Progressive multiple sclerosis differential diagnosis marker based on immunophenomics and application thereof

Abstract

The invention discloses a progressive multiple sclerosis differential diagnosis marker based on immunophenomics and application of the progressive multiple sclerosis differential diagnosis marker. The invention specifically provides an immune biomarker set for identifying progressive or recurrent remission type multiple sclerosis and a corresponding reagent and kit thereof. The immune biological marker provided by the invention comprises one or more of the following groups: a) activating a T cell subset; b) a CD28 < + > and CD28-T cell subset; c) forming a subgroup by the CD8 + T cells; and d) a MAIT cell subset category. The immune biomarker disclosed by the invention can also be applied in a multi-index combination manner, and can be applied to a) multiple sclerosis patients which are not subjected to disease modification treatment; b) a patient with multiple sclerosis treated by disease modification; and c) a very good effect of distinguishing clinical subtypes of the multiple sclerosis can be achieved in the three types of people of the multiple sclerosis patients who do not distinguish whether the multiple sclerosis patients are subjected to the disease modification treatment or not.

Description

Technical Field

[0001] The present invention relates to a differential diagnosis biomarker for progressive multiple sclerosis based on immunophenomics and its application, belonging to the technical field of clinical laboratory and diagnosis. Background Art

[0002] Multiple sclerosis is an immune-mediated inflammatory demyelinating disease of the central nervous system. It can damage the protective layer around the nerves in the brain and spinal cord due to inflammation. In the areas of the brain and spinal cord affected by multiple sclerosis, the signals transmitted across nerves are slowed down or blocked, leading to neurological symptoms, thus resulting in a decline in quality of life and disability. Multiple sclerosis usually occurs between the ages of 20 and 30, and there is a gender bias in its onset. The likelihood of women developing multiple sclerosis is almost three times that of men.

[0003] There are multiple clinical subtypes within multiple sclerosis, including relapsing-remitting multiple sclerosis, and progressive multiple sclerosis represented by primary progressive multiple sclerosis and secondary progressive multiple sclerosis.

[0004] Progressive multiple sclerosis rarely has an obvious relapse-remission process. At the same time, the disability dysfunction of patients shows a slow progressive aggravation independent of relapses, seriously affecting the daily life of patients. Currently, the diagnosis of progressive multiple sclerosis is usually a retrospective conclusion obtained through a combination of disability dysfunction scores, clinical, and imaging data. There are often cases of delayed diagnosis, and there is still a lack of clear diagnostic criteria. It can be seen that the above diagnostic process requires relatively high clinical experience of doctors and there is also a risk of misdiagnosis, which is not conducive to the early diagnosis and targeted treatment of patients with progressive multiple sclerosis.

[0005] Therefore, it is crucial to distinguish the subtypes of multiple sclerosis patients at an early stage and provide other tools for assisting in the differentiation of progressive multiple sclerosis, especially detectable biomarkers. In fact, differentiating progressive multiple sclerosis and relapsing-remitting multiple sclerosis at an early stage can help more appropriately conduct targeted follow-up and personalized treatment plan formulation for multiple sclerosis patients. Summary of the Invention

[0006] In view of the above-mentioned disadvantages of the prior art, the purpose of the present invention is to provide a biomarker for differentiating progressive multiple sclerosis and relapsing-remitting multiple sclerosis. The subjects are patients with multiple sclerosis, and the sclerosis patients can be multiple sclerosis patients who have or have not undergone disease-modifying treatment, or multiple sclerosis patients who have or have not been treated.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] In a first aspect of the present invention, there is provided an immunobiomarker for assisting in the diagnosis of an internal clinical subtype of multiple sclerosis, wherein the internal clinical subtype of multiple sclerosis is progressive multiple sclerosis or relapsing-remitting multiple sclerosis, and the immunobiomarker comprises one or more of the following immune cell subsets:

[0009] a) Activated T cell subset;

[0010] b) CD28 + and CD28 - T cell subset;

[0011] c) CD8 + T cell constituent subset;

[0012] d) MAIT cell subset category.

[0013] In some preferred embodiments of the present invention, the activated T cell subset category comprises one or more of the following immune cells: activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells); activated CD3 + T cells: which simultaneously express CD3, HLA-DR and CD38 molecules on their surface; activated CD8 + T cells: which simultaneously express CD8, HLA-DR and CD38 molecules on their surface.

[0014] In some preferred embodiments of the present invention, the CD28 + and CD28 - T cell subset includes: CD28 + CD8 + T cells, CD28 - CD8 + T cells, and CD28 + / CD28 - CD8 + T cell ratio of one or more.

[0015] In some preferred embodiments of the present invention, the CD8 + T cell constituent subset includes: Tc2 cells, Tc9 cells, Tc17Tc1 cells, and one or more of the Tc1 / Tc2 cell ratios.

[0016] In some preferred embodiments of the present invention, the MAIT cell subset categories include one or more of the following immune cells: MAIT cells, CD8 + MAIT cells.

[0017] In some preferred embodiments of the present invention, the immunobiological markers are selected from any one of the following groups:

[0018] a) One or more immune cells selected from the activated T cell subset categories and one or more immune cells selected from the CD28 + and CD28 - T cell subset categories;

[0019] b) One or more immune cells selected from the activated T cell subset categories and one or more immune cells selected from the CD8 + T cell component subset categories;

[0020] c) One or more immune cells selected from the activated T cell subset categories and one or more immune cells selected from the MAIT cell subset categories;

[0021] d) One or more immune cells selected from the CD28 + and CD28 - T cell subset categories and one or more immune cells selected from the CD8+ T cell component subset categories;

[0022] e) One or more immune cells selected from the CD28 + and CD28 - T cell subset categories and one or more immune cells selected from the MAIT cell subset categories;

[0023] f) One or more immune cells selected from the CD8 + T cell component subset categories and one or more immune cells selected from the MAIT cell subset categories;

[0024] g) One or more immune cells selected from the activated T cell subset categories and one or more immune cells selected from the CD28 + and CD28 - T cell subset categories and, one or more immune cells selected from the CD8 + T cell component subset categories;

[0025] h) One or more immune cells selected from the activated T cell subset categories and one or more immune cells selected from the CD28 + and CD28 - T cell subset categories and, one or more immune cells selected from the MAIT cell subset categories;

[0026] i) One or more immune cells selected from the group consisting of CD28 + and CD28 - T cell subset categories and one or more immune cells selected from CD8 + T cell compositional subset categories and one or more immune cells selected from MAIT cell subset categories;

[0027] j) One or more immune cells selected from the group consisting of activated T cell subset categories and one or more immune cells selected from CD28 + and CD28 - T cell subset categories and one or more immune cells selected from CD8+ T cell compositional subset categories and one or more immune cells selected from MAIT cell subset categories

[0028] In some preferred embodiments of the present invention, among the immune biomarkers in any of the above groups, there are further included clinical indicators related to increasing any one or more of the following internal clinical subtypes of multiple sclerosis:

[0029] a) EDSS Score;

[0030] b) SDMT Score;

[0031] c) FSS Score.

