Application of methylation level of mtDNA CpG sites in diagnosis of SLE

Abstract

The application discloses application of a methylation level of an mtDNA CpG site in diagnosis of SLE. Through clinical sample screening analysis, multiple CpG sites from a gene MT-COX2 on mtDNA are obtained, and the CpG sites are any one or a combination of two or more of chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919 and chrM:7925. The methylation level of the screened CpG site has significant correlation with systemic lupus erythematosus, and can be used as a biomarker for diagnosis of systemic lupus erythematosus, and has important significance for guiding diagnosis of systemic lupus erythematosus in a clinic.

Description

Technical Field

[0001] This application belongs to the field of biological detection technology, specifically relating to the application of hydroxymethylation levels based on mtDNA CpG sites in the diagnosis of SLE. Background Technology

[0002] Systemic lupus erythematosus (SLE) is an autoimmune disease with highly heterogeneous clinical manifestations, and its diagnosis mainly relies on a combination of comprehensive clinical presentations and serological autoantibody detection. However, existing mainstream serological biomarkers (such as antinuclear antibodies and anti-dsDNA antibodies) have inherent limitations in specificity or sensitivity, making it difficult for some patients to obtain an early and accurate diagnosis. Diagnostic delay is directly related to poor prognosis. Therefore, the development of novel SLE diagnostic biomarkers is of urgent clinical need for early differential diagnosis, monitoring of disease risk, and surveillance of disease activity.

[0003] Epigenetic modifications, particularly DNA hydroxymethylation (5hmC), have emerged as a promising direction for developing high-precision disease biomarkers due to their tissue specificity, dynamic nature, and direct correlation with gene transcriptional activity. Compared to DNA methylation (5mC), 5hmC, as an intermediate product of active demethylation, may more dynamically reflect the real-time activity of the disease. Existing technologies have confirmed that the methylation status of specific sites in the nuclear genome can serve as an effective diagnostic biomarker for SLE, highlighting the potential of epigenetic biomarkers. However, the application of functionally more active hydroxymethylation modifications, especially hydroxymethylation maps targeting specific genomes, to SLE diagnosis still requires further exploration.

[0004] Previous studies have shown that mitochondrial DNA (mtDNA) encodes key proteins involved in oxidative phosphorylation, and mutations, copy number changes, or abnormal expression of mtDNA are closely related to immune dysregulation in SLE. For example, damaged mtDNA can act as a damage-associated molecular pattern (DAMP) to activate innate immune pathways. Therefore, developing biomarkers based on mitochondrial genes holds promise for providing more specific pathological information at the root level of cellular energy metabolism and immune activation.

[0005] However, there are currently no reports on using mitochondrial DNA hydroxymethylation (5hmC) levels as a diagnostic biomarker for SLE. Summary of the Invention

[0006] In view of this, the primary objective of this application is to provide CpG sites for the diagnosis of SLE, and to develop novel diagnostic technologies for SLE that combine the advantages of mitochondrial genome specificity and dynamic hydroxymethylation modification. By identifying the hydroxymethylation status of these mitochondrial DNA-specific gene CpG sites, the goal of earlier and more accurate diagnosis of SLE can be achieved.

[0007] To achieve the above objectives, this application adopts the following technical solution: One aspect of this application discloses CpG sites for diagnosing SLE, wherein the CpG sites are any one or a combination of two or more of chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919, and chrM:7925, all of which are derived from the MT-COX2 gene on mtDNA.

[0008] This application also discloses the use of a reagent for detecting the hydroxymethylation level of the CpG site described in this application in the preparation of products for diagnosing SLE.

[0009] This application also discloses an in vitro diagnostic tool for SLE, which includes a reagent for detecting the hydroxymethylation level of the CpG site described in this application.

[0010] This application also discloses a system / device for diagnosing SLE, including: A data acquisition module is used to acquire the hydroxymethylation level of CpG sites in the subject's biological samples, wherein the CpG sites are as described in this application; The data processing module is used to analyze the hydroxymethylation level of the acquired CpG sites. The analysis includes statistical analysis of the correlation between the hydroxymethylation level of CpG sites and SLE, or inputting the hydroxymethylation level of CpG sites into a pre-trained machine learning model. The disease diagnosis module is used to diagnose SLE based on the analysis and processing results in the data processing module and output the diagnosis results.

