Application of SPP1 as diagnostic marker and therapeutic target of chronic gouty arthritis

Abstract

The invention provides application of SPP1 or SPP1 positive macrophages as a marker in preparation of a diagnostic reagent for chronic gouty arthritis. The invention also provides application of the SPP1 or SPP1-CD44 signal axis inhibitor in preparation of a medicine for preventing and / or treating chronic gouty arthritis. The SPP1 < + > macrophage is used as a key marker and a treatment target for gout chronic treatment for the first time, a functional network of the SPP1 < + > macrophage in a tophus microenvironment is systematically analyzed through a single cell and space transcriptomics technology, and a brand new direction is provided for clinical prediction and intervention.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biotechnology, and particularly relates to application of SPP1 as a diagnostic marker and therapeutic target for chronic gouty arthritis. BACKGROUND

[0002] Currently, the research of gouty arthritis mainly focuses on the mechanism of acute inflammation (such as activation of NALP3 inflammasome and release of IL-1β) and regulation of uric acid metabolism. However, the molecular mechanism of chronic gout (such as tophi formation and joint destruction) is limited.

[0003] The existing technology has limited research on the chronicity of gout. Dalbeth et al. described the three-layer structure of tophi (core, coronal zone, fibrovascular zone) through histological analysis, and found that the coronal zone was rich in macrophages, but did not identify specific subgroups or functions (Dalbeth, N. et al. Cellular characterization of the gouty tophus: A quantitative analysis. Arthritis & Rheumatism 62, 1549-1556 (2010). https: / / doi.org / 10.1002 / art.27356). Gu et al. found that HLA-DQA1 high Classical monocytes and PTGS2 high Monocyte increase suggests the role of monocyte / macrophage in the chronicity of gout, but does not focus on the local microenvironment of the joint (Gu, H. et al. MSU crystal deposition contributes to inflammation and immune responses in gout remission. Cell Rep 42, 113139 (2023)). Zhao et al. proposed the difference of macrophage polarization (M1 / M2) in acute and chronic gout, but did not identify specific macrophage subgroups directly related to tophi formation (Zhao, L. et al. Distinct macrophage polarization in acute and chronic gout. Laboratory Investigation 102, 1054-1063 (2022). https: / / doi.org / 10.1038 / s41374-022-00798-4).

[0004] However, the molecular mechanisms of immune-stromal cell interaction in gout tophi, such as ECM remodeling, bone erosion, have not been elucidated, especially SPP1 + The role of macrophages has not been found. The prior art also does not clearly define the key cell subpopulation of tophi formation and its molecular markers, which cannot be used for early prediction of chronic gout. In addition, existing studies are mostly aimed at acute inflammation (such as IL-1β inhibitors), but lack of targeted intervention strategies for tophi formation and chronic joint damage. SUMMARY

[0005] To solve the above problems, the present application determines the application of SPP1 as a chronic gout prediction marker and therapeutic target.

[0006] Specifically, the first aspect of the present application provides the use of SPP1 or SPP1 positive macrophages as markers in the preparation of a diagnostic reagent for chronic gout.

[0007] In some embodiments, the chronic gout is chronic gouty arthritis.

[0008] In some embodiments, the SPP1 positive macrophages include SPP1 + CHI3L1 + macrophages or SPP1 + MMP9 + macrophages.

[0009] In some embodiments, the detection sample is synovial tissue or tophi tissue.

[0010] In some embodiments, the reagent detects the transcription level of SPP1 by one or a combination of several methods of quantitative PCR and high-throughput sequencing.

[0011] In some embodiments, the reagent detects the level of the protein by one or a combination of several methods of BCA protein quantification, immunofluorescence, Western blotting, proteomics.

[0012] In some embodiments, the reagent detects the level of SPP1 positive macrophages by flow cytometry or FISH technology.

[0013] The second aspect of the present application provides a kit for the diagnosis of chronic gout, comprising a reagent for detecting the level of SPP1 or SPP1 positive macrophages in the tissue of a subject and optionally an instruction.

[0014] In some embodiments, the reagent detects the transcription level of SPP1 by one or a combination of several methods of quantitative PCR and high-throughput sequencing.

