EP2715361A1

EP2715361A1 - Methods for diagnosing multiple sclerosis

Info

Publication number: EP2715361A1
Application number: EP12724645.2A
Authority: EP
Inventors: Regina Reszka; Ulrike Rennefahrt; Susan Carvalho; Bernhard Hemmer
Original assignee: Metanomics Health GmbH
Current assignee: Metanomics Health GmbH
Priority date: 2011-05-31
Filing date: 2012-05-31
Publication date: 2014-04-09
Also published as: CA2834455A1; AU2012264688A2; AU2012264688A8; WO2012164026A8; WO2012164026A1; AU2012264688A1; JP2014517300A

Abstract

The present invention relates to the field of diagnostic methods. Specifically, the present invention contemplates a method for diagnosing multiple sclerosis in a subject, a method for identifying whether a subject is in need for a therapy of multiple sclerosis or a method for determining whether a multiple sclerosis therapy is successful. Moreover, contributed is a method for diagnosing or predicting the risk of an active status of multiple sclerosis in a subject. The invention also relates to tools for carrying out the aforementioned methods, such as diagnostic devices.

Description

METHODS FOR DIAGNOSING MULTIPLE SCLEROSIS

The present invention relates to the field of diagnostic methods. Specifically, the present invention contemplates a method for diagnosing multiple sclerosis, a method for identifying whether a subject is in need for a therapy of multiple sclerosis or a method for determining whether a multiple sclerosis therapy is successful. Moreover, contributed is a method for diagnosing or predicting the risk of an active status or the progression of multiple sclerosis in a subject. The invention also relates to tools for carrying out the aforementioned methods, such as diagnostic devices.

Multiple sclerosis (MS) affects approximately 1 million individuals worldwide and is the most common disease of the central nervous system (CNS) that causes prolonged and severe disability in young adults. Although its etiology remains elusive, strong evidence supports the concept that a T cell-mediated inflammatory process against self molecules within the white matter of the brain and spinal cord underlies its pathogenesis. Since myelin-reactive T cells are present in both MS patients and healthy individuals, the primary immune abnormality in MS most likely involves failed regulatory mechanisms that lead to an enhanced T cell activation status and less stringent activation requirements. Thus, the pathogenesis includes activation of encephalitogen- ic, i.e. autoimmune myelin-specific T cells outside the CNS, followed by: an opening of the blood-brain barrier; T cell and macrophage infiltration; microglial activation; demyelination, and irreversible neuronal damage (Aktas 2005, Neuron 46, 421 -432, Zamvil 2003, Neuron 38:685- 688 or Zipp 2006, Trends Neurosci. 29, 518-527). While much is known about the mechanisms responsible for the encephalitogenicity of T cells, little is known as yet regarding the body's endogenous control mechanisms for regulating harmful lymphocyte responses into and within the CNS. In addition, despite extensive studies on T-cell mediated demyelination, the damage processes in vivo within the CNS are not fully understood.

Currently, diagnostic tools such as neuroimaging, analysis of cerebrospinal fluid and evoked potentials are used for diagnosing MS. Magnetic resonance imaging of the brain and spine can visualize demyelination (lesions or plaques). Gadolinium can be administered intravenously as a contrast agent to mark active plaques and, by elimination, demonstrate the existence of historical lesions which are not associated with symptoms at the moment of the evaluation. Analysing cerebrospinal fluid obtained from a lumbar puncture can provide evidence of chronic inflammation of the central nervous system. The cerebrospinal fluid can be analyzed for oligoclo- nal bands, which are an inflammation marker found in 75-85% of people with MS (Link 2006, J Neuroimmunol. 180 (1 -2): 17-28. However, none of the aforementioned techniques is specific to MS, only. Therefore, most often only biopsies or post-mortem examinations can yield a reliable diagnosis. Multiple sclerosis is a chronic demyelinating disease of the central nervous system that presents with variable signs and symptoms. This variability in the clinical presentation may result in misdiagnosis, unnecessary referrals and misleading information to the patients. Since MS is a clinically highly heterogeneous disease, diagnostic and prognostic markers are needed to facilitate diagnose, predict the course of the disease in the individual patient, the necessity of treatment and the kind of therapy (Bielekova & Martin 2004, Brain 127: 1463-1478). The response to the currently available therapies differs from patient to patient without any evidences from the 5 course of the disease. Markers would alleviate the choice of drug to apply, which will be even more important within the next years, when further drugs will come on the market. Furthermore, rapidly progressing patients should be treated from the beginning more aggressively than patients with a rather benign disease course. Markers of tissue damage and, in particular, neuronal damage may be only or higher expressed in patients with rapid progression and subse- 10 quent disability. On the other hand, treating the patients with an aggressive therapy with potentially devastating side effects requires therapy response markers as well as a risk management. Thus biomarkers for disease activity and response to therapy are valuable for determining the patient's prognosis, and can allow a personalized adjustment of therapy.

15 Accordingly, means and methods for reliably diagnosing MS and for evaluating the success of a therapy are highly desired but not yet available.

Therefore, the present invention relates to a method for diagnosing multiple sclerosis in a subject comprising the steps of:

ιφ determining in a sample of the subject the amount of at least one ceramide, or the total amount of ceramides, and

b) comparing the amount of the said at least one ceramide, or the total amount of ceramides to a reference amount, whereby multiple sclerosis is to be diagnosed. 5 In particular, the present invention relates to a method for diagnosing multiple sclerosis in a subject comprising the steps of:

a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2, and

b) comparing the amount of the said at least one biomarker to a reference amount, whereby 0 multiple sclerosis is to be diagnosed.

The method as referred to in accordance with the present invention includes a method which essentially consists of the aforementioned steps or a method which includes further steps. However, it is to be understood that the method, in a preferred embodiment, is a method carried 5 out ex vivo, i.e. not practised on the human or animal body. The method, preferably, can be assisted by automation.

The term "diagnosing" as used herein refers to assessing whether a subject suffers from the disease MS, or not. As will be understood by those skilled in the art, such an assessment, alt- 0 hough preferred to be, may usually not be correct for 100% of the investigated subjects. The term, however, requires that a statistically significant portion of subjects can be correctly assessed and, thus, diagnosed. Whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p-value determination, Student^'s t-test, Anno- va, Mann-Whitney test, etc.. Details are found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Preferred confidence intervals are at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, at least 95%. The p-values are, preferably, 0.2, 0.1 , 0.05, 0.01 , 0.005, 0.001 .

The term includes individual diagnosis of MS or its symptoms as well as continuous monitoring of a patient. Monitoring, i.e. diagnosing the presence or absence of MS or the symptoms ac- companying it at various time points, includes monitoring of patients known to suffer from MS as well as monitoring of subjects known to be at risk of developing MS. Furthermore, monitoring can also be used to determine whether a patient is treated successfully or whether at least symptoms of MS can be ameliorated over time by a certain therapy. The term "MS (multiple sclerosis)" as used herein relates to disease of the central nervous system (CNS) that causes prolonged and severe disability in a subject suffering therefrom. How to diagnose MS is well known in the art. In particular, MS can be diagnosed according to the criteria as disclosed in Polman et al. ("revised McDonald criteria", Ann Neurol 2005; 58:840-846) which herewith is incorporated by reference in its entirety with respect to its entire disclosure content. The pathogenesis of MS includes activation of encephalitogenic, i.e. autoimmune mye- lin-specific T cells outside the CNS, followed by an opening of the blood-brain barrier, T cell and macrophage infiltration, microglial activation, demyelination, and irreversible neuronal damage. There are four standardized subtype definitions of MS which are also encompassed by the term as used in accordance with the present invention: relapsing remitting, secondary progressive, primary progressive and progressive relapsing. The relapsing-remitting subtype is characterized by unpredictable relapses followed by periods of months to years of remission with no new signs of disease activity. Deficits suffered during attacks (active status) may either resolve or leave sequelae. This describes the initial course of 85 to 90% of subjects suffering from MS. In cases of so-called benign MS the deficits always resolve between active status. Secondary pro- gressive MS describes those with initial relapsing-remitting MS, who then begin to have progressive neurological decline between acute attacks without any definite periods of remission. Occasional relapses and minor remissions may appear. The median time between disease onset and conversion from relapsing-remitting to secondary progressive MS is about 19 years. The primary progressive subtype describes about 10 to 15% of subjects who never have remis- sion after their initial MS symptoms. It is characterized by progression of disability from onset, with no, or only occasional and minor, remissions and improvements. The age of onset for the primary progressive subtype is later than other subtypes. Progressive relapsing MS describes those subjects who, from onset, have a steady neurological decline but also suffer clear superimposed attacks. This is the least common of all subtypes. There are also some cases of atypi- cal MS which can not be allocated in the aforementioned subtype groups. As used herein, the term "multiple sclerosis" also encompasses the clinically isolated syndrome (frequently also referred to as "CIS"). Symptoms associated with MS include changes in sensation (hypoesthesia and paraesthesia), muscle weakness, muscle spasms, difficulty in moving, difficulties with coordination and balance (ataxia), problems in speech (dysarthria) or swallowing (dysphagia), visual problems (nystagmus, optic neuritis, or diplopia), fatigue, headache, acute or chronic pain, bladder and bowel difficulties. Cognitive impairment of varying degrees as well as emotional symptoms of depression or unstable mood may also occur as symptoms. The main clinical measure of disability progression and symptom severity is the Expanded Disability Status Scale (EDSS).

Further symptoms of MS are well known in the art and are described in the standard text books of medicine, such as Stedman or Pschyrembl.

In the studies carried out in the context of the present invention, it was shown that the bi- omarkers as shown in Table 1 and 2, are particularly useful for the early diagnosis of MS. Accordingly, the present invention particularly relates to a method for the early diagnosis of MS, and, thus, to the diagnosis of MS in an early stage of MS. The early stage of MS encompasses the time period of, preferably, three years, more preferably, two years, even more preferably, one year, and most preferably, six months after the onset of MS. Also preferably, the early stage of MS encompasses the time period from the first acute neurological event (attack) of MS until the second acute neurological event (attack) of MS. It may further encompass the time pe- riod from the first acute neurological event (attack) of MS until the third acute neurological event (attack) of MS. A neurological event, preferably, refers to a demyelinating event, more preferably, to an inflammatory demyelinating event. A subject who is in an early stage of MS, preferably, has two lesions in the central nervous system. More preferably, said subject has one lesion in the central nervous system. A lesion, preferably, is an area of the central nervous system that is inflamed and/or has been demyelinated. Such lesions can be, e.g., detected by MRI. Preferably, the subject who is in an early stage also shows symptoms of MS. Preferred symptoms, in particular neurological symptoms, are disclosed elsewhere herein.

The term "biomarker" as used herein refers to a molecular species which serves as an indicator for a disease or effect as referred to in this specification. Said molecular species can be a metabolite itself which is found in a sample of a subject. Moreover, the biomarker may also be a molecular species which is derived from said metabolite. In such a case, the actual metabolite will be chemically modified in the sample or during the determination process and, as a result of said modification, a chemically different molecular species, i.e. the analyte, will be the deter- mined molecular species. It is to be understood that in such a case, the analyte represents the actual metabolite and has the same potential as an indicator for the respective medical condition.

Moreover, a biomarker according to the present invention is not necessarily corresponding to one molecular species. Rather, the biomarker may comprise stereoisomers or enantiomeres of a compound. Further, a biomarker can also represent the sum of isomers of a biological class of isomeric molecules. Said isomers shall exhibit identical analytical characteristics in some cases and are, therefore, not distinguishable by various analytical methods including those applied in the accompanying Examples described below. However, the isomers will share at least identical sum formula parameters and, thus, in the case of, e.g., lipids an identical chain length and identical numbers of double bonds in the fatty acid and/or sphingo base moieties.

