A biomarker combination for predicting or diagnosing primary sjogren's syndrome and use thereof

Abstract

The present application relates to a biomarker combination for predicting or diagnosing primary Sjogren's syndrome and application thereof, wherein the biomarker combination for predicting or diagnosing primary Sjogren's syndrome comprises CFB, CLU and NE. The biomarker combination can predict the risk of suffering from primary Sjogren's syndrome under non-invasive conditions, and the prediction accuracy is high.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology and relates to a combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome and their applications. Background Technology

[0002] Primary Sjögren's syndrome (pSS) is a systemic chronic autoimmune disease characterized by lymphocytic infiltration and autoimmune damage to the salivary and lacrimal glands, leading to dry mouth and eyes. Currently, the predictive or diagnostic criteria for pSS are typically based on clinical symptoms of dryness, serological autoantibodies, and histopathological examination of the labial gland tissue. In the most widely used 2016 ACR / EULAR criteria, anti-SSA autoantibodies and labial gland biopsy have higher weightings; a positive finding in saliva biopsy or a positive anti-SSA serological test is essential for predicting or diagnosing pSS. Although the labial gland biopsy procedure is relatively simple, it is an invasive method that can lead to complications such as bleeding, pain, and temporary sensory loss, and even tissue necrosis and persistent sensory impairment. Furthermore, as a chronic disease, pSS currently lacks indicators for disease monitoring. As an invasive procedure, labial gland biopsy is not suitable for long-term disease monitoring or assessing the effectiveness of medication.

[0003] Lip gland biopsies can lead to complications such as bleeding, pain, and temporary sensory loss, and even tissue necrosis and persistent sensory impairment. In recent years, saliva has attracted attention as a biosample for predictive or diagnostic testing due to its simple, convenient, painless, and safe collection. Current research reports the use of mass spectrometry to explore biomarkers of pSS in saliva; however, mass spectrometry is costly, requires large-scale equipment, and is not easily implemented or validated on a large scale. The application value of salivary proteins in predicting or diagnosing pSS remains unclear. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this invention is to provide a combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome and their applications.

[0005] To achieve this objective, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome, the combination of biomarkers including CFB, CLU and NE.

[0007] The expression levels of complement factor B (CFB), lectin (CLU), and neutrophil elastase (NE) are elevated in the saliva of patients with primary Sjögren's syndrome (pSS), and can serve as biomarkers for predicting or diagnosing primary Sjögren's syndrome.

[0008] In a second aspect, the present invention provides the use of the combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome according to the first aspect, or a reagent for detecting the expression level of the combination of biomarkers according to the first aspect, in the preparation of products for predicting or diagnosing primary Sjögren's syndrome.

[0009] Preferably, the application includes constructing a predictive or diagnostic model for primary Sjögren's syndrome and / or preparing a predictive or diagnostic device for primary Sjögren's syndrome.

[0010] Thirdly, the present invention provides a kit for predicting or diagnosing primary Sjögren's syndrome, the kit comprising reagents for detecting the expression levels of the combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome as described in the first aspect.

[0011] Preferably, the kit further includes reagents for detecting tear secretion, reagents for detecting SSA antibodies, and reagents for detecting Ro52 antibodies.

[0012] The combination of three markers in saliva (CFB, CLU, NE), along with existing non-invasive clinical tests (anti-SSA, anti-Ro52, and Schirmer test), has high accuracy in predicting or diagnosing pSS, and can avoid complications such as bleeding, pain, and temporary sensory loss caused by invasive labial gland biopsy.

[0013] Fourthly, the present invention provides a predictive or diagnostic model for primary Sjögren's syndrome, wherein the input variables of the predictive or diagnostic model for primary Sjögren's syndrome include the detection results of the combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome as described in the first aspect, the results of the tear secretion test, the detection results of SSA antibody, and the detection results of Ro52 antibody.

[0014] Preferably, the output variable of the primary Sjögren's syndrome prediction or diagnostic model includes a prediction probability, and the prediction probability is calculated using the following formula:

[0015] Predicted probability = -4.511 + 1.369 × CFB test result + 2.441 × CLU test result + 1.237 × NE test result + 1.194 × tear secretion test result + 0.709 × SSA antibody test result + 0.481 × Ro52 antibody test result.

