CNS-SPECIFIC BIOMARKERS FOR CNS DISEASES OR INJURIES
20170254818 · 2017-09-07
Assignee
Inventors
Cpc classification
International classification
Abstract
Methods and compositions for detecting and/or measuring biomarkers associated with compromised BBB.
Claims
1. A method of evaluating a patient suspected of having a central nervous system (CNS) disease comprising: measuring the level of at least one protein biomarker or peptide biomarker selected from SEQ ID NO:1 to SEQ ID NO:544 in a biologic sample from the patient, wherein the patient is suspected of having, is at risk of developing, or has been diagnosed with a CNS disease; classifying the subject based on the levels of at least one biomarker associated with a CNS disease or a CNS injury.
2. The method of claim 1, further comprising measuring the level of at least one protein biomarker or peptide biomarker in a plurality of samples from the patient, each sample obtained at a different time, and determining the trajectory of an expression wave for the at least one protein biomarker or peptide biomarker measured.
3. The method of claim 1, wherein the at least one protein comprises one or more of α-II-spectrin, synapsin-1/2/3, myelin basic protein, ubiquitin carboxyl-terminal esterase L1, calcium/calmodulin-dependent protein kinase II alpha, neurofilament light and medium, parkin 2, peroxiredoxin-1/4/5/6, 14-3-3-β/ε/ζ, synaptotagmin, enolase-1/2, guanine nucleotide binding protein α and β1, superoxide dismutase 2, internexin neuronal intermediate filament protein α, tyrosine-protein phosphatase non-receptor type substrate 1, macrophage migration inhibitory factor, proteolipid protein 1, or caspase 7, and combinations thereof.
4. The method of claim 1, wherein the peptide biomarker comprises one or more of a peptide having the amino acid sequence of SEQ ID NO:1 to 544.
5. The method of claim 1, wherein the protein biomarker or peptide biomarker is measured using mass spectrometry.
6. The method of claim 5, wherein the sample is labeled using isobaric labels.
7. The method of claim 6, wherein the sample is prepared using microwave and magnetic sample preparation.
8. The method of claim 1, wherein the protein biomarker or peptide biomarker is measured using an immunoassay.
9. The method of claim 8, wherein the immunoassay is an ELISA or an antibody array.
10. The method of claim 1, wherein the CNS disease is multiple sclerosis.
11. A method of detecting a preclinical expression wave comprising measuring biomarker levels in two or more samples from a patient that were obtained at different times and determining the rate of change of biomarker expression.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0052] The following descriptions form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of the specification embodiments presented herein.
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DETAILED DESCRIPTION OF THE INVENTION
[0065] Multiple sclerosis (MS) can be used as one example of a disease state that involves the compromise of the blood brain barrier (BBB). Clinical diagnosis of MS, versus other similar neurological diseases, and classification into the consensus definitions of the four major subtypes of MS is based on a limited diagnostic repertoire, including: clinical appearance, disease history and laboratory imaging and/or diagnostics (Steinman, Cell 85, 299-302, 1996; Sospedra and Martin, Annu Rev Immunol 23, 683-747, 2005; Noseworthy et al., N Engl J Med 343, 938-952, 2000; Thompson et al., Brain: a journal of neurology 120 (6), 1085-1096, 1997; Lublin and Reingold, Neurology 46, 907-911, 1996; Confavreux et al., The New England journal of medicine 343, 1430-1438, 2000). Currently, MS is classified into relapsing-remitting (RRMS), secondary-progressive (SPMS), primarily-progressive (PPMS) and progressive-relapsing (PRMS). Approximately 80% of the patients initially develop the RRMS form of the disease, characterized by clinical attacks (relapses) with diverse neurological dysfunctions, followed by functional recovery (remission). More than half of these patients will eventually develop SPMS, characterized by progressive residual neurological deficiencies with or without attacks during the progressive phase (Lublin and Reingold, Neurology 46, 907-911, 1996). Current immunomodulatory treatments ameliorate, but do not cure, MS, including: beta-interferons, therapeutic antibodies, glucocorticoids, and glatiramer acetate. Responses to treatments are highly variable between patients and no accurate means exist to predict efficacy of a particular drug. Individual responses to treatment are typically evaluated by clinical measures of disease progression such as the expanded disability status scale (EDSS) (Poonawalla et al., Mult Scler 16, 1117-1125, 2010) and magnetic resonance imaging (MRI) of brain lesion volume (Bakshi et al., Lancet Neurol 7, 615-625, 2008; Tourdias and Dousset, Neurotherapeutics, 2012; Filippi and Agosta, J Magn Reson Imaging 31, 770-788, 2010; Neema et al., Neurotherapeutics 4, 602-617, 2007). However, these clinical measures lack sensitivity and specificity for a large population of MS patients, and they fail to show a strong correlation between specific treatments and their efficacy in slowing disease progression in individual MS patients.
[0066] Thus, there is a need for molecular biochemical markers (biomarkers) with improved diagnostic, prognostic, and predictive power. However, poorly understood variations of genetic, environmental, and socioeconomic factors in the MS patient population present profound challenges for biomarker research. A diagnostic matrix with a particular combination of biomarkers might enable more precise molecular stratification of individual patients into treatment groups. Moreover, a particular combination of biomarkers might be necessary because not all of these molecules are expected to be exclusive to MS and might also be found in other diseases and neurological disorders.