The biomarker to be used in the context of the method of the present invention, is preferably, a ceramide. Ceramides are lipid molecules which are composed of aminoalcohol, coupled to a single fatty acid via amid linkage. Sphingosine (2-aminooctadec-4-ene-1 ,3-diol). Preferably, the amino alcohol is sphingosine (2-aminooctadec-4-ene-1 ,3-diol), a long chain aliphatic amine. Other aminoalcohols, also referred to as "Long Chain Bases" (LCB), eg with different chain lengths such as d16-, d17- or d20-Sphingosine and also the respective saturated aminoalcohols (Dihydrosphingosine or Sphinganine) may occur. The nomenclature used to describe the different Ceramide species is according to the "Lipidmaps" classification system as described in "Update of the LIPID MAPS comprehensive classification system for lipids"; Fahy E., Subramaniam S., Murphy R., Nishijima M., Raetz C, Shimizu T., Spener F., van Meer G., Wakelam M., and Dennis E., Journal of Lipid Research 50, S9-S14 (2009).

The fatty acid coupled to sphingosine may have variable chain length and different degrees of saturation/unsaturation. Preferred ceramides are C21 -, C22, C23 or C24 ceramides. Particularly preferred ceramides to be used as a biomarker in the context of the method of the present invention are listed herein below and/or in Table 1 and/or 2.

Accordingly, the ceramide in the context of the methods of the present invention is preferably selected from the group of ceramides consisting of ceramide (d16:1 ,C22:0), ceramide

(d16:1 ,C23:0), ceramide (d16:1 ,C24:0), ceramide (d17:1 ,C22:0), ceramide (d17:1 ,C23:0), ceramide (d17:1 ,C24:0), ceramide (d17:1 ,C24:1 ), ceramide (d18:1 , C21 :0), ceramide

(d18:1 ,C22:0), ceramide (d18:1 ,C22:1 ), ceramide (d18:1 , C23:0), ceramide (d18:1 ,C23:1 ), ceramide (d18:1 , C24:0), ceramide (d18:1 , C24:1 ), ceramide (d18:2,C22:0), ceramide

(d18:2,C23:0), ceramide (d18:2,C24:0), and ceramide (d18:2,C24:1 ).

In a further preferred embodiment, the ceramide is selected from the group of ceramides consisting of ceramide (d16:1 , C22:0), ceramide (d16:1 , C23:0), ceramide (d16:1 , C24:0), ceramide (d17:1 , C22:0), ceramide (d17:1 , C23:0), ceramide (d17:1 , C24:0), ceramide (d17:1 , C24:1 ), ceramide (d18:1 , C21 :0), ceramide (d18:1 , C22:0), ceramide (d18:1 , C22:1 ), ceramide (d18:1 , C23:0), ceramide (d18:1 , C23:1 ), ceramide (d18:2,C22:0), ceramide (d18:2, C23:0), ceramide (d18:2, C24:0), and ceramide (d18:2,C24:1 ). In one embodiment, the ceramide is not ceramide (d18:1 , C24:0) or not ceramide (d18:1 , C24:1 ).

Preferred methods for the determination of ceramides are disclosed in the Examples or, are those known in the art, see, e.g. Kasumov et al., Analytical Biochemistry 401 (2010) 154 to 161 which hereby is incorporated by reference with respect to the entire disclosure content. In the method according to the present invention, at least one metabolite of the aforementioned group of biomarkers, i.e. the biomarkers as shown in Table 1 and/or Table 2, is to be determined. However, more preferably, a group of biomarkers will be determined in order to strengthen specificity and/or sensitivity of the assessment. Such a group, preferably, comprises at least 2, at least 3, at least 4, at least 5, at least 10 or up to all of the said biomarkers shown in the Tables. In addition to the specific biomarkers recited in the specification, other biomarkers may be, preferably, determined as well in the methods of the present invention.

In the context of the method of the present invention, it is also envisaged to determine in step a) of the methods of the present invention the total amount of ceramides in a sample instead of the amount of at least one biomarker as listed in Tables 1 to 3, in particular in Tables 1 and 2. Thus, the total ceramide content shall be determined. In step b) said total amount of ceramides shall be compared to a reference amount. Preferably, the total amount of C21 ceramides, C22 ceramides, C23 ceramides, or C24 ceramides is determined. More preferably, the total amount of C21 to C24 ceramides is determined. An increase of the total amount of ceramides as compared to the reference is, preferably, indicative for the diagnosis of MS, in particularly for the diagnosis of an early stage of MS. In a preferred embodiment of the method of the invention, said at least one biomarker is selected from the group of biomarkers listed in Table 1 a and/or Table 2a. An increase in such a biomarker is indicative for multiple sclerosis, in particular for an early stage of multiple sclerosis. Preferably, an increase of at least 10%, of at least 20%, of at least 30%, or of at least 50% is indicative for the diagnosis of MS (in an increasing order of preference). The same applies if the biomarker is a ceramide. The same applies also if the total amount of ceramides is determined in the sample.

In another preferred embodiment of the method of the present invention said at least one biomarker is selected from the group of biomarkers listed in Table 1 b and/or Table 2b. A de- crease in such a biomarker is indicative for multiple sclerosis, in particular for an early stage of multiple sclerosis. Preferably, a decrease of at least 10%, of at least 20%, of at least 30%, of at least 50% is indicative for the diagnosis of MS (in an increasing order of preference).

In a preferred embodiment of the method of the present invention, the amount of at least one biomarker as shown in Table 2 is determined, if the subject to be tested is suspected to be in an acute stage of MS. A subject who suspected to be in an acute stage of MS, preferably, shows symptoms of the acute stage of MS, whereas a subject who is not suspected to be in an acute stage of MS, preferably, does not show symptoms of the acute stage of MS. Preferably, the at least one biomarker is selected from the group of biomarkers listed in Table 2a if the subject to be tested is suspected to be in an acute stage of MS. An increase in such a biomarker is indicative for multiple sclerosis. Said increase is preferably an increase of at least 10%, of at least 20%, of at least 30%, of at least 50% (in an increasing order of preference).

Preferably, the at least one biomarker is selected from the group of biomarkers listed in Table 2b if the subject to be tested is suspected to be in an acute stage of MS. A decrease in such a biomarker is indicative for multiple sclerosis.

A metabolite as used herein refers to at least one molecule of a specific metabolite up to a plu- rality of molecules of the said specific metabolite. It is to be understood further that a group of metabolites means a plurality of chemically different molecules wherein for each metabolite at least one molecule up to a plurality of molecules may be present. A metabolite in accordance with the present invention encompasses all classes of organic or inorganic chemical compounds including those being comprised by biological material such as organisms. Preferably, the metabolite in accordance with the present invention is a small molecule compound. More preferably, in case a plurality of metabolites is envisaged, said plurality of metabolites representing a metabolome, i.e. the collection of metabolites being comprised by an organism, an organ, a tissue, a body fluid or a cell at a specific time and under specific conditions. The metabolites are small molecule compounds, such as substrates for enzymes of metabolic pathways, intermediates of such pathways or the products obtained by a metabolic pathway. Metabolic pathways are well known in the art and may vary between species. Preferably, said pathways include at least citric acid cycle, respiratory chain, glycolysis, gluconeogenesis, hex- ose monophosphate pathway, oxidative pentose phosphate pathway, production and β- oxidation of fatty acids, urea cycle, amino acid biosynthesis pathways, protein degradation pathways such as proteasomal degradation, amino acid degrading pathways, biosynthesis or degradation of: lipids, polyketides (including e.g. flavonoids and isoflavonoids), isoprenoids (including eg. terpenes, sterols, steroids, carotenoids, xanthophylls), carbohydrates, phenylpro- panoids and derivatives, alcaloids, benzenoids, indoles, indole-sulfur compounds, porphyrines, anthocyans, hormones, vitamins, cofactors such as prosthetic groups or electron carriers, lignin, glucosinolates, purines, pyrimidines, nucleosides, nucleotides and related molecules such as tRNAs, microRNAs (miRNA) or mRNAs. Accordingly, small molecule compound metabolites are preferably composed of the following classes of compounds: alcohols, alkanes, alkenes, alkines, aromatic compounds, ketones, aldehydes, carboxylic acids, esters, amines, imines, amides, cyanides, amino acids, peptides, thiols, thioesters, phosphate esters, sulfate esters, thioethers, sulfoxides, ethers, or combinations or derivatives of the aforementioned compounds. The small molecules among the metabolites may be primary metabolites which are required for normal cellular function, organ function or animal growth, development or health. Moreover, small molecule metabolites further comprise secondary metabolites having essential ecological function, e.g. metabolites which allow an organism to adapt to its environment. Furthermore, metabolites are not limited to said primary and secondary metabolites and further encompass artificial small molecule compounds. Said artificial small molecule compounds are derived from exogenously provided small molecules which are administered or taken up by an organism but are not primary or secondary metabolites as defined above. For instance, artificial small molecule compounds may be metabolic products obtained from drugs by metabolic pathways of the animal. Moreover, metabolites further include peptides, oligopeptides, polypeptides, oligonucle- otides and polynucleotides, such as RNA or DNA. More preferably, a metabolite has a molecular weight of 50 Da (Dalton) to 30,000 Da, most preferably less than 30,000 Da, less than 20,000 Da, less than 15,000 Da, less than 10,000 Da, less than 8,000 Da, less than 7,000 Da, less than 6,000 Da, less than 5,000 Da, less than 4,000 Da, less than 3,000 Da, less than 2,000 Da, less than 1 ,000 Da, less than 500 Da, less than 300 Da, less than 200 Da, less than 100 Da. Preferably, a metabolite has, however, a molecular weight of at least 50 Da. Most preferably, a metabolite in accordance with the present invention has a molecular weight of 50 Da up to 1 ,500 Da.

The term "sample" as used herein refers to samples from body fluids, preferably, blood, plasma, serum, saliva, urine or cerebrospinal fluid, or samples derived, e.g., by biopsy, from cells, tissues or organs, in particular from the CNS including brain and spine. More preferably, the sample is a blood, plasma or serum sample, most preferably, a serum or plasma sample. Biological samples can be derived from a subject as specified elsewhere herein. Techniques for obtaining the aforementioned different types of biological samples are well known in the art. For example, blood samples may be obtained by blood taking while tissue or organ samples are to be obtained, e.g., by biopsy.

The aforementioned samples are, preferably, pre-treated before they are used for the method of the present invention. As described in more detail below, said pre-treatment may include treat- ments required to release or separate the compounds or to remove excessive material or waste. Suitable techniques comprise centrifugation, extraction, fractioning, ultrafiltration, protein precipitation followed by filtration and purification and/or enrichment of compounds. Moreover, other pre-treatments are carried out in order to provide the compounds in a form or concentration suitable for compound analysis. For example, if gas-chromatography coupled mass spec- trometry is used in the method of the present invention, it will be required to derivatize the compounds prior to the said gas chromatography. Suitable and necessary pre-treatments depend on the means used for carrying out the method of the invention and are well known to the person skilled in the art. Pre-treated samples as described before are also comprised by the term "sample" as used in accordance with the present invention.

The term "subject" as used herein relates to animals and, preferably, to mammals. More preferably, the subject is a primate and, most preferably, a human. The subject, preferably, is suspected to suffer from MS, i.e. it may already show some or all of the symptoms associated with the disease.