[0016] Preferably, if the CFB concentration is higher than 173.50 ng / mL, the CFB detection result is recorded as 1; otherwise, the detection result is recorded as 0.

[0017] If the CLU concentration is higher than 221.40 ng / mL, the CLU detection result is recorded as 1; otherwise, the detection result is recorded as 0.

[0018] If the NE concentration is higher than 0 ng / mL, the NE detection result is recorded as 1; otherwise, the detection result is recorded as 0.

[0019] If the tear secretion test shows that less than 5 mm of tear fluid wets the filter paper in either eye within 5 minutes, the result is recorded as 1; otherwise, the result is recorded as 0.

[0020] SSA antibody test results are selected from 0, 1, 2, and 3;

[0021] Ro52 antibody test results are selected from 0, 1, 2, and 3.

[0022] The anti-SSA antibody results are selected from the clinical antinuclear extract antibody test report. The test results are recorded according to the number of "+" signs: "+" test results are recorded as 1, "++" test results are recorded as 2, "++++" test results are recorded as 3, and negative "-" test results are recorded as 0.

[0023] The results of the anti-Ro52 antibody test are selected from the clinical antinuclear extract antibody test report. The test results are recorded according to the number of "+" signs: "+" test results are recorded as 1, "++" test results are recorded as 2, "++++" test results are recorded as 3, and negative "-" test results are recorded as 0.

[0024] Preferably, the criterion for a positive result for primary Sjögren's syndrome is a predicted probability ≥ 0.6881, such as 0.6881, 0.7, 0.75, 0.8, 0.85, 0.9, etc. Other specific values ​​within the above range can be selected, and will not be elaborated here.

[0025] Fifthly, the present invention provides a device for predicting or diagnosing primary Sjögren's syndrome, the device comprising a detection unit and an analysis unit;

[0026] The detection unit is used to perform the following: detecting the expression levels of a combination of biomarkers used to predict or diagnose primary Sjögren's syndrome, tear secretion, SSA antibody, and Ro52 antibody in the sample of the individual to be tested;

[0027] The analysis unit is used to perform the following:

[0028] The results of biomarker detection, tear secretion test, SSA antibody detection, and Ro52 antibody detection used to predict or diagnose primary Sjögren's syndrome are input into the primary Sjögren's syndrome prediction or diagnosis model described in the fourth aspect for data analysis, outputting the prediction probability, and determining whether it is positive for primary Sjögren's syndrome.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] Elevated expression levels of complement factor B (CFB), lectin (CLU), and neutrophil elastase (NE) in the saliva of patients with primary Sjögren's syndrome (pSS) can serve as biomarkers for predicting or diagnosing pSS. The combination of these three salivary markers (CFB, CLU, and NE), along with existing non-invasive clinical tests (anti-SSA, anti-Ro52, and Schirmer tests), demonstrates high accuracy in predicting or diagnosing pSS, avoiding complications such as bleeding, pain, and temporary sensory loss associated with invasive labial gland biopsy. Attached Figure Description

[0031] Figure 1 These are the results of ELISA detection of CFB, CLU, and NE concentrations in the saliva of pSS and non-pSS patients. Figure A shows the results of CFB concentration detection in the saliva of pSS and non-pSS patients, Figure B shows the results of CLU concentration detection in the saliva of pSS and non-pSS patients, and Figure C shows the results of NE concentration detection in the saliva of pSS and non-pSS patients.

[0032] Figure 2 The ROC curve analysis of CFB, CLU, and NE in saliva distinguishing between pSS and non-pSS is shown in Figure A, Figure B, and Figure C.

[0033] Figure 3 The figures show the concentrations of CFB, CLU, and NE in the saliva of newly diagnosed pSS patients and pSS patients after medication, as measured by ELISA. Figure A shows the CFB concentration in the saliva of newly diagnosed pSS patients and pSS patients after medication, Figure B shows the CLU concentration in the saliva of newly diagnosed pSS patients and pSS patients after medication, and Figure C shows the NE concentration in the saliva of newly diagnosed pSS patients and pSS patients after medication, as measured by ELISA.