[0032] It is generally considered that patients with progressive multiple sclerosis have more severe neurological deficits, lower cognitive abilities, and more severe fatigue, but it is also affected by the course of multiple sclerosis itself. Therefore, these three types of clinical scores cannot directly determine the likelihood of being identified as a progressive subtype, and it requires the judgment of a clinician in combination with other results.

[0033] In some preferred embodiments of the present invention, the immune biomarker is selected from any one of the immune cell subset marker combinations in Table 1 or Table 3 of the specification.

[0034] In some preferred embodiments of the present invention, the immune biomarker in combination with the clinical scores related to the internal clinical subtypes of multiple sclerosis is selected from any one of the combinations of immune cell subset markers and clinical scores in Table 2 or Table 4 of the specification.

[0035] In some preferred embodiments of the present invention, the biomarker is derived from a blood or whole blood sample.

[0036] In a second aspect of the present invention, there is provided a reagent for assisting in the diagnosis of internal clinical subtypes of multiple sclerosis, the reagent comprising a reagent for detecting the immune biomarker described in the first aspect of the present invention.

[0037] In some preferred embodiments of the present invention, the reagent includes substances for detecting the immunobiomarkers described in the first aspect of the present invention by immunoprecipitation, flow cytometry, Western blotting, ELISA, ELISPOT, antibody microarray, immunohistology, dot blotting, protein microarray, tissue microarray coupled with immunohistochemistry, or other well-known conventional immunological detection / analysis techniques.

[0038] In some preferred embodiments of the present invention, the reagent includes antibodies corresponding to each immunobiomarker in the biomarker set described in the first aspect of the present invention.

[0039] In some preferred embodiments of the present invention, detecting the immunobiomarker refers to determining the proportion of immune cells or determining the function of immune cells.

[0040] Preferably, the proportion of immune cells refers to the percentage of the number of immune cell subsets or immune cells in the immune cells in peripheral blood.

[0041] More preferably, the proportion of immune cells refers to the percentage of the number of immune cell subsets or immune cells in peripheral blood CD45 + cells or white blood cells.

[0042] More preferably, the proportion of immune cells refers to the percentage of the number of immune cell subsets or immune cells in their progenitor population of immune cells or the percentage of the number of immune cells in their parental population of immune cells.

[0043] Preferably, the function of immune cells refers to the expression level of immune function molecules, or the protein level of immune function molecules.

[0044] Preferably, the method for detecting the immunobiomarker includes one or more of the following: immunoprecipitation, flow cytometry, Western blotting, ELISA, ELISPOT, antibody microarray, immunohistology, dot blotting, protein microarray, tissue microarray coupled with immunohistochemistry, or other well-known conventional immunological detection / analysis techniques.

[0045] In the third aspect of the present invention, there is provided a kit for detecting the proportion of immune cells and / or the function of immune cells of the immunobiomarkers described in the first aspect of the present invention, the kit comprising: specific tools or reagents for measuring the proportion of immune cells and / or the function of immune cells in a biological sample, and auxiliary reagents for measuring immune cell subsets and / or the function of immune cells in a biological sample.

[0046] In some preferred embodiments of the present invention, the kit further comprises a positive control sample, such samples being calibrated to represent the proportion value and / or the immune cell function value of immune cells of patients / subjects with a high risk of progressive multiple sclerosis. Preferably, the positive control sample is from one or more patients / subjects known to have progressive multiple sclerosis.

[0047] In some preferred embodiments of the present invention, the kit further comprises a negative control sample, such samples being calibrated to represent the proportion value and / or the immune cell function value of immune cells of patients / subjects with a low risk of progressive multiple sclerosis. Preferably, the negative control sample is from one or more patients / subjects known to have relapsing-remitting multiple sclerosis.

[0048] In another preferred example, the kit further comprises an instruction manual, which stipulates that if the proportion values of Tc2, activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells) among the detected immunobiological markers are higher than the reference value, it indicates that the subject has a high risk of being a patient with progressive multiple sclerosis. If the proportion or immune cell function value of immune cells among other said immunobiological markers is lower than the reference value, it indicates that the subject has a high risk of being a patient with progressive multiple sclerosis.

[0049] In another preferred example, the kit is used to assist in diagnosing the internal clinical subtypes of multiple sclerosis patients, that is, to distinguish between progressive multiple sclerosis and relapsing-remitting multiple sclerosis.

[0050] In the fourth aspect of the present invention, there is provided an application of an immunobiological marker or a detection reagent thereof as described in the first aspect of the present invention in the preparation of a product for assisting in diagnosing the internal clinical subtypes of multiple sclerosis, wherein the internal clinical subtypes of multiple sclerosis are progressive multiple sclerosis or relapsing-remitting multiple sclerosis.

[0051] In some preferred embodiments of the present invention, the population for the said application includes: a) multiple sclerosis patients who have not undergone disease-modifying treatment; b) multiple sclerosis patients who have undergone disease-modifying treatment; c) multiple sclerosis patients regardless of whether they have undergone disease-modifying treatment.

[0052] In a fifth aspect of the present invention, there is provided a method for establishing a model for assisting in diagnosing internal clinical subtypes of multiple sclerosis, the method comprising the step of identifying differential biomarkers in biological samples between progressive multiple sclerosis and relapsing-remitting multiple sclerosis in patients with multiple sclerosis, wherein the differential biomarkers include the immunobiomarkers described in the first aspect of the present invention, and using a machine learning algorithm to screen for a feature combination with diagnostic value and construct a diagnostic model, the feature combination being selected from at least two of the immunobiomarkers, or at least one of the immunobiomarkers and components of a clinical score; the clinical score being selected from at least one of an EDSS score, an SDMT score, and an FSS score.

[0053] In some preferred embodiments of the present invention, the clinical scoring metrics include one or more of an Expanded Disability Status Scale (EDSS) score, a symbol digit modalities test (SDMT) score, and a fatigue severity scale (FSS) score.

[0054] In some preferred embodiments of the present invention, the machine learning algorithm includes one or more of a support vector machine (SVM), a random forest, a logistic regression, a LASSO regression, and a partial least squares discriminant analysis (PLSDA).

[0055] In some preferred embodiments of the present invention, the constructing of the diagnostic model includes: first screening for a feature combination with diagnostic value using a LASSO regression model, and then constructing a random forest diagnostic model with the screened feature combination.

[0056] In a sixth aspect of the present invention, there is provided a system for assisting in diagnosing internal clinical subtypes of multiple sclerosis, the system comprising:

[0057] A feature receiving module for receiving feature data from a sample of a subject to be tested; the feature data including: the levels of the immunobiomarkers as described in the first aspect of the present invention in the sample of the subject to be tested, which include the proportion value and / or the functional value of immune cells of the immunobiomarkers.

