Drug and method for treating amyotrophic lateral sclerosis

Abstract

A personalized medical method for treating amyotrophic lateral sclerosis (ALS), comprising screening out a subpopulation of ALS patients having highly immunologically active causes, and administering a therapeutically effective amount of a Janus kinase (JAK) inhibitor to the patients screened out thereby. Also provided are the use of a corresponding JAK inhibitor, an in vitro diagnostic method for screening patients, a kit, and a computer-implemented method. After patients screened out by means of the method are treated with a JAK inhibitor (such as tofacitinib), the level of a nerve damage marker is significantly reduced, and clinical functions are stabilized or improved, and therefore the present invention shows a good therapeutic prospect.

Description

Drugs and methods for treating amyotrophic lateral sclerosis (ALS)

[0001] Cross-citation of related applications

[0002] This application claims priority to Chinese patent application CN 202410925762.6, filed on July 10, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to the medical field, and specifically to methods for treating amyotrophic lateral sclerosis (ALS). Background Technology

[0004] Globally, neurodegenerative diseases, particularly amyotrophic lateral sclerosis (ALS), have long been a significant challenge for the medical and research communities. ALS is a rare but severe disease characterized by the degeneration of motor neurons, impairing the brain's ability to initiate and control muscle movement. This leads to muscle weakness, paralysis, and ultimately affects vital functions such as breathing and swallowing. ALS typically develops gradually, resulting in increasing disability over time, although the rate of progression varies from person to person.

[0005] ALS, with its rapid progression and the lack of effective treatment to date, places immense psychological and physical stress on patients and their families. Currently, there are no treatments worldwide that can cure ALS or significantly improve the quality of life for patients; treatment focuses on symptom control, providing supportive care, and improving patients' quality of life.

[0006] Multiple studies have demonstrated the significant role of genetic factors in familial ALS. Approximately 10% of ALS cases are familial (FALS), often affecting multiple generations. Several gene mutations are known to be significantly associated with ALS (both familial and sporadic), such as mutations in the C9orf72, SOD1, TARDB, and FUS genes. Other gene mutations, such as OPTN, ATXN2, and TBK1, are also considered to be genetically related to ALS. These mutations may affect neuronal function and survival through various mechanisms. Beyond definite single-gene mutations, complex genetic risks are also associated with the pathogenesis of ALS. Multiple studies have shown that the combined effects of multiple genes and genetic variations may play a crucial role in the development of sporadic ALS. However, the majority of ALS cases (approximately 90-95%) are sporadic, meaning they have no known family history. Furthermore, gene mutations only cover a very small percentage of ALS patients, and breakthroughs in treatment by discovering or studying ALS-related pathogenic mutations have had limited effectiveness. A deeper understanding of the underlying causes of ALS is needed.

[0007] All of these factors necessitate the innovation of effective treatments. Advances in fields such as genome sequencing, biomedicine, computational science, and drug development offer unique opportunities to address this problem, allowing for in-depth exploration of the causes, mechanisms, and treatment pathways of ALS. By analyzing large-scale genomic data, we can identify and pinpoint potential therapeutic targets and drugs. Summary of the Invention

[0008] The purpose of this disclosure is to provide a medicine and method for treating amyotrophic lateral sclerosis (ALS).

[0009] In one aspect, this disclosure provides a method for treating amyotrophic lateral sclerosis (ALS) in a subject of need, the method comprising:

[0010] (a) By analyzing biological samples obtained from the subject, the quantitative level of at least one pre-defined immune-related feature is obtained;

[0011] (b) Calculate the etiology score of immune activity based on the quantification level of the at least one immune-related feature;

[0012] (c) Comparing the immune activity etiology score with a preset threshold to determine whether the subject is a patient with a high immune activity etiology; and

[0013] (d) For patients identified in step (c) as having a high immune response, administer a therapeutically effective dose of a Janus kinase (JAK) inhibitor.

[0014] In another aspect, this disclosure provides a Janus kinase (JAK) inhibitor for the treatment of amyotrophic lateral sclerosis (ALS) in subjects of need, wherein the subjects are patients identified as having a highly immunologically active etiology according to the methods of this disclosure.

[0015] In another aspect, this disclosure provides the use of a Janus kinase (JAK) inhibitor in the preparation of a medicament for the treatment of amyotrophic lateral sclerosis (ALS), wherein the medicament is suitable for administration to a subject in need, the subject being a patient identified as having a hyperimmune etiology according to the methods of this disclosure.

[0016] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, in step (a), the quantification level is obtained by calculation and inference from genomic data in the biological sample.

[0017] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, in step (a), the quantification level is obtained by direct physical or biochemical measurement of the biological sample.

[0018] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the at least one immune-related feature is selected from the group consisting of:

[0019] (1) Activity level of the IL-2 signal transduction pathway;

[0020] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0021] (3) Activity level of the iNOS signal transduction pathway;

[0022] (4) Activity level of the fMLP signal transduction pathway in neutrophils;

[0023] (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells;

[0024] (6) Activity level of the GM-CSF signal transduction pathway;

[0025] (7) Activity level of the interferon α signal transduction pathway;

[0026] (8) Activity level of the interferon-γ signal transduction pathway;

[0027] (9) Activity level of the IL-1 signaling pathway;

[0028] (10) The activity level of the Toll-like receptor signaling pathway; and

[0029] (11) Quantitative levels related to CD8+ T cell function.

[0030] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the at least one immune-related feature includes at least one, two, or more immune-related features selected from the group consisting of:

[0031] (1) Activity level of the IL-2 signal transduction pathway;

[0032] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0033] (3) Activity level of the interferon α signal transduction pathway;

[0034] (4) The activity level of the interferon-γ signaling pathway; and

[0035] (5) Quantitative levels related to CD8+ T cell function.

[0036] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the at least one immune-related feature includes the following five immune-related features:

[0037] (1) Activity level of the IL-2 signal transduction pathway;

[0038] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0039] (3) Activity level of the interferon α signal transduction pathway;

[0040] (4) The activity level of the interferon-γ signaling pathway; and

[0041] (5) Quantitative levels related to CD8+ T cell function.

[0042] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the quantification level associated with CD8+ T cell function is based on an assessment of the expression levels of at least one protein selected from the group consisting of: CD8A, GZMB, PRF1, Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

[0043] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, in step (b), the immune activity etiology score is calculated by the following steps:

[0044] (i) Calculate the Z-score for each of the at least one immune-related feature; and

[0045] (ii) Sum the Z-scores of each feature obtained in step (i).

[0046] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the Z-score is calculated based on the mean (μ) and standard deviation (σ) of the corresponding characteristics obtained from an ALS patient cohort.

[0047] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the preset threshold is a score cutoff value determined based on retrospective clinical data that can distinguish between patient populations that respond to and do not respond to treatment with the JAK inhibitor.

[0048] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, the JAK inhibitor is tofacitinib, preferably administered at a dose of about 10 mg daily.

[0049] In some embodiments of the methods, JAK inhibitors, or uses disclosed herein, administration to a subject of a therapeutically effective amount of one or more agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets, said agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets being selected from the group consisting of insulin, metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors, preferably insulin.

[0050] In another aspect, this disclosure provides an in vitro method for identifying amyotrophic lateral sclerosis (ALS) subjects with highly immunologically active etiologies, the method comprising:

[0051] (a) By analyzing biological samples obtained from candidate subjects, the quantitative level of at least one pre-defined immune-related feature is obtained;

[0052] (b) Based on the quantification level of the at least one immune-related feature, an immune activity etiology score is calculated; and

[0053] (c) If the immune activity etiology score is higher than a preset threshold, the candidate subject is identified as an ALS subject with a high immune activity etiology.

[0054] In some implementations, the at least one immune-related feature is selected from the group consisting of:

[0055] (1) Activity level of the IL-2 signal transduction pathway;

[0056] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0057] (3) Activity level of the iNOS signal transduction pathway;

[0058] (4) Activity level of the fMLP signal transduction pathway in neutrophils;

[0059] (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells;

[0060] (6) Activity level of the GM-CSF signal transduction pathway;

[0061] (7) Activity level of the interferon α signal transduction pathway;

[0062] (8) Activity level of the interferon-γ signal transduction pathway;

[0063] (9) Activity level of the IL-1 signaling pathway;

[0064] (10) The activity level of the Toll-like receptor signaling pathway; and

[0065] (11) Quantitative levels related to CD8+ T cell function.

[0066] In some embodiments, the at least one immune-related feature includes at least one, two, or more immune-related features selected from the group consisting of:

[0067] (1) Activity level of the IL-2 signal transduction pathway;

[0068] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0069] (3) Activity level of the interferon α signal transduction pathway;

[0070] (4) The activity level of the interferon-γ signaling pathway; and

[0071] (5) Quantitative levels related to CD8+ T cell function.

[0072] In some implementations, the at least one immune-related feature includes the following five immune-related features:

[0073] (1) Activity level of the IL-2 signal transduction pathway;

[0074] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0075] (3) Activity level of the interferon α signal transduction pathway;

[0076] (4) The activity level of the interferon-γ signaling pathway; and

[0077] (5) Quantitative levels related to CD8+ T cell function.

[0078] In some implementations, the quantification level associated with CD8+ T cell function is based on an assessment of the expression levels of at least one protein selected from the group consisting of: CD8A, GZMB, PRF1, Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

[0079] In some implementations, the immune activity etiology score is calculated using the following steps:

[0080] (i) Calculate the Z-score for each of the at least one immune-related feature; and

[0081] (ii) Sum the Z-scores of each feature obtained in step (i).

[0082] In some implementations, the Z-score is calculated based on the mean (μ) and standard deviation (σ) of the corresponding feature obtained from an ALS patient cohort.

[0083] In some implementations, the preset threshold is a score cutoff value determined based on retrospective clinical data that can distinguish between patient groups that respond to and do not respond to JAK inhibitor treatment.

[0084] In another aspect, this disclosure provides a kit for treating amyotrophic lateral sclerosis (ALS), the kit comprising:

[0085] (a) one or more Janus kinase (JAK) inhibitors; and

[0086] (b) Instructions for use, which contain instructions for administering the JAK inhibitor to ALS subjects identified as having a highly immunologically active etiology according to the method described in this disclosure.

[0087] In another aspect, this disclosure provides a computer-implemented method for generating personalized treatment recommendations for subjects with amyotrophic lateral sclerosis (ALS), the method comprising:

[0088] (a) On one or more hardware processors, data representing the analysis of the subject's biological sample is received, the data including the quantification level of at least one preset immune-related feature;

[0089] (b) Execute instructions stored in non-transitory memory to calculate the subject's immune activity etiology score according to the method of this disclosure; and

[0090] (c) Based on the immune activity etiology score, generate a report containing recommendations for administering a Janus kinase (JAK) inhibitor to the subject.

[0091] In another aspect, this disclosure provides a method for monitoring the therapeutic effect of a Janus kinase (JAK) inhibitor in ALS subjects identified as having a highly immunologically active etiology according to the method described in this disclosure, the method comprising:

[0092] (a) During the course of treatment with the JAK inhibitor administered to the subject, the level of neurofilament light chains (NfL) in the subject's biological samples was measured multiple times; and

[0093] (b) Associate the reduction in NfL level with positive treatment effects, wherein the positive treatment effects include at least one of slowing disease progression, stabilization or improvement of ALS Functional Rating Scale-Revised (ALSFRS-R) score, or improvement of forced vital capacity (FVC).

[0094] In another aspect, this disclosure provides a method for treating a subject with amyotrophic lateral sclerosis (ALS) in need, comprising administering to the subject a therapeutically effective amount of one or more inhibitors or antagonists of immune-related pathways and / or targets, said inhibitors or antagonists of immune-related pathways and / or targets being selected from the group consisting of:

[0095] IL-2, IL-2 receptor, and IL-2 signaling pathway antagonists

[0096] CD28 antagonists, antagonists that block the CD28 signaling pathway in T helper cells.

[0097] Antagonists that block the iNOS signal transduction pathway

[0098] Antagonists that block the fMLP signaling pathway in neutrophils

[0099] Antagonists that block the iCOS-iCOSL signaling pathway in T helper cells

[0100] GM-CSF antagonists, antagonists that block the GM-CSF signal transduction pathway,

[0101] Antagonists of type I IFN interferon-alpha, antagonists that block the interferon-alpha signal transduction pathway

[0102] Antagonists of interferon-gamma, antagonists that block the interferon-gamma signal transduction pathway,

[0103] IL-1α and IL-1β antagonists, and antagonists that block the IL-1 signaling pathway.

