A miRNA marker and kit for diagnosis and identification of tuberculosis

Abstract

The present invention belongs to the technical field of diagnostic markers, and specifically relates to a miRNA marker and a kit for the diagnosis and identification of tuberculosis. The miRNA is any one or any combination of the following three miRNAs, and the names and sequences are as follows: miR-342-3p, which is the SEQ ID NO:1 sequence; miR-199a-3p, which is the SEQ ID NO:2 sequence; miR-199b-3p, which is the SEQ ID NO:2 sequence. A kit for the diagnosis and identification of tuberculosis, the kit comprising primers designed for miRNA markers. The present invention innovatively discovered that the expression composition of peripheral blood miR-342-3p and miR-199a / b-3p is an important diagnostic marker, which provides a new direction for the hematological diagnosis of tuberculosis at the molecular level, and has important theoretical value and potential application value. High-efficiency auxiliary diagnosis of lung cancer and PTB can assist in the differential diagnosis of simple PTB and PTB combined with extrapulmonary tuberculosis, simple PTB and PTB combined with hemoptysis.

Description

Technical Field

[0001] The present invention belongs to the technical field of diagnostic markers, and in particular relates to a miRNA marker and a kit for diagnosing and identifying tuberculosis. Background Art

[0002] Tuberculosis is an infectious disease that WHO focuses on controlling. Early diagnosis of pulmonary tuberculosis (PTB) is very important for treatment and prevention of continued spread. When PTB occurs, PTB patients can act as active sources of infection to spread pathogens, continuously expanding the number of infected people. In addition, early diagnosis of tuberculosis is crucial for the treatment and survival of PTB patients. Therefore, early differential diagnosis of PTB is particularly important.

[0003] The current differential diagnosis methods have various deficiencies in distinguishing PTB from lung cancer and PTB subgroups. The main methods for diagnosing PTB currently used in clinical practice are:

[0004] (1) Sputum smear: ① Low positive rate: about 30%, usually 5000-10000 bacteria / ml are needed to get a positive result; ② Poor specificity: many mycobacteria can be stained, and further identification is needed to determine whether it is Mycobacterium tuberculosis; ③ Unable to distinguish between dead and live bacteria; ④ Many influencing factors: Affected by the technical level of the inspector and the quality of the collected sputum specimens. In summary, it can lead to a large number of missed diagnoses and misdiagnoses. (2) Bacterial culture: ① Long culture cycle (6-8 weeks); ② Low positive rate: about 30%-40%; ③ Further identification is needed to determine whether it is Mycobacterium tuberculosis. (3) Tuberculin test (PPD): The main problem is a high level of false positive results. A positive PPD only means that there has been tuberculosis infection, not that the disease is currently present. At the same time, the PPD test measurement is easily affected by many factors, such as BCG vaccination. (4) Detection of tuberculosis antigens: ① Difficulty in antibody preparation: It is very difficult to prepare highly active specific tuberculosis antibodies against tuberculosis antigens, which limits the large-scale application of this method; ② The antibody specificity is not ideal: Existing studies use the method of immunizing animals to prepare antiserum. Although high-titer tuberculosis antibodies can be obtained after purification, their specificity is not high and they will cross-react with non-tuberculous mycobacteria and even unrelated bacteria. (5) Interferon-γ release assay (IGRA): It is expensive and difficult to popularize, and the technology cannot perform specific and sensitive differential diagnosis of PTB subgroups; (6) Tuberculosis antibody detection: Both sensitivity and specificity are low. Based on the above problems, it is urgent to develop new diagnostic strategies.

[0005] MicroRNAs (miRNAs) as biomarkers: miRNAs are a new type of single-stranded non-coding small RNAs that are endogenous to cells and play an important regulatory role in pathological and physiological processes such as cell proliferation and apoptosis, organ development and differentiation, disease development, and tumor formation. In recent years, with the continuous deepening of research on miRNAs, its advantages in differential diagnosis of diseases are as follows: ① miRNAs are highly specific and highly conservative for different diseases; ② circulating miRNAs in body fluids such as serum or plasma have good stability, are stably expressed and can exist stably in the peripheral blood of normal people, and there is no significant individual difference; ③ blood specimens are easy to obtain, not easy to be contaminated, and the cost of detection is not high; it has great potential in the application field of biomarkers.

