CN113604553B

CN113604553B - Adult still's disease biomarker, diagnostic reagent and application thereof

Info

Publication number: CN113604553B
Application number: CN202110850962.6A
Authority: CN
Inventors: 陆前进; 赵明; 饶诗佳; 龙海; 张博; 李雨薇
Original assignee: Second Xiangya Hospital of Central South University
Current assignee: Second Xiangya Hospital of Central South University
Priority date: 2021-07-27
Filing date: 2021-07-27
Publication date: 2023-08-15
Anticipated expiration: 2041-07-27
Also published as: CN113604553A

Abstract

The invention discloses a DNA methylation marker of adult still's Disease (Adult Onset Still's Disease, AOSD), a diagnostic reagent and application thereof. Comprising 6 methylation sites: one or more of chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6: 139794538. The invention uses specific DNA methylation sites as molecular markers for the first time to carry out auxiliary screening on adult still patients, healthy people, rheumatoid arthritis (Rheumatoid Arthritis, RA), sepsis (Sepsis), drug eruption (drug eruption) and T cell lymphoma (TcellLymphoma) patients, opens up a new way and mode for diagnosis in the field, has fewer needed blood specimens, is convenient and easy to develop, and has good application prospect.

Description

Adult still's disease biomarker, diagnostic reagent and application thereof

Technical Field

The invention belongs to the technical field of medical molecular biology detection, and particularly relates to a diagnostic marker and a diagnostic reagent for adult still's disease and application thereof.

Technical Field

Adult still's Disease (Adult Onset Still' Disease, AOSD) is a rare clinical syndrome that involves systemic multisystems. At present, the cause of the disease is not clear, the pathogenesis of the disease is complex, and the disease is often considered to be influenced by factors such as infection, heredity, immunity and the like. Because adult still's disease has a low incidence rate and lacks specific clinical characteristics and laboratory examination indexes, diseases such as infection, tumor, connective tissue disease and the like must be removed first before clinical diagnosis, so that the diagnosis of the disease at present is still a great challenge for clinicians. Moreover, the diagnosis elimination process is long, the examination items are numerous, and some invasive examinations are included, so that the psychological, physiological and economic burdens of patients are brought. There is a constant search for a highly specific marker that can diagnose adult still's disease rapidly, accurately and with low risk of injury.

Epigenetic markers are epigenetic molecules in peripheral blood, other body fluids or tissues, which can reflect the occurrence and development of diseases, and are non-invasive, easy to detect, capable of reflecting disease activity and drug therapeutic ability, and specific epigenetic modifications can be used as novel biomarkers for diseases.

At present, there is no satisfactory high-sensitivity high-specificity AOSD diagnostic marker in clinic, and IL-18 is not unique to AOSD as a cytokine although more is reported; ferritin binding glycosylated ferritin analysis together can improve sensitivity and specificity, but it is also not unique to AOSD and difficult to develop; other studies reported AOSD biomarkers such as sCD163, AGEs and sRAGE, S100A 8/A9 and A12, CXCL10, CXCL13, and the like lack multi-organization co-validation. For this reason, AOSD patients often need to combine other auxiliary items including invasive examinations such as bone marrow puncture and more expensive examinations such as PET-CT, so that diagnosis and treatment costs of the disease are greatly increased, and psychological, physiological and economic burdens of the patients are increased. Therefore, it is necessary to develop a novel AOSD diagnostic marker with high sensitivity and high specificity, and it is important to increase the diagnosis and treatment level of AOSD.

Disclosure of Invention

The present invention finds biomarkers for early diagnosis of AOSD comprising 6 CpG sites (methylation sites) located on different DNA fragments, which can aid early diagnosis of AOSD by detecting methylation levels at 6 CpG sites, analyzing single site methylation levels or combining Logistic binary regression and ROC curve analysis, while also being able to distinguish between rheumatoid arthritis (Rheumatoid Arthritis, RA), sepsis (Sepsis, SP), drug eruption (DrugEruption, DE) and T cell Lymphoma (Tcell Lymphoma, TL).

The primary object of the present invention is to provide the use of a product for detecting the methylation level of one or more of 6 methylation sites in the preparation of a formulation for aiding in the diagnosis of adult still's disease.

The 6 methylation sites are: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6:139794538.

Specifically, for adult still's patients, the methylation levels of chr11:114167495, chr6:35654359, chr6:35654363 and chr6:139794538 are reduced compared with the healthy control group, and the methylation levels of chr1:198568084 and chr13:113327910 are increased compared with the healthy control group.

To improve the reliability of diagnosis, the methylation levels of these methylation sites are further used to distinguish between rheumatoid arthritis (Rheumatoid Arthritis, RA), sepsis (Sepsis, SP), drug eruptions (DrugEruption, DE) and T cell Lymphoma (Tcell Lymphoma, TL) diseases that are similar to the symptoms of adult still's disease patients. The method comprises the following steps:

The methylation level of chr11:114167495, chr1:198568084, chr6:35654359 and chr6:35654363 of adult still's patients is reduced compared with rheumatoid arthritis, and the methylation level of chr13:113327910 is increased compared with rheumatoid arthritis; adult patients with still's disease have reduced methylation levels at chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363 compared to sepsis, and increased methylation levels at chr13:113327910 compared to sepsis; the methylation level of the chr11:114167495, chr6:35654359 and chr6:35654363 sites of adult still's patients is reduced compared with the drug eruption, and the methylation level of the chr1:198568084 and chr13:113327910 sites is increased compared with the drug eruption; adult patients with still's disease have a reduced methylation level at positions chr11:114167495, chr6:35654359, chr6:35654363, chr6:139794538 compared to T cell lymphoma, and a higher methylation level at positions chr1:198568084, chr13:113327910 compared to T cell lymphoma.