[0104] Antagonists that block the Toll-like receptor signaling pathway, and

[0105] JAK inhibitors include tofacitinib, baricitinib, upadacitinib, and filgotinib.

[0106] Some embodiments further include administering to the subject a therapeutically effective amount of one or more agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets, wherein the agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets are selected from the group consisting of insulin, metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors, preferably insulin. Attached Figure Description

[0107] Figures 1 through 10 illustrate 10 signaling pathways significantly activated in the ALS population. Figure 1 shows the IL-2 signaling pathway. Figure 2 shows the CD28 signaling pathway in T helper cells. Figure 3 shows the iNOS signaling pathway. Figure 4 shows the fMLP signaling pathway in neutrophils. Figure 5 shows the iCOS-iCOSL signaling pathway in T helper cells. Figure 6 shows the GM-CSF signaling pathway. Figure 7 shows the interferon-γ signaling pathway. Figure 8 shows the interferon-α signaling pathway. Figure 9 shows the IL-1 signaling pathway. Figure 10 shows the Toll-like receptor signaling pathway.

[0108] Figures 11 to 14 illustrate the four signaling pathways significantly suppressed in the ALS population and their corresponding cellular functions. Figure 11 shows the NOTCH signaling pathway. Figure 12 shows the cell cycle G2M-DNA damage checkpoint regulation pathway. Figure 13 shows the Wnt / β-catenin signaling pathway. Figure 14 shows pancreatic β cells. The y-axis values ​​in Figures 11 to 14 represent normalized values ​​of signaling pathway activity and cellular function levels.

[0109] Figure 15 shows the APSP difference analysis between ALS patients of different sexes and healthy elderly people of the same sex.

[0110] Figure 16 shows the distribution of all patient etiology scores (Sum of Z-score(all features)) obtained in Example 3.

[0111] Figure 17 shows a graph illustrating the change in serum neurofilament light chain (NfL) levels over time in patients of Example 4 during tofacitinib treatment.

[0112] Figure 18 shows a graph of the change in ALSFRS-R score over time in patients of Example 4 during tofacitinib treatment.

[0113] Figure 19 shows a graph illustrating the change in serum neurofilament light chain (NfL) levels over time in patients of Example 5 during tofacitinib treatment.

[0114] Figure 20 shows a graph of forced vital capacity (FVC%) over time in patients of Example 5 during tofacitinib treatment.

[0115] Figure 21 shows a graph of the change in ALSFRS-R score over time in patients of Example 5 during tofacitinib treatment. Detailed Implementation

[0116] It should be understood that this disclosure is not limited to the specific embodiments described herein. It should also be understood that the terminology used herein is for describing specific embodiments only and is not restrictive, as the scope of this disclosure is limited only by the appended claims.

[0117] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. While any methods and materials similar to or equivalent to those described herein may also be used in the practice or experimentation of this disclosure, preferred methods and materials are presented here. All publications mentioned herein disclose and describe methods and / or materials relevant to the cited publications.

[0118] If the provided numerical range has one or two limits, it can be understood that this disclosure includes the smaller range between any specified intermediate value within the range and any limit of the specified range. When the range includes one or two limits, the range excluding any one or two limits is also included in this disclosure.

[0119] the term

[0120] It must be noted that the singular forms "a", "an" and "the" used herein and in the appended claims include plural references unless the context clearly specifies otherwise.

[0121] Unless otherwise stated, the terms "comprise," "include," "contain," and variations thereof, such as comprising, comprises, and comprised, do not imply the exclusion of other members, components, integers, or steps. These terms also include the meaning of "consist of" or "consisting of."

[0122] The term "approximately" refers to a range equal to plus or minus ten percent (+ / - 10%) of a specific value.

[0123] The term "and / or" refers to any one, several, or all of the elements connected by the term.

[0124] As used herein, the term "amyotrophic lateral sclerosis (ALS)" refers to a progressive neurodegenerative disease that affects upper motor neurons (motor neurons in the brain) and / or lower motor neurons (motor neurons in the spinal cord) and leads to motor neuron death. In some embodiments, amyotrophic lateral sclerosis includes all classifications of amyotrophic lateral sclerosis known in the art, including but not limited to classic amyotrophic lateral sclerosis (typically affecting both lower and upper motor neurons), primary lateral sclerosis (PLS, typically affecting only upper motor neurons), progressive bulbar palsy (PBP or medullary onset, a form of amyotrophic lateral sclerosis that typically begins with difficulty swallowing, chewing, and speaking), progressive muscular atrophy (PMA, typically affecting only lower motor neurons), and familial amyotrophic lateral sclerosis (the inherited form of amyotrophic lateral sclerosis). In some implementations, the term "amyotrophic lateral sclerosis" refers to the symptoms of amyotrophic lateral sclerosis, including but not limited to progressive weakness, atrophy, fasciculations, hyperreflexia, dysarthria, dysphagia, and / or respiratory paralysis.

[0125] As used herein, the term "hyperimmune-active etiology" refers to a specific subtype or identifiable pathological state in patients with amyotrophic lateral sclerosis (ALS), characterized by a quantifiable, abnormally high level of activation of the patient's immune system in relation to the disease. In this disclosure, whether a patient is a "hyperimmune-active etiology" patient is determined by an objective "immune-active etiology score." Specifically, this score is based on a comprehensive assessment of the quantification levels of one or more predefined immune-related features obtained from the patient's biological sample. The "quantification level" of said feature can be obtained by analyzing said biological sample, through methods including but not limited to: (a) computational inference pathways: by calculating and inferring from genomic data in the biological sample; or (b) direct measurement pathways: by performing direct physical or biochemical measurements on the biological sample (e.g., detecting relevant protein or cellular markers using methods such as ELISA, flow cytometry, etc.). A patient is identified or characterized as having a "high immune activity etiology" when the calculated "immune activity etiology score" is higher than a pre-defined threshold that can effectively distinguish between patients who have a clinical response to a specific immunosuppressive therapy (such as a JAK inhibitor) and those who do not.

[0126] As used herein, the term "biosample" refers to any material obtained from the body of a subject (e.g., a human patient) that contains their genetic material (i.e., genomic DNA). Such samples are obtained for the purpose of performing genomic analysis, such as whole-exome sequencing (WES) or whole-genome sequencing (WGS), to obtain genomic data for use in the diagnostic or screening methods described in this disclosure. Non-limiting examples of biosamples include: peripheral blood (and its components, such as leukocytes), saliva, oral epithelial cells isolated from oral swabs or oral rinsing solutions, skin biopsies, hair follicle cells, or any other cells or tissues containing a nucleus. Preferably, the biosample is readily obtainable through non-invasive or minimally invasive methods, such as peripheral blood or oral swabs.

[0127] As used herein, the term “application” means the absorption, ingestion, injection, inhalation, implantation, or other introduction of the compound (“active agent”) or pharmaceutical composition thereof disclosed herein. The term “treatment” means reversing, alleviating, delaying the onset of or inhibiting the progression of a “pathological condition” (e.g., a disease, symptom, or illness, or one or more signs or symptoms thereof) described herein. In some embodiments, treatment may be administered after one or more signs or symptoms of a disease or symptom have developed or been observed. In other embodiments, treatment may be administered in the absence of signs or symptoms of a disease or symptom. For example, treatment may be given to a susceptible individual before the onset of symptoms (e.g., based on a history of symptoms and / or based on genetic or other susceptibility factors). Treatment may also continue after symptoms have subsided, for example, to delay or prevent recurrence. As used herein, the terms “disease,” “symptom,” “illness,” and “pathological condition” are used interchangeably.

[0128] As used herein, the term "active agent" refers to a pharmaceutically active chemical substance having a certain pharmacological action for the treatment or prevention of diseases such as amyotrophic lateral sclerosis (ALS). In this disclosure, "active agent" may include "inhibitor," "antagonist," "agonist," and / or other active agents. In this disclosure, "active agent" is also intended to include derivatives of these pharmaceutically active chemical substances, pharmaceutically acceptable salts, solvates, and / or prodrugs, as well as other variations.

[0129] As used herein, the terms "inhibitor" and "antagonist" are used interchangeably to refer to any molecule that partially or wholly blocks or inhibits the activity of a target (such as a protein or signaling pathway used as a target in this disclosure).

[0130] As used herein, the term "agonist" refers to any molecule that partially or wholly activates or revitalizes the activity of a target (such as a protein or signaling pathway used as a target in this disclosure).

[0131] As used herein, the term "derivative" of a compound means any pharmaceutically acceptable molecule derived from the compound and having similar or substantially the same activity as the compound, which, upon administration to a subject, can (directly or indirectly) provide the active agent compound or its active metabolite. Examples of derivatives include, but are not limited to, pharmaceutically acceptable salts, hydrates, solvates, prodrugs, or metabolites.

[0132] As used herein, the term "pharmaceutically acceptable salt" refers to a relatively non-toxic inorganic or organic acid salt of the compounds disclosed herein. These salts can be prepared in situ during the final separation and purification of the compounds, or the purified free compounds can be reacted separately with suitable organic or inorganic acids, and the resulting salts can be isolated. Representative acid salts include, but are not limited to, acetate, adipic acid salt, aspartate, benzoate, bicarbonate / carbonate, hydrogen sulfate / sulfate, borate, citrate, citrate, cycloaliphatic acid salt, oxalate, acetate, formate, fumarate, gluconate, glucuronide, hexafluorophosphate, benzoate, hydrochloride / hydrochloride, hydrobromide / bromide, hydroiodide / iodide, isoiodide / isoiodide, hydroiodide / isoiodide, hydroxyiodide / iodide, isosulfate, lactate, malate, maleate, malonate, methanesulfonate, methyl sulfate, naphthalate, 2-naphthoate, nicotinate, nitrate, orotate, oxalate, palmitate phosphate / hydrogen phosphate / dihydrogen phosphate, pyroglutamate, glycosides, stearate, succinate, tannic acid salt, tartrate, p-toluenesulfonate, trifluoroacetate, and cinnarizine. In one implementation, the pharmaceutically acceptable salt is hydrochloride / chlorate.

[0133] As used herein, the term "solvate" refers to a stoichiometric complex formed by a solute (such as the active agent of this disclosure) and a solvent. For the purposes of this disclosure, such solvents must not interfere with the biological activity of the solute. Examples of suitable solvents include, but are not limited to, water, methanol, ethanol, and acetic acid.

[0134] As used herein, the term "prodrug" refers to a precursor of a compound that is produced when administered to a biological system. For example, a prodrug may have an X-drug structure, where X is an inert carrier molecule and the drug is the active compound.

[0135] As used herein, the term "metabolite" of a compound refers to a molecule that is produced after a compound has been modified or processed following administration to a subject. A metabolite may refer to a modified or processed drug that retains at least some of the activity of the parent compound.

[0136] As used herein, the term "pharmaceutically acceptable" means a compound, material, composition, and / or dosage form that, to a reasonable extent of medical judgment, is suitable for contact with the tissues of a subject without causing excessive toxicity, irritation, allergic reactions, or other problematic complications commensurate with a reasonable benefit / risk ratio.

[0137] As used herein, the term "pharmaceuticalally acceptable carrier" refers to any carrier that has substantially no long-term or permanent harmful effects when administered to a subject, such as stabilizers, diluents, additives, excipients, and other similar substances. A "pharmaceuticalally acceptable carrier" should be a pharmaceutically inert material that is substantially non-biologically active and constitutes a major part of the formulation.

[0138] As used herein, the term "subject" refers to any organism to which the active agent of this disclosure may be administered, such as an organism used for experimental, diagnostic, preventive, and / or therapeutic purposes. Typical subjects include animals (e.g., mammals such as mice, rats, rabbits, non-human primates such as chimpanzees and other ape species, and humans). Subjects can be mammals, particularly humans, including males or females, and also include newborns, infants, adolescents, young adults, adults, or the elderly, as well as various races and ethnicities. In some embodiments, the subject is an ALS patient assessed based on their genomic data as having a highly immunologically active etiology.

[0139] As used herein, the terms "therapeutic effective dose" or "effective dose" are used interchangeably with "therapeutic effective amount" or "effective amount" and refer to an amount that is effective in treating a disease (such as amyotrophic lateral sclerosis) as determined by clinical testing and evaluation, patient observation, and / or similar methods. "Effective amount" can also refer to an amount that causes a detectable change in biological or chemical activity. Detectable changes can be detected and / or further quantified by professionals skilled in the relevant mechanisms or processes. Furthermore, "effective amount" can also refer to an amount that maintains ideal physiological conditions, i.e., an amount that reduces or prevents significant decline and / or promotes disease improvement.

