CN113178263A - Pulmonary tuberculosis lesion activity marker, kit, method and model construction method - Google Patents
Pulmonary tuberculosis lesion activity marker, kit, method and model construction method Download PDFInfo
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Abstract
The invention relates to a tuberculosis lesion activity marker, a kit, a method and a model construction method, which are characterized in that the tuberculosis lesion activity marker is a plasma protein biomarker in a blood sample, and the plasma protein biomarker is a combined marker comprising one or more of C1QB protein and CCL19(MIP3B) protein; the invention adopts the combined marker of C1QB and CCL19(MIP3B) as the biomarker for detecting the activity of the pulmonary tuberculosis lesion for the first time, constructs a rapid diagnosis model for detecting the activity of the pulmonary tuberculosis lesion, provides a new direction for the clinical diagnosis of tuberculosis, provides a new target point for the diagnosis of the activity of the pulmonary tuberculosis lesion as a technical idea for diagnosing the activity of the pulmonary tuberculosis lesion; therefore, the invention overcomes the defects of low diagnosis detectable rate, long time consumption and the like of the existing active tuberculosis, has the characteristics of good specificity and high sensitivity, and has good clinical application value for the auxiliary diagnosis of the lesion activity of the tuberculosis.
Description
Technical Field
The invention belongs to the technical field of biomedicine, and particularly relates to a diagnostic marker, a kit, a detection method and a model construction method for tuberculosis lesion activity by using C1QB and CCL19(MIP 3B).
Background
Tuberculosis is one of ten causes of death worldwide and is also the leading cause of death of a single infectious agent. Tuberculosis is a chronic infectious disease caused by infection with mycobacterium tuberculosis. In 2019, it is estimated that 1000 million people worldwide have tuberculosis. Diagnostic tests for tuberculosis include sputum smear microscopy (developed over 100 years ago), rapid molecular tests (first approval by WHO 2010), which found acid-fast bacilli only in about 50-60% of tuberculosis patients, and culture-based methods, which required up to 8 weeks to provide results, but both are still the reference gold standard. If the diagnosis is not clear, and effective anti-tuberculosis treatment cannot be performed in time, the mortality rate of tuberculosis is high.
The WHO 2020 worldwide tuberculosis report shows that the relative transmission rate of the bacteria-negative tuberculosis patients and the bacteria-positive tuberculosis patients is 22%, and at least 30% of tuberculosis cases in China are transmitted by sputum smear negative tuberculosis. According to the Japanese study, 73% of patients who were culture-negative before surgery could not detect viable Mycobacterium tuberculosis in their lesions. After the anti-tuberculosis treatment of the bacterial negative tuberculosis is finished, the lung still has persistent inflammation. These inflammatory reactions not only have no effect on control of tuberculosis infection, but can exacerbate the disease, causing tuberculosis relapse and infection. Uptake of 18-fluorodeoxyglucose (18F-FDG) is reflected in intracellular glycolysis and is increased in tuberculosis, other granulomatous inflammatory conditions, and tumor cells. High uptake of 18F-FDG has a higher correlation with the degree of disease activity. The lesion activity of the bacteria-negative tuberculosis can be evaluated by using 18F-FDG PET/CT at present. However, 18F-FDG-PET/CT is costly and involves radiation exposure, and often lacks specificity for qualitative lesion diagnosis, often failing to reliably distinguish tuberculosis lesions from malignancies. Therefore, it is important to find a biomarker that can replace PET-CT to evaluate the activity of tuberculosis focus.
Disclosure of Invention
The invention aims to solve the technical problems of poor specificity, low sensitivity and time-consuming detection of the existing tuberculosis lesion activity diagnosis marker, provides a technical concept of taking the combination of C1QB and CCL19(MIP3B) as the tuberculosis lesion activity diagnosis, provides a new target point for the active tuberculosis diagnosis, and has good clinical application value for the active tuberculosis diagnosis.
In particular, one aspect of the invention provides the use of a reagent combination marker that selectively detects C1QB and CCL19(MIP3B) for the manufacture of a kit for the rapid diagnosis of tuberculosis lesion activity, for determining the level of C1QB and CCL19(MIP3B) in plasma obtained from said subject, wherein an increase in the level of C1QB relative to the level in a normal human subject and a decrease in the level of CCL19(MIP3B) relative to the level in a normal human subject is indicative of the presence of active tuberculosis in said subject.
A tuberculosis lesion activity marker which is a plasma protein biomarker in a blood sample, wherein the plasma protein biomarker is a combined marker comprising one or more of C1QB protein, CCL19 protein or MIP3B protein.
