CN113604553A

CN113604553A - Biomarker and diagnostic reagent for adult still's disease and application thereof

Info

Publication number: CN113604553A
Application number: CN202110850962.6A
Authority: CN
Inventors: 陆前进; 赵明; 饶诗佳; 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: 2021-11-05
Anticipated expiration: 2041-07-27
Also published as: CN113604553B

Abstract

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

Description

Biomarker and diagnostic reagent for adult still's disease 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 (AOSD) is a rare clinical syndrome involving multiple systemic systems. At present, the etiology of the disease is not clear, the pathogenesis of the disease is complex, and the disease is considered to be influenced by factors such as infection, heredity, immunity and the like. Because the incidence rate of adult still's disease is low, and the specific clinical characteristics and laboratory examination indexes are lacked, diseases such as infection, tumor, connective tissue diseases and the like must be excluded before clinical diagnosis, so that the diagnosis of the diseases at present still remains a huge challenge for clinical doctors. Moreover, the process of excluding diagnosis is long, and the examination items are many, including some invasive examinations, which bring heavy burden to the psychology, physiology and economy of the patient. There is a constant search for a highly specific marker that can be used to diagnose adult still's disease rapidly, accurately and with low toxicity.

The epigenetic marker is an epigenetic molecule in peripheral blood, other body fluids or tissues, can reflect the occurrence and development of diseases, has the characteristics of non-invasiveness, easy detection and capability of reflecting disease activity and drug treatment, and can be used as a novel biomarker of diseases through specific epigenetic modification.

At present, no satisfactory AOSD diagnostic marker with high sensitivity and high specificity exists in clinic, IL-18 is reported more, but the IL-18 is not unique to AOSD as a cytokine; while the sensitivity and specificity can be improved by analyzing ferritin in combination with glycosylated ferritin, it is not unique to AOSD and is difficult to perform; other studies have reported that AOSD biomarkers such as sCD163, AGEs, and sRAGE, S100 A8/a9 and a12, CXCL10, CXCL13, and the like lack multi-institution co-validation. For this reason, AOSD patients often need to combine other auxiliary items including invasive examination such as bone marrow puncture and more expensive examination such as PET-CT, which greatly increases the diagnosis cost of the disease and increases the psychological, physiological and economic burden of the patients. Therefore, it is necessary to develop a new AOSD diagnostic marker with high sensitivity and high specificity, which is of great significance for improving the diagnosis and treatment level of AOSD.

Disclosure of Invention

The invention discloses biomarkers for AOSD early diagnosis, which comprise 6 CpG sites (methylation sites) located in different DNA fragments, and the biomarkers can assist in early diagnosis of AOSD and can also distinguish Rheumatoid Arthritis (RA), Sepsis (Sepsis, SP), drug eruption (DrugErupation, DE) and T-cell Lymphoma (Tcell Lymphoma, TL) by detecting the methylation level of the 6 CpG sites, analyzing the methylation level of a single site or combining Logistic binary regression and ROC curve analysis.

The invention primarily aims to provide the application of a product for detecting the methylation level of one or more of 6 methylation sites in the preparation of a preparation for assisting 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, adult still's disease patients have a reduced methylation level at chr11:114167495, chr6:35654359, chr6:35654363 and chr6:139794538 sites compared with a healthy control group, and have an increased methylation level at chr1:198568084 and chr13:113327910 sites compared with the healthy control group.

To improve the reliability of the diagnosis, the methylation level regions of these methylation sites were further exploited for Rheumatoid Arthritis (RA), Sepsis (Sepsis, SP), Drug Eruption (DE) and T-cell Lymphoma (TL) diseases with similar symptoms to patients with adult still's disease. The method comprises the following specific steps:

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

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

Preferably, adult still's disease, as compared to healthy controls,

carrying out binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y of-0.224A +0.068B + 8.901; y value is more than-0.589, and adult still's disease is diagnosed;

or carrying out binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y of-0.155A-0.286C + 17.499; y value is greater than 0.5905, and adult still's disease is diagnosed;

or carrying out binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y which is-0.147A-0.189D + 17.241; y value is greater than 0.0735, and adult still's disease is diagnosed;

or binary Logistic regression analysis is carried out by combining the methylation levels of 2 CpG loci to obtain a formula Y which is-0.226A +0.044E + 10.904; y value is greater than-0.423, and adult still's disease is diagnosed;

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

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y which is-0.187C-0.151D + 11.352; y value is greater 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 of-0.376C +0.011E + 9.227; y value greater than-0.045, diagnosed as adult still's disease;

or carrying out binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y which is-0.233D +0.025E + 7.876; y value is greater than 0.5435, and adult still's disease is diagnosed;