Further, the product obtains methylation levels of 6 CpG sites contained in the sequence by analyzing a plurality of sample sequencing results, singly analyzes methylation levels of one CpG site, or combines methylation levels of a plurality of CpG sites to perform binary Logistic regression analysis, and makes a formula for detecting a sample to be detected, preferably one CpG site, two CpG site combinations, three CpG site combinations, four CpG site combinations or five CpG site combinations.

Preferably, adult stinll's disease is compared to healthy control,

binary Logistic regression analysis is performed by combining methylation levels of 2 CpG sites to obtain a formula Y= -0.224A+0.068B+8.901; y is greater than-0.589, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.155A-0.286C+17.499; y is larger than 0.5905, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.147A-0.189D+17.241; y is larger than 0.0735, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.226A+0.044E+10.904; y is greater than-0.423, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.06B-0.365 C+5.238; y is greater than-0.2395, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.077B-0.232D+3.976; y value is greater than 0.431, and adult still's disease is diagnosed;

Or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.187C-0.151D+11.352; y is larger than 0.4645, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.376C+0.0110+9.227; y is greater than-0.045, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.233D+0.025E+7.876; y is larger than 0.5435, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.157A+0.025B-0.266C+15.185; y is greater than 0.6335, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.14A+0.044B-0.18D+13.127; y is greater than 0.227, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.215A+0.05B+0.045E+6.234; y is greater than-0.1485, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.137A-0.163C-0.112D+17.754; y is greater than 0.533, and is diagnosed as adult still's disease;

Or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.154A-0.28C-0.00PE+17.808; y value is greater than 0.574, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.144A-0.182D+0.004E+16.438; y is greater than 0.048, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.07B-0.171C-0.151D+5.668; y is greater than-0.371, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.058B-0.354C+0.003E+4.856; y is greater than-0.272, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.076B-0.223D+0.016E+2.509; y is greater than 0.561, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.179C-0.147D+0.0110.133; y is greater than 0.314, and is diagnosed as adult still's disease;

Or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.134A+0.031B-0.151C-0.108D+14.773; y is larger than 0.2295, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.155A+0.025B-0.259C-0.004E+15.221; y is greater than 0.666, and is diagnosed as adult still's disease;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.137A+0.043B-0.173D+0.003E+12.548; y is greater than 0.31, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.135A-0.157C-0.109D-0.002E+17.574; y is greater than 0.586, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y=0.07B-0.164C-0.147D+0.004E+5.129; y is greater than 0.161, and adult still's disease is diagnosed;

or combining methylation levels of 5 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.132A+0.031B-0.145C-0.106D-0.002E+14.59; y is larger than 0.2535, and adult still's disease is diagnosed;

Wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; e represents the methylation number of chr13: 113327910.

Adult stinll's disease is compared with rheumatoid arthritis,

binary Logistic regression analysis is performed in combination with methylation levels of 2 CpG sites to obtain a formula Y= -0.335A-1.209B+123.735; y is greater than 0.0615, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.642B-0.113C+57.602; y is larger than 0.6385, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.727B-0.118D+66.571; y is larger than 0.9905, and adult still's disease is diagnosed;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.618B+0.186E+38.784; y is greater than 0.303, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.347A-1.216B+0.044C+124.233; y is greater than 0.237, and adult still's disease is diagnosed;

Or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.311A-1.247B-0.072D+127.695; y is greater than 0.052, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.393A-1.182B+0.241E+105.428; y is greater than-0.289, diagnosing adult stinll's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.166A+0.542C-0.245D+7.598; y is greater than 0.32, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.182A+0.136C+0.034E+5.913; y is greater than 1.055, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.673B+0.232C-0.205D+60.292; y is greater than 0.811, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.641B-0.062C+0.1688E+43.279; y is greater than 0.6465, and adult still's disease is diagnosed;

Or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.742B-0.112D+0.16E+55.059; y is greater than 0.649, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.372A-1.304B+0.329C-0.188D+133.636; y is greater than-0.5185, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.472A-1.202B+0.164C+0.294E+105.134; y is larger than 0.9485, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.363A-1.23B-0.058D+0.231E+110.375; y is greater than 1.026, and is diagnosed as adult still's disease;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.171A+0.562C-0.246D+0.034E+4.828; y is greater than 0.095, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.6744B+0.284C-0.225D+0.182E+45.58; y value is greater than 0.413, and is diagnosed as adult still's disease;

Or combining methylation levels of 5 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.512A-1.333B+0.522C-0.244 D+0.348 E+114.933; y is greater than-0.4115, and adult still's disease is diagnosed;

wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; e represents the methylation value of chr13: 113327910;

adult stinll's disease is compared with sepsis,

binary Logistic regression analysis is performed in combination with methylation levels of 2 CpG sites to obtain a formula Y= -0.189A-0.424B+47.342; y is greater than 1.612, and is diagnosed as adult still's disease;

or combining methylation levels of 2 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.284B+0.152E+13.101; y is larger than 1.719, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.177A-0.483B-0.085C+53.338; y is larger than 2.033, and adult still's disease is diagnosed;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.185A-0.487B-0.048D+53.961; y is larger than 1.3705, and adult still's disease is diagnosed;

Or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.227A-0.545B+0.185E+45.262; y is greater than 1.43, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.347B-0.087C+0.143E+20.879; y is greater than 1.59, and is diagnosed as adult still's disease;

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.354B-0.057D+0.156E+20.446; y is greater than 1.063, and is diagnosed as adult still's disease;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.191A-0.47B+0.0719D+52.403; y is larger than 1.2075, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.22A-0.566B-0.037C+0.181E+47.712; y is larger than 0.7945, and adult still's disease is diagnosed;

or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.239A-0.626B-0.033D+0.204E+52.431; y is larger than 1.158, and adult still's disease is diagnosed;

