Biomarkers for the diagnosis of systemic vasculitis and uses thereof

Abstract

The present application relates to the technical field of systemic vasculitis identification, in particular to a biomarker for systemic vasculitis diagnosis and application thereof, wherein the biomarker combination comprises the following serum markers: cold-inducible RNA binding protein, myeloid cell trigger receptor-1, Toll-like receptor 4. The biomarker provided by the present application is used for systemic vasculitis diagnosis, disease activity assessment, kidney damage risk early warning and treatment effect monitoring, so as to solve the technical problem of lack of specific and sensitive biomarkers in the prior art.

Description

Technical Field

[0001] This invention relates to the field of systemic vasculitis identification technology, and in particular to a biomarker for the diagnosis of systemic vasculitis and its application. Background Technology

[0002] Systemic vasculitis (SV) is a heterogeneous group of diseases characterized by inflammation and necrosis of the blood vessel walls, which can affect various organ systems throughout the body. Based on the size and type of affected vessels, this disease spectrum mainly includes ANCA-associated vasculitis (AAV) and Takayasu's arteritis (TAK). AAV, as a representative subtype of small vessel vasculitis, includes granulomatous polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatous polyangiitis (EGPA); TAK primarily affects the aorta and its major branches, and is more common in young women.

[0003] Although the overall incidence of AAV is low, its mortality and disability rates remain high. Epidemiological data show that the mortality risk of AAV patients is 2.6 times that of the general population, and the 5-year survival rate is only 78%. The core challenges currently facing this field are: the pathogenesis is not fully understood, and there is a lack of specific biomarkers that can accurately reflect disease activity, predict relapse risk, and guide individualized treatment. Existing indicators such as ANCA are valuable for differentiating subtypes of small vessel vasculitis, but approximately 10% of patients test negative for ANCA, and its level does not correlate entirely with disease activity; while there are still no specific blood laboratory indicators for Takayasu arteritis. Therefore, developing serum biomarkers with early diagnostic value and innovative treatment strategies is of great clinical significance for effectively reducing the mortality risk of this disease and optimizing long-term clinical outcomes for patients. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention aims to provide a biomarker for the diagnosis of systemic vasculitis and its application, thereby solving the technical problem of the lack of specific and sensitive biomarkers in existing technologies, effectively reducing the risk of death from the disease and optimizing long-term clinical outcomes for patients.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] According to a first aspect of the present invention, a combination of biomarkers for the diagnosis of systemic vasculitis is provided, comprising the following serum biomarkers:

[0007] Cold-induced RNA-binding protein (CIRP), myeloid trigger receptor-1 (TREM-1), and Toll-like receptor 4 (TLR4).

[0008] According to a second aspect of the invention, there is provided an application of a combination of biomarkers or a detection reagent thereof in the preparation of a product for diagnosing or assisting in the diagnosis of systemic vasculitis, wherein the detection reagent is used to detect the level of the combination of biomarkers in a sample to be tested.

[0009] According to an embodiment of the present invention, the systemic vasculitis is antineutrophil cytoplasmic antibody-associated vasculitis (AAV) or aortitis (TAK).

[0010] According to a third aspect of the present invention, a diagnostic kit for diagnosing or assisting in the diagnosis of systemic vasculitis is provided, the diagnostic kit comprising reagents for detecting the levels of a combination of biomarkers in a sample to be tested.

[0011] According to a fourth aspect of the invention, there is provided a combination of biomarkers or a detection reagent thereof for use in the preparation of a product for assessing the risk of kidney damage in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV), the detection reagent being used to detect the level of the combination of biomarkers in a sample to be tested.

[0012] According to a fifth aspect of the invention, a kit is provided for assessing the risk of kidney damage in patients with anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV), the kit comprising reagents for detecting the levels of a combination of biomarkers in a sample to be tested.

[0013] According to a sixth aspect of the present invention, there is provided an application of a combination of biomarkers or a detection reagent thereof in the preparation of a product for monitoring the treatment effect in patients with systemic vasculitis, wherein the detection reagent is used to detect the level of the combination of biomarkers in a sample to be tested.

[0014] According to a seventh aspect of the present invention, a kit for monitoring the treatment effect in patients with systemic vasculitis is provided, the kit comprising reagents for detecting the levels of a combination of biomarkers in a sample to be tested.

[0015] This invention systematically detected the expression levels of CIRP, TLR4, and TREM-1 in the serum of AAV and TAK patients in the same system. It found that all three were significantly higher than those in healthy controls, and there was a high positive correlation among the three, which clinically confirms the synergistic role of the "DAMP-PRR-amplifier axis" in the immunopathology of vasculitis.

[0016] This invention provides a highly sensitive and specific diagnostic biomarker for accurate assessment of disease activity: This invention found that serum CIRP, TLR4, and TREM-1 levels in patients with active AAV and TAK were significantly higher than those in patients in remission (p<0.05). Multivariate regression analysis confirmed that CIRP and TLR4 are independent risk factors for AAV disease activity, and TREM-1 is an independent risk factor for TAK disease activity. The thresholds provided by this invention (97.148 ng / L and 97.471 ng / L) can effectively distinguish between patients in the active and remission phases.

[0017] The biomarkers provided by this invention can be used for early warning of organ damage risk and monitoring of treatment response: Patients with atrial vasculitis (AAV) and renal impairment had significantly higher levels of CIRP, TLR4, and TREM-1 than those without renal impairment (p<0.01); multivariate regression analysis showed that all three were independent risk factors for renal damage in AAV. CIRP was positively correlated with 24-hour urinary protein quantification, and TLR4 was positively correlated with serum creatinine. In TAK, CIRP was significantly positively correlated with the number of affected vessels. This provides a basis for the use of this invention for early warning of organ damage. This invention confirms that serum CIRP, TLR4, and TREM-1 levels significantly decreased after treatment in AAV patients (p<0.05), suggesting that these three can serve as dynamic monitoring indicators for assessing treatment efficacy. Attached Figure Description

[0018] The present invention includes the following figures:

[0019] Figure 1 This is a flowchart illustrating the research groupings in Embodiment 1 of the present invention;

[0020] Figure 2 This is the CIRP standard concentration curve in Example 1 of the present invention;

[0021] Figure 3 This is the TREM-1 standard concentration curve in Example 1 of the present invention;

[0022] Figure 4 This is the TLR4 standard concentration curve in Example 1 of the present invention;

[0023] Figure 5 This is the experimental result comparing serum CIRP, TLR4, and TREM-1 levels between the healthy control group and the case group in Example 2 of this invention;

[0024] Figure 6 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in the disease activity group and the remission group of AAV patients in Example 2 of the present invention;

[0025] Figure 7This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in TAK patients in Example 2 of the present invention between the disease activity group and the remission group;

[0026] Figure 8 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in the infected and non-infected groups of patients with systemic vasculitis in Example 2 of the present invention.

[0027] Figure 9 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in the newly treated group and the previously treated group of patients with systemic vasculitis in Example 2 of the present invention.