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 3 CpG loci to obtain a formula Y which is-0.14A +0.044B-0.18D + 13.127; y value greater than 0.227, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.215A +0.05B +0.045E + 6.234; y value greater than-0.1485, diagnosed as adult still's disease;

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 3 CpG loci to obtain a formula Y-0.154A-0.28C-0.007E + 17.808; y value is greater than 0.574, and adult still's disease is diagnosed;

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

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

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG loci to obtain a formula Y which is 0.058B-0.354C +0.003E + 4.856; y value is greater than-0.272, and adult still's disease is diagnosed;

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 3 CpG loci to obtain a formula Y of-0.179C-0.147D +0.011E + 10.133; y value greater than 0.314, 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 of-0.134A +0.031B-0.151C-0.108D + 14.773; y value is greater than 0.2295, and adult still's disease is diagnosed;

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

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

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 4 CpG loci to obtain a formula Y of 0.07B-0.164C-0.147D +0.004E + 5.129; y value greater than 0.161, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 5 CpG loci to obtain a formula Y which is-0.132A +0.031B-0.145C-0.106D-0.002E + 14.59; y value is greater than 0.2535, diagnosing 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 number of chr13: 113327910.

Adult still's disease is comparable to rheumatoid arthritis,

performing binary Logistic regression analysis by combining the methylation levels of 2 CpG loci to obtain a formula Y of-0.335A-1.209B + 123.735; y value is more than 0.0615, and the adult still's disease is diagnosed;

or binary Logistic regression analysis is carried out by combining the methylation levels of 2 CpG loci to obtain a formula Y which is-0.642B-0.113C + 57.602; y value is greater than 0.6385, and adult still's disease is diagnosed;

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

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

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.347A-1.216B +0.044C + 124.233; y value greater than 0.237, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.311A-1.247B-0.072D + 127.695; y value is more than 0.052, and adult still's disease is diagnosed;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.393A-1.182B +0.241E + 105.428; y value is greater than-0.289, diagnosed as adult still's disease;

or carrying out binary Logistic regression analysis by combining the methylation levels of 3 CpG loci to obtain a formula Y which is-0.166A +0.542C-0.245D + 7.598; y value is greater than 0.32, and adult still's disease is diagnosed;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG loci to obtain a formula Y which is-0.182A +0.136C +0.034E + 5.913; y value greater than 1.055, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.673B +0.232C-0.205D + 60.292; y value is more than 0.811, and adult still's disease is diagnosed;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG loci to obtain a formula Y which is-0.641B-0.062C +0.168E + 43.279; y value is greater than 0.6465, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG sites to obtain a formula Y which is-0.742B-0.112D +0.16E + 55.059; y value is greater than 0.649, diagnosed as adult still's disease;

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

or performing binary Logistic regression analysis by combining the methylation levels of 4 CpG sites to obtain a formula of-0.472A-1.209B +0.164C +0.294E + 105.134; y value is greater than 0.9485, and adult still's disease is diagnosed;

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

or performing binary Logistic regression analysis by combining the methylation levels of 4 CpG sites to obtain a formula of-0.171A +0.562C-0.246D +0.034E + 4.828; y value greater than 0.095, diagnosed as adult still's disease;

or binary Logistic regression analysis is carried out by combining the methylation levels of 4 CpG loci to obtain a formula Y which is-0.674B +0.285C-0.225D +0.182E + 45.58; y value is greater than 0.413, and adult still's disease is diagnosed;

or performing binary Logistic regression analysis by combining the methylation levels of 5 CpG sites to obtain a formula Y of-0.512A-1.333B +0.522C-0.244D +0.342E + 114.933; y value greater than-0.4115, 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 number of chr13: 113327910;

in contrast to sepsis in adult still's disease,

performing binary Logistic regression analysis by combining the methylation levels of 2 CpG sites to obtain a formula Y of-0.189A-0.424B + 47.342; y value greater than 1.612, diagnosed as adult still's disease;

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

or performing binary Logistic regression analysis by combining the methylation levels of 3 CpG sites to obtain a formula Y of-0.177A-0.483B-0.085C + 53.338; y value greater than 2.033, 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 which is-0.185A-0.487B-0.048D + 53.961; y value is greater than 1.3705, and adult still's disease is diagnosed;

or performing binary Logistic regression analysis by combining the methylation levels of 3 CpG sites to obtain a formula of-0.227A-0.545B +0.185E + 45.262; y value greater than 1.43, diagnosed as adult still's disease;

