USPatent applicationPatented

Methods for predicting the response of multiple sclerosis patients to interferon therapy and diagnosing multiple sclerosis

Granted 6 Dec 2011 · 2 office actions

Assignee: Max Planck Society

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Inventors: Daria Salyakina, Florian Holsboer, Manfred Uhr, Frank Weber +2 · Examiner: Jeanine A Goldberg · AU 1634 · TC 1600

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Abstract

The present invention relates to a method of diagnosing a predisposition of a multiple sclerosis (MS) patient for responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) and means to perform the method. Furthermore, the invention relates to a method of diagnosing a predisposition of a patient for developing multiple sclerosis (MS) and corresponding means.

Description

12 parts
›This application is the National Phase of International…

This application is the National Phase of International Application

PCT/EP2007/001689, filed Feb. 27, 2007 which designated the U.S. and that International Application was published under PCT Article 21(2) in English, and claims priority to European Application Serial No. 06 00 3978.1, filed Feb. 27, 2006.

The present invention provides a method of diagnosing a predisposition of a multiple sclerosis (MS) patient for responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) and means to perform the method. Furthermore, the invention provides a method of diagnosing a predisposition of a patient for developing multiple sclerosis (MS) and corresponding means.

A variety of documents is cited throughout this specification. The disclosure content of said documents including manufacturer's manuals is herewith incorporated by reference in its entirety.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system involving the destruction of myelin on neuronal axons (i.e. demyelination) which leads to the formation of multifocal plaques. MS can be divided into two categories: relapsing-remitting, and chronic-progressive. Chronic-progressive MS is further subdivided into primary-progressive, secondary-progressive, and progressive-relapsing.

Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system in young adults. Over 1 million individuals worldwide are afflicted with MS. It's prevalence is estimated at 60-100/100.000 in the northern United States and northern Europe (see Kesselring Ed. “Epidemiologie.” 3 ed. Psychiatrie, Neurologie, Klinische Psychologie. Stuttgart: Kohlhammer, 70-76, 1997). Although the mortality due to MS is low, neurological sequelae often occur early in life and prohibit private and professional development. Symptoms of MS include optic neuritis, fatigue, poor coordination, spasticity, dizziness, tremors, speech difficulties, swallowing difficulties, pain, and emotional mood swings.

In about 80 to 90% of patients, the disease starts with a clinically isolated syndrome which proceeds to a relapsing-remitting course. After several years there is an increasing tendency for the patient to enter a phase of slow, steady or fluctuating deterioration of neurologic function, which is then called a secondary progressive course. Only 10-15% of patients demonstrate a primary progressive deterioration without any relapses just from the beginning.

The pathological hallmark of MS is the demyelinated plaque with relative axonal sparing and glial scar formation (Pnneas “The Neuropathology of Multiple Sclerosis.” Ed. J. C. Koetsier. Amsterdam: Elsevier Science Publishers, 213-257, 1985; Lassmann (1998) Mult Scler 4: 93-98). MS has been considered an autoimmune disorder consisting of auto-reactive T cells and autoantibodies that drive an inflammatory process, leading to macrophage recruitment, and subsequent destruction of myelin/oligodendrocytes and axons. Recent detailed studies on large collections of MS lesions, however, have indicated that structural features of the plaques are extremely variable and the events involved in the immunopathogenesis of MS may be more complicated (Lucchinetti et al. (2000) Ann Neurol 47:707-717; Lassmann et al. (2001) Trends Mol Med 7: 115-121). A structural analysis of oligodendrocyte pathology demonstrated two principal patterns of oligodendrocyte pathology in MS lesions with oligodendrocyte survival or progenitor recruitment in the first and extensive destruction of myelinating cells in the second pattern. In addition quite diverse paftems of myelin destruction were observed and grouped into four subtypes: (1) Macrophage-mediated demyelination; (2) Antibody-mediated demyelination; (3) distal oligodendrogliopathy and apoptosis; and (4) primary oligodendroglia degeneration (Lassmann et al. (2001) Trends Mol Med 7: 115-121). The finding of such heterogeneity is also supported by experimental data in animal models of MS.

The majority of MS cases is sporadic. However, about 15% of the MS patients have an affected relative with the highest risk of recurrence being observed in siblings (Ebers et al. (1986) N Engl J Med 315: 1638-1642). In a large population-based study, it was found that almost 20% of the index cases had an affected relative, again with the highest risk in siblings (Sadovnick et al. (1988) Am J Med Genet. 29: 533-541). The case for heritability is supported also by studies in twins in whom one of each pair is known to have MS. Ebers et al. verified the diagnosis in 7 of 27 pairs of monozygotic twins (26%) and in only one of 43 pairs of dizygotic twins (2.3%). In two clinically normal monozygotic twins, lesions were detected by MRI, bringing the concordance rate to 33% (Ebers et al. (1986) N Engl J Med 315: 1638-1642). The concordance rate in dizygotic pairs is similar to that in nontwin siblings. Within families with more than one affected member, no consistent genetic pattern has emerged. Studies dealing with the epidemiology and genetics of MS indicate multifactorial origin with environmental and genetic factors affecting disease susceptibility. (Sadovnick et al. (1988) Am J Med Genet. 29: 533-541). Several genome screens have verified the association with HLA-DR2 and identified a number of markers with increased sharing in MS families with somewhat discouraging results (Dyment et al. (2001) Neurogenetics. 3: 145-151; Sawcer et al. (2002) Brain 125: 1337-1347). This finding is not surprising with respect to the described heterogeneity of the disease. However, a study, which correlates genetic markers with responders versus non-responders to a given therapy has not been done so far.

There are presently three major categories of therapies for the treatment of MS: (1) type I interferons (type I IFN) such as interferon-beta (IFN-β), which includes interferon-beta1a (IFN-β1a), or interferon beta1b (IFN-β1b), and interferon-alpha (IFN-α); (2) glatiramer acetate; and (3) mitoxantrone. Several clinical trials have evaluated the various therapeutic options, for example, interferon-β, glatiramer acetate, immunoglobulins and mitoxantrone for patients suffering from different clinical subtypes of MS such as relapsing-remitting, primary or secondary-chronic progressive disease. Randomized, placebo-controlled, double-blind clinical trials with different preparations of IFN-β1a (Avonex®, Rebif®) and IFN-β1b (Betaferon®) were completed between 1993 and 1998 and resulted in the approval of these drugs for relapsing-remitting MS (RRMS). These studies found that IFN-β reduced relapse rates by approximately 30% and inhibited new magnetic resonance imaging (MRI) lesions by approximately 70% (Rudick et al. (2004) Ann Neurol 56: 548-55). Similar results were also obtained with IFN-α (Durelli et al. (1995) Mult Scler 1 Suppl 1:S32-S37; Myhr et al. (1999) Neurology 52:1049-1056). Despite of extensive research, the exact mechanism of IFN-β and IFN-α in treatment of MS remains unclear. Several hypotheses have been proposed which are based on the suppression of lymphocyte proliferation, suppression of antigen presentation, suppression of migration of proinflammatory cells across the blood brain barrier, or a cytokine shift from TH1 to TH2 (Hartung et al. (2004) J Neurol 251: v12-v29).

›It is widely assumed that individual patients differ…

It is widely assumed that individual patients differ in their therapeutic response to interferon treatment. Patients who continue to experience disease activity during therapy are termed non-responders, suboptimal responders, or breakthrough patients. The Expanded Disability Status Scale (EDSS) scale is often used as measurement of clinical deterioration (Kurtzke (1983) Neurology 33:1444-1452). Criteria, however, vary among the different studies and lack validation. Response has been defined as having a lower relapse rate during IFN-β treatment compared with 1 to 2 years before therapy. A study of 262 patients from the European Database for Multiple Sclerosis found that 33% of individuals were non-responders while the remaining individuals were classified as responders (Waubant et al. (2003) Neurology 61: 184-189). Another study found that half of the patients treated with IFN-β demonstrates no benefit based on the EDSS as a measure of deterioration during treatment (R10 et al. (2002) Ann Neurol 52: 400-406). A recent study found that new MRI lesion activity during IFN-β1a treatment correlated with poor response to IFN-β1a (Rudick et al. (2004) Ann Neurol 56: 548-555). Some smaller studies correlated the response to treatment with IFN-β to biological markers such as reduced IFN-γ production (Petereit et al. (2002) Mult Scler 8: 492-494), decreased mitogen driven T cell proliferation (Killestein et al. (2002) J Neuroimmunol 133: 217-224), or the early and sustained induction of the tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) (Wandinger et al. (2003) Lancet 361: 2036-2043). In a set of 70 selected genes, nine sets of gene triplets were identified which predicted response to therapy in 52 patients with 86% accuracy (Baranzini et al. (2005) PLoS Biol 3: 166-176). Using microarray technology, non-responder and responder phenotypes to IFN-β were assessed by longitudinal gadolinium-enhanced MRI scans and clinical disease activity was shown to differ in their ex vivo gene expression profile (Sturzebecher et al. (2003) Brain 126: 1419-1429).

However, there presently exist no reliable methods to predict the response of an individual patient to the chosen therapy prior to treatment. An observation period of 1 to 2 years during therapy is necessary to classify the individual patient as responder or non-responder by means of relapse rate and measurement of clinical deterioration. Furthermore IFN-β therapy is associated with a number of adverse reactions, including flu-like symptoms, transient laboratory abnormalities, increased spasticity and injection site reactions. Therefore, there is an unmet need in the field of MS for methods and kits for assessing and predicting the response to therapy.

At present, the clinical subtypes do not correlate with the histopathologically defined subtypes, which indicates that different immunopathological mechanisms operate within the clinically defined subtypes (Lucchinetti et al. (2000) Ann Neurol 47: 707-717). Although brain biopsy can help to determine the response of a MS patient to therapy (Keegan et al. (2005) Lancet 366: 579-82), it is an invasive method that is not ethically justified in MS patients with typical clinical and radiological findings. An identification of genotypes that respond to a given therapy without major side effects would enable an individualized therapy with therapeutic drugs.

Finally, a more efficient, individualized immunomodulatory therapy will not only be a major breakthrough for the large number of MS patients, but also lead to a dramatic cost reduction in the health system by decreasing hospitalization time and disease related disability.