Furthermore, the amino acid sequence of the CCL19 protein or MIP3B protein in the combined marker is shown as SEQ ID NO. 2, and the nucleotide sequence is shown as SEQ ID NO. 1.
Furthermore, the amino acid sequence of the C1QB protein in the combined marker is shown as SEQ ID NO. 4, and the nucleotide sequence is shown as SEQ ID NO. 3.
A tuberculosis lesion activity detection kit based on a tuberculosis lesion activity marker is characterized by comprising a reagent related to plasma extraction and separation in a whole blood sample, a reagent related to proteomic quantitative analysis of a plasma sample, and a reagent related to protein expression level determination of C1QB protein, CCL19 protein or MIP3B protein in the plasma sample; the kit also comprises a standard substance, wherein the standard substance is one or more of C1QB protein, CCL19 protein or MIP3B protein.
A method for detecting a tuberculosis lesion activity detection kit based on a tuberculosis lesion activity marker, wherein a detection reagent in the kit is used for determining the expression level of the marker protein in a plasma sample obtained from a subject, comprising the following steps:
a. determining the expression level of C1QB protein, CCL19 protein, or MIP3B protein in plasma from the subject;
b. comparing the level of expression of the marker protein in the plasma of the subject to the level of expression of the marker protein in the plasma of a normal subject;
c. based on the comparison made in step b, wherein an increase in the expression level of C1QB protein in the plasma sample of the subject relative to the level in a normal human subject, a decrease in the expression level of CCL19 or MIP3B protein relative to the level in a normal human subject is indicative of the presence of active tuberculosis in the subject; an increase in the expression level of the C1QB protein and CCL19 or MIP3B protein relative to the level of improvement in tuberculosis or a cured subject, indicating the presence of active tuberculosis in the subject.
Further, a method of determining the level of a plasma protein biomarker in a biological sample comprises: a protein quantitative method, a protein concentration determination method and a model construction algorithm.
Further, including, but not limited to tandem mass spectrometry-liquid chromatography/mass spectrometry (TMT-LC/MS), liquid chromatography-parallel reaction monitoring/mass spectrometry (LC-PRM/MS), etc.), enzyme linked immunosorbent assay (ELISA), immunoblotting (WB), protein chips, etc., and logistic regression algorithms, decision trees, neural network algorithms, etc., Polymerase Chain Reaction (PCR), real-time polymerase chain reaction (RT-PCR).
Determining the levels of C1QB and CCL19(MIP3B) in plasma from the subject, wherein an increase in the levels of C1QB and CCL19(MIP3B) relative to the level in a subject with improved or cured tuberculosis is indicative of the presence of active tuberculosis in the subject.
And establishing a model, and predicting the activity of the tuberculosis lesion according to the index. A construction method of a tuberculosis lesion activity detection model based on a pulmonary tuberculosis lesion activity marker is characterized in that a detection algorithm is used for constructing an active tuberculosis rapid diagnosis model of C1QB protein, CCL19 protein or MIP3B protein; the detection algorithm comprises the following steps:
(1) collecting and processing a plasma sample, separating the plasma sample from whole blood, and acquiring sample data by using a data acquisition module;
(2) determining a plasma sample, the data processing module determining from the sample an indicator of a plasma protein biomarker, the plasma protein biomarker specifically comprising C1QB protein, CCL19 protein, or MIP3B protein;
(3) the data model construction module uses a neural network method to fit a training set to construct a model, 70% of sample size is used as the training set, 30% of sample size is used as a test set, expression of the plasma protein marker is subjected to integrated analysis, and optimal model parameters are recorded; meanwhile, a threshold calculation module calculates the threshold of the model classification by using a verification set according to an ROC curve to construct and obtain an active tuberculosis detection model,
(4) wherein an increase in the expression level of C1QB protein in the plasma sample of the subject relative to the level in a normal human subject, a decrease in the expression level of CCL19 or MIP3B protein relative to the level in a normal human subject is indicative of the presence of active tuberculosis in the subject;
(5) or an increase in the expression level of the C1QB protein and CCL19 or MIP3B protein relative to the level of improvement in tuberculosis or a cured subject, indicating the presence of active tuberculosis in the subject.
The invention has the beneficial effects that:
the invention adopts a combined marker of C1QB and CCL19(MIP3B) which are derived from plasma protein for the first time as a biomarker for detecting the activity of the tuberculosis lesion, constructs a rapid diagnosis model for detecting the activity of the tuberculosis lesion, provides a new direction for clinical diagnosis of tuberculosis, provides a new target for diagnosing the activity of the tuberculosis lesion as a technical idea for diagnosing the activity of the tuberculosis lesion, and has good clinical application value for diagnosing the activity of the tuberculosis lesion; therefore, the invention overcomes the defects of low detectable rate, long time consumption and the like of the existing tuberculosis lesion activity diagnosis, has the characteristics of good specificity and high sensitivity, and has good clinical application value for the auxiliary diagnosis of the tuberculosis lesion activity.
