Application of fos as biomarker of neuroimmunological disease and its inhibitor in preparation of medicine for improving neuroimmunological disease

Abstract

The application discloses a kind of FOS as neuroimmunological disease biomarker and its inhibitor in preparation improve neuroimmunological disease drug application.The neuroimmunological disease biomarker of the present application is FOS, FOS is significantly high in the peripheral blood immune cells of neuroimmunological disease patient, and ROC curve shows that it has good distinguishing ability to patient and healthy population, FOS can be used as auxiliary detection or evaluation neuroimmunological disease biomarker.And the FOS inhibitor of the present application has the application potential as the drug candidate for improving neuroimmunological related inflammatory reaction, can be used as the new drug candidate for improving neuroinflammation, provides new choice for traditional treatment resistance or recurrence patient.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, specifically to the application of FOS as a biomarker for neuroimmune diseases and its inhibitors in the preparation of drugs to improve neuroimmune diseases. Background Technology

[0002] Neuroimmune diseases are a class of inflammatory diseases of the central nervous system mediated by immune abnormalities. They are usually accompanied by abnormal activation of immune cells, imbalance in the release of inflammatory mediators, and damage to nerve tissue, leading to a variety of neurological symptoms such as visual impairment, motor dysfunction, sensory abnormalities, and cognitive impairment. Major neuroimmune diseases include autoimmune encephalitis (AE), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), Guillain-Barré syndrome (GBS), inflammatory myopathy (IM), myasthenia gravis (MG), oligodendrocyte glycoprotein antibody-associated disease (MOGAD), multiple sclerosis (MS), and neuromyelitis optica spectrum disorders (NMOSD). These diseases are typically characterized by prolonged course, frequent relapses, and a high risk of disability, and their development is closely related to persistent neuroinflammation. Therefore, screening for key molecules that reflect disease activity and participate in the regulation of neuroinflammation is of great significance for the status assessment and intervention treatment of neuroimmune diseases.

[0003] Currently, clinical treatment for neuroimmunological diseases mainly includes acute-phase anti-inflammatory interventions, immunomodulation, and disease-correcting therapy during remission. Treatment primarily involves acute-phase glucocorticoid pulse therapy and plasma exchange, as well as remission-phase immunosuppression, immunomodulation, and targeted biologics. In recent years, precision therapies targeting B cells or the complement system have significantly improved the prognosis of some patients; however, a considerable proportion of patients still experience persistent disease activity, prolonged neuroinflammation, and even relapse. Especially after receiving potent immunomodulatory interventions, some patients may still experience disease reactivation, suggesting that key molecular mechanisms promoting persistent or amplified neuroinflammation in neuroimmunological diseases remain not fully elucidated.

[0004] Neuroinflammation is a crucial pathological basis in the development of neuroimmunological diseases. This process involves the activation, proliferation, migration, and interaction of various immune cells, including T cells, B cells, plasma cells, NK cells, and myeloid cells, accompanied by the abnormal release of various inflammatory factors, chemokines, and effector molecules. Sustained or amplified neuroinflammatory responses not only participate in the acute injury process but are also closely related to the risk of disease recurrence, the degree of tissue damage, and clinical prognosis. Therefore, screening key molecules that can reflect the activity status of neuroimmunological diseases and participate in the regulation of neuroinflammation, and developing novel biomarkers and drug targets for disease activity assessment and intervention, has significant scientific and clinical value.

[0005] FOS is an important member of the immediate early response genes. Its encoded protein can form the activator protein-1 (AP-1) transcription factor complex, participating in the regulation of the transcriptional expression of various immune responses and inflammation-related genes. FOS / JUN expression can be induced by various factors such as antigen stimulation, cytokines, oxidative stress, hypoxia, tissue damage, and the inflammatory microenvironment, and further participates in regulating biological processes such as immune cell activation, inflammatory factor release, chemokine expression, cell migration, and stress responses. It serves as a crucial node in the conversion of inflammatory signals into intranuclear transcriptional responses. Existing research indicates that the FOS-related AP-1 transcriptional program is closely related to various inflammatory diseases, immune abnormalities, and tissue damage processes, and can interact with inflammatory signaling pathways such as NF-κB, MAPK, and JAK / STAT, jointly participating in the initiation, persistence, and amplification of inflammatory responses. However, the expression characteristics of FOS in neuroimmunological diseases, its relationship with disease activity, the degree of neuroinflammation, and abnormal immune cell activation, and whether combined FOS detection can serve as a biomarker for assessing the activity status of neuroimmunological diseases, still lack systematic research and clear applications.

[0006] Therefore, clarifying the expression changes of FOS in neuroimmune diseases and its relationship with neuroinflammation-related pathological processes is of great significance for developing combined biomarkers to assess the activity status of neuroimmune diseases and for developing novel intervention strategies that target FOS to improve neuroinflammation. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide an application of FOS as a biomarker of neuroimmune diseases and its inhibitors in the preparation of drugs to improve neuroimmune diseases.

[0008] To achieve the above objectives, the technical solution designed by the present invention is as follows: This invention provides the application of a reagent for detecting the FOS gene in the preparation of reagents for diagnosing neuroimmunological diseases, wherein the neuroimmunological diseases are any one of autoimmune encephalitis, neuromyelitis optica spectrum disorders, myelin oligodendrocyte glycoprotein antibody-associated diseases, multiple sclerosis, chronic inflammatory demyelinating polyradiculoneuropathy, Guillain-Barré syndrome, inflammatory myopathy, and myasthenia gravis. The NCBI accession number for FOS in this invention is 2353.

