Friday 4 November 2016

#ResearchSpeak: can we predict who will develop MS?

Proof-of-principle study to develop an MS risk score. #ResearchSpeak #MSBlog #MSResearch

In the following study on the 'MS endophenotype' we set out to study the feasibility of developing a MS risk score in the hope that we can identify a cohort of people from the general population at very high risk of developing MS. In summary, the algorithm, or risk score, we tested works. We were able to create a hierarchy of risk based on genetics (HLA-DRB1*1501), demographics (gender, month of birth) and environmental factors (smoking, history of IM, EBV serology, vD). In our model vD was not predictive simply because too many pwMS were on vD supplements. 

We now have to role out this risk score to the wider population to assess how it performs prospectively. We propose recruiting and following more than 100,000 people between the ages of 18 and 35 to see how reliable our risk score is at predicting who will develop MS or not. The ambition is to be able to identify at risk people to participate in MS prevention studies. What do you think? Is it worth pursuing MS prevention trials or should we simply stand by and watch whilst the incidence of MS increases and ever more people develop the disease? 


I would like to thank all  the participants who volunteered to participate in this study, the ABN and the MS Society of Great Britain and Northern Ireland for funding the study and Dr Ruth Dobson for tirelessly slaving away at the task in hand. 

Dobson et al. A Risk Score for Predicting Multiple Sclerosis. PLoS One. 2016 Nov 1;11(11):e0164992.

OBJECTIVE: Multiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI.

METHODS: 78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals.

RESULTS: There was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75-0.88).

INTERPRETATIONS: The risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies.

For more information on this study please read the following post:

Feb 18, 2011 ... Towards an endophenotype in multiple sclerosis. This study is recruiting people with MS who have brothers and/or sisters without MS, and ...

CoI: This study was performed by TeamG