WO2010005387A1 - New method and biomarkers for the diagnosis of multiple sclerosis - Google Patents

Abstract

The present invention relates to biological markers for multiple sclerosis. More specifically, the present invention relates to the use of such markers to diagnose multiple sclerosis, to monitor progression of the disease in clinical or preclinical trials, as well as for drug screening and drug development.

Description

NEW METHOD AND BIOMARKERS FOR THE DIAGNOSIS OF MULTIPLE SCLEROSIS

The present invention relates to biological markers for multiple sclerosis. More specifically, the present invention relates to the use of such markers to diagnose multiple sclerosis, to monitor progression of the disease in clinical or preclinical trials, as well as for drug screening and drug development.

Multiple sclerosis (MS) is an autoimmune disease involving the nervous system and the disease affects twice as many women as it does men worldwide nearly 2.5 million individuals. In the western world, more than 80 per 100,000 populations are affected. The mean age of onset for MS is 30 years; there are two prevalent age groups. The majority of the patients are between 21 and 25 years at onset and a smaller percentage are 41 to 45 years of age. There is a high economic burden associated with the disease. The total annual cost for all people with MS in the US has been estimated to be more than $9 billion dollars.

MS can be divided into four different forms; clinical isolated syndrome (CIS), relapsing remitting (RR), secondary progressive (SP) and primary progressive (PP) respectively. CIS can be the first step in developing the disease from which 30-80% actually develops MS. RR is characterized by a series of exacerbations that result in varying degrees of disability from which the patient recovers. The course of the disease in about 60-80% of RR patients steadily changes to SP in which the patient does not experience exacerbations, but instead reports a gradual decline. PP does not include the typical exacerbations as in RR instead the disease progression gradually progress.

MS is a chronic demyelinating disease in which inflammation of the CNS is associated with lesions appearing typically in plaques within white matter. This inflammatory process involves activation and recruitment of T cells, macrophages and microglia to lesion sites. Symptoms are believed to occur from axonal demyelination that inhibits or blocks conduction throughout the nervous system. Plaques may be found throughout the brain and spinal cord. Recovery of symptoms has been attributed to partial remyelination and resolution of inflammation. Based on accumulating data from immunological studies of MS patients and a wealth of animal model data, autoimmune dysregulation has been viewed as the major contributor to tissue damage.

The current model of MS immunopathology suggests that autoreactive T cells within the periphery become activated. Activated T cells express up-regulated levels of adhesion molecules and are able to migrate across the blood- brain barrier much more efficiently than naive, resting T cells. Extravasation across the blood-brain barrier is thought to involve a sequence of overlapping molecular interactions between inducible ligand- receptor pairs on the surface of the migrating cell and the endothelial barrier. Selective expression of adhesion molecules, chemokines and chemokine receptors and matrix metalloproteinases are likely to be important in mediating the transmigration of effector cells across the blood-brain barrier and into the central nervous system (CNS) perivascular tissue in demyelinating diseases.

The pathogenic mechanisms of MS may not be limited to autoimmunity. Demyelination may occur through many proposed mechanisms: Fas/Fas ligand interactions, toxic cytokines, reactive oxygen species, antibody dependent cellular toxicity and metabolic instability of oligodendrocytes. In addition, axonal damage is increasingly recognized as a prominent pathological feature in MS lesions as well as in normal appearing white matter in MS brains. Whereas these observations do not preclude the role of inflammatory demyelination in MS pathogenesis, axonal compromise may predate the inflammatory lesions, raising the possibility that an independent axonal pathology may contribute to the primary pathobiology of the disease. Studies of the mechanisms of axonal damage and neurodegeneration in MS are in their infancy. However, axonal damage may determine clinical outcome to a large extent. CNS tissue destruction markers would be useful not only for inflammatory demyelination but for neurodegenerative processes in MS.

MS is a systemic disease in terms of its autoimmune pathogenesis and a compartmental disease in as much as the end-organ damage is in the CNS. Thus, biomarkers of the disease could likely be found in the CSF that surrounds the brain, as well as in other more easily obtainable fluids, such as serum or urine, that are reflective of systemic disease.

The availability of treatments that favourably impact the early course of MS underscores the importance of timely and accurate diagnosis. Currently, the diagnosis of MS is time consuming, expensive and uncertain especially in the early stages of disease. MRI has also been used to assess MS disease activity, disease burden and the dynamic evolution of these parameters over time (Bourdette, D. et al., J Neuroimmunol 98, 16-21 (1999)). Serial MRI studies have unequivocally demonstrated that clinically apparent changes reflect only a minor component of disease activity. Overall MRI is limited in its ability to provide specific information about pathology in MS. In the absence of a specific defining assay, the diagnosis of MS continues to be predicated on the clinical history and neurological exam, though use of the MRI has had a major impact on early diagnosis (McDonald, W. I. et al., Ann Neurol 50, 121-127 (2001)).

Post-translational modifications such as glycosylation patterns may enable the origin of subsets of these proteins to be distinguished (Hoffmann, A. et al., FEBS Lett 359, 164-168 (1995); Grunewald, S. et al., Biochim Biophys Acta 1455, 54-60 (1999)).

The disease course of MS is highly variable within and between patients indicating that there is disease heterogeneity. Indeed, heterogeneity in MS lesions has been shown in MRI and pathologic studies. MRI affords the ability to identify atrophy and different types of lesions, however it lacks pathologic specificity. Because of its intimate association with the CNS, considerable efforts have been made to identify prognostic and diagnostic markers in the CSF from patients with MS.

Phosphorylation of proteins is also regarded as a post-translational modification that can act as on or off signal for protein action, (see Principles of interleukin (IL)-6-type cytokine signalling and its regulation by. Heinrich, P, et al. J374, 1-20. (2003) for discussion). The area, phosphorylations and glycosylations, with a proteomics approach on CSF has not been well investigated although some studies shows examples (Yuko Ogata, M. et al., Journal of Proteome Research, 4, 837- 845 837 (2005)). Characterization of proteins in CSF with proteomic approaches has been sparse. Many of the published studies employ 2-D electrophoresis, which is rather cumbersome and typically requires more protein than routinely can be obtained with CSF. Furthermore, proteins showing extreme low- or high molecular weight, high hydrophobicity, low abundance and the entire metabolome are not amenable to electrophoresis (Manabe, T., Electrophoresis 21, 1116-1122 (2000)). Poor sensitivity has hampered some studies; others have used very large amounts of fluid to compensate. These efforts have yielded identification of a very limited number of proteins (Puchades, M., et al., Rapid Commun Mass Spectrom 13, 2450-2455 (1999)). Nonetheless, employing 2- D electrophoresis proteomics and discovery driven strategies, researchers have identified candidate or potential biomarkers within CSF. For example, a complement factor was identified in the CSF of patients with cerebral arteriopathy (UnIu, M. et al., Neurosci Lett 282, 149-152 (2000)).

In the context of the present invention, the inventors have used depletion of Albumin and IgG combined with fluorescent stain for total protein. This is a novel approach for quantification and identification of proteins in CSF from MS patients.

The present invention provides biological markers ("biomarkers") indicative of Multiple Sclerosis (MS). These biomarkers can be used to diagnose the disease, monitor its progression, assess response to therapy and screen drugs for treating MS. Early diagnosis and knowledge of disease progression could allow early institution of treatment when it is most appropriate and would be of the greatest benefit to the patient. In addition, such information will allow prediction of exacerbations and classification of potential MS subtypes. The ability to evaluate response to therapy will allow the personalized treatment of the disease and provided the basis for clinical trials aimed at evaluating the effectiveness of candidate drugs.

Due to the disease course of MS with a pronounced inflammatory component in the early stage (CIS, RR), followed by significant changes in biology to a neurodegenerative state in the later stages of the disease (SP), it indicates that these biomarkers can be used in monitoring the development of other neuroinflammatory and/or neurodegenerative disorders. Such neuroinflammatory or neurodegenerative disorders could be, but are not limited to, Parkinson's disease, Alzheimer's Disease, Mild Cognitive Impairment, Dementia, Age-Associated Memory Impairment, Age-Related Cognitive Decline, Disorder(s) associated with neurofibrillar tangle pathologies, Dementia due to Alzheimer's Disease, Dementia due to Schizophrenia, Dementia due to Parkinson's Disease, Dementia due to Creutzfeld- Jacob Disease, Dementia due to Huntington's Disease, Dementia due to Pick's Disease, Stroke, Head Trauma, Spinal Injury, Multiple Sclerosis, Migraine, Pain, Systemic Pain, Localized Pain, Nociceptive Pain, Neuropathic Pain, Urinary Incontinence, Sexual Dysfunction, Premature Ejaculation, Motor Disorder(s), Endocrine Disorder(s), Gastrointestinal Disorder(s), and Vasospasm.

The biomarkers of the present invention include the level of particular proteins whose measurement values in a biological sample are different (either higher or lower) in a subject with MS as compared to a standard level or reference range established by obtaining measurement values for the biomarker in subjects who do not have the disease ("normal controls") and such differences may be statistically significant. Alternatively, CSF from individual patients may be analysed longitudinal, prior to and during treatment.