[0028] Figure 10 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in AAV patients in Example 2 of this invention between the p-ANCA positive group and the c-ANCA positive group;

[0029] Figure 11 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in AAV patients with renal impairment and those without renal impairment in Example 2 of this invention;

[0030] Figure 12 This is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels before and after treatment in patients with systemic vasculitis in Example 2 of the present invention. Figure 12 (A) shows the experimental results comparing serum CIRP, TREM-1, and TLR4 levels in AAV patients before and after treatment in Example 2 of this invention. Figure 12 (B) is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in TAK patients before and after treatment in Example 2 of the present invention;

[0031] Figure 13 This is a heatmap showing the correlation between serum CIRP, TLR4, TREM-1 and laboratory indicators in the AAV group in Example 3 of the present invention.

[0032] Figure 14 This is a scatter plot showing the correlation between serum CIRP, TLR4, TREM-1 and laboratory indicators in the AAV group in Example 3 of the present invention.

[0033] Figure 15 This is a heatmap showing the correlation between serum CIRP, TLR4, TREM-1 and laboratory indicators in the TAK group in Example 3 of the present invention.

[0034] Figure 16 This is a scatter plot showing the correlation between serum CIRP, TLR4, TREM-1 and laboratory indicators in the TAK group in Example 3 of the present invention.

[0035] Figure 17 This is a scatter plot showing the correlation between serum CIRP, TLR4, TREM-1 and the number of affected organs in the AAV group in Example 3 of this invention.

[0036] Figure 18 This is a scatter plot showing the correlation between serum CIRP, TLR4, TREM-1 and the number of affected vessels in the TAK group in Example 3 of the present invention.

[0037] Figure 19 This is a heatmap showing the intrinsic correlation analysis between CIRP, TREM-1, and TLR4 in AAV and TAK patients in Example 3 of the present invention. Figure 19 (A) is a heatmap showing the intrinsic correlation analysis between CIRP, TREM-1, and TLR4 in TAK patients in Example 3 of this invention. Figure 19 (B) is a heatmap showing the intrinsic correlation analysis between CIRP, TREM-1, and TLR4 in AAV patients in Example 3 of the present invention;

[0038] Figure 20 This is a heatmap showing the correlation between serum CIRP, TLR4, TREM-1 and renal function indicators in the renal-affected subgroup of AAV patients in Example 3 of the present invention.

[0039] Figure 21 This is a scatter plot showing the correlation between serum CIRP, TLR4, TREM-1 and renal function indicators in the renal-affected subgroup of AAV patients in Example 3 of the present invention.

[0040] Figure 22 This is a comparative graph showing the distribution of different clinical outcomes of AAV patients in the high / low CIRP expression groups in Example 4 of the present invention;

[0041] Figure 23 This is a comparative graph showing the distribution of different clinical outcomes in TAK patients in the high / low CIRP expression groups in Example 4 of the present invention;

[0042] Figure 24 This is a graph showing the diagnostic predictive value of serum CIRP, TREM-1, and TLR4 expression levels for AAV in Example 5 of the present invention.

[0043] Figure 25 This is a graph showing the diagnostic predictive value of serum CIRP, TREM-1, and TLR4 expression levels for TAK in Example 5 of the present invention.

[0044] Figure 26 This is a graph showing the serum CIRP, TREM-1, and TLR4 levels in the SV2 group and the healthy control group in Example 6 of this invention.

[0045] Figure 27This is a graph showing the serum CIRP, TREM-1, and TLR4 levels in the TAK group, AAV group, and healthy control group in Example 6 of this invention.

[0046] Figure 28 This is a graph showing the diagnostic predictive value of serum CIRP, TREM-1, and TLR4 expression levels for SV in Example 6 of the present invention.

[0047] Figure 29 This is a comparison chart of serum CIRP, TREM-1, and TLR4 levels before and after treatment in patients with systemic vasculitis in Example 6 of the present invention. Figure 29 (A) shows the experimental results comparing serum CIRP, TREM-1, and TLR4 levels in AAV patients before and after treatment in Example 6 of this invention. Figure 29 (B) is the experimental result comparing serum CIRP, TREM-1, and TLR4 levels in TAK patients before and after treatment in Example 6 of the present invention;

[0048] Figure 30 This is a graph showing the levels of CIRBP, TREM-1, and TLR4 in the AAV group and the healthy control group in GSE108113 in Example 6 of the present invention.

[0049] Figure 31 This is a graph showing the TREM-1 and TLR4 levels in the AAV group and the healthy control group in GSE298999 in Example 6 of the present invention;

[0050] Figure 32 This is a graph showing the levels of CIRBP, TREM-1, and TLR4 in the TAK group of GSE33910 relative to the healthy control group in Example 6 of the present invention. Detailed Implementation

[0051] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings.

[0052] The following examples involve biological definitions and classifications:

[0053] Definition of infection: There is clear microbiological evidence (such as positive bacterial or fungal culture or positive viral PCR test); there are clinical symptoms, signs or imaging evidence consistent with the site of infection; and the clinician makes a decision on targeted anti-infective treatment based on this.

[0054] Definition of renal involvement: Kidney involvement is defined by one or more of the following criteria: 1) Proteinuria (>300 mg / day) and / or hematuria (>5 red blood cells / high-power field), with or without elevated serum creatinine levels; 2) Serum creatinine >120 μmol / L or estimated glomerular filtration rate (eGFR) <60 ml / min / 1.73 m³ / min. 2;3) Necrotizing glomerulonephritis with low levels of immune complexes on renal biopsy.

[0055] Definition of Organ System Involvement: This study used the number of organ systems involved as an indicator of the extent of disease. The definition was based on the Birmingham Vasculitis Activity Scale (BVAS, version 3) with its nine system categories (systemic symptoms, skin and mucous membranes, ear, nose and throat, chest, cardiovascular, abdomen, kidneys, nervous system, and others). If any active clinical manifestation within a system was deemed "new or worsening," that system was counted as "involved." Ultimately, the number of involved systems was the sum of all affected systems, ranging from 0 to 9.

[0056] Vascular complications are defined as: new vascular occlusion, stenosis progression or requiring revascularization, new or progressive aneurysm, new acute myocardial infarction, new stroke or transient ischemic attack.

[0057] Disease activity score and definition: The TAK disease activity assessment adopts the Kerr score standard developed by the National Institutes of Health (NIH), including: (1) systemic symptoms: general malaise, fever, fatigue, weight loss >2kg, etc.; (2) vascular ischemia symptoms and signs; (3) Elevated ESR (≥20mm / h); (4) positive results of vascular imaging such as MRA, CTA, PET-CT, etc.; each item is scored as 1 point, and a total score ≥2 points indicates TAK activity. The AAV disease activity assessment is based on the BVAS standard, which scores organ damage caused by vasculitis disease activity. The total score is 63 points, and a score ≥15 points indicates disease activity. Based on the BVAS level, it is divided into two groups: the active group (BVAS ≥15 points) and the inactive group (BVAS <15 points).

[0058] Aortitis can be classified into four types depending on the affected site: Brachiocephalic artery type (aortic arch syndrome): Head ischemia can cause headache, dizziness, memory loss, and even convulsions, hemiplegia, or coma. Subclavian artery involvement can cause unilateral or bilateral upper limb weakness, numbness, coldness, and even muscle atrophy; weakened or absent pulses in the carotid, brachial, and radial arteries; and a grade II or higher systolic vascular murmur can be heard in the neck or supraclavicular fossa. Aortic or renal artery type: Renal hypertension occurs, especially with a significant increase in diastolic blood pressure; weakness, coldness, soreness, and intermittent claudication occur in the lower limbs; and a vascular murmur can be heard above or to the side of the umbilicus. Extensive type: It has the characteristics of the above two types, but the lesions are widespread, multiple in location, and the condition is generally more severe. Pulmonary artery type: Symptoms of pulmonary hypertension include palpitations, shortness of breath, a systolic murmur in the pulmonary valve area, and an accentuated second pulmonary heart sound.