The term "determining the amount" as used herein refers to determining at least one characteristic feature of a biomarker to be determined by the method of the present invention in the sam- pie. Characteristic features in accordance with the present invention are features which characterize the physical and/or chemical properties including biochemical properties of a biomarker. Such properties include, e.g., molecular weight, viscosity, density, electrical charge, spin, optical activity, colour, fluorescence, chemoluminescence, elementary composition, chemical structure, capability to react with other compounds, capability to elicit a response in a biological read out system (e.g., induction of a reporter gene) and the like. Values for said properties may serve as characteristic features and can be determined by techniques well known in the art. Moreover, the characteristic feature may be any feature which is derived from the values of the physical and/or chemical properties of a biomarker by standard operations, e.g., mathematical calcula- tions such as multiplication, division or logarithmic calculus. Most preferably, the at least one characteristic feature allows the determination and/or chemical identification of the said at least one biomarker and its amount. Accordingly, the characteristic value, preferably, also comprises information relating to the abundance of the biomarker from which the characteristic value is derived. For example, a characteristic value of a biomarker may be a peak in a mass spectrum. Such a peak contains characteristic information of the biomarker, i.e. the m/z information

(mass/charge ratio or quotient), as well as an intensity value being related to the abundance of the said biomarker (i.e. its amount) in the sample.

As discussed before, each biomarker comprised by a sample may be, preferably, determined in accordance with the present invention quantitatively or semi-quantitatively. For quantitative determination, either the absolute or precise amount of the biomarker will be determined or the relative amount of the biomarker will be determined based on the value determined for the characteristic feature(s) referred to herein above. The relative amount may be determined in a case were the precise amount of a biomarker can or shall not be determined. In said case, it can be determined whether the amount in which the biomarker is present is enlarged or diminished with respect to a second sample comprising said biomarker in a second amount. In a preferred embodiment said second sample comprising said biomarker shall be a calculated reference as specified elsewhere herein. Quantitatively analysing a biomarker, thus, also includes what is sometimes referred to as semi-quantitative analysis of a biomarker.

Moreover, determining as used in the method of the present invention, preferably, includes using a compound separation step prior to the analysis step referred to before. Preferably, said compound separation step yields a time resolved separation of the metabolites comprised by the sample. Suitable techniques for separation to be used preferably in accordance with the present invention, therefore, include all chromatographic separation techniques such as liquid chromatography (LC), high performance liquid chromatography (HPLC), gas chromatography (GC), thin layer chromatography, size exclusion or affinity chromatography. These techniques are well known in the art and can be applied by the person skilled in the art without further ado. Most preferably, LC and/or GC are chromatographic techniques to be envisaged by the method of the present invention. Suitable devices for such determination of biomarkers are well known in the art. Preferably, mass spectrometry is used in particular gas chromatography mass spectrometry (GC-MS), liquid chromatography mass spectrometry (LC-MS), direct infusion mass spectrometry or Fourier transform ion-cyclotrone-resonance mass spectrometry (FT-ICR-MS), capillary electrophoresis mass spectrometry (CE-MS), high-performance liquid chromatography coupled mass spectrometry (HPLC-MS), quadrupole mass spectrometry, any sequentially coupled mass spectrometry, such as MS-MS or MS-MS-MS, inductively coupled plasma mass spectrometry (ICP-MS), pyrolysis mass spectrometry (Py-MS), ion mobility mass spectrometry or time of flight mass spectrometry (TOF). Most preferably, LC-MS and/or GC-MS are used as described in detail below. Said techniques are disclosed in, e.g., Nissen 1995, Journal of Chromatography A, 703: 37-57, US 4,540,884 or US 5,397,894, the disclosure content of which is hereby incorporated by reference. As an alternative or in addition to mass spectrometry tech- niques, the following techniques may be used for compound determination: nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), Fourier transform infrared analysis (FT- IR), ultraviolet (UV) spectroscopy, refraction index (Rl), fluorescent detection, radiochemical detection, electrochemical detection, light scattering (LS), dispersive Raman spectroscopy or flame ionisation detection (FID). These techniques are well known to the person skilled in the art and can be applied without further ado. The method of the present invention shall be, preferably, assisted by automation. For example, sample processing or pre-treatment can be automated by robotics. Data processing and comparison is, preferably, assisted by suitable computer programs and databases. Automation as described herein before allows using the method of the present invention in high-throughput approaches.

Moreover, the at least one biomarker can also be determined by a specific chemical or biological assay. Said assay shall comprise means which allow to specifically detect the at least one biomarker in the sample. Preferably, said means are capable of specifically recognizing the chemical structure of the biomarker or are capable of specifically identifying the biomarker based on its capability to react with other compounds or its capability to elicit a response in a biological read out system (e.g., induction of a reporter gene). Means which are capable of specifically recognizing the chemical structure of a biomarker are, preferably, antibodies or other proteins which specifically interact with chemical structures, such as receptors or enzymes. Specific antibodies, for instance, may be obtained using the biomarker as antigen by methods well known in the art. Antibodies as referred to herein include both polyclonal and monoclonal antibodies, as well as fragments thereof, such as Fv, Fab and F(ab)2 fragments that are capable of binding the antigen or hapten. The present invention also includes humanized hybrid antibodies wherein amino acid sequences of a non-human donor antibody exhibiting a desired antigen- specificity are combined with sequences of a human acceptor antibody. Moreover, encom- passed are single chain antibodies. The donor sequences will usually include at least the antigen-binding amino acid residues of the donor but may comprise other structurally and/or functionally relevant amino acid residues of the donor antibody as well. Such hybrids can be prepared by several methods well known in the art. Suitable proteins which are capable of specifically recognizing the biomarker are, preferably, enzymes which are involved in the metabolic conversion of the said biomarker. Said enzymes may either use the biomarker as a substrate or may convert a substrate into the biomarker. Moreover, said antibodies may be used as a basis to generate oligopeptides which specifically recognize the biomarker. These oligopeptides shall, for example, comprise the enzyme^'s binding domains or pockets for the said biomarker. Suitable antibody and/or enzyme based assays may be RIA (radioimmunoassay), ELISA (enzyme- linked immunosorbent assay), sandwich enzyme immune tests, electrochemiluminescence sandwich immunoassays (ECLIA), dissociation-enhanced lanthanide fluoro immuno assay (DELFIA) or solid phase immune tests. Moreover, the biomarker may also be determined based on its capability to react with other compounds, i.e. by a specific chemical reaction. Further, the biomarker may be determined in a sample due to its capability to elicit a response in a biological read out system. The biological response shall be detected as read out indicating the presence and/or the amount of the biomarker comprised by the sample. The biological response may be, e.g., the induction of gene expression or a phenotypic response of a cell or an organism. In a preferred embodiment the determination of the least one biomarker is a quantitative process, e.g., allowing also the determination of the amount of the at least one biomarker in the sample

As described above, said determining of the at least one biomarker can, preferably, comprise mass spectrometry (MS). Mass spectrometry as used herein encompasses all techniques which allow for the determination of the molecular weight (i.e. the mass) or a mass variable corresponding to a compound, i.e. a biomarker, to be determined in accordance with the present invention. Preferably, mass spectrometry as used herein relates to GC-MS, LC-MS, direct infusion mass spectrometry, FT-ICR-MS, CE-MS, HPLC-MS, quadrupole mass spectrometry, any sequentially coupled mass spectrometry such as MS-MS or MS-MS-MS, ICP-MS, Py-MS, TOF or any combined approaches using the aforementioned techniques. How to apply these techniques is well known to the person skilled in the art. Moreover, suitable devices are commercially available. More preferably, mass spectrometry as used herein relates to LC-MS and/or GC- MS, i.e. to mass spectrometry being operatively linked to a prior chromatographic separation step. More preferably, mass spectrometry as used herein encompasses quadrupole MS. Most preferably, said quadrupole MS is carried out as follows: a) selection of a mass/charge quotient (m/z) of an ion created by ionisation in a first analytical quadrupole of the mass spectrometer, b) fragmentation of the ion selected in step a) by applying an acceleration voltage in an additional subsequent quadrupole which is filled with a collision gas and acts as a collision chamber, c) selection of a mass/charge quotient of an ion created by the fragmentation process in step b) in an additional subsequent quadrupole, whereby steps a) to c) of the method are carried out at least once and analysis of the mass/charge quotient of all the ions present in the mixture of substances as a result of the ionisation process, whereby the quadrupole is filled with collision gas but no acceleration voltage is applied during the analysis. Details on said most preferred mass spectrometry to be used in accordance with the present invention can be found in WO 03/073464.

More preferably, said mass spectrometry is liquid chromatography (LC) MS and/or gas chromatography (GC) MS. Liquid chromatography as used herein refers to all techniques which allow for separation of compounds (i.e. metabolites) in liquid or supercritical phase. Liquid chromatography is characterized in that compounds in a mobile phase are passed through the stationary phase. When compounds pass through the stationary phase at different rates they become separated in time since each individual compound has its specific retention time (i.e. the time which is required by the compound to pass through the system). Liquid chromatography as used herein also includes HPLC. Devices for liquid chromatography are commercially available, e.g. from Agilent Technologies, USA. Gas chromatography as applied in accordance with the present invention, in principle, operates comparable to liquid chromatography. However, rather than having the compounds (i.e. metabolites) in a liquid mobile phase which is passed through the stationary phase, the compounds will be present in a gaseous volume. The compounds pass the column which may contain solid support materials as stationary phase or the walls of which may serve as or are coated with the stationary phase. Again, each compound has a spe- cific time which is required for passing through the column. Moreover, in the case of gas chromatography it is preferably envisaged that the compounds are derivatised prior to gas chromatography. Suitable techniques for derivatisation are well known in the art. Preferably, derivatisa- tion in accordance with the present invention relates to methoxymation and trimethylsilylation of, preferably, polar compounds and transmethylation, methoxymation and trimethylsilylation of, preferably, non-polar (i.e. lipophilic) compounds.

The term "reference" refers to values of characteristic features of each of the biomarker which can be correlated to a medical condition, i.e. the presence or absence of the disease, diseases status or an effect referred to herein. If the biomarker is selected from the biomarkers shown in Table 1 a, 2a, or 3a, a reference is, preferably, a threshold amount for a biomarker whereby amounts found in a sample to be investigated which are higher than or essentially identical to the threshold are indicative for the presence of a medical condition while those being lower are indicative for the absence of the medical condition. If the biomarker is selected from the biomarkers shown in Table 1 b or 2b, or 3b, a reference is, preferably a threshold amount for a biomarker whereby amounts found in a sample to be investigated which are lower or identical than the threshold are indicative for the presence of a medical condition while those being higher are indicative for the absence of the medical condition.

In accordance with the aforementioned method of the present invention, a reference is, prefera- bly, a reference amount obtained from a sample from a subject known to suffer from MS. In particular, the reference amount is obtained from a sample from a subject known to be in an early stage of MS. Preferably, an amount for the at least one biomarker found in the test sample being essentially identical is indicative for the presence of the disease. Moreover, the reference, also preferably, could be from a subject known not to suffer from MS, preferably, an apparently healthy subject. More preferably, the reference could be derived from a subject known not to suffer from MS, but showing symptoms of MS (or from a group of said subjects). Accordingly, said subject shall show MS-like symptoms. The MS or MS-like symptoms of said subject shall be caused by neurological diseases other than MS. Preferred symp- toms are disclosed elsewhere herein. Moreover, said symptoms shall be preferentially symptoms similar or identical to MS symptoms and include changes in sensation (hypoesthesia and paraesthesia), muscle weakness, muscle spasms, difficulty in moving, difficulties with coordina- tion and balance (ataxia), problems in speech (dysarthria) or swallowing (dysphagia), visual problems (nystagmus, optic neuritis, or diplopia), fatigue, headache. If the reference amount is derived from the aforementioned subject, or group thereof, an amount for the at least one bi- omarker found in the test sample being altered with respect to the reference is indicative for the presence of the disease. Preferably, said amount is being altered by at least 10%, by at least 20%, by at least 30%, by at least 50%. Preferably, an amount of the biomarker in the test sample being increased as compared to the reference is indicative for the presence of MS, if the biomarker is selected from the group of biomarkers shown in Table 1 a or 2a (and if the biomarker is a ceramide, or if the total amount of ceramides is determined). Preferably, an amount of the biomarker in the test sample being decreased as compared to the reference is indicative for the presence of MS, if the biomarker is selected from the group of biomarkers shown in Table 1 b or 2b.

