Biomarker for diagnosing rheumatoid arthritis and uses thereof

Abstract

The present invention relates to a marker composition for diagnosing rheumatoid arthritis, comprising angiotensinogen (ACT) as a marker, a method for providing information necessary to determine the occurrence of rheumatoid arthritis using the marker composition, a composition for determining the occurrence of rheumatoid arthritis, comprising an agent for measurement of the expression level of the marker, and a kit for determining the occurrence of rheumatoid arthritis, comprising a device for measurement of the expression level of the marker. The method for providing information for use in determining the occurrence of rheumatoid arthritis provided by the present invention can be widely utilized to determine the occurrence of various joint diseases, including rheumatoid arthritis since it is possible to measure the expression levels of proteins of which the expression levels are changed at the time of the occurrence of rheumatoid arthritis, and to more objectively and accurately determine the occurrence of rheumatoid arthritis when the method is used.

Claims

1. A method for providing information necessary to determine occurrence of rheumatoid arthritis, the method comprising: (a) quantitatively analyzing an expression level of angiotensinogen (AGT) in a serum sample of an individual suspected of having rheumatoid arthritis; and (b) correlating the quantitatively analyzed expression level of angiotensinogen with determination of occurrence of rheumatoid arthritis.

2. The method according to claim 1, wherein the correlating step (b) is performed by applying a quantitatively analyzed expression level of angiotensinogen to an analysis method selected from the group consisting of a logistic regression method; a linear or nonlinear regression analysis method; a linear or nonlinear classification analysis method; ANOVA; a neural network analysis method; a genetic analysis method; a support vector machine, analysis method; a hierarchical duster analysis or cluster analysis method; a hierarchical algorithm using decision trees, or Kernel principal component analysis method; a Markov Blanket analysis method; a recursive feature elimination or entropy-based recursive feature elimination analysis method; a forward floating search or backward floating search analysis method; and a combination thereof,

3. The method according to claim 1, wherein the step (a) further includes quantitatively analyzing an expression level of a protein selected from the group consisting of retinol-binding protein 4 (RBP4), serum amyloid A-4 (SAA4), vitamin D-binding protein (VDBP), and a combination thereof.

4. The method according to any one of claims 1 to 3, wherein the step (b) further includes correlating an expression level of a protein selected from the group consisting of retinol-binding protein 4, serum amyloid A-4, vitamin D-binding protein, and a combination thereof with determination of occurrence of rheumatoid arthritis.

5. The method according to claim 4, wherein the correlating step is performed by combining quantitative analysis results of angiotensinogen, retinol-binding protein 4, serum amyloid A-4, and vitamin D-binding protein.

6. The method according to claim 5, wherein the combination of quantitative analysis results is performed using a computer algorithm.

Description

BRIEF DESCRIPTION OF DRAWINGS

[0049] FIG. 1A is a graph illustrating the results of principal component analysis performed on unique proteins contained in the samples of a control group and an experimental group;

[0050] FIG. 1B is a graph illustrating proteins having an expression level changed by 2-fold or more and a p-value of 0.05 or less at the same time when volcano plot analysis is performed on proteins contained in the samples of a control group and an experimental group;

[0051] FIG. 1C is a diagram illustrating the results of heatmap analysis performed on proteins having an expression level changed by 2-fold or more, which are proteins contained in the samples of a control group and an experimental group;

[0052] FIGS. 2A-G are extracted ion chromatograms (EIC) of peptides used for absolute MRM quantification of angiotensinogen (A), C-reactive protein (B), gelsolin (C), lymphatic vessel endothelial hyaluronan receptor 1 (D), retinol-binding protein 4 (E), serum amyloid A-4 (F), and VDBP (G) contained in the serum samples of an experimental group;

[0053] FIG. 3A is a graph illustrating the concentration of angiotensinogen contained in the serum samples of a control group and an experimental group;

[0054] FIG. 3B is a graph illustrating the concentration of serum amyloid A-4 contained in the serum samples of a control group and an experimental group;

[0055] FIG. 3C is a graph illustrating the concentration of retinol-binding protein 4 contained in the serum samples of a control group and an experimental group;

[0056] FIG. 3D is a graph illustrating the concentration of vitamin D-binding protein contained in the serum samples of a control group and an experimental group;

[0057] FIG. 4A is a graph illustrating the concentration of angiotensinogen contained in the serum samples of a control group and each type of patients with rheumatoid arthritis;

[0058] FIG. 4B is a graph illustrating the concentration of serum amyloid A-4 contained in the serum samples of a control group and each type of patients with rheumatoid arthritis;

[0059] FIG. 4C is a graph illustrating the concentration of retinol-binding protein 4 contained in the serum samples of a control group and each type of patients with rheumatoid arthritis;

[0060] FIG. 4D is a graph illustrating the concentration of vitamin D-binding protein contained in the serum samples of a control group and each type of patients with rheumatoid arthritis;

[0061] FIG. 5A is an ROC graph illustrating the results of logistic regression analysis performed on the expression levels of four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) in the serum samples of a control group and an experimental group; and

[0062] FIG. 5B is an ROC graph illustrating the results of logistic regression analysis performed on a combination of the expression levels of four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) in the serum samples of a control group and an experimental group.