[0067] Studying the relation of protein expression trajectories to disease progression within individual MS patients can mitigate population variability to a certain degree and account for potential patient-specific factors. More than 24,000 genes are translated and post-translationally modified into an estimated 2 million protein isoforms in humans, encoding far more molecular diversity than the relatively static genome or transcriptome. Paradoxically, less than 100 proteins are routinely quantified in serum today (Rifai et al., Nat Biotechnol 24, 971-983, 2006; Anderson and Anderson, Mol Cell Proteomics 1, 845-867, 2002). Thus, the most sensitive (most true-positive) and specific (least false-positive) biomarkers are expected to be at the protein level. Notably, proteins must be measured directly due to the poor correlation between the transcriptome and proteome due to alternative splicing, post-translational modifications, single nucleotide polymorphisms, limiting ribosomes available for translation, mRNA, protein stability and other factors (e.g., microRNA).
[0068] CNS specific proteins (CSPs), transported across the damaged BBB to cerebral spinal fluid (CSF) and/or blood are promising diagnostic, prognostic, and predictive (therapeutic) protein biomarkers of disease in individual MS patients because they are not expected to be present at appreciable levels in the circulation of healthy subjects. Compared to the highly variable clinical spectrum of individual MS patients, disease in groups of mice with experimental autoimmune encephalomyelitis (EAE), the major animal model for MS, is less heterogeneous and more synchronous, providing a strong rationale for preclinical biomarker studies.
I. BIOMARKERS
[0069] A biomarker is an organic biomolecule, such as a protein or fragment thereof, that is differentially present in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease). A biomarker is differentially present between different phenotypic statuses if the mean or median expression level of the biomarker in the different groups is calculated to be statistically significant. Common tests for statistical significance include, among others, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and odds ratio. Biomarkers, alone or in combination, provide measures of relative risk that a subject belongs to one phenotypic status or another. As such, they are useful as markers for disease (diagnostics), therapeutic effectiveness of a drug (theranostics) and of drug toxicity.
[0070] Aspects described herein seek to develop methods for identifying, monitoring, and classifying patients at risk of having a compromised BBB based expression profiling. However, identification of predictive biomarkers in complex biofluids, such as plasma, have been challenging for proteomics technologies. Plasma is a complex biofluid, with its constituent proteins present in a broad dynamic concentration range spanning 6 log orders of magnitude or more (Anderson and Anderson Mol Cell Proteomics 1:845-67, 2002; Rifai and Gerszten, Clinical Chemistry 52:1635-37, 2006). Moreover, high-abundance proteins tend to adsorb lower-abundance proteins and peptides (Gundry et al. Proteomics Clin. Appl. 1:73-88, 2007; Seferovic et al., J Chrom. B Analyt. Technol. Biomed. Life Sci. 865:147-152, 2008). The presence of proteases may produce peptide fragments (Villanueva et al., J Proteome Res. 4:1060-72, 2005; Villanueva et al., Mol. Cell Proteomics 7:509-18, 2008), and the individual variation in plasma protein abundances serve to compound the difficulties in comprehensive proteomic analyses of plasma. With the advancement of multidimensional profiling techniques, the systematic and quick identification of predictive proteins associated with a disease is now feasible.
[0071] The spectrin-family is comprised of a group of membrane-bound proteins, including α-II-spectrin, that are present in most vertebrate tissues and were initially discovered as a component of erythrocyte membrane. Spectrin is composed of two subunits, α and β, that coil around each other to form a heterodimer. The α subunit is encoded by two different genes, while the β subunit is encoded by five different genes: alternative splicing generates additional isoforms. In the CNS, almost all major cell types express spectrin, with distinct isoforms found in different cell types. α-II-spectrin is predominantly localized to axons and to presynaptic terminals of neurons with an essential role in Ca+ mediated exocytosis and neurotransmitter release through its association with synapsin proteins that are found in the neuronal vesicles. α-II-spectrin is also cleaved by calcium-dependent cysteine proteases such as calpains and caspases during necrosis and apoptosis to generate breakdown products that are often protease-specific.
[0072] Synapsin-1, one of the CSPs reported in this application, is a phosphorylated CSP found at synaptic vesicles in neurons that can bind to several cytoskeleton components including actin, microtubules and α-II-spectrin. It is involved in synaptogenesis and calcium-dependent neurotransmitter release from synaptic vesicles, particularly glutamate release.
[0073] Biomarkers described herein comprise peptides having amino acid sequences corresponding to SEQ ID NO: 1 to 543. In certain aspects the biomarker is selected from human or mouse α-II-spectrin, synapsin-1/2/3, myelin basic protein, ubiquitin carboxyl-terminal esterase L1, calcium/calmodulin-dependent protein kinase II alpha, neurofilament light and medium, parkin 2, peroxiredoxin-1/4/5/6, 14-3-3-β/ε/ζ, synaptotagmin, enolase-1/2, guanine nucleotide binding protein α and β1, superoxide dismutase 2, internexin neuronal intermediate filament protein α, tyrosine-protein phosphatase non-receptor type substrate 1, macrophage migration inhibitory factor, proteolipid protein 1, and/or caspase 7.