Or combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.345B+0.031C-0.07D+0.157E+19.472; y is greater than 1.554, and is diagnosed as adult still's disease;

or combining methylation levels of 5 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.276A-0.608B+0.211C-0.119D+0.228E+49.789; y is larger than 2.4195, and adult still's disease is diagnosed;

compared with the drug eruption,

binary Logistic regression analysis is performed in combination with methylation levels of 4 CpG sites to obtain a formula Y= -0.129A+0.597C-0.233D+0.092E-2.065; y is larger than 2.0895, and adult still's disease is diagnosed;

or combining methylation levels of 5 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.128A+0.034B+0.67C-0.249D+0.115E-7.468; y is greater than 1.637, and is diagnosed as adult still's disease;

Adult stinll's disease is compared to T cell lymphomas,

according to the methylation level value of the single site of the sample chr6:139794538 to be detected, diagnosing adult still's disease when the value is smaller than 58.42; furthermore, when the Pouchot's score of the patient to be diagnosed is more than or equal to 4 points, namely the score meets the active period standard of the adult stinll's disease, diagnosing the adult stinll's disease according to the methylation value of the single site of the sample chr6:139794538 to be detected, and when the value is less than 57.79.

It is a second object of the present invention to provide an AOSD diagnostic reagent comprising a product for detecting the methylation level of the above 6 methylation sites.

Further, the product includes PCR reagents and pyrosequencing reagents.

Further, the primer pairs adopted by the PCR reagent are as follows:

chr11:114167495：F：GGTGATGTTAAAAGGGTTGTGAA

R：ATCTATTATCTACATATCTCCCCACTA

chr1:198568084：F：AGGGAATAGGTAGTTTGGTGAATTA

R：ATAAACTTTAACCACCACCATCTA

chr6:35654359 and chr6:35654363:

F：TTGGGTTTAGTTTAGTTTTTTAAAGGT

R：CTTATCCAATTCCTTTCAACTATTTACA

chr13:113327910：F：AGAGGATTTAGTTGGTTATATGTAGAT

R：AATAATCTACCCCCCTTAACCTCCCA

chr6:139794538：F：ATGGTTAGGAGTAGTTTAAAAAGTTGTAT

R：TTCCCCTCCCCCTCTCTAATA

it is a third object of the present invention to provide DNA methylation markers for AOSD comprising 6 methylation sites: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6:139794538.

Wherein the two methylation sites on chr6:35654359 and chr6:35654363, namely chr6:cg03546163, can share the same primer pair.

The methylation site screening method comprises the following steps:

Dna methylation CpG site screening: whole blood samples of 50 AOSD and 49 healthy controls (NC) were tested on a whole blood genome 850k methylation chip to screen DNA methylation CpG sites for differences in expression between AOSD and healthy controls. Whole blood genome 850k methylation chip detection is carried out on 50 AOSD, 50 rheumatoid arthritis, 24 sepsis, 24 drug eruptions and 24T cell lymphomas, and DNA methylation CpG sites with different expression between AOSD and disease control are screened.

2. Identification of DNA methylation markers: and (3) carrying out pyrosequencing on the screened DNA methylation CpG sites, and carrying out large sample verification in AOSD, healthy control and rheumatoid arthritis, sepsis, drug eruption and T cell lymphoma patients to identify the DNA methylation CpG sites which can be used for auxiliary diagnosis of the AOSD. And ROC curve analysis is carried out to obtain the specificity, sensitivity and other numerical values of the DNA methylation marker.

The specific experimental steps comprise: (1) extracting whole genome DNA of peripheral blood of a subject; (2) determining the concentration of extracted genomic DNA; (3) sulfite treating genomic DNA; (4) amplifying the DNA fragment to be detected by the specific PCR primer; (5) detecting the PCR product by agarose gel electrophoresis; (6) pyrosequencing the PCR product; (7) Analyzing the sequencing result to obtain methylation levels of 6 CG sites contained in the sequence to be detected, and analyzing the methylation level of one CpG site independently or combining the methylation levels of 1, 2, 3, 4 or 5 CpG sites to perform binary Logistic regression analysis, and making a formula to obtain a Y value, and performing ROC curve analysis by using the Y value to obtain AUC, sensitivity and specificity of diagnosis AOSD.

The Y-value corresponding to methylation levels of 5 CpG sites was used for ROC profile for AOSD diagnosis compared to healthy controls, see fig. 3.

Compared to rheumatoid arthritis, the Y values corresponding to methylation levels of 4 CpG sites are used for the ROC profile of AOSD diagnosis, see FIG. 4.

The Y values corresponding to methylation levels of 5 CpG sites compared to sepsis are used for the ROC profile of AOSD diagnosis, see FIG. 5.

The Y values corresponding to methylation levels of 4 CpG sites compared to drug eruptions are used for the ROC profile of AOSD diagnosis, see FIG. 6.

In contrast to T cell lymphomas, chr6:139794538 is used for the ROC profile of AOSD diagnosis, see FIG. 7.

In contrast to T cell lymphomas, chr6:139794538 is used for ROC profiling of active AOSD diagnosis, see FIG. 8.

The invention has the beneficial effects that:

the invention uses the screened specific DNA methylation site as a molecular marker for the first time to carry out auxiliary screening on patients with AOSD, rheumatoid arthritis, sepsis, drug eruption and T cell lymphoma, and opens up a new way and mode for diagnosis in the field.

The invention utilizes the whole blood of the patient to detect the DNA methylation site, achieves the aim of early auxiliary diagnosis of the AOSD, can further distinguish the patients with rheumatoid arthritis, sepsis, drug eruptions and T cell lymphomas, has less blood specimens, is convenient and easy to develop, and has good application prospect.

Drawings

FIG. 1 is a graph showing the results of methylation chip detection of 8 DNA methylation CpG sites screened for differential expression between AOSD and healthy control;

FIG. 2 is a graph showing the results of methylation chip detection of 18 DNA methylation CpG sites screened for differential expression of AOSD and disease control;

FIG. 3 is an agarose gel electrophoresis of 5 pairs of primers designed based on 6 CpG sites for PCR amplification of a target DNA fragment;

FIG. 4 is a graph comparing methylation levels of 6 CpG sites of AOSD with NC and other disease controls.

