CN110305953A - Application of a system for detecting miRNA expression in the preparation of products to differentiate between tuberculous meningitis and viral meningitis - Google Patents

Abstract

The invention discloses a kind of systems for detecting miRNA expression quantity to distinguish the application in tubercular meningitis and viral meningitis product in preparation；The miRNA is four kinds, three kinds, two kinds or a kind of in hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p and hsa-miR-199a-5p.Present invention discloses the miRNA spectrums in tubercular meningitis and the peripheral blood mononuclear cells of Patients with Virus Meningitis, be conducive to the pathogenesis for being best understood from both diseases, more importantly identification obtains 4 miRNA that can be used for differentiation or supplementary globe tubercular meningitis and viral meningitis, and the diagnosis for improving tubercular meningitis has a very important significance.

Description

A system for detecting miRNA expression in preparation to distinguish tuberculous meningitis from viral Use in meningitis products

technical field

The invention relates to the field of biotechnology, in particular to the application of a system for detecting miRNA expression in preparing a product for distinguishing tuberculous meningitis from viral meningitis.

Background technique

Tuberculous meningitis (TBM) is a very serious chronic infection of the central nervous system (CNS) caused by Mycobacterium tuberculosis (M.TB) infection, accounting for approximately 1% of all active tuberculosis- 2%, and about 8% in extrapulmonary tuberculosis. Although there is currently no exact epidemiological data on the incidence of tuberculous meningitis in China, according to the national tuberculosis epidemiological survey data, it is estimated that the prevalence of tuberculous meningitis is about 5/100,000. Although the incidence of tuberculous meningitis is relatively low, in countries with a high burden of tuberculosis, the mortality and morbidity rates may reach 44%-69%. Delays in diagnosis and treatment are considered to be the main factors contributing to the high mortality in patients with tuberculous meningitis. Existing diagnostic methods for tuberculous meningitis mainly rely on cerebrospinal fluid Mycobacterium tuberculosis culture, cerebrospinal fluid acid-fast bacilli smear and cerebrospinal fluid XpertMTB/RIF detection, but the sensitivity is low, and it is difficult to obtain clinical evidence for diagnosis, which leads to delayed treatment, and delayed treatment makes Tuberculous meningitis is aggravated and has a poor prognosis. Tuberculous meningitis is similar to other viral meningitis, bacterial meningitis and fungal meningitis (mainly cryptococcal meningitis) in clinical symptoms, signs, and routine biochemical manifestations of cerebrospinal fluid. It is important to differentiate between meningitis and other chronic infectious meningitis. Fortunately, with the use of antibiotics, the incidence of bacterial meningitis has been decreasing year by year and it is easy to diagnose. Differential diagnosis becomes the biggest challenge. In order to realize the differential diagnosis of these two diseases, there are continuous researches to carry out the identification and verification of novel biomarkers to improve the sensitivity and specificity of the diagnosis of tuberculous meningitis.

microRNA (miRNA) is a conserved small non-coding RNA of 18-25 nucleotides in length, involved in gene expression and regulation of various biological signaling pathways, including cell proliferation, differentiation, apoptosis, immune response and angiogenesis Wait. Previous studies have found that the abnormal expression of miRNAs in the tissue or blood of patients with active tuberculosis is closely related to the occurrence and development of the disease. But so far, only one study has used microarrays to identify differential miRNA profiles between tuberculous meningitis and healthy individuals, and another study has only validated the association of miR-29 with childhood tuberculous meningitis. Screening and validation of differential miRNA profiles in tuberculous meningitis and viral meningitis have not been performed.

Therefore, it is of great significance to screen the differential miRNA profiles of tuberculous meningitis and viral meningitis for clinical differential diagnosis.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is how to distinguish patients with tuberculous meningitis from patients with viral meningitis.

In order to solve the above technical problems, the present invention provides the application of a system for detecting miRNA expression in preparing a product for distinguishing or assisting in distinguishing between patients with tuberculous meningitis and patients with viral meningitis;

The miRNAs are four, three, two or one of hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p and hsa-miR-199a-5p.

In the above application, the hsa-miR-126-3p is the RNA shown in the sequence 1, the hsa-miR-130a-3p is the RNA shown in the sequence 2, and the hsa-miR-151a-3p is the sequence 3 The RNA shown, the hsa-miR-199a-5p is the RNA shown in sequence 4.

