Noyce, AJ; (2016) Identifying Subjects At Risk of Parkinson’s Disease in the Community: PREDICT-PD. Doctoral thesis , UCL (University College London).

Preview

Text Noyce_thesis corrected 9.2.16.pdf.COMBINED.pdf Download (28MB) | Preview

Abstract

There has been great interest in a definable prodromal period of Parkinson’s disease (PD), which is thought to be characterised by non-motor manifestations. In preparatory work, an extensive review of early non-motor features and risk factors was undertaken to develop a preliminary algorithm to identify subjects at increased risk of PD. A website was configured and keyboard-tapping test developed to aid in risk-stratifying subjects for future PD. This thesis first documents the validation of the keyboard-tapping test in PD patients and healthy controls, before its use alongside objective smell testing and a questionnaire formulated to assess early non-motor features and risk factors, all of which were delivered via the internet. The thesis describes the recruitment at baseline of over 1,300 healthy older people and annual follow-up assessments with the questionnaire, smell test and tapping test, which comprise the preliminary screening algorithm. Each year those estimated to be at higher risk were compared to lower risk subjects in terms of intermediate markers (smell loss, sleep disturbance and finger tapping speed) and differences between extremes of risk have been observed, consistent with the notion that higher risk subjects possess early features of PD. Selected higher and lower risk subjects were further investigated to determine whether there were differences in the frequency of genes associated with PD (GBA and LRRK2), and a proportion of subjects have been scanned using transcranial sonography and 123I-FP-CIT SPECT to determine whether there were imaging differences between extremes of risk. The thesis concludes by demonstrating that higher risk subjects were more likely to be diagnosed with PD during follow-up over 3 years and proposes further lines of enquiry that can be followed, building on the work undertaken to-date.

Download activity - last month

Export as XMLCSVJSON

Download activity - last 12 months

Export as JSONCSVXML

Downloads by country - last 12 months

Export as JSONCSVXML

Archive Staff Only

View Item