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Research paper
PREDICT-PD: Identifying risk of Parkinson's disease in the community: methods and baseline results
  1. Alastair J Noyce1,2,
  2. Jonathan P Bestwick3,
  3. Laura Silveira-Moriyama1,4,
  4. Christopher H Hawkes2,
  5. Charles H Knowles2,
  6. John Hardy1,
  7. Gavin Giovannoni2,
  8. Saiji Nageshwaran5,
  9. Curtis Osborne2,
  10. Andrew J Lees1,
  11. Anette Schrag5
  1. 1Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, London, UK
  2. 2Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
  3. 3Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
  4. 4Child Neurology Unit, Department of Neurology, University of Campinas, UNICAMP, Campinas, Brazil
  5. 5Department of Clinical Neuroscience, Institute of Neurology, Royal Free Campus, University College London, London, UK
  1. Correspondence to Dr Anette Schrag, Department of Clinical Neuroscience, Institute of Neurology, Royal Free Campus, University College London, London NW3 2PF, UK; a.schrag{at}ucl.ac.uk

Abstract

Objectives To present methods and baseline results for an online screening tool to identify increased risk for Parkinson's disease (PD) in the UK population.

Methods Risk estimates for future PD were derived from the results of a systematic review of risk factors and early features of PD. Participants aged 60–80 years without PD were recruited by self-referral. They completed an online survey (including family history, non-motor symptoms and lifestyle factors), a keyboard-tapping task and the University of Pennsylvania Smell Identification Test. Risk scores were calculated based on survey answers. Preliminary support for the validity of this algorithm was assessed by comparing those estimated to be higher risk for PD with those at lower risk using proxies, including smell loss, REM-sleep behaviour disorder and reduced tapping speed, and by assessing associations in the whole group.

Results 1324 eligible participants completed the survey and 1146 undertook the keyboard-tapping task. Smell tests were sent to 1065 participants. Comparing the 100 highest-risk participants and 100 lowest-risk participants, median University of Pennsylvania Smell Identification Test scores were 30/40 versus 33/40 (p<0.001), mean number of key taps in 30 s were 55 versus 58 (p=0.045), and 24% versus 10% scored above cut-off for REM-sleep behaviour disorder (p=0.008). Regression analyses showed increasing risk scores were associated with worse scores in the three proxies across the whole group (p≤0.001).

Conclusions PREDICT-PD is the first study to systematically combine risk factors for PD in the general population. Validity to predict risk of PD will be tested through longitudinal follow-up of incident PD diagnosis.

  • Parkinson×s Disease
  • Smell
  • Sleep Disorders
  • Scales
  • Epidemiology

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