The invention provides a method for determining whether a subject has MS. Further, the invention provides a method for determining whether a subject is more likely than not to have MS, or is more likely to have MS than to have another disease. The method is performed by analysing a biological sample, such as serum or CSF, from the subject; measuring the level of protein of at least one of the biomarkers in the biological sample; and comparing the measured level with a standard level or reference range. Typically, the standard level or reference range is obtained by measuring the same marker or markers in a normal control or, more preferably, a set of normal controls. Depending upon the difference between the measured level and the standard level or reference range, the patient can be diagnosed as having MS, or as not having MS. As will be appreciated by one of skill in the art, a standard level or reference range is specific to the biological sample at issue. Thus, a standard level or reference range for the marker in serum that is indicative of MS would be expected to be different from the standard level or reference range (if one exists) for that same marker in CSF, urine or another tissue, fluid or compartment. Thus, references herein to measuring biomarkers will be understood to refer to measuring the level of the biomarker. Furthermore, references herein to comparisons between a marker measurement level and a standard level or reference range will be understood to refer to such levels or ranges for the same type of biological sample.

Further, the invention provides a method for monitoring a MS patient over time to determine whether the disease is progressing. The method is performed by analysing a biological sample, such as serum or CSF, from the subject at a certain time; measuring the level of at least one of the biomarkers in the biological sample; and comparing the measured level with the level measured with respect to a biological sample obtained from the subject at an earlier time. Depending upon the difference between the measured levels, it can be seen whether the marker level has increased, decreased, or remained constant over the interval. Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times. The same type of method also can be used to assess the efficacy of a therapeutic intervention in a subject where the therapy is instituted, or an ongoing therapy is changed.

Further, the invention provides a method for conducting a clinical trial to determine whether a candidate drug is effective in treating MS. The method is performed by analysing a biological sample from each subject in a population of subjects diagnosed with MS, and measuring the level of at least one of the biomarkers in the biological samples. Then, a dose of a candidate drug is administered to one portion or sub-population of the same subject population ("experimental group") while a placebo is administered to the other members of the subject population ("control group"). After drug or placebo administration, a biological sample is acquired from the experimental and control groups and the same assays are performed on the biological samples as were previously performed to obtain measurement values. Depending upon the difference between the measured levels between the experimental and control groups, it can be seen whether the candidate drug is effective. The relative efficacy of two different drugs or other therapies for treating MS can be evaluated using this method by administering the drug or other therapy in place of the placebo. As will be apparent to one of skill in the art, the methods of the present invention may be used to evaluate an existing drug, being used to treat another indication, for its efficacy in treating MS (e.g., by comparing the efficacy of the drug relative to one currently used for treating MS in a clinical trial, as described above).

The present invention also provides molecules (for example antibodies) that specifically bind to protein and low molecular weight markers. Such marker specific reagents have utility in isolating the markers and in detecting the presence of the markers, e.g., in immunoassays.

The present invention also provides kits for diagnosing MS, monitoring progression of the disease and assessing response to therapy, the kits comprising a container for a sample collected from a subject and at least one marker specific reagent.

The present inventors have surprisingly identified that the level of certain biological markers whose presence and measured protein levels are indicative of multiple sclerosis (MS). The biomarkers include protein and low molecular weight molecules. According to one definition, a biological marker ("biomarker") is "a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacological responses to therapeutic interventions." NIH Biomarker Definitions Working Group (1998). Biomarkers can also include patterns or ensembles of characteristics indicative of particular biological processes. The biomarker measurement can increase or decrease to indicate a particular biological event or process. In addition, if a biomarker measurement typically changes in the absence of a particular biological process, a constant measurement can indicate occurrence of that process. For more information on biomarker measurement and discovery, see U.S. patent application Ser. No. 09/558, 909, "Phenotype and Biological Marker Identification System," filed Apr. 26, 2000, herein incorporated by reference in its entirety.

In the present invention, the biomarkers are primarily used for diagnostic purposes. However they may also be used for therapeutic, drug screening and patient stratification purposes (e.g., to group patients into a number of "subsets" for evaluation). The present invention is based on the findings of a study designed to identify biological markers for MS. Samples of CSF and serum from patients with MS were analyzed using liquid chromatography, 2D gel electrophoresis and mass spectrometry. The markers of the present invention were identified by comparing the levels of markers measured in samples obtained from MS patients with the levels of markers measured in samples obtained from patients who did not have the disease. Peaks consistently higher or lower in patients with MS were further investigated by using liquid chromatography mass combined with tandem mass spectrometry techniques to identify the molecules at issue.

Measurement of values of the biomarkers was found to differ in biological samples from patients with MS as compared to biological samples from normal controls. Accordingly, it is believed that these biomarkers are indicators of MS.

The present invention includes all methods relying on correlations between the biomarkers described herein and the presence of MS. In a preferred embodiment, the invention provides methods for determining whether a candidate drug is effective at treating MS by evaluating the effect it has on the biomarker values. In this context, the term "effective" is to be understood broadly to include reducing or alleviating the signs or symptoms of MS, improving the clinical course of the disease, decreasing the number or severity of exacerbations, reducing the number of plaques, reducing the amount or rate of axonal demyelination, reducing the number of inflammatory cells in existing plaque or reducing in any other objective or subjective indicia of the disease. Different drugs, doses and delivery routes can be evaluated by performing the method using different drug administration conditions. The method may also be used to compare the efficacy of two different drugs or other treatments or therapies for MS.

It is expected that the levels of the biomarkers described herein will be measured in combination with other signs, symptoms and clinical tests of MS, such as MRI scans or MS biomarkers reported in the literature. Likewise, more than one of the biomarkers of the present invention may be measured in combination. Measurement of the biomarkers of the invention along with any other markers known in the art, including those not specifically listed herein, falls within the scope of the present invention. The present invention provides a method for determining whether a subject has MS. Biomarker level measurements are taken of a biological sample from a patient suspected of having the disease and compared with a standard level or reference range. Typically, the standard biomarker level or reference range is obtained by measuring the same marker or markers in a set of normal controls. Measurement of the standard biomarker level or reference range need not be made contemporaneously; it may be a historical measurement. Preferably the normal control is matched to the patient with respect to some attribute(s) (e.g., age or sex). Depending upon the difference between the measured and standard level or reference range, the patient can be diagnosed as having MS or as not having MS.

Thus, in a first aspect of the present invention, there is provided a method for screening or diagnosis of multiple sclerosis in a subject, for determining the stage or severity of multiple sclerosis in a subject, for identifying a subject at risk of developing multiple sclerosis, or for monitoring the effect of therapy administered to a subject having multiple sclerosis, said method comprising:

(a) analysing a test sample of body fluid from the subject by two-dimensional electrophoresis to generate a two-dimensional array of features, said array comprising one or more of the following one or more of the following multiple sclerosis proteins (MSPs): alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; Apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS- glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha- amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

(b) comparing the abundance of the one or more MSPs in the test sample with the abundance of the one or more of said proteins in a body fluid sample from one or more subjects free from multiple sclerosis, or with a previously determined reference range for that feature in subjects free from multiple sclerosis.

In another aspect of the present invention, there is provided a method for screening or diagnosis of multiple sclerosis in a subject, for determining the stage of multiple sclerosis in a subject or for monitoring the effect of therapy administered to a subject having multiple sclerosis, said method comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following multiple sclerosis proteins (MSPs): alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; Apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

In one embodiment of these two aspects, there is provided a method, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is clinical isolated syndrome multiple sclerosis. For example, there is provided a method, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2- macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1- microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1 ; carnosinase 1 ; contactin 1 ; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

In another embodiment of these two aspects, there is provided a method, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is relapsing remitting multiple sclerosis. For example, there is provided a method, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2- macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1- microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1 ; carnosinase 1 ; contactin 1 ; complement C3 fragment; complement C4-A; component C9; fibulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

In another embodiment of these two aspects, there is provided a method, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is secondary progressive multiple sclerosis. For example, there is provided a method, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2- macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1- microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1 ; carnosinase 1 ; contactin 1 ; complement C3 fragment; complement C4-A; component C9; fibulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

In another embodiment of these two aspects, there is provided a method, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is neurodegenerative stage of multiple sclerosis. For example, there is provided a method, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha- 2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1- microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1 ; carnosinase 1 ; contactin 1 ; complement C3 fragment; complement C4-A; component C9; fibulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

In another aspect of the present invention, the methods described herein are carried out in vitro. In another aspect of the present invention, the methods described herein, the test sample of body fluid is selected from blood, serum, plasma, cerebrospinal fluid, urine and saliva.

In another aspect of the present invention, there is provided an antibody capable of binding to the MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2- macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1- microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1 ; carnosinase 1 ; contactin 1 ; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

In one embodiment of this aspect, said antibody is a monoclonal antibody.

In another aspect of the present invention, there is provided a kit comprising one or more of said antibodies, other reagents and instructions for use. Said kit can be used in the screening or diagnosis of multiple sclerosis in a subject, for determining the stage or severity of multiple sclerosis in a subject, for identifying a subject at risk of developing multiple sclerosis, or for monitoring the effect of therapy administered to a subject having multiple sclerosis. Aid kit may comprise a plurality of said antibodies.

In another aspect of the present invention, there is provided a pharmaceutical composition comprising a therapeutically effective amount of said antibody, or a fragment or derivative of an antibody, and a pharmaceutically acceptable carrier.

In another aspect of the present invention, there is provided a method of treating or preventing multiple sclerosis, comprising administering to a subject in need of such treatment a therapeutically effective amount of said antibody. In another aspect of the present invention, there is provided a method of screening for agents that interact with one or more MSPs: alpha- 1 -antitrypsin; leucine -rich alpha-2- glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apo lipoprotein E; ceruloplasmin; chitinase- 3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fibulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin; said method comprising:

(a) contacting an MSP with a candidate agent; and

(b) determining whether or not the candidate agent interacts with the MSP.