FIG. 5 is a graph of ROC for AOSD diagnosis at average methylation levels of 5 CpG sites compared to healthy controls;

FIG. 6 is a graph of ROC for average methylation level of 4 CpG sites compared to rheumatoid arthritis for AOSD diagnosis;

FIG. 7 is a graph of ROC for average methylation levels of 5 CpG sites compared to sepsis for AOSD diagnosis;

FIG. 8 is a graph of ROC for AOSD diagnosis at average methylation levels for 4 CpG sites compared to drug eruptions;

FIG. 9 is a ROC graph of methylation levels of chr6:139794538 compared to T cell lymphoma for AOSD diagnosis;

FIG. 10 is a ROC graph of the methylation level of chr6:139794538 compared to T cell lymphoma for active AOSD diagnosis.

Detailed Description

For a further understanding of the present invention, reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The following description of embodiments of the invention should not be construed as limiting the invention in any way, and all other embodiments, which may be made by those of ordinary skill in the art without the benefit of the present disclosure, are intended to be encompassed by the present invention. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

Unless otherwise specified, all reagents involved in the examples of the present invention are commercially available products and are commercially available.

The AOSD cases incorporated by the invention are all patients clinically diagnosed as adult still's disease by dermatologists or rheumatists, all meet the Yamaguchi standard, and exclude any of the following cases combined: 1. rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, dermatomyositis, connective tissue diseases such as malignant tumor, and severe infection.

Normal people: healthy, not suffering from adult still's disease, excluding any combination of the following: 1. rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, dermatomyositis, connective tissue diseases such as malignant tumor, and severe infection.

All rheumatoid arthritis patients met the rheumatoid arthritis diagnostic criteria of the american society of rheumatisms (ACR) and excluded any combination of the following: 1. osteoarthritis, ankylosing spondylitis, psoriatic arthritis 2, connective tissue diseases such as systemic lupus erythematosus, dermatomyositis and the like 3, adult still's disease and related arthritis.

All sepsis patients met the sepsis-2 consensus standard, excluding the concomitant adult stilll's disease.

All patients with drug eruptions were diagnosed by clinical manifestations and clear drug history, excluding the concomitant adult still's disease.

The T cell lymphoma patients included in the invention comprise 5 subtypes of peripheral T cell lymphoma, angioimmunoblastic T cell lymphoma, subcutaneous panomeningitis-like T cell lymphoma, extranodal NK/T cell lymphoma and cutaneous T cell lymphoma, all conform to the diagnostic criteria of the national Integrated cancer network (NCCN) guidelines, and exclude the incorporation of any of the following: 1. other lymphadenomegaly diseases 2 are definitely diagnosed with infectious mononucleosis 3, with connective tissue diseases such as systemic lupus erythematosus and dermatomyositis 4, with other malignant tumors 5, with infectious diseases 6, adult still's disease.

Examples:

1. DNA methylation CpG site screening

Whole blood samples of 50 AOSD and 49 healthy controls were subjected to whole blood genome 850k methylation chip detection, and DNA methylation CpG sites with differential expression between AOSD and healthy controls were initially screened. Whole blood genome 850k methylation chip detection is carried out on 50 AOSD and 50 rheumatoid arthritis, 24 sepsis cases, 24 drug eruptions and 24T cell lymphomas, and DNA methylation CpG sites with different expression of AOSD and disease control are initially screened.

2. DNA methylation CpG site identification

By designing primers, amplifying target gene bands by PCR, pyrosequencing and other experiments. Differentially expressed DNA methylation CpG sites were finally screened and identified for diagnosis of AOSD.

Experimental reagent:

(1) Reagents for extracting whole blood DNA: gene jet whole blood genome DNA purification kit (Thermo Scientific Sieimer's fly), reagent product number K0782, lot 00239303

TABLE 1

(2) Reagent required for sulfite treatment: DNA methylation kit (EZ DNA Methylation) ^TM Kit, zymo Research), cat No. D5002

TABLE 2

* Each tube of CT transformation reagent was mixed with 750. Mu.l of water and 210. Mu.l of dilution buffer.

* 96 ml of 100% ethanol was added to 24ml of wash buffer.

(3) Reagents required for PCR:

TABLE 3 Table 3

(4) Reagents required for pyrosequencing:

TABLE 4 Table 4

The equipment used in the experiment:

genomic DNA purification column, collection tube, pipetting gun, pipetting tip head, disposable glove, 1.5mL centrifuge tube, PCR tube, micro centrifuge, hybridization oven, vortex shaker; hybridization oven, nanoDrop 2000 ultraviolet spectrophotometer, PCR instrument (eppendorf), agarose gel electrophoresis instrument, real-time quantitative pyrophosphate sequence analyzer (PyroMark Q24).

The experimental steps are as follows:

step 1: extraction of peripheral blood genome DNA of adult still's disease patient

(using a commercial whole blood DNA extraction kit):

(1) 200 μl of whole blood is taken to a 1.5ml centrifuge tube, then 20 μl of proteinase K solution is added, and vortex mixing is carried out; (2) 400. Mu.l of the lysate was added and vortexed. (3) incubating for 10min at 56 ℃ in a hybridization oven; (3) adding 200 μl of absolute ethanol, and mixing upside down; (4) Transferring the mixed solution into a centrifugal adsorption column, and centrifuging 6000g for 1min; (5) transferring the adsorption column to a new waste liquid pipe; (6) Adding 500 μl of washing buffer 1, centrifuging at 8000g (1000 rpm) for 1min, and discarding the waste liquid; (6) Adding 500 μl of washing buffer 2, centrifuging for 3min with 13000g, and discarding the waste liquid; (7) 13000g again centrifuged for 1min, and the column is transferred to a new 1.5ml centrifuge tube; (8) adding 70 μl of elution buffer, and standing at room temperature for 2min; (9) centrifuging at 8000g for 1min, and collecting genomic DNA.