The same applies mutatis mutandis for a calculated reference, most preferably the average or median, for the relative or absolute amount of the at least one biomarker of a population of individuals comprising the subject to be investigated. The absolute or relative amounts of the at least one biomarker of said individuals of the population can be determined as specified elsewhere herein. How to calculate a suitable reference value, preferably, the average or median, is well known in the art. The population of subjects referred to before shall comprise a plurality of subjects, preferably, at least 5, 10, 50, 100, 1 ,000 or 10,000 subjects. It is to be understood that the subject to be diagnosed by the method of the present invention and the subjects of the said plurality of subjects are of the same species.

The amounts of the test sample and the reference amounts are essentially identical, if the val- ues for the characteristic features and, in the case of quantitative determination, the intensity values are essentially identical. Essentially identical means that the difference between two amounts is, preferably, not significant and shall be characterized in that the values for the intensity are within at least the interval between 1 ^st and 99^th percentile, 5^th and 95^th percentile, 10^th and 90^th percentile, 20^th and 80^th percentile, 30^th and 70^th percentile, 40^th and 60^th percentile of the reference value, preferably, the 50^th, 60^th, 70^th, 80^th, 90^th or 95^th percentile of the reference value. Statistical test for determining whether two amounts are essentially identical are well known in the art and are also described elsewhere herein.

An observed difference for two amounts, on the other hand, shall be statistically significant. A difference in the relative or absolute amount is, preferably, significant outside of the interval between 45^th and 55^th percentile, 40^th and 60^th percentile, 30^th and 70^th percentile, 20^th and 80^th percentile, 10^th and 90^th percentile, 5^th and 95^th percentile, 1 ^st and 99^th percentile of the reference value. Preferred changes and fold-regulations are described in the accompanying Tables as well as in the Examples. Preferably, the reference, i.e. values for at least one characteristic features of the at least one biomarker, will be stored in a suitable data storage medium such as a database and are, thus, also available for future assessments. The term "comparing" refers to determining whether the determined amount of a biomarker is essentially identical to a reference or differs therefrom. Preferably, a biomarker is deemed to differ from a reference if the observed difference is statistically significant which can be determined by statistical techniques referred to elsewhere in this description. If the difference is not statistically significant, the biomarker amount and the reference amount are essentially identical. Based on the comparison referred to above, a subject can be assessed to suffer from the disease, or not.

For the specific biomarkers referred to in this specification, preferred values for the changes in the relative amounts (i.e. "fold"- regulation) or the kind of regulation (i.e. "up"- or "down"- regulation resulting in a higher or lower relative and/or absolute amount) are indicated in the following Tables and in the Examples below. If it is indicated in said Table that a given biomarker is "up- regulated" in a subject, the relative and/or absolute amount will be increased, if it is "down-regulated", the relative and/or absolute amount of the biomarker will be decreased. In the case of "up"-regulation the ratio of median shall exceed 1 .0 while it will be below 1.0 in the case of a "down"-regulation. Moreover, the "fold"-change indicates the degree of increase or decrease, e.g., a 2-fold increase means that the median of one group, e.g., the MS group, is twice the median of the biomarker of the other group, e.g., the reference group. Accordingly, the direction of regulation can be derived from the Tables as well. The comparison is, preferably, assisted by automation. For example, a suitable computer program comprising algorithms for the comparison of two different data sets (e.g., data sets comprising the values of the characteristic feature(s)) may be used. Such computer programs and algorithm are well known in the art. Notwithstanding the above, a comparison can also be carried out manually.

Advantageously, it has been found in the study underlying the present invention that the amounts of the specific biomarkers referred to above are indicators for MS. Accordingly, the at least one biomarker as specified above in a sample can, in principle, be used for assessing whether a subject suffers from MS. This is particularly helpful for an efficient diagnosis of the disease as well as for improving of the pre-clinical and clinical management of MS as well as an efficient monitoring of patients. Moreover, the findings underlying the present invention will also facilitate the development of efficient drug-based therapies against MS as set forth in detail below. The definitions and explanations of the terms made above apply mutatis mutandis for the following embodiments of the present invention except specified otherwise herein below. Moreover, the present invention relates to a method for differentiating between i) a subject showing symptoms of multiple sclerosis and suffering from multiple sclerosis and ii) a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclerosis, said method comprising the steps of

a5 determining in a sample of a subject showing symptoms of multiple sclerosis the amount of at least one ceramide, or the total amount of ceramides, and

b) comparing the amount of the said at least one ceramide, or the total amount of ceramides, to at least one reference amount, whereby it is differentiated between i) and ii).

10 In particular, the present invention relates to a method for differentiating between i) a subject showing symptoms of multiple sclerosis and suffering from multiple sclerosis and ii) a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclerosis, said method comprising the steps of

a) determining in a sample of a subject showing symptoms of multiple sclerosis the amount of at 15 least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2, and b) comparing the amount of the said at least one biomarker to at least one reference amount, whereby it is differentiated between i) and ii).

The term "differentiating" as used herein, preferably, means to distinguish between a subject 0 showing symptoms of multiple sclerosis and suffering from multiple sclerosis and a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclerosis. Thus, the aforementioned method allows for assessing whether a subject who shows symptoms of multiple sclerosis suffers from MS or not. As will be understood by those skilled in the art, such an assessment is usually not intended to be correct for 100% of the subjects to be differentially 5 diagnosed. The term, however, requires that a statistically significant portion of subjects can be correctly diagnosed. Whether a diagnosis is correct can be confirmed by methods well known in the art. Moreover, whether a portion is statistically significant can be determined without further ado by the person skilled in the art using various well known statistic evaluation tools, e.g., determination of confidence intervals, p- value determination, Student's t-test, Mann- Whitney test, 0 ANOVA etc.. Details are found in Dowdy and Wearden, Statistics for Research, John Wiley & Sons, New York 1983. Preferred confidence intervals are at least 90%, at least 95%, at least 97%, at least 98% or at least 99 %. The p-values are, preferably, 0.2, 0.1 , 0.05, 0.01 , 0.005, or 0.0001 . 5 In a preferred embodiment of the aforementioned method, it is differentiated between i) a subject showing symptoms of multiple sclerosis and suffering from an early stage of multiple sclerosis and ii) a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclerosis. 0 The term "subject" has been defined elsewhere herein. In accordance with the aforementioned method the subject, preferably, shall show symptoms of MS, in particular neurological symptoms of MS. A subject who shows symptoms of MS, but does not suffer from MS, preferably, suffers from a neurological disease other than MS. Preferred diseases are disclosed in the Examples section.

Symptoms of MS have been described elsewhere herein. Preferred symptoms include changes in sensation (hypoesthesia and paraesthesia), muscle weakness, muscle spasms, difficulty in moving, difficulties with coordination and balance (ataxia), problems in speech (dysarthria) or swallowing (dysphagia), visual problems (nystagmus, optic neuritis, or diplopia), fatigue, headache. Preferably, a subject showing symptoms of MS shall suffer from headache, in particular migraine, hypaesthesia, paresthesia, or meningitis or from combinations thereof.

In a preferred embodiment of the method of the invention, said at least one biomarker is selected from the group of biomarkers listed in Table 1 a and/or Table 2a. An increase in such a biomarker as compared to the reference, preferably, indicates that the subject showing symptoms of MS suffers from MS, whereas an unchanged amount or a decrease of such as biomarker as compared to the reference, preferably, indicates that the subject showing symptoms of MS does not suffer from MS. The same applies if the biomarker is a ceramide. The same also applies if the total amount of ceramides is determined in the sample. Preferred references have been disclosed elsewhere herein. Preferably, the aforementioned increase or decrease is an increase/decrease of at least 10%, of at least 20%, of at least 30%, or of at least 50% (in an increasing order of preference).

In a further preferred embodiment of the method of the invention, said at least one biomarker is selected from the group of biomarkers listed in Table 1 b and/or Table 2b. A decrease in such a biomarker as compared to the reference, preferably, indicates that the subject showing symptoms of MS suffers from MS, whereas an and unchanged amount or increase of in such a biomarker as compared to the reference, preferably, indicates that the subject showing symptoms of MS does not suffer from MS. Preferred references have been disclosed above. Preferably, the at least one biomarker is selected from the group of biomarkers listed in Table 2, 2a and 2b, respectively, if the subject to be tested is suspected to be in an acute stage of MS.

The present invention also relates to a method for identifying whether a subject is in need for a therapy of multiple sclerosis comprising the steps of the aforementioned method of diagnosing MS and the further step of identifying a subject in need if multiple sclerosis is diagnosed.

The phrase "in need for a therapy of multiple sclerosis" as used herein means that the disease in the subject is in a status where therapeutic intervention is necessary or beneficial in order to ameliorate or treat MS or the symptoms associated therewith. Accordingly, the findings of the studies underlying the present invention do not only allow diagnosing MS in a subject but also allow for identifying subjects which should be treated by an MS therapy. Once the subject has been identified, the method may further include a step of making recommendations for a therapy of MS.

A therapy of multiple sclerosis as used in accordance with the present invention, preferably, 5 relates to a therapy which comprises or consists of the administration of at least one drug selected from the group consisting of: Interferon Betal a, Interferon Beta 1 b, Azathioprin, Cyclophosphamide, Glatiramer Acetate, Immunglobuline Methotrexat, Mitoxantrone, Leustatin, IVIg, Natalizumab, Teriflunomid, Statins, Daclizumab, Alemtuzumab, Ritximab, Sphingosin 1 phosphate antagonist Fingolimod (FTY720), Cladribine, Fumarate, Laquinimod, drugs affecting B- 10 cells, and antisense agents and agents against CD49d.

Also, the present invention contemplates a method for determining whether a multiple sclerosis therapy is successful comprising the steps of:

a) determining at least one ceramide, or the total amount of ceramides, in a first and a second

15 sample of the subject wherein said first sample has been taken prior to or at the onset of the multiple sclerosis therapy and said second sample has been taken after the onset of the said therapy; and

b) comparing the amount of the said at least one ceramide, or the total amount of ceramides, in the first sample to the amount or total amount in the second sample.

0

In the context of the aforementioned method, a decrease in the amount determined in the second sample in comparison to the first sample is, preferably, indicative for multiple sclerosis therapy being successful. An increase in the amount determined in the second sample in comparison to the first sample, preferably, indicates that multiple sclerosis therapy is not successful. 5 Said increase is preferably an increase of at least 10%, of at least 20%, of at least 30%, or of at least 50% (in an increasing order of preference).

The term "ceramide" has been described elsewhere herein. Preferably, the ceramide is selected from the ceramides listed in Table 1 and/or Table 2.

0

(d16:1 ,C23:0), ceramide (d16:1 ,C24:0), ceramide (d17:1 ,C22:0), ceramide (d17:1 ,C23:0), ceramide (d17:1 ,C24:0), ceramide (d17:1 ,C24:1 ), ceramide (d18:1 ,C21 :0), ceramide

5 (d18:1 ,C22:0), ceramide (d18:1 ,C22:1 ), ceramide (d18:1 ,C23:0), ceramide (d18:1 ,C23:1 ),

ceramide (d18:1 , C24:0), ceramide (d18:1 , C24:1 ), ceramide (d18:2,C22:0), ceramide

(d18:2,C23:0), ceramide (d18:2,C24:0), and ceramide (d18:2,C24:1 ).

In a further preferred embodiment, the ceramide is selected from the group of ceramides con- 0 sisting of ceramide (d16:1 , C22:0), ceramide (d16:1 , C23:0), ceramide (d16:1 , C24:0), ceramide (d17:1 , C22:0), ceramide (d17:1 , C23:0), ceramide (d17:1 , C24:0), ceramide (d17:1 , C24:1 ), ceramide (d18:1 , C21 :0), ceramide (d18:1 , C22:0), ceramide (d18:1 , C22:1 ), ceramide (d18:1 , C23:0), ceramide (d18:1 , C23:1 ), ceramide (d18:2,C22:0), ceramide (d18:2, C23:0), ceramide (d18:2, C24:0), and ceramide (d18:2,C24:1 ). In one embodiment, the ceramide is not ceramide (d18:1 , C24:0) or not ceramide (d18:1 , C24:1 ).