In one embodiment of this aspect, said determination of interaction between the candidate agent and the MSP comprises quantitatively detecting binding of the candidate agent and the MSP.

In another aspect of the present invention, there is provided a method of screening for or identifying agents that modulates the expression or activity of one or more more MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS- glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha- amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin; comprising:

(a) contacting a first population of cells expressing the MSP(s) with a candidate agent;

(b) contacting a second population of cells expressing said MSP(s) with a control agent; and (c) comparing the level of said MSPs in the first and second populations of cells, or comparing the level of induction of a downstream effecter in the first and second populations of cells.

In another aspect of the present invention, there is provided a method of screening for or identifying agents that modulate the expression or activity of one or more more MSPs: alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS- glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha- amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin; said method comprising:

(a) administering a candidate agent to a first mammal or group of mammals;

(b) administering a control agent to a second mammal or group of mammals; and

(c) comparing the level of expression of the MSP(s), or mRNA encoding said MSP(s) in the first and second groups, or comparing the level of induction of a downstream effecter in the first and second groups.

In one embodiment of this aspect, said administration of a candidate agent results in an increase in the level of said MSPs, or mRNA encoding said MSPs, or said downstream effecter in the first population of cells or mammals compared to the second population of cells or mammals.

In another embodiment of this aspect, said administration of a candidate agent results in a decrease in the level of said MSPs, or mRNA encoding said MSPs , or said downstream effecter in the first population of cells or mammals compared to the second population of cells or mammals.

In another aspect of the present invention, there is provided a method of screening for or identifying agents that modulate the activity of one or more of the MSPs: alpha- 1- antitrypsin; leucine -rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS- glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha- amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin;, said method comprising:

(a) in a first aliquot, contacting a candidate agent with the MSP(s) and;

(b) determining and comparing the activity of the MSP(s) in the first aliquot after addition of the candidate agent with the activity of MSP(s) in a control aliquot, or with a previously determined reference range.

The above-mentioned methods may relates to MSP(s), wherein said MSP(s) is a recombinant protein.

What is presently referred to as MS may turn out to be a number of related, but distinguishable conditions. Indeed, four types of MS have already been recognized: (i) early MS e.g. clinical isolated syndrome (CIS), (ii) relapsing remitting MS (RR), (iii) secondary chronic progressive MS (SP), and (iv) primary progressive MS (PP). Additional classifications may be made, and these types may be further distinguished into subtypes. Any and all of the various forms of MS are intended to be within the scope of the present invention. Indeed, by providing a method for subsetting patients based on biomarker measurement level, the compositions and methods of the present invention may be used to uncover and define various forms of the disease.

The methods of the present invention may be used to make the diagnosis of MS, independently from other information such as the patient's symptoms or the results of other clinical or paraclinical tests. However, the methods of the present invention are preferably used in conjunction with such other data points.

Because a diagnosis is rarely based exclusively on the results of a single test, the method may be used to determine whether a subject is more likely than not to have MS, or is more likely to have MS than to have another disease, based on the difference between the measured and standard level or reference range of the biomarker. Thus, for example, a patient with a putative diagnosis of MS may be diagnosed as being "more likely" or "less likely" to have MS in light of the information provided by a method of the present invention.

The biological sample may be of any tissue or fluid. Preferably, the sample is a CSF or serum sample, but other biological fluids or tissue may be used. Possible biological fluids include, but are not limited to, plasma, urine and neural tissue. CSF represents a preferred biological sample to analyze for MS markers as it bathes the brain and removes metabolites and molecular debris from its liquid environment. Thus, biomolecules associated with the presence and/or progression of MS is expected to be present at highest concentrations in this body fluid. A CSF biomarker in itself may be particularly useful for early diagnosis of disease. Furthermore, molecules initially identified in CSF may also be present, presumably at lower concentrations, in more easily obtainable fluids such as serum and urine. Such biomarkers may be valuable for monitoring all stages of the disease and response to therapy. Serum and urine also represent preferred biological samples as they are expected to be reflective of the systemic manifestations of the disease. In some embodiments, the level of a marker may be compared to the level of another marker or some other component in a different tissue, fluid or biological "compartment." Thus, a differential comparison may be made of a marker in CSF and serum. It is also within the scope of the invention to compare the level of a marker with the level of another marker or some other component within the same compartment.

As will be apparent to those of ordinary skill in the art, the above description is not limited to making an initial diagnosis of MS, but also is applicable to confirming a provisional diagnosis of MS or "ruling out" such a diagnosis. It is to be understood that any correlations between biological sample measurements of these biomarkers and MS, as used for diagnosis of the disease or evaluating drug effect, are within the scope of the present invention.

In the methods of the invention, biomarker levels are measured using conventional techniques. A wide variety of techniques are available, such as mass spectrometry, chromatographic separations, 2 -D gel separations, binding assays (e.g., luminex immunoassays) and competitive inhibition assays. Any effective method in the art for measuring the level of a protein or low molecular weight marker is included in the invention. It is within the ability of one of ordinary skill in the art to determine which method would be most appropriate for measuring a specific marker. Thus, for example, a robust ELISA assay may be best suited for use in a physician's office while a measurement requiring more sophisticated instrumentation may be best suited for use in a clinical laboratory. Regardless of the method selected, it is important that the measurements are reproducible.

The markers of the invention can be measured by mass spectrometry, which allows direct measurements of analytes with high sensitivity and reproducibility. A number of mass spectrometric methods are available and could be used to accomplish the measurement. Electrospray ionization (ESI), for example, allows quantification of differences in relative concentration of various species in one sample against another; absolute quantification is possible by normalization techniques (e.g., using an internal standard). Matrix-assisted laser desorption ionization (MALDI) or the related SELDI® technology (Ciphergen, Inc.) also could be used to make a determination of whether a marker was present, and the relative or absolute level of the marker. Moreover, mass spectrometers that allow time-of- flight (TOF) measurements have high accuracy and resolution and are able to measure low abundant species, even in complex matrices like serum or CSF.

For protein markers, quantification can be based on derivatization in combination with isotopic labeling, referred to as isotope coded affinity tags ("ICAT"). In this and other related methods, a specific amino acid in two samples is differentially and isotopically labeled and subsequently separated from peptide background by solid phase capture, wash and release. The intensities of the molecules from the two sources with different isotopic labels can then be accurately quantified with respect to one another.

In addition, one- and two-dimensional gels have been used to separate proteins and quantify gels spots by silver staining, fluorescence or radioactive labeling. These differently stained spots have been detected using mass spectrometry, and identified by tandem mass spectrometry techniques.

The markers may also be measured using mass spectrometry in connection with a separation technology, such as liquid chromatography-mass spectrometry or gas chromatography-mass spectrometry. It is preferable to couple reverse-phase liquid chromatography to high resolution, high mass accuracy ESI time-of-flight (TOF) mass spectroscopy. This allows spectral intensity measurement of a large number of biomolecules from a relatively small amount of any complex biological material without sacrificing sensitivity or throughput. Analyzing a sample will allow the marker (specified by a specific retention time and m/z) to be determined and quantified. As will be appreciated by one of skill in the art, many other separation technologies may be used in connection with mass spectrometry. For example, a vast array of separation columns is commercially available. In addition, separations may be performed using custom chromatographic surfaces (e.g., a bead on which a marker specific reagent has been immobilized). Molecules retained on the media subsequently may be eluted for analysis by mass spectrometry.

Analysis by liquid chromatography-mass spectrometry produces a mass intensity spectrum, the peaks of which represent various components of the sample, each component having a characteristic mass- to-charge ratio (m/z) and retention time (r.t.). The presence of a peak with the m/z and retention time of a biomarker indicates that the marker is present. The peak representing a marker may be compared to a corresponding peak from another spectrum (e.g., from a control sample) to obtain a relative measurement. Any normalization technique in the art (e. g., an internal standard) may be used when a quantitative measurement is desired. In addition, deconvoluting software is available to separate overlapping peaks. The retention time depends to some degree on the conditions employed in performing the liquid chromatography separation. The better the mass assignment, the more accurate will be the detection and measurement of the marker level in the sample. Thus, the mass spectrometer selected for this purpose preferably provides high mass accuracy and high mass resolution. The mass accuracy of a well- calibrated Micromass TOF instrument, for example, is reported to be approximately 2 mDa, with resolution m/Am exceeding 5000.

A number of the assays discussed above employ a reagent that specifically binds to the marker ("marker specific reagent"). Any molecule that is capable of specifically binding to a marker is included within the invention. In some embodiments, the marker specific reagents are antibodies or antibody fragments. In other embodiments, the marker specific reagents are non-antibody species. Thus, for example, a marker specific reagent may be an enzyme for which the marker is a substrate. The marker specific reagents may recognize any epitope of the targeted markers.

A marker specific reagent may be identified and produced by any method accepted in the art. Methods for identifying and producing antibodies and antibody fragments specific for an analyte are well known. Examples of other methods used to identify marker specific reagents include binding assays with random peptide libraries (e.g., phage display) and design methods based on an analysis of the structure of the marker.

The markers of the invention, especially the low molecular weight markers, may also be detected or measured using a number of chemical derivatization or reaction techniques known in the art. Reagents for use in such techniques are known in the art, and are commercially available for certain classes of target molecules.