[0009] The beneficial effects of this invention are: This invention reveals the key regulatory roles of FOS and JUN in neuroimmune diseases and their multiple applications, with the following significant beneficial effects: 1. Providing novel disease biomarkers. This invention, through single-cell transcriptome sequencing and independent cohort validation, confirms that FOS and JUN are significantly highly expressed in peripheral blood immune cells of patients with eight neuroimmune diseases, including autoimmune encephalitis, neuromyelitis optica spectrum disorders, and multiple sclerosis. ROC curves show that they have good discriminatory power between patients and healthy individuals (AUC up to 1.000). As detectable molecules in peripheral blood, FOS and JUN are convenient to obtain and non-invasive, overcoming the limitations of cerebrospinal fluid or imaging biomarkers, and providing a simple and stable new tool for the auxiliary diagnosis and population screening of neuroimmune diseases.

[0010] 2. Assisting in the assessment of disease activity. This invention found that the expression levels of FOS and JUN are correlated with the activity status of neuroimmunological diseases. In various diseases such as NMOSD and MS, the overall expression of FOS and JUN in patients during the active phase is higher than that in patients during the remission phase, which is further supported by independent validation cohorts. This biomarker helps to reflect the degree of inflammatory activity in the disease, providing a reference for clinical differentiation between the resting phase and the relapse phase, guiding individualized treatment decisions, and prognostic assessment.

[0011] 3. Objective quantification of neuroinflammation levels. This invention establishes a positive correlation between FOS and JUN expression and neuroinflammation characteristic scores, specifically in B cells and CD4+. + T, CD8 + Significant positive correlations were observed in T cells, monocyte / macrophage ratios, and NK cells. FOS and JUN directly reflect neuroinflammatory burden, providing quantitative evidence for assessing anti-inflammatory efficacy and disease progression.

[0012] 4. Providing novel therapeutic targets. This invention validates the therapeutic potential of FOS and JUN inhibitors in neuroimmunological diseases. In vitro functional experiments show that silencing FOS or JUN can significantly reduce the expression of neuroinflammatory factors such as IL-1β, IL-6, TNFα, SPP1, and NLRP3, while downregulating the activity of chemokines such as CCR1, CXCL9, and CCL2, as well as inflammatory signaling pathways such as TLR4, MAPK14, and NF-κB, inhibiting abnormal activation of immune cells and amplification of inflammation from multiple dimensions. FOS and JUN inhibitors can serve as novel drug candidates for improving neuroinflammation, providing new options for patients resistant to or relapsed by traditional treatments.

[0013] In summary, this invention constructs a complete technology chain from diagnosis and assessment to targeted intervention, possessing both basic scientific value and clinical translational potential. Attached Figure Description

[0014] Figure 1 Box plot to identify differences in FOS expression in peripheral blood immune cells of patients with different neuroimmune diseases and healthy controls in the cohort; Figure 2Box plot to identify differences in JUN expression in peripheral blood immune cells of patients with different neuroimmune diseases and healthy controls in the cohort; Figure 3 To discover ROC curves that differentiate patients with different neuroimmune diseases from healthy controls based on FOS expression levels in the cohort; Figure 4 To discover the ROC curves that differentiate patients with different neuroimmune diseases from healthy controls based on JUN expression levels in the cohort; Figure 5 Box plots were used to identify differences in FOS expression between patients in remission and active phases of different neuroimmunological diseases in the cohort. Figure 6 Box plots were used to identify differences in JUN expression between patients in remission and active phases of different neuroimmunological diseases in the cohort. Figure 7 To discover ROC curves that differentiate patients in remission and active phases of different neuroimmune diseases based on FOS expression levels in the cohort; Figure 8 To discover ROC curves in the cohort that differentiate patients in remission and active phases of different neuroimmunological diseases based on JUN expression levels; Figure 9 To discover the correlation between FOS expression levels and neuroinflammatory feature scores in different major immune cell populations in the cohort; In the diagram, A represents all cells, B represents B cells and plasma cells, and C represents CD4+ cells. + T cells, D is CD8 + T cells, E cells are myeloid cells, and F cells are NK cells; Figure 10 To discover the correlation between JUN expression levels and neuroinflammatory feature scores in different major immune cell populations in the cohort; In the diagram, A represents all cells, B represents B cells and plasma cells, and C represents CD4+ cells. + T cells, D is CD8 + T cells, E cells are myeloid cells, and F cells are NK cells; Figure 11 Box plot to verify the differential expression of FOS in peripheral blood immune cells of patients with different neuroimmune diseases and healthy controls in the cohort; Figure 12 Box plots were used to verify the differential expression of JUN in peripheral blood immune cells of patients with different neuroimmunological diseases and healthy controls in the cohort. Figure 13 To validate the ROC curves in the cohort that distinguished patients with different neuroimmune diseases from healthy controls based on FOS expression levels; Figure 14To validate the ROC curves in the cohort that differentiated patients with different neuroimmune diseases from healthy controls based on JUN expression levels; Figure 15 To verify the difference in FOS expression between patients in remission and active phases of different neuroimmunological diseases in the cohort; Figure 16 To validate the differential expression of JUN in patients with different neuroimmunological diseases during remission and active phases in the cohort; Figure 17 To validate the ROC curves in the cohort that differentiate between patients in remission and active phases of different neuroimmunological diseases based on FOS expression levels; Figure 18 To validate the ROC curves in the cohort that differentiate between patients in remission and active phases of different neuroimmunological diseases based on JUN expression levels; Figure 19 To validate the correlation between FOS expression levels and neuroinflammatory feature scores in different major immune cell populations in the cohort; In the diagram, A represents all cells, B represents B cells and plasma cells, and C represents CD4+ cells. + T cells, D is CD8 + T cells, E cells are myeloid cells, and F cells are NK cells; Figure 20 To validate the correlation between JUN expression levels and neuroinflammatory feature scores in different major immune cell populations in the cohort; In the diagram, A represents all cells, B represents B cells and plasma cells, and C represents CD4+ cells. + T cells, D is CD8 + T cells, E cells are myeloid cells, and F cells are NK cells; Figure 21 Figure showing the results of inhibiting FOS / JUN to reduce neuroimmune-related neuroinflammation; In the diagram, A represents B cells, B represents NK cells, and C represents CD8 cells. + T cells, D is CD4 + T cells, E cells are monocytes; Figure 22 The result of inhibiting FOS / JUN to reduce neuroimmune-related immune chemotaxis; In the diagram, A represents B cells, B represents NK cells, C represents monocytes, and D represents CD8 cells. + T cells, E is CD4 + T cells; Figure 23 The result of inhibiting FOS / JUN to reduce the activation of neuroimmune-related inflammatory signaling pathways is shown in the figure. In the diagram, A represents B cells, B represents NK cells, C represents monocytes, and D represents CD8 cells. +T cells, E is CD4 + T cells. Detailed Implementation

