Patent Application
20220260594
The present invention relates to multiple sclerosis (MS) and methods for diagnosing the same.
Multiple sclerosis (MS) is the most common cause of progressive disability in the Western world. MS can be divided into several subtypes: Relapsing-Remitting MS (RRMS), Secondary-Progressive MS (SPMS), and Primary-Progressive MS (PPMS). RRMS is defined by discrete and temporary periods of disability worsening/disease flare-up (relapses) followed by recovery or periods with no disability worsening or disease activity (remission). RRMS is the most common type of MS, affecting ˜85% of MS patients. The majority of RRMS patients will eventually proceed to develop SPMS. SPMS diagnosis, by definition, must follow an RRMS diagnosis. This type of MS is characterised by continued accrual of disability and progressive worsening of symptoms over time, typically with no more discrete relapses. PPMS is the rarest type of MS, affecting ˜10% of patients. In PPMS, the patient never has a relapsing/remitting phase and enters the progressive phase from onset.
MS presents with an initial neurological attack, termed clinically isolated syndrome (CIS). Some patients who experience CIS will not convert to clinically definite MS (CDMS) (non-convertors), and, for those who do (convertors), time to conversion varies. The McDonald criteria is typically used to diagnose MS (e.g. RRMS) in the clinic and uses brain MRI in an attempt at early diagnosis (at the point of CIS) without the need for waiting for a second attack (indicative of true CDMS). The McDonald criteria is reviewed every few years, with the most recent criteria summarised in Lancet Neurol. 2018 February; 17(2):162-173. doi: 10.1016/S1474-4422(17)30470-2. Previous diagnostic criteria can be found at: 2010 Diagnostic Criteria: Ann Neurol. 2011 February; 69(2):292-302; and 2001 (original) diagnostic criteria: Ann Neurol. 2001 July; 50(1):121-7).
While the revised McDonald criteria aims to diagnose MS early using a combination of clinical and radiological data along with the presence of oligoclonal bands (OCB), it is associated with a number of disadvantages. First, 27% of CDMS patients do not fulfil McDonald MRI criteria at the point of CIS. Secondly, 50% of patients who do fulfil McDonald MRI criteria never have a second attack and never convert to CDMS (potentially incorrectly diagnosed/treated). Thirdly, there is no prognostic measure that is able to identify fast converters. Indeed, only 59% of OCB positive CIS patients convert to CDMS within 4 years.
There is thus a need for an improved method of diagnosing MS, and, in particular, an improved method for determining conversion of a subject from CIS to CDMS.
The present invention provides a solution to at least one of the problems described above.
The present inventors have surprisingly found that a method comprising measuring a concentration of one or more polypeptides described herein and/or one or more metabolites described herein in a sample from a subject allows for an improved method of diagnosing MS.
The methods of the invention allow for improved diagnosis of MS per se, CIS, and/or CDMS, as well as determining prognosis of MS. In particular, the methods of the invention allow determination of conversion of a subject from CIS to CDMS (e.g. within 4 years). Advantageously, the methods of the invention are particularly accurate and/or sensitive and/or specific.
Thus, in one aspect the invention provides a method for determining conversion of a subject from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), the method comprising:
In one embodiment the invention provides a method for determining conversion of a subject from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), the method comprising:
In another embodiment the invention provides a method for determining conversion of a subject from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), the method comprising:
“CIS” may refer to a first episode of neurologic symptoms that lasts for at least 24 hours and that is caused by inflammation and/or demyelination in the brain of the subject. Preferably, said symptom is one that is suggestive of MS with no other clinically-reasonable explanation. “CIS” is preferably associated with a brain lesion.
“CDMS” may refer to the stage at which at least one further episode of neurological symptoms have occurred in a subject. Preferably, CDMS is diagnosed when other possible diagnoses have been ruled out. “CDMS” may be associated with at least a further brain lesion when compared to CIS.
The methods of the invention preferably allow for a determination of the rate of conversion of a subject from CIS to CDMS. In one embodiment, a method of the invention determines whether or not a subject will convert from CIS to CDMS within a period of 10 years from CIS occurring. In another embodiment a method of the invention determines whether or not a subject will convert from CIS to CDMS within a period of 5 years from CIS occurring. Preferably, a method of the invention determines whether or not a subject will convert from CIS to CDMS within a period of 4 years from CIS occurring.
By using the methods of the invention, the convertor status of a subject can be determined. Advantageously, said status can be used to determine a suitable therapeutic strategy for the subject. For example, if the subject is identified as being a convertor to CDMS (e.g. a rapid convertor) early therapeutic intervention can be employed, which may, ultimately, delay conversion to CDMS. Thus, in one aspect the invention may comprise administering a suitable therapeutic to a subject: determined to be a convertor (e.g. a rapid convertor), diagnosed as having MS, and/or determined to have a poor prognosis in accordance with a method of the invention. In one embodiment the invention may comprise administering to the subject predicted to be a convertor a suitable therapeutic that delays conversion.
In one aspect the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one aspect the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one aspect the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a therapeutic for use in a method of treating MS in a subject, said method comprising:
In one aspect the invention provides a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a method of treating MS in a subject, said method comprising:
In one aspect the invention provides a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a method of treating MS in a subject, said method comprising:
In one aspect the invention provides a method of treating MS in a subject, said method comprising:
In one embodiment the invention provides a method of treating MS in a subject, said method comprising:
In one aspect, the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
In one embodiment the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
In one aspect the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
In one embodiment the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
In one aspect the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
In one embodiment the invention provides use of a therapeutic in the manufacture of a medicament for treating MS, comprising:
A “rapid convertor” (used synonymously with “fast convertor” herein) may be a subject who converts from CIS to CDMS within 10 years of CIS occurring. In one embodiment a “rapid convertor” is a subject who converts from CIS to CDMS within 5 years of CIS occurring. Preferably, a “rapid convertor” is a subject who converts from CIS to CDMS within 4 years of CIS occurring.
A “slow convertor” may be a subject who converts from CIS to CDMS in more than 10 years of CIS occurring. In one embodiment a “slow convertor” is a subject who converts from CIS to CDMS in more than 5 years of CIS occurring. Preferably, a “slow convertor” is a subject who converts from CIS to CDMS in more than 4 years of CIS occurring.
The methods of the invention may allow the determination of whether a subject is a “rapid convertor” or a “slow convertor”. In one embodiment, where a method is a method for determining conversion of a subject from CIS to CDMS and where it has been determined that the subject will convert from CIS to CDMS, preferably this means that the subject is a fast convertor. In contrast, in one embodiment, where a method is a method for determining conversion of a subject from CIS to CDMS and where it has been determined that the subject will not convert from CIS to CDMS, preferably this means that the subject is a slow convertor or a non-convertor.
In one aspect the invention provides a method for diagnosing multiple sclerosis (MS), the method comprising:
In one aspect there is provided a method for diagnosing Multiple Sclerosis (MS) in a (preferably human) test subject, the method comprising:
In one aspect the invention provides a method for diagnosing relapsing-remitting multiple sclerosis (RRMS), the method comprising:
In a related aspect the invention provides a method for determining prognosis of multiple sclerosis (MS), the method comprising:
In one aspect the invention provides a method, the method comprising:
In one aspect the invention provides a method for diagnosing multiple sclerosis (MS), the method comprising:
In a related aspect the invention provides a method for determining prognosis of multiple sclerosis (MS), the method comprising:
In one aspect the invention provides a method for predicting whether a subject will convert from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), the method comprising:
In one aspect the invention provides a method for diagnosing MS, the method comprising:
In one aspect, the invention provides a method for predicting prognosis of MS, the method comprising:
In one embodiment the invention provides a method for diagnosing multiple sclerosis (MS), the method comprising:
In one embodiment the invention provides a method for diagnosing multiple sclerosis (MS), the method comprising:
In one embodiment the invention provides a method, the method comprising:
In a related aspect the invention provides a method for determining prognosis of multiple sclerosis (MS), the method comprising:
In a related aspect the invention provides a method for determining prognosis of multiple sclerosis (MS), the method comprising:
Preferably, a method of the invention allows for the diagnosis of MS, such as RRMS and/or CDMS.