[0140] As used herein, the term "unit dosage form" refers to a physically discrete unit (such as a capsule, tablet, or cylinder into a syringe) suitable as a unit dose for a subject.

[0141] As used herein, the term "unit dose" refers to the dose of a unit dosage form of a substance (such as the active agent of this disclosure).

[0142] As used herein, the term "computer-readable medium" is intended to include any type of non-transitory storage medium having computer program instructions stored thereon that are executable by one or more hardware processors. When executed, these instructions enable a computer system to implement the specific methods described in this invention, such as methods for identifying subjects with highly immune-active ALS etiologies or methods for generating personalized treatment recommendations. The term "non-transitory computer-readable medium" does not include transient, propagating signals themselves, but includes physical and tangible media for storing information. Non-limiting examples include: semiconductor storage devices (such as read-only memory ROM, random access memory RAM, flash memory), magnetic storage devices (such as hard disks, floppy disks), optical storage devices (such as optical discs CD-ROM, digital versatile optical discs DVD), and any other known or future-developed storage technologies capable of tangibly storing instructions and data.

[0143] Active preparations for treating amyotrophic lateral sclerosis (ALS)

[0144] Through extensive research, the inventors have discovered multiple target points and pathways that can be used to treat amyotrophic lateral sclerosis (ALS), including but not limited to immune-related pathways and / or targets, such as IL-2, IL-2 receptor, IL-2 signaling pathway, CD28, CD28 signaling pathway in T helper cells, iNOS signaling, fMLP signaling pathway in neutrophils, iCOS-iCOSL signaling pathway in T helper cells, GM-CSF, GM-CSF signaling pathway, type I IFN interferon α, interferon α signaling pathway, interferon γ, interferon-γ signaling pathway, IL-1α, IL-1β, IL-1 signaling pathway, Toll-like receptor signaling pathway, JAK inhibitors; metabolic-related pathways and / or targets; cell communication, development, or division-related pathways and / or targets, such as the Wnt / β-catenin signaling pathway, cell cycle G2M-DNA damage checkpoint regulation pathway, and Notch signaling. Antagonists, inhibitors, or agonists of the aforementioned target sites and pathways can be used to treat amyotrophic lateral sclerosis (ALS).

[0145] The active agent used to treat amyotrophic lateral sclerosis (ALS) can be an inhibitor or antagonist of any immune-related pathway and / or target, particularly an inhibitor or antagonist of T-cell-related pathways and / or targets. In some embodiments, the inhibitor or antagonist of the immune-related pathway and / or target is selected from the group consisting of:

[0146] IL-2, IL-2 receptor, and IL-2 signaling pathway antagonists

[0147] CD28 antagonists, antagonists that block the CD28 signaling pathway in T helper cells.

[0148] Antagonists that block the iNOS signal transduction pathway

[0149] Antagonists that block the fMLP signaling pathway in neutrophils

[0150] Antagonists that block the iCOS-iCOSL signaling pathway in T helper cells

[0151] GM-CSF antagonists, antagonists that block the GM-CSF signal transduction pathway,

[0152] Antagonists of type I IFN interferon-alpha, antagonists that block the interferon-alpha signal transduction pathway

[0153] Antagonists of interferon-gamma, antagonists that block the interferon-gamma signaling pathway,

[0154] IL-1α and IL-1β antagonists, and antagonists that block the IL-1 signaling pathway.

[0155] Antagonists that block the Toll-like receptor signaling pathway, and

[0156] JAK inhibitors include tofacitinib, baricitinib, upadacitinib, and filgotinib.

[0157] The active agent used to treat amyotrophic lateral sclerosis (ALS) can be an agonist, inhibitor, or antagonist of any metabolic-related pathway and / or target, particularly an agonist, inhibitor, or antagonist of a glucose metabolism pathway and / or target. In some embodiments, the agonist, inhibitor, or antagonist of the metabolic-related pathway and / or target is selected from the group consisting of insulin, metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors.

[0158] The active agent used to treat amyotrophic lateral sclerosis (ALS) can be an agonist of any cell communication, development, or division-related pathway and / or target. In some embodiments, the agonist of the cell communication, development, or division-related pathway and / or target is selected from the group consisting of:

[0159] Wnt / β-catenin signaling pathway agonists,

[0160] Agonists that enhance the cell cycle G2M-DNA damage checkpoint regulatory pathway, and

[0161] Agonists that enhance Notch signaling.

[0162] The dosage of each active agent in a unit dosage form can be 1-1000 mg, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 250, 300, 350, 400, 450, 500, 600, 700, 750, 800, 900, 1000 mg, or any range between any two specific values ​​above. In some preferred embodiments, the dosage of the active agent, the JAK inhibitor tofacitinib, in a unit dosage form is 5 mg.

[0163] Methods for determining the level of immune-related characteristics

[0164] In this disclosure, in order to obtain a quantitative level of immune-related features required for calculating an “immune activity etiology score”, in some embodiments the quantitative level is obtained by calculating and inferring genomic data in a biological sample, and in some embodiments the quantitative level is obtained by performing direct physical or biochemical measurements on the biological sample.

[0165] Computational inference methods based on genomic data and etiology scoring models for immune activity

[0166] In some embodiments of this disclosure, the quantification level of the immune-related characteristics is obtained by calculation and inference from the subject's genomic data. The core advantage of this method is that it requires only a single genome sequencing to assess a relatively stable immune response predisposition determined by an individual's genetic background, offering a prospective and non-invasive approach.

[0167] This disclosure provides an innovative scoring model (hereinafter referred to as the "Model") for identifying and screening amyotrophic lateral sclerosis (ALS) patients with highly immune-active etiologies. The core objective of this Model is to transform complex genetic variation information into a quantitative, clinically significant "immunologically active etiology score" through in-depth analysis of individual patient genomic data, thereby accurately identifying patient subgroups most likely to benefit from immune-targeted therapies such as Janus kinase (JAK) inhibitors. This Model not only provides an objective basis for personalized treatment of ALS but also solves the problem of the inability to effectively predict treatment efficacy in existing technologies.

[0168] Model building and calculation steps

[0169] In some implementations, the immune activity etiology scoring model is constructed and applied through a series of defined bioinformatics and statistical steps, the specific process of which is as follows:

[0170] Data Acquisition and Preprocessing

[0171] First, a biological sample containing complete genetic information is obtained from the subject to be evaluated (e.g., an ALS patient). This biological sample can be peripheral blood, oral epithelial cells, etc. Next, genomic DNA is extracted from the sample and high-throughput sequencing technologies, such as whole-exome sequencing (WES) or whole-genome sequencing (WGS), are used to generate raw sequencing data (e.g., Fastq format files). Subsequently, the raw data is processed using standard bioinformatics workflows in the field (e.g., GATK Best Practices), including alignment, variant detection, etc., to finally generate a variant detection format (VCF) file containing information on rare genetic variant sites of the subject (e.g., minor allele frequency MAF < 0.01).

[0172] Generation of Pathway Activity Profile (APSP)

[0173] Using the VCF file obtained in the previous step as input, an artificial intelligence-based genomic mutation damage assessment algorithm, such as the DAGM algorithm (SCI journal: EBioMedicine. 2021 Jul; 69:103446; Chinese patent number: ZL201880003025.3, authorization announcement number CN111602201B, the entire contents of which are incorporated herein by reference), is used to calculate the global gene expression level and signaling pathway activity profile (APSP) of the subjects.

[0174] In some implementations, the computation process of the DAGM algorithm includes:

[0175] Step 1: Calculate the global protein expression profile. The algorithm first calculates and predicts the global expression levels or trends of various proteins in the subject's body based on the input subject's genomic data (e.g., VCF file).

[0176] Step 2: Calculate pathway activity and functional levels. Subsequently, based on the protein expression profile obtained in the previous step, the algorithm performs higher-level calculations:

[0177] For "signal pathway activity level", the algorithm will use a pre-set biological knowledge base (which defines the member proteins contained in each pathway and their positive or negative regulatory effects in the pathway) to weight and integrate the predicted expression levels of all relevant member proteins in the pathway, thereby calculating a single composite score that can represent the overall activation or inhibition state of the pathway.

[0178] For the "quantitative level related to immune cell function," the algorithm extracts the predicted expression levels of one or more key proteins directly related to immune cell function and integrates them into a comprehensive score. In some preferred embodiments, the immune cells are CD8+ T cells. In some preferred embodiments, the key proteins used to calculate the score are proteins directly related to CD8+ T cell function, including at least one or more of CD8A, GZMB, and PRF1, and may also include one or more selected from Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

[0179] This method can ultimately generate a quantified pathway activity profile (APSP) for each subject, containing the aforementioned multiple immune-related features, and the values ​​therein are used as input for subsequent score calculations.

[0180] Selection and extraction of immune-related features

[0181] Extract at least one immune-related feature that is highly correlated with ALS immunopathology from the APSP generated in the previous step.

[0182] In some preferred embodiments, the immune-related features highly associated with ALS immunopathology include, but are not limited to, the following:

[0183] (1) Activity level of the IL-2 signal transduction pathway;

[0184] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0185] (3) Activity level of the iNOS signal transduction pathway;

[0186] (4) Activity level of the fMLP signal transduction pathway in neutrophils;

[0187] (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells;

[0188] (6) Activity level of the GM-CSF signal transduction pathway;

[0189] (7) Activity level of the interferon α (type I IFN) signal transduction pathway;

[0190] (8) Activity level of the interferon-γ signal transduction pathway;

[0191] (9) Activity level of the IL-1 signaling pathway;

[0192] (10) Activity levels of the Toll-like receptor signaling pathway; and

[0193] (11) Quantitative levels related to the function of immune cells such as CD8+ T cells.

[0194] In some preferred embodiments, the at least one immune-related feature includes at least one, two, or more immune-related features selected from the group consisting of:

[0195] (1) Activity level of the IL-2 signal transduction pathway;

[0196] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0197] (3) Activity level of the interferon α signal transduction pathway;

[0198] (4) The activity level of the interferon-γ signaling pathway; and

[0199] (5) Quantitative levels related to CD8+ T cell function.

[0200] In some preferred embodiments, the at least one immune-related feature includes the following five immune-related features:

[0201] (1) Activity level of the IL-2 signal transduction pathway;

[0202] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0203] (3) Activity level of the interferon α signal transduction pathway;

[0204] (4) The activity level of the interferon-γ signaling pathway; and

[0205] (5) Quantitative levels related to CD8+ T cell function.

[0206] In some preferred embodiments, the quantification level related to CD8+ T cell function is based on an assessment of the expression levels of at least one protein selected from the group consisting of: CD8A, GZMB, PRF1, Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

[0207] Eigenvalue standardization (Z-score calculation)

[0208] To eliminate differences in units and numerical ranges between different features, the activity level of each feature needs to be standardized. This step uses the Z-score method. The Z-score, also known as the standard score, is a commonly used indicator in statistics for calculating sample variability, used to measure the relative position of a data point to the mean of the dataset. Essentially, it is the process of standardizing the original data to a "standard normal distribution" (mean of 0, standard deviation of 1), which facilitates comparison between different datasets or outlier detection (Dowdy, S., Wearden, S., & Childo, D. (2011). Statistics for research. John Wiley & Sons.).

[0209] In specific calculations, a pre-established reference cohort is required, for example, consisting of a large population of ALS patients (such as the 188 patients in Example 3). First, the mean (μ) and standard deviation (σ) of each of one, two, or more features in the reference cohort (e.g., immune-related features highly correlated with ALS immunopathology as described in the preferred embodiment) are calculated. Then, for any subject to be evaluated, the Z-score (Z) of a specific feature is calculated using the following formula: Z = (x - μ) / σ, where x is the subject's original activity level value for that feature, and μ and σ are the mean and standard deviation of that feature in the reference cohort, respectively.

[0210] In some embodiments, the ALS patient cohort is a reference ALS patient cohort established for at least one immune-related feature described in this disclosure.

[0211] Sum of immune activity etiology scores

[0212] The Z-scores of at least one, such as two or more, immune-related features of the subject being evaluated, calculated in the previous step are summed to obtain the subject's final "immune activity etiology score." This score comprehensively reflects the overall activation status of the patient's individual immune system.

[0213] Those skilled in the art will understand that the summation of Z-scores can be achieved not only through simple arithmetic summation, but also by employing other mathematical methods to integrate the Z-scores of various features to obtain an immune activity etiology score. For example, the Z-scores of each feature can be weighted and summed based on their respective contributions to the prediction of clinical efficacy. Alternatively, the Z-scores of each feature can be used as input, and a classification or regression model can be constructed using machine learning algorithms (such as logistic regression, random forest, support vector machine, etc.), the output of which can then be used as the immune activity etiology score. All variations of these calculation methods fall within the protection spirit of this disclosure.

