Application of TPD52 as myasthenia gravis urine diagnostic marker

Abstract

The invention discloses an application of TPD52 as a myasthenia gravis urine diagnostic marker, which detects and finds the difference condition of urine proteins between myasthenia gravis and a healthy control group through a high-throughput proteomics method. The TPD52 protein in the urine can be used for detecting the myasthenia gravis and healthy people, further screening is carried out, and clinical samples verify that the TPD52 protein in the urine can be used for remarkably distinguishing the myasthenia gravis from the healthy people, so that the TPD52 protein can be used as a urine diagnosis marker and is used for noninvasive detection of the myasthenia gravis, and a new way is provided for clinical early diagnosis.

Description

Technical Field

[0001] This invention relates to the field of diagnostic technology for myasthenia gravis, specifically the application of TPD52 as a urinary diagnostic marker for myasthenia gravis. Background Technology

[0002] Myasthenia gravis is an autoimmune disease, a rare condition with a prevalence of approximately 30 cases per 100,000 people. However, women aged 20 to 40 and older men (who have a higher incidence of thymoma associated with myasthenia gravis) are most affected. Current diagnostic methods include: 1. Serum antibody testing: Acetylcholine receptor antibodies are highly specific and positive in approximately 85% of cases of systemic ocular myasthenia gravis, but only in 50% of cases of isolated ocular myasthenia gravis. 2. Electrodiagnostic testing: This includes repetitive nerve stimulation testing (relatively low sensitivity) and single-fiber electromyography (high sensitivity, but must be performed by a neuromuscular specialist). 3. Chest computed tomography (CT) scan: Performed after a diagnosis of myasthenia gravis to rule out the presence of thymoma (occurring in 10%-15% of patients).

[0003] Among bodily fluids, urine offers significant clinical advantages through non-invasive methods. The kidneys filter plasma, and many proteins detected in plasma can also be detected in urine, including potential biomarkers. In urine studies, the supernatant is typically used while sediment and particulate matter (related to urinary tract diseases and urinary tract infections) are discarded. Seventeen high-abundance proteins constitute 50% of urine samples, and detecting the levels of low-abundance proteins has important clinical diagnostic significance.

[0004] Urine can reflect the physiological and pathological changes of the entire body's tissues and organs. Analysis of the sources of these proteins reveals that they originate from various sources, not just the kidneys and urinary system, but from multiple tissues and organs throughout the body, such as the brain, digestive tract, heart, and lungs. In fact, these proteins can all be found in urine. Therefore, it can reflect the physiological and pathological changes of the entire body's tissues and organs. Furthermore, compared to blood, urine exhibits less inhibition of high-abundance proteins, making it easier to identify low-abundance proteins. Therefore, studying urine significantly increases the probability of finding medium- and low-abundance proteins. In contrast to blood, urine is a waste product of the organism, while blood circulates throughout the body's fluid system, providing the internal environment for multiple tissues and organs. Therefore, blood must maintain a relatively stable state; significant changes could affect overall physiological function. In disease states, there is a high probability of excess protein being excreted from the body, and urine is the best outlet. Therefore, unlike blood, urine is a waste product of the organism and does not need to maintain the body's internal environment, thus it does not need to maintain homeostasis and can accumulate physiological and pathological changes within the body. Therefore, urine can reflect more changes and is an important source of disease biomarkers, especially for early disease diagnosis.

[0005] Therefore, it is of great significance to look for diagnostic markers of myasthenia gravis in urine. Summary of the Invention

[0006] This invention provides a urine diagnostic marker, TPD52 protein, for non-invasive detection of myasthenia gravis, offering a new approach for early clinical diagnosis.

[0007] In view of this, the solution of the present invention is as follows: This invention proposes the application of a reagent for detecting the expression level of TPD52 protein in urine in the preparation of diagnostic products for myasthenia gravis.

[0008] Furthermore, the expression level of TPD52 was elevated in the urine of patients with myasthenia gravis.

[0009] Furthermore, the applications include at least one of early diagnosis, risk assessment, prognosis prediction, and / or treatment planning for myasthenia gravis.

[0010] Furthermore, the diagnostic product includes at least one of a reagent kit, test strip, instrument, or system.

[0011] Furthermore, the diagnostic product includes a reference line for the expression level of TPD52 protein in urine. If the expression level of TPD52 protein in the urine of a healthy person is selected as the reference line, a level exceeding the reference line is judged as myasthenia gravis.

[0012] Furthermore, the diagnostic product also includes at least one of a urine protein extraction device and a purification reagent.

[0013] Furthermore, the detection reagents include one or more reagents used in mass spectrometry, immunochemical methods, fluorescence analysis, and radiochemical analysis.

