A marker for differential diagnosis of tuberculosis patients and application thereof

Abstract

The application belongs to the technical field of biology and specifically relates to a marker for differential diagnosis of tuberculosis patients and application. The biological marker of the application is simple to sample, only peripheral blood is needed for detection, and the reporting result is fast, avoiding the disadvantages of tuberculosis diagnosis smear and sputum culture. The biological marker of the application has high accuracy: receiver operating characteristic curve (ROC) analysis shows that the area under the ROC curve is 0.976 (95% CI: 0.940-1.000, P<0.0001), the sensitivity is 90% (95% CI: 73.5%-97.9%), the specificity is 100% (95% CI: 88.4%-100.0%), and the tuberculosis patients and healthy people can be effectively distinguished.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biotechnology, and particularly relates to a marker for differential diagnosis of patients with tuberculosis and application thereof. BACKGROUND

[0002] Tuberculosis (TB) is a serious infectious disease caused by Mycobacterium tuberculosis (M.tb) infection, which is a major threat to global public health. The diagnosis of TB mainly relies on bacteriological and molecular biological detection techniques (Pulmonary tuberculosis diagnosis industry guidelines, WS-288-2017). In TB high-burden countries, smear microscopy is widely used, but it is labor-intensive, low sensitivity, and cannot rule out non-tuberculosis mycobacterial infection (Zhang et al. Laboratory diagnosis methods and detection technology research progress of Mycobacterium tuberculosis infection. International Respiratory Journal, 2019, 39: 1586-1591); sputum culture, as the gold standard for diagnosing TB, even if the rapid liquid culture method (such as modified Lowenstein-Jensen medium) is used for Mycobacterium tuberculosis culture, positive results still need at least 2 weeks to obtain, and negative results need about 45 days to report, which affects the efficiency of early diagnosis and treatment (Pai M, Schito M. Tuberculosis diagnostics in 2015: landscape, priorities, needs, and prospects [J]. J Infect Dis, 2015, 211(Suppl 2): S21-S28.); In recent years, the development of molecular biology technology has been active and rapid, and GeneXpert MTB / RIF technology has the advantages of rapid diagnosis (Nathakorn Pongpeeradech, Yuthichai Kasetchareo et al. Evaluation of the use of GeneXpert MTB / RIF in a zone with high burden of tuberculosis in Thailand. PLoS ONE (2022).), with higher sensitivity and specificity than traditional bacteriological detection methods, but the technology has higher requirements for sputum sample quality, and higher requirements for infrastructure and biological safety of detection environment, which is limited in primary hospitals and general hospitals. Other immunological detection methods such as tuberculosis antigen or antibody detection have limited detection capacity. In addition, tuberculin test and γ-interferon release experiment cannot distinguish active tuberculosis and latent infection, and imaging technology for the diagnosis of tuberculosis has similar imaging manifestations with other lung diseases, with low specificity. In order to control the spread of tuberculosis, the World Health Organization (WHO) recommends early active screening for suspected tuberculosis patients, but the existing diagnostic techniques cannot meet the clinical needs.

[0003] Biomarkers can reflect disease status, risk of progression, biological effects after treatment, treatment effect and prognosis evaluation, and play an important role in disease diagnosis, treatment and prevention, and provide key basis for the development of new anti-tuberculosis drugs and vaccines. In view of this situation, WHO has developed target product profile (TPP), which is a set of standards for defining the key characteristics that an ideal diagnostic tool should have (Sarah C Charnaud, V. Moorthy et al. “WHO target product profiles to shape global research and development.” Bulletin of the World Health Organization (2023).). According to the TPP standard requirements, the sensitivity for smear-positive and culture-positive pulmonary tuberculosis should not be less than 98%, and the sensitivity for smear-negative and culture-positive pulmonary tuberculosis should reach more than 68%, while the specificity should be maintained at more than 98%; for tuberculosis diagnosis tools, WHO sets the sensitivity of 65% and the specificity of 98% as the target; and in terms of the performance of tuberculosis screening, the sensitivity for active tuberculosis screening should not be less than 90% and the specificity should not be less than 70% (High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva: World Health Organization, 2014.; M. Correia-Neves, Gabrielle et al. “Biomarkers for tuberculosis: the case for lipoarabinomannan.” ERJ Open Research (2019).). TPP emphasizes the use of non-sputum samples for detection, and requires that the detection method should be simple and rapid, and suitable for use in resource-limited areas. Therefore, it is of great significance to find new tuberculosis biomarkers stably expressed in non-sputum samples for improving the existing diagnosis system and enhancing the diagnostic efficiency.