[0214] The DAGM algorithm used in this disclosure is an artificial intelligence-based method for assessing genomic mutation damage. It employs eQTL (expression Quantitative Trait Loci, a type of genetic locus that can influence gene expression levels) analysis technology to establish a correlation between gene expression and gene mutations. This algorithm can efficiently transform complex, discrete, and high-dimensional genomic variation information into continuous, lower-dimensional, and highly correlated pathway activity profiles (APSPs). Through this process, the DAGM algorithm takes genomic data as input and, with the help of multiple technologies such as its built-in data model, deep learning model, and knowledge model, ultimately outputs the overall cellular gene expression levels and pathway function profiles of the subject, providing a comprehensive assessment of cellular biological function.

[0215] The DAGM algorithm includes, but is not limited to, the following steps:

[0216] Step I. Constructing a global gene expression driving force template

[0217] The purpose of this step is to pre-compute and build a "driving force matrix" based on a large-scale public dataset. This matrix quantifies the potential impact of a mutation in any one gene on the expression of all other genes in the genome.

[0218] I.1. Data Source:

[0219] Large-scale, publicly available cell line genome and transcriptome databases (e.g., the Cancer Cell Line Encyclopedia COSMIC or CCLE) were utilized, which contain gene mutation information and whole-genome expression profiles of hundreds of cell lines from different sources.

[0220] I.2. Driving force calculation:

[0221] For each gene in the genome (denoted as gene i), all cell lines in the database are divided into two groups: a "mutant group" that carries a rare coding mutation on gene i, and a "wild-type group" that does not carry the mutation.

[0222] Subsequently, for each gene in the genome (denoted as gene j), the difference in its expression level between the "mutant group" and the "wild-type group" was calculated. This difference value preliminarily characterizes the "driving force" of the mutation of gene i on the expression of gene j.

[0223] I.3. Standardization Processing:

[0224] To eliminate the interference of random factors, the driving force values ​​were standardized using statistical methods such as the permutation test, resulting in a standardized driving force matrix. Each element of this matrix represents the standardized effect of mutation of gene i on the expression of gene j.

[0225] Step II. Calculate the individualized global gene expression impact profile

[0226] The purpose of this step is to integrate multiple mutational information from a specific subject into an overall impact on expression across the entire genome.

[0227] II.1. Input:

[0228] Input the genomic data of a specific subject (e.g., a VCF file obtained through WES sequencing) and identify a list of all genes containing rare coding mutations carried by that subject (assuming there are m mutated genes).

[0229] II.2. Impact on Integration:

[0230] From the driving force matrix established in step I, extract the rows corresponding to the m mutated genes. Then, for each gene j in the genome, calculate the global driving force (GDF) of all mutations of the subject on the expression of gene j by weighted averaging of the driving forces of the m mutated genes.

[0231] II.3. By repeating this step for all genes in the genome, the discrete m mutation information of the subject is ultimately transformed into a one-dimensional continuous vector. Each dimension of this vector represents the overall impact of the subject's gene mutation combination on the expression of the corresponding gene in the genome.

[0232] Step III. Calculate the Pathway Activity Score (APSP)

[0233] The purpose of this step is to further transform the global gene expression impact profile obtained in step II into activity scores for specific biological signaling pathways.

[0234] III.1. Pathway Definition:

[0235] A set of biological signaling pathways related to this disclosure (e.g., the IL-2 signaling pathway described in this disclosure) is predefined, and the list of member genes contained in each pathway is specified, as well as whether each member gene plays an activating (positive) or inhibitory (negative) role in the pathway.

[0236] III.2. Activity Calculation:

[0237] For each predefined signaling pathway, the combined driving force values ​​of all its member genes calculated in step II are weighted and summed according to their positive / negative effects in that pathway. This final weighted sum constitutes the subject's quantitative activity score in that signaling pathway.

[0238] By repeating this step for all pre-defined signaling pathways, a Pathway Activity Profile (APSP) is ultimately generated for the subject. Each dimension of this APSP represents the subject's activity status in a specific signaling pathway. The "Immune Activity Etiology Score" described in this disclosure is calculated based on the relevant feature values ​​in this APSP.

[0239] Through the above steps, the model disclosed herein can objectively and reproducibly convert complex genomic variation information into signaling pathway activity scores that are highly correlated with clinical phenotype and drug efficacy, thereby providing a solid technical foundation for screening patients with "highly immune-active etiologies".

[0240] Methods based on direct measurement of biomarkers

[0241] In some embodiments of this disclosure, the quantification level of the immune-related characteristics can also be obtained by direct physical or biochemical measurements of biological samples obtained from the subject.

[0242] Specifically, techniques known in the art can be used to quantitatively detect the corresponding biomarkers.

[0243] In some implementations, the direct physical or biochemical measurement includes:

[0244] Sample collection and processing: For example, a peripheral blood sample is collected from the subject and plasma (or serum) and peripheral blood mononuclear cells (PBMCs) are obtained by centrifugation.

[0245] Pathway activity measurement: Using plasma samples, the concentrations of key cytokines associated with at least one immune-related characteristic are quantitatively detected by multiplex immunoassay (such as ELISA or Luminex). For example, IL-2, GM-CSF, IFN-γ, IL-1β, etc. are measured as representative indicators of the corresponding immune-related characteristic.

[0246] In some implementations, the pathway is selected from one, two, or more of the following:

[0247] (1) IL-2 signal transduction pathway;

[0248] (2) T helper cell CD28 signal transduction pathway;

[0249] (3) iNOS signal transduction pathway;

[0250] (4) Neutrophil fMLP signal transduction pathway;

[0251] (5) T helper cell iCOS-iCOSL signal transduction pathway;

[0252] (6) GM-CSF signal transduction path;

[0253] (7) Interferon α (Type I IFN) signal transduction pathway;

[0254] (8) Interferon-γ signal transduction pathway;

[0255] (9) IL-1 signal transduction pathway; and

[0256] (10) Toll-like receptor signaling pathway.

[0257] In some implementations, the pathway is selected from at least two of the following groups:

[0258] (1) IL-2 signal transduction pathway;

[0259] (2) T helper cell CD28 signal transduction pathway;

[0260] (3) Interferon α (type I IFN) signal transduction pathway; and

[0261] (4) Interferon-γ signal transduction pathway.

[0262] In some implementations, the pathway includes:

[0263] (1) IL-2 signal transduction pathway;

[0264] (2) T helper cell CD28 signal transduction pathway;

[0265] (3) Interferon α (type I IFN) signal transduction pathway; and

[0266] (4) Interferon-γ signal transduction pathway.

[0267] Cellular function measurements: Using isolated PBMCs, the immune cell population was analyzed by flow cytometry, and the expression levels of their surface activation markers or their ability to secrete cytokines after in vitro stimulation were measured to obtain a quantitative level of their function.

[0268] In some embodiments, the immune cell population is a D8+ T cell population, and proteins directly related to CD8+ T cell function are measured to obtain a quantitative level of their function. In some preferred embodiments, the proteins directly related to CD8+ T cell function include at least one or more of CD8A, GZMB, and PRF1, and may also include one or more selected from Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

[0269] The quantitative measurement results obtained by the above method can also be used as input for subsequent score calculations. For the standardization of eigenvalues ​​(Z-score calculation) and the summation of immune activity etiology scores, please refer to the relevant content in the section on calculation and inference methods based on genomic data in this disclosure, which will not be repeated here.

[0270] In some implementations, the methods used for direct physical or biochemical measurements include, but are not limited to, Western blotting, enzyme-linked immunosorbent assay (ELISA), flow cytometry, immunohistochemistry, immunoprecipitation, mass spectrometry, protein microarray, and RNA sequencing. Those skilled in the art can determine the specific biochemical methods to use based on actual needs.

[0271] Determining the screening threshold

[0272] A key innovation of this model lies in the fact that the threshold used to screen patients with "highly immune-active etiologies" is not arbitrarily set, but rather empirically determined through retrospective analysis based on real-world clinical data. As shown in Embodiment 3 of this disclosure, by comparing the immune-active etiology scores of a group of ALS patients treated with JAK inhibitors with their final clinical efficacy (e.g., whether disease progression slowed), a critical score that can best distinguish between "treatment responders" and "treatment non-responders" can be found. This critical score is adopted as the "preset threshold" of this model. This method ensures that the selected patient population is statistically significantly correlated with positive treatment effects, greatly improving the accuracy and success rate of treatment.

[0273] In some implementations, the preset threshold is a preset threshold determined for at least one immune-related feature described in this disclosure.

[0274] Computer implementation of the model

[0275] The immune activity etiology scoring model described in this disclosure can be fully automated using a computer system. In some implementation schemes, typical implementation methods include:

[0276] System architecture: One or more servers or local computing devices configured with hardware processors, memory, and non-transitory computer-readable media.

[0277] Software module: A series of software modules or program instructions stored on a computer-readable medium that, when executed by a processor, enable the complete flow of the model.

[0278] Execution process:

[0279] 1. Input module: Responsible for receiving and parsing patient genomic data stored in a standard format (such as VCF).

[0280] 2. APSP Calculation Module: Embedded or calling the DAGM algorithm, it processes the input VCF file and generates a signaling pathway activity profile containing one, two or more key immune features.

[0281] 3. Scoring Calculation Module: Reads the statistical parameters (μ and σ) of the pre-stored reference queue from the database, calculates the standardized score of each feature according to the Z-score formula, and sums them to obtain the final score.

[0282] 4. Decision and Reporting Module: This module compares the calculated score with preset clinical thresholds and automatically generates a structured, easily interpretable, personalized treatment recommendation report based on the comparison results. The report clearly indicates whether the patient has been identified as having a "highly immunologically active etiology" and, accordingly, recommends whether to use a JAK inhibitor for treatment.

[0283] In this way, the model can serve as an efficient and reproducible clinical decision support tool, seamlessly integrated into the workflow of modern precision medicine.

[0284] Calculation of immune activity etiology score

[0285] In this disclosure, the quantitative levels of one or more immune-related features of a subject are obtained through computational inference methods based on genomic data or through methods based on direct measurement of biomarkers. Subsequent scoring steps aim to integrate these feature data into a single, clinically interpretable "immune activity etiology score".

[0286] Flexibility of feature combination

[0287] In some embodiments, the methods of this disclosure use at least one immune-related feature highly correlated with ALS immunopathology. In some preferred embodiments, the immune-related feature highly correlated with ALS immunopathology includes, but is not limited to, the following:

[0288] (1) Activity level of the IL-2 signal transduction pathway;

[0289] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0290] (3) Activity level of the iNOS signal transduction pathway;

[0291] (4) Activity level of the fMLP signal transduction pathway in neutrophils;

[0292] (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells;

[0293] (6) Activity level of the GM-CSF signal transduction pathway;

[0294] (7) Activity level of the interferon α (type I IFN) signal transduction pathway;

[0295] (8) Activity level of the interferon-γ signal transduction pathway;

[0296] (9) Activity level of the IL-1 signaling pathway;

[0297] (10) Activity levels of the Toll-like receptor signaling pathway; and

[0298] (11) Quantitative level of CD8+ T cell function.

[0299] In some implementation schemes, any one, two, three, four, five, six, seven, eight, nine, ten, or all eleven of these eleven pre-defined immune-related characteristic species may be used.

[0300] In some embodiments, the at least one immune-related feature includes at least two, preferably five, features selected from the group of immune-related features highly associated with ALS immunopathology disclosed herein.

[0301] Those skilled in the art will understand that, based on the findings of this disclosure, any one of the 11 features, or any combination of any number of subsets thereof, can be used to construct an effective screening model. For example, a simplified scoring model can be constructed using only the two features of IL-2 signaling pathway activity and CD8+ T cell function.

[0302] In some preferred embodiments, the at least one immune-related feature includes at least one, two, or more immune-related features selected from the group consisting of:

[0303] (1) Activity level of the IL-2 signal transduction pathway;

[0304] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0305] (3) Activity level of the interferon α signal transduction pathway;

[0306] (4) The activity level of the interferon-γ signaling pathway; and

[0307] (5) Quantitative levels related to CD8+ T cell function.

[0308] In some preferred embodiments, the at least one immune-related feature includes the following five immune-related features:

[0309] (1) Activity level of the IL-2 signal transduction pathway;

[0310] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0311] (3) Activity level of the interferon α signal transduction pathway;

[0312] (4) The activity level of the interferon-γ signaling pathway; and

[0313] (5) Quantitative levels related to CD8+ T cell function.

