Application of programmed cell death protein 5 in monitoring course of autoimmune disease

Abstract

The invention provides application of programmed cell death protein 5 in monitoring the course of an autoimmune disease, and relates to the technical field of biological detection, and the autoimmune disease is systemic lupus erythematosus. According to the technical scheme, 158 patients newly diagnosed as SLE and 63 healthy controls are used, and basic clinical data, including various biochemical indexes, of the SLE patients are collected; a measured peripheral blood mononuclear cell blood sample is collected in residual blood clinically used for conventional whole blood cell counting, gene expression of programmed cell death protein 5 and cell factors is detected through real-time fluorescent quantitative PCR, and the relation between the expression of the programmed cell death protein 5 and SLE morbidity and alleviation is evaluated through Logistic regression. The predictive ability and important indexes of the programmed cell death protein 5 on SLE attack and alleviation are evaluated by analyzing a working characteristic curve of a subject.

Description

Technical Field

[0001] The present invention relates to the field of biological detection technology, and in particular to an application of programmed cell death protein 5 in monitoring the course of autoimmune diseases. Background Art

[0002] Systemic lupus erythematosus (SLE) is a complex autoimmune disease, and the development of disease course monitoring technology is crucial to improving the quality of life and prognosis of patients. Currently, the medical community uses a variety of methods and technologies to monitor the activity of SLE and evaluate the treatment effect, mainly including laboratory tests, clinical symptom assessment, and imaging examinations.

[0003] Currently, laboratory tests for SLE include blood tests such as antinuclear antibodies (ANA), anti-double-stranded DNA antibodies (ds-DNA), and complement C3 and C4 levels. Among them, the detection of antinuclear antibodies may have false positive results and has low specificity. ds-DNA antibody levels and complement C3 and C4 level tests can reflect the activity of the disease, but their changes do not always match the clinical symptoms, and the test results are volatile. The clinical symptom evaluation method relies on the doctor's experience and personal judgment, which may lead to differences in the evaluation results. The symptoms of SLE vary from person to person, which increases the difficulty of accurately assessing the condition. The imaging examination of SLE is expensive and requires professional instruments, which is costly and has a cumbersome testing process. Summary of the invention

[0004] The main purpose of the present invention is to propose an application of programmed cell death protein 5 in monitoring the course of autoimmune diseases, aiming to solve the problems of low specificity and inconvenient detection in the detection of systemic lupus erythematosus.

[0005] To achieve the above object, the present invention proposes an application of programmed cell death protein 5 in monitoring the course of an autoimmune disease, wherein the autoimmune disease is systemic lupus erythematosus.

[0006] In the technical scheme of the present invention, 158 patients newly diagnosed with SLE (52 in active and stable phases) and 63 healthy controls were selected, and basic clinical data of SLE patients, including various biochemical indices, were collected; peripheral blood mononuclear cell (PBMC) blood samples measured by the present invention were collected from the remaining blood used for routine complete blood counts in clinical practice, and real-time fluorescence quantitative PCR (qPCR) was used to detect the gene expressions of programmed cell death protein 5 (PDCD5) and cytokines (FOXP3, IFN-γ, IL-17A, IL-6 and TNF-α), and Logistic regression was used to evaluate the relationship between PDCD5 expression and the incidence and remission of SLE, and receiver operating characteristic (ROC) analysis was used to evaluate the predictive ability and important indicators of PDCD5 for the onset and remission of SLE. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0008] Figure 1 This is a graph showing the difference in PDCD5 expression between different patient groups and a healthy control group in Example 3 of the present invention;

[0009] Figure 2 This is a graph showing the results of the correlation analysis between PDCD5 expression and clinical parameters of SLE patients in Example 4 of the present invention.

[0010] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0011] To make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them.

