Protein biomarkers of inflammatory activity in multiple sclerosis

Abstract

The present invention includes a method of treating a subject suffering from recurrent-remitting multiple sclerosis (RRMS) that is experiencing recurrence, comprising: determining that a sample of the same type from a subject or population of subjects that does not suffer from RRMS is less than a sample of the same type from a subject or population of subjects that does not suffer from RRMS; the expression level of two or more biomarkers selected from the group consisting of a urokinase plasminogen activator (uPA), kallikrein 8 (hK8), kallikrein 11 (hK11) or desmoplasmin 3 (DSG3) in a biological sample of the subject, determining the expression level of two or more biomarkers selected from the group consisting of urokinase plasminogen activator (uPA), kallikrein 8 (hK8), kallikrein 11 (hK11) and desmoplasmin 3 (DSG3); if the expression level of the two or more biomarkers in the subject is reduced, diagnosing the subject being experiencing recurrence; and administering to the subject a therapeutically effective amount of a treatment for RRMS.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application Serial No. 63 / 312,168, filed on February 21, 2022, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present invention relates generally to the field of novel protein biomarkers and, more particularly, to novel protein biomarkers of inflammatory activity in multiple sclerosis (MS).

[0004] Statement on Federally Sponsored Research

[0005] This invention was made with government support under R01AI137047 and R01EY027346 awarded by the National Institutes of Health. The government has certain rights in this invention. Background Art

[0006] Without limiting the scope of the invention, the background of the invention is described in conjunction with multiple sclerosis (MS).

[0007] Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS) that affects more than 2.5 million people worldwide. It is thought to be triggered by an autoimmune response to CNS antigens, leading to the destruction of myelin and neurons and disabling the patient [1]. Approximately 85% of MS patients are diagnosed with an initial relapsing and remitting disease process. A relapse (MS attack or exacerbation) is defined as a new or worsening clinical symptom followed by a period of remission in which the patient partially or completely recovers. Disability accumulates when the patient does not fully recover normal function. It is often difficult to determine whether the patient is experiencing a true relapse or a pseudo-relapse that is confused by infection and comorbidities [2]. Gadolinium MRI contrast scans are often used to verify relapses [3]. However, MRI is expensive and can miss the location of lesions. Repeated gadolinium exposure creates toxicity issues [4]. In many cases, MRI is used when clinical signs are already evident and inflammatory damage has already occurred. In addition, CSF oligoclonal bands and IgG indices are helpful for diagnosis but are not used to predict relapses and progression (Becker M et al). Therefore, inexpensive, non-invasive methods for detecting recurrence are highly desirable and would benefit both clinical trials and clinical practice.

[0008] Neurofilaments are cytoskeletal proteins released from damaged axons into the cerebrospinal fluid (CSF) and blood. Recent technologies allow the detection of serum neurofilament light chain (sNfL) and show that it is elevated in MS patients with impending or recent clinical relapse [5-8]. However, elevated sNfL is also associated with other neurodegenerative diseases and increased age in healthy populations [9-11]. This raises questions about the specificity of sNfL as a marker for MS relapse. In addition, the reliable detectability of NfL levels in the blood is a problem. Only a small portion of sNfL leaked from the damaged CNS was detected in the blood. Therefore, even with the most sensitive single molecule array (SiMoA) technology, slight disease-related fluctuations in sNfL levels may not be detected, which questions the sensitivity of using only sNfL as a blood-based biomarker for MS

[12] .

[0009] Relapsing-remitting multiple sclerosis (RRMS) is characterized by the onset of new or worsening clinical symptoms followed by recovery. In addition to clinical manifestations and MRI, biomarker development is needed. Serum neurofilament light chain (sNfL) has emerged as a biomarker of inflammatory activity in MS. However, sNfL has limitations in terms of sensitivity and specificity in identifying relapses.

[0010] Therefore, what is needed are biomarkers that distinguish patients who are experiencing a relapse from those who are experiencing a pseudo-relapse, and / or biomarkers that can be used as an alternative to MRI to monitor treatment response in a clinical trial setting. Summary of the invention

[0011] As embodied and broadly described herein, one aspect of the disclosure relates to a method of treating a subject with relapsing-remitting multiple sclerosis (RRMS) who is experiencing a relapse, comprising: (a) determining the expression level of two or more biomarkers selected from urokinase plasminogen activator (uPA), kallikrein-8 (hK8), kallikrein-11 (hK11), or desmoglein-3 (DSG3) in a biological sample of the subject compared to a sample of the same type from a subject or subject population that does not have RRMS; (b) diagnosing the subject in (a) as experiencing a relapse if the expression level of the two or more biomarkers in the subject is reduced; and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the biomarker is uPA, hK8, hK11, or DSG3. In another aspect, the method further comprises determining the expression level of NfL, uPA, hK8, hK11, or DSG3, wherein the combination of biomarkers achieves a higher area under the curve compared to NfL alone. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, diroximel fumarate, cladribine, siponimod, ocrelizumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, ublituximab, steroids, adrenocorticotropic hormone (ACTH) or ponesimod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or cerebrospinal fluid (CSF). In another aspect, the relapse is an acute phase relapse.In another aspect, the relapse is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernamod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of steroid therapy results in a decrease in the expression level of FKBP5.

[0012] As embodied and broadly described herein, one aspect of the disclosure relates to a method for determining whether a subject with relapsing-remitting multiple sclerosis (RRMS) with elevated levels of an NfL biomarker is experiencing a relapse or will relapse, comprising: (a) determining the expression level of one or more biomarkers selected from uPA, hK8, hK11 or DSG3 in a biological sample from the subject compared to the same sample from a subject or a population of subjects not having RRMS, wherein the combination of the NfL biomarker and the one or more biomarkers selected from uPA, hK8, hK11 or DSG3 has greater sensitivity and selectivity than using the NfL biomarker alone; (b) diagnosing the subject in (a) as experiencing a relapse if the expression level of the uPA, hK8, hK11 or DSG3 is decreased, and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the method comprises selecting 2, 3 or 4 biomarkers selected from uPA, hK8, hK11 or DSG3. In another aspect, the method of claim 10, further comprising determining the expression level of NfL, uPA, hK8, hK11 or DSG3 and calculating the area under the curve, wherein the combination of biomarkers reaches an area under the curve of at least 0.87. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernemod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or CSF. In another aspect, the recurrence is an acute phase recurrence. In another aspect, the recurrence is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker or a combination thereof. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5.