Further, the chromatographic separation techniques described above also may be coupled to an analytical technique other than mass spectrometry such as fluorescence detection of tagged molecules, NMR, capillary UV, evaporative light scattering or electrochemical detection. Further, a method is provided for monitoring an MS patient over time to determine whether the disease is progressing. The specific techniques used in implementing this embodiment are similar to those used in the embodiments described above. The method is performed by obtaining a biological sample, such as serum or CSF, from the subject at a certain time (t 1); measuring the level of at least one of the biomarkers in the biological sample; and comparing the measured level with the protein level measured with respect to a biological sample obtained from the subject at an earlier time. Depending upon the difference between the measured levels, it can be seen whether the marker level has increased, decreased, or remained constant over the interval. A further deviation of a marker in the direction indicating MS, or the measurement of additional increased or decreased MS markers, would suggest a progression of the disease during the interval. Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times.

The ability to monitor a patient by making serial marker level determinations would represent a valuable clinical tool. Rather than the limited "snapshot" provided by a single test, such monitoring would reveal trends in marker levels over time. In addition to indicating a progression of the disease, tracking the marker levels in a patient could be used to predict exacerbations or indicate the clinical course of the disease. For example, as will be apparent to one of skill in the art, the biomarkers of the present invention could be further investigated to distinguish between any or all of the known forms of MS (early MS, relapsing remitting MS, secondary chronic progressive MS, and primary progressive MS) or any later described types or subtypes of the disease. In addition, the sensitivity and specificity of any method of the present invention could be further investigated with respect to distinguishing MS from other diseases of autoimmunity, or other nervous system disorders, or to predict relapse and remission.

Analogously, the markers of the present invention can be used to assess the efficacy of a therapeutic intervention in a subject. The same approach described above would be used, except a suitable treatment would be started, or an ongoing treatment would be changed, before the second measurement. The treatment can be any therapeutic intervention, such as drug administration, dietary restriction or surgery, and can follow any suitable schedule over any time period. The measurements before and after could then be compared to determine whether or not the treatment had an effect effective. As will be appreciated by one of skilled in the art, the determination may be confounded by other superimposed processes (e.g., an exacerbation of the disease during the same period).

Further, the markers may be used to screen candidate drugs in a clinical trial to determine whether a candidate drug is effective in treating MS. At time t 0, a biological sample is obtained from each subject in population of subjects diagnosed with MS. Next, assays are performed on each subject's sample to measure levels of a biological marker. In some embodiments, only a single marker is monitored, while in other embodiments, several markers are monitored. Next, a predetermined dose of a candidate drug is administered to a portion or sub-population of the same subject population. Drug administration can follow any suitable schedule over any time period. In some cases, varying doses are administered to different subjects within the sub-population, or the drug is administered by different routes. After drug administration, a biological sample is acquired from the sub-population and the same assays are performed on the biological samples as were previously performed to obtain measurement values. As before, subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times. In such a study, a different subpopulation of the subject population serves as a control group, to which a placebo is administered. The same procedure is then followed for the control group: obtaining the biological sample, processing the sample, and measuring the level of the biological markers to obtain a measurement chart.

Specific doses and delivery routes can also be examined. The method is performed by administering the candidate drug at specified dose or delivery routes to subjects with MS; obtaining biological samples, such as serum or CSF, from the subjects; measuring the level of at least one of the biomarkers in each of the biological samples; and, comparing the measured level for each sample with other samples and/or a standard level. Typically, the standard level is obtained by measuring the same marker or markers in the subject before drug administration. Depending upon the difference between the measured and standard levels, the drug can be considered to have an effect on MS. If multiple biomarkers are measured, at least one and up to all of the biomarkers must change, in the expected direction, for the drug to be considered effective. Preferably, multiple markers must change for the drug to be considered effective, and preferably, such change is statistically significant.

As will be apparent to those of ordinary skill in the art, the above description is not limited to a candidate drug, but is applicable to determining whether any therapeutic intervention is effective in treating MS.

In a typical study, a subject population having MS is selected. The population is typically selected using standard protocols for selecting clinical trial subjects. For example, the subjects are generally healthy, are not taking other medication, and are evenly distributed in age and sex. The subject population can also be divided into multiple groups; for example, different sub-populations may be suffering from different types or different degrees of the disorder to which the candidate drug is addressed. Alternatively, subgroups may be defined by the level of biomarkers.

In general, a number of statistical considerations must be made in designing the trial to ensure that statistically significant changes in biomarker measurements can be detected following drug administration. The amount of change in a biomarker depends upon a number of factors, including strength of the drug, dose of the drug, and treatment schedule. It will be apparent to one skilled in statistics how to determine appropriate subject population sizes. Preferably, the study is designed to detect relatively small effect sizes.

The subjects optionally may be "washed out" from any previous drug use for a suitable period of time. Washout removes effects of any previous medications so that an accurate baseline measurement can be taken. A biological sample is obtained from each subject in the population. Preferably, the sample is blood or CSF, but other biological fluids may be used (e.g., urine). Next, an assay or variety of assays is performed on each subject's sample to measure levels of particular biomarkers of the invention. The assays can use conventional methods and reagents, as described above. If the sample is blood, then the assays typically are performed on either serum or plasma. For other fluids, additional sample preparation steps are included as necessary before the assays are performed. The assays measure values of at least one of the biological markers described herein. In some embodiments, only a single marker is monitored, while in other embodiments, a combination of factors, up to the total number of markers, is monitored. The markers may also be monitored in conjunction with other measurements and factors associated with MS (e.g., MRI imaging). The number of biological markers whose values are measured depends upon, for example, the availability of assay reagents, biological fluid, and other resources.

Next, a predetermined dose of a candidate drug is administered to a portion or sub- population of the same subject population. Drug administration can follow any suitable schedule over any time period, and the sub-population can include some or all of the subjects in the population. In some cases, varying doses are administered to different subjects within the sub-population, or the drug is administered by different routes. Suitable doses and administration routes depend upon specific characteristics of the drug. After drug administration, another biological sample is acquired from the sub-population.

Typically, the sample is the same type of sample and processed in the same manner (for example, CSF or blood) as the sample acquired from the subject population before drug administration (the "tθ sample"). The same assays are performed on the samples to obtain measurement values. Subsequent sample acquisitions and measurements can be performed as many times as desired over a range of times.

Typically, a different sub-population of the subject population is used as a control group, to which a placebo is administered. The same procedure is then followed for the control group: obtaining the biological sample, processing the sample, and measuring the level of biological markers to obtain measurement values. Additionally, different drugs can be administered to any number of different sub-populations to compare the effects of the multiple drugs. Allocation of treatment to participating subjects should be done randomly, and the trial should preferably be double-blinded. As will be apparent to those of ordinary skill in the art, the above description is a highly simplified description of a method involving a clinical trial. Clinical trials have many more procedural requirements, and it is to be understood that the method is typically implemented following all such requirements. To obtain estimates of treatment effect of a drug in placebo-controlled trials, post- treatment measurements should be used to compare the treated group versus the placebo group. Pre-treatment measurements may be used in the analysis to adjust for potential differences in baseline values between patients.

If only one biomarker is measured, then that value must be different between the placebo and drug-treated groups to indicate drug efficacy. If more than one biomarker is measured, then drug efficacy can be indicated by change in only one biomarker, all biomarkers, or any number in between. In some embodiments, multiple markers are measured, and drug efficacy is indicated by changes in multiple markers. Measurements can be of both biomarkers of the present invention and other measurements and factors associated with MS (e.g., measurement of biomarkers reported in the literature and/or MRI imaging). Furthermore, the amount of change in a biomarker level may be an indication of the relatively efficacy of the drug.

In addition to determining whether a particular drug is effective in treating MS, biomarkers of the invention can also be used to examine dose effects of a candidate drug. There are a number of different ways that varying doses can be examined. For example, different doses of a drug can be administered to different subject populations, and measurements corresponding to each dose analyzed and, optionally,compared to placebo to determine if the differences in the inventive biomarkers are significant. In this way, a minimal dose required to effect a change can be estimated. In addition, results from different doses can be compared with each other to determine how each biomarker behaves as a function of dose.

Example The invention is hereby exemplified by the below non-limiting example. Material Samples were collected at Karolinska Hospital Stockholm, Sweden (provided by Professor Tomas Olsson, CMM, Karolinska Institute, Sweden), during investigation of patients with possible Multiple Sclerosis, diagnosis criteria described in Recommended Diagnostic Criteria for Multiple Sclerosis: Guidelines from the International Panel on the Diagnosis of Multiple Sclerosis, W. Ian McDonald et al, Ann Neurol; 50, 121-127 (2001).

CSF samples were acquired with lumbar punction and thereafter the tubes were centrifuged and CSF without cells was frozen until further analysis. Patient information is provided in Table 1.

Table 1. Patients and diagnosis

Sample preparation

All CSF samples were affinity purified with POROS anti-HSA column, 2 ml (Applied Biosystems, USA) and a HiTrap Protein G column, 1 ml (GE healthcare, USA) to remove Albumin and IgG respectively. The columns were connected in series during the purification process. The purification was performed on FPLC, LCC-501 PLUS (GE healthcare, USA). The flow rate was lml/min during the procedure. The samples were purified according to manufacturer's instructions. Briefly, the sample was diluted in 10 mM Tris-HCl pH 7.0 (Bio-Rad, Hercules, CA, USA) binding buffer including Complete^™ protease inhibitor cocktail (Roche, Germany) 1 :1. Thereafter, the sample was filtered with a 0.45 μm filter (Pall, USA). The solution was thereafter loaded onto the columns with an auto injector. The flow through was collected in 2 ml fractions pooled and frozen until further preparation and analysis. Elution of bound proteins was made with 10 column volumes (CV) 10 mM Tris-HCl, pH 2.0 elution buffer and the column were cleaned with 10 CV 1.0 M NaCl (Merck, USA) of regeneration buffer and finally 10 CV of binding buffer as preparation for a new sample.