[0059] Example 1: Screening of biomarkers and construction of evaluation models

[0060] 1. Subject screening:

[0061] The subjects were 111 patients with systemic vasculitis who were hospitalized or treated as outpatients in the rheumatology and immunology department of a certain hospital. Figure 1 As shown, based on clinical diagnostic criteria, the patients were divided into 73 patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV) and 38 patients with large arteritis (TAK), including 12 patients who were able to undergo continuous dynamic assessment (7 AAV patients and 5 TAK patients).

[0062] Inclusion criteria:

[0063] (1) Patients diagnosed with AAV who meet the 2022 American College of Rheumatology (ACR) or 2012 Chapel Hill Conference classification criteria.

[0064] (2) Meets the TAK classification diagnostic criteria established by the ACR in 1990 or the TAK classification criteria jointly established by the American College of Rheumatology / European League Against Rheumatism (ACR / EULAR) in 2022.

[0065] Common symptoms in patients with TAK include dizziness and headache (63.2%), vascular symptoms (60.5%), neck / shoulder / back / lower back pain (42.1%), lower extremity ischemia symptoms (34.2%), and cerebral ischemia symptoms (21.1%). The incidence of vascular complications is 34.2%. Based on the type of affected vessels, the proportions of patients with type I, type II, and type III were 39.5%, 5.3%, and 55.3%, respectively. The proportion of patients with pulmonary hypertension was 21.05%, and the median number of affected vessels was 3.00. In AAV patients, pulmonary symptoms (69.9%) and comorbid interstitial lung disease (56.2%) were the most common. Other common symptoms included nasal symptoms (39.7%), ear symptoms (34.2%), arthritis / arthralgia (32.9%), and neurological symptoms (32.9%). Among systemic manifestations, fever accounted for 50.7% and weight loss for 24.7%. The incidence of kidney damage was 46.6%, the positive rate of p-ANCA was 58.9%, and the positive rate of c-ANCA was 20.5%.

[0066] In summary, the TAK group patients were relatively younger and predominantly female, with prominent ischemic vascular symptoms and relatively better inflammation and renal function indicators; the AAV group patients were older, with multi-system involvement, especially significant lung and kidney damage, and significantly elevated inflammation and coagulation activation indicators. The two groups of patients showed heterogeneity in clinical manifestations and laboratory indicators.

[0067] The healthy control group included 50 individuals who underwent health checkups at a hospital. There were 27 females (54%) and 23 males (46%), with an age range of 28-82 years and a mean age of (54.94±13.91) years. Statistical analysis showed no significant differences between the case group and the healthy control group in baseline characteristics such as gender distribution and age range. p >0.05), which meets the requirements for research comparability.

[0068] This protocol has passed the ethical review of the medical ethics committee of a certain hospital (No.: IRB2024-YX-643-01) before implementation. Table 1 shows the demographic and clinical characteristics of the subjects.

[0069] Table 1. Patient baseline characteristics

[0070]

[0071] 2. CIRP, TREM-1, and TLR4 assays in subjects

[0072] The main reagents include:

[0073] CIRPELISA Kit (Tianjin Meisheng Technology Co., Ltd., China)

[0074] TREM-1 ELISA Kit (Tianjin Meisheng Technology Co., Ltd., China)

[0075] TLR4 ELISA Kit (Tianjin Meisheng Technology Co., Ltd., China)

[0076] This embodiment strictly adheres to the standardized collection process: All subjects underwent 4 ml of antecubital venous blood collection via standard venipuncture technique in the morning on an empty stomach, and the samples were then placed in sterile vacuum blood collection tubes. After the blood samples were allowed to stand at room temperature for 60 minutes to promote coagulation, serum separation was performed using a low-speed centrifuge (centrifugation parameters set at 3000 rpm, room temperature for 5 minutes). The clarified serum layer was precisely aspirated using a micropipette, aliquoted into pre-frozen storage tubes, and immediately labeled with a unique code and collection time. Finally, the tubes were transferred to ultra-low temperature storage equipment (-80℃) for a single-use cryopreservation strategy. The entire process strictly followed biobank management guidelines to avoid the impact of repeated freeze-thaw cycles on protein stability. All subjects' antecubital venous blood samples were subjected to CIRP, TREM-1, and TLR4 tests, as detailed below:

[0077] (1) CIRP detection

[0078] Dilution of Standards: This kit provides one vial of original standard, which users can dilute in small test tubes according to the following chart 2;

[0079] Table 2 Dilution of Standards

[0080]

[0081] Sample addition: Set up blank wells (blank control wells do not contain sample or enzyme-labeled reagent, all other steps are the same), standard wells, and sample wells. Accurately add 50 μl of standard to the enzyme-labeled plate. Add 40 μl of sample diluent to the sample wells, then add 10 μl of the sample to be tested (final sample dilution is 5-fold). Add the sample to the bottom of the wells, avoiding contact with the well walls, and gently shake to mix.

[0082] Incubation: After sealing the plate with sealing film, incubate at 37°C for 30 minutes;

[0083] Solution preparation: Dilute the 30-fold concentrated washing solution with distilled water 30 times and set aside;

[0084] Washing: Carefully peel off the sealing film, discard the liquid, shake dry, fill each well with washing solution, let stand for 30 seconds and then discard, repeat this 5 times, then pat dry;

[0085] Add enzyme: Add 50 μl of enzyme-labeled reagent to each well, except for the blank wells;

[0086] After incubation and washing, develop the color: Add 50 μl of color developer A to each well, then add 50 μl of color developer B, gently shake to mix, and develop the color at 37°C in the dark for 10 minutes.

[0087] Termination: Add 50 μl of stop solution to each well to stop the reaction (the blue color will immediately turn yellow).

[0088] Measurement: Zero the instrument using the blank well, and measure the absorbance (OD value) of each well sequentially at a wavelength of 450 nm. Measurements should be performed within 15 minutes of adding the stop solution.

[0089] A CIRP standard concentration curve was plotted based on experimental data. Figure 2 The CIRP concentration (ng / L) of each well was calculated based on the concentration curve.

[0090] (2) TREM-1 detection: The ELISA detection method is the same as the CIRP detection method, and the results are as follows: Figure 3 As shown, Figure 3 This is a curve showing the standard concentration of TREM-1.

[0091] (3) TLR4 detection: The ELISA detection method is the same as the CIRP detection method, and the results are as follows: Figure 4 As shown, Figure 4 This is a curve showing the standard concentration of TLR4.

[0092] Example 2: Comparison of serum CIRP, TLR4, and TREM-1 levels between the healthy control group and the case group

[0093] 1. Comparison of serum CIRP, TLR4, and TREM-1 levels between the healthy control group and the case group

[0094] The Mann-Whitney U test was used to compare the case group and the healthy control group. The results showed that the serum CIRP, TLR4 and TREM-1 expression levels in patients with systemic vasculitis were higher than those in the healthy control group, and the differences were statistically significant. p <0.05).