[0013] As embodied and broadly described herein, one aspect of the disclosure relates to a method for detecting a relapse in a subject with relapsing-remitting multiple sclerosis (RRMS), comprising: (a) determining the expression level of two or more biomarkers selected from uPA, hK8, hK11 or DSG3 in a biological sample of the subject compared to the same sample from a subject or subject population not having RRMS, and wherein one of the biomarkers is not an NfL biomarker, wherein the two or more biomarkers selected from uPA, hK8, hK11 or DSG3 have greater sensitivity and selectivity than the NfL biomarker alone; (b) if the expression level of the two or more biomarkers in the subject decreases, diagnosing the subject in (a) as experiencing a relapse, and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the method comprises selecting 2, 3 or 4 biomarkers selected from uPA, hK8, hK11 or DSG3. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or CSF. In another aspect, the relapse is an acute phase relapse. In another aspect, the relapse is from a patient who has previously received at least one of the following and is selecting a new treatment: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof. In another aspect, samples from subjects with RRMS have previously been detected to have higher NfL expression levels than samples from subjects without RRMS. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] For a more complete understanding of the features and advantages of the present invention, reference is now made to the detailed description of the invention and to the accompanying drawings, wherein:

[0015] Figures 1A to 1F The quality control (QC) of the proximity extension assay (PEA) is shown. The expression levels of 724 serum proteins were evaluated by two independent runs (Run 1 and Run 2). Figure 1A ) Pearson's correlation coefficient (r) was determined for all 724 proteins. Figure 1B ) shows a table of serum proteins belonging to each group defined by the range of r. Group 1 serum protein NFL ( Figure 1C ) and Notch 3( Figure 1D ), group 2 serum protein IL-7R ( Figure 1E ) and group 3 serum protein IL2 ( Figure 1F )’s correlation diagram.

[0016] Figures 2A to 2D Serum protein profiles distinguishing RRMS patients from healthy controls are shown. ( Figure 2A ) compared serum protein profiles of RRMS (n=64) and healthy controls (n=20). Significant proteins were identified using unpaired t-test with multiple comparisons corrected by Bonferroni and Hochberg method, setting the False Discovery Rate (FDR) to 5%. ( Figure 2B ) performed PCA analysis of serum proteins that were significantly different between RRMS and healthy controls. Also performed ( Figure 2C RRMS and Figure 2D ) Gene Ontology (GO) analysis of serum proteins elevated in healthy controls.

[0017] Figures 3A to 3C Serum protein profiles that distinguish relapses and remissions in MS patients are shown. ( Figure 3A ) compared serum protein profiles of relapsing (n=24) and remitting (n=40) MS patients. Significant proteins were identified using an unpaired t-test with multiple comparisons, setting a p-value threshold of ≤0.05. ( Figure 3B ) Unsupervised hierarchical clustering analysis of proteins that were significantly different between patients in relapse and remission divided the patients into two groups, Group 1 and Group 2. ( Figure 3C) Pie chart depicts the frequency of patients in relapse or remission in Group 1 and Group 2. Chi-squared test showed statistical significance between Group 1 and Group 2, p<0.0001.

[0018] Figures 4A to 4I shows that steroids alter the serum protein profile of patients with MS relapses. ( Figure 4A )Classification of RRMS patients based on disease status and steroid use. The following serum protein profiles were compared: Figure 4B ) Patients with MS relapses and MS remissions treated with steroids, Figure 4C ) patients with MS relapses and MS remissions who were not treated with steroids, and ( Figure 4D )MS relapse patients treated with steroids and MS relapse patients not treated with steroids. Significant proteins were identified using unpaired t-test with multiple comparisons, setting a p-value threshold of ≤ 0.05. Figure 4E ) Venn diagram of differentially abundant serum proteins comparing relapse (steroids) vs remission and relapse (steroids) vs relapse (no steroids). Comparisons were made between MS relapsing patients using steroids, MS relapsing patients not using steroids, and MS remission patients ( Figure 4F )FKBP5 and ( Figure 4H ) Serum protein levels of NFL. One-way ANOVA was used to determine the p value, and p < 0.05 was significant. Figure 4G )FKBP5 and ( Fig. 4I ) Serum protein levels of NFL were correlated with the number of weeks after steroid use. p values ​​< 0.05 were considered significant.

[0019] Figures 5A to 5C Results from monitoring longitudinal changes in serum proteins from relapse to remission are shown. Figure 5A )Fold changes of serum proteins that were significantly different between MS relapse and remission. Significant proteins were identified using paired t-test with multiple comparisons, setting a p-value threshold of ≤ 0.05. Figure 5B ) Serum levels of NFL were compared between MS patients in remission, MS relapse patients not treated with steroids, and MS relapse patients treated with steroids using ordinary one-way ANOVA. P values ​​< 0.05 were considered significant. Figure 5C ) Regression of NFL serum levels in MS relapses as a function of weeks after relapse. P values ​​< 0.05 were considered significant.

[0020] Figures 6A to 6D The serum protein panel was shown to classify MS relapses with higher accuracy than NFL alone. Fig. 6A ) Venn diagram comparing significantly enriched proteins between MS relapses and remissions from the OMRF and Stanford cohorts. ( Figure 6B ) The table shows six serum analytes that were significantly different between relapse and remission in the OMRF and Stanford cohorts. ( Figure 6C ) Receiver Operating Characteristic (ROC) curves were examined for the predictive performance of serum protein biomarkers for identifying MS relapses in a longitudinal cohort. Fig.6D ) shows a table of AUC scores for all regression models.

[0021] Figure 7 is a graph showing the AUC for various combinations. DETAILED DESCRIPTION

[0022] Although the manufacture and use of multiple embodiments of the present invention are discussed in detail below, it should be understood that the present invention provides many applicable inventive concepts that can be embodied in a wide variety of specific contexts. Some specific embodiments discussed herein are only examples of specific ways to manufacture and use the present invention and do not limit the scope of the present invention.

[0023] In order to promote understanding of the present invention, many terms are defined below. The terms defined herein have the meanings commonly understood by those of ordinary skill in the field relevant to the present invention. Terms without quantifier modification are not intended to refer only to a single entity, but include general categories that can be illustrated using their specific examples. The terms herein are used to describe some specific embodiments of the present invention, but except for those outlined in the claims, their use does not limit the present invention.

[0024] The inventors used a large-scale, non-targeted multiplex proteomic assay to discover relapse-associated protein markers in MS patients. The inventors identified novel proteins associated with relapse in MS patients and determined that the protein marker panel improved the sensitivity and specificity of identifying relapse compared to using sNfL as the only marker.

[0025] More specifically, the inventors used multiple assays to measure the levels of blood proteins in two different RRMS patient groups. The first group was a cross-sectional group of 64 patients and 20 healthy controls. The second group was a longitudinal group of 12 patients. The levels of 724 proteins in the two groups were assessed using the proximity extension assay (PEA) from Olink Biosciences. Blood protein profiling was performed using multiple paired and unpaired t-tests and age and gender covariate corrections. A logistic regression model was generated for identifying relapsed patients, and the area under the curve (Area under the Curve, AUC) was used as a comparative measure.

