Marker for evaluating curative effect of hydroxychloroquine on treating IgA nephropathy and application of marker

Abstract

The invention belongs to the technical field of biological medicines, and particularly relates to a marker for evaluating the curative effect of hydroxychloroquine on treating IgA nephropathy and application of the marker. The marker for evaluating the curative effect of the hydroxychloroquine on the IgA nephropathy is a combination of any one or any two or any three or any four or five of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine. Based on the five markers, a combined prediction model is constructed, the model shows relatively high prediction performance, and an early-stage non-invasive screening method can be provided for clinic and is used for identifying IgAN patients with potential HCQ treatment ineffectiveness.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and specifically relates to a marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy and its application. Background Art

[0002] Immunoglobulin A (IgA) nephropathy is one of the most common primary glomerular diseases worldwide. It is characterized by the deposition of IgA in the glomerular mesangium, leading to inflammation and progressive renal impairment. The clinical manifestations of this disease vary, ranging from asymptomatic hematuria to rapidly progressive renal failure. Although some patients experience slow progression, approximately 30%-40% of patients develop end-stage renal disease within 20-30 years, requiring dialysis or kidney transplantation.

[0003] Currently, the treatment strategies for IgA nephropathy mainly include blood pressure control, proteinuria management, and immunosuppressive therapy. However, the efficacy of traditional treatments is limited, and there are large individual differences. Hydroxychloroquine, as an immunomodulator, has been used to treat IgA nephropathy in recent years and has shown certain clinical efficacy. However, there are significant individual differences in patients' response to hydroxychloroquine. Some patients may experience complete remission, while others have no obvious effect or even experience side effects. Currently, there is a lack of effective methods and markers in the clinic to predict patients' response to hydroxychloroquine, resulting in a lack of precision in the selection of treatment options.

[0004] Metabolomics, a new omics technology developed after proteomics, utilizes advanced analytical instruments with high separation efficiency, high sensitivity, and low detection limits to analyze the dynamic changes of small endogenous metabolites in organisms to elucidate the physiological and pathological trends of the body as a whole. It has wide applications in qualitative and quantitative analysis of disease progression and drug-effect relationships. Therefore, metabolomics-based analytical methods provide new ideas for screening IgA nephropathy patients sensitive to hydroxychloroquine treatment.

[0005] However, the existing screening technology methods still have the following defects and shortcomings: 1) Lack of specific markers: Existing studies mostly focus on a single type of biomarker, and lack systematic research on small molecule markers such as amino acid metabolites. 2) Technical limitations: Traditional detection methods such as enzyme-linked immunosorbent assay (ELISA) technology have low detection accuracy and low sensitivity, making it difficult to detect low-abundance amino acid metabolites; and the test results are affected by many factors, and false positive or false negative results may occur; in addition, ELISA technology can only detect specific antigens or antibodies, and cannot detect complex antigen-antibody complexes; ELISA technology is complicated to operate, and the operation process needs to be strictly controlled, and it is easy to be affected by the external environment and make errors. 3) Insufficient clinical application: Existing marker screening methods mostly remain in the laboratory stage, and lack standardized and automated detection systems.

[0006] Therefore, developing a metabolomics-based marker and screening method to predict the therapeutic efficacy of hydroxychloroquine is of great significance for achieving personalized treatment of IgA nephropathy, improving treatment effects, and reducing unnecessary drug exposure. Summary of the Invention

[0007] The purpose of the present invention is to provide a marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy and its application, so as to achieve individualized treatment of IgA nephropathy, improve the treatment effect and reduce unnecessary drug exposure.

[0008] To this end, the present invention provides the following technical solutions.

[0009] The first aspect of the present invention provides a marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy, wherein the marker is any one of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine, or any two of them, or any three of them, or any four of them, or a combination of five of them.

[0010] In a preferred embodiment of the present invention, the marker is a combination of five markers including D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine.

[0011] In a preferred embodiment of the present invention, the marker is derived from the urine of the subject.

[0012] A second aspect of the present invention provides the use of a marker as described above in a study of hydroxychloroquine use for non-therapeutic purposes.

[0013] The third aspect of the present invention provides a use of a reagent for detecting the expression level of the marker as described above in the preparation of a reagent for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy or a drug sensitivity detection reagent.

