Multiple sclerosis detection proteins and methods of use thereof

Abstract

Methods of evaluating a subject for MS or detecting MS in a subject, the methods comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1. The methods may further comprise applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS. In addition, methods of treatment comprising administering a treatment to the subject when the subject is evaluated or detected to have MS.

Description

Attorney Docket No. NVLNA.010.WO1 TITLE MULTIPLE SCLEROSIS DETECTION PROTEINS AND METHODS OF USE THEREOF CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of U.S. Provisional Application No. 63 / 546,194, filed on October 28, 2023, which is incorporated herein by reference in its entirety. BACKGROUND

[0002] Multiple sclerosis (MS), a neurodegenerative disorder characterized by demyelination, remains a significant health concern. An estimated 2.8 million suffer from MS worldwide (Walton et al., 2020), and about 900,000 are affected in the U.S. MS is the most common inflammatory neurological disease in young adults (GBD 2016 Neurology Collaborators, 2019), and can lead to physical disability, cognitive impairment, and decreased quality of life (McGinley et al., 2021).

[0003] Because of the progressive nature of MS, early diagnosis is essential (Miller, 2004). However, diagnosis of MS is based on a combination of signs and symptoms such as sensory disturbances, vision problems, and / or walking difficulties; radiographic findings such as scar tissue formation and damage in the central nervous system, which can be identified through magnetic resonance imaging; and laboratory findings such as oligoclonal bands in cerebrospinal fluid, which can be obtained through a lumbar puncture (McGinley et al., 2021).

[0004] Therefore, there is a clear unmet clinical need for a simpler, more efficient method of detecting and diagnosing MS. SUMMARY OF THE INVENTION

[0005] Some of the main aspects of the present invention are summarized below. Additional aspects are described in the Detailed Description of the Invention, Examples, Drawings, and Claims sections of this disclosure. The description in each section of this disclosure is intended to be read in conjunction with the other sections. Furthermore, the various embodiments described in each section of this disclosure can be combined in variousAttorney Docket No. NVLNA.010.WO1 different ways, and all such combinations are intended to fall within the scope of the present invention.

[0006] One aspect of the invention relates to a method of evaluating a subject for MS, the method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1. In some embodiments, the method further comprises applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS.

[0007] Another aspect of the invention relates to a method of treating MS in a subject, comprising acquiring results from a method of evaluating a subject for MS as described herein, and administering a treatment to the subject.

[0008] Another aspect of the invention relates to a method of detecting MS in a subject, the method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected.

[0009] Yet another aspect of the invention relates to a method of treating MS in a subject, comprising acquiring results from a method of detecting MS in a subject as described herein, and administering a treatment to the subject.

[0010] Another aspect of the invention relates to a method of treating MS in a subject in whom MS was detected, the method comprising administering a treatment for MS to the subject, in which MS was detected in the subject by a method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected.

[0011] In some embodiments, the subject is asymptomatic of MS.

[0012] Another aspect of the invention relates to a method of evaluating a treatment for MS in a subject, the method comprising administering a treatment for MS, and determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1.Attorney Docket No. NVLNA.010.WO1

[0013] Another aspect of the invention relates to a method of evaluating the efficacy of a treatment for MS in a subject, the method comprising administering a treatment for MS to the subject, and determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1.

[0014] Another aspect of the invention relates to a method of treating MS in a subject, the method comprising administering a treatment for MS to the subject, and determining in a biological sample from the subject a concentration of one or more proteins to evaluate the efficacy of the treatment, wherein the one or more proteins are selected from Table 1.

[0015] Another aspect of the invention relates to a method of adjusting a treatment for MS in a subject, the method comprising administering a treatment for MS to the subject, and determining in a biological sample from the subject a concentration of one or more proteins, wherein the one or more proteins are selected Table 1.

[0016] Yet another aspect of the invention relates to a method of treating MS in a subject, the method comprising administering a treatment for MS to the subject, and determining in a biological sample from the subject a concentration of one or more proteins to evaluate whether the treatment requires adjustment, wherein the one or more proteins are selected from Table 1.

[0017] In some embodiments, the biological sample is selected from a plasma sample, serum sample, saliva sample, CSF sample, sweat sample, urine sample, or tear sample. In preferred embodiments, the biological sample is a urine sample.

[0018] In some embodiments, the one or more proteins are selected from Table 2.

[0019] In some embodiments, the one or more proteins are selected from Table 3.

[0020] In some embodiments, the one or more proteins are selected from Table 4. In certain embodiments, the one or more proteins are each protein from Table 4.

[0021] Another aspect of the invention relates to a method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 1.

[0022] Yet another aspect of the invention relates to a method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 2.Attorney Docket No. NVLNA.010.WO1

[0023] Another aspect of the invention relates to a method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 3.

[0024] Another aspect of the invention relates to a method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 4. In certain embodiments, the method comprises determining individual amounts of each protein from Table 4.

[0025] Another aspect of the invention relates to a kit comprising one or more components that can be used to perform assays for detecting one or more proteins of Table 1, or one or more proteins of Table 2, or one or more proteins of Table 3, or one or more proteins of Table 4. In some embodiments, the one or more proteins are selected from Table 2. In certain embodiments, the one or more proteins are selected from Table 3. In some embodiments, the one or more proteins are selected from Table 4. In certain embodiments, the one or more proteins are each protein from Table 4. BRIEF DESCRIPTION OF THE FIGURES

[0026] FIG.1 shows accuracy, measured as area-under-the-curve (AUC) of a receiver operating characteristic (ROC) curve, of detecting MS in a subject using random combinations of two to 20 proteins selected from Table 1, as described in the Example. The process of selecting the random combinations of each number of proteins (two proteins, three proteins, etc.) was performed for 1000 iterations.

[0027] FIG.2 shows an ROC curve that depicts the accuracy of detecting MS in a subject using the panel of 23 proteins listed in Table 2, as described in the Example.

[0028] FIG.3 shows an ROC curve that depicts the accuracy of detecting MS in a subject using the panel of 42 proteins listed in Table 3, as described in the Example.

[0029] FIG.4 shows ROC curves that depict the accuracy of detecting MS in a subject using each of the five proteins listed in Table 4, both individually (blue lines) and in combination (pink line), as described in the Example.Attorney Docket No. NVLNA.010.WO1 DETAILED DESCRIPTION OF THE INVENTION

[0030] The practice of the present invention can employ, unless otherwise indicated, conventional techniques of proteomics, bioinformatics, oncology, and pharmacology, which are within the skill of the art.

[0031] In order that the present invention can be more readily understood, certain terms are first defined. Additional definitions are set forth throughout the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention is related.

[0032] Any headings provided herein are not limitations of the various aspects or embodiments of the invention, which can be had by reference to the specification as a whole. Accordingly, the terms defined immediately below are more fully defined by reference to the specification in its entirety.

[0033] All references cited in this disclosure are hereby incorporated by reference in their entireties. In addition, any manufacturers’ instructions or catalogues for any products cited or mentioned herein are incorporated by reference. Documents incorporated by reference into this text, or any teachings therein, can be used in the practice of the present invention. Documents incorporated by reference into this text are not admitted to be prior art. Definitions

[0034] The phraseology or terminology in this disclosure is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance.

[0035] As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents, unless the context clearly dictates otherwise. The terms “a” (or “an”) as well as the terms “one or more” and “at least one” can be used interchangeably.