[0015] In some embodiments, the agent detects the level of the protein by one or a combination of methods selected from the group consisting of BCA protein quantification, immunofluorescence, Western blot, and proteomics.

[0016] In some embodiments, the agent detects the level of SPP1-positive macrophages by flow cytometry or FISH technology.

[0017] In some embodiments, the instructions record a standard for diagnosing chronic gout based on the detected level of SPP1 or SPP1-positive macrophages in the subject's tissue.

[0018] In some embodiments, the chronic gout is chronic gouty arthritis.

[0019] The third aspect of the present application provides use of an SPP1 or SPP1-CD44 signaling axis inhibitor in the preparation of a medicament for preventing and / or treating chronic gout.

[0020] In some embodiments, the chronic gout is chronic gouty arthritis.

[0021] In some embodiments, the medicament is selected from one or more of an antibody, a CRISPR-CAS gene editing system, a small molecule inhibitor, an AAV vector, and a small interfering RNA.

[0022] In some embodiments, the small molecule drug is selected from Tradipitant, Teniposide, Etoposide, Cepagenin, Betulinic_acid (White Birch Acid), Acetylursolic_acid (Ursolic Acid), and MolPort-019-936-959 (C41H66O14).

[0023] The fourth aspect of the present application provides use of an SPP1 or SPP1-CD44 signaling axis inhibitor in combination with a second therapeutic agent in the preparation of a medicament for preventing and / or treating chronic gout.

[0024] In some embodiments, the chronic gout is chronic gouty arthritis.

[0025] In some embodiments, the second therapeutic agent is selected from one or more of allopurinol, febuxostat, tolfenpirant, benzbromarone, pegloticase, colchicine, etoricoxib, celecoxib, prednisone, and intra-articular injection.

[0026] The fifth aspect of the present application provides a pharmaceutical combination for preventing and / or treating chronic gout, comprising a first component and a second component; the first component is an SPP1 or SPP1-CD44 signaling axis inhibitor.

[0027] In some embodiments, the second component is selected from the group consisting of allopurinol, febuxostat, topiroxostat, benzobromarone, pegloticase, colchicine, etoricoxib, celecoxib, prednisone, one or more of intra-articular injections.

[0028] In some embodiments, the first component and the second component are administered simultaneously or sequentially.

[0029] In some embodiments, the chronic gout is chronic gouty arthritis.

[0030] Compared with the prior art, the beneficial effects of the present application are:

[0031] A specific predictive marker of chronic gouty arthritis is provided: by identifying SPP1 + / MMP9 + / CHI3L1 + Macrophages as a specific cell subpopulation of tophi formation fill the gap of the lack of reliable biomarkers in the prior art.

[0032] The molecular mechanism of tophi formation is elucidated: the role of SPP1-CD44 signaling axis-mediated macrophage-fibroblast interaction in joint fibrosis and osteochondral erosion is revealed, and SPP1 + The core function of macrophages.

[0033] A targeted treatment strategy is developed: based on the regulatory pathways of SPP1 + macrophages (such as TGF-β, integrin signaling), providing new targets for inhibiting tophi formation and joint damage.

[0034] In summary, the present application first identifies SPP1 + macrophages as a key marker and therapeutic target for chronic gout, and through single-cell and spatial transcriptomic technology, systematically analyzes its functional network in the microenvironment of tophi, providing a new direction for clinical prediction and intervention. BRIEF DESCRIPTION OF DRAWINGS

[0035] Other features, objects, and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments, made with reference to the accompanying drawings:

[0036] Figure 1 Technical flow chart showing single-cell RNA sequencing and spatial transcriptomics to identify immune and stromal cell features in different types of gout patients. Synovial fluid samples were collected from five intermittent gout patients without tophi, characterized by joint pain, redness, and monosodium urate (MSU) crystal deposits observed in the joint cavity. In addition, samples were collected from five patients with chronic gouty arthritis who were determined to have tophi in the joint cavity.

