Biomarkers and application thereof in diagnosis of immune-mediated necrotizing myopathy

Abstract

The invention belongs to the technical field of molecular diagnosis and immunotherapy, and particularly relates to a group of biomarkers and application thereof in diagnosis of immune-mediated necrotizing myopathy. The invention firstly provides a group of biomarkers for predicting, treating or diagnosing immune-mediated necrotizing myopathy, and the biomarkers are protein markers, and comprise one or a combination of more than two markers selected from CSRP3, HSP90AB1, MYH1, ITGB1BP2, SMPX, MYBPC2, CD9, ICAM1, ANKRD1 and NT5C1A. The invention also provides application of the marker in preparation of a product for predicting, treating or diagnosing immune-mediated necrotizing myopathy. Through muscle proteomics analysis, a unique and shared way in anti-SRP and anti-HMGCR myopathy is disclosed, and it is determined that HSP90AB1, ITGB1BP2, CD9, ICAM1 and ANKRD1 are potential biomarkers for the severity of IMNM diseases. These findings provide valuable insights for the determination of pathogenesis and therapeutic targets of IMNM.

Description

Technical Field

[0001] This invention belongs to the field of molecular diagnostics and immunotherapy technology, specifically involving a group of biomarkers and their application in the diagnosis of immune-mediated necrotizing myopathy. Background Technology

[0002] Immune-mediated necrotizing myopathy (IMNM) is a subgroup of idiopathic inflammatory myopathy characterized by severe muscle manifestations, including rapidly progressive muscle weakness and elevated creatine kinase levels. In addition, the skeletal muscle pathology of IMNM patients is characterized by myofibril necrosis and regeneration, accompanied by membrane attack complex deposition and a large number of macrophage infiltrations, with little lymphocyte infiltration.

[0003] Anti-signal recognition particle (SRP) and anti-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) antibodies are closely associated with intramuscular myopathy (IMNM), which is classified into anti-SRP myopathy, anti-HMGCR myopathy, and seronegative IMNM. Anti-SRP and anti-HMGCR myopathy share common clinical, biological, and histological features and exhibit some antibody-related specificity. In magnetic resonance imaging studies, patients with anti-SRP myopathy typically present with more severe muscle weakness and atrophy accompanied by significant muscle damage. In contrast, anti-HMGCR myopathy is often associated with statin exposure. Both subtypes are associated with poor prognosis, frequent relapses, and the need for combination therapy. However, the molecular and pathophysiological mechanisms underlying these differences and similarities remain to be elucidated. Investigating and elucidating the precise mechanisms of IMNM may help identify novel biomarkers and therapeutic targets for this disease.

[0004] Mass spectrometry (MS) proteomics analysis of clinical samples is a powerful strategy for studying disease mechanisms and molecular characterization. While blood samples are often used for biomarker research due to their accessibility, skeletal muscle tissue more accurately reflects the pathological processes behind IMNM. Unbiased labeled proteomics analysis using TMT-MS (tandem mass tagging combined mass spectrometry) can quantify more than 2,000 proteins in skeletal muscle samples in a single analysis. This technique produces rich datasets from which novel biomarkers associated with key pathophysiological processes in disease that are disrupted and regulated by therapeutic interventions can be identified, potentially for predicting treatment response. Given its analytical depth and comparative quantification capabilities, proteomics analysis is well-suited for muscle protein analysis and biomarker discovery.

[0005] Based on this, the purpose of this invention is to use high-throughput TMT-MS to comprehensively analyze the skeletal muscle proteome in IMNM and to identify new biomarkers and their corresponding uses. Summary of the Invention

[0006] Anti-signal recognition particle (SRP) and anti-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) myopathy are the main subtypes of immune-mediated necrotizing myopathy (IMNM) and have some antibody-related specific clinicopathological features.

[0007] This invention selected 4 patients with anti-SRP myopathy, 4 patients with anti-HMGCR myopathy, and 4 age-matched controls for muscle proteomics and bioinformatics analysis, and evaluated the correlation between key differentially expressed proteins (DEPs) and clinical parameters as well as diagnostic efficacy.

[0008] The purpose of this invention is to study the shared muscle proteomic features of anti-signal recognition particles (SRP) and anti-3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) myopathy subtypes, and to screen for potential biomarkers for the development of products for the treatment or diagnosis of immune-mediated necrotizing myopathy (IMNM).

