Genomics – a new crystal ball for predicting the course of MS?

Multiple Sclerosis is a complex disease caused by interactions between genes
and the environment. We now know a
fair amount about how genetic variants influence the risk of developing MS
but we still know very little about how genes influence the course of the
disease. Are there specific gene variants which are associated with more
relapses and faster progression of disability?
To answer this important question, Bruce Taylor and
colleagues sequenced the entire genomes of 127 people who had experienced a
first clinical episode suggestive of MS
. The authors then focussed
on a specific set of 116 gene variants known to increase someone’s risk of developing
MS in the first place. Participants were followed up for 5 years to assess the
number of relapses, the rate of disability progression, and conversion to
clinically-definite MS. The aim of the study was to see if there was any
association between these 116 single nucleotide polymorphisms (SNPs = gene
variants) and the course of the disease over a 5 year period.
The authors divided up the SNPs into two categories – those located in
the human leukocyte antigen (HLA) genes, which code for the proteins the immune
system uses to recognise foreign particles, and those not. 7 non-HLA SNPs were
associated with conversion to MS and/or risk of relapse. But – and this is an
important but – none of these associations were individually statistically
significant. Combining these 7 SNPs into a composite genetic risk score was
predictive of conversion to MS and risk of relapse, suggesting that while the
effects of individual gene variants on the course of MS is small, the
cumulative effect of lots of these variants is important. People with 5 or more
‘risk’ gene variants were around 6x more likely to develop clinically-definite
MS over the study period compared to patients with 2 or fewer ‘risk’ variants.
A different set of 7 non-HLA SNPs was associated with disability
progression. Again, none of these associations were individually significant,
but were significant when combined into a genetic risk score. People with 2 or
fewer ‘risk’ SNPs had, on average, a yearly increase in EDSS score of 0.14,
compared to 0.62 for patients with 6 or 7 risk SNPs.
Of the 6 HLA SNPs assessed, the only significant association was between
B*44:02 and risk of relapse. This variant was actually protective
– it was associated with a lower risk of relapse than the general cohort.
There are some
very interesting observations made in this study. A particularly striking
finding was the complete dichotomy between genes associated with conversion to
MS or relapse and genes associated with disability progression. This
strengthens the argument that the pathways involved in relapses and disability
progression are quite separate. Another interesting observation is that variants
in a key MS risk gene, HLA-DRB1*15, were not associated with the clinical
outcomes assessed in this study. This is intriguing because earlier studies
have reported an association between HLA-DRB1*15 variants and the risk of
progressive disease
– ethnic differences between the study
populations may explain this discrepancy.  
For me the main message of this study is that gene variants probably do influence the course of
MS – while the contributions of individual SNPs might be small, the sum total
of a person’s ‘risk’ SNPs is likely to influence how the disease progresses. The
problem with this study, and with other studies aiming to do the same thing, is
that it is incredibly difficult to find statistically significant associations
between gene variants and clinical outcomes. This is because of two factors –
because the effects of individual variants is so small, and because these
studies have to look at so many gene variants. The problem with testing so many
gene variants is that it increases your chance of seeing false positives, or spurious
associations.  Why is this?
results of statistical tests of association are usually given as p values –
this expresses the probability that the association is not real, and is just
due to chance. Normally researchers call a result statistically significant if
the p value is less than 0.05, which means that there is less than a 5% chance
that the result is not real. However, if you do 20 statistical tests and get 20
p values of 0.05, there is a good chance that one of these associations will be
a false positive (as 20 x 5% = 100%). In this study, the researchers looked at
116 gene variants – if they accepted a p value of 0.05 as statistically
significant, they would get lots of spurious associations between gene variants
and outcomes. So, to adjust for this, researchers adjust the p value threshold
they count as significant depending on the number of statistical tests they are
doing. This is why so many of the associations reported in this study are not
individually significant.
So this study
suggests that the genetic influence on the course of MS is, predictably,
polygenic – i.e. a product of lots of ‘risk’ gene variants, none of which are
individually sufficient to cause the disease. As well as being a product of
multiple genetic factors, the course of the disease is clearly influenced by
all kinds of environmental factors, such as the disease-modifying therapies (DMTs)
used, vitamin D exposure, and potentially exposure to infectious agents like
We are still a
long way from being able to use this kind of genetic information in a clinical
setting. It would be great if we could use SNP data to predict who will benefit
from different types of DMT and who would benefit from early aggressive
treatment. Whilst this study does not provide this kind of information just
yet, it demonstrates that genomics could play an important role in caring for
people with MS in the future.
Background The genetic drivers of multiple sclerosis (MS) clinical course are
essentially unknown with limited data arising from severity and clinical
phenotype analyses in genome-wide association studies.
Methods Prospective cohort study of
127 first demyelinating events with genotype data, where 116 MS risk-associated
single nucleotide polymorphisms (SNPs) were assessed as predictors of
conversion to MS, relapse and annualised disability progression (Expanded Disability
Status Scale, EDSS) up to 5-year review (ΔEDSS). Survival analysis was used to
test for predictors of MS and relapse, and linear regression for disability
progression. The top 7 SNPs predicting MS/relapse and disability progression
were evaluated as a cumulative genetic risk score (CGRS).
Results We identified 2 non-human
leucocyte antigen (HLA; rs12599600 and rs1021156) and 1 HLA (rs9266773) SNP
predicting both MS and relapse risk. Additionally, 3 non-HLA SNPs predicted
only conversion to MS; 1 HLA and 2 non-HLA SNPs predicted only relapse; and 7
non-HLA SNPs predicted ΔEDSS. The CGRS significantly predicted MS and relapse
in a significant, dose-dependent manner: those having ≥5 risk genotypes had a
6-fold greater risk of converting to MS and relapse compared with those with
≤2. The CGRS for ΔEDSS was also significant: those carrying ≥6 risk genotypes
progressed at 0.48 EDSS points per year faster compared with those with ≤2, and
the CGRS model explained 32% of the variance in disability in this study
Conclusions These data strongly suggest
that MS genetic risk variants significantly influence MS clinical course and
that this effect is polygenic.