The present invention may comprise detecting one or more polypeptides described herein (e.g. in Table 1). Thus, in one embodiment a polypeptide is one or more selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytosolic acyl coenzyme A thioester hydrolase, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Rho guanine nucleotide exchange factor 2, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, RING finger protein 165, Natural cytotoxicity triggering receptor 1, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Interleukin-5 receptor subunit alpha, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Protein NOV homolog, Mitotic-spindle organizing protein 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Carbonyl reductase [NADPH] 1, Epididymal-specific lipocalin-10, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, ETS domain-containing protein Elk-1, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Beclin-1, Inositol polyphosphate 5-phosphatase OCRL-1, Dynein light chain Tctex-type 1, Thrombospondin-2, C—C motif chemokine 17, Dorsal root ganglia homeobox protein, Proenkephalin-A, T-lymphocyte surface antigen Ly-9, Muscle, skeletal receptor tyrosine-protein kinase, Myeloid zinc finger 1, Protein DGCR6, Tumor necrosis factor receptor superfamily member EDAR, Protocadherin alpha-7, High affinity immunoglobulin gamma Fc receptor I, CD40 ligand, Dickkopf-related protein 2, Growth-regulated alpha protein, Metalloproteinase inhibitor 2, Brother of CDO, BRISC complex subunit Abro1, Endoplasmic reticulum resident protein 44, Clumping factor B, Collagenase 3, Prokineticin-2, Peptidyl-prolyl cis-trans isomerase-like 2, Interleukin-22 receptor subunit alpha-2, Beta-sarcoglycan, Transmembrane glycoprotein NMB, Tumor necrosis factor receptor superfamily member 11B, Microfibril-associated glycoprotein 4, Collagen alpha-2(VI) chain, RNA polymerase II elongation factor ELL2, EF-hand calcium-binding domain-containing protein 14, Essential MCU regulator (mitochondrial), Importin subunit alpha-1, Leucine-rich repeat-containing protein 3, V-set and immunoglobulin domain-containing protein 2, Serine protease inhibitor Kazal-type 13, Insulin-like growth factor-binding protein 1, Beta-defensin 123, Spermatogenesis-associated protein 9, Heterogeneous nuclear ribonucleoprotein K, Drebrin-like protein, Desert hedgehog protein N-product, Inhibin beta A chain:Inhibin beta B chain heterodimer, Retinoic acid receptor responder protein 2, Lutropin-choriogonadotropic hormone receptor, Thrombospondin-4, Glial fibrillary acidic protein, and Allergin-1.
Representative sequences for the polypeptides for use in the invention are described in the Sequence Listing herein, together with the appropriate UniProt Accession numbers. A polypeptide for use in the invention may be one or more shown as SEQ ID NOs: 1-91 or a variant thereof, such as a transcript isoform therefore. A polypeptide for use in a method of the invention may comprise (or consist of) a polypeptide sequence having at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99% or 100% sequence identity to any one of SEQ ID NOs: 1-91. Thus, in one embodiment, the invention comprises measuring the concentration of one or more polypeptides having at least 20% sequence identity to any one of SEQ ID NOs: 1-91. In one embodiment, the invention comprises measuring the concentration of one or more polypeptides having at least 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99% or 100% sequence identity to any one of SEQ ID NOs: 1-91. In one embodiment, the invention comprises measuring the concentration of one or more polypeptides having at least 70% (preferably at least 80%, 90%, or 95%, more preferably 100%) sequence identity to any one of SEQ ID NOs: 1-91.
In one embodiment a polypeptide is one or more selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytosolic acyl coenzyme A thioester hydrolase, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Rho guanine nucleotide exchange factor 2, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, RING finger protein 165, Natural cytotoxicity triggering receptor 1, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Interleukin-5 receptor subunit alpha, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Protein NOV homolog, Mitotic-spindle organizing protein 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Carbonyl reductase [NADPH] 1, Epididymal-specific lipocalin-10, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, ETS domain-containing protein Elk-1, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Beclin-1, Inositol polyphosphate 5-phosphatase OCRL-1, Dynein light chain Tctex-type 1, Thrombospondin-2, C—C motif chemokine 17, Dorsal root ganglia homeobox protein, Proenkephalin-A, T-lymphocyte surface antigen Ly-9, Muscle, skeletal receptor tyrosine-protein kinase, and Myeloid zinc finger 1.
Preferably, at least one polypeptide is selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytosolic acyl coenzyme A thioester hydrolase, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Rho guanine nucleotide exchange factor 2, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, and RING finger protein 165.
More preferably, at least one of the polypeptides is selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytosolic acyl coenzyme A thioester hydrolase, Cytoplasmic tyrosine-protein kinase BMX, and Cathepsin K.
Measuring a concentration of a polypeptide of the invention may be carried out by any means known to the person skilled in the art. For example, the polypeptide concentration can be measured directly (by measuring the amount/concentration of polypeptide itself) or indirectly by assessing gene expression, e.g. at the level of transcription. In one embodiment, mRNA of a target gene can be detected and quantified by e.g. Northern blotting or by quantitative reverse transcription PCR (RT-PCR). In one embodiment, gene expression levels are determined by measuring the mRNA/cDNA levels of the genes of the present invention, such as RNA sequencing (RNA-Seq).
In some embodiments the invention may employ high-throughput techniques. High-throughput techniques can be used to analyse whole genomes, proteomes and transcriptomes rapidly, providing data, including the expression levels, of all of the genes, polypeptides and transcripts in a sample. For example, RNA sequencing (RNA-Seq) may be used. The invention may comprise the use of transcriptomics. Typically, proteomics is carried out by mass-spectrometry, including tandem mass-spectrometry, and gel-based techniques, including differential in-gel electrophoresis.
Preferably, polypeptide concentrations are determined directly by analysing polypeptide amounts in a sample. Suitable techniques may include mass spectrometry, e.g. liquid chromatography and mass spectrometry (LC-MS/MS), enzyme-linked immunosorbent assay (ELISA) or a Luminex assay (commercially available from R&D Systems, USA). More preferably, a polypeptide concentration may be determined using a SOMAscan Assay (SomaLogic, Inc., Boulder, Colo., USA). Directly determining polypeptide concentrations by analysing polypeptide amounts in a sample has advantages over other non-direct techniques, such as nucleic acid-based techniques, e.g. transcriptomics/gene expression analysis. Specifically, directly determining polypeptide concentrations may be more accurate and/or sensitive and/or specific when compared to indirect techniques. For example, nucleic acid-based techniques may not directly correlate to the final polypeptide concentrations. Thus, in one embodiment methods of the invention do not use indirect techniques for determining polypeptide concentrations, for example, methods of the invention may not use nucleic acid-based techniques for determining polypeptide concentrations, such as RNA analysis and/or transcriptomics.