[0011] The beneficial effects of this application are: This application obtained CpG sites from the mitochondrial gene MT-COX2 through screening clinical samples. Their hydroxymethylation levels were significantly correlated with SLE. Experiments verified that the hydroxymethylation levels of these CpG sites have a certain diagnostic differentiation ability between SLE patients and healthy individuals, providing new biomarkers for early clinical diagnosis of SLE, which is of great significance for the accurate diagnosis of SLE. Attached Figure Description

[0012] Figure 1 This is a study of the diagnostic efficacy of the selected CpG sites for SLE in Example 3. Figure 1 In the figure, A represents the ROC curves for the initial screening sample and the validation sample. Figure 1 In the middle, B represents the ROC curve of the training and validation sets in the merged sample. Detailed Implementation

[0013] The embodiments of this application will be clearly and completely described below. The technical solutions in the embodiments described below are exemplary and only possible technical implementations of this application, not all possible implementations. Those skilled in the art can combine the embodiments of this application to obtain other embodiments without creative effort, and these embodiments are also within the protection scope of this application.

[0014] The first aspect of this application discloses CpG sites for diagnosing SLE. This application involves obtaining a certain number of clinical samples, including SLE patients and healthy controls. After collecting biological samples from these subjects, DNA is extracted, amplified by multiplex PCR, and the PCR products are sequenced and analyzed to calculate the corresponding hydroxymethylation levels. Through statistical analysis, CpG sites significantly associated with SLE are screened. In this application, the CpG sites are any one or a combination of two or more of chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919, and chrM:7925, all originating from the MT-COX2 gene on mtDNA.

[0015] As described in this application, the term "mtDNA" refers to mitochondrial DNA, which is another genetic material in human cells besides nuclear DNA. "MT-COX2" is a gene on the mitochondrial genome encoding cytochrome c oxidase subunit II. The CpG sites screened in this application are precisely located on a specific mitochondrial genome; therefore, the CpG sites provided in this application are biomarkers for diagnosing SLE that combine mitochondrial genome specificity with the advantages of dynamic hydroxymethylation modification.

[0016] As described in this application, the term "CpG site" refers to a location in a DNA sequence where cytosine (C) is immediately followed by guanine (G), where "p" represents the intermediate phosphodiester bond, and these sites have a "CpG" structure. These regions are the primary sites where epigenetic modifications such as DNA methylation and hydroxymethylation occur.

[0017] In this application, the diagnosis of these SLEs is determined by the hydroxymethylation level of the CpG sites. This can be done by detecting the hydroxymethylation level of any one CpG site, or by detecting a combination of two or more of them. As a preferred example, the hydroxymethylation level of all six CpG sites is detected.

[0018] As described in this application, the term "hydroxymethylation" is a chemical modification of DNA, specifically referring to the addition of a hydroxymethyl group (-CH2OH) to the fifth carbon atom of cytosine (C), forming 5-hydroxymethylcytosine (5hmC). It is a more stable epigenetic marker than conventional methylation (5mC).

[0019] The "hydroxymethylation level" refers to the abundance of the chemical modification 5-hydroxymethylcytosine (5hmC) at a specific CpG site or region. Its detection and calculation can be performed using methods known in the art without particular limitation. For example, in some specific examples, it can be obtained using a "percentage / ratio" based on sequencing technology, where the hydroxymethylation level of a specific CpG site = (number of reads detected as 5hmC at that site) / (total number of reads covered by that site) × 100%. Furthermore, in other examples, quantification can be based on mass spectrometry or high-performance liquid chromatography (HPLC), where the extracted DNA is completely hydrolyzed into mononucleotides or bases. Using techniques such as mass spectrometry or HPLC, 5hmC is separated from other bases such as cytosine (C) and 5-methylcytosine (5mC) according to their molecular weight or chemical properties, and their contents (e.g., peak area or ionic intensity) are measured separately. Alternatively, a "comprehensive score / index" based on a statistical model can be used. For example, several sites most relevant to SLE can be selected from multiple candidate CpG sites. A classification model (such as logistic regression, support vector machine, or random forest) can be trained using hydroxymethylation data of these sites from a training set sample (including known SLE patients and healthy individuals). The model automatically learns the "contribution weight" of each site to the diagnostic result. For example, for a new sample, the hydroxymethylation levels of each site are substituted into the trained model formula. The model's output value (e.g., the logit value in logistic regression, or the probability value output by a random forest) is the "comprehensive score" for that sample.

