work will shed more light on how viruses evolve through recombination.