When compared to a non-convertor reference standard the concentration of one or more polypeptides selected from: Cytosolic acyl coenzyme A thioester hydrolase, Rho guanine nucleotide exchange factor 2, RING finger protein 165, Natural cytotoxicity triggering receptor 1, Interleukin-5 receptor subunit alpha, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Epididymal-specific lipocalin-10, ETS domain-containing protein Elk-1, Beclin-1, Dynein light chain Tctex-type 1, C—C motif chemokine 17, T-lymphocyte surface antigen Ly-9, Myeloid zinc finger 1, Protein DGCR6, Growth-regulated alpha protein, Clumping factor B, Peptidyl-prolyl cis-trans isomerase-like 2, Interleukin-22 receptor subunit alpha-2, Beta-sarcoglycan, Transmembrane glycoprotein NMB, Collagen alpha-2(VI) chain, Beta-defensin 123, and Glial fibrillary acidic protein may be increased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the concentration of one or more polypeptides selected from: Cytosolic acyl coenzyme A thioester hydrolase, Rho guanine nucleotide exchange factor 2, RING finger protein 165, Natural cytotoxicity triggering receptor 1, Interleukin-5 receptor subunit alpha, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Epididymal-specific lipocalin-10, ETS domain-containing protein Elk-1, Beclin-1, Dynein light chain Tctex-type 1, C—C motif chemokine 17, T-lymphocyte surface antigen Ly-9, Myeloid zinc finger 1, Protein DGCR6, Growth-regulated alpha protein, Clumping factor B, Peptidyl-prolyl cis-trans isomerase-like 2, Interleukin-22 receptor subunit alpha-2, Beta-sarcoglycan, Transmembrane glycoprotein NMB, Collagen alpha-2(VI) chain, Beta-defensin 123, and Glial fibrillary acidic protein may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a non-convertor reference standard the concentration of one or more polypeptides selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Protein NOV homolog, Mitotic-spindle organizing protein 1, Carbonyl reductase [NADPH] 1, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Inositol polyphosphate 5-phosphatase OCRL-1, Thrombospondin-2, Dorsal root ganglia homeobox protein, Proenkephalin-A, Muscle, skeletal receptor tyrosine-protein kinase, Tumor necrosis factor receptor superfamily member EDAR, Protocadherin alpha-7, High affinity immunoglobulin gamma Fc receptor I, CD40 ligand, Dickkopf-related protein 2, Metalloproteinase inhibitor 2, Brother of CDO, BRISC complex subunit Abro1, Endoplasmic reticulum resident protein 44, Collagenase 3, Prokineticin-2, Tumor necrosis factor receptor superfamily member 11B, Microfibril-associated glycoprotein 4, RNA polymerase II elongation factor ELL2, EF-hand calcium-binding domain-containing protein 14, Essential MCU regulator (mitochondrial), Importin subunit alpha-1, Leucine-rich repeat-containing protein 3, V-set and immunoglobulin domain-containing protein 2, Serine protease inhibitor Kazal-type 13, Insulin-like growth factor-binding protein 1, Spermatogenesis-associated protein 9, Heterogeneous nuclear ribonucleoprotein K, Drebrin-like protein, Desert hedgehog protein N-product, Inhibin beta A chain:Inhibin beta B chain heterodimer, Retinoic acid receptor responder protein 2, Lutropin-choriogonadotropic hormone receptor, Thrombospondin-4, and Allergin-1 may be decreased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the concentration of one or more polypeptides selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Protein NOV homolog, Mitotic-spindle organizing protein 1, Carbonyl reductase [NADPH] 1, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Inositol polyphosphate 5-phosphatase OCRL-1, Thrombospondin-2, Dorsal root ganglia homeobox protein, Proenkephalin-A, Muscle, skeletal receptor tyrosine-protein kinase, Tumor necrosis factor receptor superfamily member EDAR, Protocadherin alpha-7, High affinity immunoglobulin gamma Fc receptor I, CD40 ligand, Dickkopf-related protein 2, Metalloproteinase inhibitor 2, Brother of CDO, BRISC complex subunit Abro1, Endoplasmic reticulum resident protein 44, Collagenase 3, Prokineticin-2, Tumor necrosis factor receptor superfamily member 11B, Microfibril-associated glycoprotein 4, RNA polymerase II elongation factor ELL2, EF-hand calcium-binding domain-containing protein 14, Essential MCU regulator (mitochondrial), Importin subunit alpha-1, Leucine-rich repeat-containing protein 3, V-set and immunoglobulin domain-containing protein 2, Serine protease inhibitor Kazal-type 13, Insulin-like growth factor-binding protein 1, Spermatogenesis-associated protein 9, Heterogeneous nuclear ribonucleoprotein K, Drebrin-like protein, Desert hedgehog protein N-product, Inhibin beta A chain:Inhibin beta B chain heterodimer, Retinoic acid receptor responder protein 2, Lutropin-choriogonadotropic hormone receptor, Thrombospondin-4, and Allergin-1 may be increased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the concentration of one or more polypeptides selected from: Cytosolic acyl coenzyme A thioester hydrolase, Rho guanine nucleotide exchange factor 2, RING finger protein 165, Natural cytotoxicity triggering receptor 1, Interleukin-5 receptor subunit alpha, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Epididymal-specific lipocalin-10, ETS domain-containing protein Elk-1, Beclin-1, Dynein light chain Tctex-type 1, C—C motif chemokine 17, T-lymphocyte surface antigen Ly-9, Myeloid zinc finger 1, Protein DGCR6, Growth-regulated alpha protein, Clumping factor B, Peptidyl-prolyl cis-trans isomerase-like 2, Interleukin-22 receptor subunit alpha-2, Beta-sarcoglycan, Transmembrane glycoprotein NMB, Collagen alpha-2(VI) chain, Beta-defensin 123, and Glial fibrillary acidic protein may be increased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the concentration of one or more polypeptides selected from: Cytosolic acyl coenzyme A thioester hydrolase, Rho guanine nucleotide exchange factor 2, RING finger protein 165, Natural cytotoxicity triggering receptor 1, Interleukin-5 receptor subunit alpha, Lymphotoxin alpha2:beta1, Mitochondrial antiviral-signaling protein, GTP cyclohydrolase 1, Guanine nucleotide exchange factor DBS, Vascular cell adhesion protein 1, Epididymal-specific lipocalin-10, ETS domain-containing protein Elk-1, Beclin-1, Dynein light chain Tctex-type 1, C—C motif chemokine 17, T-lymphocyte surface antigen Ly-9, Myeloid zinc finger 1, Protein DGCR6, Growth-regulated alpha protein, Clumping factor B, Peptidyl-prolyl cis-trans isomerase-like 2, Interleukin-22 receptor subunit alpha-2, Beta-sarcoglycan, Transmembrane glycoprotein NMB, Collagen alpha-2(VI) chain, Beta-defensin 123, and Glial fibrillary acidic protein may be decreased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the concentration of one or more polypeptides selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Protein NOV homolog, Mitotic-spindle organizing protein 1, Carbonyl reductase [NADPH] 1, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Inositol polyphosphate 5-phosphatase OCRL-1, Thrombospondin-2, Dorsal root ganglia homeobox protein, Proenkephalin-A, Muscle, skeletal receptor tyrosine-protein kinase, Tumor necrosis factor receptor superfamily member EDAR, Protocadherin alpha-7, High affinity immunoglobulin gamma Fc receptor I, CD40 ligand, Dickkopf-related protein 2, Metalloproteinase inhibitor 2, Brother of CDO, BRISC complex subunit Abro1, Endoplasmic reticulum resident protein 44, Collagenase 3, Prokineticin-2, Tumor necrosis factor receptor superfamily member 11B, Microfibril-associated glycoprotein 4, RNA polymerase II elongation factor ELL2, EF-hand calcium-binding domain-containing protein 14, Essential MCU regulator (mitochondrial), Importin subunit alpha-1, Leucine-rich repeat-containing protein 3, V-set and immunoglobulin domain-containing protein 2, Serine protease inhibitor Kazal-type 13, Insulin-like growth factor-binding protein 1, Spermatogenesis-associated protein 9, Heterogeneous nuclear ribonucleoprotein K, Drebrin-like protein, Desert hedgehog protein N-product, Inhibin beta A chain:Inhibin beta B chain heterodimer, Retinoic acid receptor responder protein 2, Lutropin-choriogonadotropic hormone receptor, Thrombospondin-4, and Allergin-1 may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the concentration of one or more polypeptides selected from: Ribosomal protein S6 kinase alpha-5, DNA repair protein XRCC1, Cytoplasmic tyrosine-protein kinase BMX, Cathepsin K, Tropomyosin alpha-3 chain, Pleckstrin homology domain-containing family A member 1, Calcium uptake protein 2, mitochondrial, AP-1 complex subunit gamma-like 2, Prostaglandin reductase 1, Testis-specific serine/threonine-protein kinase 2, Tyrosine-protein kinase BLK, Protein NOV homolog, Mitotic-spindle organizing protein 1, Carbonyl reductase [NADPH] 1, Coiled-coil domain-containing protein 80, Grancalcin, Polypeptide N-acetylgalactosaminyltransferase 16, Complement factor H, Interleukin-32, RAF proto-oncogene serine/threonine-protein kinase, D-glucuronyl C5-epimerase, Proteasomal ubiquitin receptor ADRM1, Nuclear receptor subfamily 1 group D member 2, Beta-crystallin B2, Zinc finger protein 41, Guanylyl cyclase-activating protein 1, Interferon regulatory factor 1, Inositol polyphosphate 5-phosphatase OCRL-1, Thrombospondin-2, Dorsal root ganglia homeobox protein, Proenkephalin-A, Muscle, skeletal receptor tyrosine-protein kinase, Tumor necrosis factor receptor superfamily member EDAR, Protocadherin alpha-7, High affinity immunoglobulin gamma Fc receptor I, CD40 ligand, Dickkopf-related protein 2, Metalloproteinase inhibitor 2, Brother of CDO, BRISC complex subunit Abro1, Endoplasmic reticulum resident protein 44, Collagenase 3, Prokineticin-2, Tumor necrosis factor receptor superfamily member 11B, Microfibril-associated glycoprotein 4, RNA polymerase II elongation factor ELL2, EF-hand calcium-binding domain-containing protein 14, Essential MCU regulator (mitochondrial), Importin subunit alpha-1, Leucine-rich repeat-containing protein 3, V-set and immunoglobulin domain-containing protein 2, Serine protease inhibitor Kazal-type 13, Insulin-like growth factor-binding protein 1, Spermatogenesis-associated protein 9, Heterogeneous nuclear ribonucleoprotein K, Drebrin-like protein, Desert hedgehog protein N-product, Inhibin beta A chain:Inhibin beta B chain heterodimer, Retinoic acid receptor responder protein 2, Lutropin-choriogonadotropic hormone receptor, Thrombospondin-4, and Allergin-1 may be increased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
The present invention may comprise detecting one or more metabolites described herein (e.g. in Table 2 or 3). Relevant NMR resonance values in for said metabolites are provided in Tables 2 and 3. Thus, in one embodiment a metabolite may be one or more selected from: creatinine, creatine, mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), isoleucine, leucine, mobile lipoprotein —CH3 resonances (HDL and LDL), betaine, mobile —N(CH3)3/free choline, formate, 3-hydroxybutyrate, myo-inositol, NAC1/=CH—CH2-CH2-, glucose, glutamine, and lactate.
