Kit for auxiliary diagnosis of systemic sclerosis related interstitial lung disease based on GFPT2 gene expression detection

Abstract

The invention discloses a biomarker GFPT2 gene for diagnosing interstitial lung diseases related to systemic sclerosis, which makes up for the deficiency of existing diagnosis targets of systemic sclerosis and interstitial lung diseases. Research shows that whether the SSc-ILD risk exists or not can be effectively judged by detecting the expression level of the GFPT2 gene. The expression level of the GFPT2 gene in peripheral blood of SSc-ILD patients is obviously lower than that of healthy people, so that high sensitivity and specificity of the marker in disease diagnosis are proved. Accordingly, the inventor further develops a diagnostic kit, the kit provides a new molecular target for early diagnosis of SSc-ILD, compared with an existing diagnostic method, the kit has higher accuracy, accurate screening and early intervention of SSc-ILD patients can be achieved, a simple, convenient, efficient and high-specificity diagnostic tool is provided for clinic, and the kit can be applied to clinical diagnosis of SSc-ILD patients. According to the SSc-ILD gene detection kit, gene detection can be rapidly carried out, the diagnosis period is shortened, the complexity of experiment operation is reduced, and doctors are assisted to carry out precise SSc-ILD diagnosis and treatment decision making clinically.

Description

Technical Field

[0001] The present invention belongs to the technical field of systemic sclerosis diagnosis and detection, and in particular relates to a kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection. Background Art

[0002] Systemic sclerosis (SSc) is a rare autoimmune disease characterized by fibrosis and vascular lesions in the skin and internal organs. Interstitial lung disease (ILD) is one of the most common complications in SSc patients and is closely associated with high mortality. The pathogenesis of SSc-ILD is complex, involving immune system abnormalities, fibrotic processes, and interactions with multiple immune cells. Therefore, early diagnosis and monitoring of SSc-ILD are crucial to improving patient prognosis and enhancing treatment outcomes.

[0003] With the rapid development of genomics and bioinformatics technologies, researchers have gradually discovered potential biomarkers for SSc and SSc-ILD through high-throughput genomic analysis. Early studies focused on known immune cell function and fibrosis markers, such as antinuclear antibodies (ANA) and anti-Scl-70 antibodies. Although these markers provide support for the diagnosis of SSc, their specificity and sensitivity for ILD are limited, especially in the early stages of the disease.

[0004] Although the research on SSc-ILD continues to deepen, the existing technology still has significant deficiencies, mainly reflected in the following aspects: (1) Insufficient specificity and sensitivity of diagnostic markers: Currently, the diagnosis of SSc-ILD relies on imaging examinations and some immunological markers, such as SP-D, CCL18, CCL2, etc. SP-D is considered to be a good biomarker for diagnosing SSc-ILD, but its expression changes in other lung diseases affect the accuracy of diagnosis. Although the expression levels of CCL18 and CCL2 are associated with the progression of SSc-ILD, the sensitivity and specificity of these markers are still insufficient to provide sufficiently accurate early diagnosis. (2) Lack of early markers reflecting disease specificity: Although a variety of markers have been used in clinical studies of SSc and SSc-ILD, most studies focus on systemic manifestations and lack markers that can specifically reflect the occurrence and development of interstitial lung disease (ILD). Because the clinical manifestations of SSc-ILD are often hidden, early detection and disease progression monitoring are particularly difficult. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection, so as to achieve high sensitivity and specificity of early detection and diagnosis of SSc-ILD.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] The biomarker for diagnosing systemic sclerosis-related interstitial lung disease is the GFPT2 gene.

[0008] The specific primer pair for amplifying the biomarker of claim 1 is the base sequence of SEQ ID NO.1 and SEQ ID NO.2 in the sequence listing.

[0009] Non-diagnostic applications of the above-mentioned specific primer pairs in PCR amplification of the above-mentioned biomarkers.