Desalting and concentration Individual samples were placed in a 15 ml Amni con-Ultra spin column with a cut-off at 5 KDa (Millipore, USA). The centrifugation was 3X40" + 1X30" and the sample was diluted in Tris-HCl pH 7 between each centrifugation step. The decrease insalt concentration was estimated to be <2000 times and it was performed in Megafuge2.0 R for 4000 rpm in 4⁰C. After centrifugation the remaining sample was transferred to 1.5 ml eppendorf tubes

(Eppendorf, USA) and speedvaced until dryness. Thereafter the samples were frozen until the following day.

SDS-PAGE for detection of protein concentration To adjust for different protein concentrations in the samples, one-dimensional gel electrophoresis followed by image analysis and the total protein concentration were determined. The sample was resolved in 25 μl sample buffer, Nupage LDS Sample Buffer (4X concentration, Invitrogen, USA) with 5% glycerol (BDH laboratory, UK) and 5OmM DTT (DTT, Servan, Germany) added and boiled for 3X15" in 95⁰C on a plate heater. Between the boiling steps, samples were mixed accurate for 5"and after the last boiling step 75 μl Rh (see below) buffer was added to a final volume of 100 μl and the sample was finally mixed for 15". 1.2 μl of boiled sample was transferred into a 1.5 ml eppendorf tube and 10.8 μl Nupage LDS Sample Buffer (Invitrogen, USA) was added to an final volume of 12 μl. Ten μl were added onto each lane on Novex gradient gels (bis-tris 10 lanes, 4-14 %, Invitrogen, USA) The gels were run for 30"in MES buffer (Invitrogen, USA) at 200V, constant run. Thereafter the gels were put into fixation solution (FS) (20% Ethanol and 7% acetic acid) for more than 30" . To visualise total protein the gels were washed in Milli Q water MQ water and then placed in 75 ml Sypro Ruby® stain (Molecular Probes, Inc. USA) overnight as described by [Kiera Berggren, Elena Chernokalskaya, Thomas H. Steinberg, Courtenay Kemper, Mary F. Lopez, Zhenjum Diwu, Richard P. Haugland,

Wayne F. Patton, Proteomics, 1, 54-665, (2001)]. The following day the gels were washed in fixation solution once for 5" followed by MQ 3X15", thereafter the gels were scanned with Molecular Imager FX (Bio-Rad, Hercules, CA, USA) at 100 μm resolution. To adjust for different protein concentrations in the samples a volume report analysis was made with the Quantity One (Bio-Rad, Hercules, CA, USA). Two-dimensional gel electrophoresis

Before isoelectric focusing, samples were wortexed 3(Tand centrifuged 15" at 13000Xg to erase insoluble molecules. Thereafter the estimated equal protein amounts in their respectively volume were transferred to 1.5 ml eppendorf tubes and rehydration solution (RH; Urea 8 M (Sigma, USA) DTT 19.5 mM, NP-40 (10%) 0.5 % (v/v) (USB Corporation, USA) IPG-buffer 4-7, 0.5 % (v/v) (GE healthcare, USA) Glycerol 7 % (v/v) CHAPS 1.5 % (Genomic solutions, USA), thiourea 2M, (Fluka, Germany)) was added to a final volume of 460 μl. 2 μl BFB was added to give colour. The sample was placed in a porslin tray and the strip was placed with the gel facing down. Thereafter the strip was covered with Plus one mineral oil (GE Healthcare, USA) and a plastic lid was placed on the top. Isoelectric focusing was performed in IPGphor (GE Healthcare, USA) with IPG strips pH4-7 Liner, 24 cm (GE Healthcare, USA) for a total 120kVhrs. After the run the strips were sealed in plastic bags and stored in -35⁰C. Prior to the 2-D run, the IPG strips were subjected to a two-step reduction and alkylation step by equilibrating the strips for 15 min first in 50 mM Tris-HCl, pH 6.8, 6 M urea, 30% v/v glycerol, 2% w/v SDS (Bio-Rad, Hercules, CA, USA), and 65 mM DTT, and then for 15 min in 50 mM Tris-HCl, pH 8.8, 6 M urea, 30% v/v glycerol, 2% w/v SDS, and 259 mM iodoacetamide (IAA, Matrix Scientific, USA). Thereafter the strips were placed on the top of the gel and sealed with heated agarose (1% w/v, Low melting agarose, USB Corporation, USA). The gels were allow to cool down before placed in a Hoefer Isodalt tank with Tris/glyc/SDS running buffer (Bio-Rad, Hercules, CA, USA) for > 19h on 10Ov constant. The 2-D separation was conducted in 1.0 X 220 X 200 mm thick 12,5% polyacrylamide gel. Gels were stained using automated strainers (GE Healthcare, USA) for total protein staining with Sypro Ruby^®. The autostainer program included the following step; 2X 15'MQ, 3X 30'fixation, 12h Sypro Ruby^®, 3X 15'MQ for and final step in fixation solution. Thereafter the gels were scanned with Molecular Imager^® FX at 100 μm resolution. After scanning the gels is stored in plastic bags in a 0.01% sodium azid solution. Image analysis

Image files (16 bit grey levels and lOOμm resolution) representing SyproRuby® stained gels were processed for background subtraction and protein spot detection using one defined set of parameters. These parameters were optimized using tools given by the software PDQuest (version 7.3, Bio-Rad, Hercules, CA, USA). Detected protein spots were then matched between gels and a synthetic master image was prepared to represent most of the protein spots present in all gels. The quantity of each protein spot was expressed as ppm (parts per million) of the total sum of the integrated spot volumes of the given gel image. This procedure allow for quantitative comparison of all protein spots detected in all gels. Protein spots of interest were excised from gels using a spot cutter robot (Bio-Rad, Hercules, CA, USA), transferred to 96-well plates.

Data analysis

The image analysis resulted in 1499 detected and matched spots for the whole matchset, which included the patient groups described in Tab.1. Due to biological and experimental variation it is not possible to match all spots in all gels. For example, in some cases the spot can be missing due to low expression level and in other cases the spot is present on the gel, but has been missed out during the matching. Thus, there will be values that are missing for some spots in some gels. Missing values are represented as zeros in the data- table, regardless of the reason the spot is missing. Therefore, in the data analysis, two approaches were taken to handling missing values that resulted in two datasets. In one dataset, all zeros were replaced by a low value (2 ppm) that could be considered as a background value (zeros were replaced to allow data to be log transformed) - dataset 1. In the other approach, data were imputed using a model-based approach, which utilises information on correlations between spots and/or gels in replacing missing values [LS impute: accurate estimation of missing values in microarray data with least squares methods Nucleic Acids Research 2004 VoI 32 No 3 Hellem Bø T., Dysvik B., Jonassen L] - dataset 2, Filtering of spots was done with respect to each MS group (Tab.l): for dataset 1 the criterion was set that at least 40 % of the samples in either MS group or control (OND/HC) should be matched for a spot to be included in the dataset. For dataset 2, a somewhat stricter criterion was used: a spot should be matched in at least 50% of the samples in either MS or the control group.

Data was logtransformed and batch correction was performed on a per spot basis using a mixed models approach to estimate batch effects (Applied Mixed Models in Medicine, Brown, H. and Prescott, R. Wiley 2nd ed 2006) prior to multivariate modelling.

Partial Least Squares (PLS) was used to model the data. (PLS-regression: a basic tool of chemometrics Chemometrics and Intelligent laboratory systems Wold S, Sjόstrόm M, Eriksson, L, 2001 58 109-130) modelling. It is a regression method that reduces the dimensions in the data through maximising the co variance of the predictor matrix (X) with the response matrix (Y), keeping the corresponding dimensions (PLS components/latent variables). It is possible to identify variables that are important for the relationship between X and Y. One such variable importance measure is the Variable Importance in the Projection (VIP) parameter. VIP is a weighted sum of squares of the PLS weights, with the weights calculated from the amount of Y-variance of each PLS component in the model. Here, the predictor matrix is the 2DE data, and the response is a binary vector denoting class membership, in this case zeros represents the OND/HC class and ones each of the MS classes (Tab. 1). To determine the class memberships for new samples predicted with the model, a cutoff needs to be set for the y, such that if the predicted y value is below the cutoff, the predicted class membership will be OND/HC in this case, and if the predicted y value is above the cutoff, the predicted class membership will be CIS, RR rem, RR rel or SP (Tab.l). In addition to these classes or patient groups, two new groups were formed: one consisting of MS patients with clinically low level of neurodegeneration (inclusion criteria: diagnosis CIS and RR, low level of neuroinflammation, low MRI score and EDSS <= 3, N=8) and another group consisting of MS patients with high grade of neurodegeneration (inclusion criteria: diagnosis SP, low level of neuroinflammation,

EDSS> 3.5, no limit for MRI score, N=I 1) were defined and data compared by PLS. The aim of this comparative analysis (called "ND") was to identify neurodegeneration markers.