[0026] In the cross-sectional cohort, the inventors identified 5 elevated proteins (including NfL) and 41 decreased proteins in patients experiencing relapse. In the longitudinal study, the inventors found that in patients with relapse, 10 proteins (including NfL) were elevated and 26 proteins were decreased. Next, the inventors compared the differentially abundant proteins in relapse and remission in the cross-sectional and longitudinal cohorts, and identified 5 proteins shared by relapsers and non-relapsers. Finally, using logistic regression analysis to generate a receiver operating characteristic (ROC) curve, the inventors found that 5 common proteins can identify relapse in patients with higher accuracy (AUC = 0.87) than sNfL alone (AUC = 0.71).

[0027] Using two different RRMS patient cohorts, these studies confirmed that sNfL levels are elevated during relapse. In addition, the inventors identified 4 new blood proteins that are differentially abundant during relapse. In summary, these blood biomarkers can be used as a panel to monitor disease activity in RRMS patients.

[0028] As used herein, "biological sample" refers to a biological sample derived from a body fluid, such as blood, preferably peripheral (or circulating) blood or cerebrospinal fluid. The blood sample can be, for example, whole blood, serum, or plasma. In certain embodiments, serum can be used as a source of biomarkers because the sample is easily available and is commonly obtained for other sampling, serum is stable, and requires less processing, thus making it ideal for places with little refrigeration or electricity, serum is easy to transport, and is usually handled by medical support personnel.

[0029] In certain embodiments, the expression level of the selected biomarkers is measured in a blood, plasma, serum or cerebrospinal fluid sample obtained from the subject. In some embodiments, the expression level of one or more biomarkers is compared to the expression level of the corresponding one or more biomarkers in a statistical sample representative of the subject, wherein the comparison is used to determine whether the subject needs to be screened for relapsing-remitting multiple sclerosis (RRMS).

[0030] As used herein, a "normal" individual or a sample from a "normal" individual refers to quantitative data, qualitative data, or both from an individual who has been or will be assessed by a physician as not having relapsing-remitting multiple sclerosis (RRMS). Typically, a "normal" individual is also age-matched to the sample of the individual to be assessed within the range of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 years.

[0031] As used herein, the term "treatment" refers to the alleviation, improvement and / or stabilization of symptoms of a particular condition, specifically, relapsing-remitting multiple sclerosis (RRMS), as well as the delay of symptom progression. For example, "treatment" of multiple sclerosis (MS) includes any one or more of the following: (1) eliminating one or more symptoms of MS, (2) alleviating one or more symptoms of MS, (3) stabilizing symptoms of MS (e.g., not progressing to a more advanced stage of MS), and (4) delaying the onset of one or more symptoms of MS; and (5) delaying the progression (i.e., worsening) of one or more symptoms of MS. The treatment for MS used in the present invention includes providing a therapeutic agent to a patient suspected of having RRMS based on the detection of the biomarkers herein, wherein the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernemod.

[0032] In some embodiments, one or more biomarkers include uPA, hK8, hK11 or DSG3. In some embodiments, two or more biomarkers include uPA and hK8. In some embodiments, three or more biomarkers include uPA, hK8 and hK11. In some embodiments, four biomarkers include uPA, hK8, hK11 and DSG37. In some embodiments, five biomarkers include uPA, hK8, hK11, DSG3 and NfL. In some embodiments, four or more biomarkers include hK8, hK11, DSG3 and NfL. In some embodiments, three or more biomarkers include hK11, DSG3 and NfL. In some embodiments, two or more biomarkers include DSG3 and NfL. In some embodiments, one or more biomarkers include uPA, hK11, DSG3 and NfL. In some embodiments, one or more biomarkers include uPA, hK8, DSG3 and NfL. In some embodiments, one or more biomarkers include uPA, hK8, hK11 and NfL. In some embodiments, one or more biomarkers include uPA, DSG3 and NfL. In some embodiments, one or more biomarkers include hK8, hK11 and NfL. In some embodiments, one or more biomarkers include uPA, hK11, DSG3 and NfL. In some embodiments, one or more biomarkers include uPA, hK8, DSG3 and NfL. In some embodiments, one or more biomarkers include hK8, hK11 and DSG3. In some embodiments, one or more biomarkers include uPA, hK11 and DSG3. In some embodiments, one or more biomarkers include uPA, hK8 and DSG3. In some embodiments, one or more biomarkers include uPA, hK8 and hK11. In some embodiments, one or more biomarkers include uPA and DSG3. In some embodiments, one or more biomarkers include hK8 and DSG3. In some embodiments, one or more biomarkers include hK11 and DSG3.

[0033] Patient cohort. Cross-sectional cohort: Serum samples were collected from 64 RRMS patients and 20 healthy donors at the Multiple Sclerosis Center of Excellence, Oklahoma Medical Research Foundation (OMRF). Demographic information of OMRF MS patients and healthy controls is shown in Supplementary Table 1. MS relapse is defined as new or worsening clinical symptoms lasting for more than 48 hours in the absence of fever, infection, or other confounding medical conditions. It was further determined using both clinical assessment and the presence of an increase in gadolinium-enhanced lesions using magnetic resonance imaging (MRI)

[13] . All serum samples were obtained before the start of disease-modifying therapy (DMT).

[0034] Longitudinal cohort: Paired plasma samples were collected from 12 RRMS patients from the Stanford MS Clinic. Demographic and treatment information of Stanford RRMS patients is shown in Supplementary Table 2. Samples were collected from these patients during clinical relapse and remission (0 to 19 months).

[0035] For both groups, patients were diagnosed with RRMS by a board-certified neurologist using the McDonald criteria

[13] . Written informed consent was obtained from individuals prior to participation in the study, which was approved by the Institutional Review Board of the Oklahoma Medical Research Foundation. Samples were assayed without knowledge of clinical data.

[0036] Protein quantification. Protein was measured using the proximity extension assay (PEA) technique

[14] with Olink cardiac metabolism, cardiovascular III, development, inflammation, neural exploration, neurology, oncology II, and oncology III panels. Overall, the present inventors used multiplex assays to measure blood protein levels in two different cohorts of RRMS patients. The first cohort was a cross-sectional cohort of 64 patients and 20 healthy controls. The second cohort was a longitudinal cohort of 12 patients. The levels of 724 proteins were evaluated in both cohorts using the proximity extension assay (PEA) from Olink Biosciences. Blood protein profiling was performed using multiple paired and unpaired t-tests with age and sex covariate correction. A logistic regression model was generated for identifying relapsing patients, and the area under the curve (AUC) was used as a comparative metric. The expression levels of 724 proteins were measured. Data were represented as base-2 logarithm-normalized protein expression (NPX) values. For quality control of PEA

[14] , the expression levels of all 724 serum proteins were measured from two independent runs from 20 individuals from the OMRF cohort and further correlated between the two runs.