[0095] The serum CIRP level in the case group (median 105.473 ng / L, 96.98 ± 131.31) was higher than that in the healthy control group [84.777 ± 9.914 ng / L, ( p <0.001); TLR4 expression was also significantly elevated in the case group [median 15.741 ng / ml, 13.97 ± 17.47 vs control group 13.817 ± 1.657 ng / ml, ( p <0.001); meanwhile, the TREM-1 level in the case group (median 256.661 ng / L, 212.87341.97) was higher than that in the control group [213.426 ± 34.732 ng / L, ( p <0.001), such as Figure 5 As shown.

[0096] 2. Comparison of serum CIRP, TREM-1, and TLR4 levels in different subgroups

[0097] (1) Comparison of serum CIRP, TREM-1, and TLR4 levels between the active disease group and the remission group

[0098] The Mann-Whitney U test was used to compare the serum CIRP, TLR4, and TREM-1 expression levels in patients with active and remission phases of disease. The results showed that in both AAV and TAK patients, the serum CIRP, TLR4, and TREM-1 expression levels were significantly higher in patients with active disease than in those with remission. p <0.05).

[0099] In the AAV group, the median serum CIRP level in patients with active disease was 135.88 ng / L (119.20-182.01), which was higher than that in patients with remission [97.52 ng / L (92.36-102.68)]. p <0.001); TLR4 also increased during the active phase [median 16.82 ng / ml (15.31-19.43) vs 14.57 ± 2.94 ng / ml during remission, ( p<0.001); meanwhile, the median TREM-1 level during the active phase was 294.71 ng / L (249.87-401.91), which was higher than that during the remission phase [229.06 ng / L (213.16-269.44)]. p <0.001), such as Figure 6 As shown.

[0100] In the TAK group, the median serum CIRP level in patients with active disease was 115.99 ng / L (107.62-129.43), which was higher than that in patients with remission [93.93±5.69 ng / L, ( p <0.01); The median TLR4 level during the active phase was 16.79 ng / ml (14.57-17.77), which was higher than that during the remission phase [14.02±2.19 ng / ml, ( p <0.05)]; The median TREM-1 level during the active phase was 300.20 ng / L (251.22-365.26), which was also higher than that during the remission phase [218.14±29.55 ng / L, ( p <0.01), such as Figure 7 As shown.

[0101] (2) Comparison of serum CIRP, TREM-1, and TLR4 levels between the infected and non-infected groups

[0102] The Mann-Whitney U test was used to compare the serum CIRP, TLR4, and TREM-1 expression levels between infected and non-infected patients. The results showed that in AAV, the serum CIRP, TLR4, and TREM-1 expression levels in the infected group were significantly higher than those in the non-infected group (p<0.05). In TAK, the serum CIRP and TREM-1 expression levels in the infected group were significantly higher than those in the non-infected group (p<0.05). p <0.05).

[0103] In the AAV group, the median CIRP level in infected patients was 143.78 μg / L (128.37-184.39), significantly higher than that in uninfected patients [98.58±8.20 μg / L, ( p <0.001), the median TLR4 level in the infected group was 16.62 ng / ml (14.88-19.74), which was also higher than that in the uninfected group [15.06±2.92 ng / ml, ( p <0.01)], while the median TREM-1 level in the infected group was 364.40 μg / L (256.66-410.50), which was higher than that in the uninfected group [230.54 μg / L (215.35-266.69)], ( p<0.001)], such as Figure 8 As shown.

[0104] In the TAK group, the median CIRP level in patients with infection was 133.17 μg / L (127.52-180.28), which was higher than that in uninfected patients [101.61±10.40 μg / L, ( p <0.01)], TREM-1 levels were elevated in the infected group [409.11±194.04 μg / L vs. median 224.91 μg / L (203.86-265.78)], ( p <0.01], the serum TLR4 level in the infected group was 20.34±7.62 ng / ml, which was not statistically significant compared with the non-infected group [median 15.22 ng / ml (12.44-16.79)]. p >0.05), such as Figure 8 As shown.

[0105] (3) Comparison of serum CIRP, TREM-1, and TLR4 levels between the newly treated and previously treated groups

[0106] The Mann-Whitney U test was used to compare serum inflammatory marker levels in newly diagnosed and non-newly diagnosed patients with AAV and TAK. In the AAV group, the median serum CIRP, TLR4, and TREM-1 levels in newly diagnosed patients were 114.54 μg / L, 16.32 ng / ml, and 274.33 μg / L, respectively, all slightly higher than those in the non-newly diagnosed group (104.83 μg / L, 15.51 ng / ml, and 245.79 μg / L, respectively), but the differences were not statistically significant. p >0.05. In the TAK group, there were no statistically significant differences in serum CIRP (106.44 μg / L vs. 103.43 μg / L), TLR4 (14.24 ng / ml vs. 15.58 ng / ml), and TREM-1 (238.70 μg / L vs. 246.10 μg / L) levels between newly diagnosed and non-newly diagnosed patients. p >0.05), such as Figure 9 As shown.

[0107] 3. Comparison of serum CIRP, TREM-1, and TLR4 levels among different subgroups of AAV patients

[0108] (1) Comparison of serum CIRP, TREM-1, and TLR4 levels between p-ANCA-positive and c-ANCA-positive groups in AAV patients

[0109] Serum CIRP, TLR4, and TREM-1 levels in c-ANCA-positive and p-ANCA-positive patients with AAV were compared using the Mann-Whitney U test. The median serum CIRP level in c-ANCA-positive patients was 120.18 μg / L (98.11-178.53), which was higher than that in the p-ANCA-positive group [104.18 μg / L (98.06-139.98)]. Serum TLR4 in the c-ANCA-positive group was 18.85±7.25 ng / ml, also higher than the median of 15.78 ng / ml (14.06-17.00) in the p-ANCA-positive group. Meanwhile, the average serum TREM-1 level in the c-ANCA-positive group was 350.05±145.02 μg / L, higher than the median of 253.63 μg / L (214.62-352.69) in the p-ANCA-positive group, but the differences were not statistically significant. p >0.05), such as Figure 10 As shown.

[0110] (2) Comparison of serum CIRP, TREM-1, and TLR4 levels in AAV patients with and without renal impairment.

[0111] The Mann-Whitney U test was used to compare serum inflammatory marker levels in AAV patients with and without renal involvement. Results showed that serum CIRP, TLR4, and TREM-1 expression levels were significantly higher in patients with renal involvement than in those without renal involvement, and the differences were statistically significant. p <0.05).

[0112] In AAV patients with renal involvement, the median serum CIRP level was 137.98 ng / L (106.76-184.24), which was higher than that in patients without renal involvement [101.08 ng / L (93.76-110.44)]. p <0.001]; The median TLR4 level in the group with renal involvement was 17.22 ng / mL (15.39-20.90), which was also higher than that in the group without renal involvement [14.93 ng / mL (13.97-16.33)]. p <0.001)]; meanwhile, the median serum TREM-1 level in the group with renal involvement was 342.52 ng / L (236.39-404.36), which was higher than that in the group without renal involvement [240.39 ng / L (211.99-271.89)], ( p <0.01), such as Figure 11 As shown.