[0015] The present invention will now be described in further detail with reference to specific embodiments, so that those skilled in the art can understand it.

[0016] Example 1: High expression of FOS and JUN in neuroimmunological diseases and their analysis as disease biomarkers 1. Collect peripheral blood samples from patients with neuroimmune diseases and healthy controls.

[0017] Among them, 31 healthy control subjects (HC) served as normal control subjects; patients with neuroimmune diseases included 16 subjects with autoimmune encephalitis (AE), 73 subjects with neuromyelitis optica spectrum disorder (NMO / NMOSD), 16 subjects with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), 51 subjects with multiple sclerosis (MS), 10 subjects with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), 3 subjects with Guillain-Barré syndrome (GBS), 10 subjects with inflammatory myopathy (IM), and 10 subjects with myasthenia gravis (MG).

[0018] 2. Sample collection and preparation, and single-cell RNA sequencing: (1) Peripheral blood samples were collected from patients with neuroimmune diseases and from healthy controls using sterile blood collection tubes.

[0019] (2) Isolation of peripheral blood mononuclear cells (PBMCs): Using Ficoll-Paque PLUS separation solution (Cytiva), density gradient centrifugation was performed strictly according to the experimental protocol provided by the manufacturer to obtain single-cell suspensions.

[0020] (3) Load the single-cell suspension onto the 10 X Genomics Chromium platform for analysis. Use CellRanger to demultiplex and align the raw RNA data.

[0021] (4) Cell Ranger software was used to demultiplex, compare and quantify the raw sequencing data to generate a gene-cell expression matrix.

[0022] (5) The Seurat v4.2.0 software package was used to perform quality control, normalization, dimensionality reduction, clustering, and cell type annotation on the data to obtain information on the main immune cell populations and gene expression in peripheral blood. Transcriptome expression data were extracted from each group of samples to obtain the expression levels of FOS and JUN. The expression levels of FOS and JUN in the neuroimmunological disease group and the healthy control group were compared and analyzed.

[0023] The results are as follows Figure 1 and Figure 2 As shown in the figure, FOS and JUN were significantly elevated in peripheral blood immune cells of patients with various neuroimmunological diseases compared with healthy controls.

[0024] For FOS, the FOS expression level was significantly higher in the AE group than in the HC group (p=4.0×10^-6); significantly higher in the NMO group (p=6.5×10^-10); significantly higher in the MOGAD group (p=1.7×10^-7); significantly higher in the MS group (p=1.4×10^-6); significantly higher in the CIDP group (p=9.1×10^-7); significantly higher in the GBS group (p=0.0013); significantly higher in the IM group (p=9.1×10^-6); and significantly higher in the MG group (p=5.2×10^-7).

[0025] For JUN, the JUN expression level was significantly higher in the AE group than in the HC group (p=3.5×10^-6); significantly higher in the NMO group (p=8.4×10^-6); significantly higher in the MOGAD group (p=0.00018); significantly higher in the MS group (p=1.9×10^-6); significantly higher in the CIDP group (p=0.00042); significantly higher in the GBS group (p=1.7×10^-10); significantly higher in the IM group (p=2.0×10^-6); and significantly higher in the MG group (p=2.7×10^-8).

[0026] 3. Further analysis was conducted using receiver operating characteristic (ROC) curves to examine the ability of FOS and JUN expression levels to differentiate between patients with different neuroimmunological diseases and healthy controls.

[0027] The results are as follows Figure 3 and Figure 4 As shown, ROC curves constructed based on FOS or JUN expression levels have a good ability to distinguish between patients with various neuroimmunological diseases and healthy controls.