[0037] Figure 2 Display gout tophi formation related specific macrophage subpopulations. A graph-based unsupervised clustering method was used to assign a categorical label called cell subpopulation identifier to each cell, and 23 different macrophage subpopulations were identified Figure 2 A). Comparative analysis of cell composition showed that subpopulations M0, M6 and M9 were specifically present in the chronic gouty arthritis group, while subpopulations M1, M3 and M5 were specific to the intermittent gout group Figure 2 B, 2C). Cell developmental or differentiation trajectories were constructed Figure 2 D, left), pseudotemporal analysis showed that IGAMs were at the starting point and TGAMs were at the end point Figure 2 D, right). M0, M6 and M9 were identified as chronic gouty arthritis related macrophages (TGAMs), while M1, M3 and M5 were identified as intermittent related macrophages (IGAMs) Figure 2 E). Screening the most DEGs in TGAMs and IGAMs, two marker genes SPP1 and FOLR2 were found Figure 2 F). Based on the pathway enrichment analysis of DEGs in TGAMs subpopulations, several pathways related to gout pathogenesis (such as NF-κB, NLRP and TNF signaling pathways) and pathways related to chronic inflammation (such as osteoclast differentiation and IL-17 signaling) were found Figure 2 G). The expression of SPP1 and FOLR2 in macrophage subpopulations was detected, and the results showed that the expression pattern of SPP1 and FOLR2 was closely related to the distribution of TGAMs and IGAMs Figure 2 H). SPP1 + cells, and ECM regulatory genes such as MMP9 and CHI3L1 were elevated. In contrast, subpopulations M1, M3 and M5 were almost free of SPP1 + cells, mainly composed of FOLR2 high cells Figure 2 I). Re-evaluation of the expression levels of SPP1, FOLR2 and MMP9 in chronic gouty arthritis samples and intermittent gout samples confirmed the presence of a large number of SPP1 + MMP9 + macrophages in chronic gouty arthritis samples, while FOLR2 + macrophages were present in intermittent gout samples Figure 2 J).

[0038] Figure 2Pseudo-time distribution of macrophages and osteoclasts and DEGs enrichment results. The upper panel shows the pseudo-time distribution of macrophages and osteoclasts, and the enrichment analysis of differentially expressed genes (DEGs) up-regulated with pseudo-time; the lower panel shows the cell number distribution of each subtype and sample in pseudo-time analysis.

[0039] Figure 3 Flow cytometry verification of co-expression of SPP1, MMP9, CHI3L1 in chronic gouty arthritis.

[0040] Figure 4 DCI analysis results of the existence of potential macrophage-fibroblast intermediate state and SPP1 in the coronal area of tophi. Immunofluorescence staining was performed on tophi sections to detect fibroblast marker S100A4, macrophage marker CD68 and SPP1, and the results showed that the proportion of S100A4+SPP1+CD68+ triple positive cells in the coronal area increased Figure 5 A). Line graph analysis showed that S100A4 / CD68, S100A4 / SPP1, SPP1 / CD68 co-localization in the coronal area was significantly higher than that in the fibrovascular area Figure 5 B). To further explore SPP1 in TGAMs, SPP1 and CHI3L1 were used as seed nodes in the two pathways, and a difference causal inference (DCI) analysis was performed Figure 5 C). DCI analysis found that SPP1 formed a causal network with TGF-β signaling core factors Figure 5 C, upper panel). SPP1 formed a regulatory network with ECM-related receptors and structural molecules, suggesting its regulation of ECM remodeling Figure 5 C, lower panel).

[0041] Figure 5 SPP1 + Characteristics differences of TGAMs and peripheral blood mononuclear cells and their association with gout risk. Quality control and differential gene expression analysis were performed on the bulk RNA-seq data of peripheral blood mononuclear cells (PBMCs) of patients with gout onset (n=3) and healthy controls (n=6) Figure 6 A). Cross comparison of stage-specific genes in the SPP1+ TGAM subpopulation with genes that did not appear up-regulated during gout onset determined genes uniquely associated with tophi Figure 6 B). Genes such as SPP1, CHI3L1, LPL, MMP9 were significantly up-regulated only in TGAMs, with no changes in PBMCs during gout onset Figure 6 C). Enrichment analysis showed that genes related to lipid metabolism and leukocyte migration were up-regulated in TGAMs Figure 6 D). SPP1, CHI3L1 were positively correlated with key glycolytic enzyme PKM, suggesting metabolic reprogramming Figure 6E) Mendelian randomization analysis showed that elevated SPP1 expression was associated with increased risk of gout flare Figure 6 F, Figure 6 G).