[0009] To achieve the above objectives, the technical solution created by this invention is implemented as follows: This invention first provides a set of biomarkers for predicting, treating or diagnosing immune-mediated necrotizing myopathy (IMNM).

[0010] Specifically, the biomarkers are protein biomarkers, including one or more of the following: CSRP3, HSP90AB1, MYH1, ITGB1BP2, SMPX, MYBPC2, CD9, ICAM1, ANKRD1, and NT5C1A.

[0011] Preferably, the marker is one or a combination of two or more markers selected from HSP90AB1, ITGB1BP2, CD9, ICAM1 and ANKRD1.

[0012] More preferably, the marker is a combination of HSP90AB1, ITGB1BP2, CD9, ICAM1 and ANKRD1.

[0013] Furthermore, based on a general inventive concept, the present invention also provides the use of the said biomarker in the preparation of products for the prediction, treatment or diagnosis of immune-mediated necrotizing myopathy (IMNM).

[0014] Specifically, the product is a reagent kit, a pharmaceutical preparation, or a biochip.

[0015] More preferably, when the product is a kit, the kit contains one or more biomarker standards selected from HSP90AB1, ITGB1BP2, CD9, ICAM1 and ANKRD1.

[0016] Furthermore, based on a general inventive concept, the present invention also provides a product for predicting, treating, or diagnosing immune-mediated necrotizing myopathy (IMNM).

[0017] Specifically, the product is a reagent kit, a pharmaceutical preparation, or a biochip.

[0018] Specifically, the kit contains one or more biomarker standards selected from HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention identified 4281 proteins in skeletal muscle samples from 8 IMNM patients (including 4 anti-SRP myopathy group and 4 anti-HMGCR myopathy group) and 4 control groups after pretreatment, TMT labeling, HPLC fractionation, liquid chromatography-MS / MS analysis, and proteomics analysis.

[0020] Compared with the control group, 645 DEPs were identified in the anti-SRP myopathy group and 157 DEPs were found in the anti-HMGCR myopathy group. Correlation analysis showed that the expression levels of HSP90AB1 and ITGB1BP2 were negatively correlated with MMT8 scores and positively correlated with serum lactate dehydrogenase levels; the expression levels of CD9, ICAM1, and ANKRD1 were negatively correlated with MMT8 scores (all...). P <0.05). ROC analysis showed that the AUC of HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1 was 1.000.

[0021] This invention, through muscle proteomics analysis, reveals unique and shared pathways in anti-SRP and anti-HMGCR myopathy, and identifies HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1 as potential biomarkers for IMNM disease severity. These findings provide valuable insights into the pathogenesis of IMNM and the identification of therapeutic targets. Attached Figure Description

[0022] Figure 1 DEP analysis chart; Figure 1The figures in the middle are as follows: (A) Basic statistics of identified proteins; (B) PCA plot for each individual sample; (C) Volcano plot and heatmap of DEP in the anti-SRP myopathy group and the control group; (D) Volcano plot and heatmap of DEP in the anti-HMGCR myopathy group and the control group; (E) Volcano plot and heatmap of DEP between the anti-SRP myopathy group and the anti-HMGCR myopathy group; (F) Venn diagram showing overlapping and non-overlapping DEP between different groups; DEPs, differentially expressed proteins; Principal component analysis; SRP, signal recognition particle; HMGCR, 3-hydroxy-3-methylglutaryl-CoA reductase; Figure 2 ClueGO enrichment and PPI network analysis diagram; Figure 2 The figures in the image are: (A) GO enriched interaction network; (B) KEGG enriched interaction network; (C) PPI network analysis of shared DEPs in anti-SRP and anti-HMGCR myopathy, where the more purple the node, the higher its degree; (D) PPI network showing the top 10 shared DEPs in anti-SRP and anti-HMGCR myopathy, where darker node colors indicate higher degree values. PPI, protein-protein interaction; GO, gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEPs, differentially expressed proteins; SRP, signal recognition particle; HMGCR, 3-hydroxy-3-methylglutaryl-CoA reductase. Detailed Implementation

[0023] The present invention will be further described in detail below with reference to embodiments, but the embodiments of the present invention are not limited thereto. Unless otherwise specified, the reagents, methods, and equipment used in the present invention are conventional reagents, methods, and equipment in this technical field. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as known to those skilled in the art. Furthermore, any methods and materials similar to or equivalent to those described herein can be applied to the methods of the present invention.