[0014] Furthermore, the detection reagents include ELISA detection reagents, and at least one of a standardized curve and a normalization processing reagent.

[0015] Preferably, the normalization reagent includes a creatinine detection reagent.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention uses high-throughput proteomics to detect differences in urinary proteins between patients with myasthenia gravis and healthy controls. Furthermore, through screening and clinical sample verification, it was found that the TPD52 protein in urine can significantly distinguish between patients with myasthenia gravis and healthy individuals. Therefore, the TPD52 protein can be used as a urinary diagnostic biomarker for non-invasive detection of myasthenia gravis, providing a new approach for early clinical diagnosis. Attached Figure Description

[0017] Figure 1 The figure shows the urine proteomics analysis process and related results in Example 1 of the present invention.

[0018] Figure 2 The results are related to the differential protein KEGG enrichment analysis and GO functional annotation in Example 1 of this invention.

[0019] Figure 3 This is the result of screening diagnostic biomarkers using a classification model in Embodiment 1 of the present invention.

[0020] Figure 4 This is the diagnostic result of using TPD52 protein in urine as a diagnostic marker based on clinical samples in Example 2 of the present invention. Detailed Implementation

[0021] The technical solution of the present invention will now be clearly and completely described in conjunction with preferred embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In one embodiment, we used high-throughput proteomics to detect differences in urinary proteins between patients with myasthenia gravis and healthy controls, finding significant differential protein expression between the two groups. We then used lasso regression and machine learning to identify eight potential disease biomarkers that could significantly distinguish between myasthenia gravis and healthy individuals. Among them, TPD52 protein expression was potentially higher in myasthenia gravis patients than in the normal group, exhibiting the highest AUC value of 0.87, thus distinguishing between the two groups. These results suggest that detecting TPD52 protein in urine may be useful in differentiating between myasthenia gravis patients and healthy individuals. For further validation, we used ELISA to detect TPD52 expression between myasthenia gravis patients and healthy individuals in a validation set. The results confirmed that TPD52 was significantly highly expressed in myasthenia gravis, with an AUC value of 0.7461. We also found that TPD52 expression was significantly higher in patients with myasthenia gravis and thymoma than in patients with thymoma alone. The above results suggest that TPD52 is a potential non-invasive urinary diagnostic marker for the rare disease myasthenia gravis. That is, detecting TPD52 protein in urine can relatively accurately distinguish between people with myasthenia gravis and healthy individuals.

[0023] Example 1: Screening of urinary protein biomarkers

[0024] To screen for differentially expressed urinary protein and potential biomarkers in patients with myasthenia gravis (MG), we conducted the following: Figure 1 The proteomics analysis workflow is shown in Figure A. First morning urine samples were collected from 10 MG patients (sample information is shown in Table 1) and 10 healthy controls. Data-independent acquisition (DIA) analysis was performed using an Orbitrap Astral mass spectrometer.

[0025] Table 1: Clinical sample information used for mass spectrometry analysis

[0026] The procedure for urinary protein processing for mass spectrometry identification was as follows: Midstream urine samples were collected in the morning under aseptic conditions. The samples were centrifuged at 4 °C, 4,000 × g for 30 minutes to remove cells and impurities. For mass spectrometry identification, 20 mL of urine was diluted with 20 mL of 0.2 M Na₂HPO₄ solution. The supernatant was filtered through a 0.22 μm nitrocellulose membrane (Millipore) mounted on a vacuum filtration apparatus. After filtration, the membrane was dried at 56 °C, and then the protein-bound membrane was cut into small pieces and transferred to 2 mL centrifuge tubes. Proteins were precipitated with acetone to remove impurities. The mixture was shaken for 10 minutes, incubated at 4 °C for 1 hour, and then centrifuged at 12,000 × g for 30 minutes. The resulting protein precipitate was dissolved in lysis buffer, and the protein concentration was determined by the BCA method.

[0027] Figure 1 B shows a significant difference in protein abundance before and after enrichment in a representative sample pair; the remaining nine sample pairs also showed similar enrichment and detection results. Figure 1 C). Principal component analysis (PCA) results showed significant clustering and separation between the MG group and the healthy control group (HC), suggesting significant differences in urinary proteomic profiles. Slight deviations in a few samples within either the MG or HC groups may reflect inter-individual biological variations. Figure 1 D). A total of 1796 proteins were identified in MG samples and 1899 proteins were identified in healthy samples. Figure 1 E), of which two groups contain a total of 1692 proteins ( Figure 1 F and Supplementary Table S1). Volcano diagram analysis ( Figure 1 G) identified 216 significantly differentially expressed proteins (|fold change| ≥ 1.2, p < 0.05). The heatmap illustrates the expression patterns of these differentially expressed proteins in each sample. Figure 1 H). Tissue-specific enrichment analysis showed that these proteins were highly expressed in neural tissues, especially brain tissue. Figure 1 I), suggesting that it is related to the neuroimmunopathological process of MG.