[0014] In a preferred embodiment of the present invention, the reagent for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy or the reagent for drug sensitivity detection is a reagent for evaluating the efficacy or drug sensitivity detection of hydroxychloroquine in the process of treating IgA nephropathy.

[0015] In a preferred embodiment of the present invention, the sample for drug efficacy evaluation or drug sensitivity testing is urine of the subject.

[0016] In a preferred embodiment of the present invention, the reagent determines the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, and turbidimetry.

[0017] The fourth aspect of the present invention provides a kit for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy, comprising a reagent for detecting the expression amount of a marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy as described above.

[0018] In a preferred embodiment of the present invention, the detection is a quantitative detection of the marker level in the subject's urine.

[0019] In a preferred embodiment of the present invention, the reagent determines the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, and turbidimetry.

[0020] In a preferred embodiment of the present invention, the kit is an ELISA kit.

[0021] A fifth aspect of the present invention provides a method for evaluating whether hydroxychloroquine can prevent or treat IgA nephropathy, comprising using any one of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine, or any two of them, or any three of them, or any four of them, or five of them as markers to evaluate the effect of hydroxychloroquine.

[0022] The sixth aspect of the present invention provides a method for screening compounds capable of preventing or treating IgA nephropathy, comprising using any one of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine, or any two of them, or any three of them, or any four of them, or five of them as markers to evaluate the effect of the compound.

[0023] A seventh aspect of the present invention provides a hydroxychloroquine efficacy analysis system for IgA nephropathy, comprising: Target expression detection device: used to detect the expression level of the markers mentioned above in the sample; The sample is the subject's urine; Drug efficacy analysis device: Determines the drug efficacy for IgA nephropathy based on the expression level of markers; Result output device: used to output the results obtained by the drug efficacy analysis device.

[0024] In a preferred embodiment of the present invention, the reagents used in the target expression detection device determine the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near-infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, and turbidimetry.

[0025] An eighth aspect of the present invention provides a use of a drug for inhibiting the expression of the aforementioned marker in the preparation of a pharmaceutical composition for treating IgA nephropathy, wherein the pharmaceutical composition contains hydroxychloroquine.

[0026] A ninth aspect of the present invention provides a pharmaceutical composition for treating IgA nephropathy, comprising hydroxychloroquine and a drug that inhibits the expression of the markers described above.

[0027] By means of the above technical solution, the present invention has at least the following advantages: The present invention combines metabolomics data to screen out a combination of biomarkers associated with hydroxychloroquine treatment response, and by detecting the content of biomarkers, it can accurately evaluate the efficacy of hydroxychloroquine in treating IgA nephropathy. In one aspect, the present invention utilizes the high sensitivity and high specificity of LC-MS / MS technology to achieve accurate detection of low-abundance biomarkers; in another aspect, the present invention also uses advanced machine learning algorithms to construct an efficient prediction model to improve the accuracy of marker screening and efficacy prediction. Finally, the present invention also develops a standardized detection system to promote the transformation of biomarker screening methods from laboratory research to clinical application. The present invention is expected to provide IgA nephropathy patients with a non-invasive, early, and accurate method for predicting the efficacy of hydroxychloroquine treatment, thereby promoting the development of personalized medicine.