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

or binary Logistic regression analysis is carried out by combining the methylation levels of 3 CpG loci to obtain a formula Y which is-0.354B-0.057D +0.156E + 20.446; y value greater than 1.063, diagnosed as adult still's disease;

or carrying out binary Logistic regression analysis by combining the methylation levels of 4 CpG sites to obtain a formula Y which is-0.191A-0.47B +0.071C-0.079D + 52.403; y value is greater than 1.2075, and adult still's disease is diagnosed;

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

or carrying out binary Logistic regression analysis by combining the methylation levels of 4 CpG loci to obtain a formula Y of-0.239A-0.626B-0.033D +0.204E + 52.431; y value greater than 1.158, diagnosed as adult still's disease;

or performing binary Logistic regression analysis by combining the methylation levels of 4 CpG sites to obtain a formula of-0.345B +0.031C-0.07D +0.157E + 19.472; a Y value greater than 1.554, diagnosed as adult still's disease;

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

compared with drug eruption,

combining methylation levels of 4 CpG sites to perform binary Logistic regression analysis to obtain a formula Y which is-0.129A +0.597C-0.233D + 0.092E-2.065; y value is greater than 2.0895, and adult still's disease is diagnosed;

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

adult still's disease in contrast to T-cell lymphoma,

diagnosing adult still's disease when the methylation level value of the chr6:139794538 single site of the sample to be tested is less than 58.42; further, when the Pouchot's score of the patient to be diagnosed is more than or equal to 4, namely the activity period standard of the adult still's disease is met, the adult still's disease is diagnosed according to the methylation value of the single site of the chr6:139794538 sample 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 comprises 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 a DNA methylation marker of AOSD, comprising 6 methylation sites: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6: 139794538.

Wherein 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 from 50 AOSD and 49 healthy controls (NC) were subjected to a whole blood genome 850k methylation chip assay to screen for DNA methylated CpG sites with AOSD and healthy control expression differences. Whole blood samples of 50 cases of AOSD and 50 cases of rheumatoid arthritis, 24 cases of sepsis, 24 cases of drug eruption and 24 cases of T cell lymphoma were subjected to whole blood genome 850k methylation chip detection, and DNA methylated CpG sites with expression difference between AOSD and disease control were selected.

2. Identification of DNA methylation markers: and (3) applying pyrosequencing to the screened DNA methylation CpG sites, and performing large sample verification on patients with AOSD, health control, rheumatoid arthritis, sepsis, drug eruption and T cell lymphoma to identify the DNA methylation CpG sites capable of being used for auxiliary diagnosis of AOSD. And carrying out ROC curve analysis to obtain values such as specificity and sensitivity of the DNA methylation marker.

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

The corresponding Y values for methylation levels of 5 CpG sites compared to healthy controls were used in ROC plots for AOSD diagnosis, see figure 3.

ROC plots of the methylation levels of 4 CpG sites versus rheumatoid arthritis for AOSD diagnosis are shown in FIG. 4.

The ROC plot of the methylation levels of 5 CpG sites versus sepsis for AOSD diagnosis is shown in fig. 5.

The ROC graph for AOSD diagnosis of the corresponding Y values for the methylation levels of 4 CpG sites compared to drug eruptions is shown in fig. 6.

ROC plots for chr6:139794538 for AOSD diagnosis compared to T cell lymphoma, see fig. 7.

ROC plots for chr6:139794538 for active AOSD diagnosis compared to T cell lymphoma, see fig. 8.

The invention has the beneficial effects that:

the invention firstly utilizes the screened specific DNA methylation sites as molecular markers to carry out auxiliary screening on patients with AOSD, rheumatoid arthritis, sepsis, drug eruptions and T cell lymphoma, and opens up a new way and a new mode for diagnosis in the field.

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

Drawings

FIG. 1 is a diagram showing the results of detecting 8 DNA methylation CpG sites with differential expression between the screened AOSD and the healthy control on the methylation chip;

FIG. 2 is a diagram showing the results of detecting 18 DNA methylated CpG sites with differential expression between the screened AOSD and the disease control on the methylation chip;

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

FIG. 4 is a graph comparing the level of methylation of AOSD with NC and other disease control 6 CpG sites.

FIG. 5 is a ROC plot of mean methylation levels for 5 CpG sites compared to healthy controls for AOSD diagnosis;

FIG. 6 is a ROC plot of mean levels of methylation at 4 CpG sites compared to rheumatoid arthritis for AOSD diagnosis;

FIG. 7 is a ROC plot of mean levels of methylation at 5 CpG sites compared to sepsis for AOSD diagnosis;

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

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

FIG. 10 is a ROC plot of methylation levels of chr6:139794538 compared to T cell lymphoma for active phase AOSD diagnosis.