[0020] The above are just a few examples of quantitative hydroxymethylation levels, but are not limited to these. Those skilled in the art can obtain the corresponding hydroxymethylation levels based on methods known in the art, according to experimental purposes and research needs.

[0021] The second aspect of this application discloses the use of a reagent for detecting the hydroxymethylation level of the CpG site in the preparation of products for diagnosing SLE.

[0022] Furthermore, an in vitro diagnostic tool for SLE is disclosed, which includes a reagent for detecting the hydroxymethylation level of the CpG site described in this application.

[0023] As used in this application, the term "reagent" refers to any substance capable of detecting the hydroxymethylation level of the CpG site described in this application. Typical examples include primer pairs that amplify DNA fragments containing the target CpG site, and nucleic acid probes that specifically hybridize with the CpG site to detect its hydroxymethylation level, but are not limited thereto.

[0024] The term "primer pair" refers to a pair of short nucleotide sequences consisting of an upstream primer and a downstream primer, used in amplification reactions such as PCR (polymerase chain reaction) to specifically recognize and bind to both ends of a target DNA fragment (i.e., the MT-COX2 gene fragment containing the CpG site described in this application), thereby initiating replication and amplifying the fragment in large quantities. The specific primer pair can be designed based on the DNA fragment containing the target CpG site using development tools or websites known in the art, and those skilled in the art are capable of doing so. As a preferred example, the nucleotide sequence of the upstream primer is shown in SEQ ID NO.1, and the nucleotide sequence of the downstream primer is shown in SEQ ID NO.2.

[0025] The term "nucleic acid probe" refers to a short nucleotide sequence with a detectable marker, designed to specifically hybridize (bind) to a target CpG site or a DNA sequence in its vicinity. By detecting the marker signal, the presence or modification status of the target sequence can be determined. The "detectable marker" can be a fluorescent group (FAM, Cy, etc.), biotin, enzyme, etc., without any specific limitations.

[0026] As described in this application, the terms "product" and "in vitro diagnostic tool" refer to any combination of instruments, devices, or articles used for in vitro detection, including but not limited to reagent kits and chips. As a preferred example, the product is a reagent kit. In addition to the reagents necessary for detecting the hydroxymethylation level of the CpG site, these products or in vitro diagnostic tools may also include appropriate auxiliary reagents (such as buffer solutions, washing solutions, enzymes, extraction solutions, etc.) depending on the detection technology. Furthermore, consumables and instructions for use are typically also included.

[0027] It is understandable that the instructions for use should at least describe the steps for using the kit to detect the CpG sites and the steps for interpreting the test results.

[0028] In some specific examples, the method for detecting the hydroxymethylation level of the CpG site includes the following steps: Obtain biological samples from the subjects and extract DNA from the biological samples; After glycosylation and deamination of the extracted DNA, the target fragment was amplified by multiplex PCR. Sequencing of PCR amplification products; Sequencing data were analyzed to determine the hydroxymethylation level of the CpG sites.

[0029] The term "biosample" refers to any biological material containing the genetic material (i.e., DNA, particularly mitochondrial DNA) collected from a subject (an individual suspected of having systemic lupus erythematosus or a healthy control individual). Specific examples include, but are not limited to, blood samples (such as whole blood, peripheral blood mononuclear cells, plasma / serum, etc.), tissue samples, and body fluid samples (such as urine, saliva / oral mucosal swabs, etc.).

[0030] As a preferred example, the biological sample obtained is a peripheral blood sample from the subject; more preferably, it is peripheral blood mononuclear cells (PBMCs) isolated from whole blood. The peripheral blood sampling process is simple and has the advantages of being minimally invasive and standardized, making it easy to promote on a large scale in clinical practice, thereby greatly improving the practicality and operability of the technology.

[0031] It is understood that the acquisition of biological samples and the extraction of DNA from biological samples can be carried out in accordance with methods known in the art, without any particular limitation.