In the above application, the system for detecting the expression of miRNA includes a system for detecting the expression of hsa-miR-126-3p, a system for detecting the expression of hsa-miR-130a-3p, and a system for detecting the expression of hsa-miR-151a-3p. One, two, three or four of the systems, systems for detecting the expression level of hsa-miR-199a-5p, alone or in combination.

In the above-mentioned application, the system for the detection of miRNA expression is the following M1) or M2):

M1) a system for detecting the expression of the miRNA by quantitative PCR;

M2) A system for detecting the expression level of the miRNA using a high-throughput microarray chip.

The system may include reagents and/or kits and/or instruments, in particular:

The system for detecting the expression of hsa-miR-126-3p may include reagents and/or kits and/or instruments for detecting the expression of hsa-miR-126-3p, such as detecting hsa-miR by a high-throughput microarray chip -Reagents, kits and instruments required for the expression level of 126-3p or reagents, kits and instruments required for detecting the expression level of hsa-miR-126-3p by quantitative PCR. More specifically, the system for detecting the expression level of hsa-miR-126-3p by quantitative PCR may include a set of primers, probe sets, kits and/or quantitative PCR for amplifying the full length or fragment of hsa-miR-126-3p. Other reagents and/or instruments required. Of course, the above-mentioned system for detecting the expression of hsa-miR-126-3p may only consist of PCR primer pairs for amplifying the full length or fragment of hsa-miR-126-3p, or it may only be composed of detecting the expression of hsa-miR-126-3p Amount of kit composition. The PCR primer pair for amplifying the full length or fragment of hsa-miR-126-3p and other reagents required for quantitative PCR reaction can be packaged independently.

The system for detecting the expression of hsa-miR-130a-3p may include reagents and/or kits and/or instruments for detecting the expression of hsa-miR-130a-3p, such as detecting hsa-miR by a high-throughput microarray chip -Reagents, kits and instruments required for the expression level of 130a-3p or reagents, kits and instruments required for detecting the expression level of hsa-miR-130a-3p by quantitative PCR. More specifically, the system for detecting the expression level of hsa-miR-130a-3p by quantitative PCR may include a set of primers, a set of probes, a kit and/or quantitative PCR for amplifying the full length or fragment of hsa-miR-130a-3p. Other reagents and/or instruments required. Of course, the above-mentioned system for detecting the expression of hsa-miR-130a-3p may only consist of PCR primer pairs for amplifying the full length or fragment of hsa-miR-130a-3p, or it may only be composed of detecting the expression of hsa-miR-130a-3p Amount of kit composition. The PCR primer pair for amplifying the full length or fragment of hsa-miR-130a-3p and other reagents required for quantitative PCR reaction can be packaged independently.

The system for detecting the expression of hsa-miR-151a-3p may include reagents and/or kits and/or instruments for detecting the expression of hsa-miR-151a-3p, such as detecting hsa-miR by a high-throughput microarray chip -Reagents, kits and instruments required for the expression level of 151a-3p or reagents, kits and instruments required for detecting the expression level of hsa-miR-151a-3p by quantitative PCR. More specifically, the system for detecting the expression level of hsa-miR-151a-3p by quantitative PCR can include a set of primers, probe sets, kits and/or quantitative PCR for amplifying the full length or fragment of hsa-miR-151a-3p. Other reagents and/or instruments required. Of course, the above-mentioned system for detecting the expression of hsa-miR-151a-3p may only consist of PCR primer pairs for amplifying the full length or fragment of hsa-miR-151a-3p, or it may only be composed of detecting the expression of hsa-miR-151a-3p Amount of kit composition. The PCR primer pair for amplifying the full length or fragment of hsa-miR-151a-3p and other reagents required for quantitative PCR reaction can be packaged independently.

