阅读说明：本技术 一种关节滑膜液生物标记物adamdec1的应用 (Application of joint synovial fluid biomarker ADAMDEC1 ) 是由 康乐 李勇 王利宏 于 2021-09-03 设计创作，主要内容包括：本发明公开了一种关节滑膜液生物标记物ADAMDEC1及其检测产品在类风湿性关节炎与骨关节炎两种疾病诊断区分中的应用。本发明在诊断区分类风湿性关节炎与骨关节炎方面具有很高的诊断价值,诊断准确度高,比现有的诊断标准更加直接针对局部病灶,易于操作。(The invention discloses an ADAMDEC1 biomarker of synovial membrane liquid of joints and application of a detection product thereof in diagnosis and differentiation of rheumatoid arthritis and osteoarthritis. The invention has high diagnosis value in the aspect of diagnosing and distinguishing rheumatoid arthritis and osteoarthritis, has high diagnosis accuracy, is more directly aimed at local focuses than the existing diagnosis standard, and is easy to operate.)

1. The application of ADAMDEC1 as a joint synovial fluid biomarker is characterized by being used for diagnosing and distinguishing rheumatoid arthritis and osteoarthritis.

2. The application of a detection reagent product of the joint synovial fluid biomarker ADAMDEC1 as claimed in claim 1 in diagnosis and differentiation of rheumatoid arthritis and osteoarthritis.

Technical Field

The invention belongs to the field of disease differential detection and diagnosis, relates to application of biomarkers in the direction of disease differential detection and diagnosis, and particularly relates to application of a joint synovial fluid biomarker ADAMDEC1 in diagnosis and differentiation of rheumatoid arthritis and osteoarthritis diseases.

Background

Rheumatoid Arthritis (RA) is a chronic, systemic, inflammatory disease of unknown etiology that affects mainly the synovial joints, with the main symptoms of pain, stiffness (especially morning stiffness) and multiple joint swelling. This arthritis is usually symmetrical and if the condition is not controlled, cartilage and bone are eroded to cause destruction of the joint, resulting in joint deformity. The disease can cause serious motion disability, obviously reduce the life quality and even lose the labor capacity within 10 to 20 years. Female incidence is 2 to 3 times greater than male. RA can occur in patients of any age and its severity increases with age, with peak morbidity between 50 and 75 years. Inflammatory arthritis is present in at least 3 joints of RA; RF and/or ACPA positive, such as anti-cyclic citrullinated peptide (anti-CCP) antibodies; elevation of CRP or ESR; diseases with similar clinical characteristics, particularly psoriatic arthritis, acute viral polyarthritis, polyarthritis or calcium pyrophosphate deposition disease (CPPD) and SLE are excluded; symptoms persist for more than 6 weeks, etc., see in particular the RA classification criteria of the American College of Rheumatology (ACR)/European antirheumatic union (EULAR) 2010.

Osteoarthritis (OA) is a chronic inflammatory disease of the joints common to the elderly. There are a variety of risk factors for OA, including age, obesity, and genetic factors. The pathological features of OA include degeneration of articular cartilage, synovial inflammation, and atypical bone formation. OA occurs well in the hands, knees, hips, and spine, and less frequently in the shoulder, elbow, wrist, and ankle joints. Generally based on the following clinical situations: 1 or several joints have sustained use-related joint pain; the age is greater than or equal to 45 years old; early initial diagnosis of peripheral joint OA was confirmed in less than or equal to 30 minutes of morning stiffness. Typical features of OA can be found by radiographic imaging, including marginal osteophytes, narrowing of the joint space, subchondral sclerosis and cysts. X-ray films can also be used to measure joint space narrowing, which is sometimes used as a surrogate measure of cartilage loss. Radiographic changes in OA, however, are insensitive, particularly in early stage OA, and often have poor association with symptoms. In addition, radiographic examinations often show incidental OA manifestations in older patients. MRI can identify OA at an early stage before significant radiographic manifestations occur. These manifestations include cartilage defects and bone marrow lesions. MRI can also assess lesions for other joint structures that cannot be visualized by radiographic examination, such as effusion, synovium, and ligaments. Ultrasonography can also show structural changes associated with OA, which can help detect synovial inflammation, fluid accumulation and osteophytes. Ultrasound is limited by the reliance on the operator and the inability to assess deeper joint structures and subchondral bone. Synovial fluid of OA joints is usually not or only slightly inflammatory (leukocytes <2000/mm3, predominantly mononuclear cells). With calcium pyrophosphate crystals, OA pools may be inflammatory.