[0024] In the following examples, room temperature refers to 25±5℃.

[0025] Example 1 I. Study Design and Patient Samples 1.1 From January 2020 to December 2024, the First Affiliated Hospital of Zhengzhou University recruited 8 newly diagnosed IMNM patients and 4 sex- and age-matched controls. All patients were >18 years old at the time of onset and were diagnosed with IMNM according to the guidelines of the 224th European Neuromuscular Center International Working Group (see the instruction manual with reference [1]). Demographic data, clinical characteristics, laboratory test results and treatment history were obtained by reviewing medical records. Muscle strength was assessed using the Manual Muscle Testing-8 (MMT8) scale. Disease activity was assessed using the myositis disease activity assessment visual analogue scales (MYOACT). The 4 control subjects were initially suspected of having muscle disease, but the possibility of having muscle disease was later ruled out by muscle biopsy and other diagnostic tests. All participants were tested for myositis-specific antibodies and myositis-related antibodies using the Euroimmun strain test (Lübeck, Germany).

[0026] 1.2 Demographic information and clinical characteristics This invention included 4 patients with anti-SRP myopathy, 4 patients with anti-HMGCR myopathy, and 4 control groups. Detailed characteristics are shown in Table 1.

[0027] Table 1. Clinical sample information.

[0028] All participants provided written informed consent prior to inclusion in the study. The study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University and conducted in accordance with the guidelines set forth in the Declaration of Helsinki by the World Medical Association.

[0029] II. Experimental Methods 2.1 Muscle biopsy Muscle biopsies were initially performed as part of routine diagnostic procedures and were rigorously re-evaluated for the purposes of this invention. Open muscle biopsies were performed on all participants after obtaining consent. Biopsies were taken from the biceps brachii or quadriceps femoris and analyzed using standard histological and immunohistochemical staining, as detailed in the appendix to the instruction manual [2]).

[0030] 2.2 Preparation of MS Samples After an open skeletal muscle biopsy, the specimen was placed on a corkboard, rapidly frozen in isopentane cooled with liquid nitrogen, and stored at -80°C until analysis. The frozen muscle (skeletal muscle) sample was transferred to a low protein binding tube (1.5 mL Eppendorf) and lysed with 500 µL digestion buffer containing 1 mM benzyl sulfonyl fluoride (Thermo Fisher Scientific, Waltham, Massachusetts, USA, Catalog No.: 36978). The sample was homogenized on ice and further lysed for 3 minutes at 80 W using an ultrasonic instrument (Scientz, Ningbo, China) at 1 second intervals. The lysate was centrifuged at 15000×g for 15 minutes at 4°C to remove insoluble fragments, and this step was repeated once. Protein concentration was measured using the dioctanine assay (relevant reagents were purchased from Thermo Fisher Scientific, Waltham, Massachusetts, USA) (see the instruction manual and reference [3] for the assay method), and the measured sample was aliquoted and stored at -80°C.

[0031] In a 10 K ultrafiltration tube (Millipore, Burlington, MA, USA), 100 micrograms of protein (i.e., aliquoted sample) were mixed with 120 μL of reduction buffer (specifically composed of 10 mM dithiothreitol, 8 M urea, 100 mM triethylammonium bicarbonate [TEAB], pH 8.0). The sample was incubated at 60°C for 1 hour, and then alkylated in the dark with 50 mM iodoacetamide (Sangon Biotech, Shanghai, China) for 40 minutes at room temperature. The treated solution was centrifuged at 12,000 rpm for 20 minutes at 4°C, and the flow-through (i.e., supernatant) was discarded. The sample was washed twice with 100 μL of 300 mM TEAB (Sigma, MO, USA) and digested at 37°C with 3 μL of sequencing-grade trypsin (1 μg / μL) (HLS, Beijing, China) for 12 hours. The digested peptides were centrifuged, washed with 50 μL of 200 mM TEAB, and lyophilized to obtain lyophilized samples.