[0314] In some implementations, any subset of these features, or even a single feature, can be used to construct a scoring model and screen patients. Those skilled in the art will understand that when different features or subsets of features are selected, the reference cohort statistics (μ and σ) used to calculate the Z-score, as well as the preset thresholds ultimately used for decision-making, all need to be independently established and optimized for that specific feature or subset of features selected.

[0315] Screening and Optimization of Feature Combinations

[0316] Through the analysis of Example 1, the inventors have for the first time revealed a set of biological characteristics highly correlated with the immune status of ALS patients, including 10 significantly activated immune signaling pathways and a key immune cell functional state, which together constitute a feature pool containing 11 candidate features. This lays a solid scientific foundation for the subsequent construction of the scoring model of this invention.

[0317] Those skilled in the art will understand that various effective scoring models can be constructed based on this feature pool containing 11 features. For example, all 11 features can be used to construct a most comprehensive model, or a subset of any one or more features can be selected to construct a model based on clinical needs or testing costs.

[0318] However, to achieve the optimal balance between predictive accuracy, clinical applicability, and computational efficiency, the inventors, through further inventive research and screening, identified an optimized combination of five core features from the aforementioned 11 candidate features. Extensive computation and data analysis have demonstrated that this combination of five features is sufficient to capture key information distinguishing the etiological status of patients' immune activity, effectively and robustly meeting the needs of screening patients with highly immune-active etiologies.

[0319] Therefore, in a particularly preferred embodiment of the present invention, the immune-related features used to calculate the immune activity etiology score include the following five items:

[0320] (1) Activity level of the IL-2 signal transduction pathway;

[0321] (2) Activity level of CD28 signal transduction pathway in T helper cells;

[0322] (3) Activity level of the interferon α signal transduction pathway;

[0323] (4) The activity level of the interferon-γ signaling pathway; and

[0324] (5) Quantitative levels related to CD8+ T cell function.

[0325] It should be emphasized that illustrating this combination of 5 features as a preferred option is not intended to limit the scope of protection of this invention. Those skilled in the art, based on the teachings of this invention, can achieve the same or equivalent patient screening results by using other features or different combinations of the original 11 feature pools, following the scoring calculation and threshold determination methodology disclosed in this invention. These variations should all be considered to fall within the spirit and scope of protection of this invention.

[0326] Dynamic optimization of model parameters and thresholds

[0327] Those skilled in the art will understand that the scoring model described in this disclosure is a dynamic system based on statistical and clinical data. Therefore, some parameters in the model may be further optimized and calibrated as more data becomes available, but this does not depart from the core ideas and scope of protection of this invention.

[0328] 1. Stability of Reference Cohort Parameters (μ and σ): In one specific embodiment of this disclosure, the mean (μ) and standard deviation (σ) used to calculate the Z-score are based on a reference cohort comprising 188 ALS patients. Those skilled in the art will understand that as larger patient cohorts are included in the future, these statistical parameters will become more stable and accurate, potentially having a subtle impact on the final score of individual subjects. However, such parameter updates based on larger sample sizes are routine optimizations performed by those skilled in the art when implementing the methods of this disclosure and do not constitute a substantial change to the core calculation steps of this disclosure (i.e., standardization and summation via Z-score).

[0329] 2. Determination and Optimization of Screening Threshold: In a specific embodiment of this disclosure, a retrospective analysis of five treated patients was conducted, and a score of "1.08" was determined as an effective and feasible preset threshold. One of the core innovations of this disclosure is that it provides a methodology for determining this threshold, namely, "finding a score threshold that can effectively distinguish between treatment responders and non-responders based on retrospective clinical data."

[0330] Therefore, the value "1.08" is itself a non-limiting example of the successful implementation of the method disclosed herein, and not the sole limitation on the scope of protection of this invention. Those skilled in the art will foresee that when more clinical data from treated patients (e.g., dozens or hundreds) become available in the future, this threshold can be further optimized or calibrated using conventional statistical methods in the art (e.g., constructing a receiver operating characteristic (ROC) curve and calculating Youden's index) to achieve higher diagnostic accuracy (i.e., higher sensitivity and specificity). Regardless of whether the final optimized threshold is 1.08, 1.20, or any other value, as long as its determination method follows the principles disclosed in this invention and is linked to clinical efficacy, its application falls within the scope of protection of this invention.

[0331] Treatment

[0332] This disclosure provides an innovative, personalized treatment approach for amyotrophic lateral sclerosis (ALS). This approach fundamentally differs from traditional, "one-size-fits-all" treatment strategies aimed at all patients. Its core lies in an integrated, closed-loop "diagnosis-treatment" process designed to precisely target highly effective immuno-targeted drugs to the patient subgroups most likely to benefit.

[0333] In some implementations, the method of this disclosure includes the following steps:

[0334] (a) Patient screening and identification:

[0335] The first step of this method is to determine whether the ALS subject in need is a patient with a “highly immune-active etiology,” which is a prerequisite for drug administration. This step is accomplished by analyzing genomic data from biological samples (e.g., peripheral blood) obtained from the subject, or by directly measuring and then analyzing biomarkers. Specifically, this determination process is achieved using the “immune-active etiology scoring model” described in detail in this disclosure. This model can convert a patient’s individual genetic information into a quantitative score, thereby objectively assessing the activation status of their immune system.

[0336] (b) Targeted drug delivery:

[0337] The second step of this method is the administration of targeted drugs. For patients identified in step (a) as having a “high immune activity etiology” (i.e., whose immune activity etiology score is higher than a preset clinical threshold), a therapeutically effective dose of a Janus kinase (JAK) inhibitor is administered.

[0338] The purpose of the treatment methods disclosed herein is to provide significant clinical benefits to a selected specific population of ALS patients. As illustrated in the embodiments of this application, these benefits include, but are not limited to: slowing the overall rate of disease progression; stabilizing or improving the patient's clinical functional status, as measured by the ALS Functional Rating Scale Revised Version (ALSFRS-R) score; improving key physiological indicators, such as forced vital capacity (FVC%); and reducing the levels of biomarkers reflecting neuronal axonal damage, such as neurofilament light chains (NfL).

[0339] Janus kinase (JAK) inhibitors

[0340] The JAK family is a class of intracellular non-receptor tyrosine kinases, comprising four members: JAK1, JAK2, JAK3, and TYK2. They are key mediators in the JAK-STAT signaling pathway, responsible for transducing signals from various cytokines, growth factors, and hormones, playing a central role in immune responses and inflammatory reactions. JAK inhibitors, by blocking JAK activity, can effectively inhibit the phosphorylation and activation of downstream STAT proteins, thereby regulating immune cell function and suppressing excessive or abnormal immune responses.

[0341] In some implementations, the JAK inhibitor is tofacitinib, chemically known as tofacitinib citrate. Tofacitinib is an approved oral JAK inhibitor with strong inhibitory effects on JAK1 and JAK3, and secondary inhibitory effects on JAK2.

[0342] This disclosure also covers other JAK inhibitors that can be used in this method. Non-limiting examples of such inhibitors include: baricitinib, upadacitinib, filgotinib, ruxolitinib, etc.

[0343] Regarding the dosing regimen, in some embodiments, the therapeutically effective dose of tofacitinib administered to patients with the aforementioned highly immunologically active etiology is approximately 10 mg daily. This daily dose may be administered as a single dose, or more preferably, orally at a frequency of 5 mg twice daily. In some embodiments, the duration of treatment may be at least 90 days, preferably at least 180 days, or as determined by the clinician based on the patient's response and tolerability. This disclosure also covers a broader range of therapeutically effective doses, such as from approximately 1 mg to approximately 50 mg daily, the specific dose of which may be adjusted by those skilled in the art based on the patient's specific circumstances.

[0344] Combination therapy

[0345] In some implementation schemes, in order to achieve synergistic effects or treat other pathophysiological abnormalities that may exist in ALS patients, other types of therapeutic drugs may be administered in combination with JAK inhibitors for patients with highly immunologically active etiologies.

[0346] As shown in Example 1 of this application, bioinformatics analysis revealed that ALS patients not only exhibit highly activated immune pathways but also show significant inhibition of specific metabolic pathways (e.g., pathways related to pancreatic β-cell function). Therefore, for patients exhibiting both of these pathological characteristics, the combined administration of JAK inhibitors and metabolic modulators can intervene in the disease process from both immune and metabolic dimensions, thereby producing a therapeutic effect superior to monotherapy.

[0347] In some embodiments, the metabolic pathway modulator is insulin. Other non-limiting examples of metabolic modulators that can be used in combination therapy include metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors. These combination therapies can be administered concurrently, separately, or sequentially with a JAK inhibitor.

[0348] Monitoring of treatment efficacy

[0349] In implementing the personalized treatment method of this disclosure for patients with highly immunologically active etiologies, objective and dynamic monitoring of treatment efficacy is crucial for guiding clinical decision-making, assessing patient response, and adjusting treatment regimens. This disclosure provides an effective method for monitoring treatment efficacy.

[0350] The core of this method lies in using neurofilament light chain (NfL) as a key biomarker. NfL is one of the main proteins that make up the neuronal axon cytoskeleton. When neurons (especially their axons) are damaged or degenerate, NfL is released into the cerebrospinal fluid and blood. Therefore, the NfL level detected in peripheral blood (such as serum or plasma) can sensitively and specifically reflect the degree of damage to the nervous system and the activity of the disease, and is a recognized reliable biomarker for the progression of ALS pathology.

[0351] The monitoring method described in this disclosure specifically includes: during the course of JAK inhibitor treatment for patients selected according to the method of this disclosure, collecting biological samples (preferably serum or plasma) from patients at multiple preset time points (e.g., at baseline before the start of treatment, and at 1 month, 3 months, 6 months after treatment, etc.), and measuring the concentration of NfL in the samples using a highly sensitive detection technology (such as Simoa single-molecule array technology).

[0352] Regarding the interpretation of monitoring results, in the methods of this disclosure, if the NfL level in the patient's body shows a continuous decreasing trend after treatment, or remains at a stable level significantly lower than the baseline for a long period, it can be regarded as an objective indicator of treatment effectiveness. As shown in the clinical case studies of this application (Examples 4 and 5), such positive changes in NfL levels are generally associated with positive outcomes of the patient's clinical functional endpoints, such as stabilization or improvement of the ALS FRS-R score, or improvement of FVC%.

[0353] Reagent test kit

[0354] To facilitate the clinical implementation of the personalized treatment methods described in this disclosure, a kit specifically designed for this purpose is also provided.

[0355] In some implementations, the kit includes the following components:

[0356] (a) Drug components:

[0357] The kit contains a therapeutically effective amount of one or more Janus kinase (JAK) inhibitors. In some preferred embodiments, the drug component is tofacitinib citrate, packaged in a unit dosage form suitable for oral administration, such as several tablets or capsules, each unit dose containing 5 mg of tofacitinib.

[0358] (b) Instruction manual:

[0359] The kit includes an instruction manual. The instruction manual contains clear, instructive text, diagrams, or electronic information, and includes at least one of the following:

[0360] ●Population limitation: Clearly instruct users (e.g., clinicians or pharmacists) to administer the JAK inhibitor in the kit to ALS subjects identified as having "high immune activity etiology" by the "immune activity etiology scoring model" described in this disclosure.

[0361] ● Tips on screening methods: The instruction manual may briefly mention or cite the methodological principles to be followed in patient screening, namely, scoring based on patient genomic data.

[0362] ● Recommended dosing regimen: Provides recommended dosage (e.g., 10 mg daily), administration method (e.g., 5 mg twice daily), route of administration (e.g., oral), and recommended duration of treatment.

[0363] ● Instructions for monitoring treatment efficacy: This may include instructions on how to assess treatment efficacy by regularly monitoring patients’ blood NfL levels, and an explanation of the association between decreased NfL levels and positive efficacy.

[0364] application

[0365] Each active agent disclosed herein can be administered orally, orally, sublingually, rectally, vaginally, parenterally, intradermally, or nasally. Parenteral administration includes intravenous, intraperitoneal, intradermal, subcutaneous, intramuscular, intracranial, intrathecal, intratumoral, transcutaneous, transarticular, intrathecal, intrasternal, intrathecal, intrahepatic, spinal, or intracranial injection or infusion.

