Currently, the incidence Alzheimer disease (AD) and Parkinson disease (PD) is increasing around the world but it is still difficult to predict the disease risk level for individuals. Although there is some existing evidence to suggest that some genetic variants can increase the AD and PD risk, there is no reliable method for AD and PD risk prediction. Therefore, further research is required.
Our aim is to develop a tool to identify individuals at high risk for AD and PD based on the genome-wide polygenic scores based on the full cohort of UK Biobank using genetic data, diagnosis data, measurements of cognitive functions, measurements of motor functions and diagnoses of cognitive impairment. The proposed project will use machine learning models to analyze existing data collected by UK Biobank and will take approximately 36 months to complete.
This is the first research to use genome-wide polygenic scores for the disease risk prediction of AD and PD. Our research will provide a powerful tool for AD and PD risk prediction for individuals. The tool could also be applied to other diseases.