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  • Im somewhat intrigued by how so many people are born with the right combination of SNPs to have MS in one form or another…especially when we don't all have the exact same combination of mutations. What's the likelihood I would have ONE of these particular SNPs, let alone 7?

  • Hi Bennie, interesting points – you are right that lots of people do have some degree of genetic predisposition to developing MS, and certain people develop it because they have a combination of genetic predisposition and are exposed to the 'right' environmental triggers. The likelihood of having the 7 specific risk SNPs is pretty small, but the likelihood of having 1 or 2 is high. Everyone has about 10 million SNPs in their genome – some of the variants you have will be harmless, and unfortunately a few will be associated with a tiny increase in the risk of developing disease.

  • Thanks for this DrBenJ, interesting post. However I must confess as a layman I sometimes feel a bit worried and depressed when I read that there may not be a link between relapses and progression, because to me that seems to tactictly imply that even the most effective RRMS drugs – given that they basically work to reduce relapses – probably aren't going to stop or slow me becoming severely disabled in the end. If relapses and progression are sepearate processes, can aggressive treatment really change the outcome? After all tysabri and lemtrada failed in progressive trials. I appreciate that this research is still progress but it's scary to think that the current treatment paradigm might not help me in the long term.

    • We know that relapses are caused by the immune system entering the CNS from the blood and I will argue that the innate (microglia) immune system drives progression using differnt genetic pathways. eg. the genes controlling the magnitude of the immune response may be important in relapse but may not be relevant for progression as differnt cells are doing the business and it may be how the genes respond to insult that determine if you progress or not and these would be unrelated to anything driving relapse.

      So don't worry about the genetics yet.

      I would arguee however that relapses will condition the progressive disease so they are interlinked and blocking relapses and the damage they cause will limit the generation of the nervous environment that drive progression. Some may argue the genetic status influences how someone responds to the relapse and how they accumulate and repair damage.

      Can aggressive treatment change outcome…yes I think so because the long term outcomes of the responders treated with Alemtuzumab have a lower incidence of switch to SPMS than would occur with placebo, but we need to see what happens in the CARE-1/II population. I think that will give and answer.

      You say lemtrada and natalizumab failed in trials, yes they failed to halt progressive MS, but did they have any positive outcome? The loss of hand function was signficantly protected so it is not quite right to say failed, they failed in view of the primary outcome, but it was not inert. The alemtuzumab trials were more look see. However HSCT tells us that people can still progress if treatment is late and progressive disease has set in.

      Remember identical twins (when I asked George Ebers) do not always have the same disease course one can be RRMS and other can be PPMS so there is more to MS than just genes

  • Thanks DrBen!

    I guess you notice that perhaps environmental factors can "speak" a little higher in the onset of MS, genetics seems to be only part of the story …

    Why, in addition to lumbar puncture to check OCBs and neurofilament and own MRI, don't make the verification of vitamin D rate and IgG levels EBNA-1 when a routine check up is on or not a case of MS?

  • Hi Cinara – there are lots of biomarkers being looked at, but only some of these are useful as aids to guide prognosis and management. In terms of the details of EBNA-1 and vitamin D levels I'm not the expert, but to my knowledge these markers aren't that helpful in predicting how the disease will behave.

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