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Information for participants

For more information on the study, what participation involves, how you can take part and to meet our team, please click on the relevant section below.

What is the aim of the study?

Multiple Sclerosis (MS) is a chronic condition that affects people at all ages but people are more often diagnosed at a young age.  There are over 100,000 people with MS in the UK.  There is no cure for MS and patients experience occasional bouts of symptoms, called relapses.  There are 13 licensed drugs that reduce the risk of MS relapses but doctors cannot predict which of these will work best for an individual.  The decision about which drug to give to a patient is currently very complicated and is based on personal preference.  Many elements that may influence treatment response, such as genetic factors, blood biomarkers, MRI markers etc are not taken into account when choosing a medication.  Medications are changed only when a new relapse occurs.  This approach is severely suboptimal for the patient, the doctor and the NHS. 

The aim of this study is to develop a computer tool that predicts whether an individual patient will respond to a medication by using special mathematical models that learn from the patient's individual MS profile and make predictions about the future.  This is a crucial step towards "personalised medicine", which means to be able to prescribe the right medication for the right patient.

What is involved?

As part of your clinical care you will be coming back to the hospital for routine follow-ups with clinical assessments and MRI scans.  If you consent to take part in the study, in addition to your routine clinical care, we will ask you to complete a few questionnaires, undergo a slightly longer MRI scan of your brain and spine and to provide a small amount of extra blood for genetic testing and immunology research. 

Participation in the study will not change the choice of your medication and you will start the treatment which has been chosen together with your neurologist as planned. You are also able to change medication while on the study if this is deemed appropriate by your clinical care team.

The design of the study includes a baseline visit (your first visit), with clinical and MRI assessments, and follow-up visits after 6 months and 18 months. The baseline and 18-month visits are routine clinical care follow-up appointments which will be just slightly longer to allow for the research elements.  The 6-month follow up scan is a new time point which we have included because we want to see whether we can pick up early clinical and MRI changes that can predict the individual treatment response. There will be as many breaks as you like during these visits and we will try to make you as comfortable as possible.

At each visit the same clinical assessments, MRI scans and questionnaires will be collected. These assessments will chart your physical condition but clinical questionnaires will also give us information on factors such as your progress, quality of life, diet and wellbeing.

The blood tests for genetic testing will only be done at the baseline visit, since genes do not change over time. The extra blood for neurofilaments and neuroimmunology research, which looks at how the immune system is affected in neurological conditions such as MS, will be collected at each time point at the same time as your routine blood tests, where possible.

The MRI scan obtains pictures of your brain and spinal cord using a strong magnetic field and radio waves. The clinical care component of the MRI requires 10 minutes of actual scanning, rest breaks are allowed as needed. For the baseline visit only, we acquire an extra 20 minutes of scanning, a total scanning time of 30 minutes. This would mean a baseline MRI appointment of around 45 minutes to an hour, but for the other visits we expect it to be approximately 30 minutes with breaks. If you are unable to undergo an MRI scan this will be excluded.

The Clinical Assessment will be very similar to what you would have in a routine neurology clinic appointment and takes around 20 minutes. We will ask you some questions about your health and will then undertake a physical examination, during which we will test your vision and assess movement and sensation throughout your body. We may also measure your walking speed and assess how nimble your arms are.

The Neuropsychological Assessment will test your memory and thinking and assess your mood. To do this, we will ask you to have a go at some memory tests, sums, a few puzzles, and ask you a little more about your mood. This will take about 30 minutes, with rest breaks as needed.

Blood Samples will be taken for the purpose of the study. The total amount of blood taken is a couple of teaspoons.  Your study samples will be stored in a registered Human Tissue Act-licensed biobank (a secure place for future use) for further testing including DNA analysis, immunology testing and neurofilaments levels.

How can I take part?

Anyone over the age of 6 years who has been diagnosed with any type of MS and who is about to start a DMT (disease modifying treatment) is eligible to take part.  Children under the age of 17 can give assent to take part but, for legal reasons, consent must also be given by a parent or legal guardian.

If you are interested in taking part or would like to know more about the study, please speak to your consultant or MS specialist nurse or look out for a member of the research team when you attend your clinic appointments. You can also email us (uclh.pitms@nhs.net) or call us on 07976 846695.  Once you have had a chance to read through the study information sheet and ask any questions you may have, you will be consented to take part in the study.  

Study Information Sheets

Where to find us

MS Clinics - UCLH

If you are interested in taking part in the study but have not yet consented to participate, you can find us in the MS clinics in the National Hospital for Neurology and Neurosurgery (NHNN) on weekdays (particularly Tuesdays).  Please seek out a member of the PITMS team if you have any questions or are interested in taking part in the study.

MS Clinics - Neuroimmunology Centre, Great Ormond Street Hospital

MS clinics for paediatric patients are run on Wednesdays and Fridays at the Neuroimmunology Centre at GOSH.  If you are interested in taking part in the study but have not yet consented to participate,  please look out for Dr. Cheryl Hemingway, Dr. Yael Hacohen or Specialist Nurse Katie Hanson if you have any questions or are interested in taking part in the study.

MRI - UCLH

If you have been booked in for your MRI scan, please come to the Institute of Neurology, Queen Square House, Queen Square, London, WC1N 3BG and report to reception.  A member of the study team will then come to meet you and accompany you to the MRI suite.  For a map of the Institute of Neurology, please click here.

