Projects & Grants
| Risk Assessment of Parkinson's Disease Development in At-Risk Individuals and First- and Second-Degree Relatives Compared to Healthy Individuals | |
|---|---|
| Project Id | |
| Main solver | Mgr. Jiří Kozel |
| Period | 1/2025 - 12/2025 |
| Provider | Specifický VŠ výzkum |
| State | solved |
| Anotation | Parkinson?s Disease (PD) is the second most common neurodegenerative disorder, affecting around 1% of individuals over 60 and over 4% of those above 85. It leads to progressive deterioration of motor and non-motor functions, such as tremor, bradykinesia, rigidity, postural instability, loss of smell, cognitive decline, and REM sleep behavior disorder (RBD). Despite advancements, there is still no treatment to stop or cure PD. Thus, prevention and early detection of individuals at high risk, especially in the preclinical stage, remain critical. This project examines individuals at risk and relatives of PD patients, as genetic predisposition is a significant risk factor. First-degree relatives are at much higher risk than the general population, making them ideal for identifying early signs and developing preventive strategies. The MDS-UPDRS (Movement Disorder Society Unified Parkinson?s Disease Rating Scale) model will assess motor and non-motor symptoms comprehensively. The analysis focuses on factors such as olfactory dysfunction, cognitive decline, motor issues, substantia nigra hyperechogenicity (via transcranial ultrasound), and lifestyle factors like physical inactivity and coffee consumption. Data from these groups will be compared with healthy controls to identify key differences, aiding early risk detection before clinical symptoms appear. Building on prior research and an established database of PD patients, their relatives, at-risk individuals, and healthy controls, this project aims to improve understanding of PD risk factors and develop effective prevention strategies. Objectives of the Project: 1. Validate and apply the MDS-UPDRS model to at-risk groups. 2. Conduct statistical analyses to identify key PD risk predictors. 3. Compare results across groups to uncover key differences and better understand PD development mechanisms. |