[0058] A discrimination processing module for comparing the received feature data with a reference value or inputting the received feature data into a pre-constructed diagnostic model to obtain a diagnostic or evaluation result, wherein when the detected immunobiomarkers Tc2, activated CD3 + T cells (HLA-DR+ CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + If the proportion value of T cells) is higher than the reference value, it indicates a high risk that the subject is a patient with progressive multiple sclerosis. If the proportion of immune cells or the functional value of immune cells among the other described immune biomarkers is lower than the reference value, it indicates a high risk that the subject is a patient with progressive multiple sclerosis;

[0059] Result output module, which is used to receive and output the evaluation result.

[0060] In some preferred embodiments of the present invention, the characteristic data further includes at least one of EDSS score, SDMT score and FSS score.

[0061] In some preferred embodiments of the present invention, the construction of the diagnostic model includes: first, screening the characteristic combinations with diagnostic value by using the LASSO regression model, and then constructing a random forest diagnostic model with the screened characteristic combinations.

[0062] In some preferred embodiments of the present invention, the subject is a patient with multiple sclerosis.

[0063] In some preferred embodiments of the present invention, the detection method for the level of the immune biomarker includes: immunoprecipitation, flow cytometry, Western blotting, ELISA, ELISPOT, antibody microarray, immunohistology, dot blotting, protein microarray, tissue microarray coupled with immunohistochemistry, or other well-known conventional immunological detection / analysis techniques.

[0064] In some preferred embodiments of the present invention, the characteristic receiving module includes a sample collector and a characteristic signal input terminal.

[0065] In some preferred embodiments of the present invention, the discrimination processing module includes a processor and a storage, wherein the storage stores the level data of the immune biomarker as described in the first aspect of the present invention from healthy controls.

[0066] In some preferred embodiments of the present invention, the output module includes any terminal, preferably a display, a printer, a tablet computer (PAD), a smart phone.

[0067] In some preferred embodiments of the present invention, the modules are connected by wired or wireless means.

[0068] In a seventh aspect of the present invention, a method is provided for using the set of immune biomarkers described in the first aspect of the present invention in a subject to be tested as an indicator for assisting in the diagnosis of the internal clinical subtypes of multiple sclerosis and for differentiating progressive multiple sclerosis from relapsing-remitting multiple sclerosis.

[0069] The method includes determining the levels of the immune biomarkers in a sample from the subject to be tested, including immune cell proportion values and / or immune cell function values.

[0070] The method uses the levels of the immune biomarkers as an indicator for assisting in the diagnosis of the internal clinical subtypes of multiple sclerosis and for differentiating progressive multiple sclerosis from relapsing-remitting multiple sclerosis.

[0071] In some preferred embodiments of the present invention, the method uses the comparison of the levels of the biomarkers with reference values as an indicator for assisting in the diagnosis of the internal clinical subtypes of multiple sclerosis and for differentiating progressive multiple sclerosis from relapsing-remitting multiple sclerosis.

[0072] In some preferred embodiments of the present invention, for the levels of the immune biomarkers, when the proportion values of the detected immune biomarkers Tc2, activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells) are higher than the reference values, it indicates a high risk that the subject to be tested is a patient with progressive multiple sclerosis. If the immune cell proportion or immune cell function value among the other described immune biomarkers is lower than the reference value, it also indicates a high risk that the subject to be tested is a patient with progressive multiple sclerosis.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] (1) The present invention discovers for the first time a new set of immune biomarkers, which include one or more of the following immune cell subsets: a) activated T cell subsets; b) CD28+ and CD28- T cell subsets; c) CD8+ T cell component subsets; d) MAIT cell subsets; By detecting the proportion or function of the above immune biomarkers, it can be used to assist in the diagnosis of the internal clinical subtypes of multiple sclerosis patients, that is, to differentiate progressive multiple sclerosis or relapsing-remitting multiple sclerosis, with relatively high prediction / evaluation accuracy, and the set of biomarkers of the present invention can also be combined with other indicators for application, having a very good effect in differentiating the internal subtypes of multiple sclerosis.

[0075] (2) The present invention can quickly determine the internal clinical subtypes of multiple sclerosis patients, which helps clinicians develop personalized diagnosis and treatment plans for patients;

[0076] (3) The patient population to which the present invention is applied includes a) multiple sclerosis patients who have not undergone disease-modifying treatment; b) multiple sclerosis patients who have undergone disease-modifying treatment; c) multiple sclerosis patients regardless of whether they have undergone disease-modifying treatment, and the application scope is wide. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 For the peripheral blood samples of the subjects used in the embodiments of the present invention, the categories of activated T cell subsets, CD28 + and CD28 - T cell subset categories, CD8 + T cell subset categories that make up the T cell subsets, MAIT cell subset categories, and other immune cell subset detection results. The patient has multiple sclerosis and is known to be in the progressive or relapsing-remitting form.

[0078] Figure 2 For the categories of activated T cell subsets, CD28 + and CD28 - T cell subset categories, CD8 + ROC curves of individual indicators of immune cell markers such as T cell subset categories that make up the T cell subsets and MAIT cell subset categories. DETAILED DESCRIPTION OF THE INVENTION

[0079] The inventors of the present invention have conducted extensive and in-depth research and for the first time discovered a new set of immune biomarkers. The immunobiological markers include one or more of the following groups: a) categories of activated T cell subsets; b) CD28 + and CD28 - T cell subset categories; c) CD8 + T cell subset categories that make up the T cell subsets; d) MAIT cell subset categories. By detecting the ratios or functions of the above immune biomarkers and applying them to three types of populations: a) multiple sclerosis patients who have not undergone disease-modifying treatment; b) multiple sclerosis patients who have undergone disease-modifying treatment; c) multiple sclerosis patients regardless of whether they have undergone disease-modifying treatment, the effects of assisting in diagnosing the internal clinical subtypes of multiple sclerosis and differentiating progressive multiple sclerosis from relapsing-remitting multiple sclerosis are achieved. On this basis, the inventors completed the present invention.

[0080] TERMS

[0081] The terms used in the present invention have the meanings commonly understood by those of ordinary skill in the relevant art. However, for a better understanding of the present invention, the following explanations of some definitions and related terms are provided:

[0082] According to the present invention, the term "individual" refers to an animal, particularly a mammal, such as a primate, and preferably a human.

[0083] According to the present invention, terms such as "a", "an", and "the" not only refer to a single individual, but also include the general category that can be used to illustrate a specific embodiment.

[0084] As used herein, the term "Disease-Modifying Therapy (DMT)" refers to a treatment that achieves a change in the clinical progression trajectory of a disease through medical intervention; the core of disease-modifying therapy lies in intervening in the pathogenesis of the disease, thereby changing its natural course, with the goal of changing the course of the disease or preventing its further development, rather than simply alleviating symptoms or managing symptoms; this treatment hopes to intervene in the early stage of the disease, thereby delaying or avoiding the occurrence of serious complications and realizing the concept of "preventing disease before it occurs"; the term "treatment" refers to traditional treatment, which often focuses more on the management and alleviation of disease symptoms rather than changing the natural course of the disease. Traditional treatment can include drug treatment, physical therapy, surgical treatment, etc., aiming to relieve the symptoms of patients and improve their quality of life, but may not be able to fundamentally change the course of the disease or prevent its further development.

