Diagnostic value of claudin 3 and family-related molecules in obstructive sleep apnea hypopnea syndrome
By detecting the expression levels of Claudin3 and its family members, the diagnostic challenge of OSA was solved, achieving highly accurate OSA diagnosis and severity assessment. Using Claudin3 and its family members as biomarkers, a diagnostic system and model were constructed, improving the detection efficiency of OSA.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN MEDICAL UNIVERSITY GENERAL HOSPITAL
- Filing Date
- 2023-10-26
- Publication Date
- 2026-05-15
AI Technical Summary
Existing technologies are insufficient for the effective detection and assessment of obstructive sleep apnea-hypopnea syndrome (OSA), especially when polysomnography is inconvenient or patients are difficult to cooperate with, and there is a lack of reliable biomarkers for the diagnosis and assessment of the severity of the disease.
Using Claudin3 and its family members Claudin1 and Claudin2 as biomarkers, a diagnostic system and model were constructed to determine the presence and severity of OSA by detecting the protein expression levels in blood and urine and combining multiple detection methods such as hematoxylin-eosin staining, Western blotting, and ELISA.
It achieves high-accuracy diagnosis of OSA, with an AUC value of 0.872 for Claudin3 detection in plasma and an AUC value of 0.906 for combined detection of Claudin1, Claudin2 and Claudin3 in urine, significantly improving the diagnostic accuracy of OSA and enabling the assessment of disease severity.
Smart Images
Figure CN117402958B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the fields of biotechnology and medicine, specifically relating to the diagnostic value of Claudin3 and related family molecules in obstructive sleep apnea-hypopnea syndrome. Background Technology
[0002] Obstructive sleep apnea-hypopnea syndrome (OSA) is a disease characterized by repeated apnea or hypopnea during sleep due to recurrent complete or incomplete upper airway obstruction, leading to hypoxemia and sleep structure disturbances. Untreated OSA significantly increases the risk of related diseases such as hypertension, heart disease, stroke, and death. Therefore, the disease burden of OSA should not be underestimated, and exploring new technologies and methods for treating sleep-related breathing disorders is of great significance.
[0003] OSA causes pathological damage to the intestines and impairs the intestinal mucosal barrier. The expression of Claudins (especially Claudin3), which belong to the tight junction protein family, in the peripheral blood of OSA patients has not yet been studied.
[0004] Polysomnography (PSG) is the gold standard for diagnosing OSA. However, due to varying medical conditions and technician skill levels, and the difficulty some patients have in cooperating with a full night of polysomnography, easily detectable biomarkers are of great significance for the diagnosis of OSA. Summary of the Invention
[0005] This invention, using an intermittent hypoxia (IH) animal model, proposes for the first time a potential self-protective mechanism of Claudin3 and its family-related molecules against the intestinal mucosal barrier. Based on basic research and then applied to clinical practice, this invention validates the diagnostic value of CLDNs and their related factors in OSA patients.
[0006] Specifically, the present invention provides the following technical solutions:
[0007] In a first aspect, the present invention provides the use of reagents for detecting the expression levels of biomarkers in the preparation of diagnostic products for obstructive sleep apnea-hypopnea syndrome (OSA), wherein the biomarkers include Claudin3 (CLDN3).
[0008] Preferably, the markers also include Claudin1 and / or Claudin2.
[0009] More preferably, the marker is Claudin3.
[0010] More preferably, the marker is a combination of Claudin1, Claudin2 and Claudin3.
[0011] On the other hand, the present invention provides the application of reagents for detecting Claudin3 expression levels in the preparation of products for assessing the severity of obstructive sleep apnea-hypopnea syndrome (OSA).
[0012] Specifically, the lower the Claudin3 expression, the more severe the obstructive sleep apnea-hypopnea syndrome (OSA).
[0013] The Claudin1-3 described in this invention all belong to the tight junction membrane protein family (Claudins) and may regulate paracellular permeability of epithelial cells by forming the inner wall of paracellular pores. They can also be referred to as "CLDN1-3".