The PLS modeling was carried out in Matlab (The Mathworks, Inc) using the PLS toolbox (Eigenvector Research) Hierarchical clustering was performed in Spotfire in order to provide a visualisation of the data. Protein identification

In-gel digestion: Protein spots of interest were excised from gels using the EXQUEST spot cutter robot (Bio-Rad, Hercules, CA, USA), transferred to 96-well plates. Up to 6 protein spots of same spot number were pooled to each well in order to facilitate the identification of low abundant protein spots. The excised gel plugs were subjected to distaining using a wash solution consisting of 70% ACN in 25 mM ammonium bicarbonate. The gel plugs were incubated this wash solution for 10 minutes. This washing procedure was repeated three times. Finally, the wash solution was removed followed by speed vaccing for 20 minutes. About 15 μL trypsin solution (0,075 μg) was added to the gel plugs and digestion was performed over night at 37⁰C. Finally, extraction was performed during 1 hour by adding 20 μL of extraction solution (1% ACN, 0.1% TFA).

High Sensitivity Micro-Tech Workstation for protein identification: A microtechnology workstation was used for high sensitivity protein analysis and identification of targets and biomarkers within the study. This microtech platform builds on chip integrated solid-phase microextraction array and a microdispenser for sample purification and trace enrichment of peptides as previously described (Wallman et al, Electrophoresis, 2004, 25, 3778-3787). Briefly, the capillary mircofluidic system is operated in an automated set-up. Chip- integrated sample clean-up of the protein sample, performed in a 96-array chip format. The microextraction array was loaded with solid-phase media (Poros R2 50 μm beads) for purification and enrichment of proteomic samples. Samples bound to the microchip were eluted in a volume of 100 nL. Next, the protein sample is eluted by utilizing a sequential capillary action that is docking to piezoelectric microdispencer. The subsequent transfer is made to the MALSI TOF mass spectrometry target plate where typically a burst of 1000 droplets of the sample is spotted onto the MALDI plate. By this approach multi-layer depositions are achieved resulting in protein signal amplification in the MALDI instrument. This micro-tech principle provide high quality data from samples in the picomolar range. The built-in force feed-back control also further ensures precise and robust integration and interfacing of solid phase chip enrichment and piezodispencing technology. The micro-proteomic platform was compared to corresponding commercial preparation protocols, showing higher MS signal intensities for peptides generated from the resulting 2D-gel spots.

LC-MALDI-MS/MS: Reversed-phase chromatography was performed with an Agilent nano 1100 HPLC system (Agilent Technologies, Waldbronn, Germany). The HPLC effluent was directly fractionated onto a 144 position ABI MALDI target plate using an Agilent micro fraction collector and spots were deposited every 30 seconds during the gradient (90 spots/run). The spots were allowed to dry completely prior to addition of I μL of CHCA matrix. The MS/MS data from the MALDI-TOF/TOF instrument was acquired acording to a method previously described by Zhen et al. (J. Am. Soc. Mass Spectrom. 2004, 15, 803-822). A standard peptide mixture containing 6 peptides diluted to about 500 fmol/μL were applied on the six calibration spot positions of the target plate and used as external calibration points.

Protein identification by database searching: MS/MS data obtained from the MALDI- TOF/TOF instrument were searched using Mascot as the search engine. All searches were performed against the human, rat, and mouse subset of in-house protein sequence databases (Genseq P, RefSeqP, PDB, PIR, SwissProt and TREMBL). The Global Proteome Server (GPS) was used for submitting data acquired from the TOF/TOF for database searching. The Mascot searching was performed using the default settings for the TOF/TOF instrument as supplied by Matrix Science (peptide mass tolerance of 50 ppm and a fragment mass tolerance of 0.2 Da). Oxidation (M) and carbamidomethyl were allowed as variable modifications.

Predictive models were built with an aim to identify a minimum number of markers that would give as good predictive value as possible. To this end, a variable selection procedure was coupled with a procedure for evaluating predictive performace. The latter is important to avoid overfitting the data. The procedure works as follows:

A model was built on the training data, variable importance weights (VIP) calculated and the test set was predicted on the model. The percentage correctly classified samples was then recorded and new models were built on successively reduced numbers of variables as ranked by the VIP parameter. This process was then repeated for 100 random partitions of the samples into training and test sets, for models with a varying number of PLS components (1-10). Prior to building a model, the training set was standardized to zero mean and unit variance. The scaling parameters obtained from the training set were then applied to the test set prior to performing the prediction. The model optimization was performed on two datasets, resulting from two different approaches to handling missing values (see above). In one dataset, missing values were considered to arise from that the protein levels were below the detection limit, and were replaced by a low value. In the other dataset, missing values were replaced using the LS impute algorithm. Variable ranks from the two models were combined to form an overal variable importance rank, and the top 50 variables were chosen for the final model. The corresponding protein spots were cut out from 2D-gels and identified by masspectrometry (Table 2-5) as described above.

Multiplex immunoassay

Microsphere-based multiplex assays for ten proteins were developed using antigen-specific capture and detection antibodies in a sandwich format (the assay for α-2 macroglubulin is a competitive assay) and other optimized reagents. Due to different requirements on sample dilution a three-plex assay for alpha- 1-antichymotrypsin, alpha-2 macroglobulin and angiotensinogen, and a seven-plex assay for contactin 1, alpha-2-HS-glycoprotein (fetuin), fibulin-1, neural cell adhesion molecule 1 (NCAM 1), neuronal cell adhesion molecule(NrCAM), superoxide dismutase 1, vitamin D-binding protein were developed. Prior to assay CSF samples were pre-diluted 10-fold for the three-plex and 200-fold for the seven-plex. All incubations toke place at room temperature in the dark. In the wells of a hard-bottom microtiter plate, a diluted mixture of capture-antibody microspheres (5 μL) were mixed with 5 μL blocking buffer and 10 μL standard, pre-diluted sample or control. The plate was incubated for 1 hour. 10 μL biotinylated detection antibody (or for α-2 macroglubulin a biotinylated antigen) were added to each well, the contents thoroughly mixed and the plate incubated for 1 hour. 10 μL diluted streptavidin-phycoerythrin were added to each well, the contents thoroughly mixed and the plate incubated for 30 minutes. A filter-membrane microtiter plate was pre-wetted by adding 100 μL wash buffer followed by aspiration via a vacuum manifold device. The reaction contents of the hard-bottom plate were then transferred to the corresponding wells of the filter plate. All wells were vacuum- aspirated and the contents were washed twice with 100 μL wash buffer. After the last wash, 100 μL wash buffer was added to each well and the washed microspheres were resuspended with thorough mixing. The plate was then analyzed on a Luminex 100 Analyzer.

Validation studies

A second set of samples from MS patients and OND patient controls were collected at Karolinska Hospital Stockholm, Sweden (provided by Professor Tomas Olsson, CMM, Karolinska Institute, Sweden), during investigation of patients with possible Multiple Sclerosis, diagnosis criteria described in Recommended Diagnostic Criteria for Multiple Sclerosis: Guidelines from the International Panel on the Diagnosis of Multiple Sclerosis, W. Ian McDonald et al, Ann Neural; 50, 121-127 (2001). CSF samples were collected by lumbar punction, the collection tubes were centrifuged and CSF without cells was frozen until analysis. The concentrations of alpha- 1-antichymotrypsin, alpha-2 macroglobulin, angiotensinogen, contactin 1, alpha-2-HS-glycoprotein (fetuin), fibulin-1, neural cell adhesion molecule 1 (NCAM 1), neuronal cell adhesion molecule(NrC AM), superoxide dismutase 1 , vitamin D-binding protein were measured using the multiplex assay. Patient information and concentrations of each protein are provided in Table 7. A third set of samples from MS patients before onset of treatment and after six and tvelve months, respectively, of administration of tysabri (natalizumab) were collected at Karolinska Hospital Stockholm, Sweden (provided by Professor Tomas Olsson, CMM, Karolinska Institute, Sweden). CSF samples were collected by lumbar punction, the collection tubes were centrifuged and CSF without cells was frozen until analysis. The concentrations of alpha- 1-antichymotrypsin, alpha-2 macroglobulin, angiotensinogen, contactin 1, alpha-2-HS-glycoprotein (fetuin), fϊbulin-1, neural cell adhesion molecule 1 (NCAM 1), neuronal cell adhesion molecule (NrCAM), superoxide dismutase 1, vitamin D-binding protein were measured using the multiplex assay. Patient information and concentrations of each protein are provided in Table 8. Table 2. Identified proteins from analysis group CIS: controls vs clinically isolated syndrome

SSP Mr Pi VIP SwissProt # Protein name and MS/MS seque

(kDa) Rank (human)

5817 102 5.57 1 CNTNl Contactin 1

6806 115 5.99 4 A2MG Alpha-2-macroglobulin

1804 104 4.52 15 TRFE Serotransferrin

5803 102 5.51 17 CNTNl Contactin 1

3606 73 5.00 20 CO9 Component C9

3815 107 5.08 26 CERU Ceruloplasmin

408 50 4.39 42 A2GL Leucine-rich alpha-2-glycoprotein

2501 67 4.73 57 ANGT Angiotensinogen

Table 3. Identified proteins from analysis group SP: controls vs secondary progressive MS

SSP Mr pi VIP SwissProt # Protein name and MS/MS sequence

(kDa) Rank (human)

