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

Noyce, AJ; R'Bibo, L; Peress, L; Bestwick, JP; Adams-Carr, KL; Mencacci, NE; Hawkes, CH; ... Schrag, A; + view all (2017) PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease. Movement Disorders , 32 (2) pp. 219-226. 10.1002/mds.26898. Green open access

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Abstract

Background A number of early features can precede the diagnosis of Parkinson's disease (PD). Objective To test an online, evidence-based algorithm to identify risk indicators of PD in the UK population. Methods 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. Results 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. Conclusions 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.

Type: Article
Title: PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/mds.26898
Publisher version: http://dx.doi.org/10.1002/mds.26898
Language: English
Additional information: © 2016 International Parkinson and Movement Disorder Society This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords: Science & Technology, Life Sciences & Biomedicine, Clinical Neurology, Neurosciences & Neurology, Parkinson's disease, prodrome, cohort, epidemiology, risk factors, SLEEP BEHAVIOR DISORDER, SCREENING QUESTIONNAIRE, PRODROMAL FEATURES, MARKERS
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/1539194
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