[0014] In this invention, the samples used for testing the marker may include blood or other fluid samples and tissue samples obtained from the subject.
[0015] Furthermore, the samples include, but are not limited to: urine, blood, serum, plasma, tissue, blood-derived cells, lymph, synovial fluid, cerebrospinal fluid, pleural fluid, bronchial lavage, peritoneal fluid, bladder irrigation fluid, secretions (e.g., breast secretions), oral irrigation fluid, swabs (e.g., oral swabs), touch preparations, fine needle aspiration materials, cell extracts, and combinations thereof.
[0016] In a specific embodiment of the present invention, the sample is preferably urine or blood (plasma) from the subject. Most preferably, the sample is urine.
[0017] When there are multiple markers, the sample may include various samples, such as blood (plasma) and urine.
[0018] Preferably, the reagents for detecting the expression level of the biomarker include reagents for detecting the expression level of protein and / or mRNA.
[0019] Preferably, the reagents used to detect protein expression levels include those used in the following methods: hematoxylin-eosin staining (HE staining), safranin O-fast green staining, Western blotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA), sandwich assay, immunohistochemistry staining, mass spectrometry, immunoprecipitation analysis, complement fixation analysis, flow cytometry, and protein chip analysis.
[0020] Preferably, the reagents for detecting mRNA expression levels include those used in the following methods: PCR-based detection methods, Southern hybridization methods, Northern hybridization methods, dot hybridization methods, fluorescence in situ hybridization methods, DNA microarray methods, ASO methods, and high-throughput sequencing platform methods.
[0021] Preferably, the reagent may further include an auxiliary detection reagent for mRNA expression levels, which includes, but is not limited to: reaction reagents that visualize the amplicon corresponding to the primer, such as reagents that visualize the amplicon by agarose gel electrophoresis, enzyme-linked gel electrophoresis, chemiluminescence, in situ hybridization, fluorescence detection, etc.; RNA extraction reagents; reverse transcription reagents; cDNA amplification reagents; standards used to prepare standard curves; and positive controls.
[0022] Preferably, the reagent may further include a protein expression level auxiliary detection reagent, which includes, but is not limited to: blocking solution; antibody dilution solution; washing buffer; colorimetric stop solution; and standards used to prepare the standard curve.
[0023] Preferably, the expression level is the protein expression level.
[0024] On the other hand, the present invention provides a diagnostic system (diagnostic device) for obstructive sleep apnea-hypopnea syndrome (OSA), the system including a computing device for determining whether obstructive sleep apnea-hypopnea syndrome (OSA) is present based on the expression level of biomarkers.
[0025] Optionally, the diagnostic system (diagnostic equipment) may further include one or more of the following: a detection device, an input device, an output device, and a communication device.
[0026] Furthermore, the detection device is used to detect the expression level of biomarkers in the subject's sample.
[0027] Furthermore, the input module is used to input the detection results of the marker expression level, which can be obtained by the detection component.
[0028] Furthermore, the output module is used to output the judgment result of the judgment component.
[0029] More preferably, the device may further include a model building component or a threshold determination component, wherein the model building component may construct a diagnostic model using any one or more of the following methods: classification and logistic regression, k-nearest neighbor algorithm, Naive Bayes, support vector machine, decision tree, random forest, regression tree, gradient boosting decision tree, xgboost, lightweight gradient boosting machine, gradient boosting machine, LASSO, and convolutional neural network.
[0030] To provide interaction with the user, the device may be a computer having: a display device for displaying information to the user; and a keyboard and pointing device (e.g., a mouse) through which the user provides input to the computer. Other types of devices may also be used to provide interaction with the user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including voice input, speech input, or tactile input).
