Application of long-chain non-coding RNA in peripheral blood as a marker in preparation of diagnostic reagent for systemic lupus erythematosus

Abstract

The application discloses application of long-chain non-coding RNA in peripheral blood as a marker in preparation of a systemic lupus erythematosus diagnostic reagent, and is characterized in that the long-chain non-coding RNA (lncRNA) is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1, preferably, the lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1. The application finds for the first time that the expression level of the above lncRNA in peripheral blood mononuclear cells of SLE patients is significantly up-regulated, and is closely related to disease activity, lymphocyte subgroups and cytokine levels. The application also provides a product for diagnosing or assisting in diagnosing systemic lupus erythematosus, a system or device for diagnosing systemic lupus erythematosus. The biomarker and product of the application are expected to be used for assisting in diagnosing SLE, evaluating disease activity and monitoring immune status.

Description

Technical Field

[0001] This invention relates to the field of biomedical detection technology, specifically to the application of long non-coding RNA (lncRNA) in peripheral blood as a biomarker in the preparation of diagnostic reagents for systemic lupus erythematosus. Background Technology

[0002] Systemic lupus erythematosus (SLE) is a chronic, multi-system autoimmune disease characterized by excessive lymphocyte activation, overproduction of autoantibodies, and cytokine imbalance. SLE can affect multiple organs, including the skin, joints, kidneys, and central nervous system, exhibiting highly heterogeneous clinical manifestations and making early diagnosis difficult. Epidemiological data show that the annual incidence of SLE is 1.5-11.0 per 100,000, primarily affecting women of reproductive age, with a male-to-female ratio of approximately 1:9.

[0003] Currently, the diagnosis of SLE primarily relies on the revised classification criteria of the American College of Rheumatology (ACR), combined with the patient's clinical manifestations, autoantibody detection (such as antinuclear antibodies and anti-dsDNA antibodies), and organ damage assessment. However, existing biomarkers such as complement C3, C4, and anti-dsDNA have insufficient sensitivity or specificity, making it difficult to accurately reflect disease activity and immune status. Therefore, the development of novel, highly sensitive, and specific molecular biomarkers is of great significance for the early diagnosis, disease monitoring, and personalized treatment of SLE.

[0004] Long non-coding RNAs (lncRNAs) are a class of non-coding RNA molecules longer than 200 nucleotides. Recent studies have shown that lncRNAs can participate in the development of autoimmune diseases by regulating immune cell differentiation and the body's immune response (see Non-Patent Literature 1). Reports have shown that several differentially expressed lncRNAs exist in peripheral blood mononuclear cells (PBMCs) of SLE patients. The expression levels of ANKRD44-AS1, LINC00200, AP001363.2, and LINC02824 are positively correlated with the number of regulatory T cells (Tregs), while the expression levels of AP000640.1, AC124248.1, LINC00482, and MIR503HG are negatively correlated with the number of Tregs (see Non-Patent Literature 2). However, currently, very few lncRNAs can be used as diagnostic markers for SLE, and the mechanisms by which they are associated with lymphocyte subsets and cytokines remain unclear.

[0005] Therefore, there is an urgent need in this field to discover new SLE-related lncRNA biomarkers and develop corresponding detection products to achieve rapid and accurate diagnosis of SLE and assessment of immune status.

[0006] Existing technical documents Non-patent literature 1: Lodde V, Murgia G, Simula ER, Steri M, Floris M, Idda ML. Long Noncoding RNAs and Circular RNAs in Autoimmune Diseases [J]. Biomolecules, 2020, 10(7); Non-patent literature 2: Bu YJ, Cen Summary of the Invention The problem that the invention aims to solve In view of the shortcomings of existing technologies, the present invention provides a lncRNA biomarker for the auxiliary diagnosis of systemic lupus erythematosus (SLE), and products for the diagnosis or auxiliary diagnosis of systemic lupus erythematosus.

[0007] Methods for solving problems To address the aforementioned issues, the inventors of this application conducted repeated and in-depth research, resulting in the discovery of lncRNA biomarkers and related products that can assist in the diagnosis of systemic lupus erythematosus (SLE).

[0008] One technical solution of this application is as follows.

[0009] The application of long non-coding RNA in peripheral blood as a biomarker in the preparation of diagnostic reagents for systemic lupus erythematosus is characterized in that the long non-coding RNA, i.e., lncRNA, is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1.