[0036] Furthermore, “and / or” is to be taken as specific disclosure of each of the two specified features or components with or without the other. Thus, the term “and / or” as used in a phrase such as “A and / or B” is intended to include A and B, A or B, A (alone), and B (alone). Likewise, the term “and / or” as used in a phrase such as “A, B, and / or C” is intendedAttorney Docket No. NVLNA.010.WO1 to include A, B, and C; A, B, or C; A or B; A or C; B or C; A and B; A and C; B and C; A (alone); B (alone); and C (alone).

[0037] Units, prefixes, and symbols are denoted in their Système International de Unites (SI) accepted form. Numeric ranges are inclusive of the numbers defining the range, and any individual value provided herein can serve as an endpoint for a range that includes other individual values provided herein. For example, a set of values such as 1, 2, 3, 8, 9, and 10 is also a disclosure of a range of numbers from 1-10. Where a numeric term is preceded by “about,” the term includes the stated number and values ±10% of the stated number. The headings provided herein are not limitations of the various aspects or embodiments of the invention, which can be had by reference to the specification as a whole. Accordingly, the terms defined immediately below are more fully defined by reference to the specification in its entirety.

[0038] Wherever embodiments are described with the language “comprising,” otherwise analogous embodiments described in terms of “consisting of” and / or “consisting essentially of” are included.

[0039] An “effective amount” of a composition as disclosed herein is an amount sufficient to carry out a specifically stated purpose. An “effective amount” can be determined empirically and in a routine manner, in relation to the stated purpose, route of administration, and dosage form.

[0040] The term “subject” or “individual” or “patient” means any subject, preferably a mammalian subject, for whom diagnosis, prognosis, or therapy is desired. Mammalian subjects include humans, domestic animals, farm animals, sports animals, and zoo animals including, e.g., humans, non-human primates, dogs, cats, guinea pigs, rabbits, rats, mice, horses, cattle, etc.

[0041] The term “symptomatic” means to exhibit one or more signs or features that are regarded as indicative, or are known to be associated with, a disease or condition. A subject may be considered as “symptomatic” of MS based on symptoms that are known in the art to be associated with MS. .

[0042] A subject may be considered as “suspected of having a MS” due to the presence of symptoms, i.e., the subject is symptomatic; genetic markers; patient’s habits orAttorney Docket No. NVLNA.010.WO1 medical history; patient’s family medical history; examination or tests known in the art for which the outcome is associated with MS or risk of MS, etc.

[0043] The term “asymptomatic” means to not exhibit any signs or features that are regarded as indicative, or are known to be associated with, a disease or condition.

[0044] Terms such as “treating” or “treatment” or “to treat” or “alleviating” or “to alleviate” refer to therapeutic measures that cure, slow down, lessen symptoms of, and / or halt progression of a diagnosed pathologic condition or disorder. Thus, those in need of treatment include those already with the disorder. In certain embodiments, a subject is successfully “treated” for a disease or disorder if the patient shows, e.g., total, partial, or transient alleviation or elimination of symptoms associated with the disease or disorder.

[0045] The term “ROC” or “ROC curve” is used to refer to a receiver operator characteristic curve. A ROC curve can be a graphical representation of the performance of a classifier system. For any given method, a ROC can be generated by plotting the sensitivity against the specificity. The sensitivity and specificity of a method for detecting the presence of MS can be determined at various concentrations of proteins in a sample from the subject. The AUC of a ROC curve is a metric that can provide a measure of diagnostic utility of a method, taking into account both the sensitivity and specificity of the method. The AUC can range from 0.5 to 1.0, where a value closer to 0.5 can indicate that the method has limited diagnostic utility (e.g., lower sensitivity and / or specificity) and a value closer to 1.0 indicates the method has greater diagnostic utility (e.g., higher sensitivity and / or specificity).

[0046] The term “third party” means a person or group different from the two persons or groups primarily involved. For example, in a multi-step method involving a subject, a third party can be a person / group other than the subject and the person / group primarily responsible for the performance of the steps. In such an example, a third party may perform one of the steps in the method. As another example, in a treatment method involving administration of a treatment to a subject, a third party may be a person / group other than the subject and the person / group administering the treatment. Methods of the Invention

[0047] The present invention involves the use of proteins in the detection of evaluation of MS in subjects. Such use can be applied in methods of evaluating a subject for MS, methods of treating subjects for MS, among others.Attorney Docket No. NVLNA.010.WO1

[0048] The proteins can be used to detect or evaluate MS based on a biological sample from the subject. The biological sample may be any biological sample capable of being obtained from the subject, and encompass fluids, solids, tissues, and gases. In some embodiments, the sample may be a blood product, such as plasma, serum and the like. In some embodiments, the sample may be a urine sample, saliva sample, cerebrospinal fluid (CSF) sample, sweat sample, or tear sample.

[0049] In preferred embodiments, the biological sample is advantageously a urine sample. Compared to blood or plasma samples, there is no homeostasis mechanism in urine that can regulate the presence of proteins in the course of maintaining relatively constant physical / chemical properties within the body (Jing and Gao, 2018). It is possible that potential biomarkers may be cleared from plasma or blood by the inherent homeostasis mechanism in order to avoid possible damage or interference to the body (id.). On the other hand, the waste materials in the urine are the cleared objects of the blood homeostasis mechanism and therefore may better reflect changes that are produced in vivo by the presence of a disease such as MS and that would not be cleared by any homeostasis mechanism (id.). In addition, urine collection is less traumatic to the body and involves no infliction of pain, is safer and less costly, and is easier and simpler to store (id.).

[0050] An aspect of the present invention relates to a method of evaluating a subject for MS. The method comprises determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1, also referred to herein as “MS detection proteins.”

[0051] In preferred embodiments, the sample is already separated / obtained / collected from the subject at the time of the evaluation. In some embodiments, the sample is separated from the subject at home and / or by the subject prior to the evaluation.

[0052] In embodiments of the invention, the method identifies whether the subject has MS. The method may further comprise applying a classifier to the concentration of the one or more MS detection proteins. The classifier identifies whether the concentration of the one or more MS detection proteins is indicative that the subject has MS.

[0053] In embodiments of the invention, the methods of evaluating a subject further comprise administering a treatment. In some embodiments, the treatment is administered when it is determined that the subject has MS.Attorney Docket No. NVLNA.010.WO1

[0054] To this end, an aspect of the present invention relates to a method of treating MS in a subject, comprising (a) acquiring results from methods of evaluating a subject for MS as described herein, and (b) administering a treatment to the subject. In some embodiments, the results from methods of evaluating a subject for MS are provided by a third party. In some embodiments, the treatment is responsive to the results, e.g., responsive to having MS.

[0055] Another aspect of the present invention relates to a method of treating MS in a subject, in which the method comprises (a) acquiring results from an evaluation of the subject that determined the subject has MS; (b) administering a treatment to the subject, e.g., a treatment for MS, in which the evaluation comprises: (I) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1, and (II) applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS. In some embodiments, the results in (a) are acquired from a third party.

[0056] An aspect of the present invention relates to a method of detecting MS in a subject, the method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1, and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected.

[0057] In embodiments of the invention, the method of detecting MS in a subject further comprises administering a treatment. In some embodiments, the treatment is administered when MS is detected.

[0058] To this end, an aspect of the present invention relates to a method of treating MS in a subject, comprising (a) acquiring results from a method of detecting MS in a subject as described herein, and (b) administering a treatment to the subject. In some embodiments, the results from the method of detecting MS in a subject are provided by a third party. In some embodiments, the treatment is responsive to the results, e.g., responsive to MS being detected.