[0042] Figure 6 ROC curve showing SPP1 as a diagnostic marker for gout. Based on preliminary analysis of the full population data, an ROC curve was plotted for SPP1 expression levels to diagnose gout. SPP1 had an AUC of 0.69 to diagnose gout, suggesting moderate predictive power as a screening marker for gout. DETAILED DESCRIPTION

[0043] So that the objects, technical solutions and advantages of the embodiments of the present application are more apparent, the technical solutions of the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the described embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0044] Unless otherwise defined, technical terms or scientific terms used herein should be understood as having the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0045] Sample collection and sequencing of Example 1

[0046] Figure 7 :

[0047] Single-cell RNA sequencing (scRNA-seq) was performed on synovial or tophus tissue from patients with gout in the intercritical phase (without tophi, i.e. early gout) and patients with chronic gouty arthritis, all of whom were diagnosed by arthroscopy. Spatial transcriptomic (ST) analysis was performed on the anatomical tophus coronal layer and fibrovascular layer corresponding to the scRNA-seq samples. The technical flow is shown in Sample collection The samples collected included tophus tissue surgically removed from 5 patients with chronic gouty arthritis and synovial tissue from 5 patients with intercritical gout. Since urate crystals have cytotoxic effects on cell activity, three samples with the highest cell activity were selected from each group for scRNA-seq.

[0048] Figure 1 :

[0049] Samples were rinsed with phosphate buffered saline (PBS), cut into small pieces (approximately 1 cubic millimeter), and then enzymatically digested with a cocktail of collagenase I (1 mg / ml), collagenase II (1 mg / ml), hyaluronidase (60 units / ml), liberase (10 units / ml), and DNase I (0.02 mg / ml) for 90 minutes at 37 °C with constant agitation.

[0050] After digestion, samples were passed through 100-micron and 40-micron cell strainers and centrifuged at 300 x g for 5 minutes. The pelleted cells were suspended in red blood cell lysis buffer (Gibco) to lyse the red blood cells, washed with DPBS containing 0.5% BSA, and then resuspended for staining and counting.

[0051] Single-cell RNA sequencing (scRNA-seq) libraries were prepared using Chromium instrument and SingleCell3' Reagent Kit V3.1 (10X Genomics). Cell suspensions were loaded onto single-cell 3' chips with gel beads for partitioning and barcoding. RNA from barcoded cells was reverse transcribed and then sequencing libraries were built according to the manufacturer's protocol. Sequencing was performed using Illumina platforms (HiSeq2000 or NovaSeq) following the manufacturer's instructions.

[0052] Single-cell RNA sequencing (scRNA-seq) :

[0053] Fresh tophi tissues (i.e., chronic gouty arthritis pathological tissues) were excised, rinsed with pre-chilled PBS or normal saline, and then blotted dry with gauze. The tissues were then embedded in OCT, cooled on dry ice, and stored at -80 °C. The OCT-embedded samples were cut into 10-20-micron-thick sections, RNA was extracted using a nucleic acid extraction kit, and RNA quality was assessed by RIN value. Hematoxylin-eosin (H&E) staining was performed to assess tissue morphology, and only samples with RIN value > 7 and intact morphology were included for further analysis.

[0054] The optimal permeabilization time was subsequently determined using the 10X Genomics Tissue Optimization Kit. The re-sectioned samples were subjected to capture labeling, including tissue stitching, fixation, H&E staining, permeabilization, cDNA synthesis, amplification, and sequencing library construction. The spatial transcriptome libraries were subjected to quality control prior to sequencing on the Illumina NovaSeq PE150 platform.

[0055] Example 2 Identification of SPP1 + / MMP9 + / CHI3L1 + Macrophages as a specific cell subset for tophi formation

[0056] Macrophages play a crucial role in gout attacks and chronic gout. Therefore, a graph-based unsupervised clustering method was used to assign a classification label, called a cell subcluster identifier, to each cell, identifying 23 distinct macrophage subclusters. Spatial transcriptomics (ST) A). Comparative analysis of cell composition showed that the M0 (p<0.0001), M6 (p<0.0001), and M9 (p<0.001) subsets were specific to the chronic gouty arthritis group, while the M1 (p<0.05), M3 (p<0.001), and M5 (p<0.01) subsets were specific to the intercritical gout group. Figure 2 (B and 2C).