[0113] 4. Comparison of CIRP, TLR4, and TREM-1 levels before and after treatment

[0114] To assess the impact of hormone and / or immunosuppressant therapy on CIRP, TLR4, and TREM-1 levels in patients with systemic vasculitis (AAV), serum samples were collected before and after treatment when the condition was stable. Wilcoxon signed-rank test was used to compare paired samples from 12 patients before and after treatment (T0 and T1). Results showed that serum CIRP, TLR4, and TREM-1 levels in AAV patients all exhibited a decreasing trend, and the differences were statistically significant. p <0.05, serum levels in TAK patients also decreased after treatment, but the differences between groups were not statistically significant. p >0.05), such as Figure 12 As shown.

[0115] The results of group-based comparisons of CIRP, TLR4, and TREM-1 levels showed that serum CIRP, TLR4, and TREM-1 levels were significantly elevated in patients with systemic vasculitis compared to the healthy control group. In AAV and TAK patients, CIRP, TLR4, and TREM-1 levels were significantly higher in patients in the active phase than in those in remission. In the co-infection group, CIRP, TLR4, and TREM-1 levels were significantly higher in AAV patients than in the non-infection group, while CIRP and TREM-1 levels were significantly higher in TAK patients than in the non-infection group; although TLR4 was elevated, the difference was not statistically significant. CIRP, TLR4, and TREM-1 levels were significantly higher in AAV patients with renal involvement than in those without renal involvement. There were no statistically significant differences in CIRP, TLR4, and TREM-1 levels between the treatment-naïve and previously treated groups, or between the p-ANCA-positive and c-ANCA-positive groups. This suggests that CIRP, TLR4, and TREM-1 may synergistically participate in the pathogenesis of systemic vasculitis as pro-inflammatory mediators, and their simultaneous elevation reflects the synergistic role of the DAMP-PRR-amplifier axis in the immunopathology of vasculitis. Their levels are closely related to disease activity and can serve as potential biomarkers for assessing disease activity. Infection can further activate this inflammatory axis, especially in AAV, suggesting that infection is an important factor exacerbating inflammation. In AAV, elevated levels of all three are closely related to kidney damage, suggesting that they may directly participate in the mechanism of kidney injury. The reason for this is that CIRP, as a classic stress response protein, can be induced and released extracellularly under stress conditions such as ischemia, hypoxia, or infection, becoming a pro-inflammatory factor. Patients with active vasculitis have more severe inflammatory responses and tissue damage, which may promote the large release of CIRP into the bloodstream; and eCIRP can further activate macrophages and neutrophils through the TLR4 and TREM-1 pathways, promoting the release of inflammatory factors, forming a positive feedback loop, and exacerbating disease progression. Infection can act as a strong stress factor, further activating CIRP-mediated inflammatory pathways. During infection, pathogen components (such as LPS) directly bind to TLR4, and infection also causes tissue damage that releases CIRP. The two work together to activate TLR4 and its downstream pathways, and the upregulation of TREM-1 expression further amplifies the inflammatory response.

[0116] This study found no statistically significant differences in CIRP, TLR4, and TREM-1 levels between the newly treated group and the previously treated group, or between the p-ANCA positive and c-ANCA positive groups. This may be because the expression levels of CIRP and its receptors mainly reflect the current inflammatory burden of the body, rather than the stage of disease or immunophenotyping. The release of eCIRP is mainly regulated by stress and inflammatory stimuli, and its level changes more directly reflect the degree of tissue damage and inflammatory activation. Therefore, under the same inflammatory state, the levels of CIRP and its receptors may show consistency regardless of the ANCA subtype.

[0117] The comparison of CIRP, TLR4, and TREM-1 levels before and after treatment showed that serum CIRP, TLR4, and TREM-1 levels significantly decreased in both AAV and TAK patients after treatment. This suggests that the decrease in these levels after immunosuppressive therapy reflects a reduction in inflammatory burden and a tendency for disease remission. The less significant decrease in TAK levels may be related to the smaller sample size, or it may reflect a slower inflammatory response to treatment in TAK or a longer time required to detect significant changes. The more significant response to AAV treatment may be related to the disease itself being more sensitive to immunosuppression. The reasons for this are that hormones inhibit the activity of transcription factors such as NF-κB, reducing the expression of inflammatory cytokine genes; immunosuppressants (cyclophosphamide, mycophenolate mofetil, etc.) inhibit lymphocyte proliferation and function, reducing immune cell activation and infiltration, thereby reducing CIRP release, TLR4 expression, and TREM-1 upregulation.

[0118] Example 3: Correlation Analysis

[0119] 1. Correlation between serum CIRP, TREM-1, TLR4 levels and laboratory test indicators in patients with systemic vasculitis

[0120] Spearman rank correlation analysis was used to explore the associations between CIRP, TLR4, TREM-1, and laboratory indicators and disease activity scores in AAV patients. The results showed that CIRP was significantly positively correlated with multiple disease activity indicators, with the strongest correlation to ESR (r=0.465). p <0.001), followed by the BVAS score (r=0.423, p =0.0002), CRP (r=0.395, p =0.0005), Scr (r=0.367, p =0.0014), 24-hour urine protein (r=0.354, p =0.0021) and WBC (r=0.345, p =0.0028). TLR4 also differs from ESR (r=0.342, p =0.003), Scr (r=0.321, p =0.0056), WBC (r=0.290, p =0.0128) and 24-hour urinary protein (r=0.271, p TREM-1 showed a significant positive correlation with 24-hour urinary protein (r=0.0202). Furthermore, TREM-1 was significantly positively correlated with 24-hour urinary protein (r=0.302). p =0.0094), ESR (r=0.292, p =0.0121), WBC (r=0.270, p=0.0208) and Scr (r=0.233, p =0.0473) also shows a positive correlation, such as Figure 13 , 14 As shown.

[0121] This study further analyzed the correlations between CIRP, TLR4, TREM-1, and laboratory indicators in TAK patients. The results showed that CIRP was significantly associated with several indicators: ESR (r=0.437, P=0.0061), neutrophil count (r=0.36, ...), and other indicators. p =0.0263) and CRP (r=0.321, p =0.0496). TLR4 was also positively correlated with inflammatory markers, including ESR (r=0.38, p =0.0186), neutrophil count (r=0.371, p =0.0219) and CRP (r=0.35, p =0.0313) showed a positive correlation; at the same time, it was positively correlated with red blood cell count (r=-0.445, p =0.0051), albumin (r=-0.369, p =0.0226), hemoglobin (r=-0.33, p =0.0432) and aspartate aminotransferase (r=-0.327, p TREM-1 showed a negative correlation with ESR (r=0.0454). Furthermore, TREM-1 also showed a positive correlation with ESR (r=0.344). p =0.0343), such as Figure 15 , 16 As shown.

[0122] 2. Correlation between CIRP, TLR4, TREM-1 and the number of systemic organs / vascular involvement

[0123] In patients with acute amyotrophic lateral sclerosis (AAV), this study further analyzed the correlation between inflammatory factors CIRP, TLR4, and TREM-1 and the number of systemic organs involved. Spearman correlation test results showed an association between CIRP and the number of organs involved (r=0.250). p =0.033), TREM-1 also showed a correlation (r=0.295, p =0.011), while the correlation between TLR4 and the number of organs involved did not reach statistical significance (r=0.207, p =0.079), and the data distribution trend shows that as the expression levels of CIRP and TREM-1 increase, the number of affected organs in patients gradually increases. Figure 17 As shown.