[0059] An aspect of the invention relates to a method of treating MS in a subject in whom MS was detected, the method comprising administering a treatment for MS; in which MS had been detected in the subject by a method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1, andAttorney Docket No. NVLNA.010.WO1 applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS. In some embodiments, the method of detecting MS was performed by a third party.

[0060] Yet another aspect of the present invention relates to a method of treating MS in a subject, in which the method comprises (a) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; (b) applying a classifier to the concentration of the one or more proteins to identify that the subject has MS; and (c) administering a treatment to the subject, e.g., a treatment for MS.

[0061] Another aspect of the present invention relates to a method of treating a patient who has been or was determined to have MS, comprising administering a treatment for MS to the patient, in which the patient was determined to have MS by a method comprising (a) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1, and (b) applying a classifier to the concentration of the one or more proteins. The classifier identifies whether the concentration of the one or more proteins is indicative that the subject has MS.

[0062] In some embodiments, the subject is asymptomatic for MS. In some embodiments, the methods may be performed as part of, or may be included within, or may overlap with, a screening for MS in the subject. In some embodiments, the subject is undergoing a screen for MS.

[0063] In some embodiments, the subject is suspected of having MS, such as symptomatic of having MS. Examples of symptoms of MS include, but are not limited to, numbness or weakness in one or more limbs that typically occurs on one side of the body at a time; tingling; electric-shock sensations that occur with certain neck movements, especially bending the neck forward (Lhermitte sign); lack of coordination; unsteady gait or inability to walk; spasticity; “MS hug” (a squeezing sensation around the torso that resembles the feeling of a blood pressure cuff when it tightens); heat sensitivity; weakness; pain and / or itching; partial or complete loss of vision, usually in one eye at a time, often with pain during eye movement; prolonged double vision; blurry vision; vertigo; problems with sexual, bowel, and / or bladder function; fatigue; slurred speech; cognitive problems; and mood disturbances.

[0064] In addition, an aspect of the present invention relates to a method of evaluating a treatment for MS in a subject. The method comprises (a) administering a treatment for MS, and (b) determining in a biological sample from the subject a concentration of one or moreAttorney Docket No. NVLNA.010.WO1 proteins selected from Table 1. In preferred embodiments, the sample is already separated / obtained from the subject at the time of performing (b). In some embodiments, administration of the treatment in (a) may be performed by a third party. In other embodiments, determining the concentration of the one or more proteins in (b) may be performed by a third party.

[0065] In embodiments of the invention, the one or more proteins identifies whether the subject has MS after treatment. Thus, the method may further comprise applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS.

[0066] The treatment may be any known treatment for MS as known in the art and as described herein. The administration of the treatment in (a) may comprise a single administration or occurrence of a therapy, or may comprise multiple administrations or occurrences of a therapy.

[0067] The determination in a biological sample from the subject a concentration of one or more proteins in (b) may be performed more than once. The determination may overlap with the administration of the treatment in (a) or may occur after the administration of the treatment in (a).

[0068] In embodiments in which determination in a biological sample from the subject a concentration of one or more proteins in (b) is occurring after the administration of the treatment in (a), the determination may occur immediately after the administration of the treatment or a period of time after the administration of the treatment. The period of time may be one day or more, or one week or more, or one month or more, or one year or more; including one day, or two days, or three days, or four days, or five days, or six days, or about one week, or about two weeks, or about three weeks, or about four weeks, or about five weeks, or about six weeks, or about seven weeks, or about eight weeks, or about nine weeks, or about ten weeks, or about 11 weeks, or about 12 weeks, or about one month, or about two months, or about three months, or about four months, or about five months, or about six months, or about seven months, or about eight months, or about nine months, or about ten months, or about 11 months, or about 12 months, or about one year, or about two years, or about three years, or about four years, or about five years, or about six years, or about seven years, or about eight years, or about nine years, or about ten years, or about 11 years, or about 12 years, or about 13 years, or about 14 years, or about 15 years, or about 16 years, or aboutAttorney Docket No. NVLNA.010.WO1 17 years, or about 18 years, or about 19 years, or about 20 years, or about 21 years, or about 22 years, or about 23 years, or about 24 years, or about 25 years, or about 26 years, or about 27 years, or about 28 years, or about 29 years, or about 30 years, or more; including any ranges formed with these time periods as endpoints, for examples about 4 weeks to about 13 years, about 7 months to about 3 years, etc.

[0069] In some embodiments, the presence of MS after treatment may be indicative that the treatment was not effective. Thus, another aspect of the invention is a method of evaluating the efficacy of a MS treatment, comprising (a) administering a treatment for MS, and (b) determining in a biological sample from the subject a concentration of one or more proteins, as described herein. Yet another aspect is a method of treatment, comprising (a) administering a treatment for MS , and (b) determining in a biological sample from the subject a concentration of one or more proteins, as described herein, to evaluate whether the treatment was effective.

[0070] In some embodiments, the presence of MS after treatment may be indicative that the treatment requires adjustment. Thus, another aspect of the invention is a method of adjusting a treatment for MS, comprising (a) administering a treatment for MS, and (b) determining in a biological sample from the subject a concentration of one or more proteins, as described herein, to evaluate whether the treatment requires adjustment; such method may further comprise administering a second treatment. The second treatment may be different from the original treatment, for example, a different therapy or different dosage of the same therapy.

[0071] An aspect of the present invention relates to a method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 1. In some embodiments, the individual amounts of the one or more proteins is determined in a biological sample from the subject.

[0072] In some embodiments, the biological sample is a plasma sample, serum sample, saliva sample, CSF sample, sweat sample, urine sample, or tear sample. In preferred embodiments, the biological sample is a urine sample.

[0073] In embodiments of the invention, the methods may further comprise obtaining or collecting a biological sample from the subject before determining the concentration of one or more proteins in the biological sample. The collection of the biological sample mayAttorney Docket No. NVLNA.010.WO1 be performed in a home (e.g., the home of the subject) or at a medical facility (e.g., doctor’s office, hospital, urgent care center, etc.).

[0074] In some embodiments, the determination of the concentration of one or more proteins in the biological sample may be performed in a home (e.g., the home of the subject) or at a medical facility (e.g., doctor’s office, hospital, urgent care center, etc.).

[0075] In some embodiments of the invention, the one or more proteins may be selected from Table 2. In some embodiments of the invention, the one or more proteins may be each protein of Table 2.

[0076] In some embodiments of the invention, the one or more proteins may be selected from Table 3. In some embodiments of the invention, the one or more proteins may be each protein of Table 3.

[0077] In some embodiments of the invention, the one or more proteins may be selected from Table 4. In some embodiments of the invention, the one or more proteins may be each protein of Table 4.

