This review looked at the many biomarkers for MS that have been investigated. Biomarkers can be used in diagnostic tests and as measures of response to treatment or of progression. The review shows that biomarkers have huge potential but much work is still required before reliable tests will be available.
Wouldn't it be nice if there was a simple test to diagnose MS? And another one to measure how well someone is responding to their treatment? Perhaps even a third, that could measure the stability or progression of the condition? This is where biomarkers come in.
A biomarker is a measurable biological feature that can be used to monitor the presence or progress of a disease or the effects of treatment.
Tests using biomarkers can be easy to carry out or more high tech. An example of a biomarker is measuring someone's pulse as this tells you about the functioning of their heart. The level of electrolytes in the blood are measured and used to monitor the functioning of organs including the kidney. Other examples include using x-rays to visualise structures in the body or measuring levels of PSA (prostate specific antigen) when screening for prostate cancer
In MS, there is a great deal of interest in finding biomarkers that could be used in simple reliable tests.
How this study was carried out
This research paper is a review of a large amount of research on biomarkers in MS. It lists the most important characteristics of a biomarker and gives an up to date summary of the most promising ones along with a critique of their potential.
What was found
Characterising the biomarkers identified so far
The pathophysiology of MS is extremely complex and includes all the outward signs and symptoms of the condition. These correspond to the underlying biological and physical changes caused directly by MS. This complexity gives scope for a wide range of biomarkers with the potential to measure many different things.
To deal with the large amount of information already published, the authors sub-grouped all the potential biomarkers for MS into six categories:
- diagnostic biomarkers
- biomarkers of phenotypical expression
- biomarkers of demyelination, neuroinflammation, relapse
- biomarkers of axonal loss, neurodegeneration
- prognostic biomarkers, biomarkers of disability progression
- biomarkers of therapeutical response
The biomarkers were further sub-categorised into three:
- genetic/immunogenetic: biomarkers specified via genomics and immunogenetic techniques
- laboratorial: all other biomarkers that can be measured in body fluids
- imaging: biomarkers provided by imaging techniques.
The authors also graded each biomarker and commented on how well each biomarker reflected the category it had been placed in (for example, if it was categorised as a diagnostic biomarker, was it likely to be a good marker for diagnosis?). The applicability of a biomarker for MS was judged using the following criteria:
- biological rationale: how well did the biomarker correspond with the particular pathogenic mechanism?
- clinical rationale: how accurately did the biomarker match clinical status?
- predictability of initiation, reactivation, or progression of MS, or ability to differentiate MS from other demyelinating diseases, like neuroMyelitis optica (NMO): how well did the marker reflect the phases of MS and distinguish MS from other related conditions?
- sensitivity and specificity: did the test work on a small amount of material and how often did false negative or false positive results occur?
- reproducibility of a result: was the test reliable?
- practicality of the method: was it an easy or complex and/or time consuming test to carry out?
- correlation with therapeutic outcome: did the test accurately reflect the negative and positive effects of a therapy?
- correlation with prognosis and disability - the latter being objectively measured by instruments such as the Expanded Disability Status Scale (EDSS): how well did the marker predict the way that someone's MS was going to develop?
You can see the table of results that was generated using the above approach, with a huge array of possible biomarkers here.
The research paper is very detailed and the full text is available online. Below is a summary of some of the key points.
Biomarkers might be measured in the following:
- cerebrospinal fluid (CSF)
- MRI scans
Details are available in section 2 of the full text of the paper
Possible measuring techniques include:
- Enzyme-Linked Immunosorbent Assay (ELISA)
- Flow cytometry
- Polymerase chain reaction (PCR)
- Western blotting
- Isoelectric focusing
- "-Omics" technologies including genomics and proteomics.
Detailed descriptions of these techniques are available in section 3 of the full text of the paper
Some of the biomarkers with potential include:
HLA: Recent research has suggested that many genes play a part in MS, with polymorphisms of HLA playing the primary role. HLA (the human leukocyte antigen system) is a group of genes that allows the immune system to distinguish between foreign invaders and the body's own tissue. Certain variants of HLA seem to increase susceptibility to MS, including allowing early onset and possibly also earlier progression.