[0032] 2.3 TMT labeling and high-performance liquid chromatography (HPLC) fractionation The lyophilized samples were resuspended in 100 μL of 100 mM TEAB (pH 8.5), and 40 μL of each sample was transferred to a new test tube for labeling. TMTpro 16 labeling reagent (Tandem Mass Spectrometry (TMT) reagent, purchased from Thermo Fisher Scientific) was dissolved in anhydrous acetonitrile (Thermo Fisher Scientific, Waltham, MA, USA) at room temperature and thoroughly mixed to obtain the TMTpro 16 labeling working solution (concentration 0.025 mg / μL). Then, 10 μL of the prepared TMTpro 16 labeling working solution was added to each sample and incubated at room temperature for 1 hour. The reaction was quenched with 5 µL of 5% hydroxylamine (Sigma, MO, USA) for 15 minutes to obtain the labeled peptide, which was then lyophilized and stored at -80°C.

[0033] Separation was performed using reversed-phase high-performance liquid chromatography (RP-HPLC) with an Agilent 1100 HPLC system (Agilent Technologies, Santa Clara, California, USA) and a Zorbax Extend RP column (5 μm, 150 mm × 2.1 mm).

[0034] Mobile phases A and B were set up, both of which were composed of water and acetonitrile in different volume ratios. Mobile phase A contained 2% acetonitrile and mobile phase B contained 98% acetonitrile. Mobile phases A and B were prepared into composite solvents with different gradients for reversed-phase high-performance liquid chromatography. The solvent gradient was set as follows: 0–8 min, using a composite solvent containing 8% mobile phase A; 8–8.01 min, using a composite solvent containing 98%–95% mobile phase A; 8.01–48 min, using a composite solvent containing 95%–75% mobile phase A; 48–60 min, using a composite solvent containing 75%–60% mobile phase A; 60–60.01 min, using a composite solvent containing 60%–10% mobile phase A; 60.01–70 min, using a composite solvent containing 10% mobile phase A; 70–70.01 min, using a composite solvent containing 10%–98% mobile phase A; 70.01–75 min, using a composite solvent containing 98% mobile phase A. Elution was then carried out at a rate of 300 μL / min, and the fractions were monitored at 210 nm and 280 nm. Fractions were collected every minute from 8 to 60 minutes into tubes 1-15 and frozen for mass spectrometry analysis.

[0035] 2.4 Liquid Chromatography-MS / MS Analysis The collected fractions were analyzed using a Q-Exactive HF mass spectrometer equipped with a Nanospray Flex source (Thermo Fisher Scientific, Waltham, Massachusetts, USA). Simultaneously, peptides were separated from the fractions analyzed by MS / MS using an EASY nLC™ 1000 system (Thermo Fisher Scientific, Waltham, Massachusetts, USA) at a column flow rate of 300 nL / min (YMC C18 column, 15 cm × 75 µm, 5 μm).

[0036] Set up mobile phase a and mobile phase b. Mobile phase a is 0.1% formic acid / water solution and mobile phase b is 0.1% formic acid / acetonitrile solution. Prepare composite solutions of mobile phase a and mobile phase b with different gradients. When passing the column, use composite solutions with different gradients and perform linear gradient treatment for 75 minutes. The composite solution gradient was set as follows: 0-63 min, using a composite solvent containing 5-45% mobile phase b; 63-65 min, using a composite solvent containing 45-90% mobile phase b; 65-75 min, using a composite solvent containing 90% mobile phase b.

[0037] The specific settings for liquid chromatography-MS / MS are as follows: A full MS scan was acquired at a velocity of 60,000 m / s, covering a mass range of 350–1500 m / s, with an automatic gain control target of 1 × 10⁶. The first 20 peaks in the MS spectrum were broken up using high-energy collisional dissociation (collision energy: 360). MS / MS spectra were acquired at a resolution of 30,000 m / s, with an automatic gain control target of 1 × 10⁵ and a maximum injection time of 80 ms. Dynamic exclusion was set to 30.0 sec, and the system was operated in positive mode.