ADAM dec1 belongs to a member of the ADAM family. It is a secreted metalloprotease. ADAMDEC1 contains a signal peptide prodomain, a catalytic domain, and an incomplete disintegrin domain, but lacks the typical transmembrane domain. In addition, ADAMDEC1 contains proteolytic sequences common to the ADAM family and exhibits metalloprotease activity. However, its physiological function is largely unknown. No research report about the relation between ADAMDEC1 and arthritis exists at present.

Disclosure of Invention

The invention aims to overcome the defects in the prior art and provides application of a joint synovial fluid biomarker ADAMDEC1 in diagnosis and differentiation of rheumatoid arthritis and osteoarthritis diseases.

The above object of the present invention is achieved by the following technical solutions:

a diagnostic marker for distinguishing rheumatoid arthritis from osteoarthritis, wherein the marker is ADAMDEC 1.

Analysis of 7 Gene chip data (GSE55235, GSE55457, GSE55584, GSE12021, GSE1919, GSE7669 and GSE36700) and one RNA sequencing data (GSE89408) in the Gene Expression comprehensive database (Gene Expression Omnibus, GEO) of the National Center for Biotechnology Information (NCBI) of China found that area AUC under ROC curve of synovial membrane biomarker ADAM 1 diagnosis for rheumatoid arthritis and bone joint patients is up to 0.9989, sensitivity is 100% and specificity is 97.83%; the area AUC under the ROC curve of 30 cases of OA and 14 cases of RA combined OA patients diagnosed by ADAMDEC1 is as high as 0.9510, the sensitivity is 92.86%, and the specificity is 88.57%.

Therefore, the ADAMDEC1 biomarker for the synovial membrane of joints has high diagnostic value in the aspect of diagnosing and distinguishing rheumatoid arthritis and osteoarthritis, has high diagnostic accuracy, is more directly aimed at local lesions than the existing diagnostic standard, and is easy to operate.

The invention also claims the application of the joint synovial fluid biomarker ADAMDEC1 in the preparation of rheumatoid arthritis and osteoarthritis diagnosis products.

Drawings

FIG. 1 shows 8 data sets with bioinformatics data to screen 17 differentially expressed genes;

FIG. 2 is a ROC analysis of ADAMDEC1 for synovial tissue gene expression data from patients with OA and RA from 8 datasets;

figure 3 shows the results of ADAMDEC1 ELISA on joint synovial fluid sample protein (p < 0.05);

FIG. 4 is a ROC analysis of the synovial fluid sample ELISAADAMDEC1 data.

Detailed Description

The invention is further described with reference to the drawings and examples in the specification, but the invention is not limited thereto in any way. The reagents, methods and equipment adopted by the invention are conventional in the technical field.

Example 1:

bioinformatic data screening for biomarkers diagnostic for differentiating OA from RA

7 gene chip data (GSE55235, GSE55457, GSE55584, GSE12021, GSE1919, GSE7669 and GSE36700) and one RNA sequencing data (GSE89408) from NCBI GEO were downloaded, wherein the 8 data files contained OA and RA patient synovial tissue gene expression data. Bioinformatic data screening was performed on the above 8 datasets using a "Bioconductor" data execution environment in the R language. Firstly, each data set is subjected to quality inspection analysis, and the data files in each data set are qualified in quality inspection without RNA degradation. Each data set was then normalized, genes that differentially expressed OA versus RA synovial tissue in patients were identified from the above 8 data sets using the LIMMA, edgeR and DESeq2 data analysis package, and ROC analysis of the differentially expressed genes was performed to screen for biomarkers that potentially distinguish OA from RA.