Contact Us

uclh.pitms@nhs.net

07976 846695

Meet the Team

UCL and UCLH

Professor Olga Ciccarelli, Principal Investigator

Dr Yael Hacohen, Co-Investigator

Professor Parashkev Nachev, Co-Investigator

Professor Daniel Alexander, Co-Investigator

Professor Henry Houlden, Co-Investigator

Professor Henrik Zetterberg, Co-Investigator

Dr Sarmad Al-Araji, Clinical Research Fellow (2019 - 2022)

Dr Alessia Bianchi, Clinical Research Fellow

Alvin Zapata, Research Nurse

Dr Le Zhang, Research Associate – Computational Imaging (2019 - 2022)

Dr Baris Kanber, Senior Research Fellow – Machine Learning

Amber Strang, Study Coordinator

 

Great Ormond Street Hospital

Dr Cheryl Hemingway, Site Principal Investigator

Dr Omar Abdel-Mannan, Clinical Research Fellow

Katie Hanson, Clinical Nurse Specialist

 

Evelina Children’s Hospital

Dr Ming Lim, Site Principal Investigator

 

Birmingham Women’s & Children’s Hospital

Dr Evangeline Wassmer, Site Principal Investigator

The science behind the study

Magnetic Resonance Imaging (MRI)

MRI scan images will be processed and analysed not only to track the potential progression of your MS whilst you are on your medication but also to “teach” a computer programme to recognise lesions in your central nervous system, which are characteristic of MS.

Analysis of your scan images will be undertaken by our team in collaboration with Professor Parashkev Nachev, Professor of Neurology, supported by the NIHR UCLH BRC and Wellcome Trust and the Centre for Medical Image Computing at UCL, which is led by Professor Daniel Alexander, Professor of Imaging Science.

Genetics

We know that there are certain genetic markers that can predict response to certain disease modifying treatments (DMTs).  We also know that certain genes are associated with particular types of MS such as progressive MS and relapsing onset MS.   

By analysing participant blood samples, we will be able to learn more about the relationship between our environment (exposures) and our personal susceptibility to disease (genes). We may also come up with genetic tests that predict a positive response to a medication.

The genetic testing will be undertaken at the UCL Institute of Neurology by Professor Henry Houlden, Professor of Neurogenetics, and his team. 

Neurofilaments in Serum

The neurofilaments represent the structure that supports the neurons (nerve cells).  An increased level of neurofilaments in the blood indicates that there has been a large amount of neuronal loss. This may indicate that a particular treatment has not been effective and in future could help patients to avoid taking medications which are not necessary.

Serum is the clear liquid part of blood minus the agents which clot blood.  Blood samples will first be processed in our lab to separate the serum from the blood cells.  They will then be frozen and stored until the end of study recruitment when the concentration of neurofilaments in each sample from each visit will be analysed by Professor Henrik Zetterberg, Professor of Neurochemistry, and his team.

Machine Learning

All of the data collected over the course of the study including the results of clinical assessments, individual patient information such as age, gender, diet etc., MRI scan images, genetic biomarkers, neurofilament levels etc. will be combined.  The combined data will then be programmed into a high-dimensional model which will be tested and retested to determine its accuracy at predicting individual participant responses to particular treatments.

This aspect of the study will be undertaken by Dr Arman EshaghiDr Le Zhang and Dr Baris Kanber, with additional input from Professor Nachev’s team.

Publications

Financial Times, June 2019

NIHR UCLH BRC News, June 2019

Abdel-Mannan O, and the UK-Childhood Inflammatory Disease Network. Use of Disease-Modifying Therapies in Pediatric Relapsing-Remitting Multiple Sclerosis in the United Kingdom. Neurol Neuroimmunol Neuroinflamm. 2021 May 21;8(4):e1008. doi: 10.1212/NXI.0000000000001008.

Al-Araji S, Bianchi A, Eshaghi A, et al, …Ciccarelli O. Assessing predictors of NEDA in RRMS patients initiating dimethyl fumarate in a real-world setting. P113. Association of British Neurologists (ABN) 2022.

Al-Araji S, Jha A, Zhang L, et al, …Ciccarelli O. Bayesian prediction of individualised treatment response in multiple sclerosis. ECTRIMS October 2022. Selected for poster award.

Moccia M, Al-Araji, Zhang L, et al…, Ciccarelli O. Comparing clinical and radiological effectiveness of disease modifying treatments in the real-world. O955. ECTRIMS October 2022.

Eshaghi A, Young AL, Wijeratne PA, et al…, Ciccarelli O. Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data. Nat Commun. 2021 Apr 6;12(1):2078. doi: 10.1038/s41467-021-22265-2. (*)

Eshaghi A, Wijeratne P, Oxtoby N, et al…, Ciccarelli O. Predicting personalized risk of disability worsening in multiple sclerosis with machine learning. Nat Commun. 2022. Major revisions requested. (*)

Zhang L, Tanno R, Bronik K, et al. Ciccarelli O, Alexander DC. "Learning to segment when experts disagree." International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 179-190. Springer, Cham, 2020.

Zhang L, Tanno, R Xu MG, Ciccarelli O, Barkhof F, Alexander DC. "Disentangling Human Error from the Ground Truth in Segmentation of Medical Images." 34th Conference on Neural Information Processing Systems (NeurIPS 2020).