[0032] Furthermore, the extracted DNA undergoes glycosylation and deamination: this is a core chemical processing step in the detection process, the purpose of which is to convert the "hydroxymethylation" signal into a "sequence" that can be read by sequencing.

[0033] Glycosylation involves using a specific enzyme (such as β-glucosyltransferase) and a target substrate to specifically add a glucose group to 5-hydroxymethylcytosine (5hmC), forming glycosylated 5hmC. This group protects 5hmC from subsequent deamination. Deamination is then performed using chemical reagents (such as bisulfite) to treat the DNA. Unprotected cytosine (C) and regular 5-methylcytosine (5mC) are deaminated, converting to uracil (U) and thymine (T). The glycosylated 5hmC remains unchanged, still containing C. After these two steps, the sequence information in the original DNA is transformed.

[0034] Subsequent PCR amplification and sequencing will result in the following: in the final PCR product and sequencing results, the position that was originally 5hmC will be read as "C", while the position that was originally C or 5mC will be read as "T". In this way, the hydroxymethylation site can be accurately labeled.

[0035] In this application, the specific PCR amplification and sequencing can be performed using methods known in the art, such as introducing downstream adapter primers containing specific tag sequences for PCR amplification, adding a unique tag sequence to each sample for subsequent sample differentiation (if a candidate gene enrichment sequencing strategy is adopted, the target gene region can be amplified and enriched first using specific primers before performing this step). After sample labeling is completed, the amplification products are quantified, a high-throughput sequencing library is constructed, and high-throughput sequencing, such as whole-genome sequencing (WGB) or candidate gene enrichment sequencing technology, is used for detection to obtain the corresponding sequence information.

[0036] Finally, the sequencing data were analyzed using bioinformatics methods. The 5hmC hydroxymethylation level at the target site was determined by calculating the ratio of the number of reads with detected base C at the target site to the total number of reads.

[0037] Tagging PCR amplification products, library construction and sequencing, and bioinformatics analysis are all standard practices in this field, and therefore will not be elaborated on here.

[0038] This application further discloses a system / device for diagnosing SLE, wherein the system / device refers to a product implemented by a computer program or dedicated hardware, comprising: The data acquisition module is configured as an input interface to receive data from the detection device (such as a sequencer), which represents the hydroxymethylation levels at the CpG sites described in this application. This module can be a physical interface (such as a USB port), a software interface (such as a data upload page), or an internal data pathway.

[0039] The data processing module, configured as the core processing unit of the system / device, is responsible for calculating and analyzing the received data. Its operation is not particularly limited and can employ methods known in the art. For example, in some examples, statistical analysis can be used to compare the subject's hydroxymethylation level with a pre-set threshold (e.g., a cutoff value derived from statistical analysis of a large number of healthy individuals and SLE patients), or complex statistical tests (such as t-tests, ANOVA, etc.) can be performed to determine whether it significantly deviates from the normal range. In other examples, the hydroxymethylation level of one or more CpG sites can be used as input features and fed into a pre-trained machine learning model. This model (such as Support Vector Machine (SVM), Random Forest, Neural Network, etc.) is trained using a large amount of known hydroxymethylation data (diagnosed with SLE or healthy individuals) and can output a diagnostic prediction result based on the combined pattern of multiple input features.

[0040] The disease diagnosis module is configured as an output unit that receives the analysis results from the data processing module and generates a final, readable diagnostic conclusion based on preset rules (such as "if it is statistically significantly higher than the threshold, then it is diagnosed as positive") or the direct output of the model.

[0041] Furthermore, it should be noted that the term "diagnosis" in this application refers to a variety of information provision behaviors related to disease state assessment. These include, but are not limited to, the following situations: (1) Disease diagnosis, which involves detecting the hydroxymethylation level of a specific CpG site in a subject's biological sample and comparing it with a preset reference threshold or range to determine whether the subject has SLE. For example, if the subject's hydroxymethylation level (or comprehensive score) is significantly higher than (or lower than, depending on the correlation of the specific site) the reference value of healthy individuals and reaches the statistical significance threshold, then the subject is considered to have a high probability of having SLE. (2) Auxiliary diagnosis, which refers to using the test results as an objective biological indicator as one of the reference bases for comprehensive clinical judgment (including symptoms, signs, other laboratory tests, etc.), rather than making a final diagnosis independently. (3) Prospective studies refer to the assessment of the risk or likelihood of future disease by detecting the hydroxymethylation level of specific CpG sites in subjects before they show any clinical symptoms of SLE; for example, screening of high-risk groups (such as people with a family history of SLE), health check-ups, and screening of individuals in the "preclinical lupus" stage (i.e., those with immunological abnormalities but no clinical symptoms). (4) Disease status monitoring involves repeatedly detecting the hydroxymethylation level in diagnosed SLE patients at different treatment stages or during periods of disease fluctuation to assess disease activity, predict relapse risk, or determine treatment effectiveness.