Step 2, determining the concentration and purity of the extracted genome DNA;

1. Mu.l of the DNA sample was aspirated and spotted onto a detection plate using a Nanodrop 2000 ultraviolet spectrophotometer from Sieimer (Thermo Scientific), and the concentration of the sample and A260/A280 were read from the instrument. The DNA concentration of the sample to be tested is diluted to 10-25 ng/. Mu.l.

Step 3, treating genome DNA with sulfite;

(1) Based on the DNA concentration, a sampling volume of 200ng of the DNA required for sulfite treatment was calculated; (2) preparing CT conversion reagent in dark: 750ul of enzyme-free water plus 210 ul of dilution buffer is vortexed and mixed uniformly to avoid light for 15min; (3) 130. Mu.l of the conversion reagent was added to 20. Mu.l of DNA sample and placed in PCR tubes. (4) the mixture is reacted in a PCR instrument: 98 ℃ for 8min;54 ℃ for 60min. (5) The reaction solution from step (4) and 600. Mu.l of the binding buffer were added to the column and mixed up and down several times. (6) 11000g, centrifuging for 30s, and discarding the lower solution. (7) 100 μl wash buffer, 11000g, was added, centrifuged for 30s and the lower solution discarded. (8) 200. Mu.l of desulfurization solution was added thereto, followed by centrifugation at room temperature (20-30 ℃) for 15-20min,11000g and 30s. (9) 200 μl wash buffer, 11000g, was added, centrifuged for 1min and the lower solution was discarded. (10) 200 μl wash buffer, 13000g, was added, centrifuged for 3min and the lower solution was discarded. (11) The centrifugal column is placed in a new 1.5ml centrifugal tube, 40 μl of eluent is added, 8000g is added, and the centrifugal column is centrifuged for 30s, and the DNA after sulfite treatment is collected in the centrifugal tube.

Step 4, determining the concentration and purity of the genome DNA after bisulphite treatment;

2. Mu.l of DNA sample was aspirated and spotted onto a detection plate using a Nanodrop 2000 UV spectrophotometer from Sieimer's flight (Thermo Scientific), and the concentration of the sample and A260/A280 were read from the instrument.

Step 5 PCR amplification of the DNA fragment of interest

Primer sequence required for amplifying DNA fragments with 6 CPG sites

chr11:114167495：

F: GGTGATGTTAAAAGGGTTGTGAA, as shown in SEQ ID NO. 1.

R: ATCTATTATCTACATATCTCCCCACTA, as shown in SEQ ID NO. 2.

Pyrosequencing sequence: GAAGTAATAAAGAGAGATATAAAAT, as shown in SEQ ID NO. 3.

chr1:198568084：

F: AGGGAATAGGTAGTTTGGTGAATTA as shown in SEQ ID NO. 4.

R: ATAAACTTTAACCACCACCATCTA, as shown in SEQ ID NO. 5.

Pyrosequencing sequence: TTTATATTTTATTGGGTTAAGTAAG, as shown in SEQ ID NO. 6.

chr6:35654359 and chr6:35654363:

f: TTGGGTTTAGTTTAGTTTTTTAAAGGT as shown in SEQ ID NO. 7.

R: CTTATCCAATTCCTTTCAACTATTTACA as shown in SEQ ID NO. 8.

Pyrosequencing sequence: ATAGGTTGAATAATAATTTAT as shown in SEQ ID NO. 9.

chr13:113327910：

F: AGAGGATTTAGTTGGTTATATGTAGAT as shown in SEQ ID NO. 10.

R: AATAATCTACCCCCCTTAACCTCCCA, as shown in SEQ ID NO. 11.

Pyrosequencing sequence: ATGTAGATTTTTGATTTATGGAA, as shown in SEQ ID NO. 12.

chr6:139794538：

F: ATGGTTAGGAGTAGTTTAAAAAGTTGTAT as shown in SEQ ID NO. 13.

R: TTCCCCTCCCCCTCTCTAATA as shown in SEQ ID NO. 14.

Pyrosequencing sequence: ATAGTAGAAGGAGGTATT as shown in SEQ ID NO. 15.

TABLE 5 PCR reaction System

TABLE 6 PCR reaction conditions

	Temperature (. Degree. C.)	Time
			1	96	2min
2	96	10s
			3	50-60	30s
4	72	1min
			5	Step 2-4 40 cycles
6	72	10min
			7	4	Continuous and continuous

Step 6, pyrosequencing

1. Agarose bead immobilized PCR products

Immobilization of Biotin-labeled PCR products onto streptavidin-modified coated agarose beads

(1) The agarose beads were coated with modification with light-shaking streptavidin until a homogeneous solution was obtained.

(2) Streptavidin-modified coated agarose beads (2. Mu.l/sample) were mixed with binding buffer (40. Mu.l/sample), 18. Mu.l of high purity water in one tube. The above solution was added to an 8-row tube.

(3) Add 20. Mu.l of biotin-labeled PCR product to the PCR array (total volume of each well is 80. Mu.l).

(4) The row of tubes is sealed using an orifice plate strip cover.

(5) The PCR row tube was continuously shaken with a shaker at 1400rpm for at least 5-10min. ( Note that: agarose beads precipitate rapidly and therefore must be used immediately within one minute after shaking is stopped, i.e., the agarose beads are immediately captured )

2. Vacuum station preparation

(1) The following reagents were prepared: 50ml of 70% ethanol; 40ml of denaturing solution; 50ml of 1 Xwash buffer; 50ml of high purity water; 70ml of high purity water.

1 Xwashing buffer preparation: 5 Xwashing buffer 5ml + high purity water 45ml.

(2) And (5) turning on the vacuum pump, turning on the vacuum switch, and performing a test to determine whether the filtering probe works normally.