[0004] Circular RNAs (circRNAs) are a new type of non-coding RNA, which do not have 5' end cap and 3' end poly(A) tail, and are non-coding RNA molecules with covalent bond forming ring structure. circRNAs have tissue specificity and temporal and spatial specificity. The expression of circRNAs is different between different tissues. The expression of circRNAs in the same tissue or organ also changes at different growth stages. circRNAs can regulate gene expression from multiple aspects such as chromatin remodeling, transcriptional regulation and post-transcriptional processing, and the mechanism is diversified.

[0005] Unlike traditional non-coding, circRNA molecules are closed loop structures, which are not sensitive to nucleases (Zhongrong Zhang, Tingting Yang et al. "Circular RNAs: Promising Biomarkers for Human Diseases." EBioMedicine (2018).), so they are more stable than linear RNA. This stability makes it easy to detect circRNA in body fluids (such as blood, urine, saliva, etc.), and it has high reliability in disease diagnosis. circRNA is significantly expressed in specific tissues or cell types (Sebastian Memczak, P. Papavasileiou et al. "Identification and Characterization of Circular RNAs As a New Class of Putative Biomarkers in Human Blood." PLoS ONE (2015).), showing high conservation between different species, and can be detected by non-invasive samples such as peripheral blood (Souvick Roy, M. Kanda et al. "Diagnostic efficacy of circular RNAs as noninvasive, liquid biopsy biomarkers for early detection of gastric cancer." Molecular Cancer (2022).), providing convenience for early diagnosis and real-time monitoring. Therefore, for tuberculosis, developing suitable specific circRNAs as markers has important research and clinical significance in regulating gene transcription, as a diagnostic marker for diseases, etc. SUMMARY

[0006] The present application studies and analyzes the circRNAs expression profile of PBMC of a tuberculosis patient, finds that the relative expression amount of hsa_circ_0052124 is significantly reduced in the tuberculosis patient compared with that in a healthy person, and hsa_circ_0052124 can effectively distinguish the tuberculosis patient from the healthy person. Based on this, the present application is completed.

[0007] In a first aspect, the present application provides a biomarker for differential diagnosis of a tuberculosis patient, and the biomarker is hsa_circ_0052124, wherein the nucleotide sequence of hsa_circ_0052124 is shown as SEQ ID NO. 1.

[0008] Further, when the relative expression amount of hsa_circ_0052124 in the biological sample of the subject is ≤0.000783, the subject is a tuberculosis patient.

[0009] Further, the biological sample of the subject is selected from blood.

[0010] Further, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0011] In a second aspect, the present application provides use of the biomarker according to the first aspect of the present application in preparation of a reagent for differential diagnosis of a tuberculosis patient.

[0012] Further, when the relative expression amount of hsa_circ_0052124 in the biological sample of the subject is ≤0.000783, the subject is a tuberculosis patient.

[0013] Further, the biological sample of the subject is selected from blood.

[0014] Further, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0015] In a third aspect, the present application provides a kit for differential diagnosis of a tuberculosis patient, and the kit contains a reagent for detecting the relative expression amount of the biomarker according to the first aspect.

[0016] Further, when the relative expression amount of hsa_circ_0052124 in the biological sample of the subject is ≤0.000783, the subject is a tuberculosis patient.

[0017] Further, the biological sample of the subject is selected from blood.

[0018] Further, the blood sample of the subject is at least one of peripheral blood, plasma and / or serum.

[0019] Further, the kit can be one or more of a nucleic acid detection kit, an immunofluorescence kit, a gene chip detection kit, a molecular hybridization kit, and / or an in situ hybridization staining kit.

[0020] Further, the kit diagnosis method comprises one or more of a PCR method / qPCR method, a linear probe method, a high-resolution melting curve method, and / or a gene chip method.