[0010] Preferably, the lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

[0011] SPAG5-AS1 is an abbreviation for sperm-associated antigen 5 antisense RNA 1. SPAG5 is a mitotic spindle-associated protein that regulates the growth of various cancer cells. Some studies have shown that SPAG5 regulates podocyte autophagy by activating the AKT / mTOR pathway and is involved in the development of bladder urothelial carcinoma. SPAG5-AS1 is a neighboring gene of SPAG5 and regulates SPAG5 transcription and protein stability through interaction with ubiquitin-specific peptidase 14. Furthermore, some studies have confirmed that SPAG5-AS1 can inhibit podocyte autophagy and exacerbate apoptosis through the SPAG5 / AKT / mTOR pathway. mTOR connects immune and metabolic signaling, regulating immune cell function and the production of pro-inflammatory mediators, leading to persistent inflammation and tissue damage. However, the difference in SPAG5-AS1 expression levels between patients with systemic lupus erythematosus and healthy individuals has not been investigated in current techniques.

[0012] KDM4A-AS1, an abbreviation for histone lysine demethylase 4A antisense RNA 1, is a newly discovered lncRNA that can act as a tumor-promoting factor. One study found that inhibiting KDM4A-AS1 can reduce the viability, proliferation, and tumor growth of prostate cancer cells. KDM4A-AS1 has also been reported as a novel hypoxia-responsive gene, promoting the upregulation of hypoxia-inducible factor-1α (HIF-1α) through the KDM4A-AS1 / AKT / HIF-1α signaling pathway and enhancing the proliferation, migration, and epithelial-mesenchymal transition of liver cancer cells. HIF-1α signaling is overexpressed in diseases such as SLE and rheumatoid arthritis, altering the phenotype of dendritic cells (DCs) and promoting the differentiation of immature T cells into Th2 cells. In this study, the expression level of KDM4A-AS1 was significantly upregulated in SLE patients, negatively correlated with the Th2 cell count and Th2 cell ratio, and positively correlated with the Th1 / Th2 ratio. Th1 cells produce cytokines such as IFN-γ and IL-2 to promote cellular immunity. Th2 cells produce cytokines such as IL-4, IL-5, IL-6, and IL-10 to enhance humoral immunity and eliminate other extracellular pathogens. The shift in Th1 / Th2 balance is currently considered a key process in the pathogenesis of SLE. This suggests that KDM4A-AS1 may influence SLE progression through its interaction with the Th1 / Th2 balance. Prior to this application, the difference in KDM4A-AS1 expression levels between patients with systemic lupus erythematosus and healthy individuals had not been investigated.

[0013] LINC01484 is an abbreviation for long intergenic non-coding RNA 1484. One study showed that LINC01484 plays a crucial role in the development and metastasis of bladder urothelial carcinoma by participating in the PI3K / Akt signaling pathway and the interaction between cytokines and their receptors. This result indicates that LINC01484 can directly affect the mechanism of cytokine-receptor binding or influence downstream responses through signal transduction. Prior to this application, the difference in LINC01484 expression levels between patients with systemic lupus erythematosus (SLE) and healthy individuals had not been studied. In this invention, we found that the expression level of LINC01484 in SLE patients was negatively correlated with the proportion of total T lymphocytes and Th cells.

[0014] MALAT1, an abbreviation for metastasis-associated lung adenocarcinoma transcript-1, is an important lncRNA expressed in various tissues and involved in various diseases and biological processes. In various cancers, upregulation of MALAT1 expression can enhance tumor cell proliferation, migration, and invasion, and inhibit apoptosis. MALAT1 is aberrantly expressed in cardiovascular diseases, affecting endothelial cell function and angiogenesis. It has been reported that MALAT1 is aberrantly expressed in inflammatory diseases such as diabetic complications, sepsis, and spinal cord injury, exerting a pro-inflammatory effect as a cytokine regulator. Furthermore, MALAT1 affects the maturation of dendritic cells (DCs), macrophage differentiation, and Treg cell function. Studies have confirmed increased MALAT1 expression in PBMCs of SLE patients, and inhibiting MALAT1 can reduce IL-21 levels in monocytes, suggesting that MALAT1 plays an important role in the pathogenesis and development of SLE. However, the difference in MALAT1 expression levels between patients with systemic lupus erythematosus (SLE) and healthy individuals has not yet been investigated using current techniques. In this study, the expression level of MALAT1 in SLE patients was negatively correlated with the number of NK cells, the proportion of NK cells, and the NK / Treg ratio, and positively correlated with Th1 / Th2 and the cytokine IL-4.