The system for detecting the expression of hsa-miR-199a-5p may include reagents and/or kits and/or instruments for detecting the expression of hsa-miR-199a-5p, such as detecting hsa-miR by a high-throughput microarray chip -Reagents, kits and instruments required for the expression level of 130a-3p or reagents, kits and instruments required for detecting the expression level of hsa-miR-199a-5p by quantitative PCR. More specifically, the system for detecting the expression level of hsa-miR-199a-5p by quantitative PCR may include a set of primers, probe sets, kits and/or quantitative PCR for amplifying the full length or fragment of hsa-miR-199a-5p. Other reagents and/or instruments required. Of course, the above-mentioned system for detecting the expression of hsa-miR-199a-5p may only consist of PCR primer pairs for amplifying the full length or fragment of hsa-miR-199a-5p, or it may only be composed of detecting the expression of hsa-miR-199a-5p Amount of kit composition. The PCR primer pair for amplifying the full length or fragment of hsa-miR-199a-5p and other reagents required for quantitative PCR reaction can be packaged independently.

In above-mentioned application, the probe that described detection hsa-miR-126-3p adopts is Assay ID ^* 002228, the probe that detection hsa-miR-130a-3p adopts is Assay ID ^* 000454, detects hsa-miR-151a The probe used for -3p was Assay ID ^* 002254, and the probe used for the detection of hsa-miR-199a-5p was Assay ID ^* 000498, and the above probes were all purchased from American ABI Company.

In the above application, the system for detecting the miRNA expression level further includes a data processing device, and the data processing device is configured to convert the miRNA expression level from the object to be measured into the discrimination result of the object to be measured.

Specifically, the data processing device includes a data input module, a data comparison module and a conclusion output module; wherein, the data input module is used to input the miRNA expression level of the object to be tested, and the data comparison module is used to input the miRNA expression level of the object to be tested. The miRNA expression levels of the objects to be tested are compared, and the conclusion output module is used to output the discrimination results of the objects to be tested: if the expression level of hsa-miR-126-3p is less than or equal to 1.49, the object to be tested is tuberculous meningitis The patient or candidate is a patient with tuberculous meningitis; when the expression of hsa-miR-126-3p is greater than 1.49, the subject to be tested is or a candidate for viral meningitis; if the expression of hsa-miR-130a-3p is less than or equal to 18.19 When hsa-miR-130a-3p expression level is greater than 18.19, the test object is or candidate for viral meningitis patients; if hsa-miR-151a-3p expression When the expression level of hsa-miR-151a-3p is greater than or equal to 120.1, the test object is or can be a candidate for viral meningitis patients; if hsa-miR-151a-3p expression level is greater than 120.1 When the expression level of 199a-5p is less than or equal to 0.0006, the subject to be tested is or can be considered as a patient with tuberculous meningitis; when the expression of hsa-miR-199a-5p is greater than 0.0006, the subject to be tested is or can be selected as a patient with viral meningitis; If the probability value of the four miRNA combinations is greater than 0.61, the subject to be tested is or can be considered as a patient with tuberculous meningitis; if the probability value of the combination is less than or equal to 0.61, the subject to be tested is or can be considered as a patient with viral meningitis.

The above probability values are the probability values obtained by combining the four miRNAs using the Logistic regression method.

The present invention also provides the application of the system for distinguishing or assisting in distinguishing tuberculous meningitis patients from viral meningitis patients using the miRNA as a marker in preparing a product for distinguishing or assisting in distinguishing tuberculous meningitis patients from viral meningitis patients .

The above-mentioned system for distinguishing or assisting in distinguishing patients with tuberculous meningitis from patients with viral meningitis is the above-mentioned system for detecting the expression level of miRNA.

The present invention further provides a product for distinguishing or assisting in distinguishing patients with tuberculous meningitis from patients with viral meningitis, the product being the above-mentioned system for detecting miRNA expression level.

In the present invention, the miRNA expression level may be the expression level of miRNA in blood; specifically, it may be the expression level of miRNA in peripheral blood mononuclear cells.

The present invention further provides a method for distinguishing or assisting in distinguishing patients with tuberculous meningitis from patients with viral meningitis, including detecting hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR- Expression levels of four, three, two, or one of 151a-3p and hsa-miR-199a-5p, according to hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a The expression levels of four, three, two or one of -3p and hsa-miR-199a-5p determine whether the test object is a patient with tuberculous meningitis or a patient with viral meningitis.