[0124] In TAK patients, this study further analyzed the correlation between inflammatory factors CIRP, TLR4, and TREM-1 and the number of vascular involvements. Spearman correlation test results showed a significant positive correlation between CIRP and the number of vascular involvements (r=0.545). p =0.0004), although TREM-1 showed a certain correlation trend with the number of affected blood vessels, it did not reach statistical significance (r=0.304, r=0.0004). p =0.064), while no significant correlation was found between TLR4 and the number of affected vessels (r=0.206, r=0.064). p =0.215), such as Figure 18 As shown.

[0125] 3. Correlation analysis among the three indicators

[0126] In AAV and TAK patients, the intrinsic correlations among CIRP, TREM-1, and TLR4 were further analyzed. As shown in the figures and statistical results, these three factors exhibited significant moderate-to-strong positive correlations with each other in both patient groups (all...). p <0.001).

[0127] In the AAV group, TREM-1 showed the strongest correlation with TLR4 (r=0.741). p <0.001), followed by CIRP and TREM-1 (r=0.580, p <0.001) and CIRP and TLR4 (r=0.508, p <0.001). The TAK group also showed a similar trend, with TREM-1 and TLR4 (r=0.732, p <0.001), CIRP and TREM-1 (r=0.708, p <0.001) and CIRP and TLR4 (r=0.539, p There was a highly significant correlation between values ​​<0.001, such as... Figure 19 As shown.

[0128] 4. Correlation between CIRP and renal function indicators in the renal involvement subgroup

[0129] In the subgroup of AAV patients with renal involvement, this study analyzed the correlations between CIRP, TLR4, and TREM-1 and various renal function indicators. Spearman correlation analysis showed that CIRP was significantly positively correlated with 24-hour urinary protein quantification (r=0.389). p =0.023), and also showed a positive correlation with Scr and eGFR, but did not reach statistical significance.p The values ​​were 0.052 and 0.051, respectively. TLR4 was significantly positively correlated with Scr (r=0.350, p =0.042). TREM-1 was significantly positively correlated with 24-hour urinary protein quantification (r=0.406, p =0.017). No significant correlation was found between the three inflammatory markers and hematuria and uric acid, such as... Figure 20 , 21 As shown.

[0130] Correlation analysis showed that in AAV patients, CIRP was significantly positively correlated with ESR, BVAS, CRP, Scr, 24-hour urinary protein, and WBC; TLR4 and TREM-1 were both positively correlated with ESR, Scr, WBC, and 24-hour urinary protein. In TAK patients, CIRP and TLR4 were both positively correlated with ESR, neutrophil count, and CRP; TLR4 was also negatively correlated with red blood cell count, albumin, and hemoglobin; TREM-1 was positively correlated with ESR. In AAV patients, CIRP and TREM-1 were significantly positively correlated with the number of organs involved; in TAK patients, CIRP was significantly positively correlated with the number of blood vessels involved, and TREM-1 showed a positive correlation trend. Correlation analysis among the three indicators showed that in both AAV and TAK, CIRP, TREM-1, and TLR4 were all significantly and moderately positively correlated. In the renal subgroup of AAV, CIRP and TREM-1 were significantly positively correlated with 24-hour urinary protein, and TLR4 was significantly positively correlated with serum creatinine (Scr). This suggests that CIRP and its receptors TLR4 and TREM-1 not only participate in the inflammatory response of systemic vasculitis, but their expression levels can also reflect the inflammatory burden and organ damage degree of the disease. In AAV, all three were correlated with BVAS scores, further supporting their association with disease activity. CIRP showed the strongest correlation with multiple indicators, suggesting that it may be the most crucial inflammatory marker in AAV. In TAK, all three are involved in the systemic inflammatory response of large vessel vasculitis. TLR4 was negatively correlated with erythrocytes and hemoglobin, suggesting that chronic inflammation leads to anemia by inhibiting EPO production or promoting iron metabolism disorders. CIRP and TREM-1 levels were positively correlated with the extent of organ / vascular involvement, reflecting the widespread association of these factors with the disease: the number of organs involved in AAV reflects the extent of multi-system small vessel vasculitis, and elevated CIRP and TREM-1 indicate a heavier inflammatory burden and involvement of more organs; CIRP in TAK was strongly correlated with the number of affected vessels, suggesting its key role in multi-vessel disease. The highly significant positive correlation among the three indicators suggests that CIRP, TLR4, and TREM-1 have a synergistic expression or mutual regulatory relationship in vasculitis. In the subgroup of AAV with kidney involvement, CIRP and TREM-1 were mainly associated with proteinuria, while TLR4 was associated with serum creatinine, suggesting that the three may participate in kidney injury through different mechanisms: TREM-1 is an activation receptor expressed on the surface of neutrophils and monocytes, and its cross-linking can induce phagocytosis, respiratory burst, and degranulation, which are the core mechanisms of vascular wall necrosis and inflammation in AAV. TLR4 was significantly elevated in glomerular endothelial cells and renal tubular interstitium, suggesting that TLR4 may participate in the initiation of glomerular injury in AAV through local endothelial cell activation.

[0131] Example 4: Distribution ratio of different clinical subgroups in high and low CIRP expression groups

[0132] (1) AAV group

[0133] To explore the relationship between CIRP expression levels and clinical characteristics of AAV patients, this study divided 73 patients into a low CIRP group (n=35) and a high CIRP group (n=38) based on the median CIRP level (105.47 [98.59-138.93]), and compared the differences between the two groups in terms of disease activity, infection, and renal involvement.

[0134] The results showed that the proportion of disease activity in the high CIRP group was significantly higher than that in the low CIRP group (86.8% vs 20.0%), and the difference was highly statistically significant (χ²). 2 =30.219, p <0.001. Regarding the incidence of infection, the high CIRP group also had a significantly higher rate (84.2% vs 2.9%), and the difference between the groups was also extremely significant (χ²). 2 =45.451, p <0.001. Furthermore, the proportion of renal involvement in the high CIRP group was significantly higher than that in the low CIRP group (65.8% vs 25.7%), with a statistically significant difference (χ²). 2 =10.204, p =0.0014), such as Figure 22 As shown.

[0135] (2) TAK group

[0136] In TAK patients, this study further explored the relationship between CIRP expression levels and disease activity and infection risk. Thirty-eight patients were divided into a low CIRP group (n=19) and a high CIRP group (n=19) based on the median CIRP level (104.29 [95.69-117.49]).

[0137] The results showed that the proportion of patients with active disease in the high CIRP group was significantly higher than that in the low CIRP group (100% vs 10.5%), and the difference between the groups was highly statistically significant (χ²). 2 =27.249, p <0.001. Regarding the incidence of infection, the high CIRP group was also significantly higher than the low CIRP group (42.1% vs 5.3%), and Fisher's exact test showed a statistically significant difference. p =0.0188), such as Figure 23 As shown.