[0006] Currently, there are commercialized microRNA lung cancer early detection kit products on the market. However, in the differential diagnosis of PTB, there are still the following problems: 1. The differential diagnosis efficiency of lung cancer and PTB needs to be improved. For the differential diagnosis of PTB, its specificity (75.0%) needs to be improved, which has a great impact on the accuracy of diagnosis. 2. There are limitations in the auxiliary diagnosis of simple PTB and its subtypes, which involves the differentiation of patients with pneumonia and chronic obstructive pulmonary disease, and cannot analyze simple tuberculosis and its subtypes; 3. The number of marker molecule combinations is large and the cost is high; 4. The sample analysis volume is not large, which may affect the confidence. Therefore, finding a highly specific and sensitive miRNAs marker is the difficulty of this detection method. Summary of the invention

[0007] In view of the deficiencies in the prior art, the present invention provides a miRNA marker and a kit for the diagnosis and identification of tuberculosis, so as to improve the diagnostic efficacy of pulmonary tuberculosis, improve the ability to differentiate between PTB and lung cancer, improve the ability to differentiate between simple PTB and its subtypes, reduce the number of marker molecule combinations, and reduce costs.

[0008] In order to achieve the above object, the present invention adopts the following technical solution: a miRNA marker for diagnosis and identification of tuberculosis, wherein the miRNA is any one or any combination of the following three miRNAs, and the names and sequences are as follows:

[0009] miR-342-3p: UCUCACACAGAAAUCGCACCCGU, which is the sequence of SEQ ID NO: 1;

[0010] miR-199a-3p and miR-199b-3p: ACAGUAGUCUGCACAUUGGUUA, which is the sequence of SEQ ID NO: 2.

[0011] Furthermore, the miRNA marker is used for diagnosis and identification of tuberculosis.

[0012] A kit for diagnosing and identifying tuberculosis, comprising primers designed according to the miRNA marker according to claim 1.

[0013] Furthermore, the primers include reverse transcription primers designed according to each miRNA marker, specific upstream primers for fluorescence quantitative reaction, and specific downstream primers.

[0014] Furthermore,

[0015] The miR-342-3p reverse transcription primer sequence is shown in SEQ ID NO:4, the specific upstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:5, and the specific downstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:6;

[0016] The reverse transcription primer sequences of miR-199a-3p and miR-199b-3p are shown in SEQ ID NO:7, and the specific downstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:10;

[0017] The specific upstream primer sequence of the miR-199a-3p fluorescence quantitative reaction is shown in SEQ ID NO: 8.

[0018] The specific upstream primer sequence for the miR-199b-3p fluorescence quantitative reaction is shown in SEQ ID NO:9.

[0019] Furthermore, the kit also includes a plasma RNA extract, a reverse transcription reaction solution, a fluorescent quantitative PCR reaction solution, and an internal reference primer.

[0020] Furthermore, the internal reference is U6:

[0021] GUGCUCGCUUCGGCAGCACAUAUACUAAAAUUGGAACGAUACAGAGAAGAUUAGCAUGGCCCCUGCGCAAGGAUGACACGCAAAUUCGUGAAGCGUUCCAUAUUUUU, which is the sequence of SEQ ID NO: 3;

[0022] The internal reference U6 upstream primer sequence is shown in SEQ ID NO:11, and the reverse transcription primer and downstream primer are shown in SEQ ID NO:12.

[0023] Furthermore,

[0024] The plasma RNA extraction solution comprises: Trizol-LS reagent, chloroform, isopropanol, 75% ethanol, and RNase-free aqueous solution;

[0025] Furthermore, the reverse transcription reaction solution includes: plasma RNA, 5× reaction buffer, deoxyribonucleoside triphosphate mixture, ribonuclease inhibitor, improved reverse transcriptase, and RNase-free aqueous solution;

[0026] Furthermore, the fluorescent quantitative PCR reaction solution includes: TB Premix Ex Taq TM (TliRNaseH Plus) and RNase-free aqueous solution.