In the present invention, when the tuberculous meningitis patients and the viral meningitis patients are distinguished by detecting the expression level of hsa-miR-126-3p, when the expression level of hsa-miR-126-3p is less than or equal to 1.49, the object to be tested is a candidate or a candidate Patients with tuberculous meningitis; when the expression level of hsa-miR-126-3p is greater than 1.49, the subject to be tested is or is a candidate for patients with viral meningitis. When detecting the expression of hsa-miR-130a-3p to distinguish patients with tuberculous meningitis from patients with viral meningitis, when the expression level of hsa-miR-130a-3p is less than or equal to 18.19, the object to be tested is or is a candidate for tuberculous meningitis patients; when the expression level of hsa-miR-130a-3p is greater than 18.19, the subject to be tested is or a candidate for viral meningitis. When detecting the expression of hsa-miR-151a-3p to distinguish patients with tuberculous meningitis and patients with viral meningitis, when the expression of hsa-miR-151a-3p is less than or equal to 120.1, the test object is or can be considered as tuberculous meningitis Patients; when the expression level of hsa-miR-151a-3p is greater than 120.1, the subject to be tested is or a candidate for viral meningitis. When detecting the expression of hsa-miR-199a-5p to distinguish patients with tuberculous meningitis from patients with viral meningitis, when the expression of hsa-miR-199a-5p is less than or equal to 0.0006, the test object is or can be considered as tuberculous meningitis Patients; when the hsa-miR-199a-5p expression level is greater than 0.0006, the test object is or can be a candidate for viral meningitis patients. When the combined expression levels of the four miRNA combinations distinguish patients with tuberculous meningitis from those with viral meningitis, the logistic regression method is used to obtain the probability value. If the probability value is greater than 0.61, the test object is or is a candidate for tuberculous meningitis patients; probability If the value is less than or equal to 0.61, the object to be tested is or a candidate for viral meningitis. The area under the ROC curve (AUC) of the four miRNAs of the present invention for differentiating tuberculous meningitis and viral meningitis respectively is greater than 0.70, the sensitivity is greater than 78%, and the specificity is greater than 56%, indicating that the four miRNAs are all It can be used to distinguish patients with tuberculous meningitis from those with viral meningitis. The combined area under the ROC curve of the 4 miRNAs [AUC=0.893 (0.788-0.957)], with a sensitivity of 90.6% (75.0%-98.0%) and a specificity of 86.7% (69.3%-96.2%), with better Ability to distinguish patients with tuberculous meningitis from those with viral meningitis.

In the present invention, the miRNA expression level is the relative expression level of miRNA relative to U6SnRNA.

In the present invention, the subject to be tested is a patient with meningitis to be tested.

The invention discloses the miRNA profiles in the peripheral blood mononuclear cells of patients with tuberculous meningitis and viral meningitis, which is beneficial to better understand the pathogenesis of these two diseases, and more importantly, to identify and obtain miRNA profiles that can be used to differentiate or The four miRNAs that assist in distinguishing tuberculous meningitis from viral meningitis are of great significance for improving the diagnosis of tuberculous meningitis.

Description of drawings

Figure 1 shows the differential expression analysis of 6 differential miRNAs in expanded samples (TBM=32, VM=30, HCs=34); among them, A-F are hsa-miR-126-3p, hsa-miR-130a-3p, Expression difference analysis of hsa-miR-151a-3p, hsa-miR-199a-5p, hsa-miR-642a-3p and hsa-miR-4299.

Figure 2 shows the performance evaluation of 4 differential miRNAs and their combinations in the differential diagnosis of tuberculous meningitis and viral meningitis, and normal people; among them, A is the control group of patients with viral meningitis and patients with tuberculous meningitis as the disease The ROC curve of the differential diagnosis of the group; B is the ROC curve of the differential diagnosis of the normal control group and the patients with tuberculous meningitis as the disease group.

Detailed ways

The following examples facilitate a better understanding of the present invention, but do not limit the present invention. The experimental methods used in the following examples are conventional methods unless otherwise specified. The materials, reagents, etc. used in the following examples can be obtained from commercial sources unless otherwise specified.