DETAILED DESCRIPTION OF THE INVENTION

[0063] Hereinafter, the configuration and effects of the present invention will be described in more detail with reference to exemplary embodiments. However, these exemplary embodiments are for illustrative purposes only, and the scope of the present invention is not intended to be limited by these exemplary embodiments.

Example 1: Preparation of Samples

[0064] Serum samples of 251 patients with rheumatoid arthritis (experimental group) and serum samples of 230 healthy controls (control group) were collected from the Eulji University Hospital Institutional Review Board.

[0065] Roughly, each blood sample taken from the patients with rheumatoid arthritis and the healthy controls was left at 24° C. for 2 hours, and then centrifuged (4,000×g, 5 min) to obtain each serum.

[0066] The obtained serum was applied to an LC column (human 6-HC, 4.6 mm×50 mm; Agilent Technologies, Santa Clara, Calif., USA) to deplete serum proteins (albumin, IgG, antitrypsin, IgA, transferrin, and haptoglobin) known to be highly abundantly contained in the blood, and then applied to a Nanosep device equipped with a polyether sulfone membrane 3K (Pall, Zaventem, Belgium) to be concentrated. The concentrated sample was applied to a mass spectrometer (AB Sciex 5600, Framingham, Mass., USA) and MRM (multiple reaction monitoring)-based targeted protein quantification to select candidate biomarkers for diagnosis of rheumatoid arthritis.

[0067] At this time, the MRM-based targeted protein quantification result was evaluated by Welch's correction T test method using GraphPad Prism version 8.0 for Windows (GraphPad Software Inc., San Diego, Calif.), and logistic regression analysis method using SPSS software package version 18.0.0 (SPSS Inc., Chicago, Ill., USA) was employed,

Example 2: Processing of Samples

[0068] To the serum sample (100 μg of serum protein) obtained in Example 1, 5 mM tris(2-carboxyethyl)phosphine (Pierce Chemical Company, Rockford, Ill., USA) was added, the reaction was conducted for 30 minutes at 37° C. and 300 rpm, 15 mM iodoacetamide (Sigma-Aldrich, St. Louis, Mo., USA) was further added, the reaction was conducted again for 1 hour at 24° C. and 300 rpm under dark conditions for alkylation.

[0069] Subsequently, the alkylated sample was treated with mass spectrometry-grade trypsin gold (Promega Corporation, Fitchburg, Wis., USA), and reacted at 37° C. overnight to cleave the serum proteins into peptides.

[0070] The cleaved peptide sample was applied to the OFFGEL fractionator (3100 OFFGEL Low Res Kit, pH 3-10; Agilent Technologies, Santa Clara, Calif., USA), and separated into 12 fractions through pH 3-10 isoelectric points.

[0071] A sample of each of the separated fractions was loaded onto the Eksigent nanoLC 400 system and cHiPLC (AB Sciex, Concord, ON, Canada) for analysis, and analyzed using a TripleTOF 5600 mass spectrometer (AB Sciex).

[0072] At this time, the sample (1 μg/μL) was injected into the Eksigent ChromXP nanoLC trap column (350 μm i.d.×0.5 mm, ChromXP C 18 3 μm) at a flow rate of 5000 nL/min, and eluted from the Eksigent ChromXP nanoLC column (75 μm i.d.×15 cm) at a flow rate of 300 nL/min for 120 min, and then mobile phase B buffer was added at a gradient of 5% to 90% for 120 min (0 min/5%, 10.5 min/40%, 105.5 min/90%, 111.5 min/90%, 112 min/5%, and 120 min5%).

[0073] As a result, a total of 339 proteins were identified in the samples of the control group and the experimental group, 194 unique proteins were identified in the control samples, and 111 unique proteins were identified in the experimental group samples.

[0074] Thereafter, SWATH analysis was performed to quantify the identified proteins, and then principal component analysis (PCA) was performed using the quantification data acquired from the analysis (FIG. 1A).

[0075] FIG. 1A is a graph illustrating the results of principal component analysis performed on the unique proteins contained in the samples of the control group and the experimental group.

[0076] As illustrated in FIG. 1A, it was confirmed that the unique proteins contained in the samples of the control group and the experimental group were clearly distinguished from each other.