[0015] In this invention, the term "expression level" refers to the absolute or relative amount of the lncRNA biomarker described herein. The expression level of any of the lncRNA biomarkers described herein can be determined using various techniques known to those skilled in the art. Specifically, the absolute or relative amount of the lncRNA biomarkers described herein can be detected using methods well-known to those skilled in the art. The specific sequence information of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1 described herein can be found in the internationally available nucleic acid sequence database GeneBank.

[0016] This invention is the first to discover that the expression levels of any one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1 in peripheral blood microarrays (PBMCs) of SLE patients were significantly higher than those in healthy controls. Furthermore, experimentally determined operating curve (ROC) analyses of the expression levels of these four lncRNA molecules in peripheral blood samples from SLE patients and healthy individuals showed AUC values ​​of 0.753, 0.718, 0.684, and 0.655, respectively. Combined ROC analysis of the expression levels of these four lncRNA molecules yielded an AUC value of 0.802 (see specification). Figure 5 The levels were significantly higher than those of a single biomarker, indicating that the combined detection system of this invention has further enhanced auxiliary diagnostic value. See the embodiments and accompanying drawings for specific experiments and figures.

[0017] Another technical solution of this application is as follows.

[0018] A product for diagnosing or assisting in the diagnosis of systemic lupus erythematosus, characterized in that it comprises a reagent for detecting the expression level of lncRNA, wherein the lncRNA is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1.

[0019] Preferably, the lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

[0020] Preferably, the reagents comprise reagents used when detecting the lncRNA expression level by reverse transcription PCR, real-time quantitative PCR, nucleic acid hybridization technology, nucleic acid amplification technology, sequencing technology, chromatography technology, mass spectrometry technology, or microarray technology.

[0021] Preferably, the product comprises a kit, test strip, or chip. Further, the kit comprises reagents for detecting the lncRNA transcription level, and the chip comprises a solid-phase carrier and oligonucleotide probes immobilized on the solid-phase carrier, the oligonucleotide probes comprising oligonucleotide probes targeting the lncRNA for detecting the lncRNA transcription level.

[0022] Furthermore, the kit may also include: a container, instructions for use, a positive control, a negative control, a buffer, an adjuvant, or a solvent. Examples include solutions for suspending or fixing cells, detectable tags or labels, solutions for facilitating nucleic acid hybridization, solutions for lysing cells, or solutions for purifying nucleic acids.

[0023] In some embodiments, the kit described in this invention can be used to detect the expression of the aforementioned lncRNA by various methods selected from the group consisting of: reverse transcription PCR, real-time quantitative PCR, microarray detection, DNA blotting, RNA blotting, or in situ hybridization. Those skilled in the art can adjust and modify the detection method according to actual conditions and needs.

[0024] Another technical solution of this application is as follows.

[0025] A system or device for diagnosing systemic lupus erythematosus, characterized in that the system or device comprises: (1) Data acquisition module, used to acquire expression profile data of lncRNA in the sample of the subject to be tested, wherein the lncRNA is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1; (2) A diagnostic prediction module, used to provide the lncRNA expression profile data obtained by the data acquisition module as input data to the trained diagnostic prediction model, and the diagnostic prediction model is trained based on the expression profile data to predict the subject; (3) Prediction result acquisition module, used to acquire the output result of the diagnostic prediction model in the diagnostic prediction module and obtain the prediction result of the subject.

[0026] Preferably, the lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

[0027] Furthermore, the data acquisition module includes a detection device, which comprises a real-time quantitative PCR instrument and real-time quantitative PCR primers, a high-throughput sequencing platform, a detection chip, and a chip signal reader. The real-time quantitative PCR primers include real-time quantitative PCR primers for detecting the expression level of the lncRNA marker and internal control primers.

[0028] Furthermore, the diagnostic prediction module includes a computing device, which includes a memory and a processor; the memory stores a computer program, and the processor is configured to execute the computer program stored in the memory.