[0028] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A flow chart of a method for screening markers for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy based on metabolomics analysis provided in an embodiment of the present invention is shown; Figure 2 The figure shows the changes in 24-hour urine protein and eGFR before and after treatment of patients in the hydroxychloroquine treatment effective group and the ineffective group; among them, A is the change in 24-hour urine protein before and after treatment of the hydroxychloroquine treatment effective group, B is the change in 24-hour urine protein before and after treatment of the hydroxychloroquine treatment ineffective group; C is the change in eGFR before and after treatment of the hydroxychloroquine treatment effective group; D is the change in eGFR before and after treatment of the hydroxychloroquine treatment ineffective group; Figure 3 The ion chromatograms of the standard solution and the urine sample extraction are shown; wherein A is the ion chromatogram extracted from the standard solution; B is the ion chromatogram extracted from the sample to be tested; Figure 4 The PCA and OPLS-DA analysis diagrams of the urine amino acid metabolic profiles of the hydroxychloroquine treatment effective group and the ineffective group are shown; wherein A is the PCA score diagram; B is the OPLS-DA score diagram; C is the OPLS-DA permutation test diagram; Figure 5 The volcano plot and heat map of the differentially expressed amino acids in urine screening of the hydroxychloroquine treatment effective group and the ineffective group are shown; A is the volcano plot analysis; B is the hierarchical cluster analysis heat map; Figure 6 The figure shows the KEGG enrichment analysis diagram of differentially expressed amino acids in urine screening of the hydroxychloroquine treatment effective group and the ineffective group, wherein A is the differential amino acid enrichment analysis diagram; B is the differential abundance score analysis diagram; Figure 7 The diagram shows the metabolic pathway analysis of differentially expressed amino acids in urine screening of the hydroxychloroquine treatment effective group and the ineffective group; wherein A is a bubble diagram analysis; B is a pathway enrichment rectangular tree diagram analysis; Figure 8 Shown are ROC curves for single amino acid prediction performance evaluation; wherein A is the ROC curve for D-ornithine; B is the ROC curve for L-arginine; C is the ROC curve for L-cysteine; D is the ROC curve for L-cystine; and E is the ROC curve for D-cysteine. Figure 9 The ROC curves of the performance evaluation of the five amino acid joint prediction models are shown; among them, A is the ROC curve of model I; B is the performance of model I in the training set and the validation set; C is the ROC curve of model II; D is the performance of model II in the training set and the validation set; E is the ROC curve of model III; F is the performance of model III in the training set and the validation set. DETAILED DESCRIPTION

[0030] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0031] Example 1: Screening of markers 1. Experimental Methods like Figure 1 As shown, in this embodiment, a screening process for markers is shown, which includes: S1: Collection, treatment, grouping and acquisition of test samples of patients with primary IgA nephropathy; S2: Processing of test samples and acquisition of LC-MS / MS spectral data; S3: Processing of LC-MS / MS data, screening of differentially expressed amino acids, and search for biomarkers; S4: Use metabolomics-related databases and network software to construct biomarker metabolic pathways and perform predictive analysis; S5: ROC curve was used to evaluate the ability of biomarkers to predict the efficacy of hydroxychloroquine.

[0032] The following details: 1.1 Collection, treatment, grouping, and acquisition of test samples for primary IgA nephropathy patients The trial subjects were patients with primary IgA nephropathy collected from Nanjing Drum Tower Hospital from June 1, 2023 to May 31, 2024. According to the inclusion and exclusion criteria, a total of 60 patients met the criteria and were included in the observation, including: 1) Inclusion criteria are: A. Age 18-75 years, diagnosed with primary IgA nephropathy by pathological examination (light microscopy + electron microscopy); B. Estimated glomerular filtration rate (eGFR) > 30 mL / (min•1.73 m 2 ); C. 24-hour urine protein remains between 0.75 and 3.5 g despite receiving maximal doses of a renin-angiotensin-aldosterone system inhibitor (RAASi) for at least 3 months; D. Treatment with hydroxychloroquine alone.

[0033] 2) Exclusion criteria are: A. Secondary IgA nephropathy; B. Use of glucocorticoids or other immunosuppressants in the past 3 months; C. Currently or planning to be pregnant or breastfeeding; D. Treatment with hydroxychloroquine is contraindicated.

[0034] Subsequently, 60 subjects were treated with hydroxychloroquine for at least 6 months. Patients who dropped out during follow-up were excluded. Among them, 1 patient decided not to use hydroxychloroquine, 3 patients switched to hormones and other immunosuppressants, 2 patients developed diarrhea, and 3 patients had poor treatment compliance. Ultimately, 51 subjects were included in the final data analysis as the discovery cohort for the marker. Of these 51 subjects, 27 were in the treatment-effective group and 24 were in the treatment-ineffective group. Their clinical information is shown in Table 1.

[0035] The hydroxychloroquine dosage for the above subjects is: for eGFR ≥ 60mL / (min•1.73m 2 ), the dose is 0.2g twice a day; for eGFR 45 to 59mL / (min•1.73m 2 ), the dose is 0.1g, 3 times a day; for eGFR 30-44mL / (min•1.73m 2 ), the dose is 0.1 g twice a day; if the eGFR decreases by 25% or is less than 30 mL / (min•1.73m 2 The dose was reduced to 0.1g per day. Efficacy was assessed after 6 months of treatment and patients were divided into an effective group and an ineffective group. The effective group was defined as patients with a 24-hour urine protein count <500mg or a 50% or greater decrease in 24-hour urine protein from baseline after 6 months of treatment.