Detailed Description

For further understanding of the present invention, the technical solutions in the present invention will be clearly and completely described below with reference to the embodiments of the present invention, which are only a part of the embodiments of the present invention, but not all of the embodiments. The following description of the embodiments of the present invention should not be construed as limiting the present invention in any way, and all other embodiments obtained by those skilled in the art without making any inventive step are intended to be included within the scope of the present invention. Unless defined otherwise, 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, the reagents involved in the examples of the present invention are all commercially available products, and all of them are commercially available.

Cases of AOSD included in the present invention were patients who were clinically confirmed to be adult still's disease by dermatologists or rheumatologists, all met Yamaguchi criteria, and excluded any of the following combinations: 1. rheumatoid arthritis and other rheumatic diseases 2, systemic lupus erythematosus, dermatomyositis and other connective tissue diseases 3, malignant tumor 4 and serious infection.

Normal persons: healthy, not suffering from adult still's disease, excluding any combination of: 1. rheumatoid arthritis and other rheumatic diseases 2, systemic lupus erythematosus, dermatomyositis and other connective tissue diseases 3, malignant tumor 4 and serious infection.

All rheumatoid arthritis patients met the rheumatoid arthritis diagnostic criteria of the American College of Rheumatology (ACR) and excluded any one of the following in combination: 1. osteoarthritis, ankylosing spondylitis, psoriatic arthritis 2, systemic lupus erythematosus, dermatomyositis and other connective tissue diseases 3, adult still's disease and related arthritis.

All sepsis patients met the sepsis-2 consensus criterion, excluding the combination with adult still's disease.

All patients with drug eruption were diagnosed with their clinical manifestations and definite medication history, and the adult still's disease was excluded.

Patients with T-cell lymphoma who are included in the present invention include 5 subtypes peripheral T-cell lymphoma, angioimmunoblastic T-cell lymphoma, subcutaneous panniculitis-like T-cell lymphoma, extranodal NK/T-cell lymphoma, and cutaneous T-cell lymphoma, all of which meet the diagnostic criteria of the National Comprehensive Cancer Network (NCCN) guidelines of the united states, and exclude any combination of the following: 1. other lymphadenectasis diseases 2, infectious mononucleosis 3, connective tissue diseases 4, such as systemic lupus erythematosus and dermatomyositis, other malignant tumors 5, infectious diseases 6, adult still's disease.

Example (b):

first, DNA methylation CpG site screening

Whole blood samples of 50 cases of AOSD and 49 cases of healthy control are subjected to a whole blood genome 850k methylation chip detection, and DNA methylation CpG sites with expression difference between AOSD and the healthy control are preliminarily screened. Whole blood samples of 50 cases of AOSD and 50 cases of rheumatoid arthritis, 24 cases of sepsis, 24 cases of drug eruption and 24 cases of T cell lymphoma were subjected to a whole blood genome 850k methylation chip test, and DNA methylation CpG sites with expression difference between AOSD and disease control were preliminarily screened.

Identification of DNA methylation CpG sites

Experiments such as primer design, PCR amplification of target gene bands, pyrosequencing and the like are carried out. Finally, differentially expressed DNA methylated CpG sites are screened and identified for diagnosis of AOSD.

Experimental reagent:

(1) reagent for extracting DNA from whole blood: GeneJET Whole blood genomic DNA purification kit (Thermo Scientific Sammerfei), reagent Cat No. K0782, Lot 00239303

TABLE 1

(2) Reagents required for sulfite treatment: DNA Methylation kit (EZ DNA Methylation)^TMKit, Zymo Research), cat # D5002

TABLE 2

750. mu.l of water and 210. mu.l of dilution buffer were added to each tube of CT transformation reagent and mixed for use.

Add 96 ml 100% ethanol to 24ml wash buffer.

(3) Reagents required for PCR:

TABLE 3

(4) Reagents required for pyrosequencing:

TABLE 4

Equipment used in the experiment:

a genome DNA purification column, a collection tube, a pipette gun, a pipette tip head, disposable gloves, a 1.5mL centrifuge tube, a PCR tube, a micro centrifuge, a hybridization furnace and a vortex oscillation instrument; a hybridization oven, a NanoDrop 2000 ultraviolet spectrophotometer, a PCR instrument (eppendorf), an agarose gel electrophoresis instrument, and a real-time quantitative pyrophosphate sequence analyzer (Pyromark Q24).