[0029] In this invention, the term "sample" refers to a biological specimen obtained from or derived from the intended individual (subject). The source of the biological specimen may be a fresh, frozen, and / or preserved organ or tissue sample, or solid tissue derived from a biopsy or primers; blood or any blood component. The term "sample" or "sample to be tested" includes biological samples that have been manipulated in any way after acquisition, such as by reagent treatment, stabilization, enrichment for certain components (e.g., proteins or polynucleotides), or embedding in a semi-solid or solid matrix for sectioning purposes. Examples of "samples" include, but are not limited to: cells, tissues, organs, body fluids (blood, lymph, etc.), digestive juices, sputum, bronchial lavage fluid, urine, feces, etc. Preferably, the sample is tissue or blood.

[0030] In this invention, the term "subject" refers to any animal, including both human and non-human animals. The term "non-human animal" includes all vertebrates, such as mammals like non-human primates (especially higher primates), sheep, dogs, rodents (such as mice or rats), guinea pigs, goats, pigs, cats, rabbits, cattle, and any livestock or pets; as well as non-mammals such as chickens, amphibians, reptiles, etc. In a specific embodiment of this invention, the subject is preferably a human.

[0031] Effects of the present invention This invention reports for the first time that the expression levels of four lncRNAs, namely SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1, are significantly increased in peripheral blood mononuclear cells (PBMCs) of SLE patients, which can serve as novel biomarkers for SLE diagnosis. In particular, the combination of these four biomarkers can achieve better specificity and sensitivity, and has higher auxiliary diagnostic value. Attached Figure Description

[0032] Figure 1 The diagram shows the relative expression of lncRNAs in PBMCs of the SLE group and the HCs (healthy control) group.

[0033] Figure 2 A graph showing the correlation between lncRNA expression levels and peripheral blood lymphocyte subsets in SLE patients.

[0034] Figure 3 A graph showing the correlation between lncRNA expression levels and CD4+ T cell subsets in SLE patients.

[0035] Figure 4 A graph showing the correlation between lncRNA expression levels and cytokines in SLE patients.

[0036] Figure 5ROC curve analysis of four lncRNAs in peripheral blood of patients with systemic lupus erythematosus (SLE) and their combined ROC curve analysis. Detailed Implementation

[0037] The present invention will be further described below through specific embodiments, but this is not intended to limit the invention. Those skilled in the art can make various modifications or improvements based on the basic idea of ​​the invention, but all such modifications or improvements are within the scope of the invention as long as they do not depart from the basic idea. Unless otherwise stated, all technical terms used herein have the same meaning as commonly understood by those skilled in the art. In case of any conflict, this specification shall prevail.

[0038] I. Experimental Instructions (1) Recruitment of participants and healthy controls This study recruited 36 patients with systemic lupus erythematosus (SLE) (age 38.28 ± 14.80 years) hospitalized in the Department of Rheumatology and Immunology, Second Affiliated Hospital of Shanxi Medical University from May to October 2023. All patients met the diagnostic criteria for SLE as revised by the American College of Rheumatology in 1997. Disease activity was assessed using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), and patients with a score greater than 5 were included. The normal control group consisted of 16 healthy volunteers (age 35.50 ± 12.89 years) who underwent examinations at the health check-up center from August to October 2023, none of whom had a history of autoimmune diseases. This study was approved by the Ethics Committee of the Second Affiliated Hospital of Shanxi Medical University (approval number: 2021YX147). Informed consent was obtained from all participants. The duration of SLE in patients was 24.00 (7.50, 81.00) months, and the SLEDAI score was 12.00 (9.00, 19.00). The age distribution and sex ratio were similar between the healthy population and SLE patients, with no statistically significant differences.

[0039] (2) Total RNA extraction and RT-qPCR Fasting peripheral venous blood (8 ml) was collected from SLE patients and healthy controls in the morning using EDTA tubes. PBMCs were isolated using Ficoll gradient centrifugation. Total RNA was extracted using chloroform and TRIzol reagent (Beyotime, China). A reverse transcription reaction system was prepared using PrimeScript RT Master Mix (Takara, Japan) with the following parameters: 37°C for 15 min, 85°C for 5 s, and 4°C for ∞ min, to synthesize cDNA. PCR reaction systems were prepared using TB Green Premix Ex Taq II (Takara, Japan) and ROX Reference Dye II (Takara, Japan). The reaction conditions were: 95°C pre-denaturation for 30 s, followed by 40 cycles: 95°C for 5 s, 60°C for 34 s, and 60°C for 1 min. The relative expression levels of lncRNAs were analyzed using the 2^-ΔΔCT method. Primer sequences for four lncRNAs and β-actin are listed in the sequence listing below.