[0057] Next, their sequence is predicted along one or more virtual timelines to construct a trajectory of cell development or differentiation. Figure 2 D, left). Consistent with the unsupervised clustering results, cells of M1, M3, M5, and intercritical gout occupied the starting point of the pseudo-time trajectory, while cells of gout, especially M0, M6, and M9, were located at the ending point (D, left). Figure 2 D, right). Therefore, M0, M6, and M9 were identified as gout-associated macrophages (TGAMs), while M1, M3, and M5 were identified as intercritical gout-associated macrophages (IGAMs). Figure 2 E).

[0058] Differentially expressed genes (DEGs) were screened in TGAMs and IGAMs. Notably, among the top 10 DEGs, the inventors identified two marker genes, SPP1 and FOLR2, which have recently been considered to represent mutually exclusive macrophage classifications. Figure 2 F). Then, pathway enrichment analysis was performed using deg from the TGAMs subclusters (F). Figure 2 G). This analysis identified several pathways previously involved in gout pathogenesis in TGAMS, including the NF-κB, NLRP, and TNF signaling pathways (G). Figure 2 G). Furthermore, pathways associated with chronic inflammation, such as osteoclast differentiation and IL-17 signaling, were identified. Figure 2 G).

[0059] The roles of SPP1 and FOLR2 in different gout phenotypes and their biological significance in gout development require further investigation. To explore this, the expression of SPP1 and FOLR2 in macrophage subsets was examined. The results showed that the expression patterns of SPP1 and FOLR2 were closely related to the distribution of TGAms and IGAms. Figure 2 H). SPP1 in subgroups M0, M6, and M9 +Cell proportion is highest, and ecm-regulating genes such as MMP9 and CHI3L1 are elevated. In contrast, subpopulations M1, M3 and M5 contain almost no SPP1 + Cells, mainly composed of FOLR2high cells Figure 2 I). Furthermore, the expression levels of SPP1, FOLR2 and MMP9 in chronic gouty arthritis and intercritical samples were re-evaluated, confirming the significant presence of SPP1 + MMP9 + Macrophages, FOLR2 is significantly present in samples of intercritical gout patients + Macrophages Figure 2 J).

[0060] At the same time, to verify the differentiation relationship between macrophages and osteoclasts, the inventors performed a pseudotime analysis on all macrophage and osteoclast populations and identified genes that have significant expression changes along the pseudotime trajectory Figure 2 , top left). These genes can drive changes in cell differentiation or function. Further analysis showed that these genes are enriched in processes related to oxidative phosphorylation, arthritis and reactive oxygen species Figure 2 , top right). Moreover, the pseudotime distribution of these cells showed that IGAMs occupy the starting point and TGAMs are at the end Figure 3 , bottom).

[0061] Example 3 Clinical sample detection validation and clinical database validation

[0062] 3.1 Flow cytometry detection Figure 3 ):

[0063] CD68 + cells isolated from gout digested joint tissues and gout digested joint tissues were subjected to flow cytometry detection to validate the co-expression of SPP1, MMP9 and CHI3L1. The results showed that, compared with the intercritical gout group, the proportion of SPP1 + CHI3L1 + , SPP1 + MMP9 + and CHI3L1 + MMP9 + macrophage subpopulations was significantly increased Figure 3 ). There was also a strong correlation in the expression of SPP1, MMP9 and CHI3L1 in macrophages. Specifically, the proportion of these double-positive populations in chronic gouty arthritis samples reached about 2.74%, 0.75% and 0.53%, respectively, which was significantly higher than that in intercritical gout samples, where each subset accounted for less than 0.50%.

[0064] 3.2 Immunofluorescence validation

[0065] The inventors also found that SPP1 + / MMP9 + / CHI3L1 + has a particular association with joint fibrosis. Next, the inventors performed immunofluorescence staining of S100A4, a classical fibroblast marker, CD68 as a macrophage marker, and SPP1 in a series of sections of tophi. Notably, the corona zone, close to the tophus core, showed an elevated proportion of triple+ staining (S100A4 + SPP1 + CD68 + ), suggesting a potential macrophage-fibroblast intermediate state. In contrast, co-expression of these markers was weaker and rarely co-expressed in the fibrovascular zone ( Figure 4 A). Cell lineage analysis showed that these markers co-localized significantly within cells, with Mander's coefficients of S100A4 / CD68, S100A4 / SPP1, and SPP1 / CD68 being significantly higher in the corona zone than in the fibrovascular zone ( Figure 4 B). These findings provide spatial and protein level evidence supporting the potential of a migratory cell population to bridge TGAMs and TGAF-2 fibroblasts in the topographical microenvironment.