[0074] CSP expression waves that were consistently observed include CPSs corresponding to one or more of SEQ ID NO:1 to 544 representing peptides having an AUC of greater than 0.90, relative to two time points between −1, 0, 5, 7, 10, 15, 20, 25 days relative to immunization. In certain aspects the contrast between day −1 and 0, −1 and 5, −1 and 7, −1 and 10, −1 and 15, −1 and 20, −1 and 25, 0 and 5, 0 and 7, 0 and 10, 0 and 15, 0 and 20, 0 and 25; 5 and 7, 5 and 10, 5 and 15, 5 and 20, 5 and 25, 7 and 10, 7 and 15, 7 and 20, 7 and 25, 10 and 15, 10 and 20, 10 and 25, 15 and 20, 15 and 25, or 20 and 25 results in an AUC of about or at least 0.90, 0.91, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97, 0.98, 0.99, or 1.00.
II. ASSAYS
[0075] In certain aspects, the biomarkers of this invention can be identified, measured or detected using microwave and magnetic (M.sup.2) proteomics for quantitative liquid chromatography-tandem mass spectrometry (LC/MS/MS) and/or immunoassay.
[0076] Microwave and magnetic (M.sup.2) proteomics for quantitative liquid chromatography-tandem mass spectrometry (LC/MS/MS) can be used to assess relatively large numbers of CSPs and brain tissue specimens in murine EAE (Raphael et al., Electrophoresis 33, 3810-3819, 2012; Mahesula et al., Electrophoresis 33, 3820-3829, 2012). M.sup.2 proteomics synergizes off-line microwave-assisted chemical modification of CSPs bound to magnetic C8 microparticles, multiplexed isobaric encoding, and automated sample preparation with 96-well plates. M.sup.2 proteomics is also amino acid sequence- and post-translational modification-specific (Ottens et al., Mass spectrometry reviews 25, 380-408, 2006; Ottens et al., Analytical chemistry 77, 4836-4845, 2005; Haskins et al., Journal of neurotrauma 22, 629-644, 2005; Wang et al. International review of neurobiology 61, 215-240, 2004). Despite its advantages, LC/MS/MS-based proteomics of low abundance CSPs can be confounded by masking effects due to high abundance proteins, particularly in CSF and serum where protein abundance can span up to 12 orders of magnitude (Kushnir et al., Clinical chemistry 59, 982-990, 2013; Lehmann et al., Clinical chemistry and laboratory medicine: CCLM/FESCC 51, 919-935, 2013).
[0077] Microwave and Magnetic (M2) Sample Preparation. Isobaric labeling is a mass spectrometry strategy used in quantitative proteomics. Peptides or proteins are labeled with various chemical groups that are (at least nominally) isobaric, or the same in mass, but which fragment during tandem mass spectrometry to yield reporter ions of different mass. In a typical bottom-up proteomics workflow, proteins are enzymatically digested by a protease to produce peptides, which are then labeled with different isobaric tags. The samples are mixed in equal ratios. During a liquid chromatography-mass spectrometry analysis, the peptides are fragmented to produce sequence-specific product ions, which help to determine the peptide sequence, as well as the reporter tags, whose abundances reflect the relative ratio of the peptide in the samples that were combined. In certain aspects C8 magnetic beads (BcMg, Bioclone Inc.) are suspended and washed with an equilibration buffer (e.g., 200 mM NaCl, 0.1% trifluoroacetic acid (TFA)). Whole cell protein lysate (25-100 μg at 1 μg/μL) is mixed with pre-equilibrated beads and ⅓.sup.rd sample binding buffer (e.g., 800 mM NaCl, 0.4% TFA) by volume. The mixture is incubated at room temperature and the supernatant removed. The beads are washed (e.g., with 40 mM triethylammonium bicarbonate (TEAB)), and then 10 mM dithiolthreitol (DTT) is added. The bead-lysate mixture is heated by microwave for 10 s. DTT is removed and iodoacetamide (IAA) is added, followed by a second microwave heating for 10 s. The beads are washed twice and re-suspended in TEAB. In vitro proteolysis is performed with trypsin and microwave heated for 20 s in triplicate. The supernatant is used immediately or stored at −80° C. Released tryptic peptides from digested protein lysates, including any reference material, are modified at the N-terminus and at lysine residues with the tandem mass tagging (TMT)-6plex isobaric labeling reagents (Thermo scientific, San Jose, Calif.) or other similar reagent. Each individual specimen is encoded with one of the TMT-127-130 reagents, while reference material is encoded with the TMT-126 and -131 reagents: anhydrous acetonitrile is added to TMT labeling reagent and microwave-heated for 10s. To quench the reaction, 5% hydroxylamine is added to the sample at room temperature. To normalize across all specimens, TMT-encoded cell lysates from individual specimens, labeled with the TMT-127-130 reagents, are mixed with the reference material encoded with the TMT-126 and -131 reagents in equal ratios. These sample mixtures, including all TMT-encoded specimens, were stored at −80° C. until further use.