[0085] As used herein, when referring to a specifically listed numerical value, the term "about" means that the value can vary by no more than 1% from the listed value. For example, as used herein, the expression "about 100" includes all values between 99 and 101 (e.g., 99.1, 99.2, 99.3, 99.4, etc.).

[0086] As used herein, the term "comprising" or "including" can be open-ended, semi-closed, and closed. In other words, the term also includes "consisting essentially of...", or "consisting of...".

[0087] As used herein, a "cell subset" refers to a collection of any cells with certain common characteristics within a cell population with multiple characteristics. Regarding cell subsets with specific names known in the art, this term can be used to refer to the specific cell subset, or any property (such as the expression of cell surface markers) can be recorded to refer to the specific cell subset.

[0088] As used herein, the term "relative amount" of cells can be used interchangeably with "proportion".

[0089] Multiple sclerosis

[0090] Multiple sclerosis is an immune-mediated inflammatory demyelinating disease of the central nervous system that damages the protective layer around the nerves in the brain and spinal cord due to inflammation. In the areas of the brain and spinal cord affected by multiple sclerosis, the signals transmitted across the nerves are slowed down or blocked, leading to neurological symptoms, which in turn result in a decline in quality of life and disability.

[0091] Sample

[0092] As used herein, the term "sample" or "specimen" refers to a material specifically associated with a subject from which specific information related to the subject can be determined, calculated, or inferred. A sample can be wholly or in part composed of biological material from the subject. A sample can also be a material that has been in contact with the subject in such a way that testing the sample can provide information related to the subject. A sample can also be a material that has been in contact with other material that is not the subject, but which enables the first material to subsequently be tested to determine information related to the subject, for example, a sample can be a wash solution of a probe or scalpel. A sample can be a source of biological material outside of contact with the subject, provided that a person of ordinary skill in the art can still determine information related to the subject from the sample.

[0093] Samples are selected from biological fluids such as, for example: blood or whole blood, where "blood" or "whole blood" are used interchangeably in the present invention.

[0094] In all its embodiments, the methods as described above are applied to blood samples containing white blood cells (especially at least containing mononuclear cells). A blood sample can be, for example, a sample of purified lymphocytes. It can also be a sample of peripheral blood mononuclear cells (or PBMCs), which are composed of lymphocytes (B cells, T cells, and NK cells), dendritic cells, and monocytes, and are typically obtained by the Ficoll method well-known to those skilled in the art. However, in order to minimize manipulation of the sample and maintain the physiological cell interactions between the different cell populations involved in the immune response, and to better reflect the complexity of the patient / subject's innate and adaptive immune responses, it is preferred to directly use whole blood samples (i.e., containing all white blood cells, red blood cells, platelets, and plasma) collected by the intravenous route (e.g., by using tubes containing anticoagulants).

[0095] Expression

[0096] As used herein, the term "expression" refers to a cell surface marker (usually a protein) that, after RNA transcription, protein translation, and intracellular trafficking processes, is finally presented on the cell surface. The expression level or intensity of a cell surface marker can be measured by flow cytometry. Preferably, the "high" or "low" expression level of a specific marker between two samples can be reflected by the "more" or "less" proportion of cells whose expression level or intensity reaches or exceeds a specified level. Preferably, the "high" or "low" expression level of a specific marker between two samples is reflected by the "High" or "Low" fluorescence signal intensity.

[0097] Reference value

[0098] As used herein, the term "reference value" or "reference amount" or "reference level" refers to the value (or amount, or level) of a parameter or biomarker that indicates the status of a subject with respect to a particular disease (or minor ailment, or condition). The appropriate reference level of a parameter or biomarker can be quantified, determined, or measured by detecting the parameter / biomarker in a number of suitable reference subjects. Such reference levels can be adjusted according to a specific subject population. The reference value or reference level can be an absolute value, a relative value, a value with an upper or lower limit, a series of values, an average value, a median, an average value, or a value compared to a specific control or baseline value. The reference value can be based on the value of an individual sample, e.g., a value obtained from a sample from a tested subject but at an earlier time point. The reference level can be based on a large number of samples, such as a population of subjects in a chronological age-matched group, or on a pool of samples that includes or excludes the sample to be tested. Depending on the context, the reference level corresponds to the value of a parameter (or biomarker) that is quantified, or determined, or measured on a sample from a patient / subject with multiple sclerosis who is known to have the relapsing-remitting form (referred to as a "relapsing-remitting multiple sclerosis patient"); or corresponds to the average (mean) of the values of a parameter (or biomarker) that are quantified, or determined, or measured on different samples from the same relapsing-remitting multiple sclerosis patient (values quantified / determined / measured on samples collected from the same relapsing-remitting multiple sclerosis patient at various time intervals); or corresponds to the average (or mean) of the values of a parameter / biomarker that are determined / measured on the same sample from a relapsing-remitting multiple sclerosis patient but at various time intervals; or corresponds to the average (or mean) of the values of a parameter / biomarker that are quantified / determined / measured on samples from a number of relapsing-remitting multiple sclerosis patients (at least two relapsing-remitting multiple sclerosis patients).

[0099] The reference subjects are divided into positive reference subjects and negative reference subjects. The positive reference subjects are patients / subjects with multiple sclerosis who are known to be progressive. The negative reference subjects are patients / subjects with multiple sclerosis who are known to be relapsing-remitting.

[0100] Immune Biomarkers of the Present Invention and Their Uses

[0101] In the present invention, a set of biomarkers and their uses are provided, which can be used to prepare a kit for assisting in the diagnosis of internal clinical subtypes of multiple sclerosis and differentiating progressive multiple sclerosis from relapsing-remitting multiple sclerosis.

[0102] Among them, the immune biomarkers include one or more of the following immune cell subsets:

[0103] a) Activated T cell subset categories;

[0104] b) CD28 + and CD28 - T cell subset categories;

[0105] c) CD8 + T cell constituent subset categories;

[0106] d) MAIT cell subset categories.

[0107] In one embodiment, the kit includes: binding molecules specific for each biomarker in the set, specific antibodies, specific amplification primers, specific probes or chips, isotopes, enzyme-substrate complexes, or combinations thereof. Specifically, specific polyclonal or monoclonal antibodies can be mentioned, preferably monoclonal antibodies, or fragments or derivatives thereof.

[0108] In another preferred embodiment, each biomarker is detected or identified by one or more methods selected from the group consisting of: immunoprecipitation, flow cytometry, Western blotting, ELISA, ELISPOT, antibody microarray, immunohistology, dot blotting, protein microarray, tissue microarray coupled with immunohistochemistry, or other well-known conventional immunological detection / analysis techniques.