[0027] The benefits of the miRNA markers and kit for diagnosis and identification of tuberculosis of the present invention are as follows:

[0028] The present invention innovatively discovered that the expression combination of peripheral blood miR-342-3p and miR-199a / b-3p is an important diagnostic marker, which provides a new direction for the hematological diagnosis of tuberculosis at the molecular level, and has important theoretical value and potential application value. High-efficiency auxiliary diagnosis of lung cancer and PTB, AUC = 0.949, sensitivity: 88.30%, specificity, 89.23%, prediction accuracy, 86.70%. It can assist in the differential diagnosis of simple PTB and PTB combined with extrapulmonary tuberculosis, simple PTB and PTB combined with hemoptysis. The combination of 2-3 marker molecules can achieve auxiliary diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 The differentially expressed miRNAs in PTB patients according to the present invention;

[0030] Figure 2 The miRNA differentially expressed in lung cancer patients in the embodiment of the present invention;

[0031] Figure 3 The intersection of the Venne graph and the differential expression of miRNA in the embodiment of the present invention;

[0032] Among them, A: the intersection of the Venne graphs of the three data sets; B: the differential expression of the three miRNAs in PTB patients; C: the differential expression of the three miRNAs in LC patients; D: the differential expression of the three miRNAs in LC patients;

[0033] Figure 4 The expression levels of the three miRNAs in PTB and LC patients in the present invention are shown in the examples;

[0034] Among them, A: expression level of miRNA in PTB; B: expression level of miRNA in LC (GSE31568); C: expression level of miRNA in LC (GSE61741);

[0035] Figure 5 is the expression level of miRNA in the PTB group and the healthy control group according to the embodiment of the present invention;

[0036] Among them, AC: expression levels of miR-342-3p, miR-199a-3p, and miR-199b-3p in the PTB group and the healthy control group (*P < 0.05, **P < 0.01, ***P < 0.001);

[0037] Figure 6 The expression levels of three plasma miRNAs in the PTB group and lung cancer group in the example of the present invention;

[0038] Among them, AC: expression levels of miR-342-3p, miR-199a-3p, and miR-199b-3p in PTB group and lung cancer group (*P < 0.05, **P < 0.01, ***P < 0.001);

[0039] Figure 7 The expression levels of the three miRNAs in PTB combined with extrapulmonary tuberculosis in the present invention are shown in the examples;

[0040] Among them, AC: expression of miR-342-3p, hmiR-199a-3p and miR-199b-3p in PTB complicated with extrapulmonary tuberculosis (*P<0.05, **P<0.01, ***P<0.001);

[0041] Figure 8 The expression levels of the three miRNAs in PTB patients with hemoptysis in the present invention are shown in the examples;

[0042] Note: AC: expression of miR-342-3p, miR-199a-3p and miR-199b-3p in PTB with hemoptysis (*P<0.05, **P<0.01, ***P<0.001);

[0043] Fig. 9 The ROC curve of the serum miRNAs composition for diagnosing PTB in the pulmonary tuberculosis group and the healthy control group according to the embodiment of the present invention;

[0044] Fig.10 The ROC curve of the serum miRNAs composition for diagnosing PTB in the tuberculosis group and the lung cancer group in the embodiment of the present invention;

[0045] Fig.11The ROC curve of the serum miRNAs composition for diagnosing PTB in simple PTB and PTB combined with extrapulmonary PTB according to the embodiment of the present invention;

[0046] Fig.12 The ROC curve of the serum miRNAs composition for diagnosing PTB in simple PTB and PTB combined with hemoptysis in the embodiments of the present invention is shown. DETAILED DESCRIPTION

[0047] The specific implementation manner will be further described below in conjunction with the accompanying drawings.

[0048] The reagents and instruments in the following examples are all conventional experimental reagents and instruments.

[0049] Embodiment 1:

[0050] A miRNA marker for diagnosis and differentiation of tuberculosis:

[0051] 1. Data download:

[0052] The raw expression data of plasma-derived miRNAs were downloaded from the GEO database.

[0053] There were 172 healthy controls.

[0054] PTB sample data set (7 cases): GSE116542. Based on GPL19117 [miRNA-4] Affymetrix Multispecies miRNA-4 Array sequencing platform.

[0055] LC sample dataset (105 cases): GSE31568, GSE61741. Based on GPL9040 febit Homo Sapiens miRbase.