[0042] Furthermore, the term "threshold" in this application, also known as a critical value, cut-off value, or decision limit, refers to a pre-defined, specific numerical value or range. During the diagnostic process, the subject's disease state can be classified or risk assessed by comparing the hydroxymethylation level of a specific CpG site (or a composite score calculated based on it) to this threshold. It is understood that the threshold is not arbitrarily set but is calculated using scientific statistical methods based on a large amount of clinical sample data. In some examples, the threshold can be based on a statistic of the distribution in a healthy population; that is, from a given biological sample of a healthy control individual, the hydroxymethylation level of the target CpG site is detected to establish a reference value distribution for the healthy population, and a certain statistic from that distribution is taken as the threshold. For example, the 95th percentile of the healthy population distribution can be taken as the threshold. In other examples, receiver operating characteristic (ROC) curve analysis can be used. This involves simultaneously detecting hydroxymethylation levels in a large number of known samples (including diagnosed SLE patients and healthy controls), plotting the ROC curve with sensitivity on the ordinate and (1-specificity) on the x-axis, and selecting the Youden index, or specifying sensitivity at high specificity, or specifying specificity at high sensitivity as a threshold. In still other examples, the threshold can be based on the internal parameters of a machine learning model. In general, the threshold setting can be based on any known method in the field, depending on the experimental objectives and research needs, and therefore there are no particular limitations.

[0043] The present application will be further illustrated below with reference to specific embodiments. It should be noted that the specific embodiments below are for illustrative purposes only and do not limit the scope of the present application in any way.

[0044] 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 application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application.

[0045] In addition, unless otherwise specified, methods without detailed conditions or steps are conventional methods, and the reagents and materials used are commercially available.

[0046] Example 1: Screening of CpG sites 1.1 Clinical Samples The subjects included in this study were from the First Affiliated Hospital of Anhui Medical University and the Second Affiliated Hospital of Anhui Medical University, totaling 100 cases (50 SLE patients and 50 healthy controls). The study subjects strictly followed the 1997 American College of Rheumatology diagnostic criteria. All SLE patients were confirmed cases, and other autoimmune diseases, malignant tumors, and other serious illnesses were excluded. The healthy controls had no history of SLE, other autoimmune diseases, cancer, or other serious illnesses, and no family history of autoimmune diseases.

[0047] 1.2 Sample processing and genotyping (1) Sample collection: 5 ml of venous blood was collected from the subject’s forearm by trained medical personnel and placed in a 0.5 MEDTA anticoagulant tube.

[0048] (2) PBMCs isolation: Take 5 mL of EDTA-anticoagulated peripheral blood and gently dilute it with an equal volume of PBS or physiological saline. Slowly add the diluted blood along the tube wall to the surface of an equal volume of lymphocyte separation medium, maintaining clear stratification. Centrifuge at 1000g for 20 minutes at room temperature. After centrifugation, clear stratification is visible. Carefully aspirate the middle white, cloudy PBMCs layer to a new centrifuge tube using a pipette. Add an appropriate amount of PBS to wash the cells, centrifuge at 300g for 10 minutes, and discard the supernatant. Repeat the washing once. Finally, resuspend the cells with an appropriate amount of cryopreservation medium to complete PBMCs isolation. Store at -80℃ before subsequent experiments.