A long list of potential susceptibility gene candidates have been associated with MS. For example, polymorphisms in the interferon receptor 1 gene (IFNAR1) and interferon receptor 2 gene (IFNAR2) have been shown to confer susceptibility to MS, but not to predict response to IFN-β treatment (Leyva et al. (2005) J Neuroimmunol 163:165-171). Other potential gene candidates for MS susceptibility include the PRKCA, PTPRC, NOS2a, Ncf1, LAG3 and CD24 genes (Barton et al., (2004) Brain 127:1717-1722; Barcellos et al. (2004) Ann Neurol 55:793-800; Vyshkina et al (2004) Mult Scler 10:614-617; Hultqvist et al. (2004) Proc Natl Acad Sci USA 101:12646-12651; WO05/054810; WO03/031655). The growth factor TGFB1 has also been proposed as a potential susceptibility gene for MS (Green et al (2001) J Neuroimmunol 116:116-124). However, several studies have shown that polymorphisms in TGFB1 do not contribute in a major way to susceptibility to MS (He et al. (1998) J Neuroimmunol 86:13-19; McDonnell et al. (1999) Mult Scler 5:105-109; Weinshenker et al. (2001) J Neuroimmunol 120:138-145). Furthermore, WO05/054810 discloses methods for predicting the likelihood that an individual will develop MS and the rate of MS progression by testing for polymorphisms in CD24. WO03/014319 relates to a collection of polymorphic sites in genes known or suspected to have a role in MS. EP 1 114 998 relates to methods for determining the success rate of treatment of MS by determining the amount of at least one of the cytokines from the group consisting of IL-18, IL-12p40, IFN-γ, IL-4, IL-10, TGF-β, IL-12Rβ1, IL-12Rβ2 and/or IL-12p35.

Presently, the major histocompatibility complex (MHC) on the chromosome 6p region is the only confirmed susceptibility locus for MS (Ibrahim and Gold (2005) Curr Opin Neurol 18:231-235). However, no effect between HLA-DR2 polymorphisms of the MHC and the age of onset was observed. In addition, no differences between HLA-DR2 polymorphisms and the course of initial clinical symptoms or the distribution of responders and non-responders to an IFN type I therapy was observed (Villoslada et al. (2002) J Neuroimmunol 130:194-201).

Thus, the technical problem underlying the present invention was to provide means and methods for a physician for the verification of a diagnosis of multiple sclerosis (MS) of an individual patient and for a prediction of the likelihood of a responsiveness of an individual MS-patient to a treatment with interferon-α (IFN-α) and/or interferon-β (IFN-β).

›The solution to this technical problem is achieved…

The solution to this technical problem is achieved by the embodiments characterized in the claims.

Accordingly, the present invention relates in a first embodiment to a method of diagnosing a predisposition of a multiple sclerosis (MS) patient for responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) comprising determining in a sample from the patient the presence of at least one nucleic acid sequence motive selected from the group consisting of:

(a) a nucleic acid sequence motive in the 5′UTR region of the gene encoding HNRPUL1 selected from the nucleic acid sequence motives of Table A:

(b) a nucleic acid sequence motive in the intergenic region located between the genes encoding AXL, HNRPUL1, MGC20255, TGFB1 or MGC4093 selected from the nucleic acid sequence motives of Table B:

(c) a nucleic acid sequence motive in the intron sequence of a gene encoding CYP2S1, AXL, HNRPUL1, MGC20255 or TGFB1 selected from the nucleic acid sequence motives of Table C:

(d) a nucleic acid sequence motive in the 3′UTR region of a gene encoding MGC20255 selected from the nucleic acid sequence motives of Table D:

(e) a nucleic acid sequence motive which is complementary to a nucleotide sequence motive as defined in any one of (a) to (d);

wherein the presence of one or more of the above nucleic acid sequence motives is indicative for an inferior response of the patient to a treatment of MS with IFN-α and/or IFN-β.

Interferon-α (IFN-α) and interferon-β (IFN-β) are well known type I interferons. The cytokines bind to a receptor designated as IFN-α/β receptor or CD118.

The term “nucleic acid sequence motive” defines a part of a polynucleotide having a characteristic sequence of nucleotides. In accordance with the present invention the term “polynucleotide” defines a nucleic acid molecule consisting of more than 30 nucleotides. The group of molecules subsumed under polynucleotides also comprises complete genes. Also included by said definition are vectors such as cloning and expression vectors. The term “oligonucleotides” describes in the context of the invention nucleic acid molecules consisting of at least ten and up to 30 nucleotides.

Nucleic acid molecules (comprising polynucleotides and oligonucleotides), in accordance with the present invention, include DNA, such as cDNA or genomic DNA, RNA (e.g. mRNA), also in synthetic or semisynthetic form, further synthetic or semisynthetic derivatives of DNA or RNA (e.g. PNA or phosphorothioates) and mixed polymers, both sense and antisense strands. They may contain additional non-natural or derivatized nucleotide bases, as will be readily appreciated by those skilled in the art. Synthetic or semisynthetic derivatives of DNA or RNA are, of course, not comprised in a sample derived from a patient, but may be used as detective means in the method of the invention.

For the purposes of the present invention, a peptide nucleic acid (PNA) is a polyamide type of DNA analog and the monomeric units for the derivatives of adenine, guanine, thymine and cytosine are available commercially (Perceptive Biosystems). Certain components of DNA, such as phosphorus, phosphorus oxides, or deoxyribose derivatives, are not present in PNAs. As disclosed by Nielsen et al., Science 254:1497 (1991); and Egholm et al., Nature 365:666 (1993), PNAs bind specifically and tightly to complementary DNA strands and are not degraded by nucleases. In fact, PNA binds more strongly to DNA than DNA itself does. This is probably because there is no electrostatic repulsion between the two strands, and also the polyamide backbone is more flexible. Because of this, PNA/DNA duplexes bind under a wider range of stringency conditions than DNA/DNA duplexes, making it easier to perform multiplex hybridization. Smaller probes can be used than with DNA due to the strong binding. In addition, it is more likely that single base mismatches can be determined with PNA/DNA hybridization because a single mismatch in a PNA/DNA 15-mer lowers the melting point (T.sub.m) by 8°-20° C., vs. 4°-16° C. for the DNA/DNA 15-mer duplex. Also, the absence of charge groups in PNA means that hybridization can be done at low ionic strengths and reduce possible interference by salt during the analysis.

The term “(poly)peptide” as used herein describes a group of molecules which comprises the group of peptides, consisting of up to 30 amino acids, as well as the group of polypeptides, consisting of more than 30 amino acids. In accordance with the invention, the group of polypeptides comprises “proteins” as long as the proteins consist of a single polypeptide. Also in line with the definition the term “(poly)peptide” describes fragments of proteins. (Poly)peptides may further form dimers, trimers and higher oligomers, i.e. consisting of more than one (poly)peptide molecule. (Poly)peptide molecules forming such dimers, trimers etc. may be identical or non-identical. The corresponding higher order structures are, consequently, termed homo- or heterodimers, homo- or heterotrimers etc. Homo- or heterodimers etc. also fall under the definition of the term “protein”. The terms “polypeptide” and “protein” also refer to naturally modified polypeptides/proteins wherein the modification is effected e.g. by glycosylation, acetylation, phosphorylation and the like. Such modifications are well known in the art.

The term “position” used in accordance with the present invention means the position of either a nucleotide within a nucleic acid sequence depicted herein or the position of an amino acid within an amino acid sequence depicted herein. The start position for a sequence motive in a given nucleic acid sequence identifies the position at which a sequence motive starts. The nucleotide following the start position in a nucleic acid sequence is the nucleotide at the 3′ position of the starting nucleotide. Thus, the motives are in a 5′→3′ orientation in the genomic strand which corresponds in the sequence of exon regions of a gene with the sequence of the mRNA which is translated (+strand). The genomic strand which is complementary thereto is the −strand. Nucleotide sequence motives defined as being complementary to the nucleotide sequence motives in the +strand are at the position which is complementary to the referred relative position in the +strand depicted in SEQ ID NO: 1. The term “start position relative to SEQ ID NO 1” defines the position at which the “nucleic acid sequence motive” starts relative to SEQ ID NO: 1. More specifically, the term defines the situation that the specified nucleic acid sequence motive replaces nucleotides in SEQ ID NO: 1, starting with the position in SEQ ID NO: 1 indicated in the table. In other terms, whereas the sequence of SEQ ID NO: 1 stands for the wild-type allele (at least for the positions of interest indicated in the tables), the nucleic acid sequence motive (representing a SNP) replaces the nucleotides in the wild-type allele, starting with the position indicated in the respective table. This nucleic acid sequence motive is associated with a specific phenotype such as the inferior response to a treatment of MS with a type I IFN. The presence of at least one of the referred nucleic acid sequence motives at the indicated positions instead of nucleotides present in the wild-type sequence of SEQ ID NO:1 is indicative of the respective phenotype.

›According to the invention the presence of at…

According to the invention the presence of at least one (one or more) of the referred sequence motives in a sample from a patient is indicative for an inferior response of the patient to a treatment of MS with a type I IFN. Accordingly, a patient which comprises at least one allele for a motive associated with an inferior response in the +strand, respectively the complementary motive in the −strand, shows an inferior response to a treatment of MS with a type I IFN.

A positive response of a patient to a treatment of MS with a type I IFN is clinically characterized by a stable course during therapy for at least 2 years. This means no relapse or a reduction of relapse rate ≧⅔ compared to the relapse rate before interferon therapy and no progression in MS associated symptoms, i.e. deterioration in EDSS <1 point during the 2 years of therapy.

The term “inferior response of the patient to a treatment of MS with IFN-α and/or IFN-β” describes a response of a patient to such treatment, which is significantly reduced compared to the one of a patient with a positive response to a treatment of MS with a type I IFN. Accordingly, the lack of a response to such treatment is comprised by the definition of an inferior response.

As described herein above, the gene encoding the growth factor TGF-β has been proposed as a potential susceptibility gene for MS (Green et al. (2001) loc cit.). However, a connection between the individual sequence of the gene in a sample isolated from an MS-patient and the potential success of a treatment of MS comprising the administration of a type I IFN was never described or suggested. The nucleic acid sequence and the amino acid sequence of the human TGFB1 gene are disclosed in SEQ ID NOs: 2 and 3. The nucleic acid sequence of the complete TGFB1 gene corresponds to the sequence from position 137537 to position 160703 in SEQ ID NO: 1. Further human nucleic acids for TGFB1 are disclosed in Genbank Accession numbers NM — 000660, AY871240, AY871239, AY871245, AY871244, AY871243, AY871242, AY871241, AY871238, AY871237, AY871236, AY871235, AY871234, AY871233, AY871232, BC000125, BC022242, BC001180, AY330202, AY330201, AH013154.

