Cerebrovascular disease and cognitive impairment are the leading causes of disease burden in the world. Efforts to tackle aging-related diseases could substantially benefit by an improved understanding of modifiable risk factors that may accelerate the aging process and contribute to disease pathogenesis. Some risk factors, such as hypertension and diabetes, have been proved to be contributing to aging in epidemiological studies using mainly conventional statistical models. However, due to many reasons such as experimental design or sample size, the strength of the causal relationship is not sufficient, and more studies focusing on the spectrum and the causal impact of various diseases are warranted. Our study aims to integrate and analyze the extensive clinical, life style, genetic and imaging data available in UK biobank, in order to explore the complex interplay between different factors and age-related diseases. Data processing such as polygenic risk scores and statistical methods such as Cox proportional hazards models or Mendelian randomization analysis will be performed. Our study is unique because of its focus on the causal impact of wide range of risk factors such as life style, clinical conditions and genetics on age-related diseases such as cerebrovascular disease and cognitive impairment. It is our hope that the results generated from this project will help develop new ways to promote brain health in the elderly population, with the goal of reducing mortality and disability that are crucial for the well-being of older people.