[0012] It should be noted that, in the embodiments, those without specifying specific conditions are carried out according to normal conditions or conditions recommended by the manufacturer. Those without specifying the manufacturer of reagents or instruments used are conventional products that can be purchased commercially. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes, and "A and / or B" is taken as an example, including schemes A, B, or A and B that meet the same time. In addition, the technical schemes between the various embodiments can be combined with each other, but must be based on the ability of ordinary technicians in the field to achieve. When the combination of the technical schemes is contradictory or cannot be achieved, it should be considered that the combination of such technical schemes does not exist, and is not within the scope of protection required by the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without making creative work, all belong to the scope of protection of the present invention.

[0013] Currently, laboratory tests for SLE include blood tests such as antinuclear antibodies (ANA), anti-double-stranded DNA antibodies (ds-DNA), and complement C3 and C4 levels. Among them, the detection of antinuclear antibodies may have false positive results and has low specificity. ds-DNA antibody levels and complement C3 and C4 level tests can reflect the activity of the disease, but their changes do not always match the clinical symptoms, and the test results are volatile. The clinical symptom evaluation method relies on the doctor's experience and personal judgment, which may lead to differences in the evaluation results. The symptoms of SLE vary from person to person, which increases the difficulty of accurately assessing the condition. Imaging examinations for SLE are expensive and require professional instruments, which are costly.

[0014] Recent studies have found that T follicular helper cells (TFH) and T peripheral helper cells (TPH) play an important role in B cell maturation and autoantibody production in systemic lupus erythematosus (SLE). In addition, T lymphocytes participate in inflammatory signaling networks that cause organ damage mainly in the skin, kidneys, joints, lungs, and vascular system. Biomarkers are very important to guide clinical and therapeutic management of all stages of SLE (active phase and stable remission phase), and capable indicators can predict disease progression in at-risk patients, provide prognostic information, and evaluate treatment response.

[0015] Programmed Cell Death 5 (PDCD5) was originally thought to be an apoptosis-related gene cloned from TF-1 cells during apoptosis in 1999. Recent studies have shown that PDCD5 is involved in regulating metabolic homeostasis and maintaining cellular protein homeostasis as a cofactor. The expression of the PDCD5 gene is significantly upregulated in virally infected, inflammatory activated peripheral blood mononuclear cells (PBMCs) and inflammatory fibrotic lung tissues. Therefore, PDCD5 may play multiple roles in the cell cycle and act as a determinant of cell fate to respond to various environmental stimuli. For example, PDCD5 can promote activation-induced cell death (AICD) of autoreactive T cells, thereby inhibiting the secretion of inflammatory factors. It has been previously demonstrated that PDCD5 promotes Treg cells from Differentiation of PDCD5 cells and may play a regulatory role in autoimmune diseases. Compared with healthy controls, the expression level of PDCD5 is upregulated in PBMCs of patients with multiple sclerosis (MS). Serum and synovial PDCD5 levels are also significantly increased in RA patients. In summary, increasing evidence indicates that PDCD5 is an immune regulation-related gene. PDCD5 upregulation is involved in different inflammatory and autoimmune diseases.

[0016] However, to date, studies comparing the correlation between PDCD5 expression levels and SLE progression are still missing.

[0017] In view of this, the present invention proposes an application of programmed cell death protein 5 in monitoring the course of an autoimmune disease, wherein the autoimmune disease is systemic lupus erythematosus.

[0018] In the technical scheme of the present invention, 158 patients newly diagnosed with SLE (52 in active and stable phases) and 63 healthy controls were selected to collect basic clinical data of SLE patients, including various biochemical indices; peripheral blood mononuclear cell (PBMC) blood samples measured by the present invention were collected from the remaining blood used for routine complete blood counts in clinical practice, and real-time fluorescence quantitative PCR (qPCR) was used to detect the gene expression of PDCD5 and cytokines (FOXP3, IFN-γ, IL-17A, IL-6 and TNF-α), and Logistic regression was used to evaluate the relationship between PDCD5 expression and the incidence and remission of SLE, and receiver operating characteristic (ROC) analysis was used to evaluate the predictive ability and important indicators of PDCD5 for the onset and remission of SLE.