[0109] In a specific embodiment, it is detected or identified by specific antibodies against the surface proteins of each biomarker.

[0110] In a preferred embodiment, the present invention relates to a method for identifying progressive multiple sclerosis and relapsing-remitting multiple sclerosis, wherein the patient / subject is a patient in a hospital, preferably a patient with multiple sclerosis who has not undergone disease-modifying treatment, and more preferably a patient with multiple sclerosis who has not been treated. The method comprises the following steps or even consists of the following steps:

[0111] (1) Provide a sample from the subject to be tested, and detect each of the immune biomarkers in the set of immune biomarkers described in the first aspect of the present invention in the sample, including detecting the proportion of immune cells and / or the function of immune cells;

[0112] (2) If among the immune biomarkers measured in step (1), the proportion values of Tc2, activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells) are higher than the reference values, it indicates that the subject to be tested has a high risk of being a patient with progressive multiple sclerosis. If the proportion or function value of immune cells among other immune biomarkers included in this patent is lower than the reference value, it indicates that the subject to be tested has a high risk of being a patient with progressive multiple sclerosis.

[0113] The categories of activated T cell subsets described in the present invention include one or more of the following immune cells: activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells). Among them, both CD38 and HLA-DR are markers of cell activation. Among them, HLA-DR is the human class II major histocompatibility complex antigen. Most T cells do not express HLA-DR, but at the late stage of T cell activation during the immune response stage, some activated T cells express HLA-DR. CD38 is constitutively expressed in naive T cells, downregulated in resting memory cells, and then elevated again in activated cells.

[0114] The activated CD3 + T cells described in the present invention have the surface marker expression characteristics of CD45 + CD3 + HLA-DR +CD38 + , mainly indicating the activation state of cells, may be related to viral infections in the body, such as HIV and hepatitis B virus infections.

[0115] The activated CD8 + T cells of the present invention have surface marker expression characteristics of CD45 + CD8 + HLA-DR + CD38 + , mainly indicating the activation state of cells, may be related to viral infections in the body, such as HIV and hepatitis B virus infections.

[0116] The CD28 + and CD28 - T cell subsets of the present invention include one or more of the following immune cells: CD28 + CD8 + T cells, CD28 - CD8 + T cells, CD28 + / CD28 - CD8 + T cells. Among them, CD28 is a co-stimulatory molecule that is often expressed on naive and activated T cells and can distinguish CD8 + cytolytic T lymphocytes (CTL) and CD8 + Treg.

[0117] The CD28 + CD8 + T cells of the present invention are cytotoxic and may be related to central nervous system damage. Their surface marker characteristics are CD45 + CD3 + CD4 - CD8 + CD28 + .

[0118] The CD28 - CD8 + T cells of the present invention have the functions of immune regulation and inflammation inhibition. Their surface marker characteristics are CD45 + CD3 + CD4 - CD8 + CD28 - .

[0119] The CD8 + T cell subsets of the present invention include one or more of the following immune cells: Tc2 cells, Tc9 cells, Tc17Tc1 cells, Tc1 / Tc2 cells.

[0120] The Tc1 cells described in the present invention have the following surface marker expression characteristics: CD45 + CD3 + CD4 - CD8 + CXCR3 + CCR4 - CCR6 - , and mainly secrete IFN-γ and TNF-α.

[0121] The Tc2 cells described in the present invention have the following surface marker expression characteristics: CD45 + CD3 + CD4 - CD8 + CXCR3 - CCR4 - CCR6 + , and mainly secrete IL-4, IL-5, and IL-13.

[0122] The Tc9 cells described in the present invention have the following surface marker expression characteristics: CD45 + CD3 + CD4 - CD8 + CCR4 - CCR6 + , and mainly secrete IL-9.

[0123] The Tc17Tc1 cells described in the present invention have the following surface marker expression characteristics: CD45 + CD3 + CD4 - CD8 + CXCR3 + CCR4 - CCR6 + , and mainly secrete IL-17 and IFN-γ.

[0124] The MAIT cell subsets described in the present invention include one or more of the following immune cells: MAIT cells, CD8 + MAIT cells. Among them, MAIT cells are a class of evolutionarily conserved innate-like T lymphocytes, which play a role in maintaining intestinal homeostasis and anti-infection, and may have dual roles of promoting inflammation and immune regulation in CNS diseases.

[0125] The MAIT cells described in the present invention have the following surface marker expression characteristics: CD45 + CD3 + CD161 + TCR Vα7.2 + .

[0126] The CD8 + MAIT cells of the present invention are characterized by the surface marker expression of CD45 + CD3 + CD161 + TCR Vα7.2 + CD8 + .

[0127] In the present invention, the " + " indicates that the marker is positively expressed, and the " - " indicates that the marker is negatively expressed (not expressed). "High" indicates that the marker is expressed and the expression is relatively high, and "low" indicates that the marker is expressed but the expression is relatively low. This is a labeling method well known to those skilled in the art.

[0128] The "proportion of immune cells" or "proportion of immune cell subsets" described in the present invention can have various different calculation forms, and can be any one of the following:

[0129] (1) The percentage of the number of the immune cell subset in the immune cells in peripheral blood;

[0130] (2) The percentage of the number of the immune cell subset in the CD45 + cells in peripheral blood;

[0131] (3) The percentage of the number of the immune cell subset in its progenitor population of immune cells;

[0132] (4) The percentage of the number of the immune cell subset in its parental population of immune cells.

[0133] In the present invention, the "parental population of immune cells" refers to the upper-level immune cells according to the differentiation source of immune cells, or the upper-layer immune cells according to the gating logic sequence of flow cytometry.

[0134] In the present invention, the "progenitor population of immune cells" refers to the upper two levels of immune cells according to the differentiation source of immune cells, or the upper two layers of immune cells according to the gating logic sequence of flow cytometry. The expression level of the immune function molecule is the expression level of the immune function molecule in the immune cell subset, and is referred to as "immune cell function value" in the present invention.

[0135] The expression level of the immune function molecule is the expression level of the immune function molecule in the immune cell subset, and is referred to as "immune cell function value" in the present invention.

[0136] The immune function molecule is selected from one or more of CD28 and HLA-DR.

[0137] It is a method well-known to those skilled in the art to use antibodies against various cell surface antigen proteins / surface markers described above to detect various immune biomarkers of the present invention.

[0138] The method of the present invention is a method carried out in vitro or ex vivo. For example, compared with imaging examinations and EDSS scores, the present invention has the advantage of more easily differentiating progressive multiple sclerosis by providing directly measurable markers, especially in patients with multiple sclerosis who have not received disease-modifying treatment. The measurement of the markers is fully applicable to be carried out by an automated analysis machine or by a test method called a rapid test.

[0139] The sample for implementing the method of the present invention is also referred to as a test sample in the present invention.