Tuberculous meningitis (TBM) patients and viral meningitis (VM) patients in the following examples have the following symptoms:

Tuberculous meningitis: The patient has clinical manifestations such as fever, headache, projectile vomiting, meningeal irritation, and increased intracranial pressure, accompanied by one of the following two: (1) cerebrospinal fluid positive for Mycobacterium tuberculosis, positive PCR or Meningeal pathology is positive; (2) Clinical diagnosis of meningitis with the above indicators negative (negative for bacteria and fungi in cerebrospinal fluid) is combined with the following 3 items: 1) Brain MRI has intracranial nodules, hydrocephalus, cerebral edema and basal cistern exudation 2. Combined with other parts of tuberculosis: multiple miliary nodules in the lungs on chest CT, or pulmonary patchy cavity lesions with sputum collection of bacteria or positive culture; CT of kidneys, bones and joints showed typical tuberculosis manifestations with urine, lymph nodes, joints M.TB culture or pathological positive in effusion; ③ good effect of anti-tuberculosis treatment.

Viral meningitis: acute or subacute onset, with or without a history of viral infection 1-3 weeks before illness. Patients present with signs of brain parenchymal damage such as fever, headache, seizures, mental changes, disturbance of consciousness, and/or signs of neurological localization. EEG and head MRI showed abnormal lesions. Specific viral antibodies were detected in blood or cerebrospinal fluid, or viral DNA was detected by PCR. Cerebrospinal fluid pressure was normal or elevated, white blood cells were slightly elevated, and antiviral and symptomatic treatment was effective. No evidence of bacterial, tuberculosis and fungal infections.

The sequences of the four miRNAs in the following examples are as follows: the nucleotide sequence of hsa-miR-126-3p is 5′-CAGUGCAAUGUUAAAAGGGCAU-3′ (SEQ ID NO: 1), the nucleotide sequence of hsa-miR-130a-3p is 5'-UCGUACCGUGAGUAAUAAUGCG-3' (sequence 2), the nucleotide sequence of hsa-miR-151a-3p is 5'-CUAGACUGAAGCUCCUUGAGG-3' (sequence 3) and the nucleotide sequence of hsa-miR-199a-5p It is 5'-CCCAGUGUUCAGACUACCUGUUC-3' (sequence 4).

Example 1. Screening and verification of differential miRNA expression profiles:

1. Identification of 6 differential miRNAs by high-throughput microarray chip

The differential miRNA expression profiles in peripheral blood mononuclear cells of 4 patients with tuberculous meningitis (TBM), 4 patients with viral meningitis (VM) and 4 healthy people (HCs) were identified and analyzed by high-throughput microarray chip. The results are shown in Table 1. Twenty-eight differential miRNAs were screened between tuberculous meningitis and viral meningitis (P<0.05), and 11 differential miRNAs were obtained between tuberculous meningitis and healthy people (P<0.05). ; Among them, 6 miRNAs (hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p, hsa-miR-199a-5p, hsa-miR-642a-3p and hsa-miR -4299) is a specific miRNA for tuberculous meningitis, and there are statistical differences between viral meningitis and healthy people.

Table 1 Analysis results of differential miRNAs

2. qPCR to verify the differential expression of 6 differential miRNAs between groups

Six tuberculous meningitis-specific miRNAs (i.e. hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p, hsa-miR-199a-5p, hsa-miR-642a- 3p and hsa-miR-4299) were verified by qPCR, and the specific test steps were as follows:

1) Isolation of peripheral blood mononuclear cells (PBMCs):

1) 4ml of peripheral blood was collected with an EDTA anticoagulant blood collection tube.

2) Within 2 hours after blood collection, the whole blood samples were mixed with an equal volume of RPMI 1640 medium or normal saline, carefully added to the upper layer of Ficoll lymphocyte separation medium in a volume ratio of 2-3:1, and centrifuged at 1000g at 18°C for 22 minutes.

3) Take the white, cloudy PBMCs layer with a pipette and transfer it to a 15ml conical centrifuge tube, add 10ml AIM-V or RPMI1640 medium, and centrifuge at 600g at 18°C for 7 minutes.

4) After centrifugation, carefully remove the supernatant, add 1ml of 1xPBS, gently re-spin the cell pellet, add 1xPBS to 10ml, and centrifuge at 350g at 18°C for 7 minutes.

5) After centrifugation, the supernatant was carefully discarded, and 700ul QIAZOL (QIAGEN#79306) was used to fully lyse the cells to extract RNA.