[0028] For FOS, the AUC was 0.877 for the AE group, 0.923 for the CIDP group, 1.000 for the GBS group, 0.942 for the IM group, 0.974 for the MG group, 0.931 for the MOGAD group, 0.851 for the MS group, and 0.871 for the NMO group.

[0029] For JUN, the AUC was 0.889 for the AE group, 0.884 for the CIDP group, 0.968 for the GBS group, 0.906 for the IM group, 0.942 for the MG group, 0.861 for the MOGAD group, 0.795 for the MS group, and 0.757 for the NMO group.

[0030] The above results indicate that FOS and JUN were significantly elevated in patients with various neuroimmune diseases compared to the control group, suggesting that FOS and JUN can serve as biomarkers related to neuroimmune diseases, helping to distinguish patients with neuroimmune diseases from those without, and thus have application value as disease biomarkers.

[0031] Example 2: Analytical Study on the Correlation between FOS and JUN with Neuroimmune Disease Activity and Their Role as Biomarkers of Disease Activity Status 1. Peripheral blood samples were collected from patients with neuroimmunological diseases who had clear disease activity status information in Example 1, and the patients were divided into a remission group and an active group according to clinical stratification.

[0032] (1) The active period includes the disease activity state such as the initial diagnosis period, relapse period, crisis period or progression period. The specific determination is based on the clinical characteristics of different diseases, changes in clinical symptoms, laboratory test results, imaging test results and clinical diagnosis and treatment records. The remission period is the stage where clinical symptoms are relatively stable and there is no obvious new or aggravated inflammatory activity.

[0033] (2) Since most neuroimmune diseases are rare or have low incidence rates, after further dividing different diseases into remission and active phases, the sample size of some disease groups is too small to meet the requirements of stable statistical analysis. Therefore, this embodiment selects representative neuroimmune diseases with relatively sufficient sample size and clear activity stratification information for analysis, including neuromyelitis optica spectrum disorders (NMO / NMOSD), multiple sclerosis (MS), and myasthenia gravis (MG).

[0034] Among them, there were 29 subjects in remission and 44 subjects in active phase of neuromyelitis optica spectrum disease (NMO / NMOSD); 19 subjects in remission and 32 subjects in active phase of multiple sclerosis (MS); and 2 subjects in remission and 8 subjects in active phase of myasthenia gravis (MG).

[0035] 2. Transcriptome expression data were extracted from each group of samples to obtain the expression levels of FOS and JUN. The differences in FOS and JUN expression between the remission and active disease groups were compared. Using the remission and active disease groups as classification subjects and FOS and JUN expression levels as discriminant indicators, receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) was calculated to assess the ability of FOS and JUN to distinguish disease activity states and evaluate their application value as biomarkers of disease activity states.

[0036] The results are as follows Figure 5 and Figure 6 As shown, in patients with neuroimmunological diseases with clear disease activity stratification information, the expression of FOS and JUN in peripheral blood immune cells of patients in the active phase was generally higher than that of patients in the remission phase.

[0037] The above results indicate that FOS and JUN expression levels are associated with the activity status of some neuroimmune diseases. Specifically, in NMO patients, FOS and JUN expression levels were significantly higher in patients in the active phase than in those in remission; a certain upward trend in expression was also observed in MS and MG patients. These results suggest that FOS and JUN can serve as biomarkers reflecting the activity status of neuroimmune diseases, and can be used to assist in assessing disease activity, the degree of inflammation, and the patient's condition, thus possessing application value as biomarkers of disease activity.

[0038] Figure 7 and Figure 8 Further analysis showed that ROC curves constructed based on FOS and JUN expression levels had good discriminatory power between patients in the active and remission phases of various neuroimmunological diseases. Specifically, for FOS, the AUC was 0.625 in the MG group, 0.434 in the MS group, and 0.649 in the NMO group. For JUN, the AUC was 0.938 in the MG group, 0.408 in the MS group, and 0.629 in the NMO group. JUN showed high discriminatory power between the active and remission phases of MG patients; FOS and JUN also showed some discriminatory power in the activity status of NMO patients.

[0039] The above results indicate that in neuroimmunological diseases with clear activity stratification information, the expression levels of FOS and JUN are closely related to the disease activity status. Patients in the active phase showed higher FOS and JUN expression than those in the remission phase, and the expression levels were able to distinguish between the active and remission phases well. This suggests that FOS and JUN can serve as biomarkers reflecting the activity status of neuroimmunological diseases and can be used to assist in assessing disease activity and the degree of inflammation, thus having application value as biomarkers of disease activity status.

[0040] Example 3: Correlation between FOS and JUN and neuroinflammatory characteristics of neuroimmunological diseases and their analysis as biomarkers of neuroinflammatory states 1. Based on a pre-defined set of neuroinflammation-related genes, weighted pathway characteristic scores were calculated for each sample in Example 1 across different major immune cell populations. This index is a pathway score calculated based on a publicly available pre-defined set of neuroinflammation-related genes (WPNEUROINFLAMMATION AND GLUTAMATERGIC SIGNALING), used to reflect the neuroinflammation-related molecular characteristics in the samples.