[0019] This paper compares the expression levels of PDCD5 PBMC gene in acute and stable phases of SLE patients for the first time, explores the predictive ability of PDCD5 for the onset and remission of SLE, and further evaluates the correlation between PDCD5 gene expression and cytokines. The results show that PDCD5 may be a new biomarker with a better predictive effect on the incidence and remission of SLE.

[0020] The technical solution of the present invention is further described in detail below in conjunction with specific embodiments. It should be understood that the following embodiments are only used to explain the present invention, and are not used to limit the present invention.

[0021] Example 1

[0022] According to the 2019 American College of Rheumatology / European League Against Rheumatism (ACR / EULAR) criteria, 158 patients diagnosed with SLE admitted to Xiangyang Central Hospital from August 2022 to March 2024 were included in the present invention. Among them, samples and information of 52 patients were collected in both active and stable phases. Clinical activity was defined as SLE Disease Activity Index (SLEDAI)-2K score>6, while low disease activity was defined as SLEDAI-2K score ≤4, following the lupus low-level disease activity (LLDAS) criteria.

[0023] The exclusion criteria for SLE patients were as follows: (1) diagnosed with other autoimmune diseases; (2) receiving any glucocorticoid and / or immunosuppressive drug treatment within 1 month before enrollment; and (3) missing age, gender, and important clinical laboratory test information.

[0024] Healthy controls (HC) were obtained from the physical examination center and underwent physical examination in the hospital. The gender and age distribution were basically matched with SLE patients. The present invention has been approved by the Ethics Committee of Hubei University of Arts and Sciences. The present invention was carried out in accordance with the ethical standards of the Declaration of Helsinki. Informed consent was obtained from everyone involved in this study.

[0025] Example 2

[0026] The basic clinical data of SLE patients were collected, including white blood cells (WBC), lymphocytes, immunoglobulin (Ig) A, IgM, IgG, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), anti-dsDNA, anti-sm and other biochemical indicators. IgA, IgM and IgG were analyzed using image800

[0027] (Beckman Coulter Inc., Brea, CA). Anti-dsDNA and anti-sm were detected by indirect immunofluorescence using Sprinter XL (Euroimmune, Lubeck, Germany). CRP was detected using i-CHROMA (BodiTech Med Inc., Chuncheon, Korea). WBC and lymphocytes were detected using Sysmex XE-2100 (TOA Medical Electronics, Kobe, Japan). ESR was measured using the Vacuette ESR system (Greiner Bio-One, Germany). The SLE Disease Activity Index (SLEDAI)-2K score was obtained by evaluating the degree of disease activity.

[0028] A total of 158 active SLE patients and 63 healthy controls participated in this study. Among all SLE patients, 89 patients were in the active phase and 69 patients were in the stable phase. The demographic and clinical characteristics of SLE patients are shown in Table 1.

[0029] Table 1 Demographic and clinical characteristics of SLE patients

[0030]

[0031]

[0032] In Table 1 , continuous variables are expressed as mean ± SD or median (Q1–Q3), and categorical variables are expressed as n (%); SLE, systemic lupus erythematosus; WBC, white blood cell; Hb, hemoglobin; HCT, hematocrit; LYMPH, lymphocyte; LYM%, lymphocyte%; NEU%, neutrophil%; MON%, monocyte%; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; anti-dsDNA, anti-double-stranded DNA; anti-Sm, anti-Smith antibody; SLEDAI, SLE disease activity index.

[0033] The results showed that there were no significant differences in age (58.35±12.64 vs. 56.28±7.94, P=0.236) and gender (male: 47.2% vs. 44.9%, P=0.777) between active and stable SLE patients. The same results were also found in the comparison of smoking and drinking status between the two groups. The WBC (6.24±1.36 vs. 8.92±1.72, P<0.001) and lymphocyte (3.29±0.15 vs. 5.08±0.98, P<0.001) counts in active SLE patients were significantly lower than those in stable SLE patients. The CRP, ESR, IgG, IgA, and IgM levels in active SLE patients were significantly higher than those in stable SLE patients (all P<0.05).