[0140] The test sample is taken from a biological sample of a patient expected to be identified with an internal subtype of multiple sclerosis.

[0141] In particular, the test sample is selected from biological fluids such as, for example: blood, whole blood; preferably, in all its embodiments, the method as described above is applied to a blood sample containing white blood cells (especially containing at least mononuclear cells). The blood sample can be, for example, a sample of purified lymphocytes. It can also be a sample of peripheral blood mononuclear cells (or PBMC), which consists of lymphocytes (B cells, T cells, and NK cells), dendritic cells, and monocytes, and is usually obtained by the Ficoll method well-known to those skilled in the art. However, in order to minimize the manipulation of the sample and maintain the physiological cell interactions between different cell populations involved in the immune response, and better reflect the complexity of the patient's innate and adaptive immune responses, it is preferred to directly use a whole blood sample (i.e., containing all white blood cells, red blood cells, platelets, and plasma) collected by the intravenous route (for example, by using a tube containing an anticoagulant).

[0142] Any volume commonly used by those skilled in the art for hematological analysis will be convenient for this method. For example, the volume of the biological sample can be 100 μL, 200 μL, 300 μL, 400 μL, 500 μL, 600 μL, 700 μL, 800 μL, 900 μL, or 1000 μL (1 mL).

[0143] In the context of the present invention, the terms "detection" or "measurement" or "determination" are used interchangeably and have the same meaning. These terms can represent the detection and quantification of the proportion values of immune cells, or the detection and quantification of the expression level values of immune function molecules (the detection and quantification of the immune function molecules at the protein level is called "immune cell function value" in the present invention). For this purpose, any detection and / or quantification method well-known to those skilled in the art can be used to implement the present invention.

[0144] In particular, the determination of the proportion value of immune cells and / or the expression level value of immune function molecules (detection and quantification of the functional molecules at the protein level) is carried out using immune cell- and / or immune function molecule expression level-specific tools or reagents that allow direct or indirect determination of their presence and / or quantification of their expression level.

[0145] Among these tools or reagents capable of detecting and / or quantifying the proportion value of the immune cell subsets and / or the expression level value of immune function molecules, specifically mention may be made of specific polyclonal or monoclonal antibodies, preferably monoclonal antibodies, or fragments or derivatives thereof.

[0146] In the method of the present invention, well-known analytical techniques can be used in particular to detect and / or quantify the proportion value of immune cells and / or the expression level of immune function molecules (immune cell function value), such as cell membrane staining using biotinylation or other equivalent techniques followed by immunoprecipitation with specific antibodies, flow cytometry, Western blotting, ELISA, ELISPOT, antibody microarray, immunoprecipitation, immunohistology, dot blotting, protein microarray, or tissue microarray coupled with immunohistochemistry. Other suitable techniques include FRET or BRET, single-cell microscopy or histochemical methods using single or multiple excitation wavelengths and applying any suitable optical method, such as electrochemical methods (voltammetry and amperometry techniques), atomic force microscopy, and radiofrequency methods, such as multipolar resonance spectroscopy, confocal and non-confocal, detecting fluorescence, luminescence, chemiluminescence, absorbance, reflectance, transmittance, and birefringence or refractive index (e.g., surface plasmon resonance, ellipsometry, resonance mirror method, grating-coupled waveguide method, or interferometry), cell ELISA, radioisotopes, magnetic resonance imaging, polyacrylamide gel electrophoresis (SDS-PAGE) analysis; HPLC-mass spectrometry; liquid chromatography / mass spectrometry / mass spectrometry (LC-MS / MS). For example, when using flow cytometry, forward scatter and side scatter information helps to identify the monocyte population among other blood cells. Preferably, the proportion value of immune cell subsets and / or the expression level of immune function molecules are identified, selected, sorted, quantified (and any combination thereof) by flow cytometry.

[0147] In the present invention, the immune cell subsets and / or immune function molecules (CD28, HLA-DR, CD38) are preferably measured by, for example, flow cytometry, and the proportion value of these immune cell subsets and / or the expression level of immune function molecules are "increased" or "decreased".

[0148] Optionally, for the immune cell subsets and / or immune function molecules (CD28, HLA-DR, CD38), the "increase" or "decrease" in the levels of these immune cell subsets and / or immune function molecules can be measured, for example, by flow cytometry, to measure the "increase" or "decrease" in the levels of the immune cell subsets and / or immune function molecules. The exact amount of the surface immune cell subsets and / or immune function molecules is not important. What is important is to compare the levels of the immune cell subsets and / or immune function molecules in the biological sample to be tested with the levels of the immune cell subsets and / or immune function molecules in a control sample. In other words, it is not necessary to measure the actual quantitative "level" of the immune cell subsets and / or immune function molecules. Preferably, the "high" or "low" levels of the immune cell subsets and / or immune function molecules are measured, and then the levels of the immune cell subsets and / or immune function molecules are compared with the levels of the immune cell subsets and / or immune function molecules in the control sample.

[0149] All of the above instructions and preferences regarding measuring the levels of the immune cell subsets and / or immune function molecules apply equally to measuring the levels in a test sample and in a reference sample.

[0150] The present invention also provides the use of measuring the immune cell proportion value and / or the immune function molecule expression level value in a biological sample in vitro or ex vivo for identification in a patient who is a patient with multiple sclerosis, preferably a patient with multiple sclerosis who has not undergone disease-modifying treatment; more preferably, an untreated patient with multiple sclerosis.

[0151] The present invention also provides a kit for measuring the immune cell proportion and / or the immune function molecule expression level in a biological sample in vitro or ex vivo, the kit comprising:

[0152] Specific tools or reagents for measuring the immune cell proportion and / or the immune function molecule expression level in the biological sample; and

[0153] Auxiliary reagents for measuring the immune cell proportion and / or the immune function molecule expression level in the biological sample; and

[0154] A positive control sample calibrated to have an immune cell proportion value and / or an immune function molecule expression level value corresponding to the average measured value in a sample pool from a patient with multiple sclerosis known to be progressive; and / or

[0155] A negative control sample calibrated to have an immune cell proportion value and / or an immune function molecule expression level value corresponding to the average measured value in a sample pool from a patient with multiple sclerosis known to be relapsing-remitting.

[0156] In particular, the kit of the present invention can be used to assist in the diagnosis of the internal clinical subtypes of patients with multiple sclerosis, that is, to distinguish progressive multiple sclerosis or relapsing-remitting multiple sclerosis, and the patients are those with multiple sclerosis, preferably patients with multiple sclerosis who have not undergone disease-modifying treatment; more preferably, patients with multiple sclerosis who have not been treated.

[0157] Another positive control sample can also be a biological sample obtained from at least one patient with multiple sclerosis who is known to be progressive. Similarly, another negative control sample can also be a biological sample obtained from at least one patient with multiple sclerosis who is known to be relapsing-remitting or at least one healthy subject.