5114 18 5.67 1 SODl Superoxide dismutase 1

3821 119 5.13 4 A2MG Alpha-2-macroglobulin

4414 48 5.38 6 PAM Peptidylglycine alpha-amidating monooxygenase isoform b

4108 21 5.28 7 AGRN Agrin

3727 101 5.16 11 NRCAM Neuronal cell adhesion molecule

7112 19 6.34 13 KLK6 Kallikrein 6

4719 100 5.37 14 NRCAM Neuronal cell adhesion molecule

2218 31 4.91 18 NID2 Nidogen-2 precursor

513 69 4.37 34 AACT Alpha- 1 -antichymotrypsin

1109 23 4.55 37 A4 Amyloid beta A4 protein (fragment)

4418 50 5.43 38 PEDF Pigment epithelium-derived factor

5223 33 5.70 41 APOE Apolipoprotein E

6307 42 5.90 44 CHI3L1 Chitinase-3-like protein 1

5803 102 5.51 48 CNTNl Contactin 1

Table 4. Identified proteins from analysis groups: controls vs relapsing/remitting MS Italic text equals relapsing and non-italic equals remitting group (RR rel and RR rem)

SSP Mr pl VIP SwissProt # Protein name and MS/MS sequen

(kDa) Rank (human)

4304 35 5.26 1 APOE Apolipoprotein E

2501 67 4.73 2 ANGT Angiotensinogen

5812 101 5.63 4 CNTNl Contactin 1

6806 115 5.99 5 A2MG Alpha-2-macroglobulin

6206 29 5.86 7 SODE Extracellular superoxide dismutase

2721 92 4.87 8 FBLNl Fibulin-1

6307 42 5.90 9 CHI3L1 Chitinase-3-like protein 1

4315 41 5.47 13 HAPTO Haptoglobin

2215 29 4.90 14 AMBP Alpha- 1 -microglobulin

1516 67 4.69 14 CNDPl Carnosinase 1

3314 43 5.11 18 HEMO Hemopexin

4316 38 5.48 19 FETUA Alpha-2-HS-glycoprotein

3821 119 5.13 21 A2MG Alpha-2-macroglobulin

4307 43 5.29 22 APOE Apolipoprotein E

3722 97 5.11 27 CERU Ceruloplasmin

1832 103 4.58 34 NCAIl Neural cell adhesion molecule 1

2302 43 4.72 35 CO3 Complement C3 fragment

3408 49 5.09 37 GELS Gelsolin

4705 99 5.22 37 NRCAM Neuronal cell adhesion molecule

Table 5. Identified proteins from analysis "ND": low level of neurodegenerative MS vs high level of neurodegenerative MS, defined by clinical criteria (see "Methods")

SSP Mr pl VIP SwissProt # Protein name and MS/MS seq

(kDa) Rank (human)

2501 67 4.73 1 ANGT Angiotensinogen

1804 104 4.52 2 NCAI l Neural cell adhesion molecule 1

2515 59 4.74 6 AlAT Alpha- 1 -antitrypsin

1504 67 4.47 15 AACT alpha- 1 -antichymotrypsin

5618 86 5.73 21 GELS Gelsolin

4804 106 5.22 32 CERU Ceruloplasmin

4211 32 5.29 33 APOE Apolipoprotein E

4514 65 5.40 35 APOE Apolipoprotein E

1406 48 4.51 44 CO4A Complement C4-A

A representative 2D-gel is shown in figure 1 and the locations of the 43 identified protein spots are zoomed in. Each spot is given a unique database SSP number by the PDQuest software. Tables 2-5 show protein identities obtained by mass spectrometry analysis and estimated molecular weight/isoelectric point. Table 6 below exemplify a selection of proteins, which may be feasible for antibody-based validation.

Table 6.

Table 7

Protein OND RR RR SP PP rem rel

N = 60 N = 48 N = 13 N = 43 N = 9

Angiotensinogen Mean 15.3 5.78 2.66 15.0 16.9

SD 85.1 7.14 1.69 13.8 17.9

Median 3.53 3.92 2.34 10.6 11.2

Vitamin D-binding protein Mean 935 978 884 1240 872

(VDBP)

SD 480 525 456 495 318

Median 857 912 819 1150 869

Alpha- 1 -antichymotrypsin Mean 23400 27900 27800 31800 27600

SD 5880 5920 7830 8790 6120

Median 22900 27500 24500 32000 26400

Neural cell adhesion molecule Mean 208 234 215 217 253

1 (NCAM 1)

SD 109 90 106 63.9 154

Median 185 222 186 227 269

Alpha-2 -macroglobulin Mean 1710 2090 1960 2210 2190

SD 595 528 515 990 557

Median 1720 2050 1940 2090 2470

Neuronal cell adhesion Mean 20.9 24.3 23.9 22.1 27.4 molecule (NrCAM)

SD 14.9 11.2 16.5 14.0 22.2

Median 16.5 22.1 18.6 20.0 21.1

Fibulin 1 Mean 5790 6930 6700 7090 6030

SD 2540 2000 2420 1930 2600

Median 5420 6720 7100 7080 6820

Contactin 1 Mean 84.1 93.7 104 97.1 90.0

SD 54.8 38.5 52.5 41.3 48.6

Median 68.6 84.4 120 88.9 97.6

Superoxide dismutase 1 Mean 283 306 296 312 264

(SODl)

SD 91.8 78.6 75.1 67.6 135

Median 296 331 295 322 285

Alpha-2-HS-glycoprotein Mean 1640 1770 1760 1860 1620

(Fetuin A)

SD 945 715 609 616 498

Median 1530 1710 1840 1820 1720 Table 8

Protein 12 m treatment 6 m treatment

N=27 N=9

Before At 12 m Before At 6 m

Angiotensinogen Mean 14.6 8.52 7.57 3.19

SD 44.1 22.8 12.5 1.65

Median 3.38 4.62 2.45 3.15

Vitamin D-binding protein Mean 908 916 1440 1210 (VDBP) SD 349 419 612 769

Median 912 850 1300 1100

Alpha- 1 -antichymotrypsin Mean 26600 23900 28500 23100

SD 7080 5980 4930 5250

Median 25000 23400 28200 24200

Neural cell adhesion molecule Mean 194 204 253 174 1 (NCAM 1) SD 128 118 80.0 48.7

Median 147 172 229 167

Alpha-2 -macroglobulin Mean 2000 1910 2270 1910

SD 687 714 477 677

Median 1810 1860 2180 1830

Neuronal cell adhesion Mean 18.4 21.7 27.5 18.1 molecule (NrCAM) SD 15.8 16.3 8.67 8.09

Median 11.6 14.9 29.1 19.9

Fibulin 1 Mean 5730 5800 7350 5660

SD 2400 2530 983 1450

Median 5400 5780 7210 5770

Contactin 1 Mean 83.0 84.3 107 75.2

SD 67.0 55.3 32.6 19.9

Median 64.7 68.7 108 72.2

Superoxide dismutase 1 Mean 294 305 319 330 (SODl) SD 73.5 89.0 48.7 32.9

Median 296 323 330 351

Alpha-2-HS-glycoprotein Mean 1540 1470 2400 2030 (Fetuin A) SD 450 540 1390 1320

Median 1570 1350 2020 1650 Additional predictive models were constructed from measurements of the MSPs in the validation set as described above. Prior to analysis of the data, values below least detectable dose (LDD) were set to LDD/2. A natural log-transform, was applied to the data from the immunoassays described above, for all subjects, and all analytes prior to subsequent analysis. Two separate models were constructed using the plsr package from R [reference: The pis Package: Principal Component and Partial Least Squares Regression in R. Mevik, B.-H., Wehrens, R.; Journal of Statistical Software, 2007, 18(2), 1-24], with OND subjects classed as 0 and either RR ("RR model") or SP subjects ("SP model") classed as 1. The sensitivity and specificity of the models was calculated using the average of LOO ("Leave-one-out") cross-validation rounds at a range of cut-offs. These are presented as ROC (Receiver Operator Characteristic) plots in figure 2. The models are informative for the classification task.

The mean levels of the protein concentrations were further compared between the different MS groups versus the control group for each protein individually. To this end, a linear model with disease group and sex as fixed effects was applied to each protein variable. Pairwise comparisons for each MS group versus the control group were carried out as contrasts within the model. Estimated differences and p-values are presented in Table 9.

Protein concentrations were also compared based on pre vs. post Tysabri treatment. In this analysis, patient data was modelled using a mixed effects model with patient as random effect and time as fixed effect. This model takes into account that observations from the same patients are correlated, but assumes that observations from different patients are independent. Six and 12 months duration data were modeled separately. Estimated differences and p-values are presented in Table 10. No adjustments for multiplicity were performed.

