Defining and predicting variability in early Parkinson's disease using quantitative MRI

Lead Research Organisation: University College London
Department Name: Institute of Neurology

Abstract

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.

This work seeks to use 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. By achieving these aims, 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.

Technical Summary

Aims:
This work will recruit individuals with established PD, possible prodromal PD and healthy controls into a longitudinal MRI study to answer these principal questions:

1. Can in vivo quantitative disease staging be achieved in PD using quantitative MRI (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?

Through these, a quick, non-invasive way to quantify patterns damage in PD will be developed.

Methodology:
This work will recruit three cohorts:
- Healthy controls
- Idiopathic PD
- Rapid Eye Movement Behavioral Disturbance
Both clinical groups will undergo assessment and MRI scanning at baseline and two further annual assessments with repeat scanning at the final time-point. At baseline, the controls will be matched to the PD cohort, and a proportion of this group will undergo the same follow-up as the clinical cohorts. Detailed clinical assessment will be performed in all groups at each time-point.

Scientific opportunities:
This work is specifically powered to detect changes within brainstem structures involved at the earliest stages of PD, using imaging methods developed to allow subcortical nuclei affected by PD to be mapped in vivo. This allows a priori hypotheses based on post-mortem data, linking clinical variability to anatomical differences in PD, to be tested and developed further to predict future outcomes of disease. These approaches will also provide an accurate way to discriminate PD from normal ageing, that can then be applied to the RBD cohort to detect pre-clinical PD. Combined, this work has the potential to provide a quick, non-invasive means to diagnose pre-clinical PD, identify more homogenous PD subtypes, help tailor clinical decisions to individual patient trajectories and provide sensitive quantitative metrics for clinical trials.

Planned Impact

Who will benefit from this research?
Groups who would directly benefit over the short-medium term include:

- Patients with established PD
- Patients with possible prodromal PD
- Academics engaged in PD research and clinical trial design
- Clinicians with an interest in movement disorders
- Neuroimaging researchers
- Academics and clinicians with an interest in neurodegenerative diseases.
- Academic and clinicians with an interest in accurately defining in vivo functional anatomical regions e.g. functional neurosurgeons for deep brain stimulation targeting

Over the longer term, this work fits into the published NHS and government strategies for managing an increasing aged population.

How will they benefit from this research?
Short Term (2018-2023)
The immediate benefit of this work will be achieved through teaching and training, both of local interested researchers and also the research assistant for this project. Additionally, the study motivation and rationale would be discussed with local patient groups to gain feedback into the experiment design and data-sharing proposals.

Over the grant, the results would be presented to patient groups, specialist movement disorder meetings and international conferences. The techniques would be more widely disseminated via teaching on the SPM course, and through the release of open-source tools and datasets. The Internet would be used to disseminate the clinical findings, methodological advances, and available open-source resources. In addition to the study website, these would also be promoted via related online forums (e.g. dataset releases via the NITRC or clinical findings via the PREDICT-PD blog).

Finally, over the first two years of the fellowship I will develop a public engagement event centered on the wider issues and practical techniques of preclinical diagnostics in Neurodegeneration. Specifically, this will be developed in conjunction with allied professionals (e.g. genetics and dementia), funding stakeholders, policy-makers and patient groups (e.g. Parkinson's UK Network, Fifth Sense). The aim would be to organize this event for the third year (2020), allowing it to provide a basis for follow-up grant applications and foster wider collaborate efforts.

Medium Term (2023-2028)
In the medium term, this proposal will form the foundation for future work targeted towards understanding the complex interactions contributing to clinical variability in vivo. This will eventually require close collaborations between allied research disciplines such as genetics, epidemiology, molecular and ex vivo imaging and those engaged in clinical trials, and I will seek to foster these over this period. Taking advantage of the availability of 3T MRI and improved inter-site reliability of the qMRI acquisitions, I will work to disseminate the methods used in this proposal and promote larger multi-center collaborations. Finally, I plan to continue to develop and contribute open-source resources through my work to accelerate development in this field.

Long term (>2028)
Developing strategies aimed at slowing disease progression is an essential step, identified by the "NHS - Five Year Forward View", to manage the increasing numbers of individuals surviving to old age. Aligning with this aim, my research seeks to identify individuals during the earliest stages of disease, better understand clinical variability to more accurately phenotype disease and predict its trajectory in individuals and provide quantitative biomarkers to monitor progression in the absence of motor signs. By translating these tools, together with collaborators, I aim to help develop a clinical service designed to assess, investigate, diagnose and stratify pre-clinical and early PD. This will allow appropriate, patient-specific disease modifying therapies to be developed and commenced early in the disease course, prior to significant loss of neural tissue.
 
Title Patterns of Perception 
Description This was a collaborative project between a group of individuals with Parkinson's, Central Saint Martins, English National Ballet, University College London and artist Ruairiadh O'Connell. In 2019, a series of workshops ranging from textiles to dance and art took place to explore and understand the experience of Parkinson's. Alongisde those workshops, participants created visual diaries to record and reflect their daily lives. We worked together to create a new vocabulary based on the reccurring emotions and coping strategies that ranged from apathy and acceptance to humour. In response participants translated this text and its motifs into large textile banners and co-designed their own patterns. Patterns of Perception interweaves science, dance and visual arts to pilot new approaches: musical spiral drawing, visual responsive ballet and hybrid painting-dancing practices. We also created a five minute video capturing the process: https://youtu.be/SesG1EkBztQ 
Type Of Art Artistic/Creative Exhibition 
Year Produced 2020 
Impact 1. Public facing window display at CSM for 8 weeks 2. Art exhibition at English National Ballet planned for May 2020, running for 8 weeks 3. PPI event postponed due to COVID-19, that would bring together scientists and individuals with PD - Plan to rearrange 
URL https://youtu.be/SesG1EkBztQ
 