[0010] The procedure of PCR amplification was pre-denaturation at 95°C for 30 seconds; denaturation at 95°C for 15 seconds; extension at 60°C for 25 seconds; melting curve at 95°C for 1 minute, 60°C for 15 seconds, and 98°C for 5 seconds; and cooling at 35°C for 30 seconds.

[0011] The above-mentioned specific primer pair is used to prepare a kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection.

[0012] A kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection includes the above-mentioned specific primer pair.

[0013] The above-mentioned kit also includes an internal reference primer pair for amplifying the housekeeping gene ACTIN, and the internal reference primer pair is the base sequence of SEQ ID NO.3 and SEQ ID NO.4 in the sequence list.

[0014] The above-mentioned kit also includes SYBR Green fluorescent dye, PCR buffer and dNTPs.

[0015] In response to the current problems in the detection and diagnosis of systemic sclerosis-related interstitial lung disease, the inventors have discovered the GFPT2 gene, a biomarker that can be used to diagnose systemic sclerosis-related interstitial lung disease through comprehensive bioinformatics analysis and immune cell analysis technology, to make up for the shortcomings of existing diagnostic targets for systemic sclerosis (SSc) combined with interstitial lung disease (ILD). Studies have shown that by detecting the expression level of the GFPT2 gene in the subject's sample, it is possible to effectively determine whether there is a risk of SSc-ILD. Since the expression level of the GFPT2 gene in the peripheral blood of SSc-ILD patients is significantly lower than that of healthy people, the high sensitivity and specificity of this marker in disease diagnosis are demonstrated. Based on this feature, the inventors have also developed a related diagnostic kit. The GFPT2 gene expression detection kit provides a new molecular target for the early diagnosis of SSc-ILD. Compared with existing diagnostic methods, it has higher accuracy, helps to achieve accurate screening and early intervention of SSc-ILD patients, and provides a simple, efficient and highly specific diagnostic tool for clinicians. It can quickly perform genetic testing, shorten the diagnosis cycle, reduce the complexity of experimental operations, and assist doctors in making accurate diagnosis and treatment decisions for SSc-ILD in clinical practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Flow chart of SSc-ILD biomarker screening in the present invention, wherein: A: volcano plot of differentially expressed genes in data set GSE76808; B: volcano plot of differentially expressed genes in data set GSE231691; C: biomarker GFPT2 obtained by taking overlapping genes using the above method.

[0017] Figure 2 This is a comparative diagram of the relative expression of GFPT2 in the peripheral blood of healthy controls and SSc-ILD patients using the present invention.

[0018] Figure 3 This is a ROC curve diagram of the present invention for diagnosing SSc-ILD using the relative expression level of GFPT2. DETAILED DESCRIPTION

[0019] 1. Research Design

[0020] 1.1 Data Collection and Processing

[0021] Public data with "SSc-ILD" as the keyword were retrieved from the Gene Expression Omnibus (GEO: https: / / www.ncbi.nlm.nih.gov / ) database, and four related datasets were downloaded and collected: two datasets from lung tissue, GSE76808 (GPL571): containing lung biopsy samples from 14 SSc-ILD patients and 4 controls; GSE81292 (GPL18991): containing lung biopsy samples from 15 SSc-ILD patients and 5 controls. Two sequencing data from peripheral blood, GSE231691 (GPL20301): containing RNA sequencing of peripheral blood from 49 SSc-ILD patients and 18 controls; GSE181228 (GPL24676): containing RNA sequencing of peripheral blood from 232 SSc-ILD patients and 45 controls. First, the GEO2R tool was used to perform differential analysis on the GSE76808 and GSE231691 data sets. Genes with |log2FC|>1 and adj.P.Val<0.05 were considered differentially expressed genes.