[0040] (3) Measurement of cytokines Mix 50 μl of plasma and standard with 25 μl of fluorescent detection reagent and 25 μl of microsphere capture mixture, respectively. After thorough mixing, react at room temperature in the dark for 2.5 hours. Wash with 1 ml of PBS, centrifuge at 1500 rpm for 5 minutes, discard the supernatant, and then add 100 μl of PBS for instrument detection.

[0041] (4) Determination of peripheral blood lymphocyte subsets Add 20 μl of anti-CD45 / CD3 / CD4 / CD8 reagent to a counting tube with a known number of beads, and add 20 μl of anti-CD45 / CD3 / CD16+CD56 / CD19 reagent to a new counting tube. Collect 50 μl of peripheral venous blood using an EDTA tube and add it to the aforementioned counting tubes. Add 450 μl of hemolysin, run the test, and count using BD FACSCanto clinical software.

[0042] (5) Determination of CD4+ T lymphocyte subsets Collect 200 μl of peripheral blood using a heparin-anticoagulated tube, add 10 μl of PMA, 200 μl of RPMI-1640 medium, 10 μl of Ionomycin, and 1 μl of GolgiPlug, and mix well. Incubate at room temperature for 5 hours. Add 2.5 μl of anti-IFN-γ antibody and 10 μl of anti-IL-17 antibody, and stain in the dark for 30 minutes to detect Th1 and Th17 cells. Add 10 μl of anti-IL-4 antibody, and stain in the dark for 30 minutes to detect Th2 cells. Collect 100 μl of peripheral blood using a heparin-anticoagulated tube, add 10 μl of anti-CD4 antibody and 2.5 μl of anti-CD25 antibody, and mix well. Incubate at room temperature in the dark for 30 minutes. Then add a membrane-permeable agent and permeabilize for 30 minutes. Finally, add 2.5 μl of anti-foxp3 antibody to the mixture, and stain in the dark for 30 minutes to detect Treg cells.

[0043] (6) Statistical analysis Data were analyzed using SPSS 27.0 statistical software. Normally distributed continuous data were expressed as mean ± standard deviation, and skewed data were expressed as interquartile ranges (M, P25, P75). Independent samples t-tests were used to compare two groups of normally distributed data, and Mann-Whitney U tests were used to compare skewed data. Pearson's test was used to analyze the correlation between normally distributed continuous data groups, and Spearman's test was used to analyze the correlation between skewed data groups. P < 0.05 was considered statistically significant.

[0044] II. Results Analysis (a) Relative expression levels of lncRNAs in SLE patients and HCs The relative expression levels of lncRNAs (SPAG5-AS1, KDM4A-AS1, MALAT1, LINC01484) in the PBMCs of SLE patients were significantly higher than those in the HC group. The expression levels of lncRNAs between the two groups are shown in Table 1. Figure 1 As shown.

[0045] Table 1. Relative expression of lncRNAs in PBMCs of the SLE and HCs groups. *: P<0.05, ××: P<0.01, ×××: P<0.001 (b) Correlation analysis between lncRNA expression levels and clinical indicators in SLE patients This study analyzed the correlation between lncRNA expression levels and clinical indicators in SLE patients. The results showed that SPAG5-AS1 expression levels were positively correlated with SLEDAI (r=0.386, P=0.020) and negatively correlated with IgG (r=-0.404, P=0.015). KDM4A-AS1 expression levels were positively correlated with C-reactive protein (CRP) (r=0.444, P=0.007). LINC01484 was positively correlated with platelets (r=0.430, P=0.009). MALAT1 was positively correlated with CRP (r=0.384, P=0.021). Detailed correlation analyses are shown in Table 2.