[0056] 2. Screening of differentially expressed miRNAs

[0057] The limma R package was used to screen the normalized miRNA expression data of PTB and LC patient samples. The screening criteria were: miRNA was upregulated in PTB samples (log2 Fold Change>1), downregulated in LC samples (log2 Fold Change<0) and P value <0.05. The ggplot package was used to draw heat maps and volcano maps.

[0058] Screening of PTB differentially expressed miRNAs

[0059] A total of 312 miRNAs with statistical significance (P < 0.05) were screened out. Figure 1), among which, there were 193 up-regulated differentially expressed miRNAs and 119 down-regulated differentially expressed miRNAs.

[0060] Screening for differentially expressed miRNAs in lung cancer

[0061] 142 and 395 miRNAs with statistical significance (P < 0.05) were screened in GSE31568 and GSE61741 datasets, respectively. Figure 2 A and B), among which, there are up-regulated miRNAs (67), down-regulated miRNAs (75), and up-regulated miRNAs (201), down-regulated miRNAs (194), respectively.

[0062] Venn Analysis

[0063] The Draw Venn Diagram software was used to analyze the upregulated miRNAs in PTB samples and the downregulated miRNAs in LC samples, and to identify the miRNA molecules with common intersections in the above datasets. The PTB patient GSE116542 dataset was intersected with the LC patient GSE31568 and GSE61741 datasets. The Venne analysis results showed that the three datasets intersected 3 common miRNA molecules, namely:

[0064] miR-342-3p, miR-199a-3p and miR-199b-3p ( Figure 3 A). Among them, miR-342-3p, miR-199a-3p and miR-199b-3p were upregulated in PTB patients and downregulated in LC patients ( Figure 3 BD). The expression levels of three common miRNA molecules in three data sets ( Figure 4 ).

[0065] miR-342-3p: UCUCACACAGAAAUCGCACCCGU, which is the sequence of SEQ ID NO: 1;

[0066] miR-199a-3p: ACAGUAGUCUGCACAUUGGUUA, which is the sequence of SEQ ID NO: 2;

[0067] miR-199b-3p: ACAGUAGUCUGCACAUUGGUUA, which is the sequence of SEQ ID NO: 2.

[0068] The endogenous reference is U6 (Mμs mμs cμlμs U6 small nμclear RNA-Rnμ6):

[0069] GUGCUCGCUUCGGCAGCACAUAUACUAAAAUUGGAACGAUACAGAGAAGAUUAGCAUGGCCCCUGCGCAAGGAUGACACGCAAAUUCGUGAAGCGUUCCAUAUUUUU, which is the sequence of SEQ ID NO: 3.

[0070] Embodiment 2:

[0071] A kit for diagnosing and identifying tuberculosis comprises primers designed according to miRNA markers, plasma RNA extract, reverse transcription reaction solution, fluorescent quantitative PCR reaction solution, and internal reference primers.

[0072] Design synthetic primers, miRNA marker primers and internal reference primers. The corresponding sequences are as follows:

[0073] miR-342-3p reverse transcription primers:

[0074] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACGGGT-3', the sequence is SEQ IDNO:4,

[0075] miR-342-3p upstream primer: 5'-GCGTCTCACACAGAAATCGC-3', sequence as SEQ ID NO: 5,

[0076] miR-342-3p downstream primer: 5'-AGTGCAGGGTCCGAGGTATT-3', sequence as SEQ ID NO: 6,

[0077] miR-199a-3p reverse transcription primers:

[0078] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTAACCA-3', the sequence is SEQ IDNO:7,

[0079] miR-199a-3p upstream primer: 5'-GCTGCGACAGTAGTCTGCACAT-3', sequence as SEQ ID NO: 8,

[0080] miR-199a-3p downstream primer: 5'-AGTGCAGGGTCCGAGGTATT-3', sequence as SEQ ID NO: 10,

[0081] miR-199b-3p reverse transcription primers:

[0082] 5'-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTAACCA-3', the sequence is SEQ IDNO:7,

[0083] miR-199b-3p upstream primer: 5'-GCGCGACAGTAGTCTGCACAT-3', sequence as SEQ ID NO: 9,

[0084] miR-199b-3p downstream primer: 5'-AGTGCAGGGTCCGAGGTATT-3', sequence as SEQ ID NO: 10,