[0034] Figure 4 The ROC curve analysis distinguishes pSS from non-pSS using a model combining CFB, CLU, NE, anti-SSA, anti-Ro52, and Schirmer's test.

[0035] Figure 5 This is a validation cohort model that uses a combination of CFB, CLU, NE, anti-SSA, anti-Ro52, and Schirmer's test to distinguish between pSS and non-pSS using ROC curve analysis. Detailed Implementation

[0036] The technical solution of the present invention will be further illustrated below through specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the present invention and should not be construed as limiting the invention.

[0037] The CFB ELISA kit was purchased from Novus Biotech (Beijing) Co., Ltd., catalog number NBP2-60564.

[0038] The CLU ELISA kit was purchased from R&D Andy Biotech Co., Ltd., catalog number DCLU00;

[0039] The NE ELISA kit was purchased from R&D Andy Biotech Co., Ltd., catalog number DY9167-05.

[0040] Example 1

[0041] Saliva mass spectrometry screening

[0042] Proteins were analyzed by mass spectrometry from saliva samples of patients with and without pSS (n=6). Compared with the non-pSS group, we found 261 upregulated proteins and 198 downregulated proteins in the pSS group. Based on previous literature and our preliminary experimental results, three proteins, CFB, CLU, and NE, were selected for further experiments.

[0043] Example 2

[0044] ELISA was used to detect the levels of CFB, CLU, and NE in the saliva of the two groups.

[0045] CFB, CLU, and NE were detected in saliva samples from patients with non-pSS (n=65) and pSS (n=121) using ELISA.

[0046] Detection method:

[0047] 1. Sample collection

[0048] Saliva samples are typically collected at 8 PM or 2 hours after a meal, and patients must refrain from brushing their teeth, smoking, or eating to ensure that saliva flow is not stimulated and that the collection is conducted without any chewing or taste stimulation. Patients should be instructed to sit relaxed with their elbows resting on their knees and their head slightly tilted forward between their arms, allowing saliva to passively drain from the lower lip into a sterile sputum cup. Any movement of the tongue, cheeks, chin, or lips that could stimulate saliva production should be avoided.

[0049] 2. Sample processing

[0050] Static saliva was collected for further processing and experiments. First, the saliva was centrifuged at 9500g and 4℃ for 10 minutes to precipitate impurities. Then, the supernatant was collected, and 5μL of protease inhibitor was added per 100μL of volume before freezing and storing at -80℃.

[0051] 3. Detection of NE concentration in saliva

[0052] (1) Find the required reagents in advance and let them warm to room temperature;

[0053] (2) Dilute the NE-coated antibody to the working concentration with ELISA Coating Buffer;

[0054] (3) Plate coating: Add 100 μL of coating antibody dilution to each well of the ELISA plate, immediately cover the plate with a transparent sealing film, and place it on a shaker at 4°C and shake slowly overnight.

[0055] (4) Washing: The next day, take the microplate out of the shaker at 4°C, discard the coating solution in the wells, and wash the plate with a plate washer: add 400 μL PBST to each well, shake for 3 seconds and then aspirate the liquid in the wells; repeat this washing step 3 times, and take it out of the plate washer for the last time and pat it completely dry on a flat, clean absorbent paper.

[0056] (5) Sealing: Add 300 μL of Reagent Diluent to each well for sealing, carefully cover with sealing film, and then place on a shaker for slow and uniform incubation at room temperature for at least 1 hour;

[0057] (6) Repeat step 4 to wash the plate and pat it dry, then wait for the sample to be added;

[0058] (7) Diluting the saliva sample: Take the patient's saliva from the -80℃ freezer and thaw it slowly on ice. After the saliva has completely thawed, centrifuge at 9500g at 4℃ for 10 minutes. Take an appropriate amount of the supernatant saliva and dilute it at a ratio of 1:500.

[0059] (8) Sample addition: Add 100 μL of diluted saliva sample and standard to each well. Mark the order and position of the samples. Avoid air bubbles during sample addition and ensure the pipette tip does not touch the bottom of the plate. Cover with sealing film and incubate on a shaker at low speed at room temperature for 2 hours.