[0046] Table 2. Correlation analysis between lncRNA expression levels and clinical indicators in SLE patients. (c) Correlation analysis between lncRNA expression levels and peripheral blood lymphocyte subsets in SLE patients This study further analyzed the correlation between lncRNA expression levels and peripheral blood lymphocyte subsets in SLE patients. The results showed that LINC01484 expression levels were negatively correlated with the proportion of total T lymphocytes (r=-0.390, P=0.019), and MALAT1 was negatively correlated with NK cells (r=-0.357, P=0.033) and the proportion of NK cells (r=-0.353, P=0.035). Detailed correlation analysis is shown in Table 3 and... Figure 2 .

[0047] Table 3. Correlation analysis between lncRNA expression levels and peripheral blood lymphocyte subsets in SLE patients. (d) Correlation analysis between lncRNA expression levels and CD4+ T cell subsets in SLE patients This study analyzed the correlation between lncRNA expression levels and CD4+ T cell subsets in SLE patients. The results showed that KDM4A-AS1 expression levels were negatively correlated with Th2 cells (r=-0.347, P=0.038) and the proportion of Th2 cells (r=-0.337, P=0.044), and positively correlated with the Th1 / Th2 ratio (r=0.335, P=0.046). MALAT1 was positively correlated with the Th1 / Th2 ratio (r=0.331, P=0.049) and negatively correlated with the NK / Treg ratio (r=-0.377, P=0.023). Detailed correlation analysis is shown in Table 4 and... Figure 3 .

[0048] Table 4. Correlation analysis between lncRNA expression levels and CD4+ T cell subsets in SLE patients. (e) Correlation analysis of lncRNA expression levels and cytokines in SLE patients This study analyzed the correlation between lncRNA expression levels and cytokines in SLE patients. The results showed that MALAT1 expression levels were positively correlated with IL-4 (r=0.452, P=0.006). Detailed correlation analysis is shown in Table 5. Figure 4 .

[0049] Table 5. Correlation analysis of lncRNA expression levels and cytokines in SLE patients. (f) ROC curve analysis of four lncRNAs in peripheral blood of patients with systemic lupus erythematosus and their combined ROC curve analysis ROC curve analysis of the expression levels of four lncRNA molecules—SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1—in peripheral blood samples from SLE patients and healthy individuals showed AUC values ​​of 0.753, 0.718, 0.684, and 0.655, respectively. Combined ROC analysis of the expression levels of these four lncRNA molecules yielded an AUC value of 0.802 (see [link to ROC curve analysis]). Figure 5 The levels of the four lncRNAs were significantly higher than those of a single biomarker, suggesting that the combined detection system of the four lncRNAs has higher auxiliary diagnostic value.

Claims

1. The application of long non-coding RNA in peripheral blood as a biomarker in the preparation of diagnostic reagents for systemic lupus erythematosus, characterized in that, The long non-coding RNA, i.e., lncRNA, is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1.

2. The application of long non-coding RNA in peripheral blood as a biomarker as described in claim 1 in the preparation of diagnostic reagents for systemic lupus erythematosus, wherein, The lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

3. A product for diagnosing or assisting in the diagnosis of systemic lupus erythematosus, characterized in that, The reagent includes a reagent for detecting lncRNA expression levels, wherein the lncRNA is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1.

4. The product as described in claim 3, wherein, The lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

5. The product as described in claim 3 or 4, wherein, The reagents include those used when detecting the expression level of the lncRNA by reverse transcription PCR, real-time quantitative PCR, nucleic acid hybridization, nucleic acid amplification, sequencing, chromatography, mass spectrometry or microarray technology.

6. The product as described in any one of claims 3 to 5, wherein, The product may include a reagent kit, test strip, or chip.

7. A system or device for diagnosing systemic lupus erythematosus, characterized in that, The system or apparatus includes: (1) Data acquisition module, used to acquire expression profile data of lncRNA in the sample of the subject to be tested, wherein the lncRNA is at least one of SPAG5-AS1, KDM4A-AS1, LINC01484, and MALAT1; (2) A diagnostic prediction module, used to provide the lncRNA expression profile data obtained by the data acquisition module as input data to the trained diagnostic prediction model, and the diagnostic prediction model is trained based on the expression profile data to predict the subject; (3) Prediction result acquisition module, used to acquire the output result of the diagnostic prediction model in the diagnostic prediction module and obtain the prediction result of the subject.

8. The system or apparatus as claimed in claim 7, characterized in that, The lncRNA is a combination of SPAG5-AS1, KDM4A-AS1, LINC01484 and MALAT1.

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