[0078] In some embodiments of the present invention, for any of the MS detection proteins, the methods may comprise determining the concentration of two or more, or three or more, or four or more, or five or more, or six or more, or seven or more, or eight or more, or nine or more, or ten or more, or about 15 or more, or about 20 or more, or about 25 or more, or about 30 or more, or about 35 or more, or about 40 proteins or more, or about 40 or more, or about 45 proteins or more, or about 50 proteins or more, or about 55 proteins or more, or about 60 proteins or more, or about 65 proteins or more, proteins; including any number of proteins chosen from two, three, four, five, six, seven, eight, nine, ten, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, or 69; and including any ranges thereof, for example, about two to 69 proteins, or about two to 65 proteins, or about two to 60 proteins, or about two to 55 proteins, or about two to 50 proteins, or about two to 45 proteins, or about two to 40 proteins, or about two to 35 proteins, or about two to 30 proteins, or about two to 25 proteins, or about two to 20 proteins, or about two to 15 proteins, or about two to ten proteins, or about two to nine proteins, or about two to eight proteins, or about two to seven proteins, or about two to six proteins, or about two to five proteins, or about two to four proteins, or about two or threeAttorney Docket No. NVLNA.010.WO1 proteins, or about three to 69 proteins, or about three to 65 proteins, or about three to 60 proteins, or about three to 55 proteins, or about three to 50 proteins, or about three to 45 proteins, or about three to 40 proteins, or about three to 35 proteins, or about three to 30 proteins, or about three to 25 proteins, or about three to 20 proteins, or about three to 15 proteins, or about three to ten proteins, or about three to nine proteins, or about three to eight proteins, or about three to seven proteins, or about three to six proteins, or about three to five proteins, or about three or four proteins, or about five to 69 proteins, or about five to 65 proteins, or about five to 60 proteins, or about five to 55 proteins, or about five to 50 proteins, or about five to 45 proteins, or about five to 40 proteins, or about five to 35 proteins, or about five to 30 proteins, or about five to 25 proteins, or about five to 20 proteins, or about five to 15 proteins, or about five to ten proteins, or about five to nine proteins, or about five to eight proteins, or about five to seven proteins, or about five or six proteins, or about ten to 69 proteins, or about ten to 65 proteins, or about ten to 60 proteins, or about ten to 55 proteins, or about ten to 50 proteins, or about ten to 45 proteins, or about ten to 40 proteins, or about ten to 35 proteins, or about ten to 30 proteins, or about ten to 25 proteins, or about ten to 20 proteins, or about ten to 15 proteins, or about 15 to 69 proteins, or about 15 to 65 proteins, or about 15 to 60 proteins, or about 15 to 55 proteins, or about 15 to 50 proteins, or about 15 to 45 proteins, or about 15 to 40 proteins, or about 15 to 35 proteins, or about 15 to 30 proteins, or about 15 to 25 proteins, or about 15 to 20 proteins, or about 20 to 69 proteins, or about 20 to 65 proteins, or about 20 to 60 proteins, or about 20 to 55 proteins, or about 20 to 50 proteins, or about 20 to 45 proteins, or about 20 to 40 proteins, or about 20 to 35 proteins, or about 20 to 30 proteins, or about 20 to 25 proteins, or about 25 to 69 proteins, or about 25 to 65 proteins, or about 25 to 60 proteins, or about 25 to 55 proteins, or about 25 to 50 proteins, or about 25 to 45 proteins, or about 25 to 40 proteins, or about 25 to 30 proteins, or about 30 to 69 proteins, or about 30 to 65 proteins, or about 30 to 60 proteins, or about 30 to 55 proteins, or about 30 to 50 proteins, or about 30 to 45 proteins, or about 30 to 40 proteins, or about 30 to 35 proteins, or about 35 to 69 proteins, or about 35 to 65 proteins, or about 35 to 60 proteins, or about 35 to 55 proteins, or about 35 to 50 proteins, or about 35 to 45 proteins, or about 35 to 40 proteins, or about 40 to 69 proteins, or about 40 to 65 proteins, or about 40 to 60 proteins, or about 40 to 55 proteins, or about 40 to 50 proteins, or about 40 to 45 proteins, or about 45 to 69 proteins, or about 45 to 65 proteins, or about 45 to 60 proteins, or about 45 to 55 proteins, or about 45 to 50 proteins, or about 50 to 69 proteins, or about 50 to 65 proteins, or about 50 to 60 proteins, or about 50 to 55 proteins, or about 55 to 69 proteins,Attorney Docket No. NVLNA.010.WO1 or about 55 to 65 proteins, or about 55 to 60 proteins or about 60 to 69 proteins, or about 60 to 65 proteins, or about 65 to 69 proteins.

[0079] In some embodiments, the methods may comprise determining the concentration of each protein of Table 1. In certain embodiments, the methods may comprise determining the concentration of each protein of Table 2. In certain embodiments, the methods may comprise determining the concentration of each protein of Table 3. In certain embodiments, the methods may comprise determining the concentration of each protein of Table 4.

[0080] In some embodiments, the number of proteins for which the concentration is determined may be sufficient to achieve an AUC of a ROC curve of at least about 0.6. In certain embodiments, the number of proteins for which the concentration is determined may be sufficient to achieve an AUC of a ROC curve of at least about 0.7, or at least about 0.8.

[0081] In some embodiments, MS is in first stage, also referred to as “clinically isolated syndrome” (CIS), in which symptoms are an isolated incident caused by inflammation and damage to the myelin sheath in only one area of the brain or spinal cord. In some embodiments, MS is in second stage, also referred to as “relapsing-emitting MS” (RRMS), which features periods in which symptoms worsen (i.e., a “relapse” or “flare-up”) and then improve. In some embodiments, MS is in third stage, also referred to as “secondary-progressive MS” (SPMS), in which there are relapses followed by periods of only partial recovery, such that the symptoms do not disappear between relapses, and steadily worsens. In some embodiments, MS is in fourth stage, also referred to as “primary- progressive MS” (PPMS), which is characterized by slow and steady disease progression with no remission periods, although there may be occasional plateaus in the symptoms as well as minor improvements in function that tend to be temporary.

[0082] The treatment administered to the subjects according to the methods described herein may be treatments known in the art. Treatments may have different purposes, for instance, to reduce intensity or frequency or relapses, to reduce symptoms, to reverse or prevent demyelination, or to suppress or modulate immune function. Examples of such treatments include, but are not limited to, corticosteroids; plasma exchange; interferon beta medications such as interferon beta-1a and interferon beta-1b; glatiramer acetate; monoclonal antibodies such as ofatumumab, ocrelizumab, alemtuzumab, and natalizumab; teriflunomide; dimethyl fumarate; diroximel fumarate; monomethyl fumarate; fingolimod; siponimod;Attorney Docket No. NVLNA.010.WO1 ozanimod; ponesimod; mitoxantrone; cladribine; Bruton’s tyrosine kinase (BTK) inhibitor; stem cell transplantation; physical therapy; muscle relaxants such as baclofen, tizanidine, cyclobenzaprine, and onabotulinumtoxin A; medications to reduce fatigue such as amantadine, modafinil, and methylphenidate; medications to increase walking speed such as dalfampridine; and other medications for depression, pain, sexual dysfunction, insomnia, and bladder or bowel control problems that are associated with MS.

[0083] In certain embodiments, a MS patient subjected to a method of the invention is successfully treated if the patient’s progression-free survival, i.e., length of time a patient is treated without progression of the disease or worsening of symptoms. Survival can be measured from the date of diagnosis or from the date that treatment commences. Progression-free survival and median progression-free survival can be determined by methods known in the art and / or by those described herein.

[0084] In certain embodiments a patient with MS subjected to a method of the invention is successfully treated if the patient has an improved response to the anti-MS therapy compared with a patient having MS who has not been subjected to a method of the invention. For example, treatment of MS would be successful in a subject treated by the methods of the invention if the subject has an improved response compared to the median response of patients who have not been treated by the methods of the invention. Response to anti-MS treatment can be measured by known methods, which may include alleviation or reduction of one or more symptoms; reduction of intensity, duration, and / or frequency of relapses, etc. Protein Concentration Measurement and Application of Classifiers

[0085] The concentration of proteins in the sample may be measured using protein quantitation techniques known in the art. Such techniques include, but are not limited to, enzyme-linked immunosorbent assays, chemiluminescence immunoassays, immunohistochemistry, liquid-bead immunoassays, mass spectrometry, aptamer-based assays, reverse phase protein arrays, proximity extension assay (PEA), and a combination thereof.