2), RNA extraction (QIAGEN#217004 kit):

1) After the cells were lysed by QIAZOL, fully vortex and mix, add 140ul of chloroform, vortex and mix for 15s, and let stand at room temperature for 2min.

2) 12000g, 4 degrees centrifugation for 20min.

3) Carefully aspirate about 300ul of the supernatant, add 1.5 times anhydrous ethanol, mix well, add it to the spin column, and centrifuge at 10,000g at room temperature for 15s.

4) Add 700ul RWT buffer to the spin column and centrifuge at 10000g for 15s at room temperature.

5) Add 500ul RPE buffer to the spin column and centrifuge at 10000g for 15s at room temperature.

6) Add 500ul of 80% ethanol to the spin column and centrifuge at 10000g at room temperature for 2min.

7) Put the spin column in a clean collection tube and centrifuge at 15000g at room temperature for 2min.

8) Place the spin column in a clean EP tube, add 25ul RNase-free ddH ₂ O to the spin column, place at room temperature for 2 minutes, centrifuge at 10000g for 1 minute, and collect RNA.

3), qPCR detection:

Reverse transcription is carried out by using a reverse transcription kit (the reverse transcription kit is a product of ABI company, the article number is 4366596);

hsa-miR-126-3p was detected with Assay ID ^* 002228 probe set, hsa-miR-130a-3p was detected with Assay ID ^* 000454 probe set, hsa-miR-151a-3p was detected with Assay ID ^* 002254 Probe set for detection, hsa-miR-199a-5p using Assay ID ^* 000498 probe set for detection, hsa-miR-642a-3p using Assay ID ^* 474715_mat probe set for detection and hsa-miR-4299 Use Assay ID ^* 241744_mat probe set for detection, and the above probe set is a product of American ABI company;

The internal reference gene is U6SnRNA (Taqman probe set of ABI company, cat#4395470), and the corresponding target sequence of the internal reference gene is (found from the ABI probe library): GUGUCGCCUUCGGCAGCACAUAUACUAAAAUUGGAACGAUACAGAGAAGAUUAGCAUGGCCCCUGCGCAAGGAU6ACACGCAAAUUCGUGAAGCGUUCCAUAUUUU.

1) Prepare the reverse transcription reaction solution in a 0.2ml PCR tube in the following proportions:

Among them, 100mM dNTPs, Multiscribe Reverse Transcriptase, 10×ReverseTranscription Buffer, and Rnase Inhibitor (20U/ul) are all from reverse transcription kits; 5×RT primers corresponding to different miRNAs are from corresponding probe sets.

2) Place the PCR tube on the PCR machine and run the following procedure to obtain the reverse transcription product:

16℃ 30min

42℃ 50min

85℃ 5min

4°C ∞

3) Prepare PCR detection solution in the following proportions and add it to the 96-well reaction plate:

Reagent ingredients Volume (ul) 2×Taqman Universal PCR Buffer 10 20×Taqman MicroRNA Assay Mix 1 reverse transcript 1.25 ddH₂O 7.75 total 20

Among them, 2×Taqman Universal PCR Buffer is a product of ABI Company, and the catalog number is 4440038; 20×Taqman MicroRNA Assay Mix corresponding to different miRNAs comes from the corresponding probe set.

4) Put the 96-well plate into the ABI 7900 fluorescence quantitative PCR instrument, and run the following program:

The relative expression of each miRNA was calculated by the 2 ^-ΔCt method. The calculation formula was as follows: 2- ^ΔCT = 2- ^{(CT target gene-CT reference gene)} , and the detection results are shown in Table 2. The chip results were consistent.

Table 2 Validation results of real-time fluorescence quantitative PCR for 6 differentially expressed miRNAs

3. Expand the sample to verify the differential expression of differential miRNAs between groups

qPCR was used to verify that hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p, hsa-miR-199a-5p, hsa-miR-642a-3p and hsa-miR-4299 in tuberculosis The differences in expression among three groups of people: patients with meningitis, patients with viral meningitis and normal people, the specific steps are as follows:

Select 32 patients with tuberculous meningitis, 30 patients with viral meningitis and 34 healthy people, and detect hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a- The expression of 3p, hsa-miR-199a-5p, hsa-miR-642a-3p and hsa-miR-4299 in the above populations, the results are shown in Table 3; the differences between the two groups were analyzed, and the results were shown in Figures 1 and 1. As shown in Table 4, 4 miRNAs (hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p and hsa-miR-199a-5p) were detected in the tuberculous meningitis group (Table 4). The expression in the "TBM group") was still significantly lower than that in the viral meningitis group (the "VM group" in the table) and the healthy group (the "HCs group" in the table), and the difference was statistically significant ( n=96, P<0.01).