[0366] The active agents used herein can be formulated into pharmaceutical compositions for administration using known techniques. See, for example, Remington, *The Science and Practice of Pharmacy* (9th Ed. 1995). When manufacturing pharmaceutical compositions according to this disclosure, the active agent is typically mixed with a pharmaceutically acceptable carrier, etc. Of course, the carrier must be acceptable, i.e., compatible with any other component in the formulation and not harmful to the patient. The carrier can be solid or liquid, or both, and is preferably formulated with the compound into a unit dose formulation, such as tablets, where the active agent content can range from 0.01% or 0.5% to 95% or 99% by weight. One or more active agents may be incorporated into the formulations of this disclosure, and the preparation of the formulation can employ any well-known pharmaceutical technique, including mixing the components, optionally including one or more excipients and / or excipients. In some embodiments, any composition, carrier, excipient, and / or formulation of this disclosure contains components of natural or non-natural origin. In other embodiments, any component of the composition, carrier, excipient, and / or formulation of this disclosure may be provided in sterile form. Non-limiting examples of sterile carriers include endotoxin-free water or pyrogen-free water.

[0367] In some embodiments, the pharmaceutical compositions of this disclosure are provided as part of a sterile composition / preparation comprising the active agent of this disclosure and a pharmaceutically acceptable carrier and / or excipient.

[0368] Suitable dosage forms for oral administration include tablets, capsules, powders, pills, granules, suspensions, solutions or pre-concentrated solutions, emulsions or pre-concentrated emulsions. Acceptable drug carriers for oral dosage forms include water, ethylene glycol, oils, alcohols, flavoring agents, preservatives, and coloring agents. Carriers such as starch, sugar, microcrystalline cellulose, diluents, fillers, lubricants, granulators, binders, stabilizers, and disintegrants can be used to prepare oral solid dosage forms such as powders, capsules, or tablets.

[0369] Diluents include, but are not limited to, microcrystalline cellulose, mannitol, powdered sugar, compressible sugar, dextran, dextrin, sucrose, lactose, cellulose powder, sorbitol, sucrose, and talc, or combinations thereof. The diluent may constitute 5% to 90% of the total weight of the oral composition, preferably 10% to 80%, 20% to 70%, 30% to 60%, or 40% to 50%.

[0370] Disintegrants include, but are not limited to, cellulose, alginate, gum, cross-linked polymers (such as crosporinone or clovione), sodium glucosamine, calcium glucosamine, soybean polysaccharide, sodium starch glycolate, guar gum, or any combination thereof. The content of the disintegrant may be 1% to 15%, preferably 2% to 10%, depending on the total weight of the oral composition.

[0371] The binder includes, but is not limited to, starch, cellulose or its derivatives, such as microcrystalline cellulose, hydroxypropyl cellulose, hydroxyethyl cellulose and hydroxypropyl methyl cellulose, sucrose, glucose, corn syrup, polysaccharides, gelatin or any combination thereof. The binder content may be from 0.01% to 10% based on the total weight of the composition, preferably from 1% to 10%.

[0372] Lubricants include, but are not limited to, colloidal silica, magnesium trisilicate, cellulose powder, talc, or combinations thereof. The content of the lubricant may be from 0.1% to 10% based on the total weight of the composition, preferably from 0.1% to 0.5%.

[0373] The dosage form may be tablets or capsules, and the effective dose may be provided in one or more tablets or capsules, once a day or throughout the day, at intervals of 4, 8, or 12 hours. For example, tablets or capsules may contain 10, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1,000, 1,100, or 1,250 mg of active agent. For example, administration of the active agent of this disclosure to humans may include a daily dose in the range of 100-1,250, 150-1,000, 200-800, or 250-750 mg, which may be administered either once a day or in portions throughout the day. Liquid formulations may also be prepared for convenient dispensing of any dose at any time.

[0374] Parenteral dosage forms are preferably sterile or can be sterilized before administration to the subject. Examples of parenteral dosage forms include, but are not limited to: solutions prepared for injection, dry products prepared for dissolution or suspension in a pharmaceutically acceptable injectable carrier, suspensions prepared for injection, and emulsions.

[0375] Suitable carriers that can be used to provide the parenteral dosage forms provided herein include, but are not limited to, water for injection; aqueous carriers, such as, but not limited to, sodium chloride injection, Ringer's solution, and glucose injection; water-soluble carriers, such as, but not limited to, ethanol, polyethylene glycol, and polypropylene glycol; and non-aqueous carriers, such as, but not limited to, corn oil, cottonseed oil, peanut oil, sesame oil, ethyl oleate, isopropyl myristate, and benzyl benzoate.

[0376] Compounds that increase the solubility of one or more active agents may also be added to the parenteral dosage forms provided herein. For example, cyclodextrins and their derivatives may be used to increase the solubility of the active agents disclosed herein.

[0377] It should be understood that the effective therapeutic dose can be determined by the physician based on the type, stage and / or severity of the disease, the condition, age, weight, sex, the patient's response, and the route of administration.

[0378] Therapeutic effective dose refers to a dose sufficient to achieve a plasma concentration of about 0.01 μg / ml to about 100 μg / ml, about 0.1 μg / ml to about 10 μg / ml, or about 1 μg / ml to about 5 μg / ml when administered to a subject.

[0379] When the active agents of this disclosure are administered to a subject, the therapeutically effective amount of each active agent of this disclosure is generally in the range of about 0.5 to about 250 mg / kg, about 1 to about 250 mg / kg, about 2 to about 200 mg / kg, about 3 to about 120 mg / kg, about 5 to about 250 mg / kg, about 10 to about 200 mg / kg, or about 20 to about 120 mg / kg. In some implementations, the therapeutically effective dose may be 0.5 mg / kg, 1 mg / kg, 2 mg / kg, 3 mg / kg, 4 mg / kg, 5 mg / kg, 6 mg / kg, 8 mg / kg, 10 mg / kg, 20 mg / kg, 25 mg / kg, 40 mg / kg, 50 mg / kg, 60 mg / kg, 75 mg / kg, 100 mg / kg, 120 mg / kg, 150 mg / kg, 175 mg / kg, 200 mg / kg, 225 mg / kg, 250 mg / kg, or 300 mg / kg.

[0380] Alternatively, when administering the active agents of this disclosure to a subject, the therapeutically effective amount of each active agent of this disclosure is generally in the range of about 0.5 to about 250 mg / day, about 1 to about 250 mg / day, about 2 to about 200 mg / day, about 3 to about 120 mg / day, about 5 to about 250 mg / day, about 10 to about 200 mg / day, or about 20 to about 120 mg / day. In some embodiments, the therapeutically effective amount may be 0.5 mg / day, 1 mg / day, 2 mg / day, 3 mg / day, 4 mg / day, 5 mg / day, 6 mg / day, 8 mg / day, 10 mg / day, 20 mg / day, 25 mg / day, 40 mg / day, 50 mg / day, 60 mg / day, 75 mg / day, 100 mg / day, 120 mg / day, 150 mg / day, 175 mg / day, 200 mg / day, 225 mg / day, 250 mg / day, or 300 mg / day. Each active agent of this disclosure may be administered once or twice daily; or once every 2, 3, 4, 5, 6, 7, 8, 9, or 10 days; or once every 1, 2, or 3 weeks. In some embodiments, each active agent of this disclosure may be administered five times a week. In a five-times-a-week regimen, administration may be performed for five consecutive days (once a day), followed by two consecutive days of rest.

[0381] In some preferred embodiments, when administering the active agent of this disclosure to a subject, the therapeutically effective dose of each active agent of this disclosure is 10 mg / day. In some preferred embodiments, when administering the active agent of this disclosure to a subject, the therapeutically effective dose of each active agent of this disclosure is 5 mg / dose twice daily. In some preferred embodiments, when administering the active agent of this disclosure, such as tofacitinib, to a subject, such as an ALS patient, the therapeutically effective dose of each active agent of this disclosure is 5 mg / dose twice daily.

[0382] As used herein, the term "kit" refers to a pharmaceutical package, which typically includes instructions for use. The active agents or pharmaceutical compositions in a kit can be any of a variety of forms suitable for dispensing in a kit. These forms can include liquids, powders, tablets, suspensions, etc. Two or more active agents can be packaged separately in containers suitable for individual administration or as a combination in one container of the package. Depending on the treatment method, the kit may contain sufficient doses of one or more agents. Instructions for use generally include written instructions on how to use the formulations in the kit to treat a disease (such as ALS).

[0383] It should be understood that the compositions or pharmaceutical compositions of this disclosure may include, in addition to the active agent of this disclosure, other therapeutic agents or therapies, such as biological therapeutic agents and / or chemotherapeutic agents. In addition to administering the active agent of this disclosure, the method may also include administering other therapeutic agents or therapies, such as biological therapeutic agents and / or chemotherapeutic agents. Other therapeutic agents or therapies may be administered simultaneously, separately, or sequentially with the therapeutic agents of this disclosure.

[0384] Example

[0385] Example 1. The ALS patient population showed significant activation of immune-related pathways and significant inhibition of metabolic-related functions.

[0386] 1. Sample collection and genomic data processing

[0387] (1) Collect peripheral blood samples from ALS patients and healthy elderly people, separate leukocytes and extract their genomic DNA, and perform DNA quality control according to the second-generation sequencing requirements of Illumina NovaSeq.

[0388] (2) Samples that passed DNA quality control were subjected to whole exome sequencing on the Illumina NovaSeq 6000 platform in PE150 sequencing mode.

[0389] (3) Data with a sequencing volume ≥15G and Q30 ≥85% are considered qualified data. A total of 86 ALS patients’ whole exome sequencing (WES) data were obtained, including 29 females with an average age of 50 years and 57 males with an average age of 49 years; and 172 healthy elderly people’s whole exome sequencing (WES) data, including 114 females with an average age of 78 years and 58 males with an average age of 79 years.

[0390] Rare variant (MAF<0.01) sites were extracted from the WES data (Fastq files) of all the subjects using the GATK Best Practices workflow, forming a one-to-one corresponding VCF file.

[0391] 2. Results of analysis on signaling pathway activity and cell function

[0392] The subjects' VCF file data were input into the DAGM algorithm to calculate the global gene expression level and APSP for each subject, and the characteristic differences between ALS patients and healthy elderly individuals were compared. The results are shown in Table 1 below. The most significant differences were found in the activity of 13 signaling pathways (including 10 immune-related signaling pathways and 3 cell communication, development, or division-related signaling pathways) and the function of 1 metabolic-related cell. The values ​​are represented by the Z-score, which represents the standardized deviation of the signaling activity values ​​or cell function levels of ALS patients compared to healthy elderly individuals as a baseline.

[0393] Table 1. Functional characteristics of ALS patients (compared to healthy elderly individuals) Note: The larger the absolute value of the number in the table, the more significant it is. Negative values ​​indicate that the current pathway is significantly activated in the ALS population, while positive values ​​indicate that the current pathway is significantly inhibited in the ALS population.

[0394] The 10 pathways that were significantly activated are shown in Figure 1-10; the 4 pathways or cellular functions that were significantly inhibited are shown in Figure 11-14.

[0395] 3. Analysis results of differences in signaling pathway activity and cellular functional characteristics between different sexes

[0396] The 86 patients included various genotypes (e.g., C9orf72 gene mutation, SOD1 gene mutation, TARDBP gene mutation, FUS gene mutation, OPTN gene mutation, ATXN2 gene mutation, TBK1 gene mutation, etc.). However, the APSP of ALS patients of different sexes and healthy elderly people of the same sex showed that the differences in eigenvalues ​​were distributed from the lower left to the upper right (as shown in Figure 15, where each black dot represents a signaling pathway or cell function), and the correlation coefficient R = 0.6659, which is a strong correlation. This indicates that ALS patients, regardless of sex, have certain systematically consistent signaling pathways and cell function characteristics.

[0397] 4. There are synergistic relationships among functional pathways.

[0398] There are also synergistic relationships between functional pathways; the amplitude of functional abnormalities is correlated across different pathways. We found that if a patient has a high degree of abnormality in immune function, their metabolic pathway abnormalities will also be high. This finding is very helpful in understanding systemic etiologies.

[0399] We found that some patients had activity at both ends of the most significantly upregulated / downregulated pathways. For example, if a patient had particularly high activation of the most significantly upregulated pathway (IL-2 signaling) in a distribution of 86 patients, we found that their activity in the most significantly downregulated pathway (pancreas β cells) would rank very low. Others, however, had activity in the middle of both pathways.

[0400] 5. Targeting functional characteristic-driven biological mechanisms can guide clinical drug use.

[0401] Janus kinases (JAKs), including JAK1, JAK2, JAK3, and TYK2, require phosphorylation to form various signaling pathways under the influence of more than 30 stimuli, such as IL-2, IL-6, IFNα, IFNγ, and GM-CSF1. IL-2-JAK or IL-6-JAK signaling can enhance T cell proliferation and function. IFNα or IFNγ-JAK signaling is crucial for antiviral function and inflammation. Tofacitinib, baricitinib, upadacitinib, and filgotinib are JAK inhibitors approved by the U.S. Food and Drug Administration for the treatment of various autoimmune and inflammatory diseases.