[0034] Example 3

[0035] The blood samples measured in this study were collected from the remaining blood used for routine complete blood count (CBC) in the clinic. 2 ml of whole blood was centrifuged in an ethylenediaminetetraacetic acid vacuum container (3000 rpm, 7 min, 4 ° C) to remove plasma. The cell pellet was resuspended in 2 ml of red blood cell lysis reagent (A11895, Beckman Coulter) for 5 minutes, and then centrifuged to remove the lysis buffer (3000 rpm, 5 min, 4 ° C). After washing twice with 2 ml PBS (2000 rpm, 5 min, 4 ° C), the cell pellet was resuspended in 1 ml TRIzol (269212, Ambion, USA) and frozen at -80 ° C for use. RNA extraction and qPCR amplification were performed.

[0036] The specific primer sequences are as follows:

[0037] PDCD5:

[0038] (F) 5′-CTTGAGGCGCTGAGGAGAC-3′ (SEQ ID NO. 1),

[0039] (R) 5′-GGCCGACTGATCCAGAACTT-3′ (SEQ ID NO. 2);

[0040] INF-γ:

[0041] (F) 5′-TCCAGTTACTGCCGGTTTGA-3′ (SEQ ID NO. 3),

[0042] (R) 5′-TGGAAGCACCAGGCATGAAA-3′ (SEQ ID NO. 4);

[0043] FOXP3:

[0044] (F) 5′-TCTTCCTTGAACCCCATGCC-3′ (SEQ ID NO. 5),

[0045] (R) 5′-AAATGTGGCCTGTCCTGGAG-3′ (SEQ ID NO. 6);

[0046] IL-17A:

[0047] (F) 5′-TAATGGCCCTGAGGAATGGC-3′ (SEQ ID NO. 7),

[0048] (R) 5′-AGGAAGCCTGAGTCTAGGGG-3′ (SEQ ID NO. 8);

[0049] TNF-α:

[0050] (F)5'-GACAGATGTGGGGTGTGAGAA-3', (SEQ ID NO.9)

[0051] (R) 5'-TCTGTGTGCCAGACACCCTA-3' (SEQ ID NO. 10);

[0052] IL-6:

[0053] (F) 5′-GTCCAGTTGCCTTCTCCCTG-3′ (SEQ ID NO. 11),

[0054] (R) 5′-CTGAGATGCCGTCGAGGATG-3′ (SEQ ID NO. 12);

[0055] GAPDH:

[0056] (F) 5′-GACCACAGTCCATGCCATCAC-3′ (SEQ ID NO. 13),

[0057] (R) 5'-TCCACCACCCTGTTGCTGTAG-3' (SEQ ID NO. 14).

[0058] qPCR detection and ABI7500 instrument were used to collect data.

[0059] The expression difference of PDCD5 was detected by qPCR, and the results were as follows Figure 1 shown.

[0060] Among them, Figure 1As shown in A, compared with the healthy control group, the average expression level of PDCD5 in SLE patients was significantly increased (0.07±0.01 vs. 0.18±0.02, P<0.001).

[0061] The differences in PDCD5 expression levels between active and stable SLE patients were analyzed. Figure 1 As shown in B. The results showed that the PDCD5 mRNA expression level in active SLE patients was significantly higher than that in stable SLE patients (0.32±0.03 vs. 0.06±0.01, P<0.001).

[0062] In addition, samples from 52 SLE patients in active and stable phases were collected. Figure 1 C. Paired t-test revealed that the expression of PDCD5 in stable SLE patients was significantly lower than that in active SLE patients (0.10±0.02 vs 0.36±0.04, P<0.001).