[0028] KEGG enrichment analysis showed that these differentially expressed proteins were significantly associated with neuroinflammatory and neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease. Figure 2 A). Because these diseases share common pathological features with MG in terms of neurotransmission disorders, immune activation, and mitochondrial dysfunction, it suggests a possible overlap in their molecular mechanisms. GO Functional Annotation ( Figure 2(B) shows that the differentially expressed proteins are involved in processes such as cellular metabolism, proliferation, and extracellular secretion. These results suggest that the pathogenesis of MG may not be limited to neuromuscular junction abnormalities, but also involves systemic metabolism and inflammatory responses. Furthermore, the differentially expressed proteins are enriched in functions such as signal receptor binding, peptidase activity, and cell adhesion molecule binding, further revealing the complexity of the molecular mechanisms of MG.

[0029] To screen for potential diagnostic biomarkers, we applied LASSO regression and support vector machine (SVM) classification models to the proteomic data. LASSO identified a subset of proteins highly correlated with the MG phenotype. Figure 3 AB), while SVM combined with 10-fold cross-validation identifies proteins with higher discriminative ability ( Figure 3 C). The intersection of the two methods yielded eight overlapping core proteins: TPD52, SORL1, PLAU, TSPAN3, CASP14, QPCT, CILP2, and CTHRC1. Figure 3 D). ROC curve analysis showed that these proteins have good diagnostic potential: TPD52 AUC was 0.87, SORL1 was 0.765, PLAU was 0.79, TSPAN3 was 0.78, CASP14 was 0.84, QPCT was 0.81, CILP2 was 0.82, and CTHRC1 was 0.815. Figure 3 EL). The violin plot shows the relative expression levels of these proteins obtained by mass spectrometry quantification in the MG and control groups ( ). Figure 3 The results (MT) showed that TPD52, SORL1, and CASP14 were significantly upregulated in MG, while PLAU, TSPAN3, QPCT, CILP2, and CTHRC1 were downregulated. Among the eight core proteins, TPD52 exhibited the highest AUC value and the most significant upregulation, thus it can be considered a preferred biomarker protein.

[0030] Example 2: Application of urinary TPD52 protein in clinical detection

[0031] To further validate the clinical significance of urinary TPD52 protein, we performed ELISA on urinary TPD52 levels in 34 MG patients (sample information shown in Table 2) and healthy controls, and normalized the results to urinary creatinine. The procedure was as follows: morning midstream urine samples were collected under sterile conditions. Samples were centrifuged at 4 °C, 4,000 × g for 30 minutes to remove cells and impurities. The expression level of urinary TPD52 was detected using enzyme-linked immunosorbent assay (ELISA) (Abebio, AE13713HU). In addition, urinary creatinine concentration was measured using a creatinine assay kit (Beyotime, S0291S). To eliminate the influence of urine dilution differences, urinary protein concentrations were normalized to the corresponding creatinine levels.

[0032] Table 2: Clinical sample information used for validation

[0033] The results showed that TPD52 was significantly elevated in the urine of MG patients ( Figure 4 A). ROC curve analysis showed that TPD52 could effectively distinguish between MG and healthy controls, with an AUC of 0.7461 ( Figure 4 B). Furthermore, immunohistochemical staining of thymoma tissues from MG and non-MG patients showed significantly elevated TPD52 expression in MG-related thymomas. Figure 4 C), suggesting its involvement in the pathogenesis of MG.

[0034] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. Application of reagents for detecting TPD52 protein expression levels in urine in the preparation of diagnostic products for myasthenia gravis.

2. The application according to claim 1, characterized in that, The expression level of TPD52 was elevated in the urine of patients with myasthenia gravis.

3. The application according to claim 1, characterized in that, The applications include at least one of early diagnosis, risk assessment, prognosis prediction, and / or treatment planning for myasthenia gravis.

4. The application according to claim 1, characterized in that, The diagnostic products include at least one of reagent kits, test strips, instruments, or systems.

5. The application according to claim 1, characterized in that, The diagnostic product includes a reference line for the expression level of TPD52 protein in urine.

6. The application according to claim 1, characterized in that, The diagnostic product also includes at least one of a urine protein extraction device and a purification reagent.

7. The application according to claim 1, characterized in that, The detection reagents include one or more reagents used in mass spectrometry, immunochemical methods, fluorescence analysis, and radiochemical analysis.

8. The application according to claim 1, characterized in that, The detection reagents include ELISA detection reagents, and at least one of standardized curves and normalization processing reagents.

9. The application according to claim 8, characterized in that, The normalization reagents include creatinine detection reagents.

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