Development of a stratification tool to predict Disease Modifying Treatment response in Paediatric Onset Multiple Sclerosis

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Multiple sclerosis (MS) is a devastating condition, which is rare in children. It is caused by the body's immune system destroying parts of the myelin sheath, a fatty protective covering of nerves in the brain and spine, which is essential for transmission of messages from the brain to the rest of the body. Currently there is no cure, and over time individuals accumulate progressive disability. In children and young people this can affect movement, vision and particularly their thinking. There has been an explosion in recent years in the treatments available, most of which have not been trialled in children. There are currently 14 different treatments available which aim to modify the body's inflammatory response. Choosing the right treatment for the individual child is difficult, as there are no tools to help us predict which medication is likely to work best for them. Much of the time paediatricians need to rely on adult data. MS in children though is different from that in adults; they have more relapses, more brain lesions and develop more learning problems than adults. The only paediatric trial so far completed, identified benefits and risks of treatment which are different from those seen in adults. This makes it crucial to gather information in children, rather than relying on information acquired in adults.I am a Paediatric Neurologist who specialises in MS. In this project, I will partner with Prof Ciccarelli, who in 2018 was awarded a NIHR Research Professorship, to develop a tool to predict the best medicine to use for the individual with adult MS, by using special mathematical models that learn from the individual MS profile (demographic and diet, lifestyle, clinical findings, specific blood tests, genetics and MRI images) and make prediction about the future. I will extend this goal to children, and together we will develop a tool to help guide treatment choice for any patient with MS, independently of their age. I will take this unique opportunity to focus on cognitive impairment in children with MS. MS is a highly specialised and complex condition in childhood, and NHS England has recently agreed to fund 5 Highly Specialist Services (HSS) across England, to ensure excellence in delivering care. I lead one of these services and will collaborate with the other centres. In this project, I will look at two groups: the first group is the existing cohort of 100 children with MS across England, the second group includes 80 children with newly diagnosed MS. Children who do not wish to start a medication will still have their data recorded and will be used as a control group. We will use tablet computers in clinic to record information about diet, lifestyle, exposure to sunlight and nicotine, amongst other parameters, as well as quality of life. We will also document their clinical examination and their educational performance and academic ability. We will take blood to look for markers of inflammation which might provide important clues. We will also record their relapses, to document how well controlled their MS disease activity is. All this information, together with repeat MRI scans acquired routinely as part of the NHS HSS, will be analysed by computer both separately and together with the adult data. We will use a tiered approach to identify factors which are likely to predict which medicine will work best for any one person with MS. All these data will be stored in a national registry, thereby providing valuable information on the long-term outcome for these young people in England. All the medications and any serious side effects will also be recorded on the database. This will allow us over time to identify early any unexpected safety concerns with the medications. The ultimate goal of the project is to learn about the individual treatment response and side effects in the clinical setting and to help the child and their parents choose the best medication for them as an individual.