[0037] Statistical analysis. Pearson correlation coefficient (r) analysis was performed using the cor function

[15] from stats v4.0.5 in R to test the correlation between the NPX values of 724 proteins in two independent runs. Proteins with Pearson coefficient r > 0.75 were considered strongly correlated; 0.5 < r < 0.75 was considered moderately correlated; and -0.5 < r < 0.5 was considered weakly correlated. Significantly different proteins were determined using limma v3.46

[16] in the Bioconductor suite in R using the following: multiple t-tests corrected by the Bonferroni and Hochberg methods, with a false discovery rate (FDR) of 5%. Principal components analysis (PCA) was performed using the prcomp function

[15] in R, and the principal components with the highest variance - PC1 and PC2 - were plotted against each other. Gene ontology analysis was performed using the STRING database

[17] for functional annotation of significantly different proteins.

[0038] Logistic regression analysis was performed using caret v6.0-88

[18] in R to generate univariate or multivariate prediction models that estimate the probability of identifying relapses and remissions in RRMS patients. Repeated 10-fold cross validation

[18] was used to correct for the bias caused by validating the model on the same data set used to generate the model. Receiver operating characteristic (ROC) curves were generated using the probabilities from each model, and the effectiveness of each model for classifying relapses and remissions in MS patients was evaluated using MLeval v0.3

[19] in R. The area under the curve of the ROC curve (AUC-ROC) was used to determine the classification accuracy of each model. All of these statistical analyses were performed in R (3.6.2, 4.0.5)

[15] .

[0039] Individual serum protein levels were compared using unpaired t-tests with a significance of p < 0.05. Serum proteins that were significantly different between paired relapses and remissions in the longitudinal cohort were determined using multiple t-tests with a significance of p < 0.05. NfL and FKBP5 NPX values ​​were correlated with weeks after steroid treatment cessation using linear regression.

[0040] Quality control of proximity extension assay (PEA), a multiplex protein biomarker assay. The use of multiplex methods to measure serum proteins has been widely used in many diseases, including MS [20-22]. The accuracy and reproducibility of serum protein measurements are crucial for the discovery of robust biomarkers. In this study, the inventors used multiplex assays to measure blood protein levels in two different RRMS patient cohorts. The first cohort was a cross-sectional cohort of 64 patients and 20 healthy controls. The second cohort was a longitudinal cohort of 12 patients. The levels of 724 proteins in the two cohorts were assessed using the proximity extension assay (PEA) from Olink Biosciences. Blood protein profile analysis was performed using multiple paired and unpaired t-tests and age and gender covariate corrections. A logistic regression model was generated for identifying relapsed patients, and the area under the curve (AUC) was used as a comparative measure. The levels of 724 serum proteins in RRMS patients and healthy controls were measured using the proximity extension assay (PEA) with the aim of identifying potential biomarkers associated with patient disease activity. PEA is a relatively new antibody-based analyte detection technology. Therefore, the inventors first determined the reproducibility of each protein measurement in 20 serum samples from a cross-sectional study group consisting of six healthy donors, eight relapsed patients, and six remission patients. The inventors performed PEA on these 20 samples in two independent runs and correlated the relative levels of 724 serum proteins from Run 1 and Run 2 using the Pearson correlation coefficient r ( Figure 1A ).

[0041] Based on the correlation values, the inventors found that 448 proteins were highly reproducible with r>0.75 (Group 1), 185 proteins were moderately reproducible with r values ​​between 0.5 and 0.75 (Group 2), and 91 proteins were poorly reproducible with r values ​​between -0.5 and 0.5 (Group 3) ( Figure 1B Some examples of highly reproducible proteins are neurofilament light chain (NfL) ( Figure 1C ) and Notch 3( Figure 1D An example of a moderately reproducible protein is the interleukin-7 receptor (IL-7R) ( Figure 1E An example of a protein with poor reproducibility is interleukin-2 (IL-2) ( Figure 1F ). For this study, the inventors considered that 448 proteins with r>0.75 had passed quality control (QC), and these will be used for subsequent analysis of both cohorts.

[0042] MS patients can be distinguished from healthy donors based on their serum protein signature. The inventors next determined whether serum protein markers could distinguish RRMS patients from healthy donors. For this analysis, the inventors compared the levels of 448 serum proteins that passed QC in RRMS patients and healthy controls using multiple unpaired t-tests (setting the false discovery rate (FDR) to 5%), and adjusted for age and gender as covariates. The inventors identified 156 of the 448 proteins as significantly different between RRMS patients and healthy controls. Of these 156 proteins, 37 were elevated and 119 were decreased in RRMS patients compared to healthy controls ( Figure 2A Next, the inventors performed principal component (PC) analysis to determine whether RRMS patients and healthy controls could be distinguished based on the levels of these 156 proteins. Based on PC1 and PC2, which explained 40.7% and 8% of the variance, respectively, the inventors could cluster RRMS patients and healthy controls into two different groups ( Figure 2B). Gene Ontology (GO) database analysis identified the biological pathways to which these 156 significantly different proteins belonged. Of these 156 proteins, 152 mapped to eight GO pathways belonging to the immune (GO:0002376, GO:0002682, GO:0006952), neural (GO:0007399), and other (GO:0050789, GO:0050896, GO:0048856, GO:0009987) systems. Of the proteins elevated in RRMS patients, 29.7% mapped to immune system pathways, 29.7% mapped to nervous system pathways, and 40.6% mapped to pathways belonging to other systems ( Figure 2C ). However, for proteins decreased in RRMS patients, 59.66% mapped to immune system pathways and 40.34% mapped to pathways belonging to other systems. None of the proteins decreased in RRMS patients compared to healthy controls mapped to nervous system pathways ( Figure 2D ). These data highlight the critical involvement of the nervous system in the pathogenesis of MS and provide evidence that neural damage in MS can be detected in serum using the PEA assay.

[0043] Serum protein signatures can distinguish between relapse and remission disease states in MS patients. In the cross-sectional cohort, 24 patients were experiencing clinical relapses (confirmed by active enhancing lesions measured by MRI), and 40 patients were in remission. Using PEA, the inventors identified whether serum protein levels can distinguish between relapses and remissions in these patients. The inventors used multiple unpaired t-tests (setting p-value threshold <0.05) to compare the levels of 448 serum proteins (that have passed QC) in patients with relapses with those in remission, and adjusted for age and gender as covariates. The inventors found that compared with remission MS patients, 5 proteins in relapsed MS patients were increased and 41 proteins were decreased ( Figure 3A Next, the inventors performed an unsupervised hierarchical cluster analysis on all MS patients based on the expression levels of these 45 significantly different proteins. This analysis found that MS patients were divided into two separate groups, Group 1 and Group 2 ( Figure 3B Group 1 consisted entirely of MS patients in remission. Group 2 consisted of 70% of MS patients in remission and 30% of MS patients in remission ( Figure 3C ). Thus, these data suggest that MS patients in clinical relapse or remission can be distinguished based on their serum protein profile.