[0078] Capillary Liquid Chromatography-Fourier-Transform-Tandem Mass Spectrometry (LC/FT/MS/MS) with Protein Database Searching. Capillary LC/FT/MS/MS can be performed. For unbiased analyses, the top 6 most abundant eluting ions were fragmented by data-dependent HCD with a mass resolution of 120,000 for MS and 15,000 for MS/MS. For isobaric TMT labeling, probability-based protein database searching of MS/MS spectra against the Trembl protein database (release 2012_dec29; 59,862 sequences) was performed with a 10-node MASCOT cluster (v. 2.3.02, Matrix Science, London, UK) with the following search criteria: peak picking with Mascot Distiller; 10 ppm precursor ion mass tolerance, 0.8 Da product ion mass tolerance, 3 missed cleavages, trypsin, carbamidomethyl cysteines as a static modification, oxidized methionines, and deamidated asparagines as variable modifications, an ion score threshold of 20 and TMT-6-plex for quantification.
[0079] Immunoassay requires biospecific capture reagents, such as antibodies, to capture the biomarkers. Antibodies can be produced by methods well known in the art, e.g., by immunizing animals with a biomarker and isolating antibodies that specifically bind the biomarker. Biomarkers can be isolated from samples based on their binding characteristics. Alternatively, if the amino acid sequence of a polypeptide biomarker is known, the polypeptide can be synthesized and used to generate antibodies.
[0080] This invention contemplates using traditional immunoassays including, for example, sandwich immunoassays including ELISA or fluorescence-based immunoassays, as well as other enzyme immunoassays. In the SELDI-based immunoassay, a biospecific capture reagent for the biomarker is attached to the surface of an MS probe, such as a pre-activated ProteinChip array. The biomarker is then specifically captured on the biochip through this reagent, and the captured biomarker is detected by mass spectrometry.
III. KITS
[0081] In another aspect, the present invention provides kits for detecting and/or measuring biomarkers described herein. In one embodiment, the kit comprises a solid support, such as a chip, a microtiter plate, a bead, or resin having a capture reagent or probe attached thereon, wherein the capture reagent or probe binds a biomarker described herein. Thus, for example, the kits of the present invention can comprise mass spectrometry probes for SELDI, such as ProteinChip® arrays.
[0082] The kit can also comprise a washing solution or instructions for making a washing solution, in which the combination of the capture reagent and the washing solution allows capture of a biomarker or biomarkers on the solid support for subsequent detection by, e.g., mass spectrometry. The kit includes one or more of: (a) a substrate for holding a biological sample isolated from a human subject suspected of having or know to have a CNS-disease; (b) an agent that specifically binds at least one biomarker selected from the peptides and/or proteins described herein; and (c) printed instructions for reacting the agent with the biological sample or a portion of the biological sample to detect the presence or amount of the at least one marker in the biological sample. In the kit, the biological sample can be CSF or blood, and the agent can be an antibody, aptamer, or other molecule that specifically binds at least one peptide and/or protein described herein. The kit can also include a detectable label such as one conjugated to the agent, or one conjugated to a substance that specifically binds to the agent (e.g., a secondary antibody).
[0083] In a further embodiment, such a kit can comprise instructions for suitable operational parameters in the form of a label or separate insert. For example, the instructions may inform a consumer about how to collect the sample, how to wash the probe or the particular biomarkers to be detected. In yet another embodiment, the kit can comprise one or more containers with capture reagents, and control or reference samples.
IV. EXAMPLES
[0084] The following examples as well as the figures are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples or figures represent techniques discovered by the inventors to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention.
Example 1
Microwave and Magnetic (M2) Proteomics for CNS-Specific Protein Biomarkers of Experimental Autoimmune Encephalomyelitis and Multiple Sclerosis
[0085] A. Material and Methods
[0086] Murine Experimental Autoimmune Encephalomyelitis (EAE). Five week-old C57BL/6 female mice were purchased from the Jackson Laboratory (Stock number 000664; Bar Harbor, Me.) and used at 6-8 weeks of age in the studies. All animals were maintained in pathogen free conditions in the American Association for Laboratory Animal Science (AALAS) facility, under the guidelines established by the Institutional Animal Care and Use Committee (IACUC) at the University of Texas at San Antonio. Mice were allowed to rest for 8 days, and they were maintained under specific pathogen-free conditions. Active induction of EAE was performed with a subcutaneous injection of each mouse with 200 μg of myelin oligodendrocyte glycoprotein (MOG) 35-55 peptide (United Biochemical Research, Seattle, Wash.) in 50 μL of complete Freund's adjuvant (CFA) containing Mycobacterium tuberculosis H37Ra (Difco Laboratories, Detroit, Mich.) at a final concentration of 5 mg/mL. Two intra-peritoneal (i.p.) injections of Bordetella pertussis toxin (PTX; List Biological, Campbell, Calif.) at 200 ng per mouse were given at the time of immunization and 48 hours later (Cardali and Maugeri, Journal of neurosurgical sciences 50, 25-31, 2006). Animals were monitored and graded daily for clinical signs of EAE using the following scoring system (Hall et al., Journal of neurotrauma 22, 252-265, 2005): 0, no abnormality; 1, limp tail; 2, moderate and hind limb weakness; 3, complete hind limb paralysis; 4, quadriplegia or premoribund state; 5, death. Mice for M.sup.2 proteomics were randomly selected and sacrificed at 8 disease time points, described by the number of days (d) post-immunization [−1 d (non-immunized), 0 d (3hrs post-immunization), 5 d, 7 d, 10 d, 15 d, 20 d and 25 d] (n˜20 per time point). These time points were selected to reflect inflection points of pre-onset, disease onset, early disease, disease peak, and remission (for example See