(3) The permeability of the filtration probe was measured with high purity water before each use of the vacuum pump. A centrifuge tube containing high purity water prepared in advance was inserted into the PCR well, and the filter probe was lowered into the high purity water, which was evacuated within 20 seconds to indicate that the filter probe was normal and usable. Otherwise, the filter probe needs to be replaced.

(4) Taking down the oscillated PCR row tube, putting the sample into a PCR hole groove, carefully lowering the filtering probe into the PCR row tube, and staying for 15 seconds; ensure that all solution is aspirated to capture the microbeads containing the immobilized template (ensure that all liquid in the centrifuge tube is aspirated and all microbeads have been captured on top of the filter probe.)

(5) The vacuum was moved to the reagent tank 1 containing 70% ethanol and the filter probe was rinsed for 5 seconds.

(6) The vacuum was moved to the reagent tank 2 containing the denaturing solution and the filter probe was rinsed for 5 seconds.

(7) The vacuum was moved to the reagent tank 3 containing wash buffer and the filter probe was rinsed for 10 seconds.

(8) The vacuum was raised above the 90 ° vertical line for 5 seconds to drain the fluid from the filter needle.

(9) The switch on the vacuum device is closed and placed in the rest (P) position.

3. Isolation of DNA Single strands and release of samples into PyroMark Q24 well plates

(1) PyroMark Q24 well plates were placed on a pre-heated well plate base and heated accurately at 80℃for 2min.

(2) The well plate was removed from the well plate base and the sample was allowed to cool at room temperature (15-25 ℃) for at least 5min.

Preparation of PyroMark Q24 reagent

(1) The PyroMark Q24 kit was opened and vials containing enzyme and substrate lyophilized powder, as well as tubes containing nucleotides, were removed.

(2) According to the instruction of the kit, the enzyme and the substrate are dissolved and separated by high-purity water (the dissolved enzyme and substrate need to be stored at-20 ℃ C., and can be repeatedly frozen and thawed for 3 times at most, and the nucleotide can be stored at 4 ℃ C.), and all reagents need to be reused after being restored to room temperature.

(3) Enzyme, substrate and nucleotide A, T, G, C were added to the cartridge (cartridge was used up to 30 times, the cartridge had to be dried before use) according to the volumes calculated by the computer program.

5. Run on a real-time quantitative pyrophosphate sequencer (PyroMark Q24)

(1) Opening PyroMark Q24 software, clicking new assay→new AQ assay→inputting a mutation point sequence in sequence analysis, clicking generate pupensation, clicking for storage;

(2) Click new run→ Instrement method →005, then click the grid to be sequenced, click save to USB flash disk.

(3) And inserting the USB flash disk containing the running file into a USB port in front of the instrument.

(4) The heated well plate was placed on the instrument.

(5) The label surface of the reagent bin (enzyme, substrate and nucleotide) faces to the self-placing instrument, the orifice plate support frame is opened to be placed into the orifice plate, and the orifice plate support frame and the instrument cover are closed.

(6) Run is selected and OK is pressed.

(7) After entering Run, the file to be Run is selected by select.

(8) And after the instrument operation is finished and the operation file is confirmed to be stored in the U disk, the U disk is taken out according to close.

(9) Experimental data were analyzed.

Test results:

1. DNA methylation CpG site screening

Whole blood samples of 50 AOSD and 49 healthy controls were subjected to whole blood genome 850k methylation chip detection, and 8 DNA methylation CpG sites, 1.cg123741610, 2.cg00329101, 3.cg14521435, 4.cg25569341, 5.cg20747787, 6.cg09574909, 7.cg03546163, and 8.cg02863807, respectively, were screened for differential expression between AOSD and healthy controls. See fig. 1.

Whole blood samples of 50 AOSD and 49 healthy controls, 50 rheumatoid, 24 sepsis, 24 drug eruptions, 24T cell lymphomas were tested on a whole blood genome 850k methylation chip, and 18 DNA methylation CpG sites with differential expression of AOSD and disease controls were screened together, 1.cg00329101, 2.cg01849514, 3.cg02053407, 4.cg03064100, 5.cg03546163, 6.cg03581638, 7.cg07732037, 8.cg08043317, 9.cg08145373, 10.cg0957809, 11.cg14887853, 12.cg15551881, 13.cg15568074, 14.cg163817, 15.cg22425699, 16.cg22963164, 17.cg24894783, 18.cg259341, respectively. See fig. 2.

2. Identification of DNA methylation CpG sites

Through experiments such as primer design, PCR amplification target gene strip, pyrosequencing and the like, 6 differentially expressed DNA methylation CpG sites are finally screened out for diagnosis of AOSD. The 6 methylation sites include: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6:139794538.

As can be seen from fig. 3: after PCR using primers for DNA fragments with 6 CpG sites, a bright specific target gene band exists, and the primers have specificity.

FIG. 4 is a comparison of the methylation levels of 6 CpG sites, AOSD, NC and DC, respectively, and it can be seen from FIG. 4 that the methylation levels of 4 CpG sites, chr11:114167495, chr6:35654359, chr6:35654363, chr6:139794538, are reduced and the differences are statistically significant, compared to AOSD and NC; the methylation level of these 2 CpG sites is elevated, and the differences are statistically significant, for chr1:198568084, chr13: 113327910. The methylation level of 3 CpG sites was reduced compared to AOSD and Rheumatoid Arthritis (RA), wherein differences in 3 CpG sites of chr11:114167495, chr1:198568084, chr6:35654363 were statistically significant; methylation levels of 1 CpG site, chr13:113327910, were elevated, but the differences were not statistically significant. The methylation level of 3 CpG sites was reduced compared to Sepsis (SP), where differences in 2 CpG sites of chr11:114167495, chr1:198568084 were statistically significant; methylation levels of 1 CpG site, chr13:113327910, are elevated and the differences are statistically significant. The methylation level of 2 CpG sites was reduced compared to AOSD and Drug Eruption (DE), wherein the difference of chr11:114167495 at this CpG site was statistically significant; methylation levels of 2 CpG sites were elevated, with differences in this CpG site of chr13:113327910 being statistically significant. The methylation level of 3 CpG sites was reduced compared to the AOSD and T cell lymphoma (TL), where the difference in this CpG site of chr6:139794538 was statistically significant; methylation levels of 2 CpG sites were elevated, but none of the differences were statistically significant.