[0031] On the other hand, the present invention provides a computer-readable storage medium for diagnosing obstructive sleep apnea-hypopnea syndrome (OSA), wherein the computer-readable storage medium stores a computer program that, when executed by a processor, determines whether obstructive sleep apnea-hypopnea syndrome (OSA) is present based on the expression levels of biomarkers.
[0032] In this invention, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.
[0033] On the other hand, the present invention provides a method for diagnosing obstructive sleep apnea-hypopnea syndrome (OSA), the method comprising comparing the expression level of a biomarker with a threshold to determine the diagnostic result; the biomarker includes Claudin3 (CLDN3).
[0034] Preferably, the markers also include Claudin1 and / or Claudin2.
[0035] More preferably, the marker is Claudin3.
[0036] More preferably, the marker is a combination of Claudin1, Claudin2 and Claudin3.
[0037] On the other hand, the present invention provides a method for determining the severity of obstructive sleep apnea-hypopnea syndrome (OSA), the method comprising determining the severity based on the expression level of Claudin3.
[0038] Specifically, the lower the expression level of Claudin3, the more severe the disease condition.
[0039] The implementation of the "method or system" described in this invention may include performing or completing the selected task manually, automatically, or in combination thereof.
[0040] In this invention, the effectiveness of diagnosis is determined by calculating the area under the curve (AUC) of the ROC model. The ROC curve is a graph that displays the performance of a classification model across all classification thresholds. The curve plots two parameters: the true positive rate and the false positive rate. The area under the curve is called the AUC, which represents the prediction accuracy. A higher AUC value, i.e., a larger area under the curve, indicates a higher prediction accuracy. For example, in a specific embodiment of this invention, detecting Claudin3 expression in urine can achieve accurate diagnosis with an AUC value of 0.849. Further increasing Claudin3 expression in plasma can raise the AUC to 0.872. When detecting and diagnosing the expression levels of Claudin1, Claudin2, and Claudin3 in urine, the AUC value reaches 0.906, representing extremely high accuracy. Attached Figure Description
[0041] Figure 1 This is a diagram showing the results of H&E staining of intestinal tissue from an intermittent hypoxia animal model. A represents the infiltration of intrinsic lymphocytes, B represents the amount of epithelial mucus, C represents the MRP8 content, and D represents the Ki67 content.
[0042] Figure 2 This image shows the results of detecting CLDNs in the intestinal tissue of an intermittent hypoxic animal model. A is CLDN1, B is CLDN2, C is CLDN3, and D is CLDN4.
[0043] Figure 3 This is a comparison of the expression levels of Claudin1-3 in the plasma of patients and controls. A represents CLDN1, B represents CLDN2, and C represents CLDN3.
[0044] Figure 4 This is a comparison of the expression levels of Claudin1-3 in the urine of patients and controls. A represents CLDN1, B represents CLDN2, and C represents CLDN3.
[0045] Figure 5 This is the diagnostic ROC curve for plasma Claudin3.
[0046] Figure 6 This is the diagnostic ROC curve for Claudin3 in urine.
[0047] Figure 7 This is the diagnostic ROC curve of plasma Claudin3 + urine Claudin3.
[0048] Figure 8 This is the diagnostic ROC curve for plasma Claudin1+ plasma Claudin2+ plasma Claudin3.
[0049] Figure 9 This is the diagnostic ROC curve for urine Claudin1 + urine Claudin2 + urine Claudin3.
[0050] Figure 10 This is a graph showing the correlation between urinary Claudin3 and the apnea-hypopnea index (AHI).
[0051] Figure 11 This is a graph showing the correlation between urinary Claudin3 and the time when blood oxygen saturation is below 90% (T90). Detailed Implementation
[0052] The present invention will be further described below with reference to embodiments. The following description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make equivalent modifications to the disclosed technical content to create equivalent embodiments. Any simple modifications or equivalent changes made to the following embodiments based on the technical essence of the present invention without departing from the scope of the invention are all within the protection scope of the present invention.