[0138] The distribution of different clinical subgroups within the high / low CIRP expression groups showed that, in both AAV and TAK patients, the high CIRP expression group exhibited a more severe clinical phenotype. In the AAV group, the proportion of disease activity, infection rate, and renal involvement were significantly higher in the high CIRP group than in the low CIRP group; similarly, in the TAK group, the proportion of disease activity and infection rate were significantly higher in the high CIRP group than in the low CIRP group, with statistically significant differences. This suggests that high CIRP expression is closely related to increased disease activity, increased infection risk, and organ damage (especially renal involvement) in patients with systemic vasculitis, and elevated CIRP levels may be an important biological marker reflecting disease severity and poor prognosis. The infection rate was as high as 84.2% in the high CIRP group of AAV and 100% in TAK, further suggesting that CIRP may increase susceptibility to infection and exacerbate disease activity by promoting excessive inflammatory responses, leading to immune resource depletion or tissue barrier disruption. The reasons for this are as follows: CIRP, as a pro-inflammatory mediator, promotes neutrophil activation and NETs through the TLR4 / p38 signaling pathway, leading to vascular endothelial damage and immune complex deposition, thus disrupting endothelial barrier function. Simultaneously, excessive inflammatory responses deplete immune cell reserves, weakening the body's anti-infection ability and increasing the risk of infection. Regarding kidney damage, CIRP can directly activate inflammatory cells within the glomeruli. Studies have confirmed that eCIRP can induce acute kidney injury through interaction with TREM-1 and promote pan-apoptosis of renal tubular epithelial cells, leading to proteinuria and decreased renal function. In TAK (transmitted keratitis), CIRP is highly expressed in the vascular wall during the active phase, activating TLR4 on smooth muscle and endothelial cells, exacerbating vascular inflammation and stenosis, and disrupting the vascular barrier through excessive inflammation, increasing the chance of pathogen invasion.

[0139] Example 5: Analysis of Disease Risk Factors and Diagnostic Value

[0140] (1) Analysis of independent risk factors for AAV and TAK disease activity

[0141] Clinical data and inflammatory markers from the two groups were compared between groups. Univariate analysis was performed, and variables with statistically significant differences were included in LASSO regression to screen candidate variables. The optimal penalty parameter λ was determined through 10-fold cross-validation. Finally, five variables with non-zero coefficients were selected from 11 candidate variables: WBC, ALB, CIRP, TLR4, and whether there was concurrent renal damage. These variables were included in a multivariate logistic regression model to further analyze the independent influencing factors of disease activity in AAV patients. The results showed (Table 3): Elevated WBC (OR=2.104, 95%CI: 1.086–4.075), p =0.027), CIRP increased (OR=1.396, 95%CI: 1.094~1.781,p =0.007), TLR4 increased (OR=2.393, 95%CI: 1.042~5.494, p =0.040) and the presence of kidney involvement (OR=1.669, 95%CI: 1.055–2.640, ). p =0.029) was an independent risk factor for disease activity in AAV patients; while elevated ALB (OR=0.711, 95%CI: 0.508–0.994, p =0.046) was an independent protective factor against AAV disease activity. The model fit test results showed that the Hosmer-Lemeshow χ² test... 2 =5.858, df=8, p =0.663, indicating a good model fit.

[0142] Table 3 Multivariate Logistic Regression Analysis of Disease Activity in AAV Patients

[0143]

[0144] Similarly, the TAK group was analyzed, and four non-zero coefficient variables were selected from seven candidate variables: age, hematuria, TREM-1, and the number of affected vessels. These variables were then included in a multivariate logistic regression model to further analyze the independent influencing factors of disease activity in TAK patients. The results showed (Table 4): increased age (OR=1.227, 95%CI: 1.005–1.498), p =0.045), and TREM-1 levels increased (OR=1.071, 95%CI: 1.001–1.145). p =0.045) and affected vessels (OR=1.765, 95%CI: 1.068–2.915, p =0.027) was an independent risk factor for disease activity in TAK patients. The model fit test results showed that the Hosmer-Lemeshow χ² test... 2 =2.820, df=8, p =0.945, indicating that the model fits well.

[0145] Table 4. Multivariate Logistic Regression Analysis of Disease Activity in TAK Patients

[0146]

[0147] (2) Analysis of independent risk factors for kidney involvement in AAV

[0148] Further analysis of independent influencing factors of renal impairment in AAV patients revealed 8 non-zero coefficient variables from 11 candidate variables: EOS, eGFR, ESR, CIRP, TLR4, TREM-1, number of systemic organ involvements (organ_involvement_count), and presence of infection. These variables were incorporated into a multivariate logistic regression model. The results showed (Table 5): elevated eGFR (OR=0.982, 95%CI: 0.969–0.996), p =0.01) was an independent protective factor against renal impairment in AAV patients; while elevated CIRP (OR=1.318, 95%CI: 1.050–1.654, p =0.017), TLR4 increased (OR=2.753, 95%CI: 1.203~6.301, p =0.017), TREM-1 increased (OR=1.48, 95%CI: 1.805~2.018), p =0.013) and an increased number of affected organs (OR=1.374, 95%CI: 1.067–1.769, ). p =0.014) was an independent risk factor for renal impairment in AAV patients. Eosinophil count, erythrocyte sedimentation rate, and infection did not reach statistical significance in multivariate analysis ( p >0.05). The model fit test results show that the Hosmer-Lemeshow test χ² value is greater than 0.05. 2 =4.646, df=8, p =0.795, indicating that the model fits well.

[0149] Table 5 Multivariate Logistic Regression Analysis of AAV Patients with Renal Injury

[0150]

[0151] (3) ROC and AUC analysis of the combined index (CIRP+TLR4+TREM-1)

[0152] To evaluate the diagnostic value of serum CIRP, TLR4, TREM-1, and the combined detection of these three markers for AAV and TAK, this study used a healthy control group as a reference to plot receiver operating characteristic (ROC) curves, and calculated the area under the curve (AUC), sensitivity, specificity, and Youden index. The results are as follows.

[0153] In the AAV group, CIRP had an AUC of 0.924 (95% CI: 0.880–0.968), with an optimal cutoff of 97.148. At this cutoff, the sensitivity for diagnosing AAV was 78.1%, the specificity was 96.0%, and the Youden index was 1.741. TLR4 had an AUC of 0.760 (95% CI: 0.675–0.845), a cutoff of 15.418, a sensitivity of 57.5%, a specificity of 92.0%, and a Youden index of 1.495. TREM-1 had an AUC of 0.750 (95% CI: 0.666–0.834), a cutoff of 251.712, a sensitivity of 57.5%, a specificity of 88.0%, and a Youden index of 1.455. The combined detection of the three markers showed an AUC of 0.927 (95% CI: 0.883–0.971), a cutoff value of 0.662, a sensitivity of 79.5%, a specificity of 96.0%, and a Youden index of 1.755. The diagnostic efficacy of the combined model was superior to any single marker, as shown in Table 6. Figure 24 As shown.

[0154] Table 6. Predictive value of serum CIRP, TREM-1, and TLR4 expression levels for AAV diagnosis.

[0155]

[0156] In the TAK group, the AUC of CIRP was 0.901 (95% CI: 0.840–0.962), with an optimal cutoff of 97.471, a diagnostic sensitivity of 68.4%, a specificity of 96.0%, and a Youden index of 1.644. The AUC of TLR4 was 0.675 (95% CI: 0.550–0.800), with a cutoff of 15.342, a sensitivity of 50.0%, a specificity of 90.0%, and a Youden index of 1.400. The AUC of TREM-1 was 0.684 (95% CI: 0.567–0.801), with a cutoff of 250.806, a sensitivity of 50.0%, a specificity of 88.0%, and a Youden index of 1.380. The combined detection of the three methods showed an AUC of 0.919 (95% CI: 0.864–0.974), a cutoff value of 0.475, a sensitivity of 84.2%, a specificity of 86.0%, and a Youden index of 1.702. The combined model also demonstrated the highest diagnostic accuracy, as shown in Table 7. Figure 25 As shown.