[0085] U6 upstream primer: 5'-CTCGCTTCGGCAGCACA-3', sequence as SEQ ID NO: 11,

[0086] U6 reverse transcription primer and downstream primer: 5'-AACGCTTCACGAATTTGCGT-3', sequence as SEQ ID NO: 12,

[0087] The plasma RNA extraction solution includes: Trizol-LS reagent, chloroform, isopropanol, 75% ethanol, and RNAse-free aqueous solution; the reverse transcription reaction solution includes: plasma RNA, 5× reaction buffer, deoxyribonucleoside triphosphate mixture, ribonuclease inhibitor, improved reverse transcriptase, and RNAse-free aqueous solution; the fluorescent quantitative PCR reaction solution includes: TB Premix Ex Taq TM (Tli RNaseH Plus) and RNase-free aqueous solution.

[0088] The biomarker of the present invention has good stability, good diagnostic specificity and high sensitivity. The miRNA is not easy to degrade in the specimen and has high stability. The combined diagnostic efficacy of the three molecules is as follows: ①PTB: AUC=0.949, sensitivity: 88.30%, specificity, 89.23%, and prediction accuracy, 86.70%. ②PTB and lung cancer: AUC=0.9462, sensitivity: 98.94%, specificity: 80.00%, and prediction accuracy: 88.50%. It can assist in differential diagnosis of lung cancer and PTB subtypes, and use one or any combination of miR-342-3p and miR-199a / b-3p to differentially diagnose PTB, including PTB and lung cancer, simple PTB and its subtypes, such as PTB combined with extrapulmonary tuberculosis, and PTB combined with hemoptysis. The operation is simple and time-consuming. Compared with bacterial culture, the specimen collection process is not easy to be contaminated. The operation is simple. After reagentization, only simple RNA extraction, reverse transcription, and fluorescence quantitative PCR are required to analyze the sample, which is time-consuming. Compared with the interferon-γ release experiment, it has a good price advantage and is easy to promote and popularize; it reduces the number of marker molecule combinations and controls the basic cost.

[0089] Embodiment 3:

[0090] A method for using a kit for diagnosing and identifying tuberculosis,

[0091] 1. Extraction of Total RNA from Plasma

[0092] Sample collection: A total of 191 subjects were included, including 71 PTB patients, 55 LC patients, and 65 healthy controls. Among them, in the PTB patient group, there were 43 patients with simple PTB, 19 patients with PTB combined with extrapulmonary tuberculosis, and 9 patients with PTB and hemoptysis. Basic characteristics of the patients (Table 1).

[0093] Inclusion criteria: All samples were from a hospital. All experiments were approved by the ethics committee, and all participants signed informed consent. At the same time, basic information such as gender, age, and hospitalization number of the participants were collected. All patients included in the group were excluded from diseases such as syphilis, hepatitis B, and AIDS.

[0094] Table 1 Clinical characteristics of included subjects

[0095]

[0096] Strictly follow the relevant operating instructions of Trizol-LS reagent, and the extraction operation is as follows:

[0097] (1) Add 250 μL of plasma to an RNase-free centrifuge tube, and then add 750 μL of Trizol-LS reagent.

[0098] (2) Use a pipette to mix the sample thoroughly by pipetting it up and down.

[0099] (3) Place the mixed sample on an ice box for 5 minutes.

[0100] (4) Add 150 μL of chloroform to the RNase removal centrifuge tube.

[0101] (5) Mix the RNase-removing centrifuge tube containing the above reagents vigorously for 2 minutes.

[0102] (6) Place the EP tube on an ice box for 10 minutes.

[0103] (7) Centrifuge at 4°C, 12,000 g / min for 15 min. At this point, the contents of the EP tube containing the above reagents are separated into three layers. The upper layer is a colorless and clear aqueous phase layer (RNA is retained in this layer), the middle layer is white (DNA is retained in this layer), and the lower layer is a pink organic phase layer (protein is retained in this layer).

[0104] (8) Tilt the RNase-free centrifuge tube at 45° and carefully aspirate 300 μL of the aqueous phase twice using a pipette. At this time, be especially careful not to aspirate the contents of the middle and lower layers.

[0105] (9) Transfer 300 μL of the aqueous phase to a new RNase-free centrifuge tube.

[0106] (10) Add 600 μL of isopropanol to the above centrifuge tube and mix up and down.