5 Moreover, the present invention contemplates a method for determining whether a multiple sclerosis therapy is successful comprising the steps of:

a) determining at least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2 in a first and a second sample of the subject wherein said first sample has been taken prior to or at the onset of the multiple sclerosis therapy and said second sample has been taken after

10 the onset of the said therapy; and

b) comparing the amount of the said at least one biomarker in the first sample to the amount in the second sample, whereby a change in the amount determined in the second sample in comparison to the first sample is indicative for multiple sclerosis therapy being successful.

15 It is to be understood that an MS therapy will be successful if MS or at least some symptoms thereof can be treated or ameliorated compared to an untreated subject. Moreover, a therapy is also successful as meant herein if the disease progression can be prevented or at least slowed down compared to an untreated subject.

20 In a preferred embodiment of the aforementioned methods, the at least one biomarker is selected from the biomarkers listed in Table 1 a and/or 2a. In such a case, the change in step b) is a decrease. Accordingly, a decrease, preferably, indicates that the multiple sclerosis therapy is successful. Said decrease is preferably a decrease of at least 10%, of at least 20%, of at least 30%, of at least 50% (in an increasing order of preference). The same applies if the biomarker

25 is a ceramide. The same also applies if the total amount of ceramides is determined in the sample.

In yet another preferred embodiment of the aforementioned methods, the at least one biomarker is selected from the biomarkers listed in Table 1 b and/or 2b. In such a case, the change in step 30 b) is an increase. Accordingly, an increase, preferably, indicates that the multiple sclerosis therapy is successful.

The present invention, further, relates to a method for diagnosing an active status of multiple sclerosis in a subject comprising the steps of:

¾5 determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 3; and

b) comparing the amount of the said at least one biomarker to a reference amount, whereby an active status of multiple sclerosis is to be diagnosed.

40 In a preferred embodiment of the aforementioned method, said at least one biomarker is selected from the group of biomarkers listed in Table 3a and wherein an increase in the said at least one biomarker is indicative for an active status of MS. Said increase is preferably an increase of at least 10%, of at least 20%, of at least 30%, of at least 50% (in an increasing order of preference).

In another preferred embodiment of the aforementioned method, said at least one biomarker is 5 selected from the group of biomarkers listed in Table 3b and wherein a decrease in the said at least one biomarker is indicative for an active status of MS. Said decrease is preferably an decrease of at least 10%, of at least 20%, of at least 30%, of at least 50% (in an increasing order of preference).

10 The method for diagnosing the active status of MS in a subject can be, preferably, also applied in order to monitor disease progression. In particular, if the presence of an active status is determined in all samples taken over a certain time window without a sample indicating a remission status, the method will also provide an indication for disease progression, e.g., from the relapsing-remitting subtype to the secondary progressing subtype. Thus, the frequency and

15 numbers of active status which can be diagnosed by the method of the present invention can be used to further diagnose aggressiveness and progression of MS.

The present invention also relates to a method for predicting whether a subject is at risk of developing multiple sclerosis comprising the steps of:

b) comparing the amount of the said at least one ceramide, or the total amount of ceramides, to a reference amount, whereby it is predicted whether a subject is at risk of developing multiple sclerosis.

5

Preferred ceramides have been described elsewhere herein. Preferably, the ceramide is selected from the ceramides listed in Table 1 and/or 2.

Accordingly, the ceramide in the context of the methods of the present invention is preferably 0 selected from the group of ceramides consisting of ceramide (d16:1 ,C22:0), ceramide

(d18:1 ,C22:0), ceramide (d18:1 ,C22:1 ), ceramide (d18:1 ,C23:0), ceramide (d18:1 ,C23:1 ), ceramide (d18:1 , C24:0), ceramide (d18:1 , C24:1 ), ceramide (d18:2,C22:0), ceramide (d18:2, 5 C23:0), ceramide (d18:2,C24:0), and ceramide (d18:2,C24:1 ).

In a further preferred embodiment, the ceramide selected from the group of ceramides consisting of ceramide (d16:1 , C22:0), ceramide (d16:1 , C23:0), ceramide (d16:1 , C24:0), ceramide (d17:1 , C22:0), ceramide (d17:1 , C23:0), ceramide (d17:1 , C24:0), ceramide (d17:1 , C24:1 ), 0 ceramide (d18:1 , C21 :0), ceramide (d18:1 , C22:0), ceramide (d18:1 , C22:1 ), ceramide (d18:1 , C23:0), ceramide (d18:1 , C23:1 ), ceramide (d18:2,C22:0), ceramide (d18:2, C23:0), ceramide (d18:2, C24:0), and ceramide (d18:2,C24:1 ). In one embodiment, the ceramide is not ceramide (d18:1 , C24:0) or not ceramide (d18:1 , C24:1 ).

Moreover, the present invention relates to a method for predicting whether a subject is at risk of 5 developing multiple sclerosis comprising the steps of:

a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 1 and/or 2 and

b) comparing the amount of the said at least one biomarker to a reference amount, whereby it is predicted whether a subject is at risk of developing multiple sclerosis.

10

The term "predicting" as used herein, in general, refers to determining the probability according to which a subject will develop a medical condition or its accompanying symptoms within a certain time window after the sample has been taken (i.e. the predictive window). It will be understood that such a prediction will not necessarily be correct for all (100%) of the investigated sub- 15 jects. However, it is envisaged that the prediction will be correct for a statistically significant portion of subjects of a population of subjects (e.g., the subjects of a cohort study). Whether a portion is statistically significant can be determined by statistical techniques set forth elsewhere herein.

20 In a preferred embodiment of the aforementioned method for predicting whether a subject is at risk of developing multiple sclerosis, the method is repeated with one or more further samples of the subject which have been taken after the above mentioned (first) sample was taken. Accordingly, by repeating the prediction several times after the initial prediction was made, the prediction power of the method can be further increased.

25

Moreover, the present invention relates to a method for predicting whether a subject is at risk of developing an active status of multiple sclerosis. Said method shall comprise the steps of:

a) determining in a sample of the subject the amount of at least one ceramide, or the total amount of ceramides, and

Βφ comparing the amount of the said at least one ceramide, or the total amount of ceramides, to a reference amount, whereby it is predicted whether a subject is at risk of developing an active status of multiple sclerosis.

The term "ceramide" has been described elsewhere herein. In the context of the aformentioned 35 method, it is particularly preferred that the ceramide is selected from the ceramides listed in Table 3. Preferably an increased amount of the at least one ceramide (or an increased total amount of ceramides) in comparision to the reference amount is indicative for a subject being at risk of developing an active status of multiple sclerosis.

40 A method for predicting whether a subject is at risk of developing an active status of multiple sclerosis is also envisaged by the present invention. Said method shall comprise the steps of: a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 3 and

b) comparing the amount of the said at least one biomarker to a reference amount, whereby it is predicted whether a subject is at risk of developing an active status of multiple sclerosis.

5

Furthermore, the present invention relates to a method for identifying whether a subject is in need for a therapy against the active status of multiple sclerosis comprising the steps of the aforementioned two methods for predicting whether a subject is at risk of developing an active status of multiple sclerosis and the further steps of identifying a subject in need if the subject is 10 predicted to be at risk of developing an active status of multiple sclerosis.

The invention also relates to a method for establishing an aid for diagnosing whether a subject suffering from MS, or not, or the active status of MS, or not, or is at risk of developing MS or the active status thereof is contemplated, said method comprising:

a) l 5 determining the amount of at least one biomarker as referred to above in a sample of said

subject, said determining comprises (i) bringing the sample into contact with a detection agent that specifically binds to said at least one biomarker for a time sufficient to allow for the formation of a complex of the said detection agent and the biomarker from the sample, (ii) measuring the amount of the formed complex, wherein the said amount of the formed complex is pro- 20 portional to the amount of biomarker present in the sample, and (iii) transforming the amount of the formed complex into an amount of biomarker reflecting the amount of the biomarker present in the sample;

b) comparing said amount to a reference; and

c) establishing an aid for diagnosing whether a subject suffering from MS, or not, or the active 25 status of MS, or not, or is at risk of developing MS or the active status thereof based on the result of the comparison made in step b).

A suitable detection agent may be, preferably, an antibody which is specifically binds to the at least one biomarker in a sample of a subject to be investigated by the method of the invention.

30 Another detection agent that can be applied, preferably, may be an aptamere which specifically binds to at least one biomarker in the sample. In yet a preferred embodiment, the sample is removed from the complex formed between the detection agent and the at least one biomarker prior to the measurement of the amount of formed complex. Accordingly, in a preferred embodiment, the detection agent may be immobilized on a solid support. In yet a preferred embodi-

35 ment, the sample can be removed from the formed complex on the solid support by applying a washing solution. The formed complex shall be proportional to the amount of the at least one biomarker present in the sample. It will be understood that the specificity and/or sensitivity of the detection agent to be applied defines the degree of proportion of at least one biomarker comprised in the sample which is capable of being specifically bound. Further details on how the

40 determination can be carried out are also found elsewhere herein. The amount of formed complex shall be transformed into an amount of at least one biomarker reflecting the amount indeed present in the sample. Such an amount, preferably, may be essentially the amount present in the sample or may be, preferably, an amount which is a certain proportion thereof due to the relationship between the formed complex and the amount present in the original sample.

In yet a preferred embodiment of the aforementioned method, step a) may be carried out by an analyzing unit, in an aspect, an analyzing unit as defined elsewhere herein.

In a preferred embodiment of the method of the invention, the amount determined in step a) is compared to a reference. Preferably, the reference is a reference as defined elsewhere herein. In yet another preferred embodiment, the reference takes into account the proportional relation- ship between the measured amount of complex and the amount present in the original sample. Thus, the references applied in a preferred embodiment of the method of the invention are artificial references which are adopted to reflect the limitations of the detection agent that has been used. In another preferred embodiment, said relationship can be also taken into account when carrying out the comparison, e.g., by including a normalization and/or correction calculation step for the determined amount prior to actually comparing the value of the determined amount and the reference. Again, the normalization and/or correction calculation step for the determined amount adopts the comparison step such that the limitations of the detection agent that has been used are reflected properly. Preferably, the comparison is carried out automatically, e.g., assisted by a computer system or the like.

The aid for diagnosing is established based on the comparison carried out in step b) by allocating the subject either into a group of subjects suffering MS with certain likelihood or a group of subjects not suffering therefrom. As discussed elsewhere herein already, the allocation of the investigated subject must not be correct in 100% of the investigated cases. Moreover, the groups of subjects into which the investigated subject is allocated are artificial groups in that they are established based on statistical considerations, i.e. a certain preselected degree of likelihood based on which the method of the invention shall operate. Thus, the method may establish an aid of diagnosis which may, in an aspect, require further strengthening of the diagnosis by other techniques. Preferably, the aid for diagnosing is established automatically, e.g., assisted by a computer system or the like.

In a preferred embodiment of the method of the invention, the determination of the at least one biomarker is achieved by mass spectroscopy techniques (preferably GCMS and/or LCMS), NMR or others referred to herein above. In such cases, preferably, the sample to be analyzed is pretreated. Said pretreatment, preferably, includes obtaining of the at least one biomarker from sample material, e.g., plasma or serum may be obtained from whole blood or the at least one biomarker may even be specifically extracted from sample material. Moreover, for GCMS, further sample pretreatment such as derivatization of the at least one biomarker is, preferably, required. Furthermore, pretreatment also, preferably, includes diluting sample material and adjust- ing or normalizing the concentration of the components comprised therein. To this end, preferably, normalization standards may be added to the sample in predefined amounts which allow for making a comparison of the amount of the at least one biomarker and the reference and/or between different samples to be analyzed.