[0049] (3) DNA extraction: First, add 750µl of Buffer FG1 to a 1.5mL centrifuge tube, then add 300µl of the sample to be extracted and mix thoroughly. After centrifuging at 10000g for 20s, discard the supernatant and invert the centrifuge tube onto clean absorbent paper for 2min, ensuring the precipitate remains in the tube. Then, add 150µl of Buffer FG2 / QIAGENProtease to the centrifuge tube and vortex for 5s to completely dissolve the precipitate. After rapidly centrifuging the sample for 3-5s, place it in a 65°C water bath for 5min until the sample color changes from red to olive green, indicating that the protein has been digested. Then, add 150µl of 100% isopropanol to the centrifuge tube, invert the centrifuge tube and mix thoroughly until the DNA precipitate becomes flocculent. Centrifuge again at 10000g for 3 minutes, discard the supernatant, and invert the centrifuge tube onto clean absorbent paper for at least 5 minutes to absorb excess moisture, ensuring the precipitate remains in the tube. Allow the precipitate to air dry for at least 5 minutes, until all liquid has evaporated. Finally, add 200µl of Buffer FG3 to the centrifuge tube, vortex at low speed for 5 seconds, and incubate at 65°C for 1 hour to dissolve the DNA. After dissolution, take 1µl of DNA for electrophoresis quality control.

[0050] (4) DNA concentration and quality assessment: Genomic DNA integrity was assessed by agarose gel electrophoresis, requiring clearly visible bands, no obvious degradation, and no RNA contamination. Simultaneously, the quality of genomic DNA was assessed using Nanodrop 2000, requiring a concentration ≥20 ng / μL, a total amount ≥1 μg, an OD260 / 280 of 1.7–2.0, and an OD260 / 230 ≥1.8.

[0051] (5) ACE-seq technology processing: The extracted genomic DNA was processed using ACE-seq technology to convert the C and 5mc of the genomic DNA that were not modified by hydroxymethylation into U.

[0052] (6) PCR amplification reaction: The primers used to amplify the hydroxymethylation site are shown in Table 1. The PCR reaction system (20 μL) contained 2 µL of sample DNA, 1× HotStarTaq buffer, and 3.0 mM Mg2+. 2+ 0.2 mM dNTPs, 1 U HotStarTaq polymerase (Qiagen Inc.), and 1 µL of multiplex PCR primers. The PCR cycle program is shown in Table 2. Table 1 PCR amplification primers

[0053] Table 2 PCR Cycling Program

[0054] (7) Sequencing after quantification: All sample index PCR amplification products were mixed in equal volumes, and the final high-throughput sequencing library was obtained by gel extraction. The fragment length distribution of the library was verified using an Agilent 2100 Bioanalyzer. After accurate quantification of the library molar concentration, high-throughput sequencing was finally performed on the Illumina high-throughput sequencing platform using 2×150bp paired-end sequencing mode to obtain FastQ data.

[0055] (8) Bioinformatics analysis of sequencing data: The filtered R1 and R2 short reads were spliced ​​into longer reads using FLASH software (FLASH: Fast length adjustment of short reads to improve genome assemblies) to obtain FastQ files; then the spliced ​​FastQ files were processed using FastX tool (http: / / hannonlab.cshl.edu / fastx_toolkit / index.html) to generate fa format sequences; then all reads in the fa format sequences were compared with the target region reference sequence using BLAST+ software (Camacho C, (2009) "BLAST+: architecture and applications"), and reads that could cover 90% of the target sequence were selected as valid reads and their number was counted; BLAST+ was used again to compare all reads in the fa format sequences with the target region reference sequence. The software is compared with the reference sequence of the target region to obtain valid sequencing sequences and remove redundant data. At the same time, the efficiency of the conversion of base C to T after glycosylation in the valid sequencing data of each sample is calculated. Finally, CpG site hydroxymethylation analysis is performed. By calculating the ratio of the number of reads with base C detected at the site (i.e., the number of hydroxymethylated reads) to the total number of reads at the site, the hydroxymethylation level of mtDNA CpG sites in peripheral blood leukocytes is finally determined.

[0056] 1.3 Results Analysis Multivariate logistic regression analysis was performed on 100 samples from the initial screening stage in this embodiment. A total of six CpG sites were identified as having a correlation between hydroxymethylation levels and SLE (Table 3). These six CpG sites all originated from the MT-COX2 gene on mtDNA, with the reference genome being NC_012920.1 (https: / / www.ncbi.nlm.nih.gov / nuccore / NC_012920.1). Specific site information is shown in Table 4.

