Currently the only clear biomarker that predicts a response to therapy is the presence of anti-MOG autoantibodies in blood. Anti-MOG seropositive patients do not respond to approved MS medications. In fact, it seems that MS patients with anti-MOG positivity could be considered a different disease in the near future. Comparative Effectiveness Research (CER) is an emerging field in Multiple Sclerosis treatment. The response of the disease to the different available medications at this moment cannot be predicted, and would be desirable. But the ideal target is to find subtypes of the disease that respond better to a specific treatment. A good example could be the discovery that the presence of a gene called SLC9A9 appears in people who fail to respond to interferon β therapy or that the disregulation of some transcription factors define molecular subtypes of the disease Other good example could be the Hellberg-Eklund score for predicting the response to
Natalizumab. Though biomarkers are normally assumed to be chemical compounds in body fluids, image can also be considered a biomarker. For an example about research in this area, it has been found that
fingolimod is specially suitable for patients with frequently relapsing
spinal cord lesions with open-ring enhancement. Anyway, patients with spinal cord lesions could have different T-helper cells patterns that those with brain lesions. Biomarkers are also important for the expected response to therapy. As an example of the current research, in 2000 was noticed that patients with
pattern II lesions were dramatically responsive to plasmapheresis, and in February 2016, it was granted the first patent to test the lesion pattern of a patient without biopsy. Other examples could be the proposal for protein SLC9A9 (gen
Solute carrier family 9) as biomarker for the response to
interferon beta, The same was proposed to MxA protein mRNA. The presence of anti-
MOG, even with CDMS diagnosis, can be considered as a biomarker against MS disease modifying therapies like fingolimod. Diagnosis of MS has always been made by clinical examination, supported by MRI or CSF tests. According with both the pure autoimmune hypothesis and the immune-mediated hypothesis, researchers expect to find
biomarkers able to yield a better diagnosis, and able to predict the response to the different available treatments. As of 2014 no biomarker with perfect correlation has been found, but some of them have shown a special behavior like IgG- and IgM- oligoclonal bands in the cerebrospinal fluid and autoantibodies against
neurotropic viruses (MRZ reaction) and the
potassium channel Kir4.1. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention. Type 0 biomarkers are those related to the course a pathogenic process and type 1 are those that show the effects of the therapeutical intervention. As of 2014, the only fully
specific biomarkers found to date are four proteins in the CSF:
CRTAC-IB (
cartilage acidic protein),
tetranectin (a
plasminogen-binding protein),
SPARC-like protein (a calcium binding cell signalling
glycoprotein), and
autotaxin-T (a
phosphodiesterase). Nevertheless, abnormal concentrations of non-specific proteins can also help in the diagnosis, like
chitinases. This list has been expanded in 2016, with three CSF proteins (Immunoglobulins) reported specific for MS. They are the following
immunoglobulins: Ig γ-1 (chain C region),
Ig heavy chain V-III (region BRO) and Ig-κ-chain (C region).
Molecular biomarkers in blood Blood serum of MS patients shows abnormalities.
Endothelin-1 shows maybe the most striking discordance between patients and controls, being a 224% higher in patients than controls.
Creatine and
Uric acid levels are lower than normal, at least in women.
Ex vivo CD4(+) T cells isolated from the circulation show a wrong
TIM-3 (Immunoregulation) behavior, and relapses are associated with
CD8(+) T Cells. There is a set of differentially expressed genes between MS and healthy subjects in peripheral blood T cells from clinically active MS patients. There are also differences between acute relapses and complete remissions.
Platelets are known to have abnormal high levels. MS patients are also known to be
CD46 defective, and this leads to
Interleukin-10 (
IL-10) deficiency, being this involved in the inflammatory reactions. Levels of IL-2, IL-10, and GM-CSF are lower in MS females than normal. IL6 is higher instead. These findings do not apply to men. This IL-10 could be related to the mechanism of action of
methylprednisolone, together with
CCL2. Interleukin
IL-12 is also known to be associated with relapses, but this is unlikely to be related to the response to steroids.
Kallikreins are found in serum and are associated with secondary progressive stage. Related to this, it has been found that B1-receptors, part of the
kallikrein-kinin-system, are involved in the
BBB breakdown. There is evidence of
Apoptosis-related molecules in blood and they are related to disease activity.
B cells in CSF appear, and they correlate with early brain inflammation. There is also an overexpression of
IgG-free
kappa light chain protein in both CIS and RR-MS patients, compared with control subjects, together with an increased expression of an isoforms of
apolipoprotein E in RR-MS. Expression of some specific proteins in circulating
CD4+ T cells is a risk factor for conversion from CIS to clinically defined multiple sclerosis. Recently, unique autoantibody patterns that distinguish RRMS, secondary progressive (SPMS), and primary progressive (PPMS) have been found, based on
up- and down-regulation of CNS antigens, tested by
microarrays. In particular, RRMS is characterized by autoantibodies to
heat shock proteins that were not observed in PPMS or SPMS. These antibodies patterns can be used to monitor disease progression. Finally, a promising biomarker under study is an antibody against the potassium channel protein
KIR4.1. They have been proposed as biomarkers for the presence of the disease and its evolution and some of them like
miR-150 are under study, specially for those with lipid-specific oligoclonal IgM bands Circulating
MicroRNAs have been proposed as biomarkers. There is current evidence that at least 60 circulating miRNAs would be dysregulated in MS patient's blood and profiling results are continuously emerging. Circulating miRNAs are highly stable in blood, easy to collect, and the quantification method, if standardized, can be accurate and cheap. They are putative biomarkers to diagnose MS but could also serve differentiating MS subtypes, anticipating relapses and proposing a customized treatment. MiRNA has even been proposed as a primary cause of MS and its white matter damaged areas
Genetic biomarkers for MS type : :
By RNA profile : Also in blood serum can be found the
RNA type of the MS patient. Two types have been proposed classifying the patients as MSA or MSB, allegedly predicting future inflammatory events. :
By transcription factor : The autoimmune disease-associated transcription factors
EOMES and TBX21 are dysregulated in multiple sclerosis and define a molecular subtype of disease. The importance of this discovery is that the expression of these genes appears in blood and can be measured by a simple blood analysis. :
NR1H3 Mutation. : Some PPMS patients have been found to have a special genetic variant named
rapidly progressive multiple sclerosis In these cases MS is due to a mutation inside the
gene NR1H3, an
arginine to
glutamine mutation in the position p.Arg415Gln, in an area that codifies the
protein LXRA.