[0022] 1.2 Screening of biomarkers for SSc-ILD

[0023] The screening of biomarkers in the present invention mainly uses three methods, including WGCNA and RFE based on the data set GSE81292, and differential analysis of two data sets (GSE76808, GSE231691) using GEO2R. The R software package "WGCNA" was used to perform module analysis and identification of genes in the data set GSE81292. First, the samples were clustered and screened to remove outliers. Secondly, a suitable threshold was selected to construct a gene co-expression network. Finally, module detection was performed using hierarchical clustering and dynamic tree cutting functions, and the modules were associated with clinical features. Genes of related modules were selected for the next step of analysis. RFE was constructed using the R software package "caret", and genes with the highest accuracy were screened using the recursive feature elimination method. Finally, the overlapping genes in the above method were subjected to the next step of analysis.

[0024] 1.3 Peripheral blood sample collection and processing

[0025] All patients met the 2013 American College of Rheumatology (ACR) / European League Against Rheumatism (EULAR) classification diagnostic criteria for SSc. ILD was diagnosed based on chest high-resolution computed tomography (HRCT), showing one or more of the following five imaging features: lattice shadows, ground-glass shadows, honeycomb shadows, consolidation shadows, and nodular shadows. At the same time, the following were excluded: 1) lung diseases caused by environmental, drug, and other factors; 2) non-pulmonary interstitial lesions such as tuberculosis and lung tumors; 3) ILD related to other connective tissue diseases.

[0026] The clinical data of 33 patients with SSc-ILD were collected, including age, gender, disease course, disease subtype, clinical characteristics, modified Rodnan skin score (MRSS), chest HRCT score, anti-topoisomerase-1 (Scl-70), antinuclear antibody (ANA), blood routine, erythrocyte sedimentation rate, C-reactive protein, serum immunoglobulin (Ig), lung function and other clinical indicators.

[0027] 2 ml of fresh peripheral blood was drawn from 33 patients and 18 normal controls and placed in 5 ml sodium citrate anticoagulant tubes. Three times the volume (i.e. 6 ml) of RNAiso Blood (RNAiso Blood, TakaRa, Japan) was added on ice and mixed by pipetting up and down, then placed on ice for 5 minutes and frozen in an ultra-low temperature refrigerator at -80°C for subsequent real-time fluorescence quantitative PCR.

[0028] 1.4 Peripheral blood real-time fluorescence quantitative PCR

[0029] The mixed solution with 3 times volume of RNAiso Blood was taken out and thawed on ice. Total RNA was extracted according to RNA isolation reagent (RNAiso Blood, TakaRa, Japan), and then the reaction system was configured according to the instructions of the reverse transcription kit (PrimeScriptTM RTreagent Kit, TaKaRa, Japan), and then the reverse transcription reaction was performed in the reverse transcription PCR instrument according to the reverse transcription program set at 37℃-15min, 85℃-5sec. After that, the total RNA was reverse transcribed, and the cDNA was diluted 1:5 with enzyme-free water and stored in a -20℃ refrigerator. ACTIN internal reference (upstream: 5'-AGATCAAGATCATTGCTCCTCCTG-3', downstream: 5'-AGTCA TAGTCCGCCTAGAAGCAT-3'). GFPT2 (upstream: 5'-GAAGGACCACTTGAAGGAG ATTCG-3', downstream: 5'-CAACCATCACAGGAAGCTCAGTC-3'). The obtained cDNA was prepared according to the PCR reagents, and three biological replicates and three technical replicates were required. The reaction temperature was set in the PCR instrument, pre-denaturation 95℃-30sec; denaturation 95℃-15sec; extension 60℃-25sec; melting curve 95℃-1min, 60℃-15sec, 98℃-5sec; cooling 35℃-30sec. The CT value (threshold cycle number) of each sample was recorded, ΔCT=CT (target gene)-CT (reference gene), ΔΔCT=ΔCT (SSc-ILD)-ΔCT (healthy control), and the results were calculated by 2-ΔΔCT. The results were statistically significant when P<0.05.