[0053] Example 1: Screening for intestinal mucosal barrier-related genes in animals subjected to intermittent hypoxia (IH).
[0054] Step 1: Steps for constructing an animal model
[0055] Male wild-type Wistar rats (6 weeks old, weighing 120–140 g) were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China) and housed in a sterile animal facility. Our study was approved by the Ethics Committee of Tianjin Medical University General Hospital (IRB2021-DW-47). All rats were randomly assigned to two groups of eight each: an air exposure group (NC) and an intermittent hypoxia exposure group (IH5%). Rats in the IH5% group were placed in a custom-designed intermittent hypoxia chamber from 09:00 to 17:00 (during sleep). The chamber was intermittently filled with pure nitrogen for 30 seconds (6 L / min) to achieve a minimum oxygen concentration of 5%, followed by the introduction of compressed air for 90 seconds (15 L / min), during which the oxygen concentration gradually recovered to 20.9%. Each cycle lasted 2 minutes. Oxygen concentration was measured using an oxygen concentration monitor. This process creates a periodic hypoxia state under "sleep" conditions, which can then be used as an animal model to simulate human OSA (this model is an internationally recognized animal model of intermittent hypoxia used to mimic human OSA: Jing Feng AA-PC, Qi Wu, Bao-yuan Chen, Lin-yang Cui, Dong-chun Liang, Ze-li Zhang, Wo Yao. 2010. Sleep-related hypoxemia aggravates systematic inflammation in emphysematous rats). Chin Med J (Engl). ;123(17):2392-2399.). After 4 weeks of exposure, the rats were euthanized. The colon was opened longitudinally and thoroughly cleaned with ice-cold PBS for histopathological evaluation and immunohistochemical microscopic observation.
[0056] Step 2: Detect the state of intestinal damage
[0057] Intestinal tissue was stained with H&E and Alcian blue. H&E staining results showed that the IH group had more lymphocyte infiltration in the lamina propria than the NC group. Figure 1 A). Alcian Blue staining results showed that the amount of intestinal epithelial mucus in the IH group was less than that in the NC group ( Figure 1 B). MRP8 is a well-known inflammatory marker. Immunohistochemical results showed that the MRP8 content in the intestinal epithelium of the IH group was higher than that of the NC group. Figure 1 C). Ki67 is a well-known proliferation marker. Immunohistochemical results showed that the Ki67 content in the submucosa of the IH group was higher than that in the NC group. Figure 1 D).
[0058] Step 3: Detect the expression levels of CLDNs
[0059] The expression of CLDNs in IH compared with Contrl showed low expression of CLDN2, which is related to intestinal mucosal permeability, and high expression of CLDN1 / 3 / 4, which are related to the barrier. This indicates that the body protects the integrity of the intestinal mucosa in OSA by regulating CLDN expression, which may be one of the mechanisms by which the intestinal mucosa regulates its homeostasis in OSA pathological damage. Figure 2 ).
[0060] Example 2: Validating the correlation between Claudin1-3 and disease in clinical samples.
[0061] This study was a cross-sectional study that included patients who underwent sleep monitoring at the Sleep Medicine Center of Tianjin Medical University General Hospital between July and December 2022. All participants had their sleep recorded for one full night at the Sleep Medicine Center (9:00 PM–10:00 PM to 6:00 AM–7:00 AM). Continuous monitoring was performed by two technicians using a polysomnography system (Alice 5; Philips Respiratory, Murrisville, Pennsylvania, USA).
[0062] A total of 77 participants were enrolled: 34 patients with symptoms such as nocturnal awakening and daytime sleepiness, and 43 healthy volunteers who underwent polysomnography (PSG) at our sleep medicine center. Based on the PSG results, 2 patients were excluded from the OSA group. 8 volunteer patients were diagnosed with OSA. Finally, a total of 40 OSA patients and 37 healthy controls were included.
[0063] Table 1. Clinical characteristics of enrolled patients
[0064]
[0065] Note: Data is presented as mean ± SD or median [IQR].