[0021] Advantages

[0022] The biomarker of the present application is simple to sample, only peripheral blood is needed for detection, and the reporting result is fast. The biomarker of the present application has high accuracy: the receiver operating characteristic curve (ROC) analysis shows that the area under the ROC curve is 0.976 (95% CI: 0.940-1.000, P<0.0001), the sensitivity is 90% (95% CI: 73.5%-97.9%), the specificity is 100% (95% CI: 88.4%-100.0%), and the effective area can distinguish between tuberculosis patients and healthy people. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 hsa_circ_0052124 has a diagnostic value for differential diagnosis of tuberculosis. DETAILED DESCRIPTION

[0024] The specific embodiments of the present application are further described below. It should be noted that the description of these embodiments is used to help understand the present application, but does not constitute a limitation on the present application. In addition, the technical features involved in the following described embodiments can be combined with each other as long as they do not conflict with each other.

[0025] The experimental methods in the following examples are all routine methods unless otherwise specified. The experimental materials used in the following examples are all commercially available unless otherwise specified.

[0026] TERMINOLOGY

[0027] miRNeasy Mini Kit: is a kit for extracting total RNA from various samples launched by Qiagen Company. The miRNeasy Mini Kit is mainly used for extracting total RNA, including miRNAs, mRNAs and rRNAs, etc. from samples such as cells, tissues, plasma, serum, etc. The main steps are: after dissolving the sample in the lysis buffer, adding QIAzol Lysis Reagent for homogenization, then separating the RNA by centrifugation and ethanol precipitation; through vacuum filtration, the RNA is transferred to a new column, and then through washing and elution steps to obtain pure RNA.

[0028] Agilent Expression Profiling Chips: A high-throughput gene expression analysis platform that can detect gene expression levels across the entire genome. For example, the Agilent 4×44K chip can detect over 41,000 probes, covering most areas of the human genome. In addition, Agilent also provides various types of chips, such as whole genome chips (such as SurePrint G3 Human Gene Expression v2) and oligonucleotide chips (such as chips for specific genes or tissues), to meet different research needs.

[0029] Agilent Expression Profiling Chips Kits: An important tool for gene expression analysis, with a wide range of applications, including cancer research, chronic stress research, inflammation reaction analysis, and plant gene expression research.

[0030] Gene Expression Hybridization Kit: Mainly used for cDNA or RNA hybridization experiments, through the combination with probes on microarray chips, to realize the quantitative analysis of gene expression. For example, in the study of human aging-related genes GCAT and SHMT2, Agilent Technologies' Gene Expression Hybridization Kit was used for hybridization experiments, combined with microarray scanning and data analysis tools (such as Agilent Feature Extraction software) for subsequent analysis.

[0031] Hybridization Oven: A device used for DNA hybridization experiments, mainly used for the binding reaction of DNA probes with target DNA or RNA at a specific temperature. This device usually has a constant temperature control function, which can maintain a stable temperature environment to ensure the efficient progress of the hybridization reaction.

[0032] Gene Expression Wash Buffer Kit: A reagent kit used for washing steps in microarray experiments, its main function is to clean the hybridized microarray chips to remove unbound probes and other non-specifically bound molecules. Gene Expression Wash Buffer Kit contains two washing solutions: Gene Expression Wash Buffer 1 and Gene Expression Wash Buffer 2. These washing solutions usually contain a certain concentration of buffer and surfactant (such as Triton X-102) for cleaning microarray chips at different stages.

[0033] Agilent Microarray Scanner: A device used for microarray data analysis, widely applied in gene expression analysis, miRNA analysis, and other molecular biology research. There are multiple models, such as G2505B, G2506A, and G2505C, which are widely used in different types of microarray experiments. Among them, the G2505B model is used for 4644K microarray scanning in Surescan technology; the G2506A model is used for scanning miRNA microarrays; and the G2505C model is used for various experiments, including scanning miRNA microarrays and DNA microarrays.

[0034] Feature Extraction software 10.7: A software developed by Agilent Technologies for microarray data analysis. It is widely used in the extraction and analysis of gene expression data. Feature Extraction software 10.7 is mainly used to extract data from microarray images. For example, in the cyclic miRNA analysis, this software is used to extract raw data from the images scanned by the Agilent Microarray Scanner.

[0035] Quantile: A statistical concept used to describe the distribution characteristics of data. It divides data into equal parts according to size order, and each part is called a quantile interval. For example, quartiles divide data into four equal parts, and the median can be regarded as the second quantile (Q2). Quantile Regression (QR) is a statistical modeling method based on quantiles, which is different from traditional mean regression (such as least squares) and can describe the influence of independent variables on dependent variables at different quantile points, providing more comprehensive data analysis.

