Multiple sclerosis (MS) is an incurable progressive disease causing damage to the central nervous system. Clinical course varies enormously between patients and it is currently impossible to predict disease progression. Although there is no cure for MS, there are disease modifying therapies (DMT) which may improve the disease trajectory for some patients. Unfortunately, we cannot predict the optimum therapy for individual patients or their risk of suffering from adverse reactions to treatments.

 

We have established a unique cohort of clinically-verified and deeply-phenotyped subjects with MS through our Trajectories of Outcomes in Neurological Conditions (TONiC) study. We have baseline data on over 6000 subjects and over 2500 in longitudinal follow which we continue to grow on a weekly basis with a target of 5000 subjects with three time-point trajectories ('trilogies'), giving us unprecedented power to investigate the biological processes underlying MS progression. This knowledge will highlight targets for rational drug development and improve the prospects for safe effective therapies. We will also create the first UK MS biobank and bioresource to empower future MS researchers.

 

Our overarching aim is to discover the clinical, genetic and biological factors that influence MS trajectories. Our specific objectives are as follows:

 

Defining disease trajectories and progression
 

• Establish the deep phenotype of 5000 subjects with MS, each with at least 3 time points of data collection (trilogies).

• Discover predictors of MS progression through analysis of the multiple physical, psychological and social factors which are impacted by MS.

• Highly characterise a subset of the trilogies with clinical assessments, biomarker analysis and MRI brain/cervical spine

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Identifying the genetic determinants of progression
 

• Perform a genome-wide association study (GWAS) of disease progression in all 5000 trilogies using chip genotyping enabling the analysis of c. 8 million SNPs.

• Perform whole genome sequencing of patients showing the most benign and severe trajectories to explore the relevance of less common variation that cannot be assessed through chip genotyping.

• Replicate newly-discovered genome-wide significant associations in independent cohorts collected internationally.

 

Identifying molecular pathways and biomarkers linked to disease progression

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• Identify and characterise the transcriptional state of immune cell populations in the peripheral blood of MS patients.

• Identify cell populations that are linked to MS, which may play a role in disease progression.

• Identify regulatory miRNAs and metabolites in circulating blood that may be markers of MS progression.

• Identify multi-omics markers of MS progression by integrating data across the different workstreams.

 

Building a legacy resource

 

• Create a biobank comprising blood and urine samples from 5000 trilogies; plus peripheral blood mononuclear cells, plasma and MRI (in a subset of samples).