[0036] Table 1 Baseline clinical data of patients in the hydroxychloroquine treatment effective group and the ineffective group Urine samples were collected from the 51 subjects, including baseline urine before drug intervention and urine after 6 months of hydroxychloroquine treatment. All urine samples were mid-morning urine, with a sample volume of approximately 5 mL. The collected urine samples were centrifuged at 1000 rpm and 4°C for 5 minutes. After centrifugation, they were filtered through a 0.22 μm filter membrane. The supernatant was aliquoted into centrifuge tubes, 2 mL per tube, and frozen at -80°C for subsequent analysis.

[0037] 1.2 Sample processing and LC-MS / MS spectral data acquisition Thaw the frozen urine samples collected above at room temperature or 4°C. After thawing, transfer an appropriate amount of urine (e.g., 1 mL) to a centrifuge tube and centrifuge at 10,000 × g for 10 minutes to remove insoluble particles. Depending on the concentration of the target analyte, dilute the urine sample with ultrapure water or a mobile phase (e.g., 0.1% formic acid in water). Finally, filter the sample through a 0.22 μm microporous membrane and analyze it using an ultra-high-performance liquid chromatography system (Thermo Vanquish UHPLC System (Thermo Fisher)) coupled with a triple quadrupole mass spectrometer (Thermo Altis TSQ Plus (Thermo Fisher)) for LC-MS / MS analysis, acquiring the corresponding LC-MS / MS spectral data.

[0038] LC-MS / MS conditions: Liquid chromatography conditions were: a C18 reversed-phase column (e.g., 2.1 × 50 mm, 1.8 µm), an injection volume of 5–10 µL, a column temperature of 40°C, and a run time of 30 min. Mobile phase A consisted of 0.1% formic acid in water, and mobile phase B consisted of 0.1% formic acid in acetonitrile, with a flow rate of 0.3 mL / min. Elution conditions are shown in Table 2. Mass spectrometry conditions were: an electrospray ionization source, alternating between positive and negative ion modes to obtain more comprehensive metabolite profiles. The ion source temperature was 500°C, the spray voltage was 5500 V (positive ion mode) or -4500 V (negative ion mode), the curtain gas was 30 psi, the nebulizer gas was 50 psi, and the auxiliary gas was 50 psi.

[0039] Table 2 Chromatographic gradient conditions 1.3 LC-MS / MS Data Processing, Screening of Differentially Expressed Amino Acids, and Searching for Biomarkers Statistical methods were used to process and perform pattern recognition on the LC-MS / MS data obtained above to screen out urine metabolomics biomarkers in IgA nephropathy patients that are sensitive to HCQ treatment, including: Data acquisition was performed using Xcalibur software (version 4.4.16.14, Thermo Fisher), and quantitative analysis was performed using Skyline software. Data preprocessing and statistical analysis were performed primarily with R, SPSS (version 26.0), and SIMCA (version 16.0.2, Sartorius Stedim Data Analytics AB, Umea, Sweden). SIMCA software was used for logarithmic (log) transformation and CTR formatting, followed by principal component analysis. The principal component analysis (PCA) method for unsupervised pattern recognition and the orthogonal partial least squares discriminant analysis (OPLS-DA) method for supervised pattern recognition were used for discriminant analysis. In order to avoid overfitting of the test model and evaluate the statistical significance of the model, the parameter values ​​such as R2X, R2Y, and Q2 were used to evaluate the model quality. The closer R2X and R2Y were to 1, the more stable the model was, and Q2>0.5 indicated a high prediction rate. According to the variable weight value (VIP) obtained by the OPLS-DA model, the variables with VIP values ​​greater than 1 were selected as candidate variables for biomarkers. In order to verify the multidimensional The T test was used to determine whether the candidate variables found in the statistics had significant differences in unit statistics, with P < 0.05 indicating a significant difference. Combining the heat map with the screened candidate variables, the mass spectrometry information of the compounds represented by these variables was used to search, match, and infer in databases such as HMDB, KEGG, and PubChem to ultimately determine possible biomarkers. All data were statistically analyzed and processed using SPSS (version 26.0). The data for each group were expressed as (Mean ± SD), and the differences between groups were determined using two independent sample t tests or Mann-Whitney U tests.