[0063] Example 4

[0064] Characteristics were expressed as mean ± standard deviation (SD) or median (Q1-Q3) for continuous data, and N (percentage) for qualitative data. Quantitative analysis was performed using t-test, and qualitative analysis was performed using chi-square test to assess differences between variables. Linear correlation analysis was used to evaluate the correlation between PDCD5 expression and biochemical index levels. Receiver operating characteristic curve (ROC) analysis was used to evaluate the predictive ability of PDCD5 and important indexes for SLE incidence. Univariate and multivariate logistic regression were used to assess the multivariate-adjusted odds ratio (OR) and 95% confidence interval (CI) between PDCD5 expression and SLE incidence and activity. Covariates in the model included age, sex, smoking status, drinking status, and other demographic characteristics. A two-sided P value of less than 0.05 was defined as a statistically significant difference. GraphPad Prism 5 software was used to draw the figures. SAS 9.4 software (SAS Institute, Cary, NC) was used for statistical analysis.

[0065] Univariate and multivariate logistic regression were used to evaluate the relationship between PDCD5 expression and SLE incidence and remission. The results are shown in Table 2.

[0066] Table 2 Relationship between PDCD5 expression and the risk of SLE onset and remission

[0067]

[0068] *P<0.05, **P<0.01, ***P<0.001,

[0069] a Univariate analysis.

[0070] b Adjustments were made for age, sex, smoking status, alcohol drinking status, and medical history.

[0071] SLE, systemic lupus erythematosus; OR, odds ratio; CI, confidence interval.

[0072] After considering factors such as age, gender, smoking, drinking status, and medical history, the higher the PDCD5 expression, the higher the risk of SLE (OR = 3.28, 95% CI = 1.16-6.79, P = 0.007). According to the median value of PDCD5 mRNA expression level, SLE patients were divided into low / high risk groups, and the risk of SLE in the high-risk group increased by 4.26 times (OR = 4.26, 95% CI = 1.69-8.65, P < 0.001). Similar results were also shown when analyzing the relationship between PDCD5 expression and the activity of SLE patients. Multivariate logistic regression analysis showed that compared with the low-risk group, the probability of patients in the high-risk group turning to the active stage increased by 7.34 times (OR = 7.34, 95% CI = 4.90-11.69, P < 0.001).

[0073] ROC analysis was used to evaluate the predictive ability and important indicators of PDCD5 for the onset and remission of SLE. Compared with clinical indicators such as WBC, CRP, ESR, and LYMPH, the results are shown in Table 3. PDCD5 has a better predictive value for the incidence of SLE, with an AUC of 0.862 (95% CI: 0.766-0.908), a sensitivity of 89.4%, and a specificity of 82.9%. The AUC for CRP prediction was 0.790 (95% CI: 0.729-0.851), the AUC for ESR prediction was 0.768 (95% CI: 0.705-0.832), and the AUC for LYM% prediction was 0.722 (95% CI: 0.655-0.789).

[0074] Table 3 Predictive ability and important indicators of PDCD5 for SLE incidence

[0075]

[0076] In Table 3, AUC, area under the curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; WBC, white blood cell; CRP, c-reactive protein; ESR, erythrocyte sedimentation rate; LYMPH, lymphocyte; LYM%, lymphocyte%; NEU%, neutrophil%; MON%, monocyte%.

[0077] On the other hand, when evaluating the predictive ability of PDCD5 and important indices for SLE remission, PDCD5 also had the best predictive value for SLE incidence, as shown in Table 4, with an AUC of 0.893 (95% CI: 0.782-0.945), a sensitivity of 91.8%, and a specificity of 88.6%. These results indicate that PDCD5 has a better predictive ability for SLE incidence and remission than several important clinical indices. PDCD5 may be used as a new biomarker to predict SLE incidence and remission.

[0078] Table 4 Predictive ability and important indicators of PDCD5 for SLE remission

[0079]

[0080]

[0081] In Table 4, AUC, area under the curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; WBC, white blood cell; CRP, c-reactive protein; ESR, erythrocyte sedimentation rate; LYMPH, lymphocyte; LYM%, lymphocyte %; NEU%, neutrophil %; MON%, monocyte %

[0082] To explore the significance of increased PDCD5 expression in SLE patients, the correlation analysis between PDCD5 expression and clinical parameters such as WBC, CRP, ESR, anti-dsDNA, D-dimer, and SLEDAI score of SLE patients was performed. Figure 2 As shown, Figure 2 A is the correlation analysis between PDCD5 expression and CRP. Figure 2 B is the correlation analysis between PDCD5 expression and ESR. Figure 2 C is the correlation analysis between PDCD5 expression and WBC, Figure 2 D is the correlation analysis between PDCD5 expression and D-dimer, Figure 2 E is the correlation analysis between PDCD5 expression and anti-dsDNA. Figure 2 F is the correlation analysis between PDCD5 expression and SLEDAI score.