[0038] 2.5 Database Search Data obtained after liquid chromatography-MS / MS analysis were used to search the raw data using the ProteomeDiscoverer v2.4 control sample protein database, and trypsin specificity was analyzed. Cysteine ​​alkylation was considered a fixed modification during the database search. Cysteine ​​carbamate methylation and lysine and N-terminal TMT labeling were set as static modifications. A global false discovery rate of 0.01 was used, and protein quantification required ≥2 peptides.

[0039] 2.6 Quality Control Analysis For the quality control analysis of proteomics data, please refer to the attached reference [4] in the instruction manual. Skeletal muscle samples were randomly divided into two batches. The merged peptide samples were control samples labeled with TMTpro in each batch. The two batches were then integrated to obtain a merged raw abundance file. Protein levels were first scaled by dividing each protein intensity by the sum of all reporter ion intensities of the TMT channel (per sample) and then multiplying by the sum of the maximum channel-specific protein intensities. Proteins with more than 50% missing values ​​in each analysis were removed from the matrix before further processing (no imputation was performed on missing values). The technical batch variance in each dataset was adjusted using an adjustable median polishing method (see attached reference [5] in the instruction manual for details). After this, nonparametric bootstrap regression was performed on the batches.

[0040] 2.7 Bioinformatics and Statistical Analysis Abundance values ​​were log2 transformed and normalized by subtracting the median of the corresponding column (see the instruction manual and reference [6] for details). A complete list of identified proteins with raw scaled abundance values ​​is available upon request. Then, for each protein, the log2-fold change and p-value between patients and controls were calculated using an unpaired t-test. To control for multiple comparisons, p-values ​​were adjusted using the Benjamini-Hochberg method.

[0041] Proteins with an absolute fold change greater than 1.5 and an adjusted p-value less than 0.05 were considered differentially expressed proteins (DEPs) (see the instruction manual and reference [7] for details). Principal component analysis (PCA) was performed to detect sample heterogeneity. DEPs were visualized using volcano plots and cluster heatmaps. Shared and unique DEPs between different groups were visualized using Venn diagrams. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed. FDR was calculated using OECloud tools at https: / / cloud.oebiotech.com. FDR was calculated by adjusting p-values ​​using the Benjamini-Hochberg method, and an FDR threshold ≤ 0.05 was considered statistically significant.

[0042] Based on the differentially expressed protein DEP, a protein-protein interaction (PPI) network was generated using the STRING database (https: / / cn.string-db.org) and visualized using Cytoscape v3.9.1. Hub proteins were identified using the Degree algorithm in CytoHubba v0.1.

[0043] Non-redundant GO and KEGG terms were classified into functional networks using ClueGO v2.5.10 (a Cytoscape plugin). To explore the potential roles of these shared DEPs in anti-SRP and anti-HMGCR myopathy, GO and KEGG analyses of these shared DEPs were performed using ClueGO. The biological processes (BPs) analyzed in the GO analyses were the focus of attention.

[0044] Categorical data are expressed as frequencies and percentages, and quantitative data as medians (interquartile ranges). The normality of the distribution and homogeneity of variance were assessed using the Shapiro-Wilk normality test and the homogeneity of variance test, respectively. Spearman correlation analysis was used to analyze correlations, and a two-sided p-value < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses were performed on unpaired samples. Statistical analysis was performed using IBM SPSS Statistics v24.0.

[0045] III. Experimental Results 3.1 Identification of DEP Skeletal muscle samples from 8 IMNM patients (including 4 patients with anti-SRP myopathy and 4 patients with anti-HMGCR myopathy) and 4 control groups were pretreated, labeled with TMT, fractionated by HPLC, and analyzed by liquid chromatography-MS / MS. Proteomics analysis was then performed, identifying a total of 4281 proteins. Figure 1 A). The PCA plot showed good clustering, indicating good quality control and reproducibility of the experiment. Figure 1 B). Compared with the control group, 645 DEPs were found in the anti-SRP myopathy group (605 upregulated and 40 downregulated); compared with the control group, 157 DEPs were found in the anti-HMGCR myopathy group (131 upregulated and 26 downregulated). Figure 1 C and D). When comparing the anti-SRP myopathy and anti-HMGCR myopathy groups, 34 DEPs were identified (23 upregulated and 11 downregulated). Figure 1 E). Shared and unique DEPs are visualized using Venn diagrams ( Figure 1 F).