In blood vessel tissue Endothelial dysfunction has been reported in MS and could be used as biomarker via biopsia. Blood circulation is slower in MS patients and can be measured using contrast or by MRI
Interleukin-12p40 has been reported to separate RRMS and CIS from other neurological diseases
In cerebrospinal fluid The most specific laboratory marker of MS reported to date, as of 2016, is the
intrathecal MRZ (
Measles,
Rubella and
Varicella) reaction showing 78% sensitivity and 97% specificity. It has been known for quite some time that
glutamate is present at higher levels in CSF during relapses, maybe because of the
IL-17 disregulation, and to MS patients before relapses compared to healthy subjects. This observation has been linked to the activity of the infiltrating leukocytes and activated microglia, and to the damage to the axons and to the oligodendrocytes damage, supposed to be the main cleaning agents for glutamate Also a specific MS protein has been found in CSF,
chromogranin A, possibly related to axonal degeneration. It appears together with clusterin and complement C3, markers of complement-mediated inflammatory reactions. Also
Fibroblast growth factor-2 appear higher at CSF.
Varicella-zoster virus particles have been found in CSF of patients during relapses, but this particles are virtually absent during remissions. Plasma Cells in the cerebrospinal fluid of MS patients could also be used for diagnosis, because they have been found to produce myelin-specific antibodies. As of 2011, a recently discovered myelin protein
TPPP/p25, has been found in CSF of MS patients A study found that quantification of several immune cell subsets, both in blood and CSF, showed differences between intrathecal (from the spine) and systemic immunity, and between CSF cell subtypes in the inflammatory and noninflammatory groups (basically RRMS/SPMS compared to PPMS). This showed that some patients diagnosed with PPMS shared an inflammatory profile with RRMS and SPMS, while others didn't. Other study found using a proteomic analysis of the CSF that the peak intensity of the signals corresponding to Secretogranin II and Protein 7B2 were significantly upregulated in RRMS patients compared to PrMS (p<0.05), whereas the signals of Fibrinogen and
Fibrinopeptide A were significantly downregulated in CIS compared to PrMS patients As of 2014 it is considered that the CSF signature of MS is a combination of cytokines CSF
lactate has been found to correlate to disease progression Three proteins in CSF have been found to be specific for MS. They are the following
immunoglobulins: Ig γ-1 (chain C region),
Ig heavy chain V-III (region BRO) and Ig-κ-chain (C region) and the
immunoglobulin heavy chains.
Oligoclonal bands CSF also shows
oligoclonal bands (OCB) in the majority (around 95%) of the patients. Several studies have reported differences between patients with and without OCB with regard to clinical parameters such as age, gender, disease duration, clinical severity and several MRI characteristics, together with a varying lesion load. CSF oligoclonal bands can be reflected in serum or not. This points to a heterogeneous origin of them Though early theories assumed that the OCBs were somehow pathogenic autoantigens, recent research has shown that the
immunoglobulins present in them are antibodies against debris, and therefore, OCBs seem to be just a secondary effect of MS. Given that OCBs are not pathogenic, their remaining importance is to demonstrate the production of intrathecal immunoglobins (IgGs) against debris, but this can be shown by other methods. Specially interesting are the
free light chains (FLC), specially the kappa-FLCs (kFLCs). Free kappa chains in CSF have been proposed as a marker for MS evolution
Biomarkers in brain cells and biopsies Abnormal sodium distribution has been reported in living MS brains. In the early-stage RRMS patients, sodium MRI revealed abnormally high concentrations of sodium in brainstem, cerebellum and temporal pole. In the advanced-stage RRMS patients, abnormally high sodium accumulation was widespread throughout the whole brain, including normal appearing brain tissue. It is currently unknown whether post-mortem brains are consistent with this observation. The pre-active lesions are clusters of microglia driven by the
HspB5 protein, thought to be produced by stressed oligodendrocytes. The presence of HspB5 in biopsies can be a marker for lesion development. Retinal cells are considered part of the CNS and present a characteristic thickness loss that can separate MS from NMO
Biomarkers for the clinical course Currently it is possible to distinguish between the three main clinical courses (RRMS, SPMS and PPMS) using a combination of four blood protein tests with an accuracy around 80% Currently the best predictor for clinical multiple sclerosis is the number of T2 lesions visualized by MRI during the CIS, but it has been proposed to complement it with MRI measures of BBB permeability It is normal to evaluate diagnostic criteria against the "time to conversion to definite". A 2025 study found that, in comparison to MRI-only models, incorporating serum neurofilament light chain (sNfL) levels provides an improved framework to stage disease progression and inform prognosis. ==Imaging biomarkers: MRI, PET and OCT==