[0030] 1.5 Statistical analysis

[0031] All data processing and analysis were performed using R software (version 4.3.1), GraphPad Prism (version 9.5.1), and SPSS (version 26.0). Data that conformed to normal distribution were expressed as mean ± standard deviation, while data that conformed to non-normal distribution were expressed as median (interquartile range: Q1-Q3). The Mann-Whitney U test (Wilcoxon rank sum test) was used to analyze the distribution variables for non-normally distributed data between the two groups. Independent sample t-test was used to determine the differences between the two groups for the analysis of normally distributed data. Pearson correlation was used to calculate the data that conformed to normal distribution, while Spearman correlation was used to calculate the data that conformed to non-normal distribution. The difference was considered statistically significant when P < 0.05.

[0032] 2. Research Process and Results

[0033] Screening of biomarkers for SSc-ILD

[0034] The WGCNA algorithm was used to divide 11,973 genes (GSE81292) into different modules, and a gene clustering dendrogram was drawn. Subsequently, the direct correlation and significance of the modules with the disease and control groups were calculated, and the gene modules of the above clusters were divided into 14. It was found that there were 3 modules significantly associated with the disease, namely, the module "blue" had a correlation of -0.94 (p<0.001), the module "red" had a correlation of 0.77 (p<0.001), and the module "brown" had a correlation of -0.69 (p<0.05), with a total of 976 genes. The 976 genes in the above three modules were screened for potential biomarkers by using the RFE algorithm. When the accuracy reached 0.975, three potential biomarkers, "GFPT2", "LINC00472" and "B4GALT5", were screened. GSE76808 and GSE231691 were differentially analyzed by GEO2R. 804 differentially expressed genes were screened out in GSE76808, of which 366 were up-regulated and 438 were down-regulated. 823 differentially expressed genes were screened out in GSE231691, of which 765 were up-regulated and 58 were down-regulated (e.g. Figure 1 A. Figure 1 B).

[0035] The genes screened by GSE76808, GSE81292, and GSE231691 were overlapped to obtain the only biomarker glutamine-fructose-6-phosphate aminotransferase (GFPT2, accession number: NM_005110) ( Figure 1 C).

[0036] Baseline characteristics of patients with SSc-ILD

[0037] Peripheral blood samples of 33 SSc-ILD patients were collected, including 8 males (24.2%) and 25 females (75.8%), with an average age of (55.42±11.8) years, an average disease course of 1 (0.5, 4.5) years, 7 localized cases (21.2%), and 25 diffuse cases (75.8%). There were 18 healthy controls, including 5 males (27.8%) and 13 females (72.2%), with an average age of 56 (46.8, 58) years. There was no significant difference in gender and age between the two groups. Raynaud's phenomenon occurred in 28 SSc-ILD patients (84.9%), fingertip lesions in 17 cases (51.6%), joint swelling and pain in 18 cases (54.5%), and cough and shortness of breath after activity in 11 cases (33.3%), as shown in Table 1.

[0038] Table 1. Baseline characteristics of patients with SSc-ILD

[0039]

[0040] Note: lcSSc: limited systemic sclerosis; dcSSc: diffuse systemic sclerosis; mRSS score: modified Rodnan skin score; anti-Scl-70 antibody: anti-DNA topoisomerase-1; anti-ANA antibody: antinuclear antibody; ESR: erythrocyte sedimentation rate; CRP: C-reactive protein.

[0041] 2.3 Relative expression of GFPT2 in peripheral blood of healthy controls and SSc-ILD patients

[0042] like Figure 2 As shown in the figure, compared with the normal control group, the expression level of GFPT2 mRNA in the peripheral blood of SSc-ILD patients was significantly reduced [0.184 (0.065-0.357) vs 1.004 (1.001-1.012), Z = -5.499, P < 0.001].

[0043] 2.4 Study on the sensitivity and specificity of GFPT2 relative expression in the diagnosis of SSc-ILD

[0044] like Figure 3 As shown in the figure, the ROC curve analysis results showed that the AUC value of the relative expression of GFPT2 in peripheral blood for diagnosing SSc-ILD was 0.970 (P<0.001). When the cutoff value was 0.8853, the specificity was 100% and the sensitivity was 97%.