In a preferred embodiment of the method of the invention, said method further comprises a step of recommending and/or managing the subject according to the result of the aid of diagnosis established in step c). Such a recommendation may, in an aspect, be an adaptation of life style, nutrition and the like aiming to improve the life circumstances, the application of therapeutic measures as set forth elsewhere herein in detail, and/or a regular disease monitoring. In another preferred embodiment of the aforementioned method, steps b) and/or c) are carried out by an evaluation unit as set forth elsewhere herein.

The method, in another preferred embodiment, also includes a step of managing or treating a subject according to the recommendation or diagnostic result. Preferably, said treating encom- passes administering to the subject a therapeutically effective dose of at least one drug selected from the group consisting of: Interferon Betal a, Interferon Beta 1 b, Azathioprin, Cyclophosphamide, Glatiramer Acetate, Immunglobuline Methotrexat, Mitoxantrone, Leustatin, IVIg, Na- talizumab, Teriflunomid, Statins, Daclizumab, Alemtuzumab, Ritximab, Sphingosin 1 phosphate antagonist Fingolimod (FTY720), Cladribine, Fumarate, Laquinimod, drugs affecting B-cells, and antisense agents and agents against CD49d.

Accordingly, the present invention also contemplates a method of treating MS in a subject suffering thereof comprising (a) diagnosing or predicting MS or the active status of MS in a subject by applying a method as referred to herein above and (b) administering to a subject which is identified to suffer from MS or the active status of MS or which is at risk of developing MS or the active status of MS a therapeutically effective amount of at least one drug selected from the group consisting of: Interferon Betal a, Interferon Beta 1 b, Azathioprin, Cyclophosphamide, Glatiramer Acetate, Immunglobuline Methotrexat, Mitoxantrone, Leustatin, IVIg, Natalizumab, Teriflunomid, Statins, Daclizumab, Alemtuzumab, Ritximab, Sphingosin 1 phosphate antagonist Fingolimod (FTY720), Cladribine, Fumarate, Laquinimod, drugs affecting B-cells, and antisense agents and agents against CD49d.

The aforementioned methods for the determination of the at least one biomarker can be implemented into a device. A device as used herein shall comprise at least the aforementioned means. Moreover, the device, preferably, further comprises means for comparison and evaluation of the detected characteristic feature(s) of the at least one biomarker and, also preferably, the determined signal intensity. The means of the device are, preferably, operatively linked to each other. How to link the means in an operating manner will depend on the type of means included into the device. For example, where means for automatically qualitatively or quantita- tively determining the biomarker are applied, the data obtained by said automatically operating means can be processed by, e.g., a computer program in order to facilitate the assessment. Preferably, the means are comprised by a single device in such a case. Said device may ac- cordingly include an analyzing unit for the biomarker and a computer unit for processing the resulting data for the assessment. Preferred devices are those which can be applied without the particular knowledge of a specialized clinician, e.g., electronic devices which merely require loading with a sample.

5

Alternatively, the methods for the determination of the at least one biomarker can be implemented into a system comprising several devices which are, preferably, operatively linked to each other. Specifically, the means must be linked in a manner as to allow carrying out the method of the present invention as described in detail above. Therefore, operatively linked, as

10 used herein, preferably, means functionally linked. Depending on the means to be used for the system of the present invention, said means may be functionally linked by connecting each mean with the other by means which allow data transport in between said means, e.g., glass fiber cables, and other cables for high throughput data transport. Nevertheless, wireless data transfer between the means is also envisaged by the present invention, e.g., via LAN (Wireless

15 LAN, W-LAN). A preferred system comprises means for determining biomarkers. Means for determining biomarkers as used herein encompass means for separating biomarkers, such as chromatographic devices, and means for metabolite determination, such as mass spectrometry devices. Suitable devices have been described in detail above. Preferred means for compound separation to be used in the system of the present invention include chromatographic devices, 0 more preferably devices for liquid chromatography, HPLC, and/or gas chromatography. Preferred devices for compound determination comprise mass spectrometry devices, more preferably, GC-MS, LC-MS, direct infusion mass spectrometry, FT-ICR-MS, CE-MS, HPLC-MS, quad- rupole mass spectrometry, sequentially coupled mass spectrometry (including MS-MS or MS- MS-MS), ICP-MS, Py-MS or TOF. The separation and determination means are, preferably, 5 coupled to each other. Most preferably, LC-MS and/or GC-MS are used in the system of the present invention as described in detail elsewhere in the specification. Further comprised shall be means for comparing and/or analyzing the results obtained from the means for determination of biomarkers. The means for comparing and/or analyzing the results may comprise at least one databases and an implemented computer program for comparison of the results. Preferred em-

30 bodiments of the aforementioned systems and devices are also described in detail below.

Therefore, the present invention relates to a diagnostic device comprising:

an analysing unit comprising a detector for at least one biomarker as listed in any one of Tables 1 , 1 a, 1 b, 2, 2a, 2b, 3, 3a, 3b wherein said analyzing unit is adapted for determining the amount

35 of the said biomarker detected by the detector, and, operatively linked thereto;

an evaluation unit comprising a computer comprising tangibly embedded a computer program code for carrying out a comparison of the determined amount of the at least one biomarker and a reference amount and a data base comprising said reference amount as for the said biomarker whereby a multiple sclerosis in a subject, a subject is in need for a therapy of multiple 0 sclerosis or the success of a multiple sclerosis is identified, or whereby is it differentiated between i) a subject showing symptoms of multiple sclerosis and suffering from multiple sclerosis and ii) a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclera- sis, if the result of the comparison for the at least one metabolite is essentially identical to the kind of regulation and/or fold of regulation indicated for the respective at least one biomarker in any one of Tables 1 , 1 a, 1 b, 2, 2a, 2b, 3, 3a or 3b.

Ii5an preferred embodiment, the present invention relates to a diagnostic device comprising:

i) an analysing unit comprising a detector for at least one ceramide as listed in any one of Tables 1 , 1 a, 2, 2a, 3 or 3a, or a detector for ceramides wherein said analyzing unit is adapted for determining the amount of the said at least one cermide detected by the detector, and, operatively linked thereto;

)) 10 an evaluation unit comprising a computer comprising tangibly embedded a computer program code for carrying out a comparison of the determined amount of the at least one biomarker and a reference amount and a data base comprising said reference amount as for the said biomarker whereby a multiple sclerosis in a subject, a subject is in need for a therapy of multiple sclerosis or the success of a multiple sclerosis is identified, or whereby is it differentiated be- 15 tween i) a subject showing symptoms of multiple sclerosis and suffering from multiple sclerosis and ii) a subject showing symptoms of multiple sclerosis, but not suffering from multiple sclerosis, if the result of the comparison for the at least ceramide is essentially identical to the kind of regulation and/or fold of regulation indicated for the respective at least one ceramide in any one of Tables 1 , 1 a, 2, 2a, 3 or 3a.

20

In a preferred embodiment, the device comprises a further database comprising the kind of regulation and/or fold of regulation values indicated for the respective at least one biomarker in any one of Tables 1 , 1 a, 1 b, 2, 2a, 2b, 3, 3a, 3b and a further tangibly embedded computer program code for carrying out a comparison between the determined kind of regulation and/or fold of 25 regulation values and those comprised by the database.

Furthermore, the present invention relates to a data collection comprising characteristic values of at least one biomarker being indicative for a medical condition or effect as set forth above 30 (i.e. diagnosis of multiple sclerosis in a subject, identifying whether a subject is in need for a therapy of multiple sclerosis or determining whether a multiple sclerosis therapy is successful).

The term "data collection" refers to a collection of data which may be physically and/or logically grouped together. Accordingly, the data collection may be implemented in a single data storage

35 medium or in physically separated data storage media being operatively linked to each other.

Preferably, the data collection is implemented by means of a database. Thus, a database as used herein comprises the data collection on a suitable storage medium. Moreover, the database, preferably, further comprises a database management system. The database management system is, preferably, a network-based, hierarchical or object-oriented database manage-

40 ment system. Furthermore, the database may be a federal or integrated database. More preferably, the database will be implemented as a distributed (federal) system, e.g. as a Client- Server-System. More preferably, the database is structured as to allow a search algorithm to compare a test data set with the data sets comprised by the data collection. Specifically, by using such an algorithm, the database can be searched for similar or identical data sets being indicative for a medical condition or effect as set forth above (e.g. a query search). Thus, if an identical or similar data set can be identified in the data collection, the test data set will be asso- ciated with the said medical condition or effect. Consequently, the information obtained from the data collection can be used, e.g., as a reference for the methods of the present invention described above. More preferably, the data collection comprises characteristic values of all metabolites comprised by any one of the groups recited above.

In light of the foregoing, the present invention encompasses a data storage medium comprising the aforementioned data collection.

The term "data storage medium" as used herein encompasses data storage media which are based on single physical entities such as a CD, a CD-ROM, a hard disk, optical storage media, or a diskette. Moreover, the term further includes data storage media consisting of physically separated entities which are operatively linked to each other in a manner as to provide the aforementioned data collection, preferably, in a suitable way for a query search.

The present invention also relates to a system comprising:

(a) means for comparing characteristic values of the at least one biomarker of a sample operatively linked to

(b) a data storage medium as described above.

The term "system" as used herein relates to different means which are operatively linked to each other. Said means may be implemented in a single device or may be physically separated devices which are operatively linked to each other. The means for comparing characteristic values of biomarkers, preferably, based on an algorithm for comparison as mentioned before. The data storage medium, preferably, comprises the aforementioned data collection or database, wherein each of the stored data sets being indicative for a medical condition or effect referred to above. Thus, the system of the present invention allows identifying whether a test data set is comprised by the data collection stored in the data storage medium. Consequently, the methods of the present invention can be implemented by the system of the present invention.

In a preferred embodiment of the system, means for determining characteristic values of biomarkers of a sample are comprised. The term "means for determining characteristic values of biomarkers" preferably relates to the aforementioned devices for the determination of metabolites such as mass spectrometry devices, NMR devices or devices for carrying out chemical or biological assays for the biomarkers. Moreover, the present invention relates to a diagnostic means comprising means for the determination of at least one biomarker selected from any one of the groups referred to above.

The term "diagnostic means", preferably, relates to a diagnostic device, system or biological or chemical assay as specified elsewhere in the description in detail.

The expression "means for the determination of at least one biomarker" refers to devices or agents which are capable of specifically recognizing the biomarker. Suitable devices may be spectrometric devices such as mass spectrometry, NMR devices or devices for carrying out chemical or biological assays for the biomarkers. Suitable agents may be compounds which specifically detect the biomarkers. Detection as used herein may be a two-step process, i.e. the compound may first bind specifically to the biomarker to be detected and subsequently generate a detectable signal, e.g., fluorescent signals, chemiluminescent signals, radioactive signals and the like. For the generation of the detectable signal further compounds may be required which are all comprised by the term "means for determination of the at least one biomarker". Compounds which specifically bind to the biomarker are described elsewhere in the specification in detail and include, preferably, enzymes, antibodies, ligands, receptors or other biological molecules or chemicals which specifically bind to the biomarkers.

Further, the present invention relates to a diagnostic composition comprising at least one biomarker selected from any one of the groups referred to above.

The at least one biomarker selected from any of the aforementioned groups will serve as a bi- omarker, i.e. an indicator molecule for a medical condition or effect in the subject as set for the elsewhere herein. Thus, the metabolite molecules itself may serve as diagnostic compositions, preferably, upon visualization or detection by the means referred to in herein. Thus, a diagnostic composition which indicates the presence of a biomarker according to the present invention may also comprise the said biomarker physically, e.g., a complex of an antibody and the me- tabolite to be detected may serve as the diagnostic composition. Accordingly, the diagnostic composition may further comprise means for detection of the metabolites as specified elsewhere in this description. Alternatively, if detection means such as MS or NMR based techniques are used, the molecular species which serves as an indicator for the risk condition will be the at least one biomarker comprised by the test sample to be investigated. Thus, the at least one biomarker referred to in accordance with the present invention shall serve itself as a diagnostic composition due to its identification as a biomarker.

