Approved research

Refining an algorithm to identify individuals at the prediagnostic phase of Parkinson's disease

Lay summary

Primary aim: To refine and re-validate an algorithm using risk and prodromal markers for identification of increased risk for Parkinson's disease. Early diagnosis of and identification of risk for Parkinson's disease We have previously developed an algorithm to identify groups of individuals with increased risk of Parkinson's disease in the general population. A range of data gathered in the UK Biobank project will be used to validate the algorithm and improve its predictive value by inclusion of additional demographic and clinical factors and risk factors for Parkinson's disease. We will do this by: 1) Application of the previously developed algorithm to one half of the UK Biobank dataset using the identified risk and prodromal markers. 2) Further exploration for additional factors within UK Biobank data which are associated with new diagnosis of Parkinson's disease, followed by incorporation of these into the algorithm. 3) Application of the modified algorithm to the remaining dataset for validation of the modified algorithm Full cohort (clinical data)