[0086] In the methods described herein, the concentration of the two or more proteins are used and combined with mathematical, statistical, and machine-learning methods to create secondary features. One or more proteins with and without secondary features andAttorney Docket No. NVLNA.010.WO1 baseline features, including age, sex, race and ethnicity, past medical history, family history, patient’s lab values, comorbidities, and concomitant medications, are used in one or more predictive models to calculate a score.

[0087] Machine learning and statistical analyses techniques used to generate features and the final score for MS are included but not limited to the following concepts and methods: Supervised learning concepts may include AODE; Artificial neural network, such as Backpropagation, Auto encoders, Hopfield networks, Boltzmann machines, Restricted Boltzmann Machines, and Spiking neural networks; Bayesian statistics, such as Bayesian network and Bayesian knowledge base; Case-based reasoning; Gaussian process regression; Gene expression programming; Group method of data handling (GMDH); Inductive logic programming; Instance-based learning; Lazy learning; Learning Automata; Learning Vector Quantization; Logistic Model Tree; Minimum message length (decision trees, decision graphs, etc.), such as Nearest Neighbor Algorithm and Analogical modeling; Probably approximately correct learning (PAC ) learning; Ripple down rules, a knowledge acquisition methodology; Symbolic machine learning algorithms; Support vector machines; Random Forests; Ensembles of classifiers, such as Bootstrap aggregating (bagging) and Boosting (meta -algorithm ); Ordinal classification; Information fuzzy networks (IFN); Conditional Random Field; ANOVA; Linear classifiers, such as Fisher’s linear discriminant, Linear regression, Logistic regression, Multinomial logistic regression, I Bayes classifier, Perceptron, Support vector machines; Quadratic classifiers; k -nearest neighbor; Boosting; Decision trees, such as C4.5, Random forests, ID3, CART, SLIQ SPRINT; Bayesian networks, sucINaive Bayes; and Hidden Markov models . Unsupervised learning concepts may include; Expectation –maximization algorithm; Vector Quantization; Generative topographic map; Information bottleneck method; Artificial neural network, such as Self - organizing map; Association rule learning, such as Apriori algorithm, Eclat algorithm, and FP growth algorithm; Hierarchical clusterings such as Single linkage clustering and Conceptual clustering; Cluster analysis, such as K -means algorithm, Fuzzy clustering, DBSCAN, and OPTICS algorithm; and Outlier Detection, such as Local Outlier Factor. Semi-supervised learning concepts may include; Generative models; Low –density separation; Graph-based methods, and Co -training. Reinforcement learning concepts may include Temporal difference learning; Q -learning, Learning Automata, and SARSA. Deep learning conceptsAttorney Docket No. NVLNA.010.WO1 may include Deep belief networks; Deep Boltzmann machines; Deep Convolutional neural networks; Deep Recurrent neural networks; and Hierarchical temporal memory.

[0088] For concentrations obtained from detection proteins, one or more features are fed into one or more computation models. The classifiers are used to calculate a score for the patient. The scores of different classifiers are combined to identify the patient as having MS or not. The computational model may use one or more proteins or secondary features with and without baseline features that could generate a (ROC curve greater than or equal to 0.6. This step determines if the sample indicates the presence of MS.

[0089] Protein concentrations and / or secondary features are fed into one or more predictive models. The features could be similar or different from what was used in determining MS status. The classifiers are used to calculate a score for the patient for MS. The predictive models use the proteins or derived secondary features that could generate a ROC curve greater than or equal to 0.6.

[0090] Generally, machine learning algorithms are used to construct models that accurately assign class labels to examples based on the input features that describe the example.

[0091] Embodiments of the present disclosure can be further defined by reference to the following non-limiting examples. It will be apparent to those skilled in the art that many modifications, both to materials and methods, can be practiced without departing from the scope of the present disclosure. Kit

[0092] An aspect of the present invention relates to a kit for use in detecting one or more MS detection proteins, i.e., one or more proteins of Table 1, or one or more proteins of Table 2, or one or more proteins of Table 3, or one or more proteins of Table 4, or each protein of Table 4, which can be used to perform the methods described herein. The kit may comprise one or more components that can be used to perform assays such as enzyme-linked immunosorbent assays, chemiluminescence immunoassays, immunohistochemistry, liquid- bead immunoassays, mass spectrometry, aptamer-based assays, reverse phase protein arrays, PEA, or a combination thereof. Such components include, but are not limited to, antibodies or antigen binding fragments thereof that bind one or more proteins of Table 1, or one orAttorney Docket No. NVLNA.010.WO1 more proteins of Table 2, or one or more proteins of Table 3, or one or more proteins of Table 4, or each protein of Table 4.

[0093] In some embodiments, the kit comprises antibodies or antigen binding fragments thereof that bind

[0094] two or more, or three or more, or four or more, or five or more, or six or more, or seven or more, or eight or more, or nine or more, or ten or more, or about 15 or more, or about 20 or more, or about 25 or more, or about 30 or more, or about 35 or more, or about 40 proteins or more, or about 40 or more, or about 45 proteins or more, or about 50 proteins or more, or about 55 proteins or more, or about 60 proteins or more, or about 65 proteins or more, proteins; including any number of proteins chosen from two, three, four, five, six, seven, eight, nine, ten, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, or 69; and including any ranges thereof, for example, about two to 69 proteins, or about two to 65 proteins, or about two to 60 proteins, or about two to 55 proteins, or about two to 50 proteins, or about two to 45 proteins, or about two to 40 proteins, or about two to 35 proteins, or about two to 30 proteins, or about two to 25 proteins, or about two to 20 proteins, or about two to 15 proteins, or about two to ten proteins, or about two to nine proteins, or about two to eight proteins, or about two to seven proteins, or about two to six proteins, or about two to five proteins, or about two to four proteins, or about two or three proteins, or about three to 69 proteins, or about three to 65 proteins, or about three to 60 proteins, or about three to 55 proteins, or about three to 50 proteins, or about three to 45 proteins, or about three to 40 proteins, or about three to 35 proteins, or about three to 30 proteins, or about three to 25 proteins, or about three to 20 proteins, or about three to 15 proteins, or about three to ten proteins, or about three to nine proteins, or about three to eight proteins, or about three to seven proteins, or about three to six proteins, or about three to five proteins, or about three or four proteins, or about five to 69 proteins, or about five to 65 proteins, or about five to 60 proteins, or about five to 55 proteins, or about five to 50 proteins, or about five to 45 proteins, or about five to 40 proteins, or about five to 35 proteins, or about five to 30 proteins, or about five to 25 proteins, or about five to 20 proteins, or about five to 15 proteins, or about five to ten proteins, or about five to nine proteins, or about five to eight proteins, or about five to seven proteins, or about five or six proteins, or about ten to 69 proteins, or about ten to 65 proteins, or about ten to 60 proteins,Attorney Docket No. NVLNA.010.WO1 or about ten to 55 proteins, or about ten to 50 proteins, or about ten to 45 proteins, or about ten to 40 proteins, or about ten to 35 proteins, or about ten to 30 proteins, or about ten to 25 proteins, or about ten to 20 proteins, or about ten to 15 proteins, or about 15 to 69 proteins, or about 15 to 65 proteins, or about 15 to 60 proteins, or about 15 to 55 proteins, or about 15 to 50 proteins, or about 15 to 45 proteins, or about 15 to 40 proteins, or about 15 to 35 proteins, or about 15 to 30 proteins, or about 15 to 25 proteins, or about 15 to 20 proteins, or about 20 to 69 proteins, or about 20 to 65 proteins, or about 20 to 60 proteins, or about 20 to 55 proteins, or about 20 to 50 proteins, or about 20 to 45 proteins, or about 20 to 40 proteins, or about 20 to 35 proteins, or about 20 to 30 proteins, or about 20 to 25 proteins, or about 25 to 69 proteins, or about 25 to 65 proteins, or about 25 to 60 proteins, or about 25 to 55 proteins, or about 25 to 50 proteins, or about 25 to 45 proteins, or about 25 to 40 proteins, or about 25 to 30 proteins, or about 30 to 69 proteins, or about 30 to 65 proteins, or about 30 to 60 proteins, or about 30 to 55 proteins, or about 30 to 50 proteins, or about 30 to 45 proteins, or about 30 to 40 proteins, or about 30 to 35 proteins, or about 35 to 69 proteins, or about 35 to 65 proteins, or about 35 to 60 proteins, or about 35 to 55 proteins, or about 35 to 50 proteins, or about 35 to 45 proteins, or about 35 to 40 proteins, or about 40 to 69 proteins, or about 40 to 65 proteins, or about 40 to 60 proteins, or about 40 to 55 proteins, or about 40 to 50 proteins, or about 40 to 45 proteins, or about 45 to 69 proteins, or about 45 to 65 proteins, or about 45 to 60 proteins, or about 45 to 55 proteins, or about 45 to 50 proteins, or about 50 to 69 proteins, or about 50 to 65 proteins, or about 50 to 60 proteins, or about 50 to 55 proteins, or about 55 to 69 proteins, or about 55 to 65 proteins, or about 55 to 60 proteins or about 60 to 69 proteins, or about 60 to 65 proteins, or about 65 to 69 proteins.