[0040] 1.4 Use metabolomics-related databases and network software to construct metabolic pathways of biomarkers and conduct predictive analysis The metabolic profiles of the urine biomarkers identified above were entered into the MetaboAnalyst 5.0 dialog box. The metabolite names were selected in the Input tab, and the Submit button was clicked. The species was selected as Homo sapiens (human). Comprehensive analysis of the pathways in which the differentially expressed metabolites were located (including enrichment and topological analyses) was performed. Signaling pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (http: / / www.kegg.jp / ) database. Metabolite molecular annotations, associated enzymes or transporters, and their properties were analyzed using the HMDB (The Human Metabolome Database; http: / / www.hmdb.ca / ) database. Metabolic Pathway Analysis (MetPA) web software (MetaboAnalyst 5.0) was used to visualize metabolite pathways, such as bubble plots. Furthermore, to facilitate a more diverse display of metabolic level changes across samples, pathway enrichment bubble plots can be converted into pathway enrichment dendrograms. Pathway Impact and enrichment P value (Fisher's exact test) were calculated, and pathways with Impact > 0.1 and P < 0.05 were screened.

[0041] 1.5 Using ROC curves to evaluate the ability of biomarkers to predict the efficacy of hydroxychloroquine Differential amino acids identified through metabolic pathway enrichment analysis were selected as candidate biomarkers. Due to the large variability in amino acid metabolite concentrations, to facilitate clinical interpretation and application, each metabolite was transformed and then a logistic regression model was constructed to assess the association between amino acids and hydroxychloroquine efficacy. Model goodness of fit was assessed using the Hosmer-Lemeshow test and calibration plots. The predictive performance of univariate models was evaluated by plotting receiver operating characteristic (ROC) curves. Combined prediction models were constructed for each amino acid. The area under the ROC curve (AUC) was calculated using ROC curves to compare the sensitivity, specificity, and overall accuracy of the univariate and combined models. K-fold cross-validation was used to assess model stability and generalization. Ultimately, based on statistical indices and biological significance, single metabolites or metabolite combinations were identified as the best predictors of hydroxychloroquine efficacy. The ROC curve is plotted against a series of different binary classification methods (score = cutoff or decision threshold) with the true positive rate (sensitivity) on the y-axis and the false positive rate (1-specificity) on the x-axis. The AUC ranges from 1.0 to 0.5. When AUC is greater than 0.5, the closer the AUC is to 1, the better the diagnostic effect. An AUC between 0.5 and 0.7 indicates low accuracy, an AUC between 0.7 and 0.9 indicates moderate accuracy, and an AUC above 0.9 indicates high accuracy. An AUC ≤ 0.5 indicates no diagnostic value.

[0042] 2. Results and Analysis like Figure 2 As shown in the data, compared with the ineffective group, the 24-hour urine protein content of patients in the effective group decreased significantly after 6 months of hydroxychloroquine treatment, while the eGFR (estimated glomerular filtration rate) did not change significantly. The above results show that during the entire treatment process, the 24-hour urine protein content of the effective group decreased and there was no significant change in renal function in the two groups of patients.

[0043] like Figure 3 As shown, urine samples from two groups of patients were analyzed, and ion chromatograms were extracted from the standard solution and urine samples from two groups (effective group and ineffective group). The standard solution was an amino acid standard from Sigma-Aldrich (Cat. No. A6407). The standard solution was mixed to prepare a physiological concentration range of amino acids (e.g., 0.1-100 μM) with a concentration gradient of 0.1, 1, 5, 10, 50, and 100 μM (diluted with 0.1% formic acid aqueous solution). L-leucine, an amino acid isotope internal standard from MCE, was also selected. 13 C (Product No. HY-N0486S1), add ¹³C labeled amino acids to a final concentration of 5 μM. Figure 3It can be seen that: 1. With the analytical method adopted in the present invention, all target compounds exhibit symmetrical chromatographic peaks; 2. The chromatographic separation of each target compound is well achieved; 3. There is no significant difference in the retention time and chromatographic peak shape of the target compound in the biological sample and the standard solution.