[0036] Agilent Human (4*180K) Chip: One of the gene chip series produced by Agilent Company, mainly used for detecting gene expression or miRNA expression profile in human genome. The chip uses a 4x180K probe design, which can cover a wide range of gene regions and is suitable for gene expression analysis of complex samples.

[0037] Receiver operator characteristic curve (ROC curve): a curve plotted with true positive rate (sensitivity) as the ordinate and false positive rate (1-specificity) as the abscissa. The area under the ROC curve (AUC) is between 1.0 and 0.5. When AUC is greater than 0.5, the closer AUC is to 1, the better the diagnostic effect. When AUC is between 0.5 and 0.7, it indicates low accuracy. When AUC is between 0.7 and 0.9, it indicates certain accuracy. When AUC is greater than or equal to 0.9, it indicates high accuracy. When AUC is equal to 0.5, it indicates that the diagnostic method is completely ineffective and has no diagnostic value. AUC less than 0.5 does not conform to the true situation and rarely occurs in practice.

[0038] Example 1 Inclusion and exclusion criteria

[0039] A. Inclusion criteria

[0040] 1) Tuberculosis patients: according to the industry standard WS-288-2017 Tuberculosis Diagnosis, patients with clinical symptoms of tuberculosis, chest imaging suggesting active tuberculosis lesions, and one of the following conditions: positive sputum smear test for Mycobacterium tuberculosis, positive culture for Mycobacterium tuberculosis, positive molecular biology test for Mycobacterium tuberculosis, or positive histopathology.

[0041] 2) Healthy controls: no clinical symptoms of tuberculosis, no abnormalities on imaging, negative tuberculosis infection T cell test, no history of tuberculosis or tuberculosis exposure.

[0042] B. Exclusion criteria

[0043] Age < 18 years old, anti-tuberculosis treatment for more than 2 weeks.

[0044] C. Screening cohort

[0045] 9 healthy people meeting the criteria; 9 tuberculosis patients meeting the criteria.

[0046] D. Validation cohort

[0047] 30 healthy people meeting the criteria; 30 tuberculosis patients meeting the criteria.

[0048] Example 2 Screening test

[0049] The screening cohort was selected for the screening test.

[0050] (1) Experimental method

[0051] A. Isolation of PBMCs from peripheral blood

[0052] Collect whole blood, dilute the blood sample with medium after blood collection, mix well, add sample density separation liquid, and extract PBMCs by Ficoll density gradient centrifugation.

[0053] B. RNA extraction

[0054] According to the operation instruction of miRNeasy Mini Kit kit, total RNA extraction was performed, and the extracted total RNA was reserved after electrophoresis quality inspection.

[0055] C. cRNA labeling

[0056] According to the operation instruction of Agilent expression profile chip supporting kit, total RNA was amplified and labeled, and then the labeled cRNA was purified by miRNeasy mini kit.

[0057] D. Chip hybridization

[0058] According to the hybridization standard process and supporting kit provided by Agilent expression profile chip, the operation was performed according to the instruction of Gene Expression Hybridization Kit, 65℃, 10rpm, rolling hybridization in the rolling hybridization oven for 17 hours, and the chip was washed in the washing tank, and the reagent used for washing the chip was Gene Expression Wash Buffer Kit.

[0059] E. Chip scanning and data analysis

[0060] The chip completed hybridization was scanned by Agilent Microarray Scanner, and the software settings were Dyechannel: Green, Scan resolution = 3 μm, PMT 100%, 20 bit. The data was read by Feature Extraction software 10.7, and finally the limma package in R software was used for normalization processing, and the algorithm used was Quantile.

[0061] (2) Test results

[0062] Based on the microarray expression profile chip data, the top 25% of the expression profile data with higher median relative expression (including 21880 circRNAs) was used for weighted gene co-expression network analysis (WGCNA) to establish a gene co-expression network, and the gene modules significantly related to tuberculosis were screened. Further screening of genes in the module was performed with module members (MM) > 0.85 and gene significance (GS) > 0.85 as screening conditions, and 1220 circRNAs were screened. Combined with the screening criteria of fold change between groups > 4 or < 0.25, P value of inter-group difference < 0.05, and average relative expression of circRNAs in any group > 10, 9 significantly differentially expressed circRNAs were screened, including 8 down-regulated and 1 up-regulated circRNAs (Table 1).