[0107] (11) Place the RNase-removing centrifuge tube containing the above contents on an ice box for 10 minutes.

[0108] (12) Centrifuge the sample at 4°C, 12,000 g / min for 10 min. Slowly pour off the supernatant, leaving the RNA precipitated as filaments at the bottom of the RNase-free centrifuge tube.

[0109] (13) Add 1000 μL of 75% ethanol reagent to the above centrifuge tube to wash the RNA precipitated at the bottom of the RNase-removing centrifuge tube.

[0110] (14) Centrifuge the sample at 4°C, 12,000 g / min for 10 min. Then, slowly pour off the supernatant.

[0111] (15) Dry the RNA pellet at room temperature for 5 to 10 min.

[0112] (16) Use a pipette to draw up 10 μL of RNase-free aqueous solution to resuspend the RNA precipitated at the bottom of the RNase-free centrifuge tube. Gently pipette to fully mix the RNA precipitate and the RNase-free aqueous solution to form a uniform RNA solution.

[0113] The RNA aqueous solution was incubated in a metal bath at 60°C for 15 minutes, and reverse transcription was performed immediately afterwards.

[0114] 2. Reverse transcription of miRNA into cDNA

[0115] The reverse transcription process was carried out in strict accordance with the instructions of the PrimeScriptTMⅡ1st Strand cDNA Synthesis Kit of TaKaRa. The RNA aqueous solution was reverse transcribed into cDNA using the stem-loop method. The reaction system was as follows:

[0116] Prepare the following miRNA reaction system

[0117] Reverse transcription primer (RT Primer) (50 μM)

[0118]

[0119]

[0120] Incubate at 65°C in a metal bath for 5 min and cool rapidly on ice.

[0121] Add the above reagents to the following reverse transcription system

[0122]

[0123] Mix the above reagents and then perform reverse transcription according to the following reaction conditions.

[0124] 42℃60min

[0125] 95℃5min

[0126] 4℃15min

[0127] 3. Fluorescence quantitative PCR reaction

[0128] The RT-qPCR reaction process was carried out in strict accordance with the TB The reaction system was as follows:

[0129]

[0130] Seal the above reagents and centrifuge to mix. Perform RT-qPCR according to the following temperature reaction requirements.

[0131]

[0132] After the above reaction is completed, Melt Curve analysis is performed to detect the amplification product.

[0133] Using U6 as an endogenous reference, the relative quantitative calculation method was used to quantify the target plasma miRNA to be tested, and the calculation was performed using the formula 2-Δct (Δct = target miRNA-U6 endogenous reference).

[0134] The expression levels in the PTB group and the healthy control group, the expression in the lung cancer group, the expression in PTB combined with extrapulmonary tuberculosis, and the expression in PTB patients with hemoptysis ( Figure 5 , 6 , 7, 8).

[0135] 4. Statistical Analysis

[0136] The data obtained from the experiment were analyzed by SPSS 23.0 software. The statistical data between the groups were analyzed by independent sample t test, nonparametric Mann-Whitney U test and paired t test according to the distribution characteristics, and P < 0.05 was considered statistically significant. The data are expressed as SD ± SEM. The diagnostic performance analysis was performed by GraphPad Prism 8.0, and the AUC value, sensitivity and specificity in the ROC curve were used to evaluate the ability of the target miRNA as a diagnostic factor.

[0137] The ROC curve of plasma miR-342-3p and miR-199a / b-3p combination for diagnosing PTB was calculated by Logistic stepwise regression model. The regression equation of Logistic stepwise model was constructed through data calculation and analysis: logit(P)=-3.771-0.667(miR-342-3p)-17.906(miR-199a-3p)-10.673(miR-199b-3p). The ROC curve of serum miRNAs combination for diagnosing PTB ( Fig. 9 , 10 , 11, 12), the diagnostic efficacy of single miRNA molecules and their combination molecules (Tables 2, 3, 4, 5).

[0138] Table 2 Diagnostic value of three miRNAs in PTB

[0139]

[0140] Note: a:miR-342-3p+miR-199a-3p; b:miR-342-3p+miR-199b-3p; c:miR-199a-3p+miR-199b-3p; d:miR-342-3p+miR-199a-3p+miR-199b-3p.