Drawings
Figure 1 is the levels of C1QB and CCL19(MIP3B) (n ═ 88) in plasma of active tuberculosis patients, healthy volunteers and non-tuberculosis pulmonary respiratory disease.
88 cases of active tuberculosis patients (TB), healthy volunteers (HC) and non-tuberculosis pulmonary respiratory disease (ORD) plasma were each taken. Data were averaged from duplicate runs and indicated statistical differences and significant differences.
FIG. 2 is a correlation analysis of the PET-CT related indicators (SUVmax, SUVmin, SUVmean, MTV, TLGq) of the plasma marker of bacterial negative tuberculosis.
FIG. 2 is a correlation analysis of the PET-CT related indicators (SUVmax, SUVmin, SUVmean, MTV, TLGq) of the plasma marker of bacterial negative tuberculosis.
In 18 cases of the negative pulmonary tuberculosis, the correlation intensity was determined approximately according to the following distribution: 0.8-1.0 are strongly correlated; 0.6-0.8 strong correlation; 0.4-0.6 moderate correlation; 0.2-0.4 weakly correlated; 0.0-0.2 are very weakly or not correlated.
FIG. 3 shows the plasma levels of C1QB and CCL19(MIP3B) in patients with bacteria-negative active tuberculosis and patients with improved or cured tuberculosis.
FIG. 3 shows the plasma levels of C1QB and CCL19(MIP3B) in patients with bacteria-negative active tuberculosis and patients with improved or cured tuberculosis.
40 cases of patients with negative active Tuberculosis (TB) and 40 cases of patients with improved or cured tuberculosis (Improvement) were taken. Data were averaged from duplicate runs and indicated statistical differences and significant differences.
FIG. 4 is a ROC analysis of the relative levels in C1QB and CCL19(MIP3B) Tuberculosis (TB) and tuberculosis Improvement or cure (Improvement) plasma.
The area under the curve (AUC) of C1QB was 0.731, and the area under the curve of CCL19(MIP3B) was 0.621. The optimal cut-off point for C1QB is 3.117. At this point, the specificity was 72.5% and the sensitivity was 75%. The best cutoff point for CCL19(MIP3B) is 30.435. At this time, the specificity was 85% and the sensitivity was 42.5%.
Fig. 5 is a model for predicting activity of tuberculosis lesions.
(A) Activity prediction Nomogram. (B) Calibration curve of Nomogram. Note: the x-axis represents the predicted infrequent risk. The y-axis represents the actual diagnosis of non-recurrence. The dashed diagonal line represents a perfect prediction of an ideal model. The solid line represents the performance of the nomogram, with the dashed line closer to the diagonal representing better prediction.
Detailed Description
The present invention is further illustrated by the following examples, but is not limited thereto. The experimental procedures, in which specific conditions are not noted in the following examples, are generally carried out under conventional conditions or conditions recommended by the manufacturers.
The C1QB gene encodes the b chain polypeptide of a serum complement subcomponent and is a component of the serum complement system. There are studies that have shown that C1QB is associated with lupus erythematosus and glomerulonephritis. In the field of tuberculosis research, C1QB was found to distinguish between active tuberculosis and latent tuberculosis infection. This serum complement system is a component of the host immune response and plays an important role in the host's resistance to pathogen invasion. CCL19(MIP3B) is a chemokine and may also indicate the extent of an inflammatory response. At present, no research has revealed the relationship between CCL19(MIP3B) and tuberculosis.
1. Brief introduction to the drawings
The present invention provides plasma biomarkers C1QB and CCL19(MIP3B) which are indicative of active tuberculosis and which can be used to accurately diagnose active tuberculosis in a subject. In addition, a kit for diagnosing activity of tuberculosis lesions is provided. In certain embodiments, the methods entail detecting C1QB and CCL19(MIP3B) in a suitable sample.
2. Definition of
Before setting forth the invention in detail, definitions of certain terms to be used herein are provided. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.
The term "subject" is intended to include any disorder that can directly or indirectly involve active tuberculosis. Examples of subjects include mammals, e.g., humans, non-human primates, dogs, cows, horses, pigs, sheep, goats, cats, mice, rabbits, rats, and transgenic non-human animals. In certain embodiments, the subject is a human, e.g., a human suffering from active tuberculosis, a human at risk of suffering from active tuberculosis and related thereto, or a human potentially capable of suffering from active tuberculosis-related dementia.
