Comparison of computational and statistical methods for identifying genetic risk factors for cognitive decline in Parkinson's Disease
Approved Research ID: 67829
Approval date: June 16th 2021
Aim: Aim of the project is to identify genes associated to cognitive decline in Parkinson's Disease.
Scientific rationale: Idiopathic Parkinson's Disease (PD) is influenced by genetic variants. More specifically, there is likely a genetic contribution to the level of cognitive decline, which is frequently observed in PD patients. However, identifying corresponding genetic variants via classical statistical approaches remains challenging, specifically in case of rare genetic variants. Hence, statistical and computational approaches are of interest that aggregate variants, e.g. on gene level. A number of methods have been proposed, but we need to better understand their advantages and limitations, including a systematic power analysis.
Following such an analysis we will apply the most computational promising approach to unravel genes associated with cognitive decline in PD. The knowledge of such genes is an important step towards finding new and better medications in the future.
Project duration: 1 year
Public health impact: This project focuses on identifying genetic factors that contribute to cognitive decline in Parkinson's Disease (PD). Identifying such genetic factors is important to develop novel therapies in the future.