Example 2:

diagnostic efficacy of ADAMDEC1 diagnostics for differentiating RA from OA patients

First, experimental sample and reagent

Unless otherwise indicated, reagents and materials used in the following examples are commercially available.

ADAMDEC1 protein assay reagents;

ADAMDEC1 ELISA kits were purchased from CUSABIO.

Second, Experimental methods

1. Human joint synovial fluid sample collection

Collecting samples of synovial fluid of joints extracted in 30 cases of OA and 14 cases of RA of people hospitals in Dongyang city combined OA patients in joint replacement surgery, marking and storing in a refrigerator at-80 ℃ for later use.

ELISA determination of target protein content in synovial fluid of joints

The content of ADAMDEC1 in synovial membrane of joints was determined strictly according to the procedure of ELISA kit.

3. Data processing method

And establishing an ROC curve of the target protein in the data set, and calculating the area under the curve (AUC) and a 95% confidence interval. And calculating the diagnosis accuracy of the target protein for RA and OA by taking the optimal cut-off value obtained by the ROC curve as a threshold value.

Third, experimental results

1. Differential expression of target proteins in synovial tissue of RA and OA patients

17 differentially expressed genes are screened according to the bioinformatics data of the 8 data sets, the relative content of the synovial fluid ADAMDEC1 of the joint of RA patients is remarkably increased compared with that of OA patients, and the data analysis result is shown in figure 1.

2. ROC curve for diagnosis of target protein to distinguish RA from OA patients

The ROC curve is a curve drawn by base and sensitivity and specificity. And (4) taking the possible diagnosis limit values in the diagnosis test as diagnosis points, and calculating the corresponding sensitivity and specificity. The ROC curve is a possible diagnosis threshold value of each detection result, and the size of the area AUC under the curve indicates the accuracy of the diagnosis test. The AUC of the area under the ROC curve is generally accepted as the inherent accuracy index of the authenticity evaluation of the diagnostic test, and when the AUC is 0.5, the diagnostic significance is not achieved; when the AUC is 0.5-0.7, the diagnosis accuracy is low; when the AUC is 0.7-0.9, the diagnosis accuracy is moderate; AUC >0.9, indicating higher accuracy of diagnosis. The sensitivity and specificity of ADAMDEC1 for distinguishing RA from OA patients in gene expression data set samples were calculated, and ROC curves (shown in FIG. 2) were drawn based on the results, AUC was 0.9989, sensitivity was 100%, and specificity was 97.83%. The optimal cut-off value to distinguish RA from OA patients is 7.047.

3. Verification of accuracy of target protein diagnosis in distinguishing RA from OA patients

In joint synovial fluid samples, joint synovial fluid samples of RA combination OA patients are predicted by taking the optimal cut-off value for distinguishing RA and OA patients by ADAMDEC1 as a diagnosis threshold, and the consistency of the optimal cut-off value is the accuracy of distinguishing RA combination OA and OA patients by the target protein. The accuracy of ADAMDEC1 diagnosis for distinguishing RA-pooled OA and OA patients was 89.80%, AUC was 0.9510, sensitivity was 92.86%, specificity was 88.57%, and optimal cut-off value was 1957.155pg/ml (as shown in FIGS. 3 and 4).

In conclusion, the joint synovial membrane protein ADAMDEC1 has extremely high diagnostic value in the aspect of diagnosing and distinguishing RA and OA patients, has high diagnostic accuracy, is objective and easy to operate compared with the existing DAS28 scoring system, and can be used as a diagnostic kit for distinguishing RA and OA patients.