The MGC20255 gene is located on chromosome 19q13.2 and was first identified during the generation of more than 15,000 full-length human and mouse cDNA sequence (Strausberg et al. (2002) Proc Natl Acad Sci USA 99:16899-16903), and in the characterization of 21,243 full-length human cDNAs (Ota et al. (2004) Nat Genet. 36:40-45). The nucleic acid sequence and the amino acid sequence of the human MGC20255 are disclosed in SEQ ID NOs: 4 and 5. The nucleic acid sequence of the complete MGC20255 gene corresponds to the sequence from position 116980 to position 131674 in SEQ ID NO: 1. Further human nucleic acids for MGC20255 are disclosed in Genbank Accession numbers DQ052389, NM — 052848, BC011577, NT — 011109, and BC019597.

HNRPUL1 (also known has heterogeneous nuclear ribonucleoprotein U-like 1, E1B-AP5) is a nuclear RNA-binding protein of the hnRNP family. HNRPUL1 was first identified as an interacting partner of the adenovirus type 5 early 1B 55-kDa protein (Gabler et al. (1998) J Virol 72:7960-7971) and has also been found to interact with p53, BRD7, and HRMT1L1 (Barral et al. (2005) FEBS Letters 579:2752-2758; Kzhyshkowska et al. (2003) Biochem. J. 371:385-393; Kzhyshkowska et al. (2001) Biochem. J. 358:305-314). The nucleic acid sequence and the amino acid sequence of the human HNRPUL1 are disclosed in SEQ ID NOs: 6 and 7. The nucleic acid sequence of the complete HNRPUL1 gene corresponds to the sequence from position 69310 to position 114485 in SEQ ID NO: 1. Further human nucleic acids for HNRPUL1 are disclosed in Genbank Accession numbers NM — 007040, NM — 144734, NM — 144733, NM — 144732, DR005039, DN999074, DN997940, DN993239, BC002564, BC027713, NT — 086903, NT — 011109; BC004242, BC009988, and BC014232. HNRPUL1 can bind to mRNA, and has been shown to be involved in the transport and processing of RNA, and is involved in transcriptional regulation.

CYP2S1 is a dioxin-inducible member of the cytochrome P450 superfamily (Rylander et al (2001) Biochem Bioph Res Co 281:529-535). The nucleic acid sequence and the amino acid sequence of the human CYP2S1 are disclosed in SEQ ID NOs: 8 and 9. The nucleic acid sequence of the complete CYP2S1 gene corresponds to the sequence from position 1 to position 14330 in SEQ ID NO: 1. Human nucleic acids for CYP2S1 are also disclosed in Genbank Accession numbers NM — 030622, DQ052387, BC033691, DR004638, NT — 086903, NT — 011109, and in WO04/091150. CYP2S1 has been shown to be involved in the metabolism of some aromatic hydrocarbons as well as retinoic acid, suggesting a role in biotransformaUon of both exogenous and endogenous compounds. Moreover, CYP2S1 has been suggested to play a functional role in the metabolism of topical drugs and in mediating the response to photochemotherapy in psoriasis (Smith et al (2003) Lancet. 361:1336-1343). mRNA in situ hybridization analysis has shown that CYP2S1 is highly expressed in epithelial cell types, especially in the epithelia frequently exposed to xenobiotics. In the respiratory tract, the expression was strong in nasal cavity, bronchi, and bronchioli, whereas it was low in the alveolar lining cells. Similarly, CYP2S1 is highly expressed in the epithelial cells throughout the gastrointestinal tract. Strong epithelial expression is also observed in uterine cervix, urinary bladder, and skin. In many exocrine glands (e.g., adrenal gland and pancreas), secretory epithelial cells showed moderate to strong expression levels. In the liver, CYP2S1 expression was low (Saarikoski et al. (2005) J Histochem Cytochem 53:549-556). Genetic polymorphisms in CYP2S1 have been described in a Finnish Caucasian population (Saarikoski et al (2004) Mut Res 554:267-277).

AXL (also called UFO, ARK, and Tyro7) is a receptor tyrosine kinase which was first identified as a transforming gene in human leukemias (O'Bryan et al. (1991) Mol Cell Biol 11:5016-5031; Janssen et al. (1991) Oncogene 6:2113-2120). The nucleic acid sequence and the amino acid sequence of the human AXL are disclosed in SEQ ID NOs: 10 and 11. The nucleic acid sequence of the complete AXL gene corresponds to the sequence from position 25709 to position 68557 in SEQ ID NO: 1. Human nucleic acids for AXL are further disclosed in Genbank Accession numbers NM — 001699, NM — 021913, NT — 086903, NT — 011109, and BC032229. The structure of the AXL extracellular domain makes it unique among receptor tyrosine kinases in that there is a juxtaposition of two immunoglobulin-like repeats and two fibronectin type III repeats (O'Bryan et al. (1991) Mol Cell Biol 11:5016-5031). This pattern of structural elements is reminiscent of many cell adhesion molecules, and has been implicated in cell-cell interactions. The natural ligand of AXL is Gas6 (Stitt et al. (1995) Cell 80:661-670; Varnum et al. (1995) Nature 373:623-626). AXL has been proposed to be a novel regulator of vascular cell function (Melaragno et al. (1999) Trends Cardiovasc Med. 9:250-253), may be involved in the progression of kidney diseases (Yanagita (2004) Clin Exp Nephrol 8:304-309) and may control cell growth (Crosier and Crosier (1997) Pathology 29:131-135).

›As described herein above, it has been observed…

As described herein above, it has been observed in the state of the art that the therapeutic response of an individual MS-patient to a therapy comprising the administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) differs. The verified identification of a patient as a responder, i.e. a patient which shows a positive anamnesis on such therapy, requires according to the state of the art an observation period of at least one or two years. The treatment of patients which are identified 1 or 2 years after the start of a therapy with a type I IFN as an inferior responder (including no-responder) may result in side effects of the treatment such as a flu like syndrome (fever, headache, myalgia), injection site reactions (inflammation, necrosis), anaemia, leukopenia, lymphocytopenia, neutropenia, thrombocytopenia, elevation of liver enzymes, hepatitis, nausea, diarrhoea, exanthema, thyroiditis, depression, anaphylaxis, alopecia, or seizures. Accordingly, the prediction of the potential success of such therapy is of benefit for patients identified as responder type, as well as for patients identified as non- or inferior responder type.

It has been surprisingly found that single nucleotide polymorphisms (SNPs) in the identified nucleic acid sequence motives of a gene selected from MGC20255, HNRPUL1, CYP2S1, AXL, and TGFB1 are predictive of an inferior response of an MS patient to a treatment with IFN-α and/or IFN-β.

Accordingly, the present invention is based on the finding that presence of specific nucleic acid sequence motives in the recited genes are linked to an inferior responsiveness of an individual MS-patient to a therapy comprising the administration of interferon-α (IFN-α) and/or interferon-β (IFN-β).

The first type of SNPs (herein encompassed in the recited sequence motives) which contribute to a motive indicative for an inferior responder type are SNPs in the 5′UTR of the genes identified in item (a). Examples of such SNPs resulting in an inferior nucleic acid sequence motive are described herein above in table A. In the following table A2 the nucleic acid sequence motive found in the sample of a patient which shows an inferior response to a treatment of MS with a type I IFN is compared vis-à-vis the motive of the responder type. This type of SNPs can only be detected at the nucleic acid level.

A second type of SNPs in sequence motives which may contribute to a motive indicative for an inferior responder type are SNPs in exons of the genes identified herein, which lead to amino acid substitutions in the corresponding amino acid sequence. Such SNPs resulting in an inferior nucleic acid sequence motive can be detected at the nucleic acid level as well as on protein level.

A third type of SNPs in sequence motives which may contribute to a motive indicative for an inferior responder type are SNPs in exons which do not lead to amino acid substitutions in the corresponding amino acid sequence. Such SNPs resulting in an inferior nucleic acid sequence motive can be detected only at the nucleic acid level. A forth type of SNPs in sequence motives which contribute to a motive indicative for an inferior responder type are SNPs in the intergenic region of the genes identified in item (b). The intergenic region is the nucleic acid sequence located between two adjacent genes. Examples of such SNPs resulting in an inferior nucleic acid sequence motive are described herein above in table B. In the following table B2 the nucleic acid sequence motive found in the sample of a patient which shows an inferior response to a treatment of MS with a type I IFN is compared vis-à-vis the motive of the responder type. This type of SNPs can only be detected at the nucleic acid level.

A fifth type of SNPs in sequence motives which contribute to a motive indicative for the prediction of an inferior responder type are SNPs in the intron sequence of the genes identified in item (c). Examples of such SNPs resulting in an inferior nucleic acid sequence motive are described herein above in table C. In the following table C2 the nucleic acid sequence motive found in the sample of a patient which shows an inferior response to a treatment of MS with a type I IFN is compared vis-à-vis the motive of the responder type. This type of SNPs can only be detected at the nucleic acid level.

A last type of SNPs in sequence motives contributing to a motive indicative for an inferior responder type are SNPs in the 3′UTR region of the genes identified in item (d). Examples of such SNPs resulting in an inferior nucleic acid sequence motive are described herein above in table D. In the following table D2 the nucleic acid sequence motive found in the sample of a patient which shows an inferior response to a treatment of MS with a type I IFN is compared vis-à-vis the motive of the responder type. This type of SNPs can only be detected at the nucleic acid level.

In line with the above, the SNPs which contribute to the sequence motives which are indicative of a specific phenotype can be located in different regions of a gene. It is known that polymorphisms in promoter and enhancer regions can affect gene function by modulating transcription, particularly if they are situated at recognition sites for DNA binding proteins (Fishman et al., J. Clin. Invest. 102 (1998), 1369-1376). The term “polymorphism” which is used in the present invention means single nucleotide substitution, nucleotide insertion and nucleotide deletion which in the case of insertion and deletion includes insertion or deletion of one or more nucleotides at a position of a gene and corresponding alterations in expressed proteins. Polymorphisms in the 5′ untranslated region (5′UTR) of genes can affect the efficiency with which proteins are translated. A representative example of this is in the c-myc gene where a C-G SNP that creates an internal ribosome entry site is associated with increased efficiency of c-myc translation and myeloma (Chappell et al., Oncogene 19 (2000), 4437-4440). Polymorphisms in the 3′UTR can affect gene function by altering the secondary structure of RNA and efficiency of translation or by affecting motifs in the RNA that bind proteins which regulate RNA degradation. Polymorphisms within introns can affect gene function by affecting RNA splicing resulting in aberrant polypeptides. Another way in which intronic polymorphisms can affect gene function is when they affect regulatory motifs within introns. Examples are the Sp1 binding site polymorphism within intron 1 of the COLIA1 gene (Mann et al., J. Clin. Invest 107 (2001), 899-907) and a repeat polymorphisms within the IL-1Ra gene (Keen et al., Bone 23 (1998), 367-371). Further examples between intronic SNPs and gene function are described in Caceres and Komblihft, Trends Genet. 4 (2002), 186-93.