[0041] (1) The set of genes related to neuroinflammation includes ADCY1, ADCY3, ADCY8, AKT1, ARC, BCL2, BDNF, CALM1, CALM2, CAMK2A, CAMK2B, CAMK2D, CAMK2G, CAMK4, CAMKK1, CAMKK2, CFL1, CNTF, CREB1, DAO, DISC1, DLAT, DLD, FGF2, FOS, GFAP, GLS, GLS2, GLUL, GOT1, GRIA1, GRIA2, GRIA3, GRIA4, GRIK1, GRIK2, GRIK3, GRIK4, GRIK5, GRIN1, GRIN2A, GRIN2B, GRIN2C, GRIN2D, GRIN3A, GRIN3B, GRM1, GRM2, GRM4, GRM5, GRM7, GRM8, IFNG, IFNGR1, IFNGR2, IG F1, IL10, IL10RA, IL10RB, IL12A, IL12B, IL13, IL13RA1, IL1A, IL1B, IL1R1, IL1R2, IL4, IL4R, IL6, IL6R, IL6ST, INSR, IRS1, JAK1, LIF , LRRC8A, LRRC8B, LRRC8C, LRRC8D, LRRC8E, LTA, MAPK1, MAPK3, MIR6778, MIR7114, MIR7846, NFKB1, NFKB2, NGF, NOS1, NSMF, PDHA1, PHG DH, PLCB1, PLCB2, PLCB3, PLCB4, PPP1CA, PPP1CB, PPP1CC, PRKACA, PRKCA, PRKCB, PRKCG, PSAT1, PSPH, SHMT1, SHMT2, SLC17A6, SLC17A7 , SLC1A1, SLC1A2, SLC1A3, SLC1A4, SLC1A6, SLC2A1, SLC2A3, SLC38A1, SLC38A2, SLC38A3, SLC38A5, SLC6A9, SLC7A10, SMAD2, SMAD3, SM AD4, SMAD7, SOCS3, SRR, STAT1, STAT3, STAT6, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, TNF, TNFRSF1A, TNFRSF1B, TRAF5 and TRPM4.

[0042] (2) Major immune cell populations include all cells (all immune cells, AllCells), B cells / plasma cells, CD4+, and CD4+. + T cells, CD8 +T cells, myeloid cells, and NK cells.

[0043] 2. For each subject sample and each major immune cell population, the standardized expression matrix of the aforementioned neuroinflammation-related genes was first extracted from that cell population. Then, the expression value of each gene was standardized to obtain a standardized expression value. Next, a weighted average was calculated based on the average expression level, differential expression intensity, or preset weight of the neuroinflammation-related genes in that cell population to obtain the neuroinflammation characteristic score of the sample in the corresponding cell population. Pearson correlation analysis was used to assess the correlation between the expression levels of FOS and JUN in each cell population and the neuroinflammation characteristic score, and a scatter plot was generated for visualization.

[0044] The results are as follows Figure 9 and Figure 10 As shown, in various neuroimmunological diseases and healthy control samples, the expression levels of FOS and JUN were positively correlated with the overall neuroinflammatory characteristic scores.

[0045] For FOS, such as Figure 9 As shown, in all cells, FOS expression level was significantly positively correlated with neuroinflammatory feature scores (Pearson r = 0.588, p = 7.65 × 10⁻²²); in B cells and plasma cells, Pearson r = 0.610, p = 5.30 × 10⁻²⁰; and in CD4⁻¹… + In T cells, Pearson r = 0.488, p = 1.15 × 10^-12; in CD8 + In T cells, Pearson r = 0.578, p = 3.64 × 10⁻¹⁸; in myeloid cells, Pearson r = 0.457, p = 4.33 × 10⁻¹¹; and in NK cells, Pearson r = 0.670, p = 8.10 × 10⁻²⁶. These results indicate that elevated FOS expression levels are associated with higher levels of neuroinflammation-related molecular signatures in different immune cell populations.

[0046] For JUN, such as Figure 10 As shown, JUN expression levels were significantly positively correlated with neuroinflammatory feature scores in all immune cells (Pearson r = 0.455, p = 1.21 × 10⁻¹²); in B cells and plasma cells, Pearson r = 0.413, p = 6.34 × 10⁻⁹; and in CD4⁻¹ cells... + In T cells, Pearson r = 0.361, p = 3.51 × 10^-7; in CD8 +In T cells, Pearson r = 0.431, p = 6.43 × 10⁻¹⁰; in myeloid cells, Pearson r = 0.503, p = 1.91 × 10⁻¹³; and in NK cells, Pearson r = 0.579, p = 3.40 × 10⁻¹⁸. These results indicate that elevated JUN expression levels are also associated with higher levels of neuroinflammation-related molecular signatures in different immune cell populations.

[0047] In summary, the expression levels of FOS and JUN showed a consistent positive correlation with the neuroinflammatory characteristic scores of various major immune cell populations in the peripheral blood of patients with neuroimmunological diseases. This correlation was not only present in all immune cells but also widely observed in B cells, plasma cells, and CD4+ cells. + T cells, CD8 + T cells, myeloid cells, and NK cells. These results suggest that FOS and JUN expression levels can reflect the inflammatory molecular characteristics of immune cells associated with neuroimmunological diseases, supporting FOS and JUN as candidate biomarkers for auxiliary assessment of neuroinflammatory status in neuroimmunological diseases.

