MRC TS Award: Defining and predicting variability in early Parkinson's disease using quantitative MRI

One of the biggest challenges facing developed countries in the 21st centaury is the increasingly aged population and rising life expectancy. In the UK nearly a quarter of the population will be aged 65 or over within 20 years. As a consequence, more people will be living with chronic, long-standing health problems. This poses significant challenges, particularly in healthcare, and will require a shift towards pre-emptive treatments designed to prevent or slow the progression of chronic diseases in order to cope with this changing demographic.

Parkinson's disease is a common degenerative disorder of the brain that becomes more likely with age. A combination of muscle stiffness, tremor and slow movements alert the clinician to its presence. These symptoms begin to be detectable once half of the nerve cells within a brain region called the substantia nigra have already died. Once diagnosed, disease progression is highly variable. About half the people diagnosed will develop significant problems within four years.

There is evidence that Parkinson's disease actually begins up to 20 years before it is diagnosed; it starts in a different part of the brain and progresses slowly causing more subtle problems. This intervening period is called "pre-clinical Parkinson's". During this period there are certain problems, such as loss of smell or certain sleep disturbances, which are more likely to be experienced by individuals with the condition. However, it is not currently possible to identify who amongst these individuals have pre-clinical Parkinson's or how quickly the disease will progress once diagnosed.

To address these questions, the Quantitative MRI for Anatomical Phenotyping in Parkinson's Disease project (qMAP-PD) was started in 2018 at the Wellcome Centre for Human Neuroimaging, UCL. This is a longitudinal study using non-invasive brain-scanning techniques to understand why Parkinson's disease is so variable, develop ways to predict how quickly the disease will progress based on an individual's brain structure and diagnose the condition during the pre-clinical phase.

The study was entirely dependent on in-person, face-to-face assessments, and therefore was significantly delayed by the impact of the COVID-19 pandemic. Recovery from this period has been complex, time-consuming and impacted a number of other factors that introduced additional delays. Despite these unprecedented challenges, the study has managed to recruited and assess over 250 individuals, and has now achieved follow-up assessments for many of these. In order to deliver on the original aims, a short period of additional support is required to analyse and publish this acquired data, allowing the original experimental aims to be met. By achieving these, strategies aimed at slowing the condition can be researched more accurately, and the disease can be better characterized within an individual, allowing current treatments to be tailored to their present and future needs.

The qMAP-PD study is a longitudinal observational study to understand phenotypic variability and disease progression in Parkinson's disease (PD) and related disorders. The original design involved three assessment sessions, two with MRI scanning, and aimed to recruit ~250 individuals across three key cohorts:

1. Early PD (<2y from diagnosis)
2. REM Sleep Behaviour Disorder (RBD)
3. Healthy controls, matched to the PD cohort

Combining quantitative MRI (qMRI), advanced in vivo histology and deep clinical phenotyping, the study aimed to answer:

1. Can in vivo quantitative disease staging be achieved in PD using qMRI?
2. What neuroanatomical features explain the clinical variability observed in PD?
3. Can future outcomes be predicted from a single baseline time-point?
4. Can qMRI detect PD during the pre-clinical phase of the illness?

The COVID-19 pandemic occurred midway through recruitment: Entirely reliant on face-to-face assessments and specifically powered to detect brainstem changes in PD, simply analysing the data to generate publications over lockdown would have been underpowered and limit the long-term cohort value. Therefore, outputs were delayed and the priority for recovery focused on data-collection: The study was restructured to include two time points only, achieved recruitment targets late 2021 and will complete follow-up January 2023.

This application for transition support will allow the analyses and outputs to be completed as planned. These will use advanced qMRI methods to map subcortical nuclei affected by PD, linking microstructural differences to phenotypic variability. These will provide ways to discriminate PD from ageing that can then be applied to the RBD cohort. Combined, this work has the potential to provide a quick, non-invasive means to diagnose pre-clinical PD, identify more homogenous subtypes, help tailor clinical decisions to individual trajectories and provide sensitive quantitative metrics for clinical trials.