[0046] 3.2 Comparison between the anti-SRP myopathy group and the anti-HMGCR myopathy group To identify unique and shared pathways between the anti-SRP myopathy and anti-HMGCR myopathy groups, GO-BP and KEGG pathway analyses were performed using ClueGO to compare the two groups' DEPs in anti-SRP and anti-HMGCR myopathy. GO-BP terms enriched only in anti-SRP myopathy included positive regulation of actin filament motility, positive regulation of protein polymerization, and negative regulation of protein ubiquitination. Figure 2A). Specific terms for anti-HMGCR myopathy include ribosomal large subunit biosynthesis, regulation of signal transduction by p53 mediators, ribosome assembly, regulation of DNA damage response, p53-mediated signal transduction, negative regulation of ubiquitin-transferase activity, regulation of ubiquitin-protein ligase activity, and regulation of ubiquitin-converting enzyme activity. Common GO-BP terms include inosine monophosphate (IMP) metabolism, skeletal muscle organ development, myofibril sliding, myofibril assembly, and negative regulation of proteolytic processes involved in protein catabolism. KEGG analysis showed that anti-SRP myopathy was specifically enriched in endocytosis, lysosomes, focal adhesion, pathogenic E. coli infection, and phagosomes. Figure 2 B). Specific terms for anti-HMGCR myopathy include ribosomes and coronavirus disease. Abundant terms for both groups include necrotizing ptosis and the hypoxia-inducible factor 1 (HIF-1) signaling pathway.

[0047] To identify potential interactions between DEPs common to the anti-SRP myopathy and anti-HMGCR myopathy groups, a PPI network was constructed. The PPI network consists of 74 nodes and 24 edges, with darker colors indicating higher importance. Figure 2 C). The top 10 key proteins are CSRP3, HSP90AB1, MYH1, ITGB1BP2, SMPX, MYBPC2, CD9, ICAM1, ANKRD1, and NT5C1A ( Figure 2 D).

[0048] 3.3 Correlation analysis of the top ten common DEPs with clinical parameters To identify potential biomarkers in IMNM, the correlations between the top ten DEPs common in anti-SRP myopathy and anti-HMGCR myopathy and clinical parameters were analyzed. The expression levels of HSP90AB1 and ITGB1BP2 were negatively correlated with MMT8 scores and positively correlated with serum lactate dehydrogenase levels (ρ=-0.874, P=0.005; ρ=0.762, P=0.028; ρ=-0.886, P=0.003; ρ=0.762, P=0.028, respectively) (Table 2). The expression levels of MYH1 and MYBPC2 were positively correlated with MMT8 scores (ρ=0.778, P=0.023; ρ=0.719, P=0.045, respectively). Furthermore, the expression levels of CD9, ICAM1, and ANKRD1 were negatively correlated with the MMT8 score (ρ=-0.719, P=0.045; ρ=-0.862, P=0.006 and ρ=-0.755, P=0.031, respectively).

[0049] Table 2 shows the correlation analysis between the top 10 shared DEPs and clinical indicators.

[0050] 3.4 Assessment of the diagnostic efficacy of biomarkers This invention further determined the diagnostic efficacy of HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1 in IMNM. Compared with normal controls, the area under the ROC curve (AUC) of HSP90AB1 protein expression (95% CI) was 1.000 (1.000, 1.000); the area under the ROC curve (AUC) of ITGB1BP2 protein expression (95% CI) was 1.000 (1.000, 1.000); the area under the ROC curve (AUC) of CD9 protein expression (95% CI) was 1.000 (1.000, 1.000); the area under the ROC curve (AUC) of ICAM1 protein expression (95% CI) was 1.000 (1.000, 1.000); and the area under the ROC curve (AUC) of ANKRD1 protein expression (95% CI) was 1.000 (1.000, 1.000) (Table 3).

[0051] Table 3 Diagnostic efficacy of biomarkers.

[0052] IV. Conclusion This invention identified 4281 proteins in skeletal muscle samples from 8 newly diagnosed IMNM patients (including 4 patients with anti-SRP myopathy and 4 patients with anti-HMGCR myopathy) and 4 controls after pretreatment, TMT labeling, HPLC fractionation, liquid chromatography-MS / MS analysis, and proteomics analysis.