[0157] Table 7. Predictive value of serum CIRP, TREM-1, and TLR4 expression levels for TAK diagnosis.

[0158]

[0159] Multivariate logistic regression analysis showed that in AAV, CIRP (OR=1.396), TLR4 (OR=2.393), elevated WBC, and renal involvement were independent risk factors for disease activity, while elevated ALB (OR=0.711) was a protective factor. In TAK, TREM-1 (OR=1.071), increased age (OR=1.765), and the number of affected vessels (OR=1.765) were independent risk factors. For renal damage in AAV, CIRP (OR=1.318), TLR4 (OR=2.753), TREM-1 (OR=1.48), and the number of affected organs were all independent risk factors, while elevated eGFR (OR=0.982) was a protective factor. This suggests that the CIRP / TLR4 / TREM-1 axis plays a central role in vasculitis activity and organ damage. Elevated levels can independently predict disease activity and the risk of kidney damage, and its role may vary in different types of vasculitis: CIRP and TLR4 are more prominent in AAV, while TREM-1 is particularly crucial in TAK. ROC analysis further confirmed this, showing that in the diagnostic analysis of AAV and TAK, the AUC of CIRP alone was 0.924 and 0.901, with sensitivities of 78.1% and 68.4%, and specificities of 96.0% for both. When combined with TLR4 and TREM-1, the AUC increased to 0.927 and 0.919, with sensitivities of 79.5% and 84.2%, and specificities of 96.0% and 86.0%, respectively, significantly improving the sensitivity of TAK. CIRP, as a DAMP, is released early in tissue damage and has strong specificity for vasculitis; TLR4 and TREM-1 reflect the initiation and amplification of inflammation, respectively. Combined detection can cover different stages of the inflammatory pathway and improve the accuracy of early diagnosis. Therefore, this combined strategy may be used as an auxiliary screening indicator for systemic vasculitis.

[0160] Example 6: Validation of the diagnostic value of serum CIRP, TREM-1, and TLR4 expression levels for SV

[0161] 1. Subject screening:

[0162] This study included 56 patients with systemic vasculitis who were hospitalized or treated as outpatients in the Department of Rheumatology and Immunology of a certain hospital from May 2025 to January 2026. These patients were designated as group SV2 and, based on clinical diagnostic criteria, were further divided into 37 patients with anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) and 19 patients with large vessel vasculitis (TAK). The inclusion criteria were the same as in Example 1.

[0163] 2. The main reagents and experimental methods are the same as in Example 1.

[0164] 3. Experimental Results

[0165] This invention systematically collects clinical data and laboratory test results from patients with SV (Stomach Vulnerability), specifically covering medical records, ALT, AST, LDH, CK, CKMB, ESR, CRP, etc. Rheumatologists performed standardized physical assessments on enrolled patients, focusing on the presence of characteristic skin rashes, including sunspots, Gottron's sign, V-sign, and shawl sign. All laboratory test results were obtained from our hospital's laboratory and rheumatology / immunology department.

[0166] (1) The expression levels of serum CIRP, TREM-1, and TLR4 in the SV2 group and the healthy control group were determined using the same experimental methods as in Example 2. The results are shown in Table 8. Figure 26 As shown.

[0167] Table 8. Serum CIRP, TREM-1, and TLR4 expression levels in the SV2 group and the healthy control group.

[0168]

[0169] Note: *: p<0.05; **: p<0.01; ***: p<0.001; ****: p<0.0001

[0170] (2) Comparison of serum CIRP, TREM-1, and TLR4 levels between each subgroup of the SV2 group and the healthy control group. The experimental method was the same as in Example 2, and the results are shown in Table 9. Figure 27 As shown.

[0171] Table 9. Serum CIRP, TREM-1, and TLR4 levels in the TAK group, AAV group, and healthy control group.

[0172]

[0173] Note: *: p<0.05; **: p<0.01; ***: p<0.001; ****: p<0.0001; a indicates comparison with the control group, p<0.05; b indicates comparison with TAK, p<0.05

[0174] (3) The diagnostic predictive value of serum CIRP, TREM-1, and TLR4 expression levels for SV was determined using the same experimental methods as in Example 5, and the results are shown in Table 10. Figure 28 As shown.

[0175] Table 10. Predictive value of serum CIRP, TREM-1, and TLR4 expression levels for SV diagnosis.

[0176]

[0177] The results show that CIRP, TREM-1, and TLR4 are all highly expressed in the serum of SV patients, and may be involved in the pathogenesis of the disease.

[0178] (4) Comparison of CIRP, TLR4, and TREM-1 levels before and after treatment

[0179] To assess the impact of treatment on CIRP, TLR4, and TREM-1 levels in patients with systemic vasculitis (AAV), serum samples were collected before and after treatment when the condition was stable. Wilcoxon signed-rank test was used to compare paired samples from 12 patients before and after treatment (T0 and T1). Results showed that serum CIRP, TLR4, and TREM-1 levels in AAV patients all showed a decreasing trend, with statistically significant differences (p<0.05). Serum levels in TAK patients also decreased after treatment, but the differences between groups were not statistically significant (p>0.05). Figure 29 As shown.

[0180] (5) Compare the experimental results with those in the publicly available database.

[0181] In GSE108113, elevated levels of CIRBP, TREM-1, and TLR4 were found in AAV patients. Figure 30 );

[0182] In GSE298999, significantly elevated TREM-1 and TLR4 levels were found in AAV patients. Figure 31 );

[0183] In GSE33910, elevated levels of CIRBP, TREM-1, and TLR4 were found in TAK patients. Figure 32 ).

[0184] Data comparison and verification have shown that SV patients have higher levels of CIRP, TREM-1, and TLR4 compared to healthy controls, and these levels decrease after treatment. This has also been confirmed in publicly available databases, providing preliminary evidence that these levels are involved in the pathogenesis of SV. Furthermore, serum CIRP, TREM-1, and TLR4 have certain diagnostic predictive value in SV.

[0185] The above embodiments are only used to illustrate the present invention and are not intended to limit the present invention. Those skilled in the art can make various changes and modifications without departing from the essence and scope of the present invention. Therefore, all equivalent technical solutions also fall within the protection scope of the present invention.

[0186] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

Claims

1. The application of a combination of biomarkers or their detection reagents in the preparation of products for the diagnosis or auxiliary diagnosis of Takayasu arteritis, characterized in that, The biomarker combination includes the following serum biomarkers: cold-inducible RNA-binding protein, myeloid trigger receptor-1, and Toll-like receptor 4. The detection reagent is used to detect the level of the biomarker combination in the sample to be tested.

2. The use of a combination of biomarkers or their detection reagents in the preparation of products for monitoring the treatment efficacy in patients with Takayasu arteritis, characterized in that, The biomarker combination includes the following serum biomarkers: cold-inducible RNA-binding protein, myeloid trigger receptor-1, and Toll-like receptor 4. The detection reagent is used to detect the level of the biomarker combination in the sample to be tested.

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