[0077] PLS-DA (partial least squares discriminant analysis) was performed using the analysis results of the samples of the control group and the experimental group, filtering was performed by the p value (p<0.05), and duster analysis was performed on the proteins having an expression level changed by 2-fold or more (FIG. 1B).

[0078] FIG. 1B is a graph illustrating proteins having an expression level changed by 2-fold or more and a p-value of 0.05 or less at the same time when volcano plot analysis is performed on the proteins contained in the samples of the control group and the experimental group.

[0079] As illustrated in FIG. 1B, it was confirmed that the samples of the control group and the experimental group contained a large number of proteins of which the expression levels were upregulated or downregulated by 2-fold or more.

[0080] Heatmap analysis was performed on the proteins having an expression level changed by 2-fold or more, which were obtained as a result of the duster analysis (FIG. 1C).

[0081] FIG. 1C is a diagram illustrating the results of heatmap analysis performed on the proteins having an expression level changed by 2-fold or more, which were contained in the samples of the control group and the experimental group.

[0082] As illustrated in FIG. 1C, it was confirmed that a larger number of proteins having a significantly upregulated expression level was present in the samples of the experimental group than in the samples of the control group.

Example 3: Selection of Biomarkers

[0083] From the results of heatmap analysis performed in Example 2, it was attempted to select biomarkers of which the expression levels were upregulated in the samples of the experimental group than in the samples of the control group.

[0084] First, seven proteins having a significantly upregulated expression level in the samples of the experimental group compared to in the samples of the control group were first selected as biomarker candidates. Here, the selected seven proteins are angiotensinogen (AGT), C-reactive protein, gelsolin, lymphatic vessel endothelial hyaluronan receptor 1, retinal-binding protein 4 (RBP4), serum amyloid A-4 (SAA4), and vitamin D-binding protein (VDBP).

[0085] Extracted ion chromatography of selected peptides was performed to absolutely quantify the seven selected proteins, which were contained in the serum samples of the experimental group (FIG. 2).

[0086] FIG. 2 is extracted ion chromatograms (EIC) of peptides used for absolute MRM quantification of angiotensinogen (A), C-reactive protein (B), gelsolin (C), lymphatic vessel endothelial hyaluronan receptor 1 (D), retinol-binding protein 4 (E), serum amyloid A-4 (F), and VDBP (G) contained in the serum samples of the experimental group.

[0087] The area under the quantitative curve (AUC) of each protein acquired in FIG. 2 was measured, and it was confirmed that (A) angiotensinogen (AUC=0.8346), (B) C-reactive protein (AUC=0.5030), (C) gelsolin (AUC=0.6794), (D) lymphatic vessel endothelial hyaluronan receptor 1 (AUC=0.5309), (E) retinol-binding protein 4 (AUC=0.9391), (F) serum amyloid A-4 (AUC)=0.8994), and (G) vitamin D-binding protein (AUC=0.8170), respectively.

[0088] From the results, four proteins having an AUC value of 0.8 or more, including (A) angiotensinogen (AUC=0.8346), (E) retinol-binding protein 4 (AUC=0.9391), (F) serum amyloid A-4 (AUC)=0.8994), and (G) vitamin D-binding protein (AUC=0.8170) were ultimately selected as biomarkers.

Example 4: Validation of Effect of Biomarkers for Diagnosis of Rheumatoid Arthritis

Example 4-1: Comparison Between Healthy Control and Patient with Rheumatoid Arthritis

[0089] The expression levels of the four biomarkers selected in Example 3 in the serum samples of the control group and the experimental group collected in Example 1 were measured and compared (FIGS. 3A to 3D). Here, the comparison results of the expression levels of the respective biomarkers were displayed as box-and-whisker plots.

[0090] FIG. 3A illustrates the concentration of angiotensinogen contained in the serum samples of the control group and the experimental group, FIG. 3B illustrates the concentration of serum amyloid A-4 contained in the serum samples of the control group and the experimental group, FIG. 3C illustrates the concentration of retinol-binding protein 4 contained in the serum samples of the control group and the experimental group, and FIG. 3D illustrates the concentration of vitamin D-binding protein contained in the serum samples of the control group and the experimental group.

[0091] As illustrated in FIGS. 3A to 3D, it was confirmed that all of the four biomarkers selected in Example 3 were detected at higher levels in the sera of the experimental group than in the sera of the control group.

Example 4-2: Comparison According to Type of Patient with Rheumatoid Arthritis

[0092] In general, it is known that rheumatoid arthritis is divided into a type which is negative for each of the RF (rheumatoid factor) and anti-CPP (cyclic citrullinated peptide) antibody, and a type which is positive for each of the RF and anti-CPP antibody, and the expression levels of the four biomarkers selected in Example 3 in the serum samples of each type of patients with rheumatoid arthritis were measured and compared (FIGS. 4A to 4D). Here, serum samples of healthy controls (HC) were used as the control group, and the comparison results of the expression levels of the respective biomarkers were displayed as scatter plots.