›It is preferred for the method of the…

It is preferred for the method of the invention that the presence of the at least one nucleic acid sequence motive is determined by assays based on physical separation of nucleic acid molecules, ligase chain reaction assay, cleavage and digestion assay, sequencing assay, nucleic acid amplification assay, hybridization assay or assays based on protein detection.

Examples for assays based on physical separation of nucleic acid molecules include without limitation MALDI-TOF, denaturating gradient gel electrophoresis and other such methods known in the art, see for example Petersen et al., Hum. Mutat. 20 (2002) 253-259; Hsia et al., Theor. Appl. Genet. 111 (2005) 218-225; Tost and Gut, Clin. Biochem. 35 (2005) 335-350; Palais et al., Anal. Biochem. 346 (2005) 167-175.

Examples for cleavage and digestion assays include without limitation restriction digestion assays such as restriction fragments length polymorphism assays (RFLP assays), RNase protection assays, assays based on chemical cleavage methods and enzyme mismatch cleavage assays, see e.g. Youil et al., Proc. Natl. Acad. Sci. U.S.A. 92 (1995) 87-91; Todd et al., J. Oral Maxil. Surg. 59 (2001) 660-667; Amar et al., J. Clin. Microbiol. 40 (2002) 446-452.

Examples for nucleic acid amplification assays and means to perform such include without limitation PCR, (including nested PCR, RT-PCR, PCR extension assays, Nucleic Acid Sequence Base Amplification (NASBA), single-strand confirmation polymorphism (SSCP) PCR), amplification refractory mutation systems (ARMSTM) and amplification refractory mutation system linear extension (ALEXTM) assays. Details of such methods can be found in art, see, for example, Newton et al., Nucleic Acids Res. 17 (1989) 2503-2516; Agrawal (Ed.), “Protocols for Oligonucleotides and Analogs: Synthesis and Properties (Methods in Molecular Biology, 20)”, Humana Press, 1993; Haque et al., Diagn. Mol. Pathol. 7 (1998) 248-252; Innis et al. (Ed.), “PCR Applications: Protocols for Functional Genomics”, Academic Press, 1999; Chen and Janes (Ed.), “PCR Cloning Protocols: From Molecular Cloning to Genetic”, 2nd edition, Humana Press, 2002; Pissardet al., Clin. Chem. 48 (2002) 769-772; Steemers et al., Nature Meth. 3 (2006) 31-33; Kakavas et al., J. Clin. Lab. Anal. 20 (2006) 1-7.

Examples for sequencing assays comprise without limitation approaches of sequence analysis by direct sequencing, fluorescent SSCP in an automated DNA sequencer and Pyrosequencing. These procedures are common in the art, see e.g. Adams et al. (Ed.), “Automated DNA Sequencing and Analysis”, Academic Press, 1994; Alphey, “DNA Sequencing: From Experimental Methods to Bioinformatics”, Springer Verlag Publishing, 1997; Ramon et al., J. Transl. Med. 1 (2003) 9; Meng et al., J. Clin. Endocrinol. Metab. 90 (2005) 3419-3422.

Examples for hybridization assays comprise without limitation Northern and Southern blot assays, heteroduplex analysis, detection of mutations by sequence specific oligonucleotide hybridization, allele-specific oligonucleotide hybridization on DNA chips, assays based on the Illumina's® technology, assays based on the BeadArray® technology, see, for example, Barnes et al., Nucleic Acids Res. 33 (2005) 5914-5923; Fan et al., Biotechniques 39 (2005) 583-588; Shen et al., Mutat. Res.-Fund. Mol. M. 573 (2005) 70-82; Steemers and Gunderson, Pharmacogenomics, 6 (2005) 777-782.

Examples for assays based on protein detection include without limitation method steps such as ion exchange chromatography, gel filtration chromatography, affinity chromatography, high pressure liquid chromatography (HPLC), reversed phase HPLC, disc gel electrophoresis, Western blot analysis, immunoprecipitation, see, for example, Soejima and Koda, Transfusion 45 (2005) 1934-1939; Yeh et al., Anesth. Analg. 101 (2005) 1401-1406; Chou et al., Am. J. Clin. Pathol. 124 (2005) 330-338.

The above described assays are known in the art, e.g. from standard text books such as Sambrook, Russell “Molecular Cloning, A Laboratory Manual”, Cold Spring Harbor Laboratory, N.Y. (2001); Ausubel, “Current Protocols in Molecular Biology”, Green Publishing Associates and Wiley Interscience, N.Y. (1989); Higgins and Hames (Eds.) “Nucleic acid hybridization, a practical approach” IRL Press Oxford, Washington D.C., (1985); Nollau et al, Clin. Chem. 43 (1997), 1114-1128; Burczak and Mardis (Ed.), “Polymorphism Detection & Analysis Techniques”, Eaton Pub Co, 2000; Cotton et al. (Ed.), “Mutation Detection: A Practical Approach”, Irl Press, 1998; Taylor (Ed.), “Laboratory Methods for the Detection of Mutations and Polymorphisms in DNA”, CRC Press, 1997; Taylor and Day (Ed.) “Guide to Mutation Detection”, Wiley, 2005. The use of some of the recited assays is described in the appended examples.

In a preferred embodiment of the method of diagnosing a predisposition of a multiple sclerosis (MS) patient for a responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) of the invention, the nucleic acid amplification assay is a PCR performed by the use of one or more nucleic acid molecules as primers comprising a sequence as depicted in SEQ ID NOs: 12 to 91. In an alternatively preferred embodiment of this method the nucleic acid amplification assay is a PCR extension assay performed by the use of one or more nucleic acid molecules as primers comprising a sequence as depicted in SEQ ID NOs: 92 to 131.

It is also preferred for the method of diagnosing a predisposition of a multiple sclerosis (MS) patient for a responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β) of the invention that the hybridization assay is performed by the use of one or more nucleic acid molecules as probes comprising a sequence as depicted in SEQ ID NOs: 132 to 211.

The term “hybridizes/hybridizing” as used herein refers to a pairing of a polynucleotide to a (partially) complementary strand of this polynucleotide which thereby form a hybrid. Said complementary strand polynucleotides are, e.g. parts of polynucleotides (such as oligonucleotides) comprising at least 10, preferably at least 15 such as at least 25 consecutive nucleotides thereof. More preferably, these polynucleotides comprise at least 30, at least 35, at least 100, even more preferably at least 200, and most preferably at least 500 nucleotides in length. Said complementary polynucleotides may be useful as probes in Northern or Southern blot analysis of RNA or DNA preparations, respectively.

›It is well known in the art how…

It is well known in the art how to perform hybridization experiments with nucleic acid molecules. Correspondingly, the person skilled in the art knows what hybridization conditions s/he has to use to allow for a successful hybridization in accordance with item (e), above. The establishment of suitable hybridization conditions is referred to in standard text books such as Sambrook, Russell (2001), loc cit.; Ausubel (1989), loc cit.; or Higgins and Hames (1985), loc cit. In one preferred embodiment, the hybridization assay is effected under stringent conditions.

“Stringent hybridization conditions” refers to conditions which comprise, e.g. an overnight incubation at 65° C. in 4×SSC (600 mM NaCl, 60 mM sodium citrate) followed by washing at 65° C. in 0.1×SSC for one hour. Alternatively, hybridization conditions can comprise: an overnight incubation at 42° C. in a solution comprising 50% formamide, 5×SSC (750 mM NaCl, 75 mM sodium citrate), 50 mM sodium phosphate (pH 7.6), 5×Denhardt's solution, 10% dextran sulfate, and 20 μg/ml denatured, sheared salmon sperm DNA, followed by washing the filters in 0.1×SSC at about 65° C. Said conditions for hybridization are also known by a person skilled in the art as “highly stringent conditions for hybridization”. Also contemplated are nucleic acid molecules that hybridize to the polynucleotides of the invention at lower stringency hybridization conditions (“low stringency conditions for hybridization”). Changes in the stringency of hybridization and signal detection are primarily accomplished through the manipulation of formamide concentration (lower percentages of formamide result in lowered stringency), salt conditions, or temperature. For example, lower stringency conditions include an overnight incubation at 50° C. in 4×SSC or an overnight incubation at 37° C. in a solution comprising 6×SSPE (20×SSPE=3M NaCl; 0.2M NaH 2 PO4; 0.02M EDTA, pH 7.4), 0.5% SDS, 30% formamide, 100 μg/ml salmon sperm blocking DNA; followed by washes at 50° C. with 1×SSPE, 0.1% SDS. In addition, to achieve an even lower stringency, washes performed following stringent hybridization can be done at higher salt concentrations (e.g. 5×SSC). It is of note that variations in the above conditions may be accomplished through the inclusion and/or substitution of alternate blocking reagents used to suppress background in hybridization experiments. Typical blocking reagents include Denhardt's reagent, BLOTTO, heparin, denatured salmon sperm DNA, and commercially available proprietary formulations. The inclusion of specific blocking reagents may require modification of the hybridization conditions described above, due to problems with compatibility. Such modifications can generally be effected by the skilled person without further ado. A hybridization complex may be formed in solution (e.g., Cot or Rot analysis) or between one nucleic acid sequence present in solution and another nucleic acid sequence immobilized on a solid support (e.g., membranes, filters, chips, pins or glass slides to which, e.g., cells have been fixed).

It is preferred for the method of the invention that the hybridization assay is performed by the use of one or more nucleic acid molecules which are synthetic or semisynthetic nucleic acid molecules such as PNA.

In an alternative embodiment the invention provides a solid support comprising one or more of the nucleic acid molecules as depicted in SEQ ID NOs: 12 to 211 or the complementary strand thereof.

A solid support according to the invention provides a surface for the attachment of the one or more of the nucleic acid molecules. Said surface according to the invention may be any surface. The surface may be a coating applied to the support or carrier, or the surface of the support or carrier itself may be used. Support or carrier materials commonly used in the art and comprising, for example, glass, plastic, gold and silicon are envisaged for the purpose of the present invention. Coatings according to the invention, if present, include poly-L-lysine- and amino-silane-coatings as well as epoxy- and aldehyde-activated surfaces.