[0158] Preferably, the kit contains positive control samples and negative control samples, and in particular, each sample is selected from the calibration samples as defined above.

[0159] The present invention also covers the use of the kit of the present invention for implementing the method of the present invention, and in particular, the use for assisting in the diagnosis of the internal clinical subtypes of patients with multiple sclerosis, and the patients are those with multiple sclerosis, preferably patients with multiple sclerosis who have not undergone disease-modifying treatment; more preferably, patients with multiple sclerosis who have not been treated.

[0160] All the above-mentioned preferred specific embodiments related to the method and their combinations also constitute the preferred embodiments of the kit of the present invention and its use.

[0161] It should be noted that the explanations of the terms provided here are only for enabling those skilled in the art to better understand the present invention, and are not intended to limit the present invention.

[0162] The following specific embodiments illustrate the implementation manners of the present invention, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0163] Before further describing the specific implementation manners of the present invention, it should be understood that the protection scope of the present invention is not limited to the following specific implementation manners; it should also be understood that the terms used in the embodiments of the present invention are for describing specific implementation manners, rather than for limiting the protection scope of the present invention. The test methods without specific conditions noted in the following embodiments are usually carried out under conventional conditions or according to the conditions recommended by each manufacturer.

[0164] When numerical ranges are given in the embodiments, it should be understood that, unless otherwise specified in the present invention, both endpoints of each numerical range and any value therebetween can be selected. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those skilled in the art of this technology. In addition to the specific methods, devices, and materials used in the embodiments, any methods, devices, and materials of the prior art similar or equivalent to those described in the embodiments of the present invention can also be used to implement the present invention according to the knowledge of those skilled in the art of this technology and the description of the present invention.

[0165] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. The experimental methods without specific conditions noted in the following embodiments are generally carried out under conventional conditions or according to the conditions recommended by the manufacturer. Unless otherwise specified, percentages and parts are calculated by weight.

[0166] Unless otherwise specified, the reagents and materials used in the embodiments of the present invention are all commercially available products.

[0167] Example 1

[0168] Sample source:

[0169] 49 volunteers with multiple sclerosis were recruited (recruited from the Department of Neurology, Huashan Hospital, Fudan University, excluding patients with multiple sclerosis who had received disease-modifying treatment), and peripheral blood whole blood samples of the subjects were collected, including 37 patients with relapsing-remitting multiple sclerosis and 12 patients with progressive multiple sclerosis. The samples of the subjects were processed within 24 hours after collection.

[0170] Detection method:

[0171] (1) Gently mix the peripheral blood whole blood sample and add 100 μL to the flow tube;

[0172] (2) Then, add fluorescently labeled anti-human CD45, CD3, CD4, CD8, CD28, CD38, HLA-DR, CXCR3, CCR4, CCR6, CD161, TCRγδ antibodies to the flow tube. The fluorescent label is selected from one of Alexa Fluor 488, Alexa Fluor594, Alexa Fluor 647, Alexa Fluor 700, APC, APC / Cy7, APC / H7, Brilliant Violet 421, Brilliant Violet 510, Brilliant Blue 515, Brilliant Violet 570, Brilliant Violet605, Brilliant Violet 650, Brilliant Violet 711, Brilliant Violet 785, FITC, LEAF, Pacific Blue, PE, PE / Cy5, PE / Cy7, PE / Dazzle594, PerCP, and PerCP / Cy5.5. The fluorescent types can be freely combined according to the configuration of the laser and filters of the flow cytometer.

[0173] (3) Gently vortex and mix the whole blood in the tube with the fluorescently labeled antibodies, and incubate in the dark at room temperature for 15 min;

[0174] (4) Add 2 mL of red blood cell lysate to the flow tube, vortex and mix, and incubate in the dark at room temperature for 15 min;

[0175] (5) Centrifuge at 500 g for 5 min at room temperature, and discard the supernatant;

[0176] (6) Add 2 mL of PBS to the flow tube, vortex and mix, centrifuge at 500 g for 5 min at room temperature, and discard the supernatant;

[0177] (7) Add 250 μL of 1% PFA to the flow tube, vortex and mix, and store in the dark at 4 °C until detection by the flow analyzer.

[0178] Results:

[0179] Figure 1 It is the activated T cell subset categories detected by the flow analyzer in the volunteer samples used in the examples of the present invention, CD28 + and CD28 - T cell subset categories, CD8 +Results obtained after analyzing immune biomarker-related parameters such as T cell subset categories and MAIT cell subset categories using Wilcoxon rank sum tests. Among them, RRMS is relapsing-remitting multiple sclerosis, and PMS is progressive multiple sclerosis. The results of the significance test showed that compared with relapsing-remitting multiple sclerosis, the activated CD3 + T cells, activated CD8 + T cells, CD28 - CD8 + T cells, and Tc2 cells were significantly elevated, indicating a greater risk that patients with multiple sclerosis would be identified as the progressive subtype; conversely, CD28 + CD8 + T cells, CD28 + / CD28 - CD8 + T cell ratio, Tc9 cells, Tc17Tc1 cells, Tc1 / Tc2 cell ratio, MAIT cells, and CD8 + MAIT cells were significantly decreased, indicating a greater risk that patients with multiple sclerosis would be identified as the progressive subtype. In summary, the above-mentioned indicators have a good discriminatory effect on the internal subtypes of patients with multiple sclerosis.

[0180] Figure 2 This is the ROC curve graph of single indicators of immune biomarkers such as the activated T cell subset category, CD28 + and CD28 - T cell subset category, CD8 + T cell subset composition category, MAIT cell subset category, etc. used for the auxiliary diagnosis of the internal clinical subtypes of patients with multiple sclerosis. The results showed that each indicator had a good effect on the auxiliary diagnosis of the internal subtypes of multiple sclerosis, and the area under the curve of the ROC curve of each indicator was greater than 0.7.

[0181] The above results prove that detecting immune parameters such as the activated T cell subset category, CD28 + and CD28 - T cell subset category, CD8 + T cell subset composition category, MAIT cell subset category, etc. are extremely useful and reliable immunobiological markers for the auxiliary diagnosis of the internal clinical subtypes of patients with multiple sclerosis, that is, for differentiating progressive multiple sclerosis or relapsing-remitting multiple sclerosis.

[0182] Example 2

[0183] For those from the activated T cell subset category, CD28 + and CD28 -T cell subset categories, CD8 + Combined modeling was performed on the marker of the T cell component subset category and the MAIT cell subset category. First, LASSO regression was used to screen the feature combination, and then a diagnostic model was constructed by the random forest method. The specific process was as follows: 70% of the data in the dataset was selected as the training set to establish the model (optionally, hyperparameter tuning was performed), and the ROC was calculated using 30% of the dataset as the test set. The prediction effect of the model was evaluated using the ROC curve in the test set, and it was found that the combination of the above immune cells showed higher accuracy in assisting the diagnosis of the internal clinical subtypes of multiple sclerosis patients, that is, differentiating progressive multiple sclerosis or relapsing-remitting multiple sclerosis. The AUC results are shown in Table 1.