[0044] Intravenous steroid therapy changes the serum protein profile of relapsing MS patients. High-dose corticosteroids administered intravenously or orally are short-term drugs for treating clinical relapses in MS patients [23, 24]. It has been shown that the administration of steroids reduces inflammation by reducing the migration of autoreactive immune cells into the CNS, inducing apoptosis of autoreactive leukocytes, and reducing the production of inflammatory cytokines [25-28]. Therefore, the inventors next determined whether steroid therapy affects the serum protein profile of relapsing MS patients. In a cross-sectional cohort, 13 of 24 relapsing MS patients received high doses of IV and / or oral steroids during or before blood draw, while the remaining 11 did not have steroids ( Figure 4A ). The present inventors performed three comparative analyses, including an analysis comparing serum protein levels in: (1) relapsing MS patients using steroids vs. remission MS patients, (2) relapsing MS patients not using steroids vs. remission MS patients, and (3) relapsing MS patients using steroids vs. relapsing MS patients not using steroids. A multiple unpaired t-test with a p-value threshold of <0.05 and adjustment for age and sex as covariates was used for this analysis. It was found that 9 proteins were elevated and 24 proteins were decreased in relapsing MS patients using steroids compared with remission MS patients ( Figure 4B The present inventors also identified that 3 proteins were elevated and 36 proteins were decreased in relapsing MS patients not using steroids compared with remission MS patients ( Figure 4C In addition, the present inventors determined that 26 proteins were elevated and 3 proteins were decreased in relapsing MS patients using steroids compared to relapsing MS patients not using steroids ( Figure 4D ).

[0045] The inventors identified proteins strongly associated with steroid treatment in this relapsing MS patient cohort by examining the common differentially abundant proteins between the following comparisons: (1) relapsing MS patients using steroids vs. remission MS patients, and (2) relapsing MS patients not using steroids vs. remission MS patients. The inventors observed seven common proteins in this analysis ( Figure 4E ). Among the serum proteins significantly altered in steroid patients, FK506 binding protein 51 (FKBP5) and NfL are of interest. The expression of FKBP5 is directly increased in response to steroid binding to the glucocorticoid receptor on cells [29,30]. In this patient cohort, FKBP5 levels were significantly increased in relapsing MS patients who were taking steroids compared to relapsing MS patients who were not taking steroids ( Figure 4F ). It was also found that in relapsing MS patients, FKBP5 levels decreased significantly over time after cessation of steroid treatment ( Figure 4G). These data suggest that the biological effects of steroid therapy can be monitored with the aid of serum levels of FKBP5. It is also interesting that NfL levels were significantly increased in relapsing MS patients using steroids compared to both relapsing MS patients and remission MS patients not using steroids ( Figure 4H However, after cessation of steroid treatment, NfL serum levels did not decrease significantly over time ( Fig. 4I ), suggesting that the increase in NfL levels is not a direct effect of steroid treatment in these patients. These data suggest that the administration of high-dose steroids affects the serum protein profile of relapsing MS patients and is a confounding factor to be considered in biomarker discovery.

[0046] Longitudinal changes in blood protein levels from relapse to remission. In order to verify these findings from the above-mentioned cross-sectional cohort, the inventors evaluated blood proteins in a separate longitudinal cohort, where patients were drawn blood during relapse and remission. Using a multiple paired t-test with a p-value threshold <0.05, the expression levels of blood proteins (passed QC) in longitudinal blood draws from 12 RRMS patients during relapse and remission were compared. In this cohort, 10 proteins identified in relapsed MS patients were elevated and 26 proteins were reduced ( Figure 5A ). Notably, NfL was the blood protein most elevated in relapse, and NfL levels were negatively correlated with the length of time from relapse to blood draw ( Figure 5B In this group, only two patients in relapse were on acute steroid therapy at the time of blood draw. NfL levels were not highly abundant in the blood of these relapse patients on steroids ( Figure 5B ). This further suggests that steroid treatment does not directly affect serum NfL levels during active relapse.

[0047] The blood proteome identified MS relapses with greater accuracy than NfL alone. Next, we identified proteins that were common to both the cross-sectional and longitudinal study cohorts and that were significantly different in relapse and remission ( Fig. 6A ). Six proteins were found to be common between the two groups. NfL was the only protein that was elevated in relapses in both studies. While urokinase plasminogen activator (uPA), kallikrein-8 (hK8), kallikrein-11 (hK11), and desmosome mucin-3 (DSG3) were all decreased in relapses in both groups. Although mannose binding lectin 2 (MBL2) was significantly different in the two groups, the inventors found that it was decreased in relapses in the cross-sectional group, but increased in relapses in the longitudinal group ( Figure 6B ).

[0048] Although serum NfL is considered a marker for relapse in MS patients, there are doubts about the sensitivity of this serum marker in determining relapse. Therefore, the inventors compared the effectiveness of NfL alone with a panel of five serum proteins validated in two cohorts to distinguish patients in relapse or remission. Due to sample size limitations, this analysis was performed on a cross-sectional cohort. The inventors generated a logistic regression model using a cross-sectional cohort using one or more serum proteins (also referred to as predictor variables). The inventors tested the logistic regression model in a cross-sectional cohort using repeated 10-fold cross validation and plotted a receiver operating characteristic (ROC) curve for each model

[31] . It was found that the regression model with a combination of NfL, uPA, hK8, hK11 and DSG3 was able to classify relapses (area under the curve (AUC) of 0.87) compared to the NfL model alone (AUC of 0.71) ( Figure 6C Models using individual proteins other than NfL were also tested to classify relapse ( Fig.6D ). The models were generated and tested on the same dataset; therefore, they are inherently optimistic. However, the goal was to show that a combination of protein markers is better than NfL alone in classifying MS relapses, and the results herein show this. In summary, these data suggest that a regression model using a combination of NfL, uPA, hK8, hK11, and DSG3 can classify relapses in MS patients with a higher AUC than NfL alone.