In some embodiments the metabolites may be one or more cerebrospinal fluid metabolites selected from: creatinine, creatine, isoleucine, leucine, betaine, formate, myo-inositol, glucose, glutamine, and lactate.
In another embodiment the metabolites may be one or more serum metabolites selected from: mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), glucose, mobile lipoprotein —CH3 resonances (HDL and LDL), mobile —N(CH3)3/free choline, 3-hydroxybutyrate, and NAC1/=CH—CH2-CH2-.
When compared to a non-convertor reference standard the concentration of one or more metabolites selected from: mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), mobile lipoprotein —CH3 resonances (HDL and LDL), mobile —N(CH3)3/free choline, formate, glucose (CSF), NAC1/=CH—CH2-CH2-, and lactate may be increased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the concentration of one or more metabolites selected from: mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), mobile lipoprotein —CH3 resonances (HDL and LDL), mobile —N(CH3)3/free choline, formate, glucose (CSF), NAC1/=CH—CH2-CH2-, and lactate may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a non-convertor reference standard the concentration of one or more metabolites selected from: creatinine, creatine, isoleucine, leucine, betaine, 3-hydroxybutyrate, myo-inositol, glucose (serum), and glutamine may be decreased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the concentration of one or more metabolites selected from: creatinine, creatine, isoleucine, leucine, betaine, 3-hydroxybutyrate, myo-inositol, glucose (serum), and glutamine may be increased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the concentration of one or more metabolites selected from: mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), mobile lipoprotein —CH3 resonances (HDL and LDL), mobile —N(CH3)3/free choline, formate, glucose (CSF), NAC1/=CH—CH2-CH2-, and lactate may be increased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the concentration of one or more metabolites selected from: mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), mobile lipoprotein —CH3 resonances (HDL and LDL), mobile —N(CH3)3/free choline, formate, glucose (CSF), NAC1/=CH—CH2-CH2-, and lactate may be decreased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the concentration of one or more metabolites selected from: creatinine, creatine, isoleucine, leucine, betaine, 3-hydroxybutyrate, myo-inositol, glucose (serum), and glutamine may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the concentration of one or more metabolites selected from: creatinine, creatine, isoleucine, leucine, betaine, 3-hydroxybutyrate, myo-inositol, glucose (serum), and glutamine may be increased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
Preferably, one or more metabolites and one or more polypeptides may be used in a method of the invention.
The concentrations of the metabolites in a sample can be measured using any suitable technique known in the art. By way of example, the following techniques may be used to detect and quantify small molecules in solution, and are thus suitable for determining metabolite concentrations: Nuclear Magnetic Resonance (NMR) spectroscopy, mass spectrometry, gas chromatography, ultraviolet (UV) spectrometry (for example in combination with high-performance liquid chromatography [HPLC] as HPLC-UV), and infrared spectroscopy. A metabolite is preferably identified using NMR, more preferably 1H-NMR.
In one embodiment, the concentration of one or more metabolites is determined using NMR spectroscopy. In one embodiment, the concentration of one or more metabolites is determined using mass spectrometry. In one embodiment, the concentration of one or more metabolites is determined using HPLC-UV. In one embodiment, the concentration of one or more metabolites is determined using infrared spectroscopy.
The concentration of a polypeptide and/or metabolite in a sample can be expressed in a number of different ways, for example as a molar concentration (number of moles of polypeptide/metabolite per unit volume of sample) or a mass concentration (mass of polypeptide/metabolite per unit volume of sample). Alternatively, the concentration of a polypeptide/metabolite can be expressed as parts per million (ppm) or parts per billion (ppb). Such ways of expressing the concentration of a small molecule in solution are known in the art. In some embodiments a concentration of a polypeptide and/or metabolite may be expressed relative to a standard or to another polypeptide and/or metabolite within the sample. For example, when techniques such as NMR are employed a concentration may be expressed as a relative spectral intensity.
Thus, in one embodiment, the concentration of a polypeptide/metabolite in a sample is the molar concentration of said polypeptide/metabolite. In one embodiment, the concentration of a polypeptide/metabolite in a sample is the mass concentration of said polypeptide/metabolite.
The concentration of a polypeptide/metabolite in a sample may be expressed in absolute terms, for example as absolute molar concentration or absolute mass concentration. Alternatively, the concentration of a polypeptide/metabolite in a sample can be expressed by comparison to the concentration of a different polypeptide/metabolite in the same sample (i.e. in relative terms). By way of example, the concentration of a polypeptide/metabolite in the sample can be normalised by comparison to the concentration of a different reference polypeptide/metabolite within the same sample.
The methods described herein are particularly sensitive and allow for accurate and/or sensitive and/or specific determination, diagnosis and/or prognosis when using only one polypeptide. Notably, even where the concentration of a polypeptide has not been found to be statistically-significantly changed when compared to a reference standard, said polypeptide has utility in a method of the invention, especially where used in combination with a further polypeptide and/or metabolite and/or when compared to multiple reference standards.
In some embodiments more than one polypeptide may be employed. In a preferred embodiment at least 5 polypeptides are employed in a method described herein.
The term “one or more” when used in the context of a polypeptide described herein may mean at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90 or 91 of the polypeptides. In one embodiment the term “one or more” when used in the context of a polypeptide described herein may mean at least 50 of the polypeptides. When carrying out a method herein, it is preferred that those polypeptides that are highest ranked in Table 1 are selected, e.g. where 5 polypeptides are employed, it is preferred that these are the 5 highest ranking polypeptides.
Similarly, the methods described herein are particularly sensitive and allow for accurate and/or sensitive and/or specific determination, diagnosis and/or prognosis when using only one metabolite. Notably, even where the concentration of a metabolite has not been found to be statistically-significantly changed when compared to a reference standard, said polypeptide has utility in a method of the invention, especially where used in combination with a further polypeptide and/or metabolite and/or when compared to multiple reference standards.
In some embodiments more than one metabolite may be employed. In a preferred embodiment at least 2 metabolites are employed in a method described herein.
The term “one or more” when used in the context of a metabolite described herein may mean at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 metabolites. When carrying out a method herein, it is preferred that those metabolites that are highest ranked in Table 2 or 3 are selected, e.g. where 2 metabolites are employed, it is preferred that these are the 2 highest ranking metabolites. For example at least one metabolite employed in a method of the invention may be creatinine, creatine, mobile lipoprotein (—CH2-)n resonances (VLDL and LDL), isoleucine or glucose (serum).
Preferably, one or more polypeptides and one or more metabolites may be used in a method of the invention. Advantageously, this allows for improved accuracy/sensitivity and/or specificity when compared to the use of one or more polypeptide or one or more metabolite only.
In one embodiment, a method of the invention has an accuracy of at least 65%, 70%, 71%, 72%, 73%, 74%, or 75%. Preferably, a method of the invention has an accuracy of at least 80 or 85%, such as at least 90%.
In some embodiments a method of the invention may further comprise determining a subject's oligoclonal band status (i.e. positive or negative). Additionally or alternatively, a method of the invention may further comprise measuring in a sample obtained from a subject: leukocyte concentration, mononuclear cell concentration (e.g. peripheral blood mononuclear cell [PBMC] concentrations), polynuclear cell concentration (e.g. polynuclear neutrophil concentrations), serum albumin ratio (e.g. CSF/serum albumin ratios), and total protein concentration (e.g. CSF total protein concentration).