[0095] In some embodiments, the kit may also comprise one or more enzymes, substrates, labels, or other components useful for performing the assays.

[0096] In some embodiments, the kit further comprises one or more of the following: one or more containers for collecting or holding the sample (e.g., urine sample), controls, directions for performing the methods, any necessary software for analysis and presentation of results.

[0097] One skilled in the art will readily recognize that the disclosed one or more components can be readily incorporated into any of the established kit formats that are well known in the art.Attorney Docket No. NVLNA.010.WO1 EXAMPLE

[0098] Analyses were performed to identify the MS detection proteins of the present invention. Sample Collection

[0099] Urine samples were collected from a patient population diagnosed with MS, and from healthy individuals without MS. Protein Measurement

[0100] While any protein measurement technique could have been used, including enzyme-linked immunosorbent assays (ELISA), chemiluminescence immunoassays (CLIA), immunohistochemistry (IHC), liquid-bead immunoassays, mass spectrometry, aptamer-based assays, reverse phase protein arrays (RPPA), etc., a proximity extension assay (PEA) was employed to evaluate proteins in urine. In PEA, each protein was recognized by two antibodies for proper detection. In proximity assays, each of the two antibodies was conjugated to one of two different DNA oligonucleotides, and the reagents were incubated with the samples in solution. The proximity reactions underwent a dilution step. Oligonucleotides on pairs of antibodies that remain in proximity by virtue of having bound the same protein molecule then underwent DNA ligation (proximity ligation assay) or DNA polymerization (proximity extension assay). The effect of the ligation or polymerization reactions was to create amplifiable reporter DNA strands for sensitive readout via, for example, real-time PCR or next-generation sequencing, and the assays could be performed in high multiplex. By constructing the assays so that only proper pairs of antibodies can yield detection signals, but no other combination of antibodies, the detection of many different proteins in parallel was possible without eroding detection specificity by reactions of noncognate pairs.

[0101] The analytical performance of the panels was validated for sensitivity, dynamic range, specificity, precision, and scalability. The analytical measuring range was defined by the lower limit of quantification (LLOQ) and upper limit of quantification (ULOQ) and reported in pg / mL. The high dose hook effect (a state of antigen excess relative to the reagent antibodies resulting in falsely lower values) was also determined for each analyte.Attorney Docket No. NVLNA.010.WO1

[0102] All assays were thoroughly validated for precision (repeatability and reproducibility). Intra-assay variation (within-run) was calculated as the mean CV for individual samples, within each of separate runs during the validation studies. Inter-assay variation (between-runs) was calculated as the mean CV, for the same individual samples, among separate runs during the validation studies.

[0103] Each protein analyte was addressed by a matched pair of antibodies, coupled to unique, partially complementary oligonucleotides and measured by quantitative real-time PCR. Validation of the readout specificity for all of the panels was carried out using a simple, sequential approach in which pools of protein analytes were tested. Feature Selection

[0104] Proteins were used to create features that could be used for the classification of samples. The proteins were categorized based on their concentration or their patterns of change detected by different statistical or machine-learning techniques to create new features.

[0105] Machine learning and statistical analyses techniques used to generate features and the final score for MS were included but not limited to the following concepts and methods: supervised learning concepts that may include AODE; artificial neural network, such as Backpropagation, Auto encoders, Hopfield networks, Boltzmann machines, Restricted Boltzmann Machines, and Spiking neural networks; Bayesian statistics, such as Bayesian network and Bayesian knowledge base; case-based reasoning; Gaussian process regression; gene expression programming; group method of data handling (GMDH); inductive logic programming; instance-based learning; lazy learning; learning Automata; learning vector quantization; logistic model tree; minimum message length (decision trees, decision graphs, etc.), such as nearest neighbor algorithm and analogical modeling; probability approximately correct learning (PAC ) learning; ripple down rules, a knowledge acquisition methodology; symbolic machine learning algorithms; support vector machines; random forests; ensembles of classifiers, such as bootstrap aggregating (bagging) and boosting (meta -algorithm ); ordinal classification; information fuzzy networks (IFN); conditional random field; ANOVA; linear classifiers, such’as Fisher's linear discriminant, linear regression, logistic regression, multinomial logistic reIion, naive Bayes classifier, Perceptron, support vector machines; quadratic classifiers; k -nearest neighbor; boosting; decision trees, such as C4.5, random forests, ID3, CART, SLIQ SPRINT; Bayesian netI, suchAttorney Docket No. NVLNA.010.WO1 as Naive Bayes; and Hidden Markov models. cUnsupervised learning concepts may include; expectation –maximization algorithm; vector quantization; generative topographic map; information bottleneck method; artificial neural network, such as self -organizing map; association rule learning, such as Apriori algorithm, Eclat algorithm, and FP growth algorithm; hierarchical clusterings such as single linkage clustering and conceptual clustering; cluster analysis, such as K -means algorithm, fuzzy clustering, DBSCAN, and OPTICS algorithm; and outlier detection, such as local outlier factor. Semi-supervised learning concepts may include: generative models; low–density separation; graph-based methods, and co -training. Reinforcement learning concepts may include temporal difference learning; Q -learning, learning automata, and SARSA. Deep learning concepts may include deep belief networks; deep Boltzmann machines; deep convolutional neural networks; deep recurrent neural networks; and hierarchical temporal memory. MS Detection Proteins

[0106] One or more features were fed into one or more computation models. The classifiers were used to calculate a score for the patient. The scores of different classifiers were combined to identify the patient as having MS or not. The computational model only selected protein or protein combinations that could generate a receiver operating characteristic (ROC) curve of greater than or equal to 0.6. The resulting MS detection proteins are shown in Table 1. FIG.1 shows that the accuracy is over 0.7 when any two proteins through any 20 proteins are randomly selected.