[0066] Abbreviations: OSA, obstructive sleep apnea; MetS, metabolic syndrome; TG, triglycerides; BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; AHI, apnea-hypopnea index; SpO2min, lowest peripheral oxygen saturation; T90, total sleep time when oxygen saturation is below 90%; AI, apnea index; ODI, oxygen saturation drop index; SE, sleep efficiency; SD, standard deviation.
[0067] The expression levels of Claudin1-3 in the plasma and urine of patients and healthy individuals were detected. Venous blood and urine samples were collected in the early morning before breakfast. Enzyme-linked immunosorbent assay kits for human CLDN1, CLDN2, and CLDN3 were purchased from J&L Bio-Industries Co., Ltd. (Shanghai, China) and the assays were performed according to the recommended protocol.
[0068] The test results showed that the expression of Claudin1-3 in the patient's plasma and urine was higher than that in the healthy control. Figure 3-4 ).
[0069] Table 2. Diagnostic efficacy of Claudin 1-3 in plasma and urine
[0070]
[0071] Further validation of the efficacy of plasma and urine Claudin1-3 in diagnosing OSA was conducted (Table 2). Urine Claudin3 achieved an AUC value of 0.849 in diagnosing OSA, representing its diagnostic value. The ROC curve AUC of urine Claudin3 combined with urine Claudin1 and urine Claudin2 was 0.906 (95% CI, 0.831-0.981, sensitivity 82.5%, specificity 97.3%). The combination of these three components can significantly improve the accuracy of OSA diagnosis.
[0072] Example 3: Correlation between urinary Claudin3 and OSA severity
[0073] Spearman correlation analysis was used to assess the relationship between two variables.
[0074] Urinary Claudin3 was negatively correlated with the apnea-hypopnea index (AHI) and with the time when blood oxygen saturation was below 90% (T90), both of which were statistically significant. Figure 10-11 This indicates that the more severe the OSA, the lower the Claudin3 expression, and the more serious the damage to the mucosal barrier function.
Claims
1. The application of a reagent for detecting the expression level of a biomarker in the preparation of diagnostic products for obstructive sleep apnea-hypopnea syndrome, wherein the biomarker is Claudin3 or a combination of Claudin1, Claudin2 and Claudin3.
2. Application of reagents for detecting Claudin3 expression levels in the preparation of products for assessing the severity of obstructive sleep apnea-hypopnea syndrome.
3. The application as described in claim 1 or 2, wherein the detection is performed on urine and / or plasma.
4. The application as described in claim 1 or 2, wherein the reagent for detecting the expression level of the biomarker includes reagents for detecting the expression level of protein and / or mRNA.
5. The application as described in claim 4, wherein the reagent for detecting protein expression levels includes the reagents used in the following methods: hematoxylin-eosin staining, safranin O-fast green staining, Western blotting, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, sandwich assay, immunohistochemical staining, mass spectrometry, immunoprecipitation analysis, complement fixation analysis, flow cytometry, and protein chip analysis.
6. The application as described in claim 4, wherein the reagent for detecting mRNA expression levels includes reagents used in the following methods: PCR-based detection methods, Southern hybridization methods, Northern hybridization methods, dot hybridization methods, fluorescence in situ hybridization methods, DNA microarray methods, ASO methods, and high-throughput sequencing platform methods.
7. A diagnostic system for obstructive sleep apnea-hypopnea syndrome, the system comprising a computing device for determining whether obstructive sleep apnea-hypopnea syndrome is present based on the expression level of a biomarker, wherein the biomarker is Claudin3.
8. A computer-readable storage medium for diagnosing obstructive sleep apnea-hypopnea syndrome, the computer-readable storage medium storing a computer program that, when executed by a processor, determines whether obstructive sleep apnea-hypopnea syndrome is present based on the expression level of a biomarker, wherein the biomarker is Claudin3.