When compared to a non-convertor reference standard the concentration of leukocytes, mononuclear cells and/or polynuclear cells may be increased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the concentration of leukocytes, mononuclear cells and/or polynuclear cells may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a non-convertor reference standard the CSF/serum albumin ratio and/or total protein (e.g. CSF total protein) may be decreased. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a non-convertor reference standard the CSF/serum albumin ratio and/or total protein (e.g. CSF total protein) may be increased or the same. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the concentration of leukocytes, mononuclear cells and/or polynuclear cells may be increased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the concentration of leukocytes, mononuclear cells and/or polynuclear cells may be decreased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
When compared to a convertor reference standard the CSF/serum albumin ratio and/or total protein (e.g. CSF total protein) may be decreased or the same. In one embodiment, in such cases: it is determined that a subject will convert from CIS to CDMS (preferably, it is determined that a subject will be a rapid convertor to CDMS); and/or a subject is diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is poor.
When compared to a convertor reference standard the CSF/serum albumin ratio and/or total protein (e.g. CSF total protein) may be increased. In one embodiment, in such cases: it is determined that a subject will not convert from CIS to CDMS (or that a subject will be a slow convertor to CDMS); and/or a subject is not diagnosed with MS (e.g. CDMS and/or RRMS); and/or it is determined that a subject's prognosis is good.
The terms “subject” and “patient” are used synonymously herein. The “subject” may be a mammal, and preferably the subject is a human subject.
The sample that is to be tested using the method of the invention can be derived from any suitable biofluid. In one embodiment the biofluid is selected from cerebrospinal fluid (CSF), blood or urine that has been obtained from a subject. Preferably the sample is a CSF sample. Without wishing to be bound by theory, it is believed that any biofluid is suitable for use in the present invention, especially when the method employs the use of one or more metabolites. This has been evidenced by the fact that the majority of polypeptides identified in CSF herein are also present in serum (these biofluid compartments are ‘linked’, as with blood and urine polypeptides/metabolites can pass between the biofluids) and thus it is believed that the same detection methods could also be used in blood, including with the use of alternative blood fractions, such as plasma.
The term blood comprises whole blood, blood serum (henceforth “serum”) and blood plasma (henceforth “plasma”), preferably serum. Serum and plasma are derived from blood and thus may be considered as specific subtypes within the broader genus “blood”. Processes for obtaining serum or plasma from blood are known in the art. For example, it is known in the art that blood can be subjected to centrifugation in order to separate red blood cells, white blood cells, and plasma. Serum is defined as plasma that lacks clotting factors. Serum can be obtained by centrifugation of blood in which the clotting process has been triggered. Optionally, this can be carried out in specialised centrifuge tubes designed for this purpose.
A sample for use in a method of the present invention can be derived from a biofluid that has undergone processing after being obtained from a test subject. Alternatively, a sample can be derived from a biofluid that has not undergone any processing after being obtained from a test subject.
The methods of the invention thus encompass the use of samples that have undergone minimal or zero processing before testing. This provides a significant advantage over prior art methods in terms of time, cost and practicality. By way of example, a CSF sample obtained from a test subject may be tested directly using the method of the present invention, without further processing. Serum and plasma samples can be readily obtained from blood samples using simple and readily available techniques that are well known in the art, as described above.
In a preferred embodiment, the samples for use in a method of the invention are cell-free biofluid samples. In other words, the biofluid sample of the invention may be processed to remove cells. The term “cell-free biofluid samples” are biofluid samples that contain substantially no cells. The term “substantially no” when used in the context of cells herein may mean less than 10,000, 5,000, 1,000, 100 or 10 cells/ml. The term “substantially no” when used in the context of cells herein preferably means less than 1,000 cells/ml, more preferably no cells. In some embodiments the term “substantially no” when used in the context of cells herein may be expressed in absolute amounts. For example, the term “substantially no” when used in the context of cells herein may mean less than 10,000, 5,000, 1,000, 100 or 10 cells. Preferably less than 1,000 cells, more preferably no cells.
At least one advantage associated with the use of cell-free biofluid samples is that the measurement of polypeptides and/or metabolites is not adversely influenced by the populations of different cell types that may be present in an equivalent biofluid sample containing cells. Said populations of different cell types may have different polypeptide expression profiles. Moreover, the cell-free biofluid may not need to be (and is preferably not) subjected to any enrichment steps. Thus, in one embodiment, the cell-free biofluid sample is not enriched for white blood cells, preferably is not enriched for peripheral blood mononuclear cells (PBMCs), T-cells and/or monocytes. Preferably, the cell-free biofluid sample comprises substantially no white blood cells, e.g. substantially no PBMCs, T-cells and/or monocytes.
The methods of the invention comprise comparing a concentration of a polypeptide and/or metabolite to a reference standard. In one embodiment, a reference standard comprises (or consists of) a sample (e.g. a biofluid sample described herein) obtained from a reference subject or subjects, wherein the reference subject is a subject other than the subject being tested in a method of the invention.
In one embodiment, a “reference standard” comprises (or consists of) a set of data relating to the concentration of one or more polypeptides and/or metabolites in a sample obtained from a reference subject or subjects, wherein the reference subject is a subject other than the subject being tested in a method of the invention. The set of data may be derived by measuring the concentration of said one or more polypeptides and/or metabolites. Said measuring may be carried out using any suitable technique described herein.
In one embodiment, the reference standard comprises (or consists of) a set of data relating to the concentration of said one or more polypeptides and/or metabolites in a sample or samples derived from a single reference subject. In other embodiments, the reference standard comprises (or consists of) a set of data relating to the concentration of said one or more polypeptides and/or metabolites in a sample or samples derived from a plurality of reference subjects (e.g. two or more reference subjects). Thus, in one embodiment, the reference standard is derived by pooling data obtained from two or more (e.g. three, four, five, 10, 15, 20 or 25) reference subjects and calculating an average (for example, mean or median) concentration for each polypeptide and/or metabolite. Thus, the reference standard may reflect average concentrations of said one or more polypeptides and/or metabolites in a sample in a given population of reference subjects. Said concentrations may be expressed in absolute or relative terms, in the same manner as described above in relation to the sample that is to be tested using the method of the invention.
In one embodiment a method of the invention comprises the use of a plurality of reference standards. In such embodiments a method may comprise the use of a non-convertor (preferably CIS) reference standard and a convertor (preferably CDMS) reference standard.
In some embodiments a reference standard may be constructed based on polypeptide and/or metabolite concentrations for a known convertor and/or non-convertor population. In some embodiments the methods of the present invention comprise comparing measured concentrations of polypeptides and/or metabolites to the concentration of said polypeptides and/or metabolites (respectively) in both a convertor and a non-convertor reference standard (or a plurality of convertor and non-convertor reference standards) and determining to which reference standard the sample is most similar (thus allowing a determination/diagnosis according to a method of the invention).
A polypeptide and/or metabolite concentration in a reference standard may have been obtained (e.g. quantified) previously to a method of the invention.
When comparing concentrations between the sample and the reference standard, the way in which the concentrations are expressed is matched between the sample and the reference standard. Thus, an absolute concentration can be compared with an absolute concentration, and a relative concentration can be compared with a relative concentration.
A reference standard employed in the present invention may be of known convertor status.
In one embodiment the reference standard is a non-convertor reference standard. The term “non-convertor reference standard” as used herein encompasses a reference standard from a subject that has CIS or a reference standard from a healthy subject who does not have CIS, preferably a subject that has CIS. In one embodiment the term “non-convertor reference standard” as used herein refers to a reference standard from a subject that has CIS but who is a slow convertor (preferably who does not convert to CDMS by 10 or 5 years, more preferably 4 years from CIS). In a particularly preferred embodiment, a reference standard is a non-convertor reference standard from a subject that has CIS (e.g. a subject that has been diagnosed with CIS) and that does not convert to CDMS. In one embodiment a reference standard is not a reference standard from a healthy subject.
In another embodiment the reference standard is a convertor reference standard. The term “convertor reference standard” as used herein encompasses a reference standard from a subject that has CDMS or a reference standard from subject who has CIS and subsequently converted to CDMS by 10 or 5 years, more preferably by 4 years from CIS. In other words, the reference standard may have been obtained from a rapid convertor, when said rapid converter had CIS (pre-conversion). Preferably, a “convertor reference standard” is from a subject that has CDMS (e.g. a subject that has been diagnosed with CDMS).
The reference standard is typically derived from the same sample type (e.g. biofluid) as the sample that is being tested, thus allowing for an appropriate comparison between the two or more.
The methods of the present invention are in vitro methods. Thus, the methods can be carried out in vitro on an isolated sample that has been obtained from a subject.