[0402] Tofacitinib can cross the blood-brain barrier (BBB). Baricitinib has crossed the BBB in HIV mouse models. It is currently unclear whether udatinib or fioglotinib can cross the BBB.

[0403] Tofacitinib affects the activity of human stem cells. It reduces CD80 / CD86 expression and T cell stimulation capacity by inhibiting type I IFN signaling. Tofacitinib inhibits the production of tumor necrosis factor, IL-6, and IL-1β, but does not affect the production of transforming growth factor (TGF)-β and IL-10. Therefore, tofacitinib could be an effective drug for treating ALS by inhibiting the signaling of IL-2, IL-6, IL-α, IL-1β, IFNγ, IFNa, CD80 / CD86, and T cell proliferation and function.

[0404] Our data indicate that pancreatic β-cell signaling is most significantly downregulated at the gene level in ALS patients, suggesting impaired insulin function. Indeed, diabetes medication use is associated with a lower risk of ALS. Therefore, insulin-based therapy should be beneficial for ALS.

[0405] Example 2. Clinical study of tofacitinib for the treatment of ALS

[0406] Overview

[0407] Based on the functional pathway characteristics obtained in Example 1 above, ALS patients were treated with the JAK inhibitor XELJANZ (Tofacitinib).

[0408] Clinical study design

[0409] This study employs a single-center, single-arm, proof-of-concept (IIT) clinical trial protocol. Subjects will receive oral tofacitinib, one tablet (5 mg) twice daily for 180 days. The study aims to recruit 12 ALS patients meeting the following inclusion criteria:

[0410] • Individuals aged 18 to 75 years who are clinically diagnosed with early-stage ALS and do not have severe liver, kidney, or heart dysfunction;

[0411] • Able to cooperate in completing follow-up visits;

[0412] Research measurement and follow-up

[0413] Follow-up was conducted at baseline, day 30±3, day 90±7, and day 180±14, all via face-to-face visits. The following key efficacy endpoints were reviewed and collected:

[0414] • Neurofilament light chain (NfL) level;

[0415] • Forced vital capacity (FVC%);

[0416] •ALSFRS-R score.

[0417] If a subject's ALSFRS-R score decreases by 7 or more on day 90±7 of tofacitinib treatment, it indicates a poor response to treatment, and the patient will be discontinued from this study.

[0418] Since tofacitinib is an off-label treatment for ALS, the ALS Functional Rating Scale-Revised (ALSFRS-R) was performed on the 6 enrolled patients at the 90-day follow-up and reported to the Data Safety Oversight Board (DSMB).

[0419] Key efficacy assessment indicators

[0420] 1. Neurofilament light chains (NfL)

[0421] Neurofilament light chains (NfLs) are a family of neurofilament proteins, primarily found in the axons of nerve cells, and participate in the formation and maintenance of the cytoskeleton. Cerebrospinal fluid (CSF), serum, and plasma NfL levels showed high sensitivity (97%, 89%, and 90%, respectively) and specificity (95%, 75%, and 71%, respectively) in distinguishing ALS patients from healthy controls. CSF NfL levels were highly correlated with serum levels (r = 0.78, p < 0.0001). Blood NfL levels in ALS patients were approximately four times higher than in controls, and remained relatively stable during follow-up. Baseline blood NfL levels were a strong and independent predictor of survival. The highest quantile mortality hazard ratio for baseline blood NfL was 3.91 (95% confidence interval 1.98–7.94, p < 0.001).

[0422] 2. Forced vital capacity (FVC%)

[0423] FVC is the most commonly used measure to assess respiratory muscle function. The rate of FVC decline at initial visit and the percentage of predicted FVC (%FVC) are important predictors of survival in ALS patients. Among 1034 patients diagnosed or likely to have ALS, the median survival was 2.91 years for patients with baseline FVC <75%, while the median survival was 4.08 years for patients with baseline FVC >75% (p<0.001).

[0424] 3. ALS Functional Rating Scale-Revised (ALSFRS-R)

[0425] The ALS FRS-R is a standardized scale used to assess the functional status and disease progression of ALS patients, covering multiple aspects of activities of daily living. The scale consists of 12 items, each scored from 0 to 4, with a total score ranging from 0 to 48. Higher scores indicate better functional status. Assessment items include language, drooling, swallowing, writing, eating, dressing and hygiene, bed-chair transition, walking, stair climbing, dyspnea, mouth breathing assistance, and ventilator dependence. High scores indicate greater independence and better functional status in activities of daily living, with slower disease progression; low scores indicate more functional limitations and faster disease progression.

[0426] Clinical trial results

[0427] As of now, efficacy evaluation has been completed on day 90±7 of enrollment for the 5 patients in the study group. The results are as follows:

[0428] • The NfL levels of patients 001-003 all showed an upward trend after treatment, while only patient 004 showed a downward trend, indicating that the nerve damage in patient 004 was improved.

[0429] • The vital capacity (FVC%) of patients 002-004 continued to increase after treatment, indicating that the lung function of these three patients improved.

[0430] The ALSFRS-R scores of patients 002 and 003 decreased slowly, while the ALSFRS-R score of patient 004 remained unchanged, indicating that the disease progression of these three patients was significantly slowed.

[0431] Comprehensive efficacy assessment showed that patients 002, 003, and 004 experienced a significant slowdown in disease progression and were classified as patients who responded positively to treatment.

[0432] Example 3. Establishing an immune activity etiology scoring model and screening ALS patients.

[0433] Based on the immune-related signaling pathway characteristics of the ALS patient population obtained in Example 1, an immune activity etiology scoring model can be established by combining the corresponding signaling pathway characteristics with the functional status of CD8+ T cells to assess the patients' immune activity etiology status. The model quantifies and scores the immune activity etiology status of each ALS patient, and based on the scoring results, ALS patients with immune activity etiology scores higher than a preset threshold are included in the treatment plan and given tofacitinib.

[0434] The steps for constructing and using the immune activity etiology scoring model are as follows:

[0435] (1) Peripheral blood samples were collected from 188 ALS patients, leukocytes were separated from them and genomic DNA was extracted from the subjects. Genomic DNA could also be extracted from other biological samples from which the subjects' oral epithelial cells, hair follicle cells and other biological samples from which the subjects' genomic DNA could be extracted.

[0436] (2) Perform whole exome sequencing (WES) on the genomic DNA extracted above;

[0437] (3) Extract the rare variant (MAF<0.01) sites from the WES data (Fastq file format) of all the subjects to form a one-to-one corresponding VCF file;

[0438] (4) Input the VCF file of the subject into the DAGM algorithm to calculate the global gene expression level and APSP for each subject;

[0439] (5) Based on the first, second, seventh and eighth signaling pathways in Table 1, extract the corresponding signaling pathway activity value for each subject from the APSP results in (4) above;

[0440] (6) Extract the expression levels of CD8+ T cell function-related proteins for each subject from the APSP results in (4) above;

[0441] (7) Calculate the mean μ and standard deviation σ of each characteristic value in (5)-(6) above in all 188 patients;

[0442] (8) The Z score(Z) corresponding to each feature value obtained from (5)-(6) above for the 188 patients was calculated using the following formula: Z=(x-μ) / σ,

[0443] Where x represents the activity value of signaling pathways or the expression level of proteins related to CD8+ T cell function in this patient with specific characteristics;

[0444] (9) Sum the Z scores of all the feature values ​​obtained for each patient in (8) above to obtain the immune activity etiology score for that patient;

[0445] (10) The distribution of all patient etiology scores (Sum of Z-score(all features)) obtained in (9) above is shown in Figure 16. An appropriate score screening threshold will be selected based on actual patient efficacy data, and patients with scores higher than the selected threshold will be defined as patients with highly immune-active etiology.

[0446] (11) The immune activity etiology scores of the 5 ALS patients treated with the JAK inhibitor XELJANZ (Tofacitinib) in Example 2 above were obtained as follows;

[0447] Peripheral blood samples, oral epithelial cells, hair follicle cells, or other biological samples from which the subject's genomic DNA could be extracted were collected from 5 patients. Genomic DNA was then extracted from each patient.

[0448] <ii>Whole exome sequencing was performed on the extracted genomic DNA to obtain Fastq files.

[0449] <iii>Rare variant sites (MAF < 0.01) were extracted from the Fastq file to form a VCF file.

[0450] <iv>The VCF file was input into the DAGM algorithm to calculate the patient's global gene expression level and APSP.

[0451] <v>From the above <iv>The activity values ​​of signaling pathways 1, 2, 7, and 8 in Table 1 of this patient's results were extracted.

[0452] <vi>From the above <iv>The results showed that the expression levels of proteins related to CD8+ T cell function in this patient were extracted.

[0453] <vii>The Z score (Z) of the activity value and protein expression level of each signaling pathway was calculated using the following formulas.

[0454] Z = (x - μ) / σ, where μ and σ are the mean and standard deviation of each characteristic value of all 86 patients obtained in step (7) above, respectively, and x is the corresponding signaling pathway activity value or protein expression level of the patient.

[0455] <viii>The above <vii>The Z scores of each feature are summed to obtain the patient's immune activity etiology score.

[0456] (12) Comparing the immune activity etiology scores and treatment efficacy of all patients in (11) above, the results showed that the scores of the three patients who responded positively to the treatment were 5.73, 9.97 and 2.53, respectively, while the scores of the patients who did not respond positively were 1.08 and -8.71, respectively. Therefore, the highest score of 1.08 for patients who did not respond positively was selected as the threshold. When the patient's immune activity etiology score is higher than this threshold, the patient is considered to have a high immune activity etiology.

[0457] The above steps (3)-(12) constitute the immune activity etiology scoring model.

[0458] Those skilled in the art will understand that the 1.08 threshold is an effective cutoff point determined based on currently limited clinical sample data. As future clinical data accumulates, this threshold can be dynamically optimized using statistical methods known in the art (such as constructing receiver operating characteristic (ROC) curves and calculating the Youden index) to obtain optimal diagnostic performance. All scoring thresholds determined based on the principles disclosed in this invention, aimed at distinguishing between JAK inhibitor treatment responders and non-responders, should be considered to fall within the scope of protection of this invention.

[0459] Example 4: Case study of a patient with highly immunologically active etiological ALS treated with the JAK inhibitor tofacitinib

[0460] This example describes the process and efficacy of treating a 72-year-old female ALS patient with a high immune-active etiology as assessed by an immune-active etiology scoring model using the JAK inhibitor tofacitinib.

[0461] First, peripheral blood samples were collected from the patient. Then, the patient's immune activity score was calculated according to steps (11)-(12) in Example 3. The score was 1.34, which was higher than the threshold of 1.08, indicating that the patient had a high immune activity cause.

[0462] Treatment plan

[0463] Medication: Tofacitinib Citrate Tablets (Brand Name: ), specification 5mg / tablet.

[0464] Dosage and administration: Starting from August 9, 2024, take tofacitinib orally twice daily, 5 mg each time.

[0465] During treatment: The patient stopped taking the medication for about a week around September 30, 2024 for some reason, and then resumed taking the medication.

[0466] Therapeutic effect observation

[0467] Neuronal injury markers (NfL): As shown in Table 2 and Figure 17, the serum levels of neurofilament light chains (NfL) in patients generally showed a decreasing trend during treatment. At baseline (July 25, 2024), the NfL level was approximately 148 pg / mL, decreasing to approximately 68 pg / mL by June 12, 2025, indicating that neuronal damage may have been alleviated to some extent.

[0468] Table 2

[0469] Functional Rating Scale-Revised (ALSFRS-R): As shown in Figure 18, the patient's ALSFRS-R score fluctuated during treatment. Approximately 3 weeks after starting medication, the patient experienced a temporary and rapid decline in score due to a fall (from approximately 28 points on September 18, 2024 to approximately 22 points on October 18, 2024). However, with continued medication, the ALSFRS-R score showed an upward trend, reaching approximately 28 points by December 18, 2024, and remained within the range of 20-24 points during subsequent observation. This suggests that drug treatment may have a stabilizing or improving effect on functional decline caused by the disease itself.

[0470] Patient's chief complaint: The patient reported that the muscle twitching decreased after taking the medication compared to before.

[0471] in conclusion

[0472] This case demonstrates that using an immune-active etiology scoring model to screen ALS patients with highly immune-active etiologies through genomic data, and treating these ALS patients with the JAK inhibitor tofacitinib, resulted in a decrease in the level of the neurological injury marker NfL and a stabilization or improvement in the ALS FRS-R functional score, showing good therapeutic potential.