[0049] Discovering biomarkers of disease activity is an active area of ​​research in MS. There is interest in measuring NfL levels in the blood to determine if a patient is experiencing active relapses. However, there are limitations. First, the specificity is low because other disease states also have elevated sNfL levels. Second, sNfL levels in serum increase with age. Third, elevated sNfL levels can also be associated with disease progression, with increased disability in the absence of relapses. Finally, although there may be statistical differences in sNfL at the group level, sNfL itself cannot be used alone to determine relapses in individual patients. Since both the sensitivity and specificity of sNfL for relapses are not ideal, sNfL levels can also be included in other biomarker panels to help predict relapses. This study used a high-throughput proteomic assay to discover serum proteins associated with active disease in MS patients, with the goal of determining whether a serum marker panel increased the sensitivity of identifying relapses compared to using NfL levels alone.

[0050] Figure 7 is a graph showing the AUC for various combinations.

[0051] Table 1 summarizes Figure 7The results in .

[0052] Model AUC ikB 0.58 DSG3 0.6 hK11 0.67 NFL 0.71 uPA 0.76 uPA+hK8+hK11+DSG3 0.75 NFL+uPA+hK8+hK11+DSG3 0.86

[0053] An important metric for measuring the performance of a classification model is called the area under the ROC curve (AUC)

[32] . In this study, the ROC curves of three classification models were compared: 1. all measured proteins, 2. NfL alone, and 3. NfL with uPA, hK8, hK11, and DSG3. The ROC curve for classifying relapse using NfL alone was found to have an AUC of 0.71, which is similar to the previously reported AUC of 0.663 for NfL

[31] . When the other four proteins were used along with NfL, the classification model was more accurate in classifying relapse than using NfL alone (AUC of 0.87) (Figure 6). These data suggest that the biomarker panel classifies relapse with higher accuracy than NfL alone.

[0054] In this cross-sectional discovery cohort, the inventors attempted to minimize factors that could confound the discovery of acute relapse markers. The inventors recruited RRMS patients early after their diagnosis and before they received disease-modifying treatment (DMT), and limited confounding factors by correcting for age and gender during this analysis. The inventors also considered the effect of corticosteroid treatment on biomarker discovery. High-dose intravenous or oral steroids are used as a rapid-acting treatment for MS patients who are experiencing disease exacerbations [33, 34]. In the discovery cohort, approximately 50% of relapsing patients were given steroids within 4 weeks prior to the blood draw. It was found that blood marker levels in patients using steroids were altered. In steroid patients, there were two elevated protein markers of interest, FKBP5 protein and NfL. Previous studies have determined that FKBP5 expression is directly induced by steroids, with a dose-dependent increase in transcription of the gene by in vitro steroid treatment

[30] . In this group, it was found that in a cross-sectional group of RRMS patients, the FKBP5 levels of relapsing MS patients treated with steroids were increased compared with relapsing MS patients not treated with steroids. Remarkably, in relapsing MS patients, after stopping steroids, FKBP5 levels decreased significantly over time, which provides evidence that steroids directly affect biomarker levels. The inventors also found that NfL levels were increased in patients using steroids compared with patients not using steroids. However, in this case, NfL did not decrease significantly over time after steroid treatment was stopped. Therefore, it may be that steroid treatment does not lead to an increase in NfL, and on the contrary, high NfL levels reflect the severity of relapses in these patients.

[0055] Next, the inventors determined whether any disease activity biomarker identified in the cross-sectional cohort can be validated in a second independent cohort. The second cohort is a longitudinal study of 12 patients, in which blood samples are collected for the first time at acute relapse and the second sample is collected during remission within 12 months of relapse. This longitudinal cohort is different from the discovery cohort in two aspects. In the first cohort, the blood sample is serum, and the sample from the second cohort is plasma. Both serum and plasma are derived from blood and are commonly used in clinical and biological studies. After blood coagulation, fibrin clots, blood cells and other coagulation-related factors are removed and serum is produced. On the other hand, plasma is obtained by treating blood with anticoagulants such as EDTA or heparin and then removing blood cells. Due to these differences in how to handle samples, previous studies have reported differences in cytokine and chemokine measurements in serum and plasma studies [40,41]. Second, there are also differences in the DMTs received by patients between the two cohorts. Patients from the first cohort had not received treatment at the time of blood draw. However, patients from the second cohort were on multiple treatments at the time of blood draw, including glatiramer acetate, fingolimod, natalizumab, dimethyl fumarate, and omezumab. Several studies have previously shown that the administration of DMTs alters the blood protein profile of RRMS patients [35,36]. Despite these differences in sample type and treatment between the two cohorts, the inventors identified five common proteins that were significantly different in relapses and remissions in RRMS patients in both cohorts. These proteins are NfL, uPA, hK8, hK11, and DSG3.

[0056] The biological significance of changes in these proteins during relapse and remission in patients has not yet been fully elucidated. However, the established functions of these molecules provide clues to their role in MS. NfL has been shown to be elevated in the blood of relapsing MS patients and is considered a marker of neuronal damage in MS. Urokinase-type plasminogen activator (uPA) is a serine protease that converts plasminogen to plasmin and is primarily expressed by neutrophils, monocytes, macrophages, and activated T cells

[37] . Plasminogen activators play an important role in clearing fibrin / fibrinogen deposits from sites of inflammation, thereby preventing further inflammatory activity. In this study, lower levels of uPA were found during relapse compared with remission.

[0057] The inventors have also found that levels of hK8 and hK11 (members of the kallikrein family of proteases) are lower during patient relapses. Kallikreins, particularly KLK1 and KLK6, have been found to be associated with secondary progressive MS

[39] . The role of kallikreins (hK8 and hK11) during MS relapses is unknown. Finally, levels of desmosome mucin-3 (DSG3) have been found to be lower during relapses. DSG3 is a component of intercellular desmosome junctions and is important for maintaining tight junctions of the intestinal epithelial barrier

[40] . Therefore, dysregulation of DSG3 can be an indicator of intestinal permeability, a biological process associated with MS pathology [41-43].

[0058] The inventors have discovered new blood-based biomarkers for identifying and monitoring MS relapses and treating MS. The data highlight the importance of identifying confounding factors that affect biomarker discovery, including age, sex, treatment, and blood sample type. Finally, a biomarker panel was identified that improved the accuracy of identifying relapses compared to using NfL alone.

[0059] Thus, the present disclosure relates to methods of treating a subject with relapsing-remitting multiple sclerosis (RRMS) who is experiencing a relapse, comprising, consisting essentially of, or consisting of: (a) determining the expression level of two or more biomarkers selected from urokinase plasminogen activator (uPA), kallikrein-8 (hK8), kallikrein-11 (hK11), or desmocollin-3 (DSG3) in a biological sample of the subject compared to a sample of the same type from a subject or subject population that does not have RRMS; (b) diagnosing the subject in (a) as experiencing a relapse if the expression level of the two or more biomarkers in the subject is reduced; and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the biomarker is uPA, hK8, hK11, or DSG3. In another aspect, the method also includes determining the expression level of NfL, uPA, hK8, hK11 or DSG3, wherein the combination of biomarkers reaches a higher area under the curve compared to NfL alone. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), interferon beta, mitoxantrone, monomethyl fumarate, ozanimod, deloximel fumarate, cladribine, sinimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or cerebrospinal fluid (CSF). In another aspect, relapse is acute phase relapse. In another aspect, the relapse is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernamod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of steroid therapy results in a decrease in the expression level of FKBP5.