The term "treating" is used herein to mean relieving, reducing, or alleviating at least one symptom of a disease in a subject. For example, with respect to active tuberculosis, the term "treating" includes: relieving, alleviating or alleviating cognitive impairment (such as impairment of memory and/or orientation) or impairment of overall function (all functions, including activities of daily living), and/or slowing or reversing the progressive decline of overall or cognitive impairment. Thus, the term "treating" also includes: delaying or arresting the onset before the clinical manifestation of the disease or the symptoms of the disease, and/or reducing the risk of development or worsening of the symptoms of the disease.
The term "about" or "approximately" generally means within 5%, or more preferably within 1%, of a given value or range.
3. Plasma protein biomarkers for tuberculosis
The present invention relates to plasma protein biomarkers: : it was found to be differentially present in biological samples obtained from subjects with active tuberculosis compared to "normal" subjects. A plasma protein biomarker is differentially present between samples if the difference between the expression levels of the plasma protein biomarkers in the samples is determined to be statistically significant. Common tests of statistical significance include, but are not limited to: t-test, ANOVA, Kniskal-Wallis, Wilcoxon, Mann-Whitney, and odds ratios. Plasma protein biomarkers, alone or in combination, can be used to provide a measure of the relative risk of a subject to have or not have active tuberculosis.
4. Determining the expression level of a plasma protein biomarker in a sample
The level of a plasma protein biomarker in a biological sample may be determined by any suitable method. Any reliable method for measuring the level or amount of plasma protein in a sample may be used. In general, plasma proteins can be detected and quantified from a biological sample, which is a plasma sample isolated from the collection of whole blood from a subject, the method comprising: protein quantification methods (e.g., tandem mass spectrometry-liquid chromatography/mass spectrometry (TMT-LC/MS), liquid chromatography-parallel reaction monitoring/mass spectrometry (LC-PRM/MS), etc.), protein concentration determination methods (e.g., enzyme-linked immunosorbent assay (ELISA), immunoblotting (WB), protein chips, etc.), and model construction algorithms (e.g., logistic regression algorithms, decision trees, neural network algorithms, etc.). Other exemplary techniques include Polymerase Chain Reaction (PCR), real-time polymerase chain reaction (RT-PCR), and the like.
5. Determination of the Activity of tuberculosis by plasma protein biomarkers
The plasma protein biomarkers described herein may be used in diagnostic assays to assess the active tuberculosis status of a subject. The disease state includes the presence or absence of active tuberculosis. Disease states may also include monitoring the progress of active tuberculosis, e.g., monitoring disease progression. Other procedures may be indicated based on the active tuberculosis status of the subject, including, for example, other diagnostic tests or therapeutic procedures.
The ability of a diagnostic test to correctly predict a disease state is typically measured in terms of the accuracy of the assay, the sensitivity of the assay, the specificity of the assay, or the "area under the curve" (AUC) (e.g., the area under the Receiver Operating Characteristic (ROC) curve). Accuracy, as used herein, is a measure of the proportion of misclassified samples. Accuracy can be calculated as the total number of correctly classified samples divided by the total number of samples (e.g., in the test population). Sensitivity is a measure of "true positives" that are predicted to be positive by the assay and can be calculated as the number of correctly identified active tuberculosis samples divided by the total number of active tuberculosis samples. Specificity is a measure of the "true negatives" that are predicted to be negative by the assay, and can be calculated as the number of correctly identified normal samples divided by the total number of normal samples. AUC is a measure of the area under the subject's operating characteristic curve, which is a plot of sensitivity versus false positive rate (1-specificity). The greater the AUC, the more effective the predictive value of the assay. Other useful measures of the utility of the test include a "positive predictive value" (which is the percentage of actual positives for which the test is positive) and a "negative predictive value" (which is the percentage of actual negatives for which the test is negative).
The present invention is further illustrated by the following examples, but is not limited thereto. The experimental procedures, in which specific conditions are not noted in the following examples, are generally carried out under conventional conditions or conditions recommended by the manufacturers.
Unless otherwise indicated, reagents and materials used in the following examples are commercially available.
Detailed Description
The present invention is further illustrated by the following specific examples, which are not intended to limit the invention in any way. Reagents, methods and apparatus used in the present invention are conventional in the art unless otherwise indicated.
Unless otherwise indicated, reagents and materials used in the following examples are commercially available.
Example 1
Separation of plasma samples from whole blood
Collecting fasting peripheral blood whole blood of an active tuberculosis patient in the morning by using an EDTA anticoagulant tube, centrifuging for 15min at 3000rcf, and separating plasma into a new 1.5mL centrifuge tube within 6 hours. Plasma samples were stored in-80 cryo-refrigerator.