[0066] To further explore the role of SPP1 in TGAMs and TGAF-2 functions, the inventors performed differential causal inference (DCI) analysis using SPP1 and CHI3L1 as seed nodes in these two pathways. In the TGF-beta signaling module, SPP1 and CHI3L1 exhibited reconnected causal relationships with core regulators such as SMAD3, TGFB1, TGFBR1, and ALKBH5. Notably, SPP1 emerged as a central hub, receiving upstream input from SMAD7 and exerting influence on downstream SMAD3 family members, suggesting that SPP1 might play a role in modulating canonical TGF-beta transcriptional output ( Figure 5 C, top panel). In the ecm receptor interaction network, SPP1 was highly integrated into the regulatory structure, forming directional edges with matrix-associated receptors (CD44, SDC1) and structural components (FN1, COL1A1, COMP). The directionality of these edges suggests that SPP1 might be an upstream modulator of ECM assembly and remodeling ( Figure 5 C, bottom panel).

[0067] 3.3 Clinical correlation analysis

[0068] While the inventors have previously identified SPP1+ TGAMs in gout tophi, the inventors further explored the specificity of their gene expression profile. Thus, after quality control and differential gene expression analysis, bulk RNA-seq data of peripheral blood mononuclear cells (PBMCs) from gout flares patients (n=3) and healthy controls (n=6) were analyzed Figure 5 A). The inventors then cross-compared stage-specific genes in the TGAMs subpopulation with genes that did not exhibit upregulation during gout flares to determine those uniquely associated with gout tophi complex + TGAMs subpopulation with genes that did not exhibit upregulation during gout flares to determine those uniquely associated with gout tophi complex Figure 5 B).

[0069] SPP1, CHI3L1, LPL and MMP9 among others remained unchanged or downregulated during gout flares, but their expression was significantly increased in the three TGAMs subpopulations. Notably, these genes did not show significant changes between gout flares and healthy controls, suggesting a unique cellular microenvironment in gout tophi Figure 6 C). Further enrichment analysis showed different patterns compared to previous TGAMs DEG enrichment. Specifically, SPP1 + TGAMs were significantly upregulated, as were genes associated with leukocyte transendothelial migration Figure 6 D). These findings highlight potential targets for further exploration of this subpopulation. Subsequently, the inventors analyzed the co-expression correlation of SPP1 and CHI3L1 with PKM, a key enzyme in glucose metabolism, and found that SPP1 and CHI3L1 were positively correlated with PKM, especially in M6 Figure 6 E). These results suggest a potential link between these three genes and possible metabolic reprogramming in TGAMs.

[0070] To validate the potential link between SPP1 expression and gout development, the inventors performed Mendelian randomization (MR) analysis. The scatter plot shows that a one standard deviation increase in SPP1 expression is associated with a 0.6% increase in the risk of gout flares (p = 1.274 x 10"(negative variance), 1.750 x 10"(median), 4.263 x 10"(simple pattern), 7.636 x 10"(weighted pattern)) Figure 6 F). Additionally, leave-one-SNP-out plots were used to estimate the MR effect size of SPP1 expression on gout, using it as an instrumental variable in the analysis Figure 6 G).