Oligoclonal bands in CSF: in MS, the level of antibodies in the cerebrospinal fluid (CSF) is higher than normal and they can be seen as bands in laboratory tests. Oligoclonal bands show significant potential as markers of immune activation. Their diagnostic sensitivity is high but they are not good at differentiating MS from other inflammatory disorders of the CNS.
Vitamin D: this may be a biomarker of neuroprotection. The possible role of low vitamin D in susceptibility to MS has been shown in many epidemiological studies where higher latitude and lack of sun exposure correlates with increased risk for developing MS.
Optical Coherence Tomography (OCT): this is a noninvasive technique which uses infrared light through the pupil of the eye and detection of its reflection from the retina. Retinal nerve fiber layer (RNFL) thickness can then be estimated and thinning of this layer can be used as a reliable biomarker of axonal loss which correlates adequately with brain atrophy.
Magnetic Resonance Imaging (MRI): MRI is already used as a biomarker for neuroinflammation but is much less useful as a marker of neurodegeneration or disability progression.
What does it mean?
This review provides a comprehensive overview of the research so far into biomarkers for MS. The list of candidates is extremely long and some biomarkers, like oligoclonal bands and MRI, are already in clinical use.
However, there is a great need for much better biomarkers. For example, it would make a huge difference to people with symptoms suggesting MS if they could have a quick and simple diagnostic test that reliably gave a positive or negative answer rather than the often long process of diagnosis that occurs at the moment. Similarly, it would help if there was a good test to show that a DMT (disease modifying treatment) was working rather than waiting to see if the number of relapses went down. If the test showed that treatment was not effective, then someone could switch to another form of treatment much sooner.
In conclusion, biomarkers have huge potential and there is a wealth of research taking place, but much work is still required before reliable tests will be available for people with MS and for those who have symptoms that suggest that they may have MS.
Research by topic areas...
Symptoms and symptom management
Collongues N, Vermersch P.
Multiple sclerosis spasticity: 'state-of-the-art' questionnaire survey of specialized healthcare professionals.
Expert Rev Neurother. 2013 Feb;13(3 Suppl 1):21-5.
Disease modifying treatments
Paolicelli D, D'Onghia M, Pellegrini F, et al.
The impact of neutralizing antibodies on the risk of disease worsening in interferon ß-treated relapsing multiple sclerosis: a 5 year post-marketing study.
J Neurol. 2013 Feb 17. [Epub ahead of print]
Mori F, Kusayanagi H, Buttari F, et al.
Early treatment with high-dose interferon beta-1areverses cognitive and cortical plasticity de?cits in multiple sclerosis.
Funct Neurol. 2012 Jul-Sep;27(3):163-8.
Menzin J, Caon C, Nichols C, et al.
Narrative review of the literature on adherence to disease-modifying therapies among patients with multiple sclerosis.
J Manag Care Pharm. 2013 Jan;19(1 Supp A):S24-40.
Miller L, McIntee E, Mattison P.
Evaluation of the effects of reflexology on quality of life and symptomatic relief in multiple sclerosis patients with moderate to severe disability; a pilot study.
Clin Rehabil. 2013 Feb 12. [Epub ahead of print]
Blikman LJ, Huisstede BM, Kooijmans H, et al.
Effectiveness of energy-conservation treatment in reducing fatigue in multiple sclerosis: a systematic review and meta-analysis.
Arch Phys Med Rehabil. 2013 Feb 8. doi:pii: S0003-9993(13)00112-3. 10.1016/j.apmr.2013.01.025. [Epub ahead of print]
A new multiple sclerosis spasticity treatment option: effect in everyday clinical practice and cost-effectiveness in Germany.
Expert Rev Neurother. 2013 Feb;13(3 Suppl 1):15-9.
Endocannabinoid system modulator use in everyday clinical practice in the UK and Spain.
Expert Rev Neurother. 2013 Feb;13(3 Suppl 1):9-13.
Multiple sclerosis spasticity daily management: retrospective data from Europe.
Expert Rev Neurother. 2013 Feb;13(3 Suppl 1):3-7.
Kremenchutzky M, Walt L.
Perceptions of health status in multiple sclerosis patients and their doctors.
Can J Neurol Sci. 2013 Mar 1;40(2):210-218.
Messinis L, Kosmidis MH, Vlahou C, et al.
Phonological fluency strategy of switching differentiates relapsing-remitting and secondary progressive multiple sclerosis patients.
ISRN Neurol. 2013;2013:451429.