[0184] Table 1

[0185]

[0186]

[0187] Example 3

[0188] The activated T cell subset categories, CD28 + and CD28 - T cell subset categories, CD8 + Immune biomarkers such as the T cell component subset category and the MAIT cell subset category were combined with the currently popular clinical scoring parameters, including: Expanded Disability Status Scale (EDSS) score, Symbol Digit Modalities Test (SDMT) score, and Fatigue Severity Scale (FSS) score, for combined modeling (the modeling method was the same as in Example 2). Among them, the scoring rules of the Expanded Disability Status Scale (EDSS) were as follows:

[0189] The scoring range was from 0 to 10 points, and the higher the score, the more severe the degree of neurological deficit. The low-score group was defined as EDSS score ≤ 2.5 points, and the high-score group was defined as EDSS score ≥ 6.5 points.

[0190] The scoring rules of the Symbol Digit Modalities Test (SDMT) were as follows:

[0191] The scoring range was from 0 to 110 points, reflecting the cognitive function of the patient. 55 points was the passing score, and below 55 points indicated lower cognitive ability.

[0192] The scoring rules of the Fatigue Severity Scale (FSS) are as follows:

[0193] The scoring range is from 9 to 63 points. The higher the score, the more severe the fatigue. A score of 36 or higher indicates significant fatigue symptoms.

[0194] After modeling, the ROC curve was also used to evaluate the prediction effect of the model in the test set, and it was found that the prediction / evaluation effect of the combined model was further improved. The AUC results are shown in Table 2.

[0195] Table 2

[0196]

[0197]

[0198]

[0199] Example 4

[0200] The activation of T cell subset categories, CD28 + and CD28 - T cell subset categories, CD8 + Immune biomarkers such as the composition subset categories of T cells and MAIT cell subset categories were combined for modeling (the modeling method is the same as in Example 2). At the same time, combined modeling was performed with the currently popular EDSS score in clinical practice. It was applied to three groups of people: a) patients with multiple sclerosis who had not received disease-modifying treatment; b) patients with multiple sclerosis who had received disease-modifying treatment; c) patients with multiple sclerosis regardless of whether they had received disease-modifying treatment. The ROC curve was used to evaluate the prediction effect of the model, and it was found that the prediction / evaluation effect of the combined model for the internal clinical subtypes of multiple sclerosis patients was further improved. The AUC results are shown in Tables 3 and 4.

[0201] Table 3

[0202]

[0203]

[0204]

[0205] Table 4

[0206]

[0207]

[0208]

[0209] The above are only the preferred embodiments of the present invention, and do not impose any formal or substantial limitations on the present invention. It should be noted that for those of ordinary skill in the art, several improvements and supplements can still be made without departing from the present invention, and these improvements and supplements should also be regarded as the protection scope of the present invention.

Claims

1. An immune biomarker for assisting in the diagnosis of internal clinical subtypes of multiple sclerosis, characterized in that: The internal clinical subtype of multiple sclerosis is progressive multiple sclerosis or relapsing-remitting multiple sclerosis, and the immune biomarkers include one or more of the following immune cell subpopulations: a) Activation of T cell subsets; b) CD28 + and CD28 - T cell subsets; c) CD8 + T cells make up subsets; d) Classification of MAIT cell subsets.

2. The immune biomarker according to claim 1, characterized in that The activated T cell subset category includes one or more of the following immune cells: activated CD3 + T cells (HLA-DR + CD38 + CD3 + T cells), activated CD8 + T cells (HLA-DR + CD38 + CD8 + T cells).

3. The immune biomarker according to claim 1, characterized in that CD28 + and CD28 - T cell subsets include: CD28 + CD8 + T cells, CD28 - CD8 + T cells, and CD28 + / CD28 - CD8 + One or more of the T cell ratios.

4. The immune biomarker according to claim 1, characterized in that CD8 + The T cell subsets include one or more of: Tc2 cells, Tc9 cells, Tc17Tc1 cells, and Tc1 / Tc2 cell ratios.

5. The immune biomarker according to claim 1, characterized in that The MAIT cell subset category includes one or more of the following immune cells: MAIT cells, CD8 + MAIT cells.

6. A reagent for assisting the diagnosis of internal clinical subtypes of multiple sclerosis, characterized in that: The reagent comprises a reagent for detecting the immune biomarker according to claim 1.

7. A kit for detecting the immune cell ratio and / or immune cell function of the immune biomarker according to claim 1, the kit comprising: specific tools or reagents for measuring the immune cell ratio and / or immune cell function in a biological sample, and auxiliary reagents for measuring immune cell subpopulations and / or immune cell functions in a biological sample.

8. Use of the immune biomarker or detection reagent thereof according to claim 1 in the preparation of a product for assisting in the diagnosis of internal clinical subtypes of multiple sclerosis, wherein the internal clinical subtypes of multiple sclerosis are progressive multiple sclerosis or relapsing-remitting multiple sclerosis.

9. The use according to claim 8, characterized in that The populations for application include: a) multiple sclerosis patients who have not undergone disease-modifying treatment; b) multiple sclerosis patients who have undergone disease-modifying treatment; and c) multiple sclerosis patients regardless of whether they have undergone disease-modifying treatment.

10. A method for establishing a model for assisting diagnosis of internal clinical subtypes of multiple sclerosis, characterized in that: The method includes the step of identifying differential biomarkers in biological samples between progressive multiple sclerosis and relapsing-remitting multiple sclerosis in multiple sclerosis patients, wherein the differential biomarkers include the immune biomarkers described in any one of claims 1 to 5, and using a machine learning algorithm to screen feature combinations with diagnostic value and construct a diagnostic model, wherein the feature combination is selected from at least two of the immune biomarkers, or at least one of the immune biomarkers and a component of a clinical score; the clinical score is selected from at least one of an EDSS score, an SDMT score and a FSS score.

11. The method according to claim 10, characterized in that The clinical scoring indicators include one or more of the Expanded Disability Status Scale (EDSS) score, the symbol digitmodalities test (SDMT) score, and the fatigue severity scale (FSS) score.

12. The method according to claim 10, characterized in that The machine learning algorithm includes one or more of support vector machine (SVM), random forest, logistic regression, LASSO regression, and biased least squares discriminant analysis (PLSDA).

13. A system for assisting diagnosis of internal clinical subtypes of multiple sclerosis, characterized in that: The system comprises: A feature receiving module, the feature receiving module is used to receive feature data from the sample of the object to be tested; the feature data includes: the level of the immune biomarker as described in claim 1 in the sample of the object to be tested, including the immune cell ratio value and / or immune cell function value of the immune biomarker; A discrimination processing module, which compares the received characteristic data with a reference value or inputs the received characteristic data into a constructed diagnostic model to obtain a diagnosis or evaluation result; The result output module is used to receive and output the evaluation result.

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