The methods of the invention comprise comparing the measured concentrations of one or more polypeptides and/or metabolites to make a determination or diagnosis. Thus, said measured concentrations may correlate with a convertor status of a subject and/or with the presence of MS and/or with a poor prognosis. Said determination or diagnosis is typically based on measuring a concentration difference. The term “concentration difference” embraces both positive and negative differences. Thus, a concentration difference can mean that the concentration of a polypeptide and/or metabolite is higher in the sample being tested than in the reference standard. Alternatively, a concentration difference can mean that the concentration of a polypeptide and/or metabolite is lower in the sample than in the reference standard.
The comparison and/or identification of the presence or absence of a concentration difference (as described above) can be achieved using methods of statistical analysis. In one embodiment a method of statistical analysis suitable for use in the present invention includes orthogonal partial least squares discriminate analysis (OPLS-DA).
In one embodiment, the method of the invention further comprises recording the output of at least one step on a data-storage medium. By way of example, the method of the present invention can generate data relating to the subject, such data being recordable on a data-storage medium (for example, a form of computer memory such as a hard disk, compact disc, floppy disk, or solid state drive). Such data can comprise (or consist of) data relating to the concentration in a sample (from said subject) of any of one or more polypeptides and/or metabolites (as described) above.
In one aspect the invention provides a data-storage medium, comprising data obtained by a method according to the present invention.
In another aspect, the invention provides a device for use in a method of the invention, wherein said device is capable of performing the step of identifying: a concentration difference of one or more polypeptides and/or one or more metabolites in the sample when compared to the reference standard.
Treatment of multiple sclerosis (e.g. CIS and/or CDMS) may be carried out using any MS therapeutic known in the art. For example, therapy may be carried out by administering a disease modifying therapy, via cell-based treatments or via physiotherapy. A disease modifying therapy may be one or more selected from: alemtuzumab (e.g. Lemtrada), beta interferons (e.g. Avonex, Betaferon, Extavia, Plegridy, and/or Rebif), cladribine (e.g. Mavenclad), dimethyl fumarate (Tecfidera), fingolimod (Gilenya), glatiramer acetate (e.g. Copaxone and/or Brabio), natalizumab (e.g. Tysabri), ocrelizumab (e.g. Ocrevus), and teriflunomide (e.g. Aubagio). A cell-based treatment may comprise treatment with a hematopoietic cell or a functional equivalent, such as a hematopoietic stem cell and/or progenitor cell. For example, a cell-based treatment may be combined with chemotherapy (e.g. to ablate a subject's native stem cell and progenitor cell population) prior to transplanting the hematopoietic cell or functional equivalent. In some embodiments, the cells transplanted may be those of the subject removed prior to chemotherapy and treated such that, when transplanted, they will not contribute to (e.g. cause) MS and/or a symptom thereof.
The term “disorder” as used herein also encompasses a “disease”. In one embodiment the disorder is a disease. The disorder treated in accordance with the invention is MS.
The term “treat” or “treating” as used herein encompasses prophylactic treatment (e.g. to prevent onset of a disorder) as well as corrective treatment (treatment of a subject already suffering from a disorder). Preferably “treat” or “treating” as used herein means corrective treatment.
The term “treat” or “treating” as used herein refers to the disorder and/or a symptom thereof.
Therefore a therapeutic may be administered to a subject in a therapeutically effective amount or a prophylactically effective amount.
A “therapeutically effective amount” is any amount of a therapeutic formulation, which when administered alone or in combination to a subject for treating said disorder (or a symptom thereof) is sufficient to effect such treatment of the disorder, or symptom thereof.
A “prophylactically effective amount” is any amount of a therapeutic formulation that, when administered alone or in combination to a subject inhibits or delays the onset or reoccurrence of a disorder (or a symptom thereof). In some embodiments, the prophylactically effective amount prevents the onset or reoccurrence of a disorder entirely. “Inhibiting” the onset means either lessening the likelihood of a disorder's onset (or symptom thereof), or preventing the onset entirely.
Administration may be by any route known in the art and will typically be dependent on the nature of the therapeutic to be administered. For example, a therapeutic may be administered orally or parenterally. Methods of parenteral delivery include topical, intra-arterial, intramuscular, subcutaneous, intramedullary, intrathecal, intra-ventricular, intravenous, intraperitoneal, or intranasal administration.
Embodiments related to the various methods of the invention are intended to be applied equally to other methods, therapeutic uses or methods, the data storage medium or device, and vice versa.
Any of a variety of sequence alignment methods can be used to determine percent identity, including, without limitation, global methods, local methods and hybrid methods, such as, e.g., segment approach methods. Protocols to determine percent identity are routine procedures within the scope of one skilled in the art. Global methods align sequences from the beginning to the end of the molecule and determine the best alignment by adding up scores of individual residue pairs and by imposing gap penalties. Non-limiting methods include, e.g., CLUSTAL W, see, e.g., Julie D. Thompson et al., CLUSTAL W: Improving the Sensitivity of Progressive Multiple Sequence Alignment Through Sequence Weighting, Position-Specific Gap Penalties and Weight Matrix Choice, 22(22) Nucleic Acids Research 4673-4680 (1994); and iterative refinement, see, e.g., Osamu Gotoh, Significant Improvement in Accuracy of Multiple Protein. Sequence Alignments by Iterative Refinement as Assessed by Reference to Structural Alignments, 264(4) J. Mol. Biol. 823-838 (1996). Local methods align sequences by identifying one or more conserved motifs shared by all of the input sequences. Non-limiting methods include, e.g., Match-box, see, e.g., Eric Depiereux and Ernest Feytmans, Match-Box: A Fundamentally New Algorithm for the Simultaneous Alignment of Several Protein Sequences, 8(5) CABIOS 501-509 (1992); Gibbs sampling, see, e.g., C. E. Lawrence et al., Detecting Subtle Sequence Signals: A Gibbs Sampling Strategy for Multiple Alignment, 262(5131) Science 208-214 (1993); Align-M, see, e.g., Ivo Van Walle et al., Align-M—A New Algorithm for Multiple Alignment of Highly Divergent Sequences, 20(9) Bioinformatics: 1428-1435 (2004).
Thus, percent sequence identity is determined by conventional methods. See, for example, Altschul et al., Bull. Math. Bio. 48: 603-16, 1986 and Henikoff and Henikoff, Proc. Natl. Acad. Sci. USA 89:10915-19, 1992. Briefly, two amino acid sequences are aligned to optimize the alignment scores using a gap opening penalty of 10, a gap extension penalty of 1, and the “blosum 62” scoring matrix of Henikoff and Henikoff (ibid.) as shown below (amino acids are indicated by the standard one-letter codes).
The “percent sequence identity” between two or more nucleic acid or amino acid sequences is a function of the number of identical positions shared by the sequences. Thus, % identity may be calculated as the number of identical nucleotides/amino acids divided by the total number of nucleotides/amino acids, multiplied by 100. Calculations of % sequence identity may also take into account the number of gaps, and the length of each gap that needs to be introduced to optimize alignment of two or more sequences. Sequence comparisons and the determination of percent identity between two or more sequences can be carried out using specific mathematical algorithms, such as BLAST, which will be familiar to a skilled person.
The percent identity is then calculated as:
Substantially homologous polypeptides are characterized as having one or more amino acid substitutions, deletions or additions. These changes are preferably of a minor nature, that is conservative amino acid substitutions (see below) and other substitutions that do not significantly affect the folding or activity of the polypeptide; small deletions, typically of one to about 30 amino acids; and small amino- or carboxyl-terminal extensions, such as an amino-terminal methionine residue, a small linker peptide of up to about 20-25 residues, or an affinity tag.
In addition to the 20 standard amino acids, non-standard amino acids (such as 4-hydroxyproline, 6-N-methyl lysine, 2-aminoisobutyric acid, isovaline and α-methyl serine) may be substituted for amino acid residues of the polypeptides of the present invention. A limited number of non-conservative amino acids, amino acids that are not encoded by the genetic code, and unnatural amino acids may be substituted for polypeptide amino acid residues. The polypeptides of the present invention can also comprise non-naturally occurring amino acid residues.