[0057] Table 3. Association between mtDNA CpG site hydroxymethylation level and SLE

[0058] Note: In Table 3, hydroxymethylation levels are expressed as a percentage, and the data are described as median (P0.05). 25， P 75 ). Gender, age, and BMI have been adjusted.

[0059] Table 4. mtDNA CpG site information (the selected sites are hydroxymethylation sites).

[0060] Example 2: Validation of the correlation between CpG site hydroxymethylation level and SLE In this embodiment, an additional 300 clinical samples (150 SLE patients and 150 healthy controls) were used as validation samples. The sample source and inclusion criteria are as described in section 1.1 of Example 1.

[0061] Meanwhile, in this embodiment, the initial screening samples from Example 1 and the verification samples from this embodiment are combined, totaling 400 cases.

[0062] Following the experimental procedure in section 1.2 of Example 1, the hydroxymethylation levels of the six CpG sites were detected and analyzed for the above-mentioned validation samples and merged samples. Furthermore, the correlation between the hydroxymethylation levels of these six CpG sites and SLE was statistically analyzed using multivariate logistic regression analysis. The results are shown in Table 5.

[0063] Table 5. Association between mtDNA CpG site hydroxymethylation level and SLE

[0064] Note: Hydroxymethylation levels in Table 5 are expressed as percentages, and the data are described as median (P0.05). 25， P 75 ). Gender, age, and BMI have been adjusted.

[0065] The verification results showed that the CpG sites screened in this application were strongly associated with SLE, suggesting that these CpG sites could serve as biomarkers for diagnosing SLE.

[0066] Specifically, based on the statistical significance test, this embodiment adopts... OR As an assessment indicator, its numerical change can reflect the quantitative relationship between the degree of hydroxymethylation and the positivity or risk of disease: When the target CpG site OR A value significantly less than 1 indicates that for every unit increase in hydroxymethylation level at this site, the risk of disease positivity or disease incidence decreases accordingly; that is, a high hydroxymethylation status at this site is positively correlated with disease positivity or low disease incidence risk. Conversely, if... OR A value significantly greater than 1 indicates that elevated hydroxymethylation levels are associated with disease positivity or increased risk of disease development. In this case, a high hydroxymethylation status predicts SLE positivity or a high risk of disease development. According to the results presented in this application, the six CpG sites chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919, and chrM:7925... ORAll values ​​were greater than 1, indicating that for every unit increase in hydroxymethylation level, the risk of disease progression increased. OR -1. Therefore, the hyperhydroxymethylation status of chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919, and chrM:7925 can be used as biomarkers for the diagnosis of systemic lupus erythematosus.

[0067] Example 3: Diagnostic efficacy verification For the initial screening samples in Example 1, and the validation and merged samples in Example 2 (the merged samples were randomly divided into training and validation sets at a ratio of 7:3), ROC curve analysis was performed on the nomogram model constructed based on multivariate logistic regression analysis for the above six CpG loci. The results are shown in Table 6 and... Figure 1 As shown in the image.

[0068] Table 6. Sensitivity, specificity, and area under the curve for mtDNA CpG site hydroxymethylation in the diagnosis of SLE.

[0069] Through Table 6 and Figure 1 The analysis results showed that the AUC of the nomogram model in the initial screening samples was 0.736 (range 0.640-0.832), with a sensitivity of 96.0% and a specificity of 40.0%; the AUC of the nomogram model in the validation samples was 0.698 (range 0.639-0.756), with a sensitivity of 82.7% and a specificity of 47.3%; and in the merged samples, the AUC of the nomogram model in the training set was 0.691 (95%). CI= The AUC of the validation set noctilinear plot model was 0.762 (95%), with a sensitivity of 56.9% and a specificity of 71.6%. CI= The range of CpG sites is 0.677-0.847, with a sensitivity of 83.3% and a specificity of 59.1%. This indicates that these CpG sites have a certain diagnostic capability for systemic lupus erythematosus (SLE) and can be applied to the auxiliary diagnosis and prospective prediction of SLE in clinical practice. This is of great significance for the early intervention and treatment of SLE.