[0060] (9) Repeat the washing process in step 4 and pat dry;

[0061] (10) Add primary antibody: Dilute the detection antibody to one concentration with Reagent Diluent, add 100 μL of the diluted detection antibody to each well, cover with sealing film and incubate on a shaker at low speed at room temperature for 2 h.

[0062] (11) Repeat step 4 to wash the plate and pat it dry;

[0063] (12) Add secondary antibody: Add 100 μL of horseradish peroxidase (HRP) labeled secondary antibody to each well, carefully cover with sealing film, and incubate at low speed on a shaker at room temperature for 20 min, while avoiding light;

[0064] (13) Repeat the washing process in step 4 and pat dry;

[0065] (14) Color development: Add 100 μL of substrate color development solution to each well in a dark environment, cover with sealing film and incubate at room temperature for 20 min. During the incubation process, it is also important to avoid light.

[0066] (15) Termination of reaction: Closely observe the color development. When the standard shows a color gradient or the other wells show a different color gradient, add 50 μL of termination solution to each well. When the color changes from blue to yellow, immediately place it on the microplate reader and shake well to completely terminate the reaction.

[0067] (16) Set the relevant parameters of the microplate reader, with wavelengths of 450nm and 620nm, and read the OD value and calculate the corresponding concentration within 5 minutes.

[0068] 4. Detection of CFB concentration in saliva

[0069] (1) Allow the reagents to be used to room temperature in advance;

[0070] (2) Diluting the saliva sample to be tested: Take the patient's saliva out of the -80℃ freezer and thaw it slowly on ice. After the saliva has completely thawed, centrifuge at 9500g at 4℃ for 10 minutes. Take an appropriate amount of supernatant saliva and dilute it with CFB at a ratio of 1:50. Use a new pipette tip each time you take a sample to avoid cross-contamination between saliva samples.

[0071] (3) Sample addition: Open the pre-packaged CFB plate box and add 50 μL of diluted saliva sample and standard to each well. Avoid air bubbles during sample addition and be careful not to let the pipette tip touch the bottom of the plate. Cover with sealing film and incubate on a shaker at low speed at room temperature for 2 hours.

[0072] (4) Washing the plate in a plate washer: Add 400 μL of PBST to each well, shake for 3 seconds and then aspirate the liquid from the well; repeat this washing step 3 times, and take the plate out of the plate washer for the last time and pat it completely dry on absorbent paper;

[0073] (5) Add primary antibody: Dilute the detection antibody to one concentration with Reagent Diluent, add 50 μL of the diluted detection antibody to each well, cover with sealing film and incubate on a shaker at low speed at room temperature for 1 h.

[0074] (6) Repeat the washing process in step 4 and pat dry;

[0075] (7) Add secondary antibody: Add 50 μL of HRP-labeled secondary antibody to each well, cover with sealing film, and incubate on a shaker at low speed at room temperature for 30 min, taking care to avoid light;

[0076] (8) Repeat step 4 to wash the plate and pat it dry;

[0077] (9) Color development: Add 50 μL of substrate color development solution to each well, cover with sealing film and incubate at room temperature for 20 min, taking care to avoid light;

[0078] (10) Terminate the reaction: Observe the color development. When the standard shows a color gradient or the other wells show a different color gradient, add 50 μL of stop solution to each well. When the color changes from blue to yellow, immediately put it on the microplate reader and shake it to completely terminate the reaction.

[0079] (11) Set the relevant parameters of the microplate reader, with wavelengths of 450nm and 620nm, and read the OD value and calculate the corresponding concentration within 5 minutes.

[0080] 5. Detection of CLU concentration in saliva

[0081] (1) Allow the required reagents to reach room temperature beforehand;

[0082] (2) Diluting the saliva sample to be tested: Take the patient's saliva out of the -80℃ freezer and thaw it slowly on ice. After the saliva is completely thawed, centrifuge at 9500g at 4℃ for 10 minutes. Take an appropriate amount of the supernatant saliva and dilute it at a ratio of 1:50. Use a new pipette tip each time you take a sample to avoid cross-contamination between saliva samples.