[0048] Example 4: Validation of FOS and JUN as biomarkers for neuroimmunological diseases in a validation cohort To further verify the elevated expression levels of FOS and JUN in patients with neuroimmunological diseases and their stability and reproducibility as disease biomarkers, this embodiment constructs a validation cohort independent of the discovery cohort (Example 1) to validate the differences in the expression of FOS and JUN in peripheral blood immune cells of different patients with neuroimmunological diseases and healthy controls.

[0049] 1. Collect peripheral blood samples from patients with neuroimmune diseases and healthy controls, independent of the discovery cohort (Example 1).

[0050] Among them, there were 48 healthy control (HC) subjects; and patients with neuroimmune diseases including 27 subjects with autoimmune encephalitis (AE), 113 subjects with neuromyelitis optica spectrum disorder (NMO / NMOSD), 27 subjects with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), 79 subjects with multiple sclerosis (MS), 17 subjects with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), 8 subjects with Guillain-Barré syndrome (GBS), 16 subjects with inflammatory myopathy (IM), and 17 subjects with myasthenia gravis (MG).

[0051] 2. Peripheral blood samples were processed, peripheral blood mononuclear cells were isolated, single-cell transcriptome sequencing and data analysis were performed using the same method as in Example 1 to obtain the expression levels of FOS and JUN in all immune cells of peripheral blood in each sample.

[0052] 3. Further compare and validate the differences in FOS and JUN expression between patients with different neuroimmunological diseases and healthy controls in the cohort to assess the robustness of FOS and JUN as biomarkers for neuroimmunological diseases.

[0053] The results are as follows Figure 11 and Figure 12 As shown, in the independent validation cohort, FOS and JUN showed a significant upward trend in peripheral blood immune cells of patients with neuroimmune diseases compared with the healthy control group, further validating the finding that FOS and JUN were highly expressed in neuroimmune diseases in the cohort.

[0054] For FOS, the expression level of FOS in AE patients was significantly higher than that in healthy controls (p=0.00058), NMO patients (p=1.3×10^-8), MOGAD patients (p=1.2×10^-15), MS patients (p=8.3×10^-8), CIDP patients (p=3.8×10^-5), GBS patients (p=0.048), IM patients (p=0.0019), and MG patients (p=2.4×10^-8).

[0055] For JUN, the JUN expression level was higher in AE patients than in healthy controls (p=0.00059), NMO patients than in healthy controls (p=0.00012), MOGAD patients than in healthy controls (p=2.5×10^-7), MS patients than in healthy controls (p=0.00014), CIDP patients than in healthy controls (p=0.0021), GBS patients than in healthy controls (p=0.028), IM patients than in healthy controls (p=5.8×10^-5), and MG patients than in healthy controls (p=6.3×10^-5).

[0056] 4. Further, receiver operating characteristic (ROC) curve analysis was used to verify the ability of FOS and JUN expression levels in the cohort to distinguish between patients with different neuroimmunological diseases and healthy controls.

[0057] The results are as follows Figure 13 and Figure 14As shown, in the independent validation cohort, the ROC curves constructed based on FOS and JUN expression levels have a certain degree of ability to distinguish between patients with various neuroimmunological diseases and healthy controls.

[0058] The above results demonstrate that, in an independent validation cohort, FOS and JUN were not only elevated in patients with various neuroimmunological diseases compared to healthy controls, but also effectively distinguished between patients and healthy controls across different disease types. These results further validate the stability and application value of FOS and JUN as biomarkers related to neuroimmunological diseases.

[0059] In independent validation cohorts, FOS and JUN demonstrated stable discriminatory ability between patients with various neuroimmunological diseases and healthy controls, indicating that FOS and JUN have good reproducibility and consistency across different cohorts. This further supports their potential as biomarkers for neuroimmunological diseases, used to help distinguish between patients with neuroimmunological diseases and healthy controls.

[0060] Example 5: Validation of FOS and JUN as biomarkers of neuroimmune disease activity in a validation cohort To further verify the results of Example 2 regarding the correlation between FOS and JUN and the active state of neuroimmune diseases, this example analyzes the expression differences of FOS and JUN in peripheral blood immune cells of patients in different disease remission and active phases in the independent validation cohort of Example 4, and further evaluates their ability to distinguish disease activity states.

[0061] 1. Collect peripheral blood samples from patients with neuroimmunological diseases who have clear disease activity status information in the validation cohort of Example 4, and divide the patients into remission group and active group according to clinical stratification.

[0062] Among them, 45 subjects were in remission for neuromyelitis optica spectrum disease (NMO / NMOSD) and 68 subjects were in active phase; 29 subjects were in remission for multiple sclerosis (MS) and 50 subjects were in active phase; and 3 subjects were in remission for myasthenia gravis (MG) and 14 subjects were in active phase.

[0063] 2. The expression levels of FOS and JUN in each group of samples were detected using the same method as in the discovery cohort. The expression differences between the remission group and the active group in different diseases were compared, and ROC curves were constructed to evaluate the ability of FOS and JUN to distinguish the disease activity status.

[0064] The results are as follows Figure 15 and Figure 16As shown, in the independent validation cohort, FOS and JUN were generally higher in the active phase than in the remission phase in patients with various neuroimmunological diseases with clear disease activity status stratification information, further validating the finding that FOS and JUN are associated with disease activity status in the cohort.

[0065] For FOS, such as Figure 15 As shown, the FOS expression level in patients with active NMO was significantly higher than that in patients in remission (p=0.0064); the FOS expression level in patients with active MS was significantly higher than that in patients in remission (p=0.0179); the FOS expression level increased between patients with active MG and those in remission, but the difference was not statistically significant (p=0.3806).