The experimental steps are as follows:

step 1: extraction of genomic DNA from peripheral blood of adult still's disease patients

(using a commercial whole blood DNA extraction kit):

(1) taking 200 mu l of whole blood to a 1.5ml centrifuge tube, then adding 20 mu l of proteinase K solution, and uniformly mixing by vortex; (2) add 400. mu.l of lysis buffer and vortex and mix well. (3) Incubating in a hybridization oven at 56 deg.C for 10 min; (3) adding 200 mul of absolute ethyl alcohol, turning upside down and mixing evenly; (4) transferring the mixed solution to a centrifugal adsorption column, and centrifuging at 6000g for 1 min; (5) transferring the adsorption column to a new waste liquid pipe; (6) adding 500. mu.l of washing buffer solution 1, 8000g (1000rpm), centrifuging for 1min, and discarding the waste liquid; (6) adding 500 mul washing buffer solution 2, 13000g, centrifuging for 3min, and discarding the waste liquid; (7)13000g, again for 1min, transfer the adsorption column to a new 1.5ml centrifuge tube; (8) adding 70 μ l elution buffer, standing at room temperature for 2 min; (9)8000g, centrifuging for 1min, and collecting genome DNA.

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

using a NanoDrop 2000 ultraviolet spectrophotometer from the company Sammerfei (Thermo Scientific), 1. mu.l of DNA sample was aspirated, spotted onto the detection plate, 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, processing genome DNA by sulfite;

(1) calculating a sampling volume of 200ng of DNA required for sulfite treatment according to the DNA concentration; (2) preparing a CT conversion reagent in dark: vortex 750ul of non-enzyme water and 210 mul of dilution buffer solution, mix evenly and avoid light for 15 min; (3) add 130. mu.l of the conversion reagent to 20. mu.l of the DNA sample and place in a PCR tube. (4) The mixed solution reacts in a PCR instrument: 8min at 98 ℃; 54 ℃ for 60 min. (5) The reaction solution of step (4) and 600. mu.l of the binding buffer were added to a spin column, and the mixture was inverted and mixed several times. (6)11000g, centrifugating for 30s, and discarding the solution. (7) Add 100. mu.l washing buffer, 11000g, centrifuge for 30s, discard solution. (8) Adding 200 μ l of desulfurization solution, centrifuging at room temperature (20-30 deg.C) for 15-20min, 11000g, and centrifuging for 30 s. (9) Add 200. mu.l washing buffer, 11000g, centrifuge for 1min, discard the solution. (10) Add 200. mu.l of washing buffer, 13000g, centrifuge for 3min, discard the solution. (11) Placing the centrifugal column into a new 1.5ml centrifugal tube, adding 40 mul of eluent, 8000g, centrifuging for 30s, and collecting DNA after sulfite treatment in the centrifugal tube.

Step 4, determining the concentration and purity of the genome DNA treated by the bisulfite;

2. mu.l of DNA sample was aspirated and spotted onto the detection plate using a NanoDrop 2000 ultraviolet spectrophotometer from Thermo Scientific, Inc., 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 amplification of DNA fragment 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 2-440 cycles
6	72	10min
			7	4	Persistence

Step 6 pyrosequencing

1. Agarose bead-immobilized PCR products

Immobilizing biotin-labeled PCR products onto streptavidin-modified coated agarose beads

(1) The streptavidin-modified coated agarose beads were gently shaken 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 the 8-bank pipe.

(3) Add 20. mu.l biotin-labeled PCR products to the PCR array (total volume of each well was 80. mu.l).

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

(5) Continuously oscillating the PCR row-connecting pipe by using an oscillating mixer at 1400rpm for at least 5-10 min. (Note: the agarose beads precipitate rapidly, so after stopping shaking must be used within a minute immediately, i.e., immediately capturing the agarose beads)

2. Vacuum workstation 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 × washing buffer preparation: 5 × washing buffer 5ml + high purity water 45 ml.

(2) And (4) turning on the vacuum pump, turning on a vacuum switch, and carrying out a test to determine whether the filter probe works normally.

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

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

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

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

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

(8) The vacuum was raised for 5 seconds above the 90 ° vertical and the liquid was drained from the filter needle.

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

3. DNA single strands were isolated and the samples were released into Pyromark Q24 well plates

(1) The PyroMark Q24 well plate was placed on a preheated well plate base and heated precisely at 80 ℃ for 2 min.

(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 5 min.