[0060] The present disclosure also relates to methods for determining whether a subject with relapsing-remitting multiple sclerosis (RRMS) with elevated levels of an NfL biomarker is experiencing a relapse or will relapse, comprising, consisting essentially of, or consisting of: (a) determining the expression level of one or more biomarkers selected from uPA, hK8, hK11, or DSG3 in a biological sample from the subject compared to the same sample from a subject or subject population not suffering from RRMS, wherein the combination of the NfL biomarker and one or more biomarkers selected from uPA, hK8, hK11, or DSG3 has greater sensitivity and selectivity than using the NfL biomarker alone; (b) if the expression level of uPA, hK8, hK11, or DSG3 decreases, diagnosing the subject in (a) as experiencing a relapse, and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the method comprises selecting 2, 3, or 4 biomarkers selected from uPA, hK8, hK11, or DSG3. In another aspect, the method of claim 10, further comprising determining the expression level of NfL, uPA, hK8, hK11 or DSG3, and calculating the area under the curve, wherein the combination of biomarkers reaches an area under the curve of at least 0.87. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, deloximab fumarate, cladribine, sinimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or CSF. In another aspect, relapse is an acute phase relapse. In another aspect, the relapse is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernamod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of steroid therapy results in a decrease in the expression level of FKBP5.

[0061] In addition, the present disclosure relates to methods for detecting relapse in a subject with relapsing-remitting multiple sclerosis (RRMS), comprising, consisting essentially of, or consisting of: (a) determining the expression level of two or more biomarkers selected from uPA, hK8, hK11, or DSG3 in a biological sample of the subject compared to the same sample from a subject or subject population not having RRMS, and wherein one of the biomarkers is not an NfL biomarker, wherein the two or more biomarkers selected from uPA, hK8, hK11, or DSG3 have greater sensitivity and selectivity than the NfL biomarker alone; (b) if the expression level of the two or more biomarkers in the subject decreases, diagnosing the subject in (a) as experiencing a relapse, and (c) administering a therapeutically effective amount of a treatment for RRMS to the subject diagnosed in (b). In one aspect, the method comprises selecting 2, 3, or 4 biomarkers selected from uPA, hK8, hK11, or DSG3. In another aspect, the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, deloximet fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or CSF. In another aspect, relapse is acute phase relapse. In another aspect, the relapse is from a patient who has previously received at least one of the following and is selecting a new treatment: glatiramer acetate (GA), beta interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernaimod. In another aspect, the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof. In another aspect, a sample from an object with RRMS has previously been detected to have a higher NfL expression level than a sample from an object without RRMS. In another aspect, the method further comprises detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5.

[0062] It is contemplated that any embodiment discussed in this specification can be implemented with respect to any method, kit, reagent or composition of the invention, and vice versa. In addition, the compositions of the invention can be used to implement the methods of the invention.

[0063] It should be understood that some specific embodiments described herein are shown by way of example and are not intended to limit the present invention. Without departing from the scope of the present invention, the main features of the present invention may be used in a plurality of embodiments. Those skilled in the art will recognize or only utilize routine experiments to determine many equivalents of the specific steps described herein. Such equivalents are considered to be within the scope of the present invention and are covered by the claims.

[0064] All publications and patent applications mentioned in this specification are indicative of the technical level of those skilled in the art to which the invention pertains. All publications and patent applications are incorporated herein by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.

[0065] When used in conjunction with the term "comprises / includes" in the claims and / or the specification, the use of a noun without a quantifier may mean "one / kind", but it is also consistent with the meaning of "one / kind or more / kinds", "at least one / kind", and "one / kind or more than one / kind". Unless explicitly indicated to refer only to alternatives or to mutually exclusive alternatives, the use of the term "or / or" in the claims is used to mean "and / or / or", but the present disclosure supports definitions that refer only to alternatives and "and / or / or". Throughout this application, the term "about" is used to indicate that a value includes inherent error variations for the device, the method used to determine the value, or the variations that exist between the subjects of study.

[0066] As used in this specification and claims, the words "comprising" (and any variations thereof), "having" (and any variations thereof), "including" (and any variations thereof), or "containing" (and any variations thereof) are inclusive or open-ended, and do not exclude additional unrecorded elements or method steps. In the embodiments of any one of the compositions and methods provided herein, "comprising" can be replaced with "consisting essentially of" or "consisting of". As used herein, the phrase "consisting essentially of" requires a specified whole or step, as well as a whole or step that does not substantially affect the features or functions of the claimed invention. As used herein, the term "consisting of" is used to indicate that there is only an enumerated whole (e.g., a feature, element, characteristic, attribute, method / process step or restriction) or a group of a whole (e.g., a feature, element, characteristic, attribute, method / process step or restriction).

[0067] As used herein, the term "or a combination thereof" refers to all permutations and combinations of the items listed before the term. For example, "A, B, C, or a combination thereof" is intended to include at least one of: A, B, C, AB, AC, BC, or ABC, and if order is important in a particular context, it also includes BA, CA, CB, CBA, BCA, ACB, BAC, or CAB. Continuing with this example, combinations containing repetitions of one or more items or terms are expressly included, such as BB, AAA, AB, BBC, AAABCCCC, CBBAAA, CABABB, etc. Those skilled in the art will understand that, unless otherwise apparent from the context, there is generally no limit to the number of items or terms in any combination.

[0068] As used herein, approximate words such as, but not limited to, "about" or "substantially (or variations thereof)" refer to conditions that, when so modified, are understood to not necessarily be absolute or perfect, but would be considered close enough to one of ordinary skill in the art to warrant specifying that the condition exists. The degree to which the description can be varied will depend on how much change can be made and still allow one of ordinary skill in the art to recognize that the modified feature still has the characteristics and capabilities required of the unmodified feature. In general, but in accordance with the previous discussion, numerical values ​​modified by approximate words (e.g., "about") herein can vary from the stated value by at least ±1%, 2%, 3%, 4%, 5%, 6%, 7%, 10%, 12%, or 15%.