[0044] PCA analysis is an unsupervised multivariate statistical analysis method that can reflect the metabolic differences between groups of samples and the differences between groups of samples from a multidimensional space. It is a basic original state of the original data. The present invention uses PCA analysis to take baseline urine samples from patients in the effective treatment group and the ineffective treatment group. The results are shown in Figure 4 . PCA score plot (such as Figure 4 As shown in Figure A, there are certain differences in the metabolic profiles of the two groups of urine samples, but there is a cluster overlap between some samples. Subsequently, supervised OPLS-DA analysis was used to better distinguish the two groups of patients. The OPLS-DA model can exclude some variables that are not related to the grouping, and more accurately screen out valuable differential variables to improve the discrimination ability. By filtering out irrelevant orthogonal signals through OPLS-DA analysis and combining the weight value (VIP) of the differential variable, the obtained differential metabolites are more reliable. Figure 4 As shown in Figure B, the OPLS-DA model of the present invention makes the sample separation between the effective treatment group and the ineffective treatment group more obvious. The sample points of the effective group are mainly distributed in the second and third quadrants, and are relatively concentrated, with a certain degree of clustering, indicating that the differences in endogenous metabolites among patients in the group are small, and the metabolic state and change trend are relatively stable; the sample points of the ineffective group are mainly distributed in the first and fourth quadrants and are relatively scattered, with no obvious intersection and overlap with the sample points of the effective group, indicating that there are significant differences in endogenous metabolites in the urine of the two groups of patients. Moreover, the score graph shows obvious cluster separation (R2Y=0.664, Q2=0.584), both greater than 0.5, indicating that this model was successfully constructed and has good fit and predictive ability. In addition, the model permutation test results R2Y = (0.0, -0.06), Q2Y = (0.0, -1.08), indicating that the model does not have overfitting phenomenon, as shown in Figure 2. Figure 4 As shown in C.

[0045] Through the identification and analysis of the above model, it was determined that there were significant metabolic differences in the endogenous metabolites in the urine of the two groups of patients in the present invention. The contribution of the evaluation variable in the OPLS-DA model is generally expressed by the VIP value. The larger the VIP value, the greater the contribution. Since the average VIP value of the variable is close to 1, the variable with VIP>1 is often regarded as having important significance to the model. Therefore, the present invention uses variables with a VIP value greater than 1 as candidate variables for biomarkers, and finally screened out 28 variables with a VIP value greater than 1, as shown in Table 3. In order to intuitively display the distribution of these differentially expressed amino acids, volcano plots were drawn ( Figure 5 A) and hierarchical clustering heatmap ( Figure 5 B).

[0046] Table 3 Differentially expressed amino acids in urine between the hydroxychloroquine treatment effective group and the ineffective group In order to explore the potential role of the differentially expressed amino acids screened above in metabolism, the present invention further used the KEGG database to perform pathway enrichment and metabolic pathway analysis on the candidate amino acids and evaluated the overall abundance changes. The results are shown in Figure 6 .like Figure 6 The results showed that the differential metabolites were mainly enriched in the following pathways: D-aminoacid metabolism (56.25%), protein digestion and absorption (45.45%), amino acid biosynthesis (31.25%), cysteine ​​and methionine metabolism (31.25%), and aminoacyl-tRNA biosynthesis (31.25%), as shown in Figure 6A. At the same time, the Differential Abundance Score (DAS) within each pathway was analyzed to assess the overall expression changes of differential metabolites within the same pathway. The results showed that the amino acid metabolism of cysteine, methionine, and D-amino acids in the urine of the IgA nephropathy ineffective group was significantly upregulated, as shown in Figure 6B.

[0047] Based on the matching information obtained from the KEGG database, we further searched for metabolic pathways corresponding to Homo sapiens (Human), and identified a total of 22 pathways related to amino acid metabolism, as shown in Table 4. The results of metabolic pathway analysis are shown in bubble diagrams ( Figure 7 A) and pathway enrichment dendrogram ( Figure 7B) to visually demonstrate the enrichment of each pathway. Using the screening criteria of Impact > 0.1 and P < 0.05, the results showed that among the 22 pathways, two pathways reached significance: arginine and ornithine metabolism, and cysteine ​​and methionine metabolism. The differentially expressed amino acids involved in these two metabolic pathways are D-ornithine, L-arginine, L-cysteine, L-cystine, and D-cysteine, respectively. These five amino acids are considered potential biomarkers for predicting HCQ efficacy.