[0083] according to Figure 2It was found that PDCD5 expression was significantly positively correlated with CRP (r=0.727, P<0.001), ESR (r=0.648, P<0.001), WBC (r=0.780, P<0.001), D-dimer (r=0.707, P<0.001), anti-dsDNA (r=0.715, P<0.001), and SLEDAI score (r=0.814, P<0.001).

[0084] In addition, the present invention further conducted a differential analysis of the low-level and high-level expressions of PDCD5 in several clinical indicators of SLE. SLE patients were divided into high-level and low-level groups according to the median ESR level. The PDCD5 expression level in the high-level group was significantly higher than that in the low-level group (0.53±0.12 vs.

[0085] 0.26±0.08, P=0.015). The anti-dsDNA score and SLEDAI score were significantly different (anti-dsDNA score 0.64±0.13 vs. 0.28±0.19, P=0.008; SLEDAI score 0.73±0.12 vs.

[0086] 0.30±0.08,P<0.001).

[0087] FOXP3, IFN-γ, IL-17A, IL-6, and TNF-α play important roles in the remission and relapse phases of SLE. It has been previously reported that PDCD5 upregulates FOXP3 and downregulates IFN-γ, IL-17A, IL-6, and TNF-α in SLE rat models. To evaluate the importance of these factors in the increased expression of PDCD5 in SLE patients, the gene levels of FOXP3, IFN-γ, IL-17A, IL-6, and TNF-α were measured. To evaluate the correlation between PDCD5 expression and cytokines in all SLE patients and active SLE patients, linear correlation analysis was further performed, and the results are shown in Table 5.

[0088] Table 5 Relationship between PDCD5 mRNA expression and cytokines in SLE patients

[0089]

[0090] FOXP3, forkhead box protein 3; TNF-α, tumor necrosis factor-α; IFN-γ, interferon-γ; IL-17A, interleukin-17A; IL-6, interleukin 6; CI, confidence interval.

[0091] The results in Table 5 showed that the expression level of PDCD5 was positively correlated with FOXP3 (r = 0.748, P < 0.001), TNF-α (r = 0.686, P = 0.012), and IFN-γ (r = 0.782, P < 0.001). Other cytokines, such as IL-17A (r = 0.717, P = 0.031) and IL-6 (r = 0.801, P = 0.006), also had similar relationships. In addition, correlation analysis was also performed on patients with active SLE, and there was still a significant correlation between the expression of PDCD5 and cytokines, especially FOXP3 (r = 0.832, P < 0.001), IFN-γ (r = 0.793, P = 0.002), and IL-6 (r = 0.827, P < 0.001).

[0092] In addition, the difference in PDCD5 expression between low and high levels of cytokines in SLE patients was further analyzed. SLE patients were divided into high and low levels according to the median FOXP3 level. The expression level of PDCD5 in the high level group was significantly higher than that in the low level group (0.49±0.10 vs. 0.23±0.06, P=0.009). The expression was more obvious in IFN-γ and IL-6 (IFN-γ 0.72±0.10 vs. 0.31±0.19, P<0.001; IL-6 0.61±0.09 vs. 0.28±0.07, P=0.006). These results suggest that cytokines are related to the expression of PDCD5 in SLE patients, and PDCD5 may be a potential regulatory factor in the pathological microenvironment of SLE.

[0093] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A method for monitoring the course of autoimmune diseases by using programmed cell death protein 5, characterized in that: The autoimmune disease is systemic lupus erythematosus.

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