[0069] In addition, the section headings herein are provided to be consistent with the recommendations under 37 CFR 1.77, or to otherwise provide organizational clues. These headings should not limit or characterize the inventions set forth in any claims that may be generated from the present disclosure. Specifically and by way of example, although the title relates to "technical field", such claims should not be limited by the language under the title to describe the so-called technical field. In addition, the technical description in the "background technology" section should not be interpreted as admitting that the technology is the prior art of any invention in the present disclosure. "Summary of the invention" should also not be considered as a characterization of the present invention set forth in the published claims. In addition, any reference to the singular "invention" in the present disclosure should not be used to argue that there is only a single novel point in the present disclosure. According to the limitations of the multiple claims published in the present disclosure, multiple inventions can be set forth, and such claims accordingly define the inventions and their equivalents protected thereby. In all cases, the scope of such claims should be considered based on its own merits in accordance with the present disclosure, but should not be limited by the titles set forth herein.

[0070] In light of the present disclosure, all compositions and / or methods disclosed and claimed herein can be prepared and implemented without undue experimentation. Although the compositions and methods of the present invention have been described according to some preferred embodiments, it will be apparent to those skilled in the art that the compositions and / or methods described herein and the steps or sequence of steps of the methods may be changed without departing from the concept, spirit and scope of the present invention. All such similar substitutions and changes apparent to those skilled in the art are considered to be within the spirit, scope and concept of the present invention as defined by the appended claims.

[0071] To assist the Patent Office and any reader of any patent issuing from this application in interpreting the claims appended hereto, the applicants wish to note that unless the words "means for" or "step for" are expressly used in a particular claim, they do not intend for any appended claim to invoke 35 U.S.C. §112(6), USC §112(f), or equivalent provisions as they exist on the date of filing this application.

[0072] For each claim, each dependent claim may be dependent on both the independent claim and each of the prior dependent claims for each and every claim, as long as the prior claim provides an adequate antecedent basis for the claim term or element.

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Claims

1. A method of treating a subject with relapsing-remitting multiple sclerosis (RRMS) who is experiencing a relapse, comprising: (a) determining the expression level of two or more biomarkers selected from urokinase plasminogen activator (uPA), kallikrein-8 (hK8), kallikrein-11 (hK11), or desmoglein-3 (DSG3) in a biological sample of a subject as compared to a sample of the same type from a subject or a population of subjects not suffering from RRMS; (b) diagnosing the subject in (a) as experiencing a relapse if the expression levels of the two or more biomarkers in the subject decrease; as well as (c) administering to the subject diagnosed in (b) a therapeutically effective amount of a treatment for RRMS.

2. The method of claim 1, wherein the biomarker is uPA, hK8, hK11, or DSG3.

3. The method of claim 1, further comprising determining the expression level of NfL, uPA, hK8, hK11, or DSG3, wherein the combination of biomarkers achieves a higher area under the curve compared to NfL alone.

4. The method of claim 1, wherein the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernemod.

5. The method of claim 1, wherein the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC) or cerebrospinal fluid (CSF).

6. The method of claim 1, wherein the relapse is an acute phase relapse.

7. The method of claim 1, wherein the relapse is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH), or pernemod.

8. The method of claim 1, wherein the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof.

9. The method of claim 1, further comprising detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5.

10. A method for determining whether a subject with relapsing-remitting multiple sclerosis (RRMS) who has an elevated level of an NfL biomarker is relapsing or will relapse, comprising: (a) determining the expression level of one or more biomarkers selected from uPA, hK8, hK11 or DSG3 in a biological sample from the subject compared to the same sample from a subject or a population of subjects not suffering from RRMS, wherein the combination of the NfL biomarker and the one or more biomarkers selected from uPA, hK8, hK11 or DSG3 has greater sensitivity and selectivity than using the NfL biomarker alone; (b) diagnosing the subject in (a) as experiencing a relapse if the expression level of uPA, hK8, hK11 or DSG3 decreases, and (c) administering to the subject diagnosed in (b) a therapeutically effective amount of a treatment for RRMS.

11. The method of claim 10, comprising selecting 2, 3 or 4 biomarkers selected from uPA, hK8, hK11 or DSG3.

12. The method of claim 10, further comprising determining the expression level of NfL, uPA, hK8, hK11, or DSG3 and calculating the area under the curve, wherein the combination of biomarkers achieves an area under the curve of at least 0.

87.

13. The method of claim 10, wherein the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernemod.

14. The method of claim 10, wherein the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC), or CSF.

15. The method of claim 10, wherein the relapse is an acute phase relapse.

16. The method of claim 10, wherein the relapse is from a patient who has previously received at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH), or pernemod.

17. The method of claim 10, wherein the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof.

18. The method of claim 10, further comprising detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5.

19. A method for detecting a relapse in a subject suffering from relapsing-remitting multiple sclerosis (RRMS), comprising: (a) determining the expression level of two or more biomarkers selected from uPA, hK8, hK11 or DSG3 in a biological sample of the subject compared to the same sample from a subject or a population of subjects not having RRMS, and wherein one of the biomarkers is not an NfL biomarker, wherein the two or more biomarkers selected from uPA, hK8, hK11 or DSG3 have greater sensitivity and selectivity than the NfL biomarker alone; (b) diagnosing the subject in (a) as experiencing a relapse if the expression level of the two or more biomarkers in the subject decreases, and (c) administering to the subject diagnosed in (b) a therapeutically effective amount of a treatment for RRMS.

20. The method of claim 19, comprising selecting 2, 3 or 4 biomarkers selected from uPA, hK8, hK11 or DSG3.

21. The method of claim 19, wherein the therapeutic agent is selected from at least one of the following: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH) or pernemod.

22. The method of claim 19, wherein the biological sample is selected from peripheral blood, plasma, serum, peripheral blood mononuclear cells (PBMC), or CSF.

23. The method of claim 19, wherein the relapse is an acute phase relapse.

24. The method of claim 19, wherein the relapse is from a patient who has previously received at least one of the following and is selecting a new treatment: glatiramer acetate (GA), beta-interferon, mitoxantrone, monomethyl fumarate, ozanimod, desloximab fumarate, cladribine, siponimod, omezumab, daclizumab, alemtuzumab, PEG-interferon beta-1a, dimethyl fumarate, teriflunomide, fingolimod, natalizumab, laquinimod, ofatumumab, utoximab, steroids, adrenocorticotropic hormone (ACTH), or pernemod.

25. The method of claim 19, wherein the biomarker is a nucleic acid biomarker, a protein biomarker, or a combination thereof.

26. The method of claim 19, wherein the sample from the subject having RRMS has been previously detected to have a higher expression level of NfL compared to a sample from a subject not having RRMS.

27. The method of claim 19, further comprising detecting an increase in the expression level of FK506 binding protein 1 (FKBP5) in a sample from a subject with RRMS previously treated with steroid therapy, wherein cessation of the steroid therapy results in a decrease in the expression level of FKBP5.

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