[0107] The model also identified particular substes of the proteins of Table 1 from which one or more proteins can be selected from to detect MS. Such subsets are presented in Table 2, Table 3, and Table 4. In addition, it was determined that a panel of all of the proteins listed in Table 2 provides an AUC of about 0.772 (see FIG.2), a panel of all of the proteins listed in Table 3 provides an AUC of about 0.842 (see FIG.3) , and a panel of all of the proteins listed in Table 4 provides an AUC of about 0.881 (see FIG.4). Table 1. MS detection proteins.Attorney Docket No. NVLNA.010.WO1Attorney Docket No. NVLNA.010.WO1 Table 2. Subset of MS detection proteins from Table 1, which together can achieve an AUC of 0.772.Table 3. Subset of MS detection proteins from Table 1, which together can achieve an AUC of 0.842.Attorney Docket No. NVLNA.010.WO1 Table 4. Subset of MS detection proteins from Table 1, which together can achieve an AUC of 0.881.Attorney Docket No. NVLNA.010.WO1 EMBODIMENTS

[0108] Select embodiments of the present invention are as follows: Embodiment 1. A method of evaluating a subject for MS, the method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the subject for MS. Embodiment 2. The method of Embodiment 1, further comprising applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS. Embodiment 3. The method of Embodiment 1 or 2, further comprising administering a treatment to the subject. Embodiment 4. A method of treating MS in a subject, comprising (a) acquiring results from the method of Embodiments 1 or 2; and (b) administering a treatment to the subject. Embodiment 5. The method of Embodiment 4, wherein the treatment is responsive to the results acquired in (a). Embodiment 6. The method of Embodiment 4 or 5, wherein (a) comprises: (i) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and (ii) applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS. Embodiment 7. A method of treating MS in a subject, the method comprising: (a) acquiring results from an evaluation of the subject that determined the subject has MS; (b) administering a treatment to the subject,Attorney Docket No. NVLNA.010.WO1 wherein the evaluation comprises: (i) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and (ii) applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS. Embodiment 8. The method of any one of Embodiments 4-7, wherein the results in (a) are acquired from a third party. Embodiment 9. A method of detecting MS in a subject, the method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected. Embodiment 10. The method of Embodiment 9, further comprising administering a treatment to the subject. Embodiment 11. A method of treating MS in a subject, comprising (a) acquiring results from the method of Embodiment 9; and (b) administering a treatment to the subject. Embodiment 12. The method of Embodiment 11, wherein the treatment is responsive to the results acquired in (a). Embodiment 13. A method of treating MS in a subject, the method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected; and administering a treatment to the subject when MS is detected.Attorney Docket No. NVLNA.010.WO1 Embodiment 14. A method of treating MS in a subject in whom MS was detected, the method comprising administering a treatment for MS to the subject, wherein MS was detected in the subject by a method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected. Embodiment 15. The method of Embodiment 14, wherein the method of detecting MS was performed by a third party. Embodiment 16. The method of any one of Embodiments 1-15, wherein the subject is asymptomatic of MS. Embodiment 17. The method of Embodiment 16, wherein the subject is undergoing a screen for MS. Embodiment 18. The method of any one of Embodiments 1-17, wherein the subject is symptomatic of MS. Embodiment 19. A method of evaluating a treatment for MS in a subject, the method comprising: administering a treatment for MS, and determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the treatment. Embodiment 20. A method of evaluating the efficacy of a treatment for MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the efficacy of the treatment.Attorney Docket No. NVLNA.010.WO1 Embodiment 21. A method of treating MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins to evaluate the efficacy of the treatment, wherein the one or more proteins are selected from Table 1. Embodiment 22. A method of adjusting a treatment for MS in a subject, the method comprising (a) administering a treatment for MS to the subject, (b) determining in a biological sample from the subject a concentration of one or more proteins, wherein the one or more proteins are selected Table 1, and (c) administering an adjusted treatment to the subject when it is determined that the adjusted treatment is necessary. Embodiment 23. A method of treating MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins to evaluate whether the treatment requires adjustment, wherein the one or more proteins are selected from Table 1. Embodiment 24. The method of Embodiment 23, further comprising administering an adjusted treatment when it is determined that the adjusted treatment is necessary. Embodiment 25. The method of any one of Embodiments 19-24, further comprising applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS. Embodiment 26. The method of any one of Embodiments 1-25, wherein the biological sample is selected from a plasma sample, serum sample, saliva sample, CSF sample, sweat sample, urine sample, or tear sample.Attorney Docket No. NVLNA.010.WO1 Embodiment 27. The method of Embodiment 26, wherein the biological sample is a urine sample. Embodiment 28. The method of any one of Embodiments 1-27, further comprising collecting the biological sample from the subject. Embodiment 29. The method of Embodiment 28, wherein the collection of the biological sample is performed in the home of the subject. Embodiment 30. The method of Embodiment 29, wherein the collection of the biological sample is performed in a medical facility. Embodiment 31. The method of any one of Embodiments 1-30, wherein the determination of the concentration of the one or more proteins is performed in the home of the subject. Embodiment 32. The method of any one of Embodiments 1-30, wherein the determination of the concentration of the one or more proteins is performed in a medical facility. Embodiment 33. The method of any one of Embodiments 1-32, wherein the number of proteins for which the concentration is determined is sufficient to achieve an area-under-the- curve (AUC) of a ROC curve of at least about 0.6. Embodiment 34. The method of Embodiment 33, wherein the number of proteins for which the concentration is determined is sufficient to achieve an AUC of a ROC curve of at least about 0.7. Embodiment 35. The method of any one of Embodiments 1-34, wherein the concentration of the two or more proteins is determined by one or more assays. Embodiment 36. The method of any one of Embodiments 19-35, wherein the administration of the treatment in (a) is performed by a third party.Attorney Docket No. NVLNA.010.WO1 Embodiment 37. The method of any one of Embodiments 19-35, wherein the determination in a urine sample from the subject a concentration of one or more proteins in (b) is performed by a third party. Embodiment 38. A method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 1. Embodiment 39. The method of any one of Embodiments 1-38, wherein the one or more proteins are selected from Table 2. Embodiment 40. The method of any one of Embodiments 1-38, wherein the one or more proteins are selected from Table 3. Embodiment 41. The method of any one of Embodiments 1-38, wherein the one or more proteins are selected from Table 4. Embodiment 42. The method of any one of Embodiments 1-41, wherein two or more proteins are selected. Embodiment 43. The method of any one of Embodiments 1-41, wherein three or more proteins are selected. Embodiment 44. The method of any one of Embodiments 1-41, wherein five or more proteins are selected. Embodiment 45. The method of any one of Embodiments 1-40, wherein ten or more proteins are selected. Embodiment 46. The method of any one of Embodiments 1-40, wherein 20 or more proteins are selected.Attorney Docket No. NVLNA.010.WO1 Embodiment 47. The method of any one of Embodiments 1-38 or 40, wherein 30 or more proteins are selected. Embodiment 48. The method of any one of Embodiments 1-38 or 40, wherein 40 or more proteins are selected. Embodiment 49. The method of any one of Embodiments 1-38, wherein 50 or more proteins are selected. Embodiment 50. The method of any one of Embodiments 1-38, wherein 60 or more proteins are selected. Embodiment 51. The method of any one of Embodiments 1-41, wherein all proteins are selected. Embodiment 52. The method of any one of Embodiments 1-38, wherein no more than about 60 proteins are selected. Embodiment 53. The method of any one of Embodiments 1-38, wherein no more than about 50 proteins are selected. Embodiment 54. The method of any one of Embodiments 1-38 or 40, wherein no more than about 40 proteins are selected. Embodiment 55. The method of any one of Embodiments 1-38 or 40, wherein no more than about 30 proteins are selected. Embodiment 56. The method of any one of Embodiments 1- 40, wherein no more than about 20 proteins are selected. Embodiment 57. The method of any one of Embodiments 1-40, wherein no more than about ten proteins are selected.Attorney Docket No. NVLNA.010.WO1 Embodiment 58. The method of any one of Embodiments 1-41, wherein no more than about five proteins are selected.Attorney Docket No. NVLNA.010.WO1 REFERENCES GBD 2016 Neurology Collaborators, Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016, The Lancet. Neurology, 2019, 18(5): 459-480. McGinley MP., et al., Diagnosis and treatment of multiple sclerosis: a review, JAMA, 2021, 325(8): 765-779. Miller JR., The importance of early diagnosis of multiple sclerosis, Journal of Managed Care Pharmacy, 2004, 10(3 Suppl. B): S4-S11. Walton C., et al., Rising prevalence of multiple sclerosis worldwide: insights from the Atlas of MS, third edition, Multiple Sclerosis, 2020, 26(14): 1816-1821.

