PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease



Noyce, Alastair J, R'Bibo, Lea, Peress, Luisa, Bestwick, Jonathan P, Adams-Carr, Kerala L, Mencacci, Niccolo E, Hawkes, Christopher H, Masters, Joseph M, Wood, Nicholas, Hardy, John
et al (show 3 more authors) (2017) PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease. MOVEMENT DISORDERS, 32 (2). pp. 219-226.

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Abstract

<h4>Background</h4>A number of early features can precede the diagnosis of Parkinson's disease (PD).<h4>Objective</h4>To test an online, evidence-based algorithm to identify risk indicators of PD in the UK population.<h4>Methods</h4>Participants aged 60 to 80 years without PD completed an online survey and keyboard-tapping task annually over 3 years, and underwent smell tests and genotyping for glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 (LRRK2) mutations. Risk scores were calculated based on the results of a systematic review of risk factors and early features of PD, and individuals were grouped into higher (above 15th centile), medium, and lower risk groups (below 85th centile). Previously defined indicators of increased risk of PD ("intermediate markers"), including smell loss, rapid eye movement-sleep behavior disorder, and finger-tapping speed, and incident PD were used as outcomes. The correlation of risk scores with intermediate markers and movement of individuals between risk groups was assessed each year and prospectively. Exploratory Cox regression analyses with incident PD as the dependent variable were performed.<h4>Results</h4>A total of 1323 participants were recruited at baseline and >79% completed assessments each year. Annual risk scores were correlated with intermediate markers of PD each year and baseline scores were correlated with intermediate markers during follow-up (all P values < 0.001). Incident PD diagnoses during follow-up were significantly associated with baseline risk score (hazard ratio = 4.39, P = .045). GBA variants or G2019S LRRK2 mutations were found in 47 participants, and the predictive power for incident PD was improved by the addition of genetic variants to risk scores.<h4>Conclusions</h4>The online PREDICT-PD algorithm is a unique and simple method to identify indicators of PD risk. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Item Type: Article
Additional Information: publicationstatus: published
Uncontrolled Keywords: Parkinson's disease, prodrome, cohort, epidemiology, risk factors
Depositing User: Symplectic Admin
Date Deposited: 14 Feb 2019 10:23
Last Modified: 19 Jan 2023 01:03
DOI: 10.1002/mds.26898
Open Access URL: https://doi.org/10.1002/mds.26898
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3032820