[0141] Table 3 Diagnostic value of three miRNAs in PTB and lung cancer

[0142]

[0143] Note: a:miR-342-3p+miR-199a-3p; b:miR-342-3p+miR-199b-3p; c:miR-199a-3p+miR-199b-3p; d:miR-342-3p+miR-199a-3p+miR-199b-3p.

[0144] Table 4 Diagnostic value of miR-342-3p and miR-199a / b-3p in PTB combined with extrapulmonary tuberculosis

[0145]

[0146]

[0147] Note: a:miR-342-3p+miR-199a-3p; b:miR-342-3p+miR-199b-3p; c:miR-199a-3p+miR-199b-3p; d:miR-342-3p+miR-199a-3p+miR-199b-3p.

[0148] Table 5 Diagnostic value of three miRNAs in PTB with hemoptysis

[0149]

[0150] Note: a:miR-342-3p+miR-199a-3p;b:miR-342-3p+miR-199b-3p;c:miR-199a-3p+miR-199b-3p;d:miR-342-3p+miR-199a-3p+miR-199b-3p

[0151] Diagnostic performance analysis:

[0152] PTB: ① The diagnostic specificity of miR-342-3p single molecule was the highest, and the diagnostic sensitivity of miR-199b-3p single molecule was the highest. ② The sensitivity of miR-199a-3p and miR-199b-3p dual diagnosis was the same as that of triple diagnosis, but the specificity was slightly lower. ③ The triple diagnosis efficiency: AUC = 0.949, cutoff value > 0.53, sensitivity: 88.30%, specificity: 89.23%, prediction accuracy: 86.70%;

[0153] Lung cancer: ① The diagnostic sensitivity of miR-199a-3p single molecule is the highest, and the diagnostic specificity of miR-199b-3p and miR-342-3p single molecules is the same. ② The sensitivity, specificity, and cutoff value of miR-199a-3p and miR-199b-3p dual diagnosis are the same as those of triple diagnosis, which shows that dual diagnosis can play a good diagnostic effect. ③ Triple diagnosis efficiency: AUC = 0.9462, cutoff value ≤ 0.70, sensitivity: 98.94%, specificity: 80.00%, prediction accuracy: 88.50%;

[0154] PTB combined with extrapulmonary tuberculosis: ① The diagnostic specificity of miR-342-3p single molecule is the highest, and the diagnostic sensitivity of miR-199a / b-3p single molecule is the same. ② The sensitivity of miR-342-3p and miR-199a-3p dual diagnosis is lower than that of triple diagnosis, but it is better than triple diagnosis in terms of specificity, while the specificity and sensitivity of miR-342-3p and miR-199b-3p dual diagnosis are both the same as those of triple diagnosis, which shows that dual diagnosis can play a good diagnostic effect. ③ Triple diagnosis efficacy: AUC = 0.998, cutoff value > 0.07, sensitivity: 100.0%, specificity: 98.44%;

[0155] PTB with hemoptysis: ① The sensitivity of single molecular diagnosis of miR-342-3p and miR-199a-3p was equal, and the specificity of single molecular diagnosis of miR-199b-3p was the highest. ② The combined sensitivity of all dual diagnosis was equal to that of triple diagnosis, but the specificity was lower than that of triple diagnosis. ③ The efficacy of triple diagnosis: AUC = 0.995, cutoff value > 0.04, sensitivity: 100.0%, specificity: 95.31%, prediction accuracy: 86.70%.

[0156] Embodiment 4:

[0157] A method for using a kit for diagnosing and identifying tuberculosis,

[0158] 1. Blood collection and separation from suspected patients

[0159] Generally, blood is collected from patients by venous blood sampling (heparin anticoagulation is prohibited). Plasma is separated by centrifugation at 3000rpm for 15min.

[0160] 2. Fluorescence quantitative PCR

[0161] (1) The extracted RNA aqueous solution was reverse transcribed into cDNA using the stem-loop method, and the reaction system was as follows:

[0162] Prepare the following miRNA reaction system

[0163] Reverse transcription primer (RT Primer) (50 μM)

[0164]

[0165] Incubate at 65°C in a metal bath for 5 min and cool rapidly on ice.

[0166] Add the above reagents to the following reverse transcription system

[0167]

[0168] Mix the above reagents and then perform reverse transcription according to the following reaction conditions.