[0093] FIG. 4A illustrates the concentration of angiotensinogen contained in the serum samples of the control group and each type of patients with rheumatoid arthritis, FIG. 4B illustrates the concentration of serum amyloid A-4 contained in the serum samples of the control group and each type of patients with rheumatoid arthritis, FIG. 40 illustrates the concentration of retinol-binding protein 4 contained in the serum samples of the control group and each type of patients with rheumatoid arthritis, and FIG. 40 illustrates the concentration of vitamin D-binding protein contained in the serum samples of the control group and each type of patients with rheumatoid arthritis.

[0094] As illustrated in FIGS. 4A to 4D, it was confirmed that all of the four biomarkers selected in Example 3 were detected at higher levels in the serum samples of all types of patients with rheumatoid arthritis than in the serum samples of the control group.

Example 4-3: Logistic Regression Analysis

[0095] The results acquired by individually measuring the expression levels of the four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) selected in Example 3 in the serum samples of the control group and the experimental group collected in Example 1 were collected, and logistic regression analysis was performed on each of these to measure the diagnostic success rate among all patients (Tables 1 to 4 and FIG. 5A).

TABLE-US-00001 TABLE 1 Results of diagnosis using angiotensinogen by regression analysis Diagnosed Diagnosed Diagnostic as healthy as patient success rate AUC Control 209 42 83.3% 0.8346 group Experimental 61 169 73.5% group

TABLE-US-00002 TABLE 2 Results of diagnosis using serum amyloid A-4 by regression analysis Diagnosed Diagnosed Diagnostic as healthy as patient success rate AUC Control 223 28 88.8% 0.8890 group Experimental 54 176 76.5% group

TABLE-US-00003 TABLE 3 Results of diagnosis using retinol-binding protein 4 by regression analysis Diagnosed Diagnosed Diagnostic as healthy as patient success rate AUC Control 204 47 81.3% 0.8170 group Experimental 76 154 67.0% group

TABLE-US-00004 TABLE 4 Results of diagnosis using vitamin D- binding protein by regression analysis Diagnosed Diagnosed Diagnostic as healthy as patient success rate AUC Control 228 23 90.8% 0.9430 group Experimental 32 198 86.0% group

[0096] FIG. 5A is an ROC graph illustrating the results of logistic regression analysis performed on the expression levels of four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) in the serum samples of the control group and the experimental group.

[0097] As presented in Tables 1 to 4 and FIG. 5A, when four biomarkers were used, it was confirmed that the diagnostic success rate in healthy controls was 81.3% to 90.8%, the diagnostic success rate in patients with rheumatoid arthritis was 67.0% to 86.0%, and the AUC was 0.8170 to 0.9430.

[0098] In order to examine whether there is a change in the diagnostic success rate when the expression levels of the four biomarkers are combined, the results acquired by individually measuring the expression levels of the four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) selected in Example 3 in the serum samples of the control group and the experimental group collected in Example 1 were collected, and logistic regression analysis was performed on the combination of these results to measure the diagnostic success rate among all patients (Table 5 and FIG. 5B).

TABLE-US-00005 TABLE 5 Results of diagnosis using four biomarkers by regression analysis Diagnosed Diagnosed Diagnostic as healthy as patient success rate AUC Control 234 17 93.2% 0.9740 group Experimental 19 211 91.7% group

[0099] FIG. 5B is an ROC graph illustrating the results of logistic regression analysis performed on the combination of the expression levels of four biomarkers (angiotensinogen, serum amyloid A-4, retinol-binding protein 4, and vitamin D-binding protein) in the serum samples of the control group and the experimental group,

[0100] As presented in Table 5 and FIG. 5B, when four biomarkers were used in combination, it was confirmed that the diagnostic success rate in healthy controls was 93.2%, the diagnostic success rate in patients with rheumatoid arthritis was 91.7%, and the AUC was 0.9740.

[0101] Summarizing the results, it has been analyzed that the diagnostic success rate of rheumatoid arthritis can be significantly improved in the case of using four biomarkers provided by the present invention in combination compared to in the case of using the four biomarkers individually.

[0102] Based on the above description, it will be understood by those skilled in the art that the present disclosure may be implemented in a different specific form without changing the technical spirit or essential characteristics thereof. Therefore, it should be understood that the above embodiment is not limitative, but illustrative in all aspects. The scope of the disclosure is defined by the appended claims rather than by the description preceding them, and therefore all changes and modifications that fall within metes and bounds of the claims or equivalents of such metes and bounds are therefore intended to be embraced by the claims.