Preparation of Pyromark Q24 reagent

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

(2) Dissolving with high-purity water according to kit instructions, and subpackaging enzyme and substrate (the dissolved enzyme and substrate need to be preserved at-20 ℃, freeze thawing can be repeated for 3 times at most, and nucleotide can be preserved at 4 ℃), 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 reagent cartridge (reagent cartridge used up to 30 times, reagent cartridge must be dried before use) according to the volume calculated by the computer program.

5. Run on a real-time quantitative Pyrophosphate Analyzer (Pyromark Q24)

(1) Opening pyroMark Q24 software, clicking new assoy → new AQ assoy → inputting the mutation point sequence in sequence anayze, clicking general publication, clicking for saving;

(2) click new run → instument method → 005, then click the box to be sequenced, click save to the U disk.

(3) And inserting the USB flash disk containing the operation files into a USB port on the front of the instrument.

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

(5) The label side of the reagent chamber (enzyme, substrate and nucleotide) is placed into the instrument facing itself, the well plate holder frame is opened and the well plate is placed into the instrument, and the well plate holder frame and instrument cover are closed.

(6) Run was selected and OK was pressed.

(7) After entering Run, a file to be Run is selected according to select.

(8) And after the instrument finishes running and the running file is confirmed to be stored in the USB flash disk, taking out the USB flash disk according to close.

(9) The experimental data were analyzed.

And (3) test results:

1.DNA methylation CpG site screening

Whole blood samples of 50 AOSDs and 49 healthy controls were subjected to a 850k methylation chip assay of whole blood genome, and 8 DNA methylation CpG sites were selected for differences in expression between AOSDs and healthy controls, 1.cg12374610, 2.cg00329101, 3.cg14521435, 4.cg25569341, 5.cg20747787, 6.cg09574909, 7.cg03546163, and 8.cg02863807, respectively. See fig. 1.

A whole blood genome 850k methylation chip assay was performed on 50 AOSD and 49 healthy controls, 50 rheumatoid, 24 sepsis, 24 drug eruptions, and 24T cell lymphomas to screen 18 DNA methylation CpG sites with differential expression between AOSD and disease controls, namely 1.cg00329101, 2.cg01849514, 3.cg02053407, 4.cg03064100, 5.cg03546163, 6.cg03581638, 7.cg07732037, 8.cg08043317, 9.cg08145373, 10.cg09574909, 11.cg14887853, 12.cg 51881, 13.cg 68074, 14.cg16373817, 15.cg 252249, 16.cg22963164, 17.cg 894783, 2415515515541. See fig. 2.

2. Identification of DNA methylation CpG sites

Through experiments such as primer design, PCR amplification of a target gene band, pyrosequencing and the like, 6 differentially expressed DNA methylation CpG sites are finally screened for AOSD diagnosis. 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 is carried out by using primers of DNA fragments with 6 CpG sites, bright specific target gene bands exist, and the primers have specificity.

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

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

3. The methylation level of the above CpG sites was tested in 96 AOSD patients, 87 healthy controls and 50 RA patients, 28 SP patients, 21 DE patients, 62 TL patients using the above method. Analyzing the methylation level of one CpG site independently or performing binary Logistic regression analysis by combining the methylation levels of a plurality of CpG sites to obtain a formula, calculating a corresponding Y value, and calculating the sensitivity and specificity of the Y value corresponding to the methylation levels of the plurality of CpG sites in the diagnosis of AOSD by utilizing the evaluation statistic of an ROC curve, wherein the actual value range of the Area (AUC) under the ROC curve is 0.5-1, but generally considered as follows: for a diagnostic test, the diagnostic value is low when the area under the ROC curve is between 0.5 and 0.7, the diagnostic value is medium when the area is between 0.7 and 0.9, and the diagnostic value is high when the area is more than 0.9.

For example: performing binary Logistic regression analysis on the AOSD and the healthy control group by combining the methylation levels of the 5 CpG sites to obtain a formula of-0.132A +0.031B-0.145C-0.106D-0.002E + 14.59; 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 5 CpG sites, corresponding Y values were calculated and compared to healthy controls using ROC curve analysis (figure 5): AUC: 0.964, 95% CI: 0.938-0.989, sensitivity: 88.5%, specificity: 98.9 percent. The results show that AOSD patients with Y values greater than 0.2535 are considered for AOSD diagnosis compared to healthy controls. The Y values corresponding to the methylation levels of these 5 CpG sites distinguish AOSD patients from healthy controls for 88.5% sensitivity and 98.9% specificity.