Description Neuroimaging of Movement Disorders
Geographic Reach Local/Municipal/Regional 
Policy Influence Type Influenced training of practitioners or researchers
 
Description SPM: Anatomical brain analysis
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
 
Description UCL Knowledge Exchange and Innovation Fund
Amount £14,835 (GBP)
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 03/2019 
End 03/2020
 
Description UCL Movement Disorders Centre Funding
Amount £57,810 (GBP)
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 02/2019 
End 05/2020
 
Description UCL RCIF Capital Expenditure Fund
Amount £22,143 (GBP)
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 12/2018 
End 07/2019
 
Title Brainstem Automated Segmentation Toolbox (BAST) 
Description Currently updating this with new data via qMAP-PD project. Will be formally embedding the brainstem methodolgy into a toolbox for SPM12 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2019 
Provided To Others? No  
Impact Work in development. 
 
Title Improved denoising for qMRI 
Description Currently collaborating with Professor John Ashburner and his PhD student Mikael Brudfors to develop this 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2019 
Provided To Others? No  
Impact In development 
 
Title qMAP-PD: Database 
Description Creating the qMAP-PD database, currently housed in a REDCAP infrastructure. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? No  
Impact Currently supporting ongoing study. 
 
Description Dr Sonia Gandhi 
Organisation University College London
Country United Kingdom 
Sector Academic/University 
PI Contribution We are collaborating by developing induced pluripotent stem cells in the qMAP-PD cohort. I am a named collaborator on her MRC senior clinician scientist award.
Collaborator Contribution We will be taking skin biopsies from 30 PD participants for iPSC. I will scan genetic kindrids who already have iPSC lines.
Impact We have applied for joint funding to a few sources to develop a combined program bridging deep phonemics with iPSC technologies. Dr Gandhi was awarded her MRC senior clinician scientist award, where one of the work packages was this work.
Start Year 2019
 
Description Dr Thomas Foltynie 
Organisation National Hospital for Neurology and Neurosurgery
Department Unit of Functional Neurosurgery
Country United Kingdom 
Sector Hospitals 
PI Contribution Co sponsor for my MRC grant proving clinical support, advice and mentorship.
Collaborator Contribution As above
Impact Pending
Start Year 2012
 
Description PREDICT-PD: Dr Alastair Noyce 
Organisation University College London
Department Institute of Neurology
Country United Kingdom 
Sector Academic/University 
PI Contribution I am collaborating with Dr Noyce to identify individuals during the pre-clinical phase of Parkinson's Disease for the qMAP-PD study
Collaborator Contribution Currently recruiting a cohort of Rapid Eye Movement Behavioural Disorder.
Impact Not yet applicable
Start Year 2016
 
Description Professor Bogdan Draganski 
Organisation University of Lausanne
Department Neuroimaging Research Laboratory (LREN)
Country France 
Sector Academic/University 
PI Contribution Due to technical problems, the Neuroimaging group at LREN in Lausanne was approached to carry out the data collection. Together we designed a 1h optimised MR sequence. We are currently collecting the MR data for patients and controls.
Collaborator Contribution Patient recruitment. Collection of MRI data.
Impact Data collection ongoing.
Start Year 2015
 
Description Patterns of Perception: Understanding Parkinson's better through Arts and Science Research 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Patterns of Perception: Understanding Parkinson's better through Arts and Science Research

'We need to tell the story. We really do.'
Margaret Stone, participant

In the UK, two people every hour are diagnosed with Parkinson's, a progressive neurological condition. There is a discrepancy between what people think Parkinson's disease is and the actual experience of individuals living with the condition. As one participant said: "I have got something to say if anybody wants to listen." Patterns of Perception aims to help us better understand life lived with this disease. It is a collaborative project between a group of individuals with Parkinson's, Central Saint Martins, English National Ballet, University College London and artist Ruairiadh O'Connell.

In 2019, 20 individuals with Parkinson's disease attended a series of workshops ranging from textiles to dance and art took place to explore and understand the experience of Parkinson's. Alongisde those workshops, participants created visual diaries to record and reflect their daily lives. We worked together to create a new vocabulary based on the reccurring emotions and coping strategies that ranged from apathy and acceptance to humour. In response participants translated this text and its motifs into large textile banners and co-designed their own patterns.

Patterns of Perception interweaves science, dance and visual arts to pilot new approaches: musical spiral drawing, visual responsive ballet and hybrid painting-dancing practices. From brain scans to 3D dance scans, participants engaged openly and courageously with every creative challenge.

The output of this work was an 8 week, public facing window display at Central St Martins (daily footfall ~5000 people) that will then move to the English National Ballet. We had to postpone a larger related PPI event bringing together a diverse range of scientists and individuals with PD (~250) due to the COVID-19 outbreak. We plan to re-arrange this when circumstances permit, but are still holding a smaller event for the participants who helped create the display.



Exhibited artwork and diaries created by:

Edward Gretton, Martin Kerans, Sara Moore, Anita Patel, Anne Prest, Kathy Read,
Janet Roberts, Margaret Stone and other participants who would like to remain anonymous.
Year(s) Of Engagement Activity 2020
URL https://www.arts.ac.uk/colleges/central-saint-martins/whats-on-at-csm/window-galleries/patterns-of-p...