In a preferred embodiment said solid support is a DNA chip. Methods for the production of DNA chips as well as the use of DNA chip technology are well known in the art and described e.g. in Kohara et al. (2002) Nucleic Acids Res. 30 (16) e87; Flavell et al. (2003) Nucleic Acids Res. 31 (19): e115; Gunderson et al. (2005) Nature Genetics 37:549-554.

Furthermore, the invention provides a diagnostic composition or kit for diagnosing a predisposition of a patient for a responsiveness to a treatment of MS by administration of IFN-α and/or IFN-β comprising one or more of the above described nucleic acid molecules as depicted in SEQ ID NOs: 12 to 211 or the complementary strand thereof or the solid support according to the invention. The diagnostic composition or kitmay comprise appropriate packaging and instructions for the use in the method of the invention. Said composition or kit may further comprise appropriate buffer(s), and enzymes such as reverse transcriptase, thermostable polymerases etc.

In an alternative embodiment the invention also provides a method of diagnosing a predisposition of a patient for developing multiple sclerosis (MS) comprising determining in a sample from the patient the presence of at least one nucleic acid sequence motive selected from the group consisting of:

(a) a nucleic acid sequence motive in the intergenic region located between the genes encoding MGC20255 and TGFB1 selected from the nucleic acid sequence motive of Table E:

(b) a nucleic acid sequence motive in the intron sequence of a gene encoding MGC20255 or HNRPUL1 selected from the nucleic acid sequence motives of Table F:

(c) a nucleic acid sequence motive in the 3′UTR region of a gene encoding MGC20255 selected from the nucleic acid sequence motives of Table G:

(d) a nucleic acid sequence motive which is complementary to a nucleotide sequence motive as defined in any one of (a) to (c);

›wherein the presence of one or more of…

wherein the presence of one or more of the above nucleic acid sequence motives is indicative for a predisposition of the patient for developing MS.

The term “sequence motive associated with MS” describes sequence motives, the presence of at least one of these in a sample from an individual subject (patient) is indicative for MS. Accordingly, the identification of the presence of at least one of these sequence motives indicates that the patient suffers from MS or will develop MS. In contrast, the term “wt sequence motive” defines the sequence motives which are found in individuals which do not suffer from MS or will not develop MS.

The meaning of further recited terms has been described herein above in the context of the method of diagnosing a predisposition of a multiple sclerosis (MS) patient for a responsiveness to a treatment of MS by administration of interferon-α (IFN-α) and/or interferon-β (IFN-β).

As described herein above, MS is a disease which starts in about 80 to 90% of the patients with a clinically isolated syndrome which proceeds to a relapsing-remitting course. Accordingly, generally MS is diagnosed after associating the isolated syndrome with MS. It has been surprisingly found that nucleotide polymorphisms in a haplotype block comprising the genes encoding MGC2055 and HNRPUL1 are susceptible genes for MS. By use of the method of the invention it becomes possible to detect a predisposition of a patient for the development of MS prior to the first clinical indications for the disease. Several clinical studies have shown that an early diagnosis of MS permits the beginning of pre-emptive therapy which reduces the risk and slows disease progression (Trapp et al. (1999) Curr. Opin. Neurol. 12: 295-302; Johnson et al. (2000) Multiple Sclerosis 6: 255-266; Jacobs et al. (2000) New Engl. J. Med. 343: 898-904; Comi et al. (2001) The Lancet 357: 1576-1582).

The first type of SNPs which may contribute to a sequence motive associated with MS are SNPs in exons of the genes identified herein, which lead to amino acid substitutions in the corresponding amino acid sequence. Such SNPs can be detected at the nucleic acid level as well as on protein level.

A second type of SNPs which may contribute to a sequence motive associated with MS are SNPs in exons of the genes identified herein, which do not lead to amino acid substitutions in the corresponding amino acid sequence. Such SNPs can be only detected at the nucleic acid level.

A third type of SNPs which may contribute to a sequence motive associated with MS are SNPs in the 5′UTR region of the genes identified herein. This type of SNPs can only be detected at the nucleic acid level.

A forth type of SNPs contributing to a sequence motive associated with MS are SNPs in the intergenic region of the genes identified in item (a) of the alternative embodiment. Examples of such SNPs are described herein above in table E. In the following table E2 the nucleic acid sequence associated with MS is compared vis-à-vis with the wt sequence motive found in individuals without a predisposition for MS. This type of SNPs can only be detected at the nucleic acid level.

A fifth type of SNPs contributing to a sequence motive associated with MS are SNPs in the intron sequence of the genes identified in item (b) of the alternative embodiment. Examples of such SNPs are described herein above in table F. In the following table F2 the nucleic acid sequence associated with MS is compared vis-à-vis with the wt sequence motive found in individuals without a predisposition for MS. This type of SNPs can only be detected at the nucleic acid level.

A last type of SNPs contributing to a sequence motive associated with MS are SNPs in the 3′UTR region of the genes identified in item (c) of the alternative embodiment. Examples of such SNPs are described herein above in table G. In the following table G2 the nucleic acid sequence associated with MS is compared vis-à-vis with the wt sequence motive found in individuals without a predisposition for MS. This type of SNPs can only be detected at the nucleic acid level.

It is preferred for the method of diagnosing a predisposition of a patient for developing MS, that the presence of the at least one nucleic acid sequence motive is determined by assays based on physical separation of nucleic acid molecules, ligase chain reaction assay, cleavage and digestion assay, sequencing assay, nucleic acid amplification assay, hybridization assay or assays based on protein detection. Corresponding methods have been described herein above.

It is further preferred for the method of diagnosing a predisposition of a patient for developing MS, that the nucleic acid amplification assay is a PCR performed by the use of one or more nucleic acid molecules as primers comprising a sequence as depicted in SEQ ID NOs: 50 to 53, 58 to 61, 64 to 65 and 68 to 83. Alternatively it is preferred for this method, that the nucleic acid amplification assay is a PCR extension assay performed by the use of one or more nucleic acid molecules as primers comprising a sequence as depicted in SEQ ID NOs: 111 to 112, 115 to 116, 118, 120 to 127.

Moreover, it is preferred for the method of diagnosing a predisposition of a patient for developing MS, that the hybridization assay is performed by the use of one or more nucleic acid molecules as probes comprising a sequence as depicted in SEQ ID NOs: 170 to 173, 178 to 181, 184 to 185, 188 to 203.

It is preferred for the method of the invention that the hybridization assay is performed by the use of one or more nucleic acid molecules which are synthetic or semisynthetic nucleic acid molecules such as PNA.

The invention also provides a solid support comprising one or more of the nucleic acid molecules as depicted in SEQ ID NOs: 50 to 53, 58 to 61, 64 to 65 and 68 to 83, SEQ ID NOs: 111 to 112, 115 to 116, 118, 120 to 127 SEQ ID NOs: 170 to 173, 178 to 181, 184 to 185, 188 to 203 or the complementary strand thereof. In a preferred embodiment said solid support is a DNA chip.

›Finally, the invention provides a diagnostic composition for…

Finally, the invention provides a diagnostic composition for diagnosing a predisposition of a patient for MS comprising one or more of the nucleic acid molecules as depicted in SEQ ID NOs: 50 to 53, 58 to 61, 64 to 65 and 68 to 83, SEQ ID NOs: 111 to 112, 115 to 116, 118, 120 to 127 or SEQ ID NOs: 170 to 173, 178 to 181, 184 to 185, 188 to 203 or the complementary strand thereof or the solid support comprising one or more of the recited nucleic acid molecules.

›THE FIGURES SHOW

FIG. 1 :

Pairwise LD in control group in the explored region. On the upper left diagonal are the r2 measures and in the lower right diagonal D′ measures are presented.

FIG. 2 :

Association of the rs11881953, rs7245398 polymorphisms in the HNRPUL1 locus and the rs8109167, rs1865052 polymorphisms in the MGC20255 locus with increased susceptibility to MS. Each graphic depicts the proportion of genotypes in individuals with MS compared to control individuals without MS.

FIG. 3 :

Association of the rs16958994, rs16958999, rs3826714, and rs7257310 polymorphisms in the MGC20255 locus with increased susceptibility to MS. Each graphic depicts the proportion of genotypes in individuals with MS compared to control individuals without MS.

FIG. 4 :

Association of the rs2241720, rs2241719, rs2241718, and rs6957 polymorphisms in the MGC20255 locus with increased susceptibility to MS. Each graphic depicts the proportion of genotypes in individuals with MS compared to control individuals without MS.

FIG. 5 :

Association of the rs11880564 polymorphism in the MGC20255 locus with increased susceptibility to MS. The graphic depicts the proportion of genotypes in individuals with MS compared to control individuals without MS.

FIG. 6 :

Association of the rs338600, rs338584 polymorphisms in the CYP2S1 locus and the rs4803448, rs4802113 polymorphisms in the AXL locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 7 :

Association of the rs2304234 polymorphism in the AXL locus and the rs3760660, rs2304230, rs8103839 polymorphisms in the HNRPUL1 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 8 :

Association of the rs3745295, rs8105901, rs12327659, and rs3752705 polymorphisms in the HNRPUL1 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 9 :

Association of the rs2053086, rs11879562, rs7248164, and rsl 1881953 polymorphisms in the HNRPUL1 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 10 :

Association of the rs7245398, rs1865053 polymorphisms in the HNRPUL1 locus and the rs8109167 polymorphism in the MGC20255 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 11 :

Association of the rs1865052, rs1865051, rs16958994, and rs16958996 polymorphisms in the MGC20255 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 12 :

Association of the rs16958999, rs3826714, rs7257310, and rs2241720 polymorphisms in the MGC20255 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 13 :

Association of the rs2241719, rs2241718, rs6957, and rs11880564 polymorphisms in the MGC20255 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

FIG. 14 :

Association of the rs12985162 polymorphism in the MGC20255 locus and the rs11466345, rs1800472, and rs1800469 polymorphisms in the TGFB1 locus with improved response to interferon treatment in MS individuals. Each graphic depicts the proportion of genotypes in inferior interferon response and improved interferon response groups respectively.

The invention will now be described by reference to the following examples which are merely illustrative and are not to be construed as a limitation of scope of the present invention.