[0071] 3.4 Clinical database analysis to specify diagnostic strategies

[0072] Further based on the clinical follow-up data of UK Biobank, the effectiveness and applicability of SPP1 as a diagnostic biomarker for chronic gouty arthritis are systematically evaluated. The specific method includes:

[0073] Sample screening:

[0074] Patients with a clear diagnosis of gout (ICD-10 code M10) recorded, healthy population and corresponding follow-up information are included, and individuals with severe missing data or concurrent other inflammatory diseases (such as viral hepatitis, etc.) are excluded;

[0075] Data processing:

[0076] Extract the SPP1 protein expression level during the patient follow-up period, the first and multiple gout diagnosis records, and key clinical variables (such as age, gender, BMI, etc.);

[0077] Definition of chronic gouty arthritis:

[0078] Combined with the information of diagnosis interval and diagnosis times, the patients with chronic gouty arthritis (such as at least 2 times of gout diagnosis within 1 year of follow-up) are defined;

[0079] Statistical analysis:

[0080] Draw the receiver operating characteristic (ROC) curve of SPP1 expression level in diagnosing chronic gouty arthritis in patients with gout; draw the ROC curve of SPP1 expression level in diagnosing gout patients. Use multiple statistical and machine learning methods to construct diagnostic models, and use random division of training set and test set, five-fold cross-validation, etc. Calculate the area under the curve (AUC), sensitivity, specificity, confidence interval, etc.

[0081] Through the above method, the clinical value and application prospect of SPP1 in the diagnosis of chronic gouty arthritis and other diseases are determined, and solid data support is provided for the development of related diagnostic kits or equipment.

[0082] The preliminary analysis results are shown in Figure 6 Figure 6 Figure 7 Based on the preliminary analysis of the whole population data, the ROC curve of SPP1 expression level in diagnosing gout is drawn. The AUC of SPP1 in diagnosing gout is 0.69, indicating that it has moderate predictive power as a gout screening marker. However, this result has limitations due to the lack of disease stage differentiation. The follow-up plan is to develop a comprehensive model combining clinical indicators and SPP1 expression level to achieve the effect of screening for chronic gouty arthritis and gout in gout patients. The follow-up plan is to accurately mine database information, define the characteristics of chronic gouty arthritis, and construct an integrated model of SPP1 combined with clinical indicators (serum uric acid, BMI, etc.) to achieve accurate diagnosis of chronic gouty arthritis.

[0083] Example 4 Targeted therapy strategy

[0084] Target selection: SPP1 + Macrophages and its key pathways (SPP1-CD44, TGF-β, IL-17 signaling)

[0085] Inhibitor development:

[0086] 1) AlphaFold fitting SPP1 tertiary structure.

[0087] SPP1 is an intrinsically disordered protein, meaning it lacks a stable three-dimensional structure under physiological conditions, with high flexibility and dynamics. This characteristic makes it difficult to resolve the complete structure of SPP1 through traditional methods such as X-ray crystallography or cryo-electron microscopy. Therefore, there is currently no experimentally resolved structure of the complete SPP1 protein in the PDB (Protein Data Bank).

[0088] Query UniProt for the AA sequence of SPP1, perform spatial structure prediction using the AlphaFold model.

[0089] 2) MTiOpenScreen screening candidate small molecule drugs / compounds

[0090] Convert the output results into PDB format, input MTiOpenScreen, set parameters, and perform screening based on five databases: Diverse-lib and iPPI-lib (target protein interaction-focused compounds), Drugs-lib (approved drugs available for purchase), FOOD-lib (food composition compounds), and NP-lib (natural product compounds).

[0091] Each of the five databases screens out the Top100 small molecules with the highest drug development potential (the comparison standard is the binding energy of the small molecule to SPP1, the lower the better).

[0092] Top three small molecules in the database:

[0093] Drugs-lib: Tradipitant (second-generation neurokinin-1 (NK-1) receptor antagonist, predicted binding energy -7.6 kcal / mol), Teniposide (chemotherapy drug, topoisomerase inhibitor, mainly used to treat childhood acute lymphoblastic leukemia, predicted binding energy -7.6 kcal / mol), Etoposide (chemotherapy drug, topoisomerase inhibitor, treats various cancers, predicted binding energy -7.6 kcal / mol)

[0094] FOOD-lib: Cepagenin (predicted binding energy -8.1 kcal / mol), Betulinic_acid (predicted binding energy -7.8 kcal / mol), Acetylursolic_acid (predicted binding energy -7.8 kcal / mol; Ursolic acid is a component of SPP1-targeting drug adopted in a published paper, Zheng, Y. et al. Ursolic acid targets secreted phosphoprotein 1 to regulate Th17 cells against metabolic dysfunction-associated steatotic liver disease. Clin Mol Hepatol 30, 449-467 (2024), https: / / doi:10.3350 / cmh.2024.0047.)