[0070] Example 4: System / Device for Diagnosing SLE Based on the above research results, this embodiment further discloses a system / device for diagnosing SLE, which consists of three core functional modules: Data Acquisition Module: This module is used to acquire the hydroxymethylation level of the screened hydroxymethylated CpG sites. The hydroxymethylation level can be detected by implementing the method described above.

[0071] Data Processing Module: This module uses a computer to process and analyze the test results to determine the patient's hydroxymethylation level. Simultaneously, it statistically correlates hydroxymethylation levels with disease incidence (whether the disease occurs), calculating the odds ratio (OR) using logistic regression. Based on statistical significance, the OR is interpreted as: for every unit increase in hydroxymethylation level, the risk of disease occurrence increases by a factor of (OR-1). Alternatively, the hydroxymethylation level can be input into a machine learning model, which determines a threshold and compares it with the hydroxymethylation level specified in this application. It is understood that the data processing module includes not only hardware acquisition devices such as computers but also necessary analysis software and computational tools; these are all conventional methods in the field and therefore not particularly limited.

[0072] Disease Diagnosis Module: This module diagnoses systemic lupus erythematosus based on the comparison results in the data processing module and outputs the diagnostic results.

[0073] In some specific examples, the data processing module uses the OR (OR) to determine the diagnosis of SLE. Specifically, if the OR at a certain site is <1, it means that with each unit increase in hydroxymethylation level, the risk of SLE positivity or disease decreases. Therefore, it can be inferred that a high hydroxymethylation state at this site indicates a low probability of SLE positivity or disease risk. Conversely, if the OR at this site is >1, it indicates that elevated hydroxymethylation levels are positively correlated with disease positivity or disease risk. Therefore, a low hydroxymethylation state at this site suggests SLE negativity or a low risk of disease.

[0074] It should be noted that this application is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments with the same structure and effect as the technical concept within the scope of this application are included in the technical scope of this application. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of this application, are also included in the scope of this application.

Claims

1. A CpG site for diagnosing SLE, characterized in that, The CpG site originates from the MT-COX2 gene on mtDNA, and the CpG site is any one or a combination of two or more of chrM:7757, chrM:7775, chrM:7814, chrM:7850, chrM:7919, and chrM:7925.

2. The CpG site as described in claim 1, characterized in that, The diagnosis is determined by detecting the hydroxymethylation level of the CpG site.

3. The use of the reagent for detecting the level of hydroxymethylation at the CpG site as described in claim 1 or 2 in the preparation of products for diagnosing SLE.

4. The application as described in claim 3, characterized in that, The product in question is a reagent kit.

5. The application as described in claim 3, characterized in that, The reagents include primer pairs that amplify the CpG site, or nucleic acid probes that specifically bind to the CpG site.

6. The application as described in claim 5, characterized in that, The primer pair includes an upstream primer and a downstream primer, the nucleotide sequence of the upstream primer is shown in SEQ ID NO.1, and the nucleotide sequence of the downstream primer is shown in SEQ ID NO.

2.

7. An in vitro diagnostic tool for SLE, characterized in that, The in vitro detection tool includes a reagent for detecting the hydroxymethylation level of the CpG site as described in claim 1 or 2.

8. The in vitro diagnostic tool as described in claim 7, comprising an instruction manual, characterized in that, The instruction manual describes a method for detecting the hydroxymethylation level of the CpG site, the method comprising the following steps: Obtain biological samples from the subjects and extract DNA from the biological samples; After glycosylation and deamination of the extracted DNA, multiplex PCR amplification was performed on the target fragment. Sequencing of PCR amplification products; Sequencing data were analyzed to determine the hydroxymethylation level of the CpG sites.

9. The in vitro detection tool as described in claim 8, characterized in that, The biological sample is the subject's peripheral blood sample.

10. A system / device for diagnosing SLE, characterized in that, include: A data acquisition module is used to acquire the hydroxymethylation level of CpG sites in the subject's biological sample, wherein the CpG sites are as described in claim 1 or 2; The data processing module is used to analyze the hydroxymethylation level of the acquired CpG sites. The analysis includes statistical analysis of the correlation between the hydroxymethylation level of CpG sites and SLE, or inputting the hydroxymethylation level of CpG sites into a pre-trained machine learning model. The disease diagnosis module is used to diagnose SLE based on the analysis and processing results in the data processing module and output the diagnosis results.

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