›EXAMPLE 1

Polymorphisms in the TGFB1, MGC20255, HNRPUL1, CYP2S1, and/or AXL Genes can be Used to Predict Response to Interferon Treatment

105 patients diagnosed with MS were selected according to their response to interferon treatment. 53 patients responded to interferon therapy while 52 patients did not respond to interferon treatment. All patient were 18 years and older and MS was diagnosed according to criterias disclosed by Poser (Poser, et al. (1983) Ann. Neurol. 13: 227-231) or McDonaids (McDonald et al. (2001) Ann. Neurol. 50: 121-127). All individuals showed no severe internal or psychiatric disease, which can interfere with the course of MS, and received no additional immunomodulatory or immunosuppressive therapy with the exception of corticosteroids.

Patients who responded to interferon treatment were clinically stable during therapy for at least 2 years, suffered from no relapse or had a reduction of relapse rate ≧⅔ compared to the relapse rate before interferon therapy, and had no progression in MS associated symptoms (deterioration in EDSS <1 during the two years of therapy).

Patients who did not respond to interferon treatment were clinically unstable during therapy during a period of 9 months or longer, no reduction of relapse rate with at least one relapse occurring after 6 months of therapy, and a progression of MS associated symptoms (deterioration in EDSS ≧1 point within one year, such deterioration not related to side effects of therapy).

EDTA blood was collected after informed consent. The study was approved by the local ethic committee of all participating centers. DNA was extracted using the Puregene Kit (Gentra, Minneapolis, USA) with little modifications. Amount of DNA was quantified by UV-absorption and using the picogreen method. Quality of the DNA was assessed by PCR and determination of the melting point in selected samples.

SNPs were selected from the public SNP database dbSNP (http://www.ncbi.nlm.nih.gov:80/). The SNP search tool at _http://ihg.gsf.de/ihg/snps.html_was used to download SNP sequences from public databases. Prior to genotyping, the relevant regions were amplified by PCR. Primers used for PCR amplification are depicted in table 2, see herein below. These primers are also depicted in SEQ ID NOs: 12 to 91.

Genotyping was performed on a MALDI-TOF mass-spectrometer (MassArray® system) employing the Spectrodesigner software (Sequenom™, CA) for primer selection and multiplexing and the homogeneous mass-extension (hMe) process for producing primer extension products. Primers used in the primer extension assays are depicted in table 3, see herein below. These primers are also depicted in SEQ ID NOs: 92 to 131.

Genotyping was also performed by genomewide single nucleotide polymorphism (SNP) genotyping using the Infiniumil assay with the product “Sentrix Bead Chip Array HumanHap300 Genotyping Beach Chip 317k” (Illumina Inc., San Diego, USA) according to the manufacturer's protocols. Starting material was 750 ng native human genomic DNA per chip. Genotype calling was done by cluster analysis of measured fluorescence intensities, using the BeadStudio Software Ver. 2.3.43 (Illumina Inc.).”

All analyses for binary outcomes were performed using logistic regression correcting for the effects of age and sex using both R and SPSS (version 11), as well as by exact contingency table analyses using both R and SPSS. Quantitative variables were analyzed using regression analysis. Linkage disequilibrium was calculated using the “Haploview” software and visualised using “GOLD”.

Results are illustrated in table 1. Positions on chromosome 19 are according to Genbank Accession number NT — 011109.15.

P-values are given as their negative decadic logarithm. Thus, a −log10 p-value equal or above 1.30103 correspond to a p-value equal or below 0.05. Consequently, a −log10 p-value equal or above 1.30103 is considered significant.

The SNPs rs338600, rs338584, rs4802112, rs4803448, rs4803449, rs4802113, rs2304234, rs2304232, rs1946612, rs3760660, rs2304230, rs8103839, rs3745295, rs8105901, rs12327659, rs3752705, rs2053086, rs11879562, rs7248164, rsl1881953, rs7245398, rs1865053, rs8109627, rs8109167, rs1865052, rs1865051, rs16958994, rs16958996, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, rs11880564, rs12985162, rs11466345, rs1800472, and rs1800469 showed association with response and non-response to interferon therapy.

The association between response and non-response to interferon therapy for each allele of rs338600, rs338584, rs4803448, rs4802113, rs2304234, rs3760660, rs2304230, rs8103839, rs3745295, rs8105901, rs12327659, rs3752705, rs2053086, rs11879562, rs7248164, rs11881953, rs7245398, rs1865053, rs8109167, rs1865052, rs1865051, rs16958994, rs16958996, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, rsi1880564, rs12985162, rs11466345, rs1800472, and rs1800469 is further illustrated in FIGS. 6 to 14 .

Thus, assessment of the three haplotype blocks comprise at least one polymorphism selected from the group of rs338600, rs338584, rs4802112, rs4803448, rs4803449, rs4802113, rs2304234, rs2304232, rs1946612, rs3760660, rs2304230, rs8103839, rs3745295, rs8105901, rs12327659, rs3752705, rs2053086, rs11879562, rs7248164, rs11881953, rs7245398, rs1865053, rs8109627, rs8109167, rs1865052, rs1865051, rs16958994, rs16958996, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, rs11880564, rs12985162, rs11466345, rs1800472, or rs1800469 can be used to predict and determine response to interferon therapy in MS patients.

›EXAMPLE 2

MGC20255 and HNRPUL1 are Susceptibility Genes for MS

245 patients diagnosed with MS and 486 control individuals were enrolled in a study to identify susceptibility genes in MS. The age of individuals were 18 years and older. MS was diagnosed according to criterias disclosed by Poser (Poser, et al. (1983) Ann. Neurol. 13: 227-231) or McDonalds (McDonald et al. (2001) Ann. Neurol. 50: 121-127). All individuals showed no severe internal or psychiatric disease, which can interfere with the course of MS.

EDTA blood was collected after informed consent. The study was approved by the local ethic committee of all participating centers. DNA was extracted using the Puregene Kit (Gentra, Minneapolis, USA) with little modifications. Amount of DNA was quantified by UV-absorption and using the picogreen method. Quality of the DNA was assessed by PCR and determination of the melting point in selected samples.

SNPs were selected from the public SNP database dbSNP (http://www.ncbi.nim.nih.gov:80/). The SNP search tool at _http://ihg.gsf.de/ihg/snps.html_was used to download SNP sequences from public databases. Prior to genotyping, the relevant regions were amplified by PCR. Table 2 shows the PCR primers used. These primers are also depicted in SEQ ID NOs: 12 to 91.

Genotyping was performed on a MALDI-TOF mass-spectrometer (MassArray® system) employing the Spectrodesigner software (Sequenom^™, CA) for primer selection and multiplexing and the homogeneous mass-extension (hMe) process for producing primer extension products. Table 3 shows the primers used for the primer extension assays. These primers are also depicted in SEQ ID NOs: 92 to 131.

All analyses for binary outcomes were performed using logistic regression correcting for the effects of age and sex using both R and SPSS (version 11), as well as by exact contingency table analyses using both R and SPSS. Quantitative variables were analyzed using regression analysis. Linkage disequilibrium (LD) was calculated using the “Haploview” software and visualised using “GOLD”. LD structure of the explored region is shown on the FIG. 1 . All SNPs (in accordance with a preferred embodiment of the invention) are distributed in three LD blocks when the block is defined as a region with D′ between all SNPs equal to 1. The biggest block includes MGC20255, HNRPUL1 genes and part of AXL. this region was analysed (in accordance with a preferred embodiment of the invention) using r squared, several small blocks are present, so that the genes discussed above form three separate LD blocks. All associated with MS SNPs are in tightly LD (r squared between 0.93 and 1). However, the r squared measures between SNPs associated with response to interferon therapy are more variable.

Association results are illustrated in table 4. Positions on chromosome 19 are according to Genbank Accession number NT — 011109.15.

P-values are given as their negative decadic logarithm. Thus, a −log10p-value equal or above 1.30103 correspond to a p-value equal or below 0.05. Consequently, a −log10 p-value equal or above 1.30103 is considered significant.

The SNPs rs11881953, rs7245398, rs8109167, rs1865052, rs16958994, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, and rs11880564 showed association with MS.

The association with MS for each allele of rs11881953, rs7245398, rs8109167, rs1865052, rs16958994, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, and rs11880564 is further illustrated in FIGS. 2 to 5 .

Consequently, assessment of the haplotype block comprises at least one polymorphism selected from the group of rs11881953, rs7245398, rs8109167, rs1865052, rs16958994, rs16958999, rs3826714, rs7257310, rs2241720, rs2241719, rs2241718, rs6957, or rs11880564 can be used to diagnose and determine an individuals susceptibility to develop MS.