Non-naturally occurring amino acids include, without limitation, trans-3-methylproline, 2,4-methano-proline, cis-4-hydroxyproline, trans-4-hydroxy-proline, N-methylglycine, allo-threonine, methyl-threonine, hydroxy-ethylcysteine, hydroxyethylhomo-cysteine, nitro-glutamine, homoglutamine, pipecolic acid, tert-leucine, norvaline, 2-azaphenylalanine, 3-azaphenyl-alanine, 4-azaphenyl-alanine, and 4-fluorophenylalanine. Several methods are known in the art for incorporating non-naturally occurring amino acid residues into proteins. For example, an in vitro system can be employed wherein nonsense mutations are suppressed using chemically aminoacylated suppressor tRNAs. Methods for synthesizing amino acids and aminoacylating tRNA are known in the art. Transcription and translation of plasmids containing nonsense mutations is carried out in a cell free system comprising an E. coli S30 extract and commercially available enzymes and other reagents. Proteins are purified by chromatography. See, for example, Robertson et al., J. Am. Chem. Soc. 113:2722, 1991; Ellman et al., Methods Enzymol. 202:301, 1991; Chung et al., Science 259:806-9, 1993; and Chung et al., Proc. Natl. Acad. Sci. USA 90:10145-9, 1993). In a second method, translation is carried out in Xenopus oocytes by microinjection of mutated mRNA and chemically aminoacylated suppressor tRNAs (Turcatti et al., J. Biol. Chem. 271:19991-8, 1996). Within a third method, E. coli cells are cultured in the absence of a natural amino acid that is to be replaced (e.g., phenylalanine) and in the presence of the desired non-naturally occurring amino acid(s) (e.g., 2-azaphenylalanine, 3-azaphenylalanine, 4-azaphenylalanine, or 4-fluorophenylalanine). The non-naturally occurring amino acid is incorporated into the polypeptide in place of its natural counterpart. See, Koide et al., Biochem. 33:7470-6, 1994. Naturally occurring amino acid residues can be converted to non-naturally occurring species by in vitro chemical modification. Chemical modification can be combined with site-directed mutagenesis to further expand the range of substitutions (Wynn and Richards, Protein Sci. 2:395-403, 1993).
A limited number of non-conservative amino acids, amino acids that are not encoded by the genetic code, non-naturally occurring amino acids, and unnatural amino acids may be substituted for amino acid residues of polypeptides of the present invention.
Essential amino acids in the polypeptides of the present invention can be identified according to procedures known in the art, such as site-directed mutagenesis or alanine-scanning mutagenesis (Cunningham and Wells, Science 244: 1081-5, 1989). Sites of biological interaction can also be determined by physical analysis of structure, as determined by such techniques as nuclear magnetic resonance, crystallography, electron diffraction or photoaffinity labeling, in conjunction with mutation of putative contact site amino acids. See, for example, de Vos et al., Science 255:306-12, 1992; Smith et al., J. Mol. Biol. 224:899-904, 1992; Wlodaver et al., FEBS Lett. 309:59-64, 1992. The identities of essential amino acids can also be inferred from analysis of homologies with related components (e.g. the translocation or protease components) of the polypeptides of the present invention.
Multiple amino acid substitutions can be made and tested using known methods of mutagenesis and screening, such as those disclosed by Reidhaar-Olson and Sauer (Science 241:53-7, 1988) or Bowie and Sauer (Proc. Natl. Acad. Sci. USA 86:2152-6, 1989). Briefly, these authors disclose methods for simultaneously randomizing two or more positions in a polypeptide, selecting for functional polypeptide, and then sequencing the mutagenized polypeptides to determine the spectrum of allowable substitutions at each position. Other methods that can be used include phage display (e.g., Lowman et al., Biochem. 30:10832-7, 1991; Ladner et al., U.S. Pat. No. 5,223,409; Huse, WIPO Publication WO 92/06204) and region-directed mutagenesis (Derbyshire et al., Gene 46:145, 1986; Ner et al., DNA 7:127, 1988).
Multiple amino acid substitutions can be made and tested using known methods of mutagenesis and screening, such as those disclosed by Reidhaar-Olson and Sauer (Science 241:53-7, 1988) or Bowie and Sauer (Proc. Natl. Acad. Sci. USA 86:2152-6, 1989). Briefly, these authors disclose methods for simultaneously randomizing two or more positions in a polypeptide, selecting for functional polypeptide, and then sequencing the mutagenized polypeptides to determine the spectrum of allowable substitutions at each position. Other methods that can be used include phage display (e.g., Lowman et al., Biochem. 30:10832-7, 1991; Ladner et al., U.S. Pat. No. 5,223,409; Huse, WIPO Publication WO 92/06204) and region-directed mutagenesis (Derbyshire et al., Gene 46:145, 1986; Ner et al., DNA 7:127, 1988).
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. Singleton, et al., DICTIONARY OF MICROBIOLOGY AND MOLECULAR BIOLOGY, 20 ED., John Wiley and Sons, New York (1994), and Hale & Marham, THE HARPER COLLINS DICTIONARY OF BIOLOGY, Harper Perennial, NY (1991) provide the skilled person with a general dictionary of many of the terms used in this disclosure.
This disclosure is not limited by the exemplary methods and materials disclosed herein, and any methods and materials similar or equivalent to those described herein can be used in the practice or testing of embodiments of this disclosure. Numeric ranges are inclusive of the numbers defining the range. Unless otherwise indicated, any nucleic acid sequences are written left to right in 5′ to 3′ orientation; amino acid sequences are written left to right in amino to carboxy orientation, respectively.
The headings provided herein are not limitations of the various aspects or embodiments of this disclosure.
Amino acids are referred to herein using the name of the amino acid, the three letter abbreviation or the single letter abbreviation. The term “protein”, as used herein, includes proteins, polypeptides, and peptides. As used herein, the term “amino acid sequence” is synonymous with the term “polypeptide” and/or the term “protein”. In some instances, the term “amino acid sequence” is synonymous with the term “peptide”. In some instances, the term “amino acid sequence” is synonymous with the term “enzyme”. The terms “protein” and “polypeptide” are used interchangeably herein. In the present disclosure and claims, the conventional one-letter and three-letter codes for amino acid residues may be used. The 3-letter code for amino acids as defined in conformity with the IUPACIUB Joint Commission on Biochemical Nomenclature (JCBN). It is also understood that a polypeptide may be coded for by more than one nucleotide sequence due to the degeneracy of the genetic code.
Other definitions of terms may appear throughout the specification. Before the exemplary embodiments are described in more detail, it is to be understood that this disclosure is not limited to particular embodiments described, and as such may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present disclosure will be defined only by the appended claims.
Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within this disclosure. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within this disclosure, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in this disclosure.
It must be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a metabolite” includes a plurality of such candidate agents and reference to “the polypeptide” includes reference to one or more polypeptides and equivalents thereof known to those skilled in the art, and so forth.
The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that such publications constitute prior art to the claims appended hereto.
Embodiments of the invention will now be described, by way of example only, with reference to the following Figures and Examples.
Where an initial Met amino acid residue or a corresponding initial codon is indicated in any of the following SEQ ID NOs, said residue/codon is optional.
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
aureus (strain
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
sapiens OX = 9606
CSF samples were collected from 41 patients with CDMS, 71 patients with CIS, and 64 non-MS controls and analysed using a omics methodology, including multi-omics methodology. This approach used nuclear magnetic resonance spectroscopy to measure over 100 CSF and serum metabolite concentrations and an aptamer-based proteomics assay (SOMAscan) to measure over 5000 CSF protein levels combined with multivariate feature selection and pathway analysis.
Plasma: Blood was collected into BD vacutainer lithium-heparin tubes (product number 367375) and stored at room temperature for 30 mins before centrifugation at 2,200×g for 10 mins and plasma immediately aliquoted and stored at −80° C. Serum: Blood was collected into BD additive free tubes (product number) and stored at room temperature for 30 mins before centrifugation at 2,200×g for 10 mins and serum immediately aliquoted and stored at −80° C. Cerebrospinal fluid (CSF): samples were collected in to additive free tubes and immediately aliquoted and stored at −80° C.
Proteomic profiles were characterised using the SOMAscan Assay (SomaLogic, Inc.; Boulder, Colo., USA) at the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation (CHI), National Institutes of Health (Bethesda, Md., USA) as previously described (Proc. Natl. Acad. Sci. U.S.A. 109, 19971-19976 (2012), Proc. Natl. Acad. Sci. U.S.A. 112, 7153-7158 (2015), Science. 2018 Aug. 24; 361(6404):769-773.).