Comparing AOSD with rheumatoid arthritis, and carrying out binary Logistic regression analysis on methylation levels of 4 combined CpG sites to obtain a formula Y of-0.372A-1.304B +0.329C-0.188D + 133.636; wherein A represents chr11: 114167495; b represents chr1: 198568084; c represents chr6: 35654359; d represents chr6: 35654363; calculating corresponding Y values according to the methylation values of 4 CpG sites of the sample to be detected, and comparing the values with the methylation values of rheumatoid arthritis by using ROC curve analysis (figure 6): AUC: 0.988, 95% CI: 0.975-1.000, sensitivity: 97.8%, specificity: 94 percent. The results show that AOSD patients with Y values greater than-0.5185 are considered for diagnosis of AOSD compared to rheumatoid arthritis patients. The Y values corresponding to the methylation levels of the 4 CpG sites distinguish the sensitivity of the AOSD patient from the rheumatoid arthritis patient by 97.8 percent and the specificity by 94 percent.

AOSD compared to sepsis, binary Logistic regression analysis was performed in combination with methylation levels of 5 CpG sites to give the 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 5 CpG sites, corresponding Y values were calculated and compared to sepsis using ROC curve analysis (figure 7): AUC: 0.885, 95% CI: 0.808-0.962, sensitivity: 77.1%, specificity: 92.9 percent. The results show that a Y value greater than 2.4195 for AOSD patients compared to septic patients is considered diagnostic for AOSD. The Y values corresponding to the methylation levels of these 5 CpG sites distinguish AOSD from sepsis patients by 77.1% sensitivity and 92.9% specificity.

Comparing AOSD with drug eruption, and performing binary Logistic regression analysis by combining methylation levels of 4 CpG sites to obtain a formula Y of-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. Based on the methylation values of 4 CpG sites, corresponding Y values were calculated and compared to the rash using ROC curve analysis (FIG. 8): AUC: 0.842, 95% CI: 0.737-0.946, sensitivity: 72%, specificity: 90.5 percent. The results show that AOSD patients are considered to be diagnosed with AOSD if the Y value is greater than 2.0895, as compared to those with drug eruption. The Y values corresponding to the methylation levels of these 4 CpG sites distinguish AOSD patients from those with drug eruptions by 72% sensitivity and 90.5% specificity.

AOSD compared to T-cell lymphoma, based on methylation values of chr6:139794538, compared to T-cell lymphoma using ROC curve analysis (figure 9): AUC: 0.693, 95% CI: 0.606-0.781, sensitivity: 79.6%, specificity: 56.5 percent. The results show that compared with patients with T-cell lymphoma, patients with AOSD have methylation of chr6:139794538 less than 58.42, and can be considered to be diagnosed with AOSD. chr6:139794538 methylation level was 79.6% sensitive and 56.5% specific for distinguishing AOSD from T-cell lymphoma patients.

Active phase AOSD compared to T cell lymphoma, based on methylation values of chr6:139794538, using ROC curve analysis (figure 10), compared to T cell lymphoma: AUC: 0.761, 95% CI: 0.673-0.850, sensitivity: 81.5%, specificity: 67.8 percent. The results show that compared with patients with T-cell lymphoma, patients with AOSD have methylation of chr6:139794538 less than 57.79, and can be considered to be diagnosed with AOSD. chr6:139794538 methylation levels were 81.5% sensitive and 67.8% specific for distinguishing AOSD from T-cell lymphoma patients.

The following tables 7, 8, 9, 10, 11 are comparisons made with the diagnostic efficiency of diagnosing AOSD in combination with 2, 3, 4, 5 or 6 CpG sites as an example.

TABLE 7 comparison of the diagnosis efficiency of AOSD in the combined diagnosis of 2, 3, 4, 5 CpG sites compared to healthy control group

TABLE 8 comparison of the diagnosis efficiency of AOSD in the combined diagnosis of 2, 3, 4, 5 CpG sites compared to the RA group

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

TABLE 10 comparison of the diagnosis efficiency of AOSD with that of DE group for 4 and 5 CpG sites in combination diagnosis of AOSD

Compared with the AOSD and the TL groups, the area under the ROC curve (AUC) of the combination of the 2, 3 and 4 sites of the TL is basically between 0.5 and 0.65, and the AUC obtained when the formula is calculated by logistic regression and ROC analysis is carried out by using the Y value of the formula result is lower, so the AUC is not listed.

TABLE 11 comparison of the diagnosis efficiency of AOSD in the combined diagnosis of 5 and 6 CpG sites, respectively, compared with those in TL groups

In conclusion, the results show that the combination of single or multiple CpG sites for diagnosing AOSD has better AUC, sensitivity and specificity. However, the effect of combining multiple CpG sites to distinguish AOSD from T cell lymphoma is poor, the AUC, the sensitivity and the specificity are better when the chr6:139794538 is used alone, and the AUC, the sensitivity and the specificity are further improved when the Pouchot score of a patient to be diagnosed is more than or equal to 4 minutes, so that the single site of chr6:139794538 is selected to distinguish AOSD from T cell lymphoma.