[0048] Table 4 Unique pathway analysis results obtained by metabolic pathway analysis (MetPA) Note: Total: the total number of compounds in the pathway; Hits: the number of exact matches between the uploaded marker data and the metabolome library; P: the raw p-value obtained through pathway analysis; Impact: the pathway impact value obtained through topological analysis.

[0049] Example 2: Construction of prediction model and further validation of markers In this example, the selected markers were modeled and further verified: 1. Construction and internal validation of the prediction model First, a single-quantity prediction model was constructed. Considering the large numerical changes in each amino acid, each biomarker screened in the above examples was numerically converted (D-Ornithine and D-Cysteine ​​per unit change value × 100; L-Arginine, L-Cysteine, and L-Cystine per unit change value × 10000), and then a univariate logistic regression model was constructed. The results showed that these five amino acids were significant predictors of the efficacy of hydroxychloroquine (P < 0.05), and the Hosmer-Lemeshow test results did not show overfitting (P > 0.05), see Table 5. The predictive ability of each univariate model was evaluated by drawing the ROC curve, and the results are shown in Table 5. Figure 8 .like Figure 8 As shown in the figure, all five amino acids showed good prediction performance (AUC > 0.7), among which L-cysteine ​​had the highest AUC (0.924).

[0050] Table 5 Results of univariate logistic regression analysis Subsequently, three joint prediction models were constructed for the five screened biomarkers: Model I: Arginine and ornithine metabolism model (combination of D-ornithine and L-arginine); Model II: Cysteine ​​and methionine metabolism model (consisting of L-cysteine, L-cystine and D-cysteine); Model III: All five amino acids combined model.

[0051] The prediction performance of each model was evaluated by drawing the ROC curve. The results are shown in Figure 9 .like Figure 9 The results showed that all three models had good predictive ability (AUC > 0.7), among which model III (all five amino acids combined) had the best performance (AUC = 0.979) (e.g. Figure 9 A, C, and E).

[0052] 2. External validation of marker sensitivity and specificity The dataset used for external validation was: patients with primary IgA nephropathy collected from Nanjing Drum Tower Hospital between June 1, 2024, and February 28, 2025. A total of 70 patients met the inclusion and exclusion criteria and were enrolled for observation. The inclusion and exclusion criteria were the same as those in Example 1. These 70 subjects were subsequently treated with hydroxychloroquine for at least 6 months according to the method described in Example 1. During follow-up, 2 patients decided not to use hydroxychloroquine, 3 patients switched to hormones and other immunosuppressants, 1 patient developed diarrhea, and 2 patients had poor treatment compliance. Ultimately, 62 subjects were enrolled. The subjects were also divided into an effective group (n=30) and an ineffective group (n=32) according to the same criteria as in Example 1. Urine was tested and analyzed using the same LC-MS / MS method as in Example 1.

[0053] The collected data sets were randomly divided into training and validation sets in a ratio of 7:3 for cross-validation. The results showed that the prediction performance of each joint model remained stable in both the training and validation sets (AUC > 0.7). Figure 9 As shown in B, D and F.

[0054] The above results suggest that the combination of five amino acids has high sensitivity and specificity and can be used as a marker to evaluate the efficacy of hydroxychloroquine in the treatment of IgA nephropathy.

[0055] Example 3: Application of markers in non-therapeutic hydroxychloroquine use studies In this embodiment, the activity of hydroxychloroquine is studied: specific urine is selected, different batches of hydroxychloroquine are reacted with it, and the quantitative expression of one or more of the five markers (D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine) screened in Example 1 is determined, and the expression levels are compared to judge the biological activity of each batch of hydroxychloroquine.

[0056] Example 4: Kit for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy The present embodiment provides a kind of kit for evaluating the efficacy of hydroxychloroquine for treating IgA nephropathy, comprising any one of the five markers D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine ​​screened out in Detection Example 1. In the present embodiment, a quantitative reagent for detecting the expression of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine ​​is selected. By specifically detecting the expression of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine ​​in the sample, it is helpful to judge the drug sensitivity of IgA nephropathy patients to hydroxychloroquine in advance. It can be measured immediately after the IgA nephropathy patient obtains urine, evaluates the efficacy of hydroxychloroquine, and provides a personalized and accurate treatment plan for the patient.