[0087] Cytokine Immunoassays. Antigen-induced T cell responses were assessed in dissociated brain and spleen tissue by enzyme-linked immunosorbent spot (ELISPOT) assay for interferon-γ and interleukin-17A (IFN-γ and IL-17) as previously described (Beer et al., Journal of neurochemistry 75, 1264-1273, 2000) after stimulation with MOG35-55 peptide (United Biochemical Research, Seattle, Wash.). Briefly, ELISPOT plates (Multiscreen IP; Millipore) were coated with anti-IFN-γ (AN-18; 1 μg/mL) or anti-IL-17A (17F3; 2 μg/mL) capture antibodies in phosphate buffered saline (PBS). The plates were blocked with 1% bovine serum albumin (BSA) in PBS for 1 h at room temperature and then washed four times with PBS. After 1 hour of blocking with PBS/1% BSA, cells were added with or without antigen and incubated for 24 h at 37° C. The plates were washed three times with PBS and four times with PBS/Tween 20, and biotinylated anti-IFN-γ (R4-6A2; 0.5 μg/ml) or -IL-17A (eBioTC11-8H4; 0.125 μg/ml) detection antibodies were added and incubated overnight, respectively. Plates were washed four times with PBS/Tween 20 and incubated with streptavidin-alkaline phosphatase (Invitrogen). Cytokine spots were visualized with a BCIP/NBT phosphatase substrate (Kirkegaard & Perry Laboratories, Gaithersburg, Md.). Image analysis of ELISPOT assays was performed a Series 6 Universal-V Immunospot analyzer and Immunospot 5.1 software (Cellular Technology Limited) as described previously (Weiss et al., The Annals of thoracic surgery 88, 543-550, 2009; Jaros et al., Methods in molecular biology 1002, 1-11, 2013). Results for antigen-specific T cells were normalized with a negative control containing peptide-free media. All measurements were performed in duplicate.
[0088] Brain Tissue Lysate. Whole cell protein was extracted from brain tissue using the RIPA Lysis Buffer Kit (Santa Cruz Biotechnology, Inc. Santa Cruz, Calif.) according to the manufacturer's protocol. Briefly, an appropriate amount of RIPA complete lysis buffer was added to cell pellet. The mixture was incubated on ice for 5 minutes, followed by centrifugation at 14000×g for 15 min at 4° C. The supernatant was collected as brain tissue lysate and stored at −80° C. until further use. Protein concentration was determined using Invitrogen EZQ Protein Quantitation Kit (Invitrogen, Grand Island, N.Y.). Protein from all mice (n=157), spanning all time points, was pooled as reference material.
[0089] Microwave and Magnetic (M2) Sample Preparation. For isobaric TMT labeling, protein was pooled from all specimens by protein amount as reference material prior to sample preparation from individual specimens. Approximately 50 mg of C8 magnetic beads (BcMg, Bioclone Inc.) were suspended in 1 mL of 50% methanol. Immediately before use, 100 μL of the beads were washed 3 times with equilibration buffer (200 mM NaCl, 0.1% trifluoroacetic acid (TFA)). Whole cell protein lysate (25-100 μg at 1 μg/μL) was mixed with pre-equilibrated beads and ⅓.sup.rd sample binding buffer (800 mM NaCl, 0.4% TFA) by volume. The mixture was incubated at room temperature for 5 min followed by removing the supernatant. The beads were washed twice with 150 μL of 40 mM triethylammonium bicarbonate (TEAB), and then 150 μL of 10 mM dithiolthreitol (DTT) was added. The bead-lysate mixture underwent microwave heating for 10 s. DTT was removed and 150 μL of 50 mM iodoacetamide (IAA) added, followed by a second microwave heating for 10 s. The beads were washed twice and re-suspended in 150 μL of 40 mM TEAB. In vitro proteolysis was performed with 4 μL of trypsin in a 1:25 trypsin-to-protein ratio (stock=1 μg/μL in 50mM acetic acid) and microwave heated for 20 s in triplicate. The supernatant was used immediately or stored at −80° C. Released tryptic peptides from digested protein lysates, including the reference materials described above, were modified at the N-terminus and at lysine residues with the tandem mass tagging (TMT)-6plex isobaric labeling reagents (Thermo scientific, San Jose, Calif.). Each individual specimen was encoded with one of the TMT-127-130 reagents, while reference material was encoded with the TMT-126 and -131 reagents: 41 μL of anhydrous acetonitrile was added to 0.8 mg of TMT labeling reagent for 25 μg of protein lysate and microwave-heated for 10 s. To quench the reaction, 8 μL of 5% hydroxylamine was added to the sample at room temperature. To normalize across all specimens, TMT-encoded cell lysates from individual specimens, labeled with the TMT-127-130 reagents, were mixed with the reference material encoded with the TMT-126 and -131 reagents in 1.sub.126:1.sub.127:1.sub.128:1.sub.129:1.sub.130:1.sub.131 ratios. These sample mixtures, including all TMT-encoded specimens, were stored at −80° C. until further use.