[0083] (3) Sample addition: Open the pre-packaged CLU plate box, add 100 μL of Assay Diluent to each well, followed by 50 μL of diluted saliva sample and standard. Mark the order and position of the samples. Avoid air bubbles during sample addition, and be careful not to let the pipette tip touch the bottom of the plate. Cover with sealing film and incubate at low speed on a shaker at room temperature for 2 hours.

[0084] (4) Washing the plate in a plate washer: Add 400 μL of PBST to each well, shake for 3 seconds and then aspirate the liquid from the well; repeat this washing step 3 times, and take the plate out of the plate washer for the last time and pat it completely dry on absorbent paper;

[0085] (5) Add primary antibody: Add 200 μL of horseradish peroxidase-labeled primary antibody to each well, cover with sealing film, and incubate on a shaker at low speed at room temperature for 2 hours, taking care to avoid light;

[0086] (6) Repeat step 4 to wash the plate and pat it dry;

[0087] (7) Color development: Add 200 μL of substrate color development solution to each well, gently cover with sealing film, and incubate at room temperature for 30 min, taking care to avoid light;

[0088] (8) Terminate the reaction: Observe the color development. When the standard shows a color gradient or the other wells show a different color gradient, add 50 μL of stop solution to each well. When the color changes from blue to yellow, immediately put it on the microplate reader and shake well to completely terminate the reaction.

[0089] (9) Set the relevant parameters of the microplate reader, with wavelengths of 450nm and 620nm. Read the OD value and calculate the corresponding concentration within 5 minutes.

[0090] 6. Test Results:

[0091] CFB, CLU, and NE were detected in saliva samples from non-pSS (n=65) and pSS (n=121) patients using ELISA. The results are as follows: Figure 1 As shown, the results indicated significantly elevated levels of CFB, CLU, and NE in the saliva of patients with pSS. ROC curve analysis confirmed that saliva levels of CFB, CLU, and NE could distinguish between pSS and non-pSS, such as... Figure 2 As shown in Table 1, based on ROC curve analysis and the Youden index, we determined the optimal cutoff values ​​for the concentrations of CFB, CLU, and NE to distinguish between positive and negative results.

[0092] Table 1

[0093] protein Cutoff value Sensitivity (%) Specificity (%) p-value CFB (ng / mL) 173.50 84.3 44.6 0.003 CLU (ng / mL) 221.40 86.8 69.2 <0.001 NE (ng / mL) 0.00 67.8 75.4 <0.001

[0094] CFB, CLU, and NE were detected in saliva samples from newly diagnosed pSS (n=109) and pSS (n=31) after medication using ELISA. Results showed that CFB, CLU, and NE levels in the saliva of pSS patients significantly decreased after medication, as shown in the following figures. Figure 3 As shown.

[0095] Example 3

[0096] Multivariate regression analysis was used to construct a non-invasive diagnostic model for pSS.

[0097] Clinical examination data were collected from the above-mentioned non-pSS (n=65) and pSS (n=121) patients. CFB, CLU, and NE were converted into categorical variables according to the optimal cutoff value; values ​​above the cutoff value were considered positive and assigned a value of 1, while values ​​below the cutoff value were considered negative and assigned a value of 0. Schirmer's test results were converted into categorical variables according to clinical prediction or diagnostic criteria; a positive result was coded as 1, and a negative result as 0. Serum autoantibody tests, such as anti-SSA, anti-Ro52, and anti-SSB antibodies, were coded as 0, 1, 2, and 3 respectively based on the number of "+" signs on the clinical test results.

[0098] Univariate analysis showed that CFB, CLU, NE, Schirmer's test results, anti-SSA, anti-Ro52, anti-SSB, ANA titer, erythrocyte sedimentation rate (ESR), and IgG were all associated with the prediction or diagnosis of pSS. To determine the final non-invasive predictors of pSS, we further performed a multivariate regression analysis using a stepwise logistic regression model. Candidate parameters with P < 0.1 in the univariate analysis were included in the multivariate regression model. The final variables retained in the non-invasive prediction or diagnosis model were CFB, CLU, NE, anti-SSA, anti-Ro52, and Schirmer's test results. We calculated the predictive probability (PRE) for predicting or diagnosing pSS based on logistic regression analysis.