›Tables in the description — 18
TABLE A
start position relative tonucleic acid
GeneSEQ ID NO: 1sequence motive
HNRPUL169912TT
HNRPUL174951TT
TABLE B start position
Intergenic regionrelative to SEQnucleic acid
between genesID NO 1sequence motive
AXL + HNRPUL168874AA
HNRPUL1 + MGC20255115299TT
MGC20255 + TGFB1132083CC
MGC20255 + TGFB1132394GG
TGFB1 + MGC4093161183GG
TABLE C
start positionnucleic
relative toacid sequence
GeneSEQ ID NO 1sequence motive
CYP2S11230TC or CC
CYP2S113000CC or GG
AXL35377CC or CG
AXL35447CT or TT
AXL35553CC or CT
AXL41782CT or TT
AXL49640CT or TT
AXL63412GG
HNRPUL182380CC
HNRPUL186169TT
HNRPUL192979TT
HNRPUL197359TT
HNRPUL198998AA
HNRPUL1100362TT
HNRPUL1105863GG
HNRPUL1108567CC
HNRPUL1109136GG
HNRPUL1111531AA
MGC20255123873TT
MGC20255124054GG
MGC20255125354GG
MGC20255125772TT
MGC20255125868TT
MGC20255126025CC
MGC20255126073AA
MGC20255126663AA
MGC20255128007CC
TGFB1144348TT
TGFB1148747GG
TABLE D
start positionnucleic
relative toacid sequence
GeneSEQ ID NO 1sequence motive
MGC20255130196GG
MGC20255130468AA
MGC20255130493GG
MGC20255131493TT
and
TABLE A2
start position relative toinferior responseresponder sequence
GeneSEQ ID NO 1sequence motivemotive
HNRPUL169912TTAA or AT
HNRPUL174951TTCC or CT
TABLE B2
Intergenic regionstart position relativeinferior responseresponder
between genesto SEQ ID NO 1sequence motivesequence motive
AXL + HNRPUL168874AAGG
HNRPUL1 + MGC20255115299TTCC or CT
MGC20255 + TGFB1132083CCAA or AC
MGC20255 + TGFB1132394GGAA or AG
TGFB1 + MGC4093161183GGAA or AG
TABLE C2
start position relative toinferior responseresponder sequence
GeneSEQ ID NO 1sequence motivemotive
CYP2S11230TC or CCTT
CYP2S113000CC or GGCG
AXL35377CC or CGGG
AXL35447CT or TTCC
AXL35553CC or CTTT
AXL41782CT or TTCC
AXL49640CT or TTCC
AXL63412GGGA or AA
HNRPUL182380CCGG or CG
HNRPUL186169TTGG or GT
HNRPUL192979TTAA or AT
HNRPUL197359TTCC or CT
HNRPUL198998AAGG or GA
HNRPUL1100362TTCC or CT
HNRPUL1105863GGCC or CG
HNRPUL1108567CCTT or TC
HNRPUL1109136GGAA or AG
HNRPUL1111531AAGG or GA
MGC20255123873TTCC or CT
MGC20255124054GGTT or TG
MGC20255125354GGAA or AG
MGC20255125772TTCC or CT
MGC20255125868TTCC or CT
MGC20255126025CCTT or TC
MGC20255126073AAGG or GA
MGC20255126663AAGG or GA
MGC20255128007CCTT or TC
TGFB1144348TTCC or CT
TGFB1148747GGGA
TABLE D2
start position relative toinferior responseresponder sequence
GeneSEQ ID NO 1sequence motivemotive
MGC20255130196GGCC or CG
MGC20255130468AATT or TA
MGC20255130493GGAA or AG
MGC20255131493TTCC or CT
TABLE E start position
Intergenic regionrelative tonucleic acid
between genesSEQ ID NO 1sequence motive
MGC20255 + TGFB1132083CC
TABLE F start position
relative tonucleic acid
GeneSEQ ID NO 1sequence motive
HNRPUL1109136AA and AG
HNRPUL1111531AG and GG
MGC20255124054GT and TT
MGC20255125354GA and AA
MGC20255125868TC and CC
MGC20255126073AG and GG
MGC20255126663AG and GG
MGC20255128007CT and TT
TABLE G start position
relative tonucleic acid
GeneSEQ ID NO 1sequence motive
MGC20255130196GC and CC
MGC20255130468AT and TT
MGC20255130493GA and AA
MGC20255131493TC and CC
TABLE E2
startsequence
positionmotivewt
Intergenic regionrelative toassociatedsequence
between genesSEQ ID NO 1with MSmotive
MGC20255 + TGFB1132083CCCA and AA
TABLE F2
startsequence
positionmotivewt
relative toassociatedsequence
GeneSEQ ID NO 1with MSmotive
HNRPUL1109136AA and AGGG
HNRPUL1111531AG and GGAA
MGC20255124054GT and TTGG
MGC20255125354GA and AAGG
MGC20255125868TC and CCTT
MGC20255126073AG and GGAA
MGC20255126663AG and GGAA
MGC20255128007CT and TTCC
TABLE G2
startsequence
positionmotivewt
relative toassociatedsequence
GeneSEQ ID NO 1with MSmotive
MGC20255130196GC and CCGG
MGC20255130468AT and TTAA
MGC20255130493GA and AAGG
MGC20255131493TC and CCTT
TABLE 1
Position−log10
Polymorphismgeneon Chr. 19(p-value)maf
rs338600CYP2S1463921831.4870.270
rs338593CYP2S1463961440.4470.477
rs338585CYP2S1464036550.8730.421
rs338584CYP2S1464039531.8540.235
rs168109CYP2S1464081110.1510.495
rs2271546AXL464190370.6560.125
rs4802112AXL464263302.0000.282
rs4803448AXL464264002.2920.459
rs4803449AXL464265062.5230.331
rs4802113AXL464327353.0730.449
rs2304234AXL464405931.9550.412
rs2304232AXL464543652.3010.140
rs1946612AXL464598271.8240.238
rs3760660HNRPUL1464608652.9590.148
rs2304230HNRPUL1464659042.1030.155
rs8103839HNRPUL1464733331.9690.153
rs3745295HNRPUL1464771221.6050.156
rs8105901HNRPUL1464839322.2870.154
rs12327659HNRPUL1464883121.9400.155
rs3752705HNRPUL1464899511.8390.156
rs2053086HNRPUL1464913152.0630.154
rs11879562HNRPUL1464968162.1340.156
rs7248164HNRPUL1464995402.1030.156
rs11881953HNRPUL1465000892.3620.163
rs7245398HNRPUL1465024842.2460.174
rs15052HNRPUL1465052150.9330.150
rs1865053HNRPUL1465062522.2420.190
rs8109627MGC20255465148261.5850.238
rs8109167MGC20255465150071.8820.173
rs1865052MGC20255465163071.8820.174
rs1865051MGC20255465167252.0560.175
rs16958994MGC20255465168211.8820.174
rs16958996MGC20255465169781.6100.173
rs16958999MGC20255465170262.1520.196
rs3826714MGC20255465176162.1050.174
rs7257310MGC20255465189602.2730.175
rs2241720MGC20255465211492.5760.171
rs2241719MGC20255465214212.5760.172
rs2241718MGC20255465214462.1400.173
rs16959007MGC20255465219760.5130.002
rs11668308MGC2025546522276NA0.003
rs6957MGC20255465224462.0190.174
rs11880564MGC20255465230362.5760.172
rs12985162MGC20255465233472.1400.170
rs10426316MGC20255465234890.6580.001
rs8179181TGFB11465300461.1440.249
rs11466345TGFB1465353012.2480.093
rs1800472TGFB1465397001.7760.032
rs2241715TGFB1465487260.7900.323
rs12462166TGFB1465492441.2650.327
rs1800469TGFB1465521361.4630.324
rs1800468MGC4093465524270.6490.075
rs11668109MGC4093465556170.8250.318
rs1982072MGC4093465563490.8250.317
rs2241714MGC4093465612321.1860.324
rs2241713MGC4093465613080.4130.389
rs2241712MGC4093465615961.1170.321
rs9797885MGC4093465648410.8230.449
rs8106934MGC4093465671590.7390.061
rs1046909MGC4093465745520.1030.332
TABLE 2
SNP_IDforward primerreverse primer
rs338600ACGTTGGATGGCTATTTCTGCTGGGATGGGACGTTGGATGTCCAAGGTGTCTCCATCATG
rs338593ACGTTGGATGTGTCCATCCATCTTTCCCTGACGTTGGATGTGTGATGGAGCCAGGCAGAG
rs338585ACGTTGGATGACTATAAACCCCTTCCCACCACGTTGGATGTTGTGAACTAGTGTCCCTGG
rs338584ACGTTGGATGTTCTGCACCCTGGGCTTACTACGTTGGATGGCTGAGTCAGTATTCCTCAC
rs4802112ACACCAACACCACCACGTTAGGGGGACACCGCTGATCGTATAGCATTCCTGGGC
ATAGGTGTAG
rs168109ACGTTGGATGGAAAGATGAGATTGGAATCAGACGTTGGATGCTTATCAATTTATTAAGGCT
rs2271546ACGTTGGATGTATGTTGGGCTGGAGGGTGAACGTTGGATGATTCCTGACTTCCCACAACC
rs4803448ACGTTGGATGCCCTATGGAATTACACATGCACGTTGGATGTGAGTGAGTGAAATTGTGT
rs4803449GACACAGCAGGGGACGAAGGGACACCGCTGATCGTATACTCCAAATCTAT
CCCCTTCCC
rs4802113ACGTTCGATGCCACTCTGAGTGTGCCATTCACGTTGGATGTGGCAACAAGTGTCAAGCTC
rs2304234ACGTTGGATGATCACCCCTTTGGGTCCCAGACGTTGGATGAGGTTCCTTCACTATCAGGG
rs2304232GGATTTCAGATGTGCACCAACACACCTGGCGTTCAAGCAATTCTCCTGCCTCAGTCTCCC
rs1946612GATGTGGCCCCATTCCCTGGCAATTCAGTTCGTGGGCGAGGGGCGGGGTGTCTGGACTG
rs3760660ACGTTGGATGAACTGGATGCGTCTGATCTGACGTTGGATGGCCACACACTATCTCTACTC
rs2304230ACGTTGGATGACCACTCTTAGTTGAGCTCCACGTTGCATGGCGGTTCATGAAGAACCCTG
rs8103839ACGTTGGATGTACACATCCCCACCAAAGACACGTTGGATGTTATCTGGTGGGATCCAAGG
rs3745295ACGTTGGATGCTGAGAGGACTATGGTCATGACGTTGGATGGGACCCTCTCCTAAAAGATG