[0090] Capillary Liquid Chromatography-Fourier-Transform-Tandem Mass Spectrometry (LC/FT/MS/MS) with Protein Database Searching. Capillary LC/FT/MS/MS was performed with a splitless nano LC-2D pump (Eksigent, Livermore, Calif.), a 50 μm-i.d. column packed with 7 cm of 3 μm-o.d. C18 particles, and a hybrid linear ion trap-Fourier-transform tandem mass spectrometer (LTQ-ELITE; ThermoFisher, San Jose, Calif.) operated with a lock mass for calibration. The reverse-phase gradient was 2 to 62% of 0.1% formic acid (FA) in acetonitrile over 60 min at 350 nL/min. For unbiased analyses, the top 6 most abundant eluting ions were fragmented by data-dependent HCD with a mass resolution of 120,000 for MS and 15,000 for MS/MS. For isobaric TMT labeling, probability-based protein database searching of MS/MS spectra against the Trembl protein database (release 2012_dec29; 59,862 sequences) was performed with a 10-node MASCOT cluster (v. 2.3.02, Matrix Science, London, UK) with the following search criteria:peak picking with Mascot Distiller; 10 ppm precursor ion mass tolerance, 0.8 Da product ion mass tolerance, 3 missed cleavages, trypsin, carbamidomethyl cysteines as a static modification, oxidized methionines and deamidated asparagines as variable modifications, an ion score threshold of 20 and TMT-6-plex for quantification.
[0091] ELISA Immunoassays. Commercial ELISA Kits for α-II-spectrin (SEA292Mu) and synapsin-1 (SEC883Mu) were used per the manufacturer's suggested protocol (USCN Life Science Inc), where 500 μg of protein pooled from each time point (n˜20 per group) was added to the corresponding well in each plate. Plates were read at OD 450 nm for absorbance on a Synergy HT microplate reader (BioTek). For serum specimens, serum was collected from mice with mild EAE disease (disease score=1; day 10) or severe disease (score=3-4; day 20) and 1,500 μg of pooled serum samples were analyzed in triplicate with 4-5 mice per pool.
[0092] Prioritization of CSPs and Other Protein Biomarkers. CSPs and other protein biomarkers for MS patients were selected from our dataset by excluding proteins with the following descriptive terms for the protein name found in the Trembl protein database: heat shock, tubulin, histone, albumin, globin, lysosomal, mitochondrial, actin, dehydrogenase, myosin, transferrin, fructokinase, fructose, citrate, cytochrome c, glutathione, microtubule, ATP, clathrin, centromere, NADH, centrosomal, non-neuronal, elongation factor, peroxisomal, annexin, hexokinase, pyruvate, ribosomal, nucleoside, cofilin, titin, transcriptional inhibitory, initiation factor, glutamine, dynamin, RNA, cytoskeleton-associated, transducin, growth factor, vacuolar, tumor-related, phosphorylase, ribonucleoprotein, peptidyl-prolyl cis-trans isomerase, CoA, excision repair, phosphatase, zinc finger, triosephosphate isomerase, adenylyl, and keratin.
[0093] Statistical Analysis. The M2 proteomics results for each technical replicate estimate peptide expression for individual mice, encoded in sample mixtures, relative to pooled reference material from all mice, spanning all time points. Relative peptide expression levels were transformed to log base 2 for quantile normalization. Outlier arrays were removed based upon the following quality control procedures: (1) overall intensity histograms of normalized expression were compared with kernel smoothed density plots, and (2) hierarchical clustering of sample profiles was performed to assess the consistency of technical and biological variation. The association between relative peptide expression and EAE score was tested using a linear mixed-effect while treating EAE score as a continuous predictor. First, the EAE effect on relative peptide expression singly was treated as a univariate predictor. Next, the effects of EAE score were considered by adjusting for time as a quadratic effect. Changes in relative peptide expression with post-immunization time were tested using a linear mixed-effect model in which time was a treated as a multilevel factor. All the pairwise differences in relative peptide expression between all disease time points were tested, including both non-immunized mice (day −1) and 3 hrs post-immunization (day 0), using an unpaired, unequal variance t-test on the replicate averages. The relationship between the overall peptide expression profile with time or EAE score were examined using a hierarchical clustering display based upon Euclidean distance and complete linkage. For clustering analyses of relative peptide expression profiles, the subset of peptides that were most variable were considered by selecting the peptides in the top quartile (top 25%) by their standard deviation ranking Finally, the area under the receiver operating characteristic curve (AUC) were investigated for top-scoring peptides (AUC>0.9) from CSPs and other protein biomarkers, prioritized from the dataset as described above (Koutroukides et al., Journal of separation science 34, 1621-1626, 2011), and compared these values with overall p-values. Proteins were selected only if at least one peptide met the following inclusion criteria: (1) significant differential expression (AUC>0.9) between two post-immunization time points and (2) significant differential expression (overall p-value<1.0E-03) across all post-immunization time points. All statistical analysis was performed with R v3.0.2 (R-Project, Vienna, Austria).