[0053] Compared with the control group, 645 DEPs were identified in the anti-SRP myopathy group and 157 DEPs were found in the anti-HMGCR myopathy group. Correlation analysis showed that HSP90AB1 and ITGB1BP were negatively correlated with MMT8 score and positively correlated with serum lactate dehydrogenase level; CD9, ICAM1, and ANKRD1 were negatively correlated with MMT8 score (all P < 0.05). ROC analysis showed that the AUC of HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1 was 1.000.

[0054] This invention, through muscle proteomics analysis, reveals unique and shared pathways in anti-SRP and anti-HMGCR myopathy, and identifies HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1 as potential biomarkers for IMNM disease severity. These findings provide valuable insights into the mechanisms of IMNM and the development of therapeutic targets.

[0055] References attached: [1]Allenbach Y, Mammen AL, Benveniste O, Stenzel W, Immune-MediatedNecrotizing Myopathies Working G: 224th ENMC International Workshop::Clinico-sero-pathological classification of immune-mediatednecrotizingmyopathies Zandvoort, The Netherlands, 14-16 October 2016.Neuromuscul Disord 2018, 28(1):87-99. [2]Wang Y, Zhao Y, Yu M, Wei L, Zhang W, Wang Z, Yuan Y:Clinicopathologicaland circulating cell-free DNA profile in myositisassociated with anti-mitochondrial antibody. Ann Clin Transl Neurol 2023, 10(11):2127-2138. [3]Plath AMS, Huber S, Alfarano SR, Abbott DF, Hu M, Mougel V, Isa L,Ferguson SJ: Co-Electrospun Poly(epsilon-Caprolactone) / Zein ArticularCartilage Scaffolds. Bioengineering (Basel) 2023, 10(7):771. [4]Bi X, Liu W, Ding X, Liang S, Zheng Y, Zhu X, Quan S, Yi X, XiangN, DuJ et al: Proteomic and metabolomic profiling of urine uncovers immuneresponses in patients with COVID-19. Cell Rep 2022, 38(3):110271. [5]Dammer EB, Seyfried NT, Johnson ECB: Batch Correction andHarmonizationof -Omics Datasets with a Tunable Median Polish of Ratio. FrontSyst Biol 2023, 3:1092341. [6]de Vries GM, Asselbergh B, Monticelli A, De Jonghe P, Maudsley S,VanDen Bergh PYK, Bigot A, De Bleecker JL, Ermanoska B, De Ridder W et al:Ageing Signatures and Disturbed Muscle Regeneration in Muscle Proteome ofInclusionBody Myositis. J Cachexia Sarcopenia Muscle 2025, 16(3):e13845. [7]Wang M, You L, He X, Peng Y, Wang R, Zhang Z, Shu J, Zhang P, SunX,Jia L et al: Multiomics Analysis Reveals Therapeutic Targets for ChronicKidney Disease With Sarcopenia. J Cachexia Sarcopenia Muscle 2025, 16(1):e13696.

Claims

1. A group of biomarkers for predicting, treating, or diagnosing immune-mediated necrotizing myopathy, characterized in that, The biomarkers are protein biomarkers, including one or more of the following: CSRP3, HSP90AB1, MYH1, ITGB1BP2, SMPX, MYBPC2, CD9, ICAM1, ANKRD1, and NT5C1A.

2. The biomarker according to claim 1, characterized in that, The marker is one or more of the following markers: HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1.

3. The biomarker according to claim 1, characterized in that, The markers are a combination of HSP90AB1, ITGB1BP2, CD9, ICAM1 and ANKRD1.

4. The use of the biomarker of any one of claims 1-3 in the preparation of products for the prediction, treatment or diagnosis of immune-mediated necrotizing myopathy.

5. The application according to claim 4, characterized in that, The product is a reagent kit, a pharmaceutical preparation, or a biochip.

6. The application according to claim 4, characterized in that, When the product is a kit, the kit contains one or more biomarker standards selected from HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1.

7. A product for predicting, treating, or diagnosing immune-mediated necrotizing myopathy, characterized in that, The product is a reagent kit, a pharmaceutical preparation, or a biochip.

8. The product according to claim 7, characterized in that, The kit contains one or more biomarker standards selected from HSP90AB1, ITGB1BP2, CD9, ICAM1, and ANKRD1.

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