Table 3 The expression results of 4 miRNAs in different groups (TBM=32, VM=30, HCs=34) detected by qPCR detection method (relative expression amount*1000)

Table 4 Expression difference analysis of 6 miRNAs in different groups (TBM=32, VM=30, HCs=34)

4. Performance evaluation of four miRNAs and their combinations in distinguishing TBM from the other two groups

1) Distinguishing methods of identification

1. The method of distinguishing patients with tuberculous meningitis from patients with viral meningitis by using the expression of hsa-miR-126-3p relative to U6SnRNA (this method is referred to as distinguishing patients with tuberculous meningitis and patients with viral meningitis hsa-miR- 126-3p method) when the expression level of hsa-miR-126-3p is less than or equal to 1.49, it is a patient with tuberculous meningitis; when the expression level of hsa-miR-126-3p is greater than 1.49, it is a patient with viral meningitis.

2. The method of distinguishing patients with tuberculous meningitis from patients with viral meningitis using the expression of hsa-miR-130a-3p relative to U6 SnRNA (this method is referred to as hsa-miR for distinguishing patients with tuberculous meningitis and patients with viral meningitis). -130a-3p method), when the expression level of hsa-miR-130a-3p is less than or equal to 18.19, it is a patient with tuberculous meningitis; when the expression level of hsa-miR-130a-3p is greater than 18.19, it is a patient with viral meningitis.

3. The method of using hsa-miR-151a-3p relative to U6 SnRNA expression to distinguish patients with tuberculous meningitis from patients with viral meningitis (this method is referred to as hsa-miR for distinguishing patients with tuberculous meningitis from patients with viral meningitis). -151a-3p method), when the expression level of hsa-miR-151a-3p is less than or equal to 120.1, it is a patient with tuberculous meningitis; when the expression level of hsa-miR-151a-3p is greater than 120.1, it is a patient with viral meningitis.

4. The method of using hsa-miR-199a-5p relative to U6SnRNA expression to distinguish tuberculous meningitis patients from viral meningitis patients 199a-5p method): when the expression level of hsa-miR-199a-5p is less than or equal to 0.0006, it is a patient with tuberculous meningitis; when the expression level of hsa-miR-199a-5p is greater than 0.0006, it is a patient with viral meningitis.

5. Use the combined expression of the four miRNA combinations to distinguish patients with tuberculous meningitis from patients with viral meningitis:

Logistic regression method was used to obtain the combined expression (probability value) of 4 miRNAs (hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p and hsa-miR-199a-5p). , the probability value is 0.61. When the probability value is greater than 0.61, it is a patient with tuberculous meningitis; when the probability value is less than or equal to 0.61, it is a patient with viral meningitis.

2), performance evaluation

The receiver operator characteristic curve (ROC curve), originally used to evaluate radar performance, is also known as the receiver operating characteristic curve. The ROC curve is a curve drawn according to a series of different binary classification methods (cutoff value or decision threshold), with the true positive rate (sensitivity) as the ordinate and the false positive rate (1-specificity) as the abscissa. According to the knowledge of SPSS16.0, analyze the measurement results of the disease group and the reference group, determine the upper and lower limits of the measurement value, the group distance and the cut-off point, and list the cumulative frequency distribution table according to the selected group distance interval, respectively. Sensitivity, specificity and false positive rate (1-specificity) were calculated for all cut-off points. Taking the sensitivity as the ordinate to represent the true positive rate, and (1-specificity) as the abscissa to represent the false positive rate, the ROC curve was plotted.