In general, the present invention contemplates the use of at least one biomarker selected from the biomarkers listed in any one of Tables 1 , 2, 1 a, 2a, 1 b, or 2b in a sample of a subject for the diagnosis of multiple sclerosis, the use of at least one biomarker selected from the biomarkers listed in any one of Tables 3, 3a; or 3b; in a sample of a subject for diagnosing an active status of multiple sclerosis, or the use of at least one biomarker selected from the biomarkers of Table 1 and/or 2 in a sample of a subject for predicting multiple sclerosis as well as the use of at least one biomarker selected from the biomarkers of Table 3 in a sample of a subject for predicting an active status of multiple sclerosis.

All references cited herein are herewith incorporated by reference with respect to their disclosure content in general or with respect to the specific disclosure contents indicated above. The invention will now be illustrated by the following Examples which are not intended to restrict or limit the scope of this invention.

Example 1: Study design for the differential diagnosis of Multiple Sclerosis (MS) from other neurological symptoms or diseases.

Specification of the samples:

Cases: 41 newly diagnosed therapy naive patients with MS (n=15) or a Clinical Isolated Syndrom (CIS) (n=26).

Controls: 42 patients with different neurological symptoms or diseases not being CIS or MS (e.g. headache (n=1 1 ), hypaesthesia (n=10), paresthesia (n=6), meningitis patients (n=4) patients' with other symptoms (n=1 1 ). Of the patients with other symptoms one patient was diagnosed with abducens paresis, one patient had leg ache, one patient suffered from dysarthria, one patient suffered from the Els- berg-syndrome, one patient showed idiopathic facial nerve paresis, one patient suffered from headache and hypestesia, one patient suffered from neuropathy, one patient suffered from pseudotumor cerebri, and two patients exhibited giddiness.

Of the 41 CIS and MS patients, 18 patients had change in signs or symptoms (acute attack), while 23 did not clinically change (stable phase).

Additional information from all subjects (e.g. gender, age, BMI, date of sampling, disease status) was used for analysis as described in Example 3 in detail.

Serum was prepared from all samples by centrifugation, and samples were stored at -80 °C until measurements had been performed.

Example 2: Determination of metabolites Human serum samples were prepared and subjected to LC-MS/MS and GC-MS or SPE-LC- MS/MS (hormones) analysis as described in the following: Proteins were separated by precipitation from blood serum. After addition of water and a mixture of ethanol and dichloromethane the remaining sample was fractioned into an aqueous, polar phase and an organic, lipophilic phase. For the transmethanolysis of the lipid extracts a mixture of 140 μΙ of chloroform, 37 μΙ of hydrochloric acid (37% by weight HCI in water), 320 μΙ of methanol and 20 μΙ of toluene was added to the evaporated extract. The vessel was sealed tightly and heated for 2 hours at 100°C, with shaking. The solution was subsequently evaporated to dryness. The residue was dried completely.

The methoximation of the carbonyl groups was carried out by reaction with methoxyamine hydrochloride (20 mg/ml in pyridine, 100 μΙ for 1.5 hours at 60°C) in a tightly sealed vessel. 20 μΙ of a solution of odd-numbered, straight-chain fatty acids (solution of each 0.3 mg/mL of fatty acids from 7 to 25 carbon atoms and each 0.6 mg/mL of fatty acids with 27, 29 and 31 carbon atoms in 3/7 (v/v) pyridine/toluene) were added as time standards. Finally, the derivatization with 100 μΙ of N-methyl-N-(trimethylsilyl)-2,2,2-trifluoroacetamide (MSTFA) was carried out for 30 minutes at 60°C, again in the tightly sealed vessel. The final volume before injection into the GC was 220 μΙ. For the polar phase the derivatization was performed in the following way: The methoximation of the carbonyl groups was carried out by reaction with methoxyamine hydrochloride (20 mg/ml in pyridine, 50 μΙ for 1.5 hours at 60°C) in a tightly sealed vessel. 10 μΙ of a solution of odd- numbered, straight-chain fatty acids (solution of each 0.3 mg/mL of fatty acids from 7 to 25 carbon atoms and each 0.6 mg/mL of fatty acids with 27, 29 and 31 carbon atoms in 3/7 (v/v) pyri- dine/toluene) were added as time standards. Finally, the derivatization with 50 μΙ of N-methyl-N- (trimethylsilyl)-2,2,2-trifluoroacetamide (MSTFA) was carried out for 30 minutes at 60°C, again in the tightly sealed vessel. The final volume before injection into the GC was 1 10 μΙ.

The GC-MS systems consist of an Agilent 6890 GC coupled to an Agilent 5973 MSD. The au- tosamplers are CompiPal or GCPal from CTC.

For the analysis usual commercial capillary separation columns (30 m x 0,25 mm x 0,25 μηη) with different poly-methyl-siloxane stationary phases containing 0 % up to 35% of aromatic moi- eties, depending on the analysed sample materials and fractions from the phase separation step, were used (for example: DB-1 ms, HP-5ms, DB-XLB, DB-35ms, Agilent Technologies). Up to 1 μί of the final volume was injected splitless and the oven temperature program was started at 70 °C and ended at 340 °C with different heating rates depending on the sample material and fraction from the phase separation step in order to achieve a sufficient chromatographic separa- tion and number of scans within each analyte peak. Furthermore RTL (Retention Time Locking, Agilent Technologies) was used for the analysis and usual GC-MS standard conditions, for example constant flow with nominal 1 to 1 .7 ml/min. and helium as the mobile phase gas, ionisa- tion was done by electron impact with 70 eV, scanning within a m/z range from 15 to 600 with scan rates from 2.5 to 3 scans/sec and standard tune conditions.

The HPLC-MS systems consisted of an Agilent 1 100 LC system (Agilent Technologies, Wald- bronn, Germany) coupled with an API 4000 Mass spectrometer (Applied Biosystem/MDS SCI- EX, Toronto, Canada). HPLC analysis was performed on commercially available reversed phase separation columns with C18 stationary phases (for example: GROM ODS 7 pH, Thermo Betasil C18). Up to 10 μΙ_ of the final sample volume of evaporated and reconstituted polar and lipophilic phase was injected and separation was performed with gradient elution using metha- nol/water/formic acid or acetonitrile/water/formic acid gradients at a flowrate of 200 μΙ_/ηΊΐη.

Mass spectrometry was carried out by electrospray ionisation in positive mode for the non-polar fraction and negative mode for the polar fraction using multiple-reaction-monitoring-(MRM)- mode and fullscan from 100 - 1000 amu.

Steroids and their metabolites were measured by online SPE-LC-MS (Solid phase extraction- LC-MS). Catecholamines and their metabolites were measured by online SPE-LC-MS as described by Yamada et al. (J. Anal.Toxicol. (26), 2002, 17-22). For both catecholamines and related metabolites and steroids and related metabolites, quantification was achieved by means of stable-isotope-labelled standards, and absolute concentrations were calculated.

Analysis of complex lipids in serum samples:

Total lipids were extracted from serum by liquid/liquid extraction using chloroform/methanol. The lipid extracts were subsequently fractionated by normal phase liquid chromatography

(NPLC) into eleven different lipid groups according to Christie (Journal of Lipid Research (26), 1985, 507-512).

The lipid classes Monoacylglycerides (MAG), Triacylglycerides (TAG), Phosphatidylcholines (PC), Phosphatidylserines (PS) were measured by GC.

The fractions are analyzed by GC-MS after derivatization with TMSH (Trimethyl sulfonium hydroxide), yielding the fatty acid methyl esters (FAME) corresponding to the acyl moieties of the class-separated lipids. The concentrations of FAME from C14 to C24 are determined in each fraction.

The fractions were analyzed by LC-MS/MS using electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) with detection of specific multiple reaction monitoring (MRM) transitions for cholesterol esters (CE) sphingoymelins (SM), and ceramides (CER) re- spectively. Sphingosines and sphingosine-1 -phosphates (SP) were analyzed by LC-MS/MS using elec- trospray ionization (ESI) with detection of specific multiple reaction monitoring (MRM) transitions as described by Schmidt H et.al., Prostaglandins & other Lipid Mediators 81 (2006), 162-170. Metabolites in Tables 1 -3 and/or 1 a-3a and/or 1 b-3b derived from one of these fractions include the respective abbreviation in front of their name separated by an underscore.

Eicosanoids and related were measured out of serum by offline- and online-SPE LC-MS/MS (Solid phase extraction-LC-MS/MS) (Masoodi M and Nicolaou A: Rapid Commun Mass Spec- trom. 2006 20(20): 3023-3029. Absolute quantification was performed by means of stable isotope-labelled standards.

Example 3: Data analysis and statistical evaluation Serum samples were analyzed in randomized analytical sequence design with pooled samples (so called "pool") generated from aliquots of each sample. Following comprehensive analytical validation steps, the raw peak data for each analyte were normalized to the median of pool per analytical sequence to account for process variability (so called "pool-normalized ratios"). If available, absolute concentrations of metabolites were used for statistical analysis. In all other cases, pool-normalized ratios were used. All data were Iog10-transformed to achieve normal distribution.

For the study described in Example 1 , a fixed-effects ANOVA model was designed containing the factors age (numerical), BMI (numerical), gender (categorical), sample preparation time (numerical), and diagnosis (all CASES (with or without acute attack), CASES with acute attack, CASES without acute attack, and controls - reference: controls). CASES includes MS-patients as well as CIS-patients. Pairwise interactions of the factors age, BMI, and gender were considered due to high number of metabolites influenced by these factors. Statistical significance was read out from p-values of t-statistics. Direction and strength of regulation were obtained on ratio scale by back transformation of contrast estimates ("ratio = 10^Acontrast_estimate") by calculation of ratios of median values for the groups to be compared. Regulation type was determined for each metabolite as "up" for increased (ratios >1 ) within the respective group (e.g. CASES with and without acute attacks) vs. reference (controls) and "down" for decreased (ratios <1 ) vs. reference. All metabolite Tables were filtered for significance (p-value < 0.05).