[0045] 3. Research conclusions and application prospects

[0046] The sensitivity and specificity of the relative expression of the GFPT2 gene in the diagnosis of SSc-ILD are better than those of the classic biomarkers KL-6 (specificity: 70%-90%, sensitivity: 73%-86%, see references 1-3) and SP-D (specificity is 70%-80%, sensitivity is 68%-90%, see references 2, 4). Therefore, the GFPT2 gene can be used as a potential biomarker for diagnosing SSc-ILD, and can be used to achieve accurate screening and early intervention of SSc-ILD patients.

[0047] In order to facilitate rapid detection and diagnosis at the grassroots level, a kit based on GFPT2 gene expression detection can be assembled. The kit mainly includes a specific primer pair for amplifying the GFPT2 gene and other related reagents. The kit can be used to establish a method for diagnosing SSc-ILD through GFPT2 gene expression detection. The general steps include:

[0048] (1) Extracting total RNA from the sample using an RNA extraction reagent;

[0049] (2) synthesizing cDNA from the extracted RNA by reverse transcription;

[0050] (3) Amplify the GFPT2 gene and the internal reference gene using a kit by qPCR method;

[0051] (4) relative quantitative analysis was performed according to the ΔΔCT method, and the amplification products were confirmed by melting curve and electrophoresis analysis;

[0052] (5) If the expression of GFPT2 gene is significantly decreased, it indicates that the patient may suffer from SSc-ILD.

[0053] References

[0054] [1]Asano Y, Ihn H, Yamane K, et al. Clinical significance of surfactantprotein D as a serum marker for evaluating pulmonary fibrosis in patients with systemic sclerosis[J]. Arthritis Rheum, 2001, 44(6):1363-9.

[0055] [2]Hant F N,Ludwicka-Bradley A,Wang H J,et al.Surfactant Protein Dand KL-6as Serum Biomarkers of Interstitial Lung Disease in Patients withScleroderma[J].Journal of Rheumatology,2009,36(4):773-780.

[0056] [3]Hasegawa M,Fujimoto M,Hamaguchi Y,et al.Use of serum clara cell16-kDa(CC16)levels as a potential indicator of active pulmonary fibrosis insystemic sclerosis[J].J Rheumatol,2011,38(5):877-84.

[0057] [4]Elhai M,Hoffmann-Vold AM,Avouac J,et al.Performance of CandidateSerum Biomarkersfor Systemic Sclerosis-Associated Interstitial Lung Disease[J].Arthritis Rheumatol,2019,71(6):972-82.

Claims

1. Biomarkers for diagnosing systemic sclerosis-related interstitial lung disease, characterized by It is the GFPT2 gene.

2. A specific primer pair for amplifying the biomarker according to claim 1, characterized in that It is the base sequence of SEQ ID NO.1 and SEQ ID NO.2 in the sequence listing.

3. Non-diagnostic application of the specific primer pair of claim 2 in PCR amplification of the biomarker of claim 1.

4. The use according to claim 3, characterized in that The PCR amplification procedure is pre-denaturation at 95°C for 30 seconds; Denaturation 95℃-15sec; extension 60℃-25sec; melting curve 95℃-1min, 60℃-15sec, 98℃-5sec; Cool down to 35℃-30sec.

5. The specific primer pair according to claim 2 is used to prepare a kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection.

6. A kit for auxiliary diagnosis of systemic sclerosis-related interstitial lung disease based on GFPT2 gene expression detection, characterized in that Comprising the specific primer pair described in claim 2.

7. The kit according to claim 6, characterized in that It also includes an internal reference primer pair for amplifying the housekeeping gene ACTIN, and the internal reference primer pair is the base sequence of SEQ ID NO.3 and SEQ ID NO.4 in the sequence list.

8. The kit according to claim 7, characterized in that Also included are SYBR Green fluorescent dye, PCR buffer, and dNTPs.

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