Claims

Attorney Docket No. NVLNA.010.WO1 CLAIMS 1. A method of evaluating a subject for MS, the method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the subject for MS.

2. The method of claim 1, further comprising applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS.

3. The method of claim 1 or 2, further comprising administering a treatment to the subject.

4. A method of treating MS in a subject, comprising (a) acquiring results from the method of claim 1 or 2; and (b) administering a treatment to the subject.

5. The method of claim 4, wherein the treatment is responsive to the results acquired in (a).

6. The method of claim 4 or 5, wherein (a) comprises: (i) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and (ii) applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS.

7. A method of treating MS in a subject, the method comprising: (a) acquiring results from an evaluation of the subject that determined the subject has MS; (b) administering a treatment to the subject, wherein the evaluation comprises:Attorney Docket No. NVLNA.010.WO1 (i) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and (ii) applying a classifier to the concentration of the one or more proteins to identify whether the subject has MS.

8. The method of any one of claims 4-7, wherein the results in (a) are acquired from a third party.

9. A method of detecting MS in a subject, the method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected.

10. The method of claim 9, further comprising administering a treatment to the subject.

11. A method of treating MS in a subject, comprising (a) acquiring results from the method of claim 9; and (b) administering a treatment to the subject.

12. The method of claim 11, wherein the treatment is responsive to the results acquired in (a).

13. A method of treating MS in a subject, the method comprising determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected; and administering a treatment to the subject when MS is detected.Attorney Docket No. NVLNA.010.WO1 14. A method of treating MS in a subject in whom MS was detected, the method comprising administering a treatment for MS to the subject, wherein MS was detected in the subject by a method comprising: determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; and applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative that MS is detected.

15. The method of claim 14, wherein the method of detecting MS was performed by a third party.

16. The method of any one of claims 1-15, wherein the subject is asymptomatic of MS.

17. The method of claim 16, wherein the subject is undergoing a screen for MS.

18. The method of any one of claims 1-17, wherein the subject is symptomatic of MS.

19. A method of evaluating a treatment for MS in a subject, the method comprising: (a) administering a treatment for MS, and (b) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the treatment.

20. A method of evaluating the efficacy of a treatment for MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins selected from Table 1; thereby evaluating the efficacy of the treatment.Attorney Docket No. NVLNA.010.WO1 21. A method of treating MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins to evaluate the efficacy of the treatment, wherein the one or more proteins are selected from Table 1.

22. A method of adjusting a treatment for MS in a subject, the method comprising (a) administering a treatment for MS to the subject, (b) determining in a biological sample from the subject a concentration of one or more proteins, wherein the one or more proteins are selected Table 1, and (c) administering an adjusted treatment to the subject when it is determined that the adjusted treatment is necessary.

23. A method of treating MS in a subject, the method comprising (a) administering a treatment for MS to the subject, and (b) determining in a biological sample from the subject a concentration of one or more proteins to evaluate whether the treatment requires adjustment, wherein the one or more proteins are selected from Table 1.

24. The method of claim 23, further comprising administering an adjusted treatment when it is determined that the adjusted treatment is necessary.

25. The method of any one of claims 19-24, further comprising applying a classifier to the concentration of the one or more proteins that identifies whether the concentration of the one or more proteins is indicative of the subject having MS.

26. The method of any one of claims 1-25, wherein the biological sample is selected from a plasma sample, serum sample, saliva sample, CSF sample, sweat sample, urine sample, or tear sample.

27. The method of claim 26, wherein the biological sample is a urine sample.Attorney Docket No. NVLNA.010.WO1 28. The method of any one of claims 1-27, further comprising collecting the biological sample from the subject.

29. The method of claim 28, wherein the collection of the biological sample is performed in the home of the subject.

30. The method of claim 29, wherein the collection of the biological sample is performed in a medical facility.

31. The method of any one of claims 1-30, wherein the determination of the concentration of the one or more proteins is performed in the home of the subject.

32. The method of any one of claims 1-30, wherein the determination of the concentration of the one or more proteins is performed in a medical facility.

33. The method of any one of claims 1-32, wherein the number of proteins for which the concentration is determined is sufficient to achieve an area-under-the-curve (AUC) of a ROC curve of at least about 0.

6.

34. The method of claim 33, wherein the number of proteins for which the concentration is determined is sufficient to achieve an AUC of a ROC curve of at least about 0.

7.

35. The method of any one of claims 1-34, wherein the concentration of the two or more proteins is determined by one or more assays.

36. The method of any one of claims 19-35, wherein the administration of the treatment in (a) is performed by a third party.

37. The method of any one of claims 19-35, wherein the determination in a urine sample from the subject a concentration of one or more proteins in (b) is performed by a third party.Attorney Docket No. NVLNA.010.WO1 38. A method of measuring amounts of proteins in a subject, the method comprising determining individual amounts of one or more proteins selected from Table 1.

39. The method of any one of claims 1-38, wherein the one or more proteins are selected from Table 2.

40. The method of any one of claims 1-38, wherein the one or more proteins are selected from Table 3.

41. The method of any one of claims 1-38, wherein the one or more proteins are selected from Table 4.

42. The method of any one of claims 1-41, wherein two or more proteins are selected.

43. The method of any one of claims 1-41, wherein three or more proteins are selected.

44. The method of any one of claims 1-41, wherein five or more proteins are selected.

45. The method of any one of claims 1-40, wherein ten or more proteins are selected.

46. The method of any one of claims 1-40, wherein 20 or more proteins are selected.

47. The method of any one of claims 1-38 or 40, wherein 30 or more proteins are selected.

48. The method of any one of claims 1-38 or 40, wherein 40 or more proteins are selected.Attorney Docket No. NVLNA.010.WO1 49. The method of any one of claims 1-38, wherein 50 or more proteins are selected.

50. The method of any one of claims 1-38, wherein 60 or more proteins are selected.

51. The method of any one of claims 1-41, wherein all proteins are selected.

52. The method of any one of claims 1-38, wherein no more than about 60 proteins are selected.

53. The method of any one of claims 1-38, wherein no more than about 50 proteins are selected.

54. The method of any one of claims 1-38 or 40, wherein no more than about 40 proteins are selected.

55. The method of any one of claims 1-38 or 40, wherein no more than about 30 proteins are selected.

56. The method of any one of claims 1-40, wherein no more than about 20 proteins are selected.

57. The method of any one of claims 1-40, wherein no more than about ten proteins are selected.

58. The method of any one of claims 1-41, wherein no more than about five proteins are selected.

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