In order to identify biomarkers for multiple sclerosis, the read-out for diagnosis the comparison of all CASES (with or without acute attacks) vs. control reference was considered (Table 1 ). In order to read out diagnosis effects related periods of acute attacks during multiple sclerosis disease CASES with acute attacks were compared with the reference control (Table 2) and fur- thermore, the comparison between CASES with acute attacks vs. CASES without acute attacks were analyzed (Table 3). The results of the analyses are summarized in the following Tables, below. The biomarkers to be determined in accordance with the methods of the present invention are listed in the following Tables. Biomarkers not precisely defined by their name are further characterized in Table 4

Table 1 : Metabolites which are altered between CASES (CIS and MS patients) and Controls (patients with neurological symptoms or diseases)

Metabolite Kind of regMedian of p- ulation ("up" CASES value or "down") relative to of t- controls test

CEFLCeramide (d16:1,C22:0) up 1.22 0.028

CEFLCeramide (d16:1,C23:0) up 1.28 0.017

CEFLCeramide (d16:1,C24:0) up 1.25 0.018

CEFLCeramide (d17:1,C22:0) up 1.23 0.023

CER_Ceramide (d17:1,C23:0) up 1.26 0.015

CEFLCeramide (d17:1,C24:0) up 1.27 0.012

CEFLCeramide (d18:1,C21:0) up 1.18 0.012

CEFLCeramide (d18:1,C22:0) up 1.19 0.010

CEFLCeramide (d18:1,C23:0) up 1.21 0.007

CEFLCeramide (d18:1,C23:1) up 1.18 0.024

CEFLCeramide (d18:2,C22:0) up 1.20 0.018

CEFLCeramide (d18:2,C23:0) up 1.23 0.009

CEFLCeramide (d18:2,C24:0) up 1.19 0.017

CEFLCeramide (d18:2,C24:1) up 1.16 0.016

CEFLCeramide (d18:1,C24:0) up 1.14 0.038

Threonic acid up 1.13 0.022

Phosphatidylcholine (C18:0,C22:6) down 0.87 0.009

Phosphatidylcholine (C16:0,C22:6) down 0.94 0.046

Phosphatidylcholine (C18:2,C20:4) down 0.94 0.046

MAG_Palmitic acid (C16:0) down 0.80 0.012

PC_Docosahexaenoic acid (C22:cis[4,7,10,13,16,19]6) down 0.85 0.044 Table 1 a: Metabolites which are increased in CASES (CIS and MS patients) compared to Controls (patients with neurological symptoms or diseases)

Table 1 b: Metabolites which are decreased in CASES (CIS and MS patients) compared to Controls (patients with neurological symptoms or diseases)

Metabolite Kind of Median of p-value regulation CASES of t-test

- "down" relative to

controls

Phosphatidylcholine (C18:0,C22:6) down 0.87 0.009

Phosphatidylcholine (C16:0,C22:6) down 0.94 0.046

Phosphatidylcholine (C18:2,C20:4) down 0.94 0.046

MAG_Palmitic acid (C16:0) down 0.80 0.012

PC_Docosahexaenoic acid (C22:cis[4,7,10,13,16,19]6) down 0.85 0.044 Table 2: Metabolites which are altered between CASES (CIS and MS patients) with acute attack and Controls (patients with neurological symptoms or diseases)

Metabolite Kind of Median of p-value of regulation CASES t-test

("up" or with

"down") acute

attack

relative to

controls

CEFLCeramide (d16:1,C22:0) up 1.29 0.030

CEFLCeramide (d16:1,C23:0) up 1.35 0.025

CEFLCeramide (d16: 1 ,C24: 1) up 1.27 0.025

CEFLCeramide (d17:1,C23:0) up 1.29 0.038

CEFLCeramide (d17:1,C24:1) up 1.24 0.032

CEFLCeramide (d18:1,C21:0) up 1.29 0.003

CEFLCeramide (d18:1,C22:1) up 1.29 0.004

CEFLCeramide (d18:1,C23:0) up 1.24 0.021

CEFLCeramide (d18:1,C23:1) up 1.31 0.005

CEFLCeramide (d18:2,C22:0) up 1.24 0.033

CEFLCeramide (d18:2,C23:0) up 1.28 0.015

CEFLCeramide (d18:2,C24:1) up 1.22 0.016

CEFLCeramide (d18:1,C24:0) up 1.14 0.12

CEFLCeramide (d18:1,C24:1) up 1.12 0.056

Threonic acid up 1.19 0.016

MAG_Myristic acid (C14:0) down 0.26 0.008

PS_Myristic acid (C14:0) down 0.17 0.048

TAG_dihomo-gamma-Linolenic acid (C20:cis[8,11,14]3) down 0.58 0.046

Homovanillic acid (HVA) down 0.75 0.009

Pyruvate up 1.21 0.040

Table 2a: Metabolites which are increased in CASES (CIS and MS patients) with acute attack compared to Controls (patients with neurological symptoms or diseases)

Metabolite Kind of Median of p-value of regulation - CASES t-test "up" with

acute

attack

relative to

controls

CEFLCeramide (d16:1,C22:0) up 1.29 0.030

CEFLCeramide (d16:1,C23:0) up 1.35 0.025

CEFLCeramide (d16:1,C24:1) up 1.27 0.025

CEFLCeramide (d17:1,C23:0) up 1.29 0.038

CEFLCeramide (d17:1,C24:1) up 1.24 0.032

CEFLCeramide (d18:1,C21:0) up 1.29 0.003

CEFLCeramide (d18:1,C22:1) up 1.29 0.004

CEFLCeramide (d18:1,C23:0) up 1.24 0.021

CEFLCeramide (d18:1,C23:1) up 1.31 0.005

CEFLCeramide (d18:2,C22:0) up 1.24 0.033

CEFLCeramide (d18:2,C23:0) up 1.28 0.015

CEFLCeramide (d18:2,C24:1) up 1.22 0.016

CER_Ceramide (d18:1,C24:0) up 1.14 0.12

CEFLCeramide (d18:1,C24:1) up 1.12 0.056

Threonic acid up 1.19 0.016

Pyruvate up 1.21 0.040

Table 2b: Metabolites which are decreased in CASES (CIS and MS patients) with acute attack compared to Controls (patients with neurological symptoms or diseases)

Metabolite Kind of Median of p-value of regulation CASES t-test ("up" or with

"down") acute

attack

relative to

controls

MAG_Myristic acid (C14:0) down 0.26 0.008

PS_Myristic acid (C14:0) down 0.17 0.048

TAG_dihomo-gamma-Linolenic acid (C20:cis[8,11,14]3) down 0.58 0.046

Homovanillic acid (HVA) down 0.75 0.009 Table 3: Metabolites which are altered between CASES (CIS and MS patients) with acute attack and Cases without acute attack

(1 ^*: see Table4) Table 3a: Metabolites which are increased in CASES (CIS and MS patients) with acute attack compared to CASES (CIS and MS patients) without acute attack

(1 ^*: see Table4)

Table 3b: Metabolites which are decreased in CASES (CIS and MS patients) with acute attack compared to CASES (CIS and MS patients) without acute attack

Metabolite Kind of Median of p-value of regulation - CASES t-test

"down" with

acute

attack

relative to

CASES

without

attack

MAG_Myristic acid (C14:0) down 0.14 0.001

TAG_dihomo-gamma-Linolenic acid (C20:cis[8,11,14]3) down 0.36 0.001

TAG_Docosapentaenoic acid (C22:cis[4,7,10,13,16]5) down 0.31 0.007

TAG_Eicosenoic acid (C20:cis[11]1) down 0.61 0.038

Homovanillic acid (HVA) down 0.74 0.014

TAG (C16:0,C18:2) (*1) down 0.70 0.007 TAG (C18:2,C18:2) (*1) down 0.65 0.004

TAG (C16:0,C18:2,C18:2) down 0.68 0.009

TAG (C16:1,C18:1,C18:2) down 0.68 0.009

Table 4: Additional chemical/physical properties of biomarkers marked with (^*1 ) in the Tables above

Metabolite name Description

Phosphatidylcholine No 02 represents the sum parameter of phosphatidylcholines. It exhibits the following characteristic ionic

Phosphatidylcholine No 02 species when detected with LC/MS, applying electro-spray ionization (ESI) mass spectrometry: mass-to-charge ratio (m/z) of the positively charged ionic species is 808.4 (+/- 0.5).

TAG (C16:0,C18:2) represents the sum parameter of triacyl- glycerides containing the combination of a C16:0 fatty acid unit and a C18:2 fatty acid unit. It exhibits the following characteristic

TAG (C16:0,C18:2)

ionic species when detected with LC/MS, applying electro-spray ionization (ESI) mass spectrometry: mass-to-charge ratio (m/z) of the positively charged ionic species is 575.4 (+/- 0.5).

TAG (C18:2,C18:2) represents the sum parameter of triacyl- glycerides containing the combination of two C18:2 fatty acid units. It exhibits the following characteristic ionic species when

TAG (C18:2,C18:2)

detected with LC/MS, applying electro-spray ionization (ESI) mass spectrometry: mass-to-charge ratio (m/z) of the positively charged ionic species is 599.6 (+/- 0.5).

Claims

A method for diagnosing multiple sclerosis (MS) in a subject comprising the steps of: a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2, and

b) comparing the amount of the said at least one biomarker to a reference

amount, whereby multiple sclerosis is to be diagnosed.

The method of claim 1 , wherein the said at least one biomarker is selected from the group of biomarkers listed in Table 1 a and/or 2a and wherein an increase in the said at least one biomarker as compared to the reference amount is indicative for multiple sclerosis.

The method of claim 1 , wherein the said at least one biomarker is selected from the group of biomarkers listed in Table 1 b and/or Table 2b and wherein a decrease in the said at least one biomarker as compared to the reference amount is indicative for multiple sclerosis.

The method of any one of claims 1 to 3, wherein multiple sclerosis is diagnosed in an early stage of multiple sclerosis.

The method of any one of claims 1 to 4, wherein said reference amount is derived from an apparently healthy subject or from a group thereof, or from a subject known not to suffer from MS, but showing MS symptoms, or from a group thereof.

A method for identifying whether a subject is in need for a therapy of multiple sclerosis comprising the steps of the method of any one of claims 1 to 5 and the further step of identifying a subject in need for a therapy of multiple sclerosis.

A method for differentiating between i) a subject showing symptoms of multiple sclerosis and suffering from multiple sclerosis and ii) a subject showing MS symptoms, but not suffering from multiple sclerosis, comprising

a) determining in a sample of a subject showing symptoms of multiple sclerosis the amount of at least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2, and

b) comparing the amount of the said at least one biomarker to at least one reference amount, whereby it is differentiated between i) and ii).

A method for determining whether a multiple sclerosis therapy is successful comprising the steps of:

a) determining at least one biomarker selected from the biomarkers listed in Table 1 and/or Table 2 in a first and a second sample of the subject wherein said first sample has been taken prior to or at the onset of the multiple sclerosis therapy and said second sample has been taken after the onset of the said therapy; and

comparing the amount of the said at least one biomarker in the first sample to the amount in the second sample, whereby a change in the amount determined in the second sample in comparison to the first sample is indicative for multiple sclerosis therapy being successful.

The method of claim 8, wherein

i) said change is a decrease and wherein said at least one biomarker is selected from the biomarkers listed in Table 1 a and/or 2a; or

ii) said change is an increase and wherein said at least one biomarker is selected from the biomarkers listed in Table 1 b and/or 2b.

10. The method of claim 8 or 9, wherein said therapy comprises administration of at least one drug selected from the group consisting of: Interferon Betal a, Interferon Beta 1 b, Azathi- oprin, Cyclophosphamide, Glatiramer Acetate, Immunglobuline Methotrexat, Mitoxan- trone, Leustatin, IVIg, Natalizumab, Teriflunomid, Statins, Daclizumab, Alemtuzumab, Ritximab, Sphingosin 1 phosphate antagonist Fingolimod (FTY720), Cladribine, Fumarate, Laquinimod, drugs affecting B-cells, and antisense agents and agents against CD49d.

1 1 . A method for diagnosing an active status of multiple sclerosis in a subject comprising the steps of:

a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 3; and

b) comparing the amount of the said at least one biomarker to a reference

amount, whereby multiple sclerosis is to be diagnosed.

The method of claim 1 1 , wherein

i) the said at least one biomarker is selected from the group of biomarkers listed in Table 3a and wherein an increase in the said at least one biomarker is indicative for an active status of multiple sclerosis, or

ii) the said at least one biomarker is selected from the group of biomarkers listed in Table 3b and wherein a decrease in the said at least one biomarker is indicative for an active status of multiple sclerosis.

The method of claim 1 1 or 12, wherein said reference amount is derived from a subject or a group of subjects exhibiting a stable status of multiple sclerosis.

A method for predicting whether a subject is at risk of developing multiple sclerosis comprising the steps of:

a) determining in a sample of the subject the amount of at least one biomarker selected from the biomarkers listed in Table 1 and/or 2; and b) comparing the amount of the said at least one biomarker to a reference amount, whereby it is predicted whether a subject is at risk of developing multiple sclerosis.

A method for predicting whether a subject is at risk of developing an active status of multiple sclerosis comprising the steps of:

b) comparing the amount of the said at least one biomarker to a reference

amount, whereby it is predicted whether a subject is at risk of developing an active status of multiple sclerosis.