[0094] Pathway and Network Analysis. Pathway and network analysis was performed with Ingenuity Pathways Analysis (IPA, Ingenuity R Systems) according to the manufacturer's suggestions. Briefly, MASCOT results were imported to IPA as .csv files and IPA's core analysis was performed on each file. Differentially expressed proteins corresponding to genes in the IPA knowledgebase were mapped onto canonical signaling pathways and molecular networks per the manufacturer's recommendations. A vertical bar plot, showing the percentage of proteins quantified in each canonical signaling pathway, was visualized to investigate pathway and molecular network enrichment during disease progression, where p-values for enrichment were assigned by IPA.
[0095] B. Results
[0096] The EAE score distribution and disease trajectory for mice that were blindly scored for clinical symptoms, including those randomly selected for analysis with M2 proteomics, are shown in
[0097] Next, expression changes in the CNS proteome were tested in order to prioritize CSPs of EAE. Focus was on analysis of the brain-tissue proteome because MS is a major target of the brain (Peterson et al., Annals of neurology 50, 389-400, 2001; Klaver et al., Prion 7, 66-75, 2013; Lassmann, Philosophical transactions of the Royal Society of London. Series B, Biological sciences 354, 1635-1640, 1999). Overall, decoding isobarically-labeled peptide expression for each specimen relative to pooled reference materials enabled statistical calculations for 1032 peptides from CSPs and other protein biomarkers (from a total of 6608 peptides and 4512 proteins) with significant differential expression between two post-immunization time points (pair-wise time point contrasts) and significant differential expression across all post-immunization time points (overall p-value). Specifically, top-scoring peptides were required to have pair-wise time point contrast with an area under the receiver operating characteristic curve (AUC) greater than 0.9 and an overall p-value of less than 1.0E-03, respectively.
[0098] M2 proteomics revealed characteristic CSP expression waves, including synapsin-1 and α-II-spectrin, which peaked at day 7 in brain tissue and preceded clinical EAE symptoms that began at day 10 and peaked at day 20.
[0099]
[0100] CSPs and other protein biomarkers for MS patients were prioritized and selected from the dataset by excluding non-CSPs with descriptive terms for the protein name found in the Trembl protein database. Consequently, approximately four-fold more peptides (and CSPs) were observed than previously reported by applying the more stringent constraints described above (e.g., overall p-values less than 5.0E-02; AUC calculation). Statistical correlations of peptide expression to EAE score and post-immunization time were also improved and resulted in the identification of new CSP biomarkers, including: synapsin-1 and α-II-spectrin. In addition, the overall p-value previously reported for the peptide LIETYFSK (SEQ ID NO:270) from proteolipid protein 1 improved from 8.0E-04 to 7.9E-12 with the TMT126-labeled reference material. Additional confidence in this result was provided by the TMT131-labeled reference material (overall p-value=4.7E-12). Similar results were obtained for the peptide GLSATVTGGQK (SEQ ID NO:147) from proteolipid protein 1. Lastly, AUC values greater than 0.9 were observed for both peptides.
[0101] In addition to synapsin-1 and α-II-spectrin, differentially expressed CSPs and other proteins included: synapsin-2/3, myelin basic protein, ubiquitin carboxyl-terminal esterase L1, calcium/calmodulin-dependent protein kinase II alpha, neurofilament light and medium, park 2, peroxiredoxin-1/4/5/6, 14-3-3-β/ε/ζ, synaptotagmin, enolase-1/2, guanine nucleotide binding protein α and β1, superoxide dismutase 2, internexin neuronal intermediate filament protein α, tyrosine-protein phosphatase non-receptor type substrate 1, macrophage migration inhibitory factor, proteolipid protein 1, and caspase 7.
[0102] CSP expression waves, revealed with M2 proteomics of brain tissue, were confirmed with ELISAs of representative CSPs in serum specimens from an independent cohort (
[0103] To provide a better understanding of the mechanism underlying the characteristic CSP expression waves, CNS-infiltrating inflammatory cell responses were investigated by immunoassays over the course of EAE. Cytokine ELISPOT assays showed that neuroantigen-reactive T cells producing two well-studied pathogenic cytokines (IFN-γ, and IL-17) could be detected in spleen tissue as early as day 5 after disease induction, and T cell responses peaked by day 15 (
[0104] Overall, the results showed a disproportional relationship between the significant changes in CSP expression detected at day 7 and the very low number of CNS-infiltrating inflammatory cell responses at this time point. Since the magnitude of the peripheral (e.g. spleen or blood) neuroantigen-specific immune response was not correlated to EAE onset or severity, the results show that CSPs are more sensitive biomarkers for inflammatory demyelinating CNS disease than inflammatory biomarkers such as cytokines. Moreover, CSPs are also expected to be more specific biomarkers for early detection of EAE because they are not expected at appreciable levels in healthy controls, whereas neuroantigen-specific immune responses can be detected in healthy individuals (Encinas et al., Journal of immunology 157, 2186-2192, 1996; Bahmanyar et al., Journal of neuroimmunology 5, 191-196, 1983).
[0105] Stratification of risk groups was further investigated with non-supervised and supervised hierarchical clustering of relative peptide expression and/or post-immunization time. Non-supervised hierarchical clustering did not accurately stratify subjects by post-immunization time. However, many nearest neighbor misclassifications, where subjects were incorrectly grouped adjacent to one another rather than one group removed from one another, such misclassifications between day −1 and day 0 or day 10 and day 15, were observed across all top-ranked proteins (
[0106] Pathway and network analysis showed enrichment of differentially expressed CSPs and other proteins in specific signaling pathways and molecular networks. For example, P-values for enrichment of the top-ranked molecular network entitled “neurological disease and motor dysfunction” in the Ingenuity knowledgebase were most significant at day 7, coinciding with characteristic CSP expression waves. Enrichment of other key pathways that might be important to MS patients, such as the 14-3-3 signaling pathway, were also observed to peak at day 7.