Table 9

Results from comparisons of MS subgroups (RR rem [n=76], RR rel [n=22], SP [n=43], PP [n=10]) to OND [n=58] Lower Upper 95% 95%

Variable Comparison Ratio CI CI P-value

Alpha- 1- RR rem vs OND 1.21 1.11 1.31 <.0001 antichymotrypsin

RR rel vs OND 1.20 1.07 1.35 0.0023

SP vs OND 1.37 1.25 1.51 <.0001

PP vs OND 1.19 1.02 1.40 0.0299

Alpha-2-macroglobulin RR rem vs OND 1.24 1.12 1.39 0.0001

RR rel vs OND 1.20 1.03 1.40 0.0228

SP vs OND 1.29 1.13 1.46 0.0001

PP vs OND 1.31 1.06 1.62 0.0129

Angiotensinogen RR rem vs OND 0.97 0.66 1.41 0.8696

RR rel vs OND 0.85 0.50 1.46 0.5600

SP vs OND 2.96 1.92 4.56 <.0001

PP vs OND 1.59 0.76 3.33 0.2148

Contactin 1 RR rem vs OND 1.14 0.93 1.39 0.1982

RR rel vs OND 1.31 0.98 1.75 0.0663

SP vs OND 1.27 1.01 1.60 0.0443

PP vs OND 1.10 0.74 1.63 0.6251

Fetuin A RR rem vs OND 1.14 0.99 1.32 0.0715

RR rel vs OND 1.15 0.94 1.42 0.1825

SP vs OND 1.20 1.02 1.42 0.0323

PP vs OND 1.06 0.80 1.41 0.6859

Fibulin 1 RR rem vs OND 1.19 1.03 1.36 0.0163

RR rel vs OND 1.19 0.97 1.45 0.0915

SP vs OND 1.30 1.11 1.52 0.0014

PP vs OND 1.03 0.78 1.35 0.8541

NCAM l RR rem vs OND 1.09 0.90 1.32 0.3741

RR rel vs OND 1.00 0.76 1.32 0.9877

SP vs OND 1.13 0.91 1.41 0.2799

PP vs OND 1.12 0.77 1.63 0.5621

NrCAM RR rem vs OND 1.11 0.88 1.42 0.3770

RR rel vs OND 1.12 0.79 1.58 0.5268

SP vs OND 1.08 0.82 1.42 0.5904 Lower Upper 95% 95%

Variable Comparison Ratio CI CI P-value

PP vs OND 1.14 0.71 1.83 0.5814

SODl RR rem vs OND 1.11 0.98 1.26 0.0943

RR rel vs OND 1.08 0.90 1.29 0.4211

SP vs OND 1.14 0.99 1.32 0.0630

PP vs OND 0.89 0.70 1.13 0.3449

VDBP RR rem vs OND 1.09 0.91 1.30 0.3369

RR rel vs OND 0.98 0.76 1.27 0.9053

SP vs OND 1.36 1.11 1.67 0.0029

PP vs OND 1.01 0.72 1.43 0.9375

Table 10

Results from comparisons of post vs pre Tysabri, for 6 months treatment(n=9), and 12 (n=27) months treatment respectively.

Treatment Lower Upper duration 95% 95%

Variable (months) Ratio CI CI P-value

Alpha- 1 -antichymotrypsin 6 0.80 0.71 0.91 0.0029

12 0.90 0.80 1.01 0.0794

Alpha-2-macroglobulin 6 0.82 0.66 1.02 0.0667

12 0.95 0.80 1.12 0.5433

Angiotensinogen 6 0.82 0.37 1.84 0.5929

12 0.90 0.59 1.39 0.6247

Contactin 1 6 0.71 0.52 0.98 0.0395

12 1.07 0.81 1.41 0.6117

Fetuin A 6 0.77 0.56 1.04 0.0817

12 0.94 0.81 1.10 0.4188

Fibulin 1 6 0.74 0.54 1.02 0.0604

12 1.00 0.81 1.23 0.9618

NCAM 1 6 0.70 0.54 0.90 0.0123

12 1.13 0.88 1.44 0.3199

NrCAM 6 0.63 0.44 0.89 0.0162 Treatment Lower Upper duration 95% 95%

Variable (months) Ratio CI CI P-value

12 1.20 0.82 1.76 0.3322

SODl 6 1.04 0.87 1.24 0.6108

12 1.03 0.90 1.16 0.6737

VDBP 6 0.69 0.48 1.01 0.0560

12 1.00 0.85 1.17 0.9664

Claims

1. A method for screening or diagnosis of multiple sclerosis in a subject, for determining the stage or severity of multiple sclerosis in a subject, for identifying a subject at risk of developing multiple sclerosis, or for monitoring the effect of therapy administered to a subject having multiple sclerosis, said method comprising:

(a) analysing a test sample of body fluid from the subject by two-dimensional electrophoresis to generate a two-dimensional array of features, said array comprising one or more of the following one or more of the following multiple sclerosis proteins (MSPs): alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; Apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS- glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha- amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

(b) comparing the abundance of the one or more MSPs in the test sample with the abundance of the one or more of said proteins in a body fluid sample from one or more subjects free from multiple sclerosis, or with a previously determined reference range for that feature in subjects free from multiple sclerosis.

2. A method for screening or diagnosis of multiple sclerosis in a subject, for determining the stage of multiple sclerosis in a subject or for monitoring the effect of therapy administered to a subject having multiple sclerosis, said method comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following multiple sclerosis proteins (MSPs): alpha- 1 -antitrypsin; leucine-rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1-antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; Apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fibulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1 ; extracellular superoxide dismutase; and serotransferrin.

3. The method of claim 1 or 2, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is clinical isolated syndrome multiple sclerosis.

4. The method of claim 3, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine- rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1- antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

5. The method of claim 1 or 2, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is relapsing remitting multiple sclerosis.

6. The method of claim 5, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine- rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1- antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

7. The method of claim 1 or 2, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is secondary progressive multiple sclerosis.

8. The method of claim 7, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine- rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1- antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

9. The method of claim 1 or 2, which is for determining the stage of multiple sclerosis in a subject, wherein said stage is neurodegenerative stage of multiple sclerosis.

10. The method of claim 9, comprising quantitatively detecting, in a test sample of body fluid from the subject, one or more of the following MSPs: alpha- 1 -antitrypsin; leucine- rich alpha-2-glycoprotein; alpha-2-macroglobulin; amyloid beta A4 protein; alpha- 1- antichymotrypsin; agrin; alpha- 1 -microglobulin; angiotensinogen; apolipoprotein E; ceruloplasmin; chitinase-3-like protein 1; carnosinase 1; contactin 1; complement C3 fragment; complement C4-A; component C9; fϊbulin-1; alpha-2-HS-glycoprotein; gelsolin 3408; haptoglobin; hemopexin; kallikrein 6; neural cell adhesion molecule 1; nidogen-2 precursor; neuronal cell adhesion molecule; peptidylglycine alpha-amidating monooxygenase isoform b; pigment epithelium-derived factor; superoxide dismutase 1; extracellular superoxide dismutase; and serotransferrin.

11. The method according to any one of claims 1 to 10, said method being carried out in vitro.

12. The method according to any one of claims 1 to 10, said body fluid being selected from blood, serum, plasma, cerebrospinal fluid, urine, and saliva.

13. An antibody capable of binding to the MSPs according to claim 1.

14. An antibody according to claim 13, being a monoclonal antibody.

15. A kit comprising one or more antibodies according to claim 13 or 14, other reagents and instructions for use.

16. The kit of claim 15 for use in the screening or diagnosis of multiple sclerosis in a subject, for determining the stage or severity of multiple sclerosis in a subject, for identifying a subject at risk of developing multiple sclerosis, or for monitoring the effect of therapy administered to a subject having multiple sclerosis.

17. The kit according to claim 15 or 16 comprising a plurality of antibodies according to claim 13 or 14.

18. A pharmaceutical composition comprising a therapeutically effective amount of an antibody, or a fragment or derivative of an antibody according to claim 13 or 14, and a pharmaceutically acceptable carrier.

19. A method of treating or preventing multiple sclerosis, comprising administering to a subject in need of such treatment a therapeutically effective amount of an antibody according to claim 13 or 14.

20. A method of screening for agents that interact with one or more MSPs according to claim 1, said method comprising:

(c) contacting an MSP with a candidate agent; and

(d) determining whether or not the candidate agent interacts with the MSP.

21. The method according to claim 20, wherein the determination of interaction between the candidate agent and the MSP comprises quantitatively detecting binding of the candidate agent and the MSP.

22. A method of screening for or identifying agents that modulates the expression or activity of one or more more MSPs, according to claim 1, comprising:

(c) contacting a first population of cells expressing the MSP(s) with a candidate agent;

(d) contacting a second population of cells expressing said MSP(s) with a control agent; and (c) comparing the level of said MSPs in the first and second populations of cells, or comparing the level of induction of a downstream effecter in the first and second populations of cells.

23. A method of screening for or identifying agents that modulate the expression or activity of one or more more MSPs according to claim 1, said method comprising:

(c) administering a candidate agent to a first mammal or group of mammals;

(d) administering a control agent to a second mammal or group of mammals; and

(c) comparing the level of expression of the MSP(s), or mRNA encoding said MSP(s) in the first and second groups, or comparing the level of induction of a downstream effecter in the first and second groups.

24. The method according to claim 23, wherein administration of a candidate agent results in an increase in the level of said MSPs, or mRNA encoding said MSPs, or said downstream effecter in the first population of cells or mammals compared to the second population of cells or mammals.

25. The method according to any one of claims 24, wherein administration of a candidate agent results in a decrease in the level of said MSPs, or mRNA encoding said MSPs , or said downstream effecter in the first population of cells or mammals compared to the second population of cells or mammals.

26. A method of screening for or identifying agents that modulate the activity of one or more of the MSPs according to claim 1, said method comprising:

(b) in a first aliquot, contacting a candidate agent with the MSP(s) and;

(b) determining and comparing the activity of the MSP(s) in the first aliquot after addition of the candidate agent with the activity of MSP(s) in a control aliquot, or with a previously determined reference range.

27. The method according to any one of claims 23 to 26, wherein the MSP(s) is a recombinant protein.