ROC curve evaluation statistic calculation. The value of the area under the ROC curve is between 1.0 and 0.5. In the case of AUC>0.5, the closer the AUC is to 1, the better the diagnostic effect. When AUC is 0.5-0.7, it has low accuracy, when AUC is 0.7-0.9, it has certain accuracy, and when AUC is above 0.9, it has high accuracy. When AUC=0.5, it means that the diagnostic method does not work at all and has no diagnostic value. AUC<0.5 does not conform to the real situation and rarely occurs in practice. Therefore, patients with viral meningitis and normal subjects were selected as the control group, and patients with tuberculous meningitis as the disease group (ie TBM vs. VM and TBM vs. HCs), respectively, and hsa-miR-126-3p, hsa-miR-130a The differential diagnosis results of -3p, hsa-miR-151a-3p and hsa-miR-199a-5p and their combinations were subjected to ROC curve analysis, and the results are shown in Table 5 and Figure 2:

The area under the ROC curve (AUC) of the four miRNAs for differentiating tuberculous meningitis and viral meningitis were all greater than 0.70, the sensitivity was greater than 78%, and the specificity was greater than 56%.

In addition, the combination of 4 miRNAs had a better ability to discriminate between tuberculous meningitis and viral meningitis [AUC=0.893 (0.788-0.957)], sensitivity was 90.6% (75.0%-98.0%), specificity was 86.7% (69.3%-96.2%).

Table 5. Performance evaluation of 4 miRNAs and their combinations in the differential diagnosis of TBM and the other two groups

The present invention has been described in detail above. For those skilled in the art, without departing from the spirit and scope of the present invention, and without unnecessary experimentation, the present invention can be implemented in a wide range under equivalent parameters, concentrations and conditions. While the invention has been given particular embodiments, it should be understood that the invention can be further modified. In conclusion, in accordance with the principles of the present invention, this application is intended to cover any alterations, uses or improvements of the invention, including changes made using conventional techniques known in the art, departing from the scope disclosed in this application. The application of some of the essential features can be made within the scope of the following appended claims.

SEQUENCE LISTING

<110> Beijing Chest Hospital Affiliated to Capital Medical University, Beijing Institute of Tuberculosis and Thoracic Oncology

<120> Application of a system for detecting miRNA expression in the preparation of products to differentiate between tuberculous meningitis and viral meningitis

<130> GNCFY191406

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<170> PatentIn version 3.5

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Claims (10)

1. The application of the system for detecting miRNA expression in the preparation of products for distinguishing or assisting in distinguishing between patients with tuberculous meningitis and patients with viral meningitis; The miRNAs are four, three, two or one of hsa-miR-126-3p, hsa-miR-130a-3p, hsa-miR-151a-3p and hsa-miR-199a-5p. 2. application according to claim 1 is characterized in that: the system of described detection miRNA expression amount is following M1) or M2): M1) a system for detecting the expression of the miRNA by quantitative PCR; M2) A system for detecting the expression level of the miRNA using a high-throughput microarray chip. 3. application according to claim 1 or 2 is characterized in that: the system that described utilizes quantitative PCR to detect the expression level of described miRNA comprises primer set, set of probes, test kit and/or carrying out quantitative PCR required Other reagents and/or instruments. 4. The application according to any one of claims 1-3, wherein the system for detecting miRNA expression further comprises a data processing device, the data processing device is used for expressing the miRNA from the object to be tested The quantity is converted into the discrimination result of the object to be tested. 5 . The application according to claim 4 , wherein the object to be tested is a patient with meningitis to be tested. 6 . 6. The system for distinguishing or assisting in distinguishing tuberculous meningitis patients from viral meningitis patients using the miRNA described in claim 1 as a marker in preparing a product for distinguishing or assisting in distinguishing tuberculous meningitis patients from viral meningitis patients Applications. 7. The application according to claim 6, wherein the system for distinguishing or assisting in distinguishing tuberculous meningitis patients and viral meningitis patients is the detection miRNA expression level described in any of claims 1-4 system. 8. A product for distinguishing or assisting in distinguishing patients with tuberculous meningitis from patients with viral meningitis, wherein the product is the system for detecting miRNA expression according to any one of claims 1-4. 9. The application according to any one of claims 1-7, or the product according to claim 8, wherein the miRNA expression level is the miRNA expression level in blood. 10 . The application according to claim 9 , wherein the miRNA expression level is the miRNA expression level in peripheral blood mononuclear cells. 11 .