[0107] M2 proteomics of brain tissue has been shown to be an effective means to prioritize CSP biomarkers for immunoassays in CSF and serum, by measuring changes in the brain during the disease as previously suggested (Raphael et al., Electrophoresis 33, 3810-3819, 2012; Hu et al., Proteomics 6, 4321-4334, 2006; Robinson et al., Opinion. Current opinion in immunology 15, 660-667, 2003). First, M2 proteomics of CSPs in brain tissue was shown to reveal characteristic CSP expression waves that preceded the onset of clinical EAE symptoms. Second, the CNS-infiltrating inflammatory cell response and CSP expression trajectories in serum were confirmed with cytokine ELISPOT and ELISA immunoassays, respectively, for selected CSPs found to have significant expression changes prior to clinical onset. Based on these results M2 proteomics of CSPs in brain tissue is an effective means to prioritize CSP biomarkers for immunoassays in serum and/or other body fluids (e.g., CSF).
TABLE-US-00001 TABLE 1 Synapsin 1 (A2AE14_MOUSE) peptides with an AUC greater than 0.9. Post-immunization time contrast (e.g., Overall p- Overall p- day 0 vs. day 7) Peptide Sequence AUC126 AUC131 value 126 value 131 -1 5 VKVDNQHDFQDIASVVALTK (SEQ ID NO: 499) 1.00 1.00 5.0E-09 1.9E-13 -1 7 LGTEEFPLIDQTFYPNHK (SEQ ID NO: 265) 0.98 0.98 3.6E-05 9.5E-04 -1 7 MGHAHSGMGK (SEQ ID NO: 341) 1.00 0.99 1.6E-25 5.9E-22 -1 7 QHAFSMAR (SEQ ID NO: 384) 1.00 1.00 1.3E-19 4.1E-14 -1 7 TSVSGNWK (SEQ ID NO: 475) 1.00 0.99 1.7E-10 1.7E-09 -1 7 VKVDNQHDFQDIASVVALTK (SEQ ID NO: 499) 1.00 1.00 5.0E-09 1.9E-13 -1 7 VLLVIDEPHTDWAK (SEQ ID NO: 503) 0.98 0.99 5.9E-14 4.6E-13 -1 10 KLGTEEFPLIDQTFYPNHK (SEQ ID NO: 235) 0.94 0.96 3.6E-04 1.4E-06 -1 10 LGTEEFPLIDQTFYPNHK (SEQ ID NO: 265) 0.98 0.94 3.6E-05 9.5E-04 -1 10 QHAFSMAR (SEQ ID NO: 384) 0.90 0.92 1.3E-19 4.1E-14 -1 10 TSVSGNWK (SEQ ID NO: 475) 0.98 0.96 1.7E-10 1.7E-09 -1 10 VKVDNQHDFQDIASVVALTK (SEQ ID NO: 499) 1.00 1.00 5.0E-09 1.9E-13 -1 15 LGTEEFPLIDQTFYPNHK (SEQ ID NO: 265) 0.94 0.97 3.6E-05 9.5E-04 -1 15 MGHAHSGMGK (SEQ ID NO: 341) 0.94 0.95 1.6E-25 5.9E-22 -1 15 QHAFSMAR (SEQ ID NO: 384) 0.93 0.96 1.3E-19 4.1E-14 -1 15 TSVSGNWK (SEQ ID NO: 475) 0.95 0.95 1.7E-10 1.7E-09 -1 20 VKVDNQHDFQDIASVVALTK (SEQ ID NO: 499) 0.96 1.00 5.0E-09 1.9E-13 0 7 MGHAHSGMGK (SEQ ID NO: 341) 0.99 0.96 1.6E-25 5.9E-22 0 7 QHAFSMAR (SEQ ID NO: 384) 1.00 1.00 1.3E-19 4.1E-14 0 7 SLKPDFVLIR (SEQ ID NO: 434) 0.95 0.94 1.6E-11 5.0E-10 0 7 VKVDNQHDFQDIASVVALTK (SEQ ID NO: 499) 1.00 1.00 5.0E-09 1.9E-13 0 7 VLLVIDEPHTDWAK (SEQ ID NO: 503) 0.96 0.91 5.9E-14 4.6E-13 5 7 EMLSSTTYPVVVK (SEQ ID NO: 91) 0.92 0.95 1.7E-07 1.6E-03 5 7 GSHSQSSSPGALTLGR (SEQ ID NO: 163) 0.99 0.95 8.1E-12 1.9E-08 5 7 MGHAHSGMGK (SEQ ID NO: 341) 0.99 0.98 1.6E-25 5.9E-22
[0108] Proteomics analysis of CNS in the pre-onset phase reveals a list of biomarkers to predict disease onset. M2-proteomics identified several potential protein biomarkers in a pre-clinical model (EAE) of MS (for example see table 1 and