[0063] Table 1. 9 circRNA chip result analysis

[0064]

[0065] Note: P < 0.05 is statistically significant. Fc, fold change

[0066] The sequence of hsa_circ_0052124 is as follows (SEQ ID NO. 1):

[0067] hsa_circ_0052124 | NM_018555:

[0068] GCCAGCATCCTTCAGAAAAAGCATCCCCGAGGAGGAAGACGAATCGTTAAACATCTGAAAGGGTCAGGCCAGCATCCTTCAGAAAAAGCATCCCCGAGGAGGAAGACGAATCGTTAAACATCTTAGGTCAG

[0069] Example 3 verification test

[0070] A verification cohort was selected for the verification test.

[0071] (1) Test method

[0072] A. Design hsa_circ_0052124 primers

[0073] The designed target primer sequence is as follows:

[0074] a. Upstream amplification primer: 5'-CGTTAAACATCTTAGGTCAGGCCA-3'

[0075] b. Downstream amplification primer: 5'-CCTTTCAGATGTTTAACGATTCGTC-3'

[0076] qPCR reference gene: GAPDH

[0077] circRNA chip: Agilent Human (4*180K) chip

[0078] First, the full-length sequence of circRNA was obtained from the circBase database, and the 3' end of the sequence was moved to the 5' end to include splice site information; then, the primers were designed using Primer-BLAST to ensure that the primers span the splice site and adjust the primer parameters to meet the design requirements; finally, the specificity of the primers was verified by Primer-BLAST to ensure no non-specific amplification, and the verification results were optimized and adjusted.

[0079] B. Isolation of PBMCs from peripheral blood

[0080] Whole blood was collected, and after blood collection, the blood sample was diluted with culture medium, mixed, and then sample density separation liquid was added. PBMCs were extracted by Ficoll density gradient centrifugation.

[0081] C. RNA extraction

[0082] According to the operation manual of the miRNeasy Mini Kit kit, total RNA extraction was performed, and the extracted total RNA was electrophoresed and qualified for standby.

[0083] D. Reverse transcription

[0084] High Capacity cDNA Reverse Transcription Kits were used for reverse transcription, and 200 ng of RNA sample was reverse transcribed into cDNA.

[0085] E. qPCR detection

[0086] PowerUp TM SYBR TM Green Master Mix was mixed with cDNA and primer mixture for fluorescent quantitative PCR, with GAPDH as the reference to calculate 2 -ΔCT , so as to determine the relative expression of the gene.

[0087] (2) Test results

[0088] A. Relative expression of hsa_circ_0052124

[0089] RT-qPCR detection and group difference verification of the 9 candidate differentially expressed circRNAs were performed in 30 TB patients (TB group) and 30 healthy controls (HC group), respectively. Among them, the average relative expression of hsa_circ_0052124 in 30 TB samples (0.000441) was significantly lower than that in 30 healthy samples (0.002375), and the difference was statistically significant (P<0.0001), and the expression trend was consistent with that in the circRNAs microarray chip expression profile (Table 2 and Figure 1 ). The other 8 circRNAs could not be verified due to low expression abundance or lack of specific primers.

[0090] Table 2. qPCR detection of raw data (hsa_circ_0052124 relative expression)

[0091]

[0092]

[0093] B. ROC curve

[0094] The ROC curve analysis of the differentially expressed circRNA hsa_circ_0052124 was performed in 30 TB patients and 30 healthy controls using the receiver operating characteristic curve (ROC).

[0095] As shown in Figure 1 , the area under the ROC curve was 0.976 (95% CI: 0.940-1.000, P<0.0001), the sensitivity was 90% (95% CI: 73.5%-97.9%), and the specificity was 100% (95% CI: 88.4%-100.0%), which could effectively distinguish TB patients from healthy controls. Further determination of its threshold value was 0.000783, when the relative expression of hsa_circ_0052124 was ≤0.000783, the subject was a TB patient.

Claims

1. Use of a reagent for detecting the relative expression of a biomarker nucleotide sequence in the preparation of a reagent for differential diagnosis of a tuberculosis patient; the biomarker is hsa_circ_0052124; the biomarker nucleotide sequence is as shown in SEQ ID NO.

1.

2. Use according to claim 1, wherein When the relative expression of hsa_circ_0052124 in the biological sample of the subject is ≤ 0.000783, the subject is a tuberculosis patient.

3. Use according to claim 2, wherein the compound is ###0002### The biological sample of the subject is selected from blood, and the blood sample of the subject is at least one of plasma and / or serum.

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