Lange AP, Zhu F, Sayao AL, et al.
Retinal nerve fiber layer thickness in benign multiple sclerosis.
Mult Scler. 2013 Feb 11. [Epub ahead of print]
Fogarty E, Walsh C, Adams R, et al.
Relating health-related Quality of Life to disability progression in multiple sclerosis, using the 5-level EQ-5D.
Mult Scler. 2013 Feb 11. [Epub ahead of print]
Schäffler N, Schönberg P, Stephan J, et al.
Comparison of patient-reported outcome measures in multiple sclerosis.
Acta Neurol Scand. 2013 Feb 7. doi: 10.1111/ane.12083. [Epub ahead of print]
Quality of life
Boucekine M, Loundou A, Baumstarck K, et al.
Using the random forest method to detect a response shift in the quality of life of multiple sclerosis patients: a cohort study.
BMC Med Res Methodol. 2013 Feb 15;13(1):20. [Epub ahead of print]
Causes of MS
Warren SA, Olivo SA, Contreras JF, et al.
Traumatic injury and multiple sclerosis: a systematic review and meta-analysis.
Can J Neurol Sci. 2013 Mar 1;40(2):168-176.
Sheu JJ, Lin HC.
Association between multiple sclerosis and chronic periodontitis: a population-based pilot study.
Eur J Neurol. 2013 Feb 9. doi:10.1111/ene.12103. [Epub ahead of print]
Kornek B, Aboul-Enein F, Rostasy K, et al.
Natalizumab therapy for highly active pediatric multiple sclerosis.
JAMA Neurol. 2013 Feb 18:1-7.doi: 10.1001/jamaneurol.2013.923. [Epub ahead of print]
Ghezzi A, Pozzilli C, Grimaldi L, et al.
Natalizumab in pediatric multiple sclerosis: results of a cohort of 55 cases.
Mult Scler. 2013 Feb 11. [Epub ahead of print]
O Donnchadha S, Burke T, Bramham J, et al.
Symptom overlap in anxiety and multiple sclerosis.
Mult Scler. 2013 Feb 14. [Epub ahead of print]
Dlugonski D, Pilutti LA, Sandroff BM, et al.
Steps per day among persons with multiple sclerosis: variation by demographic, clinical, and device characteristics.
Arch Phys Med Rehabil. 2013 Feb 15. doi:pii: S0003-9993(12)01283-X. 10.1016/j.apmr.2012.12.014. [Epub ahead of print]
Sosnoff JJ, Socie MJ, Boes MK, et al.
Does a waist-worn ActiGraph accelerometer quantify community ambulation in persons with multiple sclerosis?
J Rehabil Res Dev. 2012 Dec;49(9):1405-10.
Scott SM, van der Linden ML, Hooper JE, et al.
Quantification of gait kinematics and walking ability of people with multiple sclerosis who are new users of functional electrical stimulation.
J Rehabil Med. 2013 Feb 14. doi:10.2340/16501977-1109. [Epub ahead of print]
Lamers I, Kerkhofs L, Raats J, et al.
Perceived and actual arm performance in multiple sclerosis: relationship with clinical tests according to hand dominance.
Mult Scler. 2013 Feb 13. [Epub ahead of print]
Specogna I, Casagrande F, Lorusso A, et al.
Functional MRI during the execution of a motor task in patients with multiple sclerosis and fatigue.
Radiol Med. 2012 Dec;117(8):1398-407.
Mandel M, Mercier F, Eckert B, et al.
Estimating time to disease progression comparing transition models and survival methods-an analysis of multiple sclerosis data.
Biometrics. 2013 Feb 14. doi: 10.1111/biom.12002. [Epub ahead of print]
Scalfari A, Neuhaus A, Daumer M, et al.
Early relapses, onset of progression, and late outcome in multiple sclerosis.
JAMA Neurol. 2013 Feb 1;70(2):214-22.
Rice CM, Cottrell D, Wilkins A, et al.
Primary progressive multiple sclerosis: progress and challenges.
J Neurol Neurosurg Psychiatry. 2013 Feb 16.[Epub ahead of print]
Pullman D, Zarzeczny A, Picard A.
"Media, politics and science policy: MS and evidence from the CCSVI Trenches".
BMC Med Ethics. 2013 Feb 12;14(1):6.