Project 454398

Alzheimer's disease (AD) is a debilitating degenerative condition common among the elderly that affects 50 million people world-wide, including over 500,000 in Canada alone. AD patients first lose the ability to remember names, faces, and places, but ultimately lose the ability to communicate and function independently. These challenges are made much worse by other serious illnesses which often emerge over the course of AD, including depression, anxiety, agitation, infection, and metabolic disorders. In fact, these co-occurring conditions are what most often lead to loss of function and death in patients. Therefore, it is of the highest importance for scientists to understand the relationship between the progression of AD and these accompanying diseases. The proposed project will analyze data from over 33,000 individuals from Canada and the United States, who have been followed from middle age, with a subset also having brain autopsy data available. Using these resources, and cutting-edge statistical techniques combining clinical, cognitive, genetic, and sociodemographic data, we will identify the genes, environments, and behaviours that most significantly predict the emergence of a wide array of health conditions in individuals who develop AD. With these predictive models, it may become possible to detect problematic patterns early, while individuals are still middle-aged and without signs of dementia, giving them the chance to make lifestyle and medical changes before it is too late. These models also have the potential to reveal molecular causes of these co-occurring conditions in the context of AD, offering new insights for further research into novel therapeutics.