At present, AOSD is diagnosed mainly according to medical history and clinical manifestations, AOSD diagnosis is challenging, and no reliable molecular marker exists in clinical application.

Sequence listing

<110> Xiangya II Hospital of Zhongnan university

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

<160> 15

<170> SIPOSequenceListing 1.0

<210> 1

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 1

ggtgatgtta aaagggttgt gaa 23

<210> 2

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 2

atctattatc tacatatctc cccacta 27

<210> 3

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 3

gaagtaataa agagagatat aaaat 25

<210> 4

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 4

agggaatagg tagtttggtg aatta 25

<210> 5

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 5

ataaacttta accaccacca tcta 24

<210> 6

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 6

tttatatttt attgggttaa gtaag 25

<210> 7

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 7

ttgggtttag tttagttttt taaaggt 27

<210> 8

<211> 28

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 8

cttatccaat tcctttcaac tatttaca 28

<210> 9

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 9

ataggttgaa taataattta t 21

<210> 10

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 10

agaggattta gttggttata tgtagat 27

<210> 11

<211> 26

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 11

aataatctac cccccttaac ctccca 26

<210> 12

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 12

atgtagattt ttgatttatg gaa 23

<210> 13

<211> 29

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 13

atggttagga gtagtttaaa aagttgtat 29

<210> 14

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 14

ttcccctccc cctctctaat a 21

<210> 15

<211> 18

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 15

atagtagaag gaggtatt 18

Claims

1. Use of a product for detecting the methylation level of one or more of 6 methylation sites in the manufacture of a formulation for diagnosing adult still's disease; the 6 methylation sites are: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6: 139794538.

2. The use of claim 1, wherein the adult still's disease patient has a decreased level of methylation at sites chr11:114167495, chr6:35654359, chr6:35654363 and chr6:139794538 as compared to the healthy control group and an increased level of methylation at sites chr1:198568084 and chr13:113327910 as compared to the healthy control group.

3. The use as claimed in claim 1, wherein the adult still's disease patient has a decreased level of methylation at sites chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363 as compared to rheumatoid arthritis, and an increased level of methylation at sites chr13:113327910 as compared to rheumatoid arthritis; the methylation level of the chr11:114167495, chr1:198568084, chr6:35654359 and chr6:35654363 sites of the adult still's disease patient is reduced compared with the sepsis, and the methylation level of the chr13:113327910 sites is increased compared with the sepsis; the adult still's disease patients have reduced methylation levels at chr11:114167495, chr6:35654359 and chr6:35654363 sites compared with drug eruptions, and have increased methylation levels at chr1:198568084 and chr13:113327910 sites compared with the drug eruptions; adult still's disease patients have reduced methylation levels at chr11:114167495, chr6:35654359, chr6:35654363 and chr6:139794538 sites compared with T-cell lymphoma, and have increased methylation levels at chr1:198568084 and chr13:113327910 sites compared with T-cell lymphoma.

4. The use of claim 1, wherein the product obtains methylation levels of 6 CpG sites contained in a sequence by analyzing sequencing results of a plurality of samples, and separately analyzes the methylation level of one CpG site, or performs binary Logistic regression analysis by combining the methylation levels of a plurality of CpG sites, and makes a formula for detecting a sample to be detected, preferably one CpG site, two CpG sites, three CpG sites, four CpG sites or five CpG sites.

5. The use of claim 4, wherein the methylation levels of 2 CpG sites in combination with adult still's disease and healthy controls are analyzed by binary Logistic regression to obtain the formula-0.224A +0.068B + 8.901; y value is more than-0.589, and adult still's disease is diagnosed;

6. The use of claim 4, wherein adult still's disease is comparable to rheumatoid arthritis,

in contrast to sepsis in adult still's disease,

compared with drug eruption,

adult still's disease in contrast to T-cell lymphoma,

7. The use of claim 1, wherein the product comprises a PCR kit pyrosequencing reagent.

8. The use of claim 7, wherein the PCR reagent uses the following primer pairs:

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。

9. a diagnostic reagent for adult still's disease comprising a product for detecting the methylation level of the methylation site according to any one of claims 1 to 8.

10. A DNA methylation marker for adult still's disease comprising: the 6 methylation sites are: chr11:114167495, chr1:198568084, chr6:35654359, chr6:35654363, chr13:113327910, chr6: 139794538.