rs8105901ACGTTGGATGACACATAGGCTAGTGTCTACACGTTGGATGAACTCTCAGATCCCTATGAC
rs12327659ACGTTGGATGTACACAGTGAGCACACAAGGACGTTGGATGCAGCCCCTTATTTCTAGCAC
rs3752705ACGTTGGATGCAGTTCCACGTCATTTCCACACGTTGGATGTCACATTTGACTCCCAGTGC
rs2053086ACGTTGGATGATAGGAACAGAGCTGCACACACGTTGGATGGGGCATTTAAGATGCATCTG
rs11879562ACGTTGGATGAAAGTTAAGTCCCCTCTCCCACGTTGGATGTTCCTATGACCAGATGCCAC
rs7248164ACGTTGGATGAGGAAGGGACAAAGCAGAAGACGTTGGATGACTCAGTTTGTCCTTCCCTG
rs11881953ACGTTGGATGCTCCTGAGTTCACCCAGTTCACGTTGGATGATTAGCCAGGCATGGTGGTG
rs7245398ACGTTGGATGTTACAGGAGCCTGTGCATACACGTTGGATGCAGAGAGCTTCAATCCTGAG
rs15052ACGTTGGATGAAAGCTTTTGGGTCTGGCACACGTTGGATGGCTCCTTCCCTTCAGAACTT
rs1865053ACGTTGGATGTAGTCAGTTTCCCTCCCTTCACGTTGGATGAATTCAGCCCCAATCTTCCC
rs8109627ACGTTGGATGGCCTACCAATCTGAAATGCCACGTTGGATGCAGGGAAGAGAATGGGACAG
rs8109167ACGTTGGATGGACACAGAAGCCTTCTGAACACGTTGGATGTGTTGTGGTCACAAGGATGC
rs1865052ACGTTGGATGGGGTAAGATTGCTGGCAGGAACGTTGGATGCAAAGAAACTGCTCGGACTC
rs1865051ACGTTGGATGTGTCAGCATGCAGGACAATGACGTTGGATGAGACTAGGGCCCCACAAACA
rs16958994ACGTTGGATGAGCTCGTGTACAACTGTGTCACGTTGGATGCACAGGACATGTGTGTGTAC
rs16958996ACGTTGGATGCATGCACACACATGCTTGGAACGTTGGATGGGCACCTGAGTGTGTGTATG
rs16958999ACGTTGGATGCTGTGTGCGCAAGCACTCATACGTTGGATGATACACAGGAAGATAGAGGC
rs3826714ACGTTGGATGACAGTGACGAGGAAGGTGAGACGTTGGATGATGAAGTGGAGACAGACAGG
rs7257310ACGTTGCATGTTGTGATTGCCCCTGCCGTGACGTTGGATGCCAGATTCCATTCAAGAGCC
rs2241720ACGTTGGATGCTCTCAGCCTTTATCTCTGGACGTTGGATGTATAGCAGCCAGGTTTGAGG
rs2241719ACGTTGGATGACAATTTTCCCTTCCTCCGCACGTTGGATGTCAGGACCCATGATAACAGC
rs2241718ACGTTGGATGACAATTTTCCCTTCCTAAGCACGTTGGATGCTCAGGACCCATGATAACAG
rs16959007ACGTTGGATGAGAACGAAAGCCTCTGCTACACGTTGGATGCCCACTTCACTAGTTCATGG
rs11668308ACGTTGGATGTGAGAAGGGTCAGATGGTAGACGTTGGATGATGACCTGATCCTGTCTGTG
rs6957ACGTTGGATGAGCTAGACTCCAGGACCTTGACGTTGGATGTACAGGCAGGTAAGAGACAG
rs11880564ACGTTGGATGGTGTCTCCTGTCCGTCCTGACGTTGGATGTTGCTTTGGCAGGACGCATG
rs12985162ACGTTGGATGCCTTGTTTTTCCCATGCCTCACGTTGGATGGAACAGAGATGGAGAATGGC
rs10426316ACGTTGGATGTCTCCTCACTTTGCCCTTTCACGTTGGATGTGTGGGAGACAGAGGAGATG
rs8179181ACGTTGGATGAGTTCTTCTCCGTGGAGCTGACGTTGGATGGGCATCTGGCTTCTATGGTG
rs11466345ACGTTGGATGACTCCTGACCTCAAGTGATCACGTTGGATGAAAGTCCTAAGAGAGGCCAG
rs1800472ACGTTGGATGAGCAATAGTTGGTGTCCAGGACGTTGGATGACCATTCATGGCATGAACCG
rs2241715ACGTTGGATGTTGGAGGGTGATGCAGAGAGACGTTGGATGCTCCGACTATTTTCTCTCCC
rs12462166ACGTTGGATGACCAGACCTGCCCCGTCTCACGTTGGATGCTTCCCTTTCCTTCCCATGC
rs1800469ACGTTGGATGAACAAGGTAGGAGAAGAGGGACGTTGGATGTTCTTACAGGTGTCTGCCTC
rs1800468ACGTTGGATGATCACTGGGTGTCCGGGGTACGTTGGATGTCCGCAACTTCGACCGCTAC
rs11668109ACGTTGGATGACAGGTCTTGGTGTTCCCAGACGTTGGATGAGGTCTTCAAGGTGGGTATC
rs1982072ACGTTGGATGCATAGTGAGCACGGGATAAGACGTTGGATGCCCCATCTTAATCCTTGGAC
rs2241714ACGTTGGATGGAGGCTACTTTCCGAGAAACACGTTGGATGTATTTTTCCCCTCCCAGGGC
rs2241713ACGTTGGATGAGTTTCCCCCCCGTCAAATGACGTTGGATGATCACGTGCACCTCAGCCAT
rs2241712ACGTTGGATGTCGGACCTGAACTCATAACGACGTTGGATGAGCGCAAAAGACCCGCCTTC
rs9797885ACGTTGGATGAGGAGCATCACTTGAACCTGACGTTGGATGAGTAGAAGTCTGGCTCTGTC
rs8106934ACGTTGGATGTGGACTTCCTGCACTCAAGGACGTTGGATGGGTTTTGCCATGTATGGCCG
rs1046909ACGTTGGATGGCTTCCTGAACCCTCGCAATACGTTGGATGTAGAGCAAAGCGCAAGGTCC
TABLE 3
SNP_IDextension primer
rs338600GGGCAGGTTCCTGGTAGAGGG
rs338593CTCTGGTTGGGTTCAGC
rs338585CCCTTCCCACCCCAGTC
rs338584CTTACTGTTGGCTCCTCCAC
rs4802112AAAAACAGTCAAGACACAAT
rs168109TTGCCACCTCCTAGCTG
rs2271546GGGTCAGAGGACATGTGG
rs4803448TGCCCAGGAATGCTCATAAGTACA
rs4803449AGACACAACCCCTGC
rs4802113GTGTGCCATTCCTCGGG
rs2304234CAGAGAGCTGGATCCAAGGC
rs2304232CAGCAAGAGCGATGTGGTAGGTGC
rs1946612GAGGACCTGGTCACAAATACA
rs3760660ACGCCTGTTTGTTTACG
rs2304230ACCTGCAGATGCCTTCTGGA
rs8103839GTTGACAATTTCTGAGGATACC
rs3745295AGGACTATGGTCATGAAACAACT
rs8105901GACATACCTAACTTTTCCTT
rs12327659GTGAGCTATCACTGCAA
rs3752705GGAATATGATTGCCAACTCT
rs2053086GCTGCACACACAAGGAC
rs11879562CTTCTTTGACTCCATTCCTAAAA
rs7248164AGAGTAAGATCAAAAAAGAAATCA
rs11881953TCTCCTGCCTCAGCCTCCC
rs7245398GGGCACTGGCTTTCCAAGAA
rs15052AGAGGAGGCAGTGGGAG
rs1865053CCTTGTTTTTGTTGCCC
rs8109627CAATCTGAAATGCCACTTCT
rs8109167AGCCTTCTGAACAAGACACAC
rs1865052CAGTCACAGCCTATGGTGCT
rs1865051ATGCAGGACAATGCAGCAGA
rs16958994CCTGCCCATGGACCTGT
rs16958996ATACACAGGAAGATAGAGGC
rs16958999CATGCAGGCACCTGAGGTCA
rs3826714TGAGGGCCAGTAGCAGG
rs7257310AGCCATGGTCACCAGAGCCTC
rs2241720TCTGGGTTTTGATCCCC
rs2241719CTCCGCCTTCCTCTCCC
rs2241718TTACACTCCCCAAATGC
rs16959007TTCTGTCCTCTGTCAGGCCC
rs11668308GCGGGCCTAACAAGGGCTCC
rs6957AGGACCTTGGGGTCATA
rs11880564GCTCGCTGGCCTGGCCG
rs12985162CCCACCTTTTCCACTCC
rs10426316GCTGCTGTGTGTCTTGGCCC
rs8179181GCTGCAGGCAGGAGAGACGC
rs11466345AGTGCTGGGATTACGGG
rs1800472GGGCCCTCTCCAGCGGG
rs2241715CAGAGACGGAGACGAGGCAAC
rs12462166CTCCGCGAGCGATCCCCGCC
rs1800469AGGGGGCAACAGGACACCTGA
rs1800468CGGGGTGTGGATGGTGGTGA
rs11668109CCCCTCCCCTCAGCCTGG
rs1982072ACGATTCTCACCCCATATTT
rs2241714TCCGAGAAACCGCTGGCCCC
rs2241713CCCCGTCAAATGGAGATAATACA
rs2241712GGGAAGCGGGGTGGCTG
rs9797885TTGCAGTGAGCCGAGATC
rs8106934GCACTCAAGGCATCCTC
rs1046909ACCCTCGCAATGACACT
TABLE 4
position−log 10
Polymorphismgeneon Chr. 19(p-value)maf
rs338600CYP2S1463921830.1530.270
rs338593CYP2S1463961440.3190.477
rs338585CYP2S1464036550.7200.421
rs338584CYP2S1464039530.4360.227
rs168109CYP2S1464081110.0480.495
rs2271546AXL464190371.1090.125
rs4803448AXL464264000.4010.459
rs4802113AXL464327350.5580.449
rs2304234AXL464405930.2620.412
rs3760660HNRPUL1464608650.5010.148
rs2304230HNRPUL1464659041.1660.155
rs8103839HNRPUL1464733330.8970.153
rs3745295HNRPUL1464771220.9830.156
rs8105901HNRPUL1464839321.0980.154
rs12327659HNRPUL1464883121.2610.155
rs3752705HNRPUL1464899511.1420.156
rs2053086HNRPUL1464913150.8090.154
rs11879562HNRPUL1464968161.1820.156
rs7248164HNRPUL1464995401.2210.156
rs11881953HNRPUL1465000891.3940.163
rs7245398HNRPUL1465024841.3810.174
rs15052HNRPUL1465052150.0070.150
rs1865053HNRPUL1465062521.1940.190
rs8109627MGC20255465148260.9300.264
rs8109167MGC20255465150071.4480.173
rs1865052MGC20255465163071.4880.174
rs1865051MGC20255465167251.2960.175
rs16958994MGC20255465168211.4800.174
rs16958996MGC20255465169781.0500.173
rs16958999MGC20255465170261.5910.196
rs3826714MGC20255465176161.6860.174
rs7257310MGC20255465189601.6400.175
rs2241720MGC20255465211491.5840.171
rs2241719MGC20255465214211.7270.172
rs2241718MGC20255465214461.4980.173
rs16959007MGC20255465219760.0030.002
rs11668308MGC20255465222760.3960.003
rs6957MGC20255465224461.5590.174
rs11880564MGC20255465230361.7270.172
rs12985162MGC20255465233471.2760.170
rs10426316MGC20255465234890.2890.001
rs8179181TGFB1465300460.2600.249
rs11466345TGFB1465353010.4820.093
rs1800472TGFB1465397000.5350.032
rs2241715TGFB1465487260.5450.323
rs12462166TGFB1465492440.6420.327
rs1800469TGFB1465521360.7870.324
rs1800468MGC4093465524270.8380.075
rs11668109MGC4093465556170.4910.318
rs1982072MGC4093465563490.5340.317
rs2241714MGC4093465612320.3950.324
rs2241713MGC4093465613080.1620.389
rs2241712MGC4093465615960.3040.321
rs9797885MGC4093465648410.6670.449
rs8106934MGC4093465671590.4100.061
rs1046909MGC4093465745520.2200.332
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IPC · International Patent Classification
Section C — Chemistry; metallurgy
  • C07H21/04
USPC · US Patent Classification
435/6.1536/23.1435/91.1435/6.11536/24.3435/91.2

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