[0066] For JUN, such as Figure 16 As shown, JUN expression levels were significantly higher in patients with active NMO than in those in remission (p=0.016); JUN expression levels were significantly higher in patients with active MG than in those in remission (p=0.046); JUN expression levels were elevated between patients with active MS and those in remission, but the difference was not statistically significant (p=0.402).

[0067] The above results indicate that, in independent validation cohorts, FOS and JUN expression levels are associated with the activity status of some neuroimmune diseases. Specifically, in NMO patients, FOS and JUN expression levels were significantly higher during the active phase than during the remission phase; in MS patients, FOS expression was mainly elevated; and in MG patients, JUN expression was mainly elevated. These results further support the potential of FOS and JUN as candidate biomarkers for auxiliary reflection of the activity status of neuroimmune diseases.

[0068] Further ROC analysis results are as follows Figure 17 and Figure 18 As shown, ROC curves constructed based on FOS or JUN expression levels have a certain ability to distinguish between patients in the active and remission phases of various neuroimmunological diseases.

[0069] For FOS, the AUC was 0.714 for the MG group, 0.610 for the MS group, and 0.614 for the NMO group.

[0070] For JUN, the AUC was 0.905 for the MG group, 0.457 for the MS group, and 0.626 for the NMO group.

[0071] The above results indicate that, in independent validation cohorts, FOS and JUN consistently showed higher activity levels than remission levels in various neuroimmune diseases with clearly defined activity status stratification. This suggests that FOS and JUN have good stability and reproducibility across different cohorts, further supporting their potential as candidate biomarkers for the activity status of neuroimmune diseases, used to assist in assessing disease activity and inflammatory activity.

[0072] Example 6: Validation of FOS and JUN as biomarkers of neuroinflammatory states in neuroimmunological diseases in a validation cohort Using the validation cohort from Example 4, the expression levels of FOS and JUN in different major immune cell populations were obtained (same as in Example 3), and neuroinflammatory feature scores were calculated based on the neuroinflammatory-related gene set. Correlation analysis was further used to assess the relationship between FOS and JUN expression levels in each cell population and the neuroinflammatory feature scores.

[0073] like Figure 19 As shown, in the independent validation cohort, FOS expression levels were positively correlated with neuroinflammatory feature scores, and this correlation was observed in all cells, B cells, plasma cells, and CD4+ cells. + T cells, CD8 + FOS expression was observed in T cells, myeloid cells, and NK cells. These results are generally consistent with the findings of the cohort in Example 3, indicating that elevated FOS expression is associated with higher levels of neuroinflammation-related molecular signatures across multiple major immune cell populations.

[0074] like Figure 20 As shown, in the independent validation cohort, JUN expression levels were also positively correlated with neuroinflammatory feature scores, and this correlation was observed in all cells, B cells, plasma cells, and CD4+ cells. + T cells, CD8 + T cells, myeloid cells, and NK cells showed a consistent correlation trend.

[0075] The above results further validate the association between JUN expression levels and neuroinflammation-related molecular features in the cohort, and further validate the application value of FOS and JUN as biomarkers of neuroinflammation status in neuroimmunological diseases.

[0076] Example 7: An analytical experiment to reduce neuroimmune-related neuroinflammation by inhibiting FOS and JUN. To directly verify the functions of FOS and JUN in regulating neuroinflammation in a disease-related context, this embodiment uses immune cells derived from patients with neuroimmunological diseases for in vitro functional studies.

[0077] 1. Peripheral venous blood samples were collected from patients with neuroimmunological diseases, and peripheral blood mononuclear cells (PBMCs) were isolated using Ficoll density gradient centrifugation. After isolation, the cells were washed twice with PBS, resuspended in a suitable culture medium, and counted to determine cell viability.

[0078] 2. PBMCs were sequentially sorted using immunomagnetic bead sorting to obtain monocytes, NK cells, and CD4+ cells, respectively. + T cells, CD8 + T cells and B cells. The sorting reagent was a Stemcell magnetic bead sorting kit.

[0079] Specifically, according to the instructions, the obtained PBMCs were mixed with the corresponding cell marker cocktail and incubated for 3-5 minutes, then mixed with magnetic beads and incubated for 3-5 minutes. After obtaining the target cells using magnetic sorting, the remaining cells were washed and sorted again. The sorted immune cells were then seeded into culture plates and cultured in vitro with the appropriate culture medium to maintain their activated and expanded state. The culture conditions were 37°C in a 5% CO2 incubator.

[0080] 3. Divide the isolated immune cells into three groups and process them separately: (1) Negative control group (NC group); negative small interfering RNA was used for treatment. The sequence of negative small interfering RNA is ACGUGACACGUUCGGAGAATT (SEQ ID NO: 3). Since it is an RNA sequence, the U base in the sequence listing is replaced with the T base.

[0081] (2) FOS interference group (si-FOS group): The small interfering RNA (siRNA-FOS) targeting FOS was used for treatment. The sequence of siRNA-FOS is CAUAGAAGGACCCAGAUAGGUTT (SEQ ID NO: 1). (3) JUN interference group (si-JUN group): small interfering RNA (siRNA-JUN) targeting JUN was used for treatment. The sequence of siRNA-JUN is UGACUUUCUGUUUAAGCUGTT (SEQ ID NO: 2).