The methylation levels of chr11:114167495, chr6:35654359, chr6:35654363 and chr6:139794538 of adult still's patients are obviously reduced compared with the healthy control group, and the methylation levels of chr1:198568084 and chr13:113327910 of adult still's patients are obviously increased compared with the healthy control group; the methylation level of chr11:114167495, chr1:198568084, chr6:35654359 and chr6:35654363 of adult still's patients is obviously reduced or decreased compared with rheumatoid arthritis, and the methylation level of chr13:113327910 is increased compared with rheumatoid arthritis; the methylation level of chr11:114167495, chr1:198568084, chr6:35654359 and chr6:35654363 of adult still's patients is obviously reduced or decreased compared with sepsis, and the methylation level of chr13:113327910 is obviously increased compared with sepsis; the methylation level of the chr11:114167495, chr6:35654359 and chr6:35654363 sites of adult still's patients is obviously reduced or decreased compared with the drug eruption, and the methylation level of the chr1:198568084 and chr13:113327910 sites is obviously increased or increased compared with the drug eruption; adult patients with still's disease have significantly reduced or decreased methylation levels at the chr11:114167495, chr6:35654359, chr6:35654363, and chr6:139794538 sites compared to T cell lymphoma, and increased methylation levels at the chr1:198568084, and chr13:113327910 sites compared to T cell lymphoma.

3. Methylation levels of the above CpG sites were measured in 96 AOSD patients, 87 healthy controls and 50 RA patients, 28 SP patients, 21 DE patients, 62 TL patients using the above method. The methylation level of one CpG site is analyzed singly, or binary Logistic regression analysis is carried out by combining the methylation levels of a plurality of CpG sites to obtain a formula, a corresponding Y value is calculated, sensitivity and specificity of the Y value corresponding to the methylation levels of the CpG sites in diagnosis AOSD are calculated by utilizing ROC curve evaluation statistics, and the actual value range of the area under the ROC curve (AUC) is 0.5-1, and is generally considered: for one diagnostic test, the diagnostic value is low when the area under the ROC curve is between 0.5 and 0.7, medium when the area under the ROC curve is between 0.7 and 0.9, and high when the area under the ROC curve is above 0.9.

For example: compared with a healthy control group, the AOSD is combined with methylation levels of 5 CpG sites to perform binary Logistic regression analysis, so that a formula Y= -0.132A+0.031B-0.145C-0.106D-0.002E+14.59 is obtained; wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; e represents chr13:113327910. From the methylation values of the 5 CpG sites, the corresponding Y values were calculated, analyzed using ROC curves (fig. 5), compared to healthy controls: AUC:0.964 95% CI:0.938-0.989, sensitivity:88.5%, specificity:98.9%. The results show that a Y value greater than 0.2535 for AOSD patients compared to healthy controls can be considered diagnostic of AOSD. The Y value corresponding to the methylation level of these 5 CpG sites distinguishes AOSD patients from healthy controls with a sensitivity of 88.5% and a specificity of 98.9%.

Compared with the AOSD and the rheumatoid arthritis, the methylation level of 4 CpG sites is combined for binary Logistic regression analysis, so that the formula Y= -0.372A-1.304B+0.329C-0.188D+133.636 is obtained; wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; according to methylation values of 4 CpG sites of a sample to be tested, corresponding Y values are calculated, and compared with rheumatoid arthritis, the corresponding Y values are analyzed by using a ROC curve (figure 6): AUC:0.988 95% CI:0.975-1.000, sensitivity:97.8%, specificity:94%. The results show that a Y value greater than-0.5185 can be considered diagnostic of AOSD in AOSD patients compared to rheumatoid arthritis patients. The Y-value corresponding to the methylation level of these 4 CpG sites distinguishes AOSD patients from rheumatoid arthritis patients with a sensitivity of 97.8% and a specificity of 94%.

Compared with sepsis, AOSD combines methylation levels of 5 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.276A-0.608B+0.211C-0.119D+0.228E+49.789; wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; e represents chr13:113327910. From the methylation values of the 5 CpG sites, the corresponding Y values were calculated, analyzed by ROC curve (fig. 7), compared to sepsis: AUC:0.885 95% CI:0.808-0.962, sensitivity:77.1%, specificity:92.9%. The results show that a Y value greater than 2.4195 can be considered diagnostic of AOSD in AOSD patients compared to sepsis patients. The Y-value corresponding to the methylation level of these 5 CpG sites distinguishes AOSD patients from sepsis patients with sensitivity of 77.1% and specificity of 92.9%.

Compared with the drug eruption, the AOSD combines methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.129A+0.597C-0.233D+0.092E-2.065; wherein A represents chr11:114167495; c represents chr6:35654359; d represents chr6:35654363; e represents chr13:113327910. From the methylation values of the 4 CpG sites, the corresponding Y values were calculated and analyzed using ROC curves (fig. 8), compared to drug eruptions: AUC:0.842 95% CI:0.737-0.946, sensitivity:72%, specificity:90.5%. The results show that a Y value greater than 2.0895 can be considered diagnostic of AOSD in AOSD patients compared to drug eruption patients. The Y value corresponding to the methylation level of these 4 CpG sites distinguishes AOSD patients from drug eruption patients with sensitivity of 72% and specificity of 90.5%.