[0099] The equation for predicting pSS is: PRE = -4.511 + 1.369 × "CFB" + 2.441 × "CLU" + 1.237 × "NE" + 1.194 × Schirmer's test + 0.709 × "anti-SSA" + 0.481 × "anti-Ro52". Based on the predicted probabilities from logistic regression analysis, the AUC of this joint prediction or diagnostic model is 0.930 (P < 0.001, 95% CI 0.877–0.965), with a sensitivity and specificity of 84.85% and 92.45%, respectively. Figure 4 As shown.

[0100] Example 4

[0101] The diagnostic efficacy of the above diagnostic model was validated using a validation queue.

[0102] Saliva samples were collected from 49 patients with pSS and 23 patients without pSS as a validation cohort. CFB, CLU, and NE were detected in the saliva samples using ELISA. The probability of diagnosing pSS in the validation cohort was calculated using the equation PRE = -4.511 + 1.369 × CFB + 2.441 × CLU + 1.237 × NE + 1.194 × Schirmer's test + 0.709 × anti-SSA + 0.481 × anti-Ro52. The AUC of PRE in the validation cohort was 0.840, with a sensitivity of 78.72% and a specificity of 86.36%, as shown in the results. Figure 5 As shown.

[0103] Combining markers in pSS saliva (CFB, CLU, NE) with existing non-invasive clinical tests (anti-SSA, anti-Ro52, and Schirmer test) has efficacy in diagnosing pSS.

[0104] The applicant declares that this invention illustrates a combination of biomarkers for predicting or diagnosing primary Sjögren's syndrome and its application through the above embodiments. However, this invention is not limited to the above embodiments, meaning that this invention does not necessarily rely on the above embodiments for implementation. Those skilled in the art should understand that any improvements to this invention, equivalent substitutions of the raw materials in the product of this invention, addition of auxiliary components, and selection of specific methods, etc., all fall within the protection and disclosure scope of this invention.

[0105] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0106] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

Claims

1. A device for predicting or diagnosing primary Sjögren's syndrome, characterized in that, The device includes a detection unit and an analysis unit; The detection unit is used to perform the following: detecting the expression levels of a combination of biomarkers used to predict or diagnose primary Sjögren's syndrome, tear secretion, SSA antibody, and Ro52 antibody in the sample of the individual to be tested; The analysis unit is used to perform the following: The results of biomarker detection, tear secretion test, SSA antibody detection, and Ro52 antibody detection used to predict or diagnose primary Sjögren's syndrome are input into the primary Sjögren's syndrome prediction or diagnosis model for data analysis, output the prediction probability, and determine whether the result is positive for primary Sjögren's syndrome. The biomarker is a combination of CFB, CLU and NE; The formula for calculating the predicted probability is: Predicted probability = -4.511 + 1.369 × CFB test result + 2.441 × CLU test result + 1.237 × NE test result + 1.194 × tear secretion test result + 0.709 × SSA antibody test result + 0.481 × Ro52 antibody test result; The diagnostic criteria for a positive result for primary Sjögren's syndrome are: a predicted probability ≥ 0.6881.

2. The device for predicting or diagnosing primary Sjögren's syndrome according to claim 1, characterized in that, When the CFB concentration is higher than 173.50 ng / mL, the CFB detection result is recorded as 1; otherwise, the detection result is recorded as 0. If the CLU concentration is higher than 221.40 ng / mL, the CLU detection result is recorded as 1; otherwise, the detection result is recorded as 0. If the NE concentration is higher than 0 ng / mL, the NE detection result is recorded as 1; otherwise, the detection result is recorded as 0. If the tear secretion test shows that less than 5 mm of tear fluid wets the filter paper in either eye within 5 minutes, the result is recorded as 1; otherwise, the result is recorded as 0. SSA antibody test results are selected from 0, 1, 2, and 3; Ro52 antibody test results are selected from 0, 1, 2, and 3.

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