[0082] Before transfection, sorted immune cells were adjusted to a suitable density of 1×10^5–1×10^6 cells / mL and seeded in culture medium. siRNA transfection was performed using Lipofectamine 3000 transfection reagent. After transfection, cells from each group were collected, and total RNA was extracted and subsequently reverse transcribed into cDNA.

[0083] 4. Real-time quantitative PCR (qPCR) was used to detect the relative mRNA expression levels of the target genes FOS, JUN, and neuroinflammation-related molecules, and normalization analysis was performed using the internal reference gene (β-Actin). Preferred neuroinflammation-related molecules included IL-1β, IL-6, TNFα, SPP1, NLRP3, IL23R, and IL12A. The regulatory effects of FOS and JUN on neuroinflammation were assessed by comparing the expression differences among the NC group, si-FOS group, and si-JUN group.

[0084] The results are as follows Figure 21 As shown, compared with the negative control group, the expression of FOS and JUN in various immune cells in the si-FOS group and si-JUN group was significantly decreased. At the same time, the expression of neuroinflammation-related molecules such as IL-1β, IL-6, TNFα, SPP1, NLRP3, IL23R and IL12A was reduced overall, suggesting that inhibiting FOS and JUN can reduce the inflammatory activation state of immune cells in patients with neuroimmune disease.

[0085] The above results indicate that FOS and JUN are involved in maintaining the neuroimmune-related neuroinflammatory state, and inhibiting FOS and JUN can alleviate the neuroinflammatory response, suggesting that FOS and JUN have the potential to be used as therapeutic targets for intervention.

[0086] Example 8: An analytical experiment to reduce neuroimmune-related immune chemotaxis by inhibiting FOS and JUN. Under the same PBMC isolation, immune cell sorting, culture, and siRNA transfection conditions as in Example 7, the effects of FOS and JUN interference on the expression of immune chemotaxis-related molecules were further investigated. After transfection, total RNA was extracted from each group of cells, reverse transcribed into cDNA, and the relative expression levels of immune chemotaxis-related molecules mRNA were detected by real-time quantitative PCR, with normalization analysis performed using an internal reference gene (β-Actin). Immune chemotaxis-related molecules included CCR1, CXCL9, and CCL2.

[0087] The results are as follows Figure 22 As shown, compared with the negative control group, the expression of CCR1, CXCL9 and CCL2 immune chemotaxis-related molecules was reduced in the si-FOS group and si-JUN group, suggesting that inhibiting FOS and JUN can weaken the chemotaxis-related activation state of immune cells in patients with neuroimmunological diseases.

[0088] The above results indicate that FOS and JUN are involved in maintaining neuroimmune-related immune chemotaxis. Inhibiting FOS and JUN can reduce the recruitment of inflammatory cells and the expression of chemotaxis-related molecules, suggesting that they have application value in improving abnormal migration of neuroimmune-related immune cells and inflammation amplification.

[0089] Example 9: An analytical experiment to analyze the effect of inhibiting FOS and JUN on the reduction of activation of neuroimmune-related inflammatory signaling pathways. Under the same PBMC isolation, immune cell sorting, culture, and siRNA transfection conditions as in Example 7, the effects of FOS and JUN interference on the expression of molecules related to inflammatory signaling pathways were further investigated. After transfection, total RNA was extracted from each group of cells, reverse transcribed into cDNA, and the relative expression levels of mRNAs related to inflammatory signaling pathways were detected by real-time quantitative PCR, with normalization analysis performed using an internal reference gene (β-Actin). Molecules related to inflammatory signaling pathways included TLR4, MAPK14, and NF-κB.

[0090] The results are as follows Figure 23 As shown, compared with the negative control group, the expression of inflammatory signaling pathway-related molecules such as TLR4, MAPK14 and NF-κB was reduced in the si-FOS group and si-JUN group, suggesting that inhibiting FOS and JUN can weaken the activation state of inflammation-related signaling pathways in immune cells of patients with neuroimmunological diseases.

[0091] The above results indicate that FOS and JUN are involved in the maintenance and amplification of neuroimmune-related inflammatory signaling pathways, and that inhibiting FOS and JUN can weaken the activation of related inflammatory pathways, thus providing an intervention basis for improving neuroimmune-related neuroinflammation.

[0092] Example 10: A FOS Inhibitor The FOS inhibitor in this embodiment includes the small interfering RNA (siRNA-FOS) that targets FOS, as described in Example 7.

[0093] Example 11: A drug for improving neuroimmune diseases The drug in this embodiment includes the FOS inhibitor from Example 10; The drug also includes a pharmaceutically acceptable carrier; wherein, a pharmaceutically acceptable carrier includes at least one of the following: sustained-release agent, excipient, filler, binder, wetting agent, disintegrant, absorption enhancer, surfactant and lubricant.

[0094] All other parts not described in detail are existing technologies. Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. The application of a reagent for detecting the FOS gene in the preparation of reagents for diagnosing neuroimmunological diseases, characterized in that: The neuroimmune diseases mentioned are any one of the following: autoimmune encephalitis, neuromyelitis optica spectrum disorders, myelin oligodendrocyte glycoprotein antibody-associated diseases, multiple sclerosis, chronic inflammatory demyelinating polyradiculoneuropathy, Guillain-Barré syndrome, inflammatory myopathy, and myasthenia gravis.

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