[0169] 42℃60min

[0170] 95℃5min

[0171] 4℃15min

[0172] (2) The cDNA obtained by reverse transcription was subjected to fluorescent quantitative PCR, and the reaction system was as follows:

[0173]

[0174]

[0175] Seal the above reagents and centrifuge to mix. Perform RT-qPCR according to the following temperature reaction requirements.

[0176]

[0177] After the above reaction is completed, Melt Curve analysis is performed to detect the amplification product.

[0178] Using U6 as an endogenous reference, the relative quantitative calculation method was used to quantify the target plasma miRNA to be tested, and the calculation was performed using the formula 2-Δct (Δct = target miRNA-U6 endogenous reference).

[0179] 3. Interpretation of results

[0180] In the embodiment, the result interpretation is based on the triple diagnosis of PTB by miR-342-3p and miR-199a / b-3p as an example. In addition, it is not excluded that any molecule of miR-342-3p and miR-199a / b-3p and their combination have better differential diagnosis ability.

[0181] ΔCt=Ct(miRNA)-Ct(U6 endogenous reference)

[0182] Using U6 as an endogenous reference, the relative quantitative calculation method was used to quantify the target plasma miRNA. The calculation was performed using the 2-Δct formula.

[0183] logit(P)=-3.771-0.667(miR-342-3p)-17.906(miR-199a-3p)-10.673(miR-199b-3p)

[0184] The cut-off value for diagnosing PTB was >0.53.

[0185] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable ordinary technicians in the field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made based on the essence of the content of the present invention should be included in the protection scope of the present invention.

Claims

1. Use of a reagent for detecting miRNA markers in the preparation of a kit for diagnosis and identification of pulmonary tuberculosis, It is characterized in that The kit comprises: primers designed according to miRNA markers, The primers include reverse transcription primers designed according to each miRNA marker, specific upstream primers for fluorescence quantitative reaction, and specific downstream primers. The miRNA is a combination of the following three miRNAs, whose names and sequences are as follows: miR-342-3p: UCUCACACAGAAAUCGCACCCGU, which is the sequence of SEQ ID NO: 1; miR-199a-3p and miR-199b-3p: ACAGUAGUCUGCACAUUGGUUA, which is the sequence of SEQ ID NO: 2, The miR-342-3p reverse transcription primer sequence is shown in SEQ ID NO:4, the specific upstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:5, and the specific downstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:6; The reverse transcription primer sequences of miR-199a-3p and miR-199b-3p are shown in SEQ ID NO:7, and the specific downstream primer sequence of the fluorescence quantitative reaction is shown in SEQ ID NO:10; The specific upstream primer sequence of the miR-199a-3p fluorescence quantitative reaction is shown in SEQ ID NO:

8. The specific upstream primer sequence for the miR-199b-3p fluorescence quantitative reaction is shown in SEQ ID NO:

9.

2. The use according to claim 1, Features: The kit also includes a plasma RNA extract, a reverse transcription reaction solution, a fluorescent quantitative PCR reaction solution, and an internal reference primer.

3. The use according to claim 2, Features: The internal reference is U6: GUGCUCGCUUCGGCAGCACAUAUACUAAAAUUGGAACGAUACAGAGAAGAUUAGCAUGGCCCCUGCGCAAGGAUGACACGCAAAUUCGUGAAGCGUUCCAUAUUUUUU, which is SEQ ID NO: 3; The internal reference U6 upstream primer sequence is shown in SEQ ID NO:11, and the reverse transcription primer and downstream primer are shown in SEQ ID NO:

12.

4. The use according to claim 2, Features: The plasma RNA extraction solution includes: Trizol-LS reagent, chloroform, isopropanol, 75% ethanol, and RNase-free aqueous solution.

5. The use according to claim 2, Features: The reverse transcription reaction solution comprises: plasma RNA, 5× reaction buffer, deoxyribonucleoside triphosphate mixture, ribonuclease inhibitor, improved reverse transcriptase, and RNase-free aqueous solution.

6. The use according to claim 2, Features: The fluorescent quantitative PCR reaction solution includes: TB Green® Premix Ex Taq™ (Tli RNaseH Plus) and RNase-free aqueous solution.

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