[0095] The results from the other three databases include MolPort-019-936-959 (C41H66O14, predicted binding energy -7.7 kcal / mol); and some reaction intermediates such as 137276043_Intermediate (predicted binding energy -7.4 kcal / mol).

[0096] Based on the database screening results, subsequent plans to select representative small molecules for gouty tophi organoid model pharmacodynamic evaluation experiments.

[0097] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be regarded as exemplary and non-limiting in any respect, and the scope of the present application is defined by the appended claims rather than the above description, and it is intended to encompass all variations falling within the meaning and scope of the equivalent elements of the claims. Any reference signs in the claims should not be regarded as limiting the claims involved.

[0098] In addition, it should be understood that although the present specification is described in terms of embodiments, not every embodiment contains only one independent technical solution, and the description of the specification in this way is only for the sake of clarity, and those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that those skilled in the art can understand.

Claims

1. Application of SPP1 or SPP1-positive macrophages as biomarkers in the preparation of diagnostic reagents for chronic gout.

2. The application according to claim 1, wherein the chronic gout is chronic gouty arthritis.

3. The application according to claim 1 or 2, wherein the SPP1-positive macrophages include SPP1. + CHI3L1 + Macrophages or SPP1 + MMP9 + Macrophages.

4. The application according to any one of claims 1-3, wherein the test sample is synovial tissue or tophi tissue.

5. The application according to any one of claims 1-4, wherein the reagent detects the transcriptional level of SPP1 by a combination of one or more methods selected from quantitative PCR and high-throughput sequencing, and / or the reagent detects the level of the protein by a combination of one or more methods selected from BCA protein quantification, immunofluorescence, Western blotting, and proteomics, and / or the reagent detects the level of SPP1-positive macrophages by flow cytometry or FISH technology.

6. A reagent kit for the diagnosis of chronic gouty arthritis, characterized in that, The kit includes reagents for detecting the level of SPP1 or SPP1-positive macrophages in the subject's tissues and, optionally, instructions for use; preferably, the reagents detect the transcriptional level of SPP1 using a combination of one or more methods selected from quantitative PCR and high-throughput sequencing, and / or the reagents detect the level of the protein using a combination of one or more methods selected from BCA protein quantification, immunofluorescence, Western blotting, and proteomics, and / or the reagents detect the level of SPP1-positive macrophages using flow cytometry or FISH technology; preferably, the instructions for use describe the criteria for diagnosing chronic gout based on the detection level of SPP1 or SPP1-positive macrophages in the subject's tissues; preferably, the chronic gout is chronic gouty arthritis.

7. The use of SPP1 or SPP1-CD44 signaling axis inhibitors in the preparation of medicaments for the prevention and / or treatment of chronic gout; preferably, the chronic gout is chronic gouty arthritis.

8. The application according to claim 7, wherein the drug is selected from one or more of antibodies, CRISPR-CAS gene editing systems, small molecule inhibitors, AAV vectors, and small interfering RNA; preferably, the small molecule drug is selected from Traditant, Teniposide, Etoposide, Cepagenin, Betulinic acid, Acetylursolic acid, and MolPort-019-936-959 (C41H66O14).

9. The use of SPP1 or SPP1-CD44 signaling axis inhibitors in combination with a second therapeutic agent in the preparation of a drug for the prevention and / or treatment of chronic gout; preferably, the chronic gout is chronic gouty arthritis; preferably, the second therapeutic agent is selected from one or more of allopurinol, febuxostat, topipirostat, benzbromarone, polyethylene glycol uricase, colchicine, etoricoxib, celecoxib, prednisone, and intra-articular injection.

10. A combination of medicines for the prevention and / or treatment of chronic gout, characterized in that, The formulation includes a first component and a second component; the first component is an SPP1 or SPP1-CD44 signaling axis inhibitor; preferably, the second component is selected from one or more of allopurinol, febuxostat, topipirostat, benzbromarone, polyethylene glycol uricase, colchicine, etoricoxib, celecoxib, prednisone, and intra-articular injection; preferably, the first component and the second component are administered simultaneously or sequentially; preferably, the chronic gout is chronic gouty arthritis.

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