In brief, 5,457 individual serum samples were treated with the detergent Tween-20 to prevent loss of reagent material to tube walls and for lysis of exosomes, and then incubated with the mixture of 5,034 SOMAmers to generate SOMAmerprotein complexes. Unbound SOMAmers and unbound or non-specifically bound proteins were eliminated by 2 bead-based immobilization wash steps and the use of polyanionic competitors. After eluting the enriched SOMAmers from their target proteins they were directly quantified on an Agilent hybridization array (Agilent Technologies). Hybridization controls were used to correct for systematic variability in detection and calibrator samples of three dilution sets (40%, 1% and 0.005%) were included so that the degree of fluorescence was a quantitative reflection of protein concentration. All scale factors were then used to normalize the protein data. To avoid batch or time of processing biases, both sample collection and sample processing for protein measurements were randomized and all samples run as a single set. The 5,034 SOMAmers that passed quality control had median intra-assay and inter-assay coefficient of variation, CV=100×σ/μ, or similar to that reported on variability in the 4 SOMAscan assays (Sci. Rep. 7, 14248 (2017)).
NMR metabolomics analysis of CSF/serum/plasma was carried out as previously described (J Crohns Colitis. 2018 Nov. 15; 12(11):1326-1337., Acta Neuropathol Commun. 2017 Dec. 6; 5(1):95.) and is discussed in more detail below.
Plasma/serum samples were defrosted at room temperature and centrifuged at 100,000×g for 30 minutes at 4° C. 150 μL of the plasma/serum supernatant was then diluted with 450 μL of 75 mM sodium phosphate buffer prepared in D2O (pH 7.4). Samples were then centrifuged at 16,000×g for 3 minutes to remove any precipitate before transferring to a 5-mm NMR tube.
CSF samples were defrosted at room temperature and centrifuged at 100,000×g for 30 minutes at 4° C. 75 μL of the CSF supernatant was then diluted with 525 μL of 75 mM sodium phosphate buffer prepared in D2O (pH 7.4)
All NMR spectra were acquired using a 700-MHz Bruker AVII spectrometer operating at 16.4 T equipped with a 1H (13C/15N) TCI cryoprobe. Sample temperature was stable at 310K. 1H NMR spectra were acquired using a 1D NOESY presaturation scheme for attenuation of the water resonance with a 2 s presaturation. A spin-echo Carr-Purcell-Meiboom-Gill (CPMG) sequence with a T interval of 400 μs, 80 loops, 32 data collections, an acquisition time of 1.5 s, a relaxation delay of 2 s, and a fixed receiver gain was used to supress broad signals arising from large molecular weight plasma components. 1H correlation spectroscopy (COSY, TOCSY) spectra were acquired on at least one sample in each classification to aid in metabolite identification. For quality control, pooled plasma samples were spread throughout the run to monitor technical variation.
Resulting free induction decays (FIDs) were zero-filled by a factor of 2 and multiplied by an exponential function corresponding to 0.30 Hz line broadening prior to Fourier transformation. All spectra were phased, baseline corrected (using a 3rd degree polynomial), and chemical shifts referenced to the lactate-CHs doublet resonance at δ=1.33 ppm in Topspin 2.1 (Bruker, Germany). Spectra were visually examined for errors in baseline correction, referencing, spectral distortion, or contamination and then exported to ACD/Labs Spectrus Processor Academic Edition 12.01 (Advanced Chemistry Development, Inc.). The regions of the spectra between 0.08-4.20 ppm and 5.20-8.50 ppm were divided in to 0.02 ppm width ‘buckets’ and the absolute value of the integral of each spectral bucket was Pareto scaled. Resonances were assigned by reference to literature values [Anal Biochem 325:260-272, J Pharm Biomed Anal 33:1103-1115] and the Human Metabolome Database [Nucleic Acids Res 41:D801-807. doi:10.1093/nar/gks1065, Nucleic Acids Res 37:D603-610. doi:10.1093/nar/gkn810, Nucleic Acids Res 35:D521-526. doi:10.1093/nar/gk1923] and further confirmed by inspection of the 2D spectra, spiking of known compounds, and 1D-TOCSY spectra.
The bucketed integrals were imported into R (R foundation for statistical computing, Vienna, Austria) [Team RC R: A Language and Environment for Statistical Computing. R Found Stat Comput]. All multivariate analysis was carried out using in-house R scripts and the ropls package [J Proteome Res 14:3322-3335]. Principal component analysis (PCA) was used to visualize the degree of separation between the disease classifications and detect potential outliers. An elastic net feature selection method was used to first identify discriminatory features within the datasets. Finally, the selected, cross-validated, features were input into an orthogonal partial least squares discriminatory analysis (OPLS-DA) to generate diagnostic mathematical models. Analysis was performed on each biofluid and dataset independently (proteomics and metabolomics) and all combined permutations in a combined-omics approach. All OPLS-DA models were optimized by internal 7-fold cross-validation. The quality of classification was assessed using a 10-fold external cross-validation scheme with 1000 repetitions in total (to correct for unequal class sizes). This validation scheme involves multiple iterations of splitting the data into training and testing sets. The training data is used to estimate the model parameters and learn the underlying discriminatory patterns between the groups under consideration, whereas the independent test set is employed to assess the accuracy and generalizability of the trained models in the ensemble. We quantified the response of the ensemble of models by calculating the accuracy, sensitivity, and specificity of each model from the predicted classifications of the external, independent test set (i.e. which is not used in model building). It is important to appreciate that the classifier (OPLS-DA) was blinded to the test set during the process of model training. This validation scheme tends to avoid over-fitting and helps assess the generalizability of the model to previously unseen datasets. For an exhaustive discussion on validation see Arlot and Celisse (2010) [Statistics surveys 4:40-79]. These values were compared with those of a null distribution (obtained from randomly permuting the classifications) using the two-sided Kolmogorov-Smirnov test (significant if p-value 0.05 or less). Discriminators were identified by calculating the variable importance (VIP) score (cut-off of 1.5). The fold changes of these variables were further investigated by analysis-of-variance (ANOVA) followed by Tukey's honest significant difference (HSD) post-hoc test. The p-values obtained were then corrected for multiple comparisons using the Bonferroni correction.
Metabolomics analysis was able to diagnose CDMS and CIS with accuracies of 71±4% and 66±2% respectively. Interestingly, removal of CIS patients who tested negative for OCBs resulted in an improved accuracy of 68±3%.
Table 1 shows top protein biomarkers identified by feature selection and multivariate analysis and ranked by importance in the multivariate model. Univariate p-value <0.05, 0.01, 0.001 represented by *,**,*** respectively. Univariate p-value <0.05, 0.01, 0.001 following Bonferonni correction for multiple comparisons represented by ‡, ‡‡, ‡‡‡ respectively:
Table 2 shows CSF NMR metabolomics hits identified. Rank in combined 'omics mode. Mean±standard deviation relative spectral intensity. Fold change of early converters relative to non-converters. Univariate p-value <0.05, 0.01, 0.001 represented by *,**,*** respectively. Univariate p-value <0.05, 0.01, 0.001 following Bonferonni correction for multiple comparisons represented by ‡, ‡‡, ‡‡‡ respectively.
Table 3 shows serum NMR metabolomics hits identified. Rank in combined 'omics mode. Mean±standard deviation relative spectral intensity. Fold change of early converters relative to non-converters. Univariate p-value <0.05, 0.01, 0.001 represented by *,**,*** respectively. Univariate p-value <0.05, 0.01, 0.001 following Bonferonni correction for multiple comparisons represented by ‡, ‡‡, ‡‡‡ respectively.
Table 4 shows Clinical Chemistry parameters included in models. Rank in combined 'omics mode. Mean±standard deviation. Fold change of early converters relative to non-converters. Univariate p-value <0.05, 0.01, 0.001 represented by *,**,*** respectively. Univariate p-value <0.05, 0.01, 0.001 following Bonferonni correction for multiple comparisons represented by ‡, ‡‡, ‡‡‡ respectively.
These results indicate that metabolomics and proteomics analyses could not only be used in diagnosis of CDMS but could also be used as a prognostic test to identify CIS patients at high risk of a second clinical attack within 4 years of onset.
All publications mentioned in the above specification are herein incorporated by reference. Various modifications and variations of the described methods and system of the present invention will be apparent to those skilled in the art without departing from the scope and spirit of the present invention. Although the present invention has been described in connection with specific preferred embodiments, it should be understood that the invention as claimed should not be unduly limited to such specific embodiments. Indeed, various modifications of the described modes for carrying out the invention which are obvious to those skilled in biochemistry and biotechnology or related fields are intended to be within the scope of the following claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 1909619.7 | Jul 2019 | GB | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/GB2020/051615 | 7/6/2020 | WO |