[0057] Example 5: Hydroxychloroquine efficacy analysis system for IgA nephropathy This embodiment provides a hydroxychloroquine efficacy analysis system for IgA nephropathy, comprising: Target expression detection device: used to detect the expression level of the marker in the sample; the sample is the patient's urine; Drug efficacy analysis device: Determines the drug efficacy for IgA nephropathy based on the expression level of markers; Result output device: used to output the results obtained by the drug efficacy analysis device.

[0058] The efficacy of the drug can be evaluated before patients use hydroxychloroquine, providing patients with personalized and accurate treatment plans.

[0059] Example 6: Pharmaceutical composition for treating IgA nephropathy A pharmaceutical composition for treating IgA nephropathy, comprising hydroxychloroquine and drugs that inhibit five markers.

[0060] For IgA nephropathy patients who have been detected to be ineffective for hydroxychloroquine treatment in Example 5, the use of the pharmaceutical composition in this example for treatment can better improve the therapeutic effect.

[0061] In summary, this study, based on LC-MS / MS metabolomics technology, screened a panel of highly sensitive biomarkers, including D-ornithine, L-arginine, L-cysteine, L-cystine, and D-cysteine, from the baseline urine of IgAN patients. These metabolites can effectively predict the efficacy of HCQ in IgAN patients. Further metabolic pathway enrichment analysis revealed that patients with poor HCQ response had disorders in arginine and ornithine metabolism, as well as cysteine ​​and methionine metabolism. Finally, a combined prediction model based on these five differentially expressed amino acids was constructed. This model demonstrated high predictive performance and could provide a clinically useful, early, non-invasive screening method for identifying IgAN patients who are potentially refractory to HCQ treatment.

[0062] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with this profession can make slight changes or modifications to equivalent embodiments of the methods and technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy, characterized in that: The marker is any one of D-ornithine, L-arginine, L-cysteine, L-cystine, and D-cysteine, or any two of them, or any three of them, or any four of them, or a combination of five of them.

2. The marker according to claim 1, characterized in that The markers are a combination of five markers, namely, D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine.

3. The marker according to claim 1 or 2, characterized in that The markers are derived from the urine of the subject.

4. Use of a reagent for detecting the expression amount of the marker according to any one of claims 1 to 3 in the preparation of a reagent for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy or a drug sensitivity detection reagent.

5. The use according to claim 4, characterized in that The reagent for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy or the reagent for drug sensitivity detection is a reagent for evaluating the efficacy of hydroxychloroquine or performing drug sensitivity detection in the process of treating IgA nephropathy; The sample for drug efficacy evaluation or drug sensitivity test is the subject's urine; The reagent determines the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, turbidimetry.

6. A kit for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy, characterized in that: The invention comprises a reagent for detecting the expression amount of a marker for evaluating the efficacy of hydroxychloroquine in treating IgA nephropathy as described in any one of claims 1 to 3.

7. The kit according to claim 6, characterized in that The detection is a quantitative detection of the marker level in the subject's urine; The reagent determines the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, turbidimetry.

8. A method for evaluating whether hydroxychloroquine can prevent or treat IgA nephropathy, characterized in that The method comprises using any one of D-ornithine, L-arginine, L-cysteine, L-cystine and D-cysteine, or any two of them, or any three of them, or any four of them, or any five of them as markers to evaluate the effect of hydroxychloroquine.

9. A method for screening a compound capable of preventing or treating IgA nephropathy, characterized in that: The method includes using any one, any two, any three, or any four or five markers of D-ornithine, L-arginine, L-cysteine, L-cystine, and D-cysteine ​​as markers to evaluate the effect of the compound.

10. A hydroxychloroquine efficacy analysis system for IgA nephropathy, characterized in that: include: Target expression detection device: used to detect the expression level of the marker according to any one of claims 1 to 3 in a sample; The sample is the subject's urine; Drug efficacy analysis device: Determines the drug efficacy for IgA nephropathy based on the expression level of markers; Result output device: used to output the results analyzed by the drug efficacy analysis device; The reagents used in the target expression detection device determine the level of the marker in the sample by one or more of the following methods: chromatography, mass spectrometry, fluorescence measurement, electrophoresis, immunoaffinity, immunohybridization, immunochemistry, ultraviolet spectroscopy, fluorescence analysis, radiochemical analysis, near-infrared spectroscopy, nuclear magnetic resonance spectroscopy, light scattering analysis, and turbidimetry.

Images