Example 2
ELISA method for determining protein expression level in plasma sample
Plasma sample collection: 88 patients with active tuberculosis, 88 healthy controls and 88 patients with nontuberculous pulmonary respiratory disease.
Expression levels of plasma protein markers were measured using human C1QB and CCL19(MIP3B) kit (CLOUD-CLONE corp. Statistical analysis was performed using t test or one-way ANOVA in GraphPad Prism 8 software (significant differences were seen when P <0.05 and very significant differences were seen when P < 0.01). Differentially expressed plasma protein data were processed as mean ± SEM and scatter plots containing error bars were plotted. The results show that C1QB and CCL19(MIP3B) can effectively distinguish active tuberculosis patients, healthy controls and non-tuberculosis pulmonary respiratory diseases, and have statistical significance. As shown in fig. 1.
Example 3
And (3) analyzing the correlation between the pulmonary tuberculosis plasma marker and PET-CT related indexes (SUVmax, SUVmin, SUVmean, MTV and TLGq).
Plasma sample collection: 18 cases of the patients with the bacterial negative tuberculosis have the SUVmax of PET-CT more than or equal to 3.
The expression level of plasma protein markers was measured using ELISA kit (closed-CLONE corp. whan. cn) using human C1QB, CCL19(MIP3B), RANTES, MHCDMb, according to standard procedures. Correlation analysis was performed using the detailed PET-CT data of 18 patients. The correlation analysis can find the relation between the PET-CT related indexes (SUVmax, SUVmin, SUVmean, MTV and TLGq) and the concentration of the biomarkers in blood. Based on the correlation analysis results, we found that there is a correlation between CCL19(MIP3B) and MTV, as shown in fig. 2.
Example 4
ELISA method for determining protein expression level in plasma sample
Plasma sample collection: the patients with bacteria negative Tuberculosis (TB) and the improved or cured (improved) plasma of the tuberculosis are 40 cases respectively.
The expression level of plasma protein markers was measured using ELISA kit (CLOUD-CLONE corp. white.cn) using human C1QB and CCL19(MIP3B) according to standard procedures. Statistical analysis was performed using t test or one-way ANOVA in GraphPad Prism 8 software (significant differences were seen when P <0.05 and very significant differences were seen when P < 0.01). Differentially expressed plasma protein data were processed as mean ± SEM and histograms containing error bars were plotted. As a result, the plasma concentration of C1QB was found to have statistical significance [3.549(3.211-3.886) vs 2.745(2.540-2.950), P <0.01], as shown in FIG. 3.
Example 5
And establishing a pulmonary tuberculosis activity prediction model.
R software (version 3.6.2, https:// www.r-project. org /) was used for all statistical analyses. The Kolmogorov-Smirnov test was used to evaluate the normal distribution of continuous variables. The concentrations of candidate biomarkers were compared for the relapse and no relapse groups using Student's t-test for normal distribution variables or nonparametric test for bias variables (Mann-Whitney U-test) expressed as median and range. P <0.05 was considered significant. The Receiver Operating Characteristic (ROC) curves and the respective area under the curve (AUC) of the candidate biomarkers were calculated. As shown in fig. 4, C1QB and CCL19(MIP3B) are statistically significant, with an area under the curve (AUC) of C1QB of 0.731 and an area under the curve of CCL19(MIP3B) of 0.621. The optimal cut-off point for C1QB is 3.117. At this point, the specificity was 72.5% and the sensitivity was 75%. The best cutoff point for CCL19(MIP3B) is 30.435. At this time, the specificity was 85% and the sensitivity was 42.5%. Meanwhile, a nomogram is drawn by using the R-package rms, and the disease activity risk of the patient is more accurately predicted by combining two or more biomarkers. The C index is used for evaluating the prediction accuracy of the nomogram, the calibration curve is used for evaluating the efficiency of the nomogram, and as shown in FIG. 5, the C index is 0.773, which shows that the nomogram has higher accuracy for predicting the recurrence of tuberculosis patients. Meanwhile, the correction curve shows that the dotted line of the alignment chart deviates a little from the diagonal line, which shows that the prediction efficiency of the alignment chart is high.
The above examples are exemplified by sputum-bacteria-negative tuberculosis, but the present invention is not limited to sputum-bacteria-negative tuberculosis, and is also applicable to sputum-bacteria-positive tuberculosis, which is described here.
The above detailed description is of the preferred embodiment for the convenience of understanding the present invention, but the present invention is not limited to the above embodiment, that is, