Approved Research

Understanding the role of genetics in multiple sclerosis and associated pathologies

Lay summary

Multiple sclerosis (MS) is the most common, disabling nervous system disease in young adults. In MS, the immune system attacks the brain and spinal cord, and current treatments all rely on switching off some part of the immune system. Our research projects are aimed at better understanding the genetics of MS, with the ultimate goal being the development of treatments aimed at protection and repair of nerve cells, rather than immune suppression.

Genetics plays an important role in MS risk. 'Case-control' studies have helped identify some of the population-level genetic risk factors for MS but can't provide the kind of genetic information that leads to new treatments.

Family studies, gene-based methods and the study of evolutionary genomics provide new approaches for gene identification in MS. Families allow us to use 'precision' or personalised medicine approaches to pinpoint specific genetic differences that might lead to MS development.

This project studies the genomes of families and individuals with MS to determine why some people are more susceptible to nerve damage following the immune attack. We also study why some populations are more at risk of developing MS, and how that might be driven by genetic variation.

In Aim 1 we will study families with an apparent enrichment of MS cases to identify rare harmful variants that may relate to MS risk.

In Aim 2 we will delve deeper into the function of variants and genes identified in MS case-control cohort data.

In Aim 3 we will examine the evolutionary and environmental causes of the pattern that is observed in some populations where the risk of developing MS is higher further from the equator.

The genetic changes identified through these studies will be investigated in population data, such as UK Biobank, to determine how these genes function and what other relevant biological processes they may influence. The ability to extend these investigations into population data helps to fast-track the identification of potential drug targets that can be screened in our human cell-based preclinical models, ultimately providing much needed information for treatments targeted towards protection and repair of nerve cells.