AOSD and T cell lymphoma compared with T cell lymphoma using ROC curve analysis (fig. 9) according to methylation number of chr6: 139794538: AUC:0.693 95% CI:0.606-0.781, sensitivity:79.6%, specificity:56.5%. The results show that methylation less than 58.42 for chr6:139794538 is considered diagnostic of AOSD in patients with AOSD compared to patients with T-cell lymphoma. The methylation level of chr6:139794538 was 79.6% and 56.5% specific for distinguishing patients with AOSD from patients with T cell lymphoma.

Active AOSD and T cell lymphoma compared to T cell lymphoma using ROC curve analysis (fig. 10) according to methylation number of chr6: 139794538: AUC:0.761 95% CI:0.673-0.850, sensitivity:81.5%, specificity:67.8%. The results show that methylation less than 57.79 for chr6:139794538 is considered diagnostic of AOSD in patients with AOSD compared to patients with T-cell lymphoma. The methylation level of chr6:139794538 was 81.5% specific for distinguishing patients with AOSD from patients with T cell lymphoma at 67.8%.

Tables 7, 8, 9, 10, 11 below are comparisons made taking as an example the diagnostic efficiency of diagnosing AOSDs in combination with 2, 3, 4, 5, or 6 CpG sites.

TABLE 7 comparison of diagnostic efficiency of AOSD by combined diagnosis of 2, 3, 4, 5 CpG sites, respectively, compared to healthy controls

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Table 8 comparison of diagnostic efficiency of combined diagnosis of AOSD for 2, 3, 4, 5 CpG sites, respectively, compared to the RA group

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TABLE 9 comparison of diagnostic efficiency of combined diagnosis of AOSD for 2, 3, 4, 5 CpG sites, respectively, compared to the SP group

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Table 10 comparison of diagnostic efficiency of combined diagnosis of AOSD for 4, 5 CpG sites, respectively, compared to the DE group

The area under ROC curve (AUC) of the combination of 2, 3 and 4 sites of TL was substantially between 0.5 and 0.65 in AOSD and TL groups, and was lower when the formula was calculated by logistic regression and ROC analysis was performed again with the Y value of the formula result, and therefore was not included.

Table 11 comparison of diagnostic efficiency of combined diagnosis of AOSD for 5 and 6 CpG sites, respectively, compared to the TL and AOSD groups

Taken together, the results show that the combined diagnosis of AOSD by combining single or multiple CpG sites has better AUC, sensitivity and specificity. However, the combined differentiation of AOSD and T cell lymphoma by multiple CpG sites has poor effect, and AUC, sensitivity and specificity are better when chr6:139794538 is used alone, and when the Pouchot score of a patient to be diagnosed is more than or equal to 4, the AUC, sensitivity and specificity are further improved, so that chr6:139794538 single site is selected to differentiate AOSD and T cell lymphoma.

The diagnosis of the AOSD is challenging mainly according to medical history and clinical manifestation, and no reliable molecular marker exists in clinical application, so that the DNA methylation marker can be used for auxiliary diagnosis of the AOSD, can be detected only by 200 mu l of whole blood of a patient in clinic, is convenient and practical, provides a new path for auxiliary diagnosis and screening of the AOSD and DC, and has good application prospect.

Sequence listing

<110> Xiangya two hospitals at university of south China

<120> adult still's disease biomarker, diagnostic reagent and uses thereof

<160> 15

<170> SIPOSequenceListing 1.0

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<213> Artificial sequence (Artificial Sequence)

<400> 2

atctattatc tacatatctc cccacta 27

<210> 3

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<212> DNA

<213> Artificial sequence (Artificial Sequence)

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gaagtaataa agagagatat aaaat 25

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<213> Artificial sequence (Artificial Sequence)

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agggaatagg tagtttggtg aatta 25

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<213> Artificial sequence (Artificial Sequence)

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ataaacttta accaccacca tcta 24

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<213> Artificial sequence (Artificial Sequence)

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tttatatttt attgggttaa gtaag 25

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<213> Artificial sequence (Artificial Sequence)

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ttgggtttag tttagttttt taaaggt 27

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<213> Artificial sequence (Artificial Sequence)

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cttatccaat tcctttcaac tatttaca 28

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Claims

1. Use of a product for detecting the methylation level of a combination of methylation sites in the preparation of a reagent for diagnosing adult still's disease; adult stinll's disease compared to healthy control,

Or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.157A+0.025B-0.266 C+ 15.185; y is greater than 0.6335, and is diagnosed as adult still's disease;

wherein A represents chr11:114167495; b represents chr1:198568084; c represents chr6:35654359; d represents chr6:35654363; e represents the methylation value of chr13: 113327910; the methylation value is the percent methylation.

2. Use of a product for detecting the methylation level of a combination of methylation sites in the preparation of a reagent for diagnosing adult still's disease; adult stinll's disease is compared with rheumatoid arthritis,

or combining methylation levels of 3 CpG sites to perform binary Logistic regression analysis to obtain a formula Y= -0.182A+0.136C+0.034E+ 5.913; y is greater than 1.055, and is diagnosed as adult still's disease;

3. Use of a product for detecting the methylation level of a combination of methylation sites in the preparation of a reagent for diagnosing adult still's disease; adult stinll's disease is compared with sepsis,

4. Use of a product for detecting the methylation level of a combination of methylation sites in the preparation of a reagent for diagnosing adult still's disease; compared with the drug eruption,

5. The use of a product for detecting the methylation level of a methylation site in the preparation of a reagent for diagnosing adult still's disease; distinguishing adult stinll's disease from T cell lymphomas,

According to the methylation level value of the single site of the sample chr6:139794538 to be detected, diagnosing adult still's disease when the value is smaller than 58.42; the methylation level value is the percent methylation.

6. The use according to claim 5, wherein,

when the Pouchot's score of the patient to be diagnosed is more than or equal to 4 points, namely the score meets the active period standard of the adult stilll's disease, diagnosing the adult stilll's disease according to the methylation value of the single site of the sample chr6:139794538 to be detected, and when the value is less than 57.79.