[0473] Example 5: Case study of a patient with ALS of another highly immunologically active etiology treated with the JAK inhibitor tofacitinib.

[0474] This example describes the process and efficacy of treating a 56-year-old male ALS patient with a high immune-active etiology as assessed by an immune-active etiology scoring model using the JAK inhibitor tofacitinib.

[0475] First, peripheral blood samples were collected from the patient. Then, the patient's immune activity score was calculated according to steps (11)-(12) in Example 3. The score was 5.96, which was higher than the threshold of 1.08, indicating that the patient had a high immune activity cause.

[0476] Treatment plan

[0477] Medication: Tofacitinib citrate tablets, 5mg / tablet.

[0478] Dosage and administration: Starting from January 16, 2025, take tofacitinib orally twice daily, 5 mg each time.

[0479] Therapeutic effect observation

[0480] Neuronal injury markers (NfL): As shown in Table 3 and Figure 19, the serum levels of neurofilament light chains (NfL) in patients generally showed a decreasing trend during treatment. At baseline (January 15, 2025), the NfL level was approximately 20.79 pg / mL, decreasing to 19.65 pg / mL by April 16, 2025, indicating that neuronal damage may have been alleviated to some extent.

[0481] Lung function (FVC%): As shown in Table 3 and Figure 20, the percentage of forced vital capacity (FVC) to predicted value improved after treatment. At baseline (January 15, 2025), FVC% was 84.8%, which increased to 87.1% after 3 months of treatment (April 16, 2025), indicating a certain degree of improvement in respiratory muscle function.

[0482] Table 3

[0483] Functional score (ALSFRS-R): As shown in Figure 21, the patient's ALSFRS-R score decreased slightly after one month of medication (from 39 points at baseline to 37 points), but remained stable at 37 points after three months of medication. This suggests that the medication may have slowed the functional decline caused by the disease.

[0484] Safety: One month after starting medication, the patient experienced a slight increase in alanine aminotransferase (ALT), but did not receive any liver-protective medication. By the time of a follow-up examination three months after starting medication, the ALT level had spontaneously returned to a safe range.

[0485] in conclusion

[0486] This case further confirms that treatment with the JAK inhibitor tofacitinib is effective and safe for ALS patients with highly immunologically active etiologies. The treatment not only stabilizes the patient's functional status (e.g., ALS FRS-R score) but also improves key physiological indicators (e.g., FVC%) and slows disease progression.

[0487] The foregoing description is intended to be merely illustrative of the principles of this disclosure. Furthermore, since many modifications and variations will be apparent to those skilled in the art, it is not intended to limit this disclosure to the exact construction and process described above. Therefore, all suitable modifications and equivalents may be considered to fall within the scope of this disclosure as defined by the appended claims.

[0488] All publications, patents and patent applications cited herein are incorporated herein by reference in their entirety.< / vii> < / viii> < / vii> < / iv> < / vi> < / iv> < / v> < / iv> < / iii> < / ii>

Claims

1. A method for treating amyotrophic lateral sclerosis (ALS) in a subject of need, the method comprising: (a) By analyzing biological samples obtained from the subject, the quantitative level of at least one pre-defined immune-related feature is obtained; (b) Calculate the etiology score of immune activity based on the quantification level of the at least one immune-related feature; (c) The immune activity etiology score is compared with a preset threshold to determine whether the subject is a patient with a high immune activity etiology. as well as (d) For patients identified in step (c) as having a high immune response, administer a therapeutically effective dose of a Janus kinase (JAK) inhibitor.

2. A Janus kinase (JAK) inhibitor for the treatment of amyotrophic lateral sclerosis (ALS) in subjects of need, wherein, The subject is a patient identified as having a highly immunologically active cause by the method according to claim 1.

3. Use of a Janus kinase (JAK) inhibitor in the preparation of a medicament for the treatment of amyotrophic lateral sclerosis (ALS), wherein, The drug is suitable for administration to subjects who are patients identified as having a hyperimmune etiology according to the method of claim 1.

4. The method, JAK inhibitor, or use according to any one of claims 1 to 3, wherein, In step (a), the quantification level is obtained by calculation and inference of genomic data in the biological sample.

5. The method, JAK inhibitor, or use according to any one of claims 1 to 3, wherein, In step (a), the quantification level is obtained by direct physical or biochemical measurements of the biological sample.

6. The method, JAK inhibitor, or use according to any one of claims 1 to 5, wherein, The at least one immune-related feature is selected from the following group: (1) Activity level of the IL-2 signal transduction pathway; (2) Activity level of CD28 signal transduction pathway in T helper cells; (3) Activity level of the iNOS signal transduction pathway; (4) Activity level of the fMLP signal transduction pathway in neutrophils; (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells; (6) Activity level of the GM-CSF signal transduction pathway; (7) Activity level of the interferon α signal transduction pathway; (8) Activity level of the interferon-γ signal transduction pathway; (9) Activity level of the IL-1 signaling pathway; (10) The activity level of the Toll-like receptor signaling pathway; and (11) Quantitative levels related to the function of immune cells such as CD8+ T cells.

7. The method, JAK inhibitor, or use according to claim 6, wherein, The at least one immune-related feature includes at least one, two or more immune-related features selected from the group consisting of: (1) Activity level of the IL-2 signal transduction pathway; (2) Activity level of CD28 signal transduction pathway in T helper cells; (3) Activity level of the interferon α signal transduction pathway; (4) The activity level of the interferon-γ signaling pathway; and (5) Quantitative levels related to CD8+ T cell function.

8. The method, JAK inhibitor, or use according to claim 7, wherein, The at least one immune-related feature includes the five immune-related features of the group.

9. The method, JAK inhibitor, or use according to any one of claims 6 to 8, wherein, The quantification level related to CD8+ T cell function is based on the assessment of the expression level of at least one protein selected from the group consisting of: CD8A, GZMB, PRF1, Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

10. The method, JAK inhibitor, or use according to any one of claims 1 to 9, wherein, In step (b), the immune activity etiology score is calculated through the following steps: (i) Calculate the Z-score for each of the at least one immune-related feature; and (ii) Sum the Z-scores of each feature obtained in step (i).

11. The method, JAK inhibitor, or use according to claim 10, wherein, The Z-score is calculated based on the mean (μ) and standard deviation (σ) of the corresponding features obtained from an ALS patient cohort.

12. The method, JAK inhibitor, or use according to any one of claims 1 to 11, wherein, The preset threshold is a score cutoff value determined based on retrospective clinical data, capable of distinguishing between patient groups that respond to and do not respond to JAK inhibitor treatment.

13. The method, JAK inhibitor, or use according to any one of claims 1 to 12, wherein, The JAK inhibitor is tofacitinib, and preferably, the dosage of tofacitinib is about 10 mg per day.

14. The method, JAK inhibitor, or use according to any one of claims 1 to 13, wherein, It also includes administering to the subject a therapeutically effective amount of one or more agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets, wherein the agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets are selected from the group consisting of insulin, metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors, preferably insulin.

15. An in vitro method for identifying amyotrophic lateral sclerosis (ALS) subjects with highly immunologically active etiologies, the method comprising: (a) By analyzing biological samples obtained from candidate subjects, the quantitative level of at least one pre-defined immune-related feature is obtained; (b) Based on the quantification level of the at least one immune-related feature, an immune activity etiology score is calculated; as well as (c) If the immune activity etiology score is higher than a preset threshold, the candidate subject is identified as an ALS subject with a high immune activity etiology.

16. The method according to claim 15, wherein, The at least one immune-related feature is selected from the following group: (1) Activity level of the IL-2 signal transduction pathway; (2) Activity level of CD28 signal transduction pathway in T helper cells; (3) Activity level of the iNOS signal transduction pathway; (4) Activity level of the fMLP signal transduction pathway in neutrophils; (5) Activity level of the iCOS-iCOSL signaling pathway in T helper cells; (6) Activity level of the GM-CSF signal transduction pathway; (7) Activity level of the interferon α signal transduction pathway; (8) Activity level of the interferon-γ signal transduction pathway; (9) Activity level of the IL-1 signaling pathway; (10) The activity level of the Toll-like receptor signaling pathway; and (11) Quantitative levels related to the function of immune cells such as CD8+ T cells.

17. The method according to claim 16, wherein, The at least one immune-related feature includes at least one, two or more immune-related features selected from the group consisting of: (1) Activity level of the IL-2 signal transduction pathway; (2) Activity level of CD28 signal transduction pathway in T helper cells; (3) Activity level of the interferon α signal transduction pathway; (4) The activity level of the interferon-γ signaling pathway; and (5) Quantitative levels related to CD8+ T cell function.

18. The method according to claim 17, wherein, The at least one immune-related feature includes the five immune-related features of the group.

19. The method according to any one of claims 16 to 18, wherein, The quantification level related to CD8+ T cell function is based on the assessment of the expression level of at least one protein selected from the group consisting of: CD8A, GZMB, PRF1, Bcl-2, CTLA-4, CD25, CD28, CD38, CD69, CD137, LAG-3, PD-1, and TIM-3.

20. The method according to any one of claims 15 to 19, wherein, The immune activity etiology score is calculated through the following steps: (i) Calculate the Z-score for each of the at least one immune-related feature; and (ii) Sum the Z-scores of each feature obtained in step (i).

21. The method according to claim 20, wherein, The Z-score is calculated based on the mean (μ) and standard deviation (σ) of the corresponding features obtained from an ALS patient cohort.

22. The method according to any one of claims 15 to 21, wherein, The preset threshold is a score cutoff value determined based on retrospective clinical data, capable of distinguishing between patient groups that respond to and do not respond to JAK inhibitor treatment.

23. A kit for treating amyotrophic lateral sclerosis (ALS), the kit comprising: (a) One or more Janus kinase (JAK) inhibitors; as well as (b) Instructions for use, which contain instructions for administering the JAK inhibitor to ALS subjects identified by the method according to any one of claims 15 to 22 as having a highly immunologically active etiology.

24. A computer-implemented method for generating personalized treatment recommendations for subjects with amyotrophic lateral sclerosis (ALS), the method comprising: (a) On one or more hardware processors, data representing the analysis of the subject's biological sample is received, the data including the quantification level of at least one preset immune-related feature; (b) Execute instructions stored in a non-transitory memory to calculate the subject's immune activity etiology score using the method according to any one of claims 15 to 22; as well as (c) Based on the immune activity etiology score, generate a report containing recommendations for administering a Janus kinase (JAK) inhibitor to the subject.

25. A method for monitoring the therapeutic effect of a Janus kinase (JAK) inhibitor in ALS subjects identified by the method according to any one of claims 15 to 22 as having a highly immunologically active etiology, the method comprising: (a) During the course of treatment with the JAK inhibitor administered to the subject, the level of neurofilament light chains (NfL) in the subject's biological samples was measured multiple times; as well as (b) Associate the reduction in NfL level with positive treatment effects, wherein the positive treatment effects include at least one of slowing disease progression, stabilization or improvement of ALS Functional Rating Scale-Revised (ALSFRS-R) score, or improvement of forced vital capacity (FVC).

26. A method of treating a subject with amyotrophic lateral sclerosis (ALS) in need, comprising administering to the subject a therapeutically effective amount of one or more inhibitors or antagonists of immune-related pathways and / or targets, said inhibitors or antagonists of immune-related pathways and / or targets selected from the group consisting of: IL-2, IL-2 receptor, and IL-2 signaling pathway antagonists CD28 antagonists, antagonists that block the CD28 signaling pathway in T helper cells. Antagonists that block the iNOS signal transduction pathway Antagonists that block the fMLP signaling pathway in neutrophils Antagonists that block the iCOS-iCOSL signaling pathway in T helper cells GM-CSF antagonists, antagonists that block the GM-CSF signal transduction pathway, Antagonists of type I IFN interferon-alpha, antagonists that block the interferon-alpha signal transduction pathway Antagonists of interferon-gamma, antagonists that block the interferon-gamma signal transduction pathway, IL-1α and IL-1β antagonists, and antagonists that block the IL-1 signaling pathway. Antagonists that block the Toll-like receptor signaling pathway, and JAK inhibitors include tofacitinib, baricitinib, upadacitinib, and filgotinib.

27. The method according to claim 26, wherein, It also includes administering to the subject a therapeutically effective amount of one or more agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets, wherein the agonists, inhibitors, or antagonists of metabolic-related pathways and / or targets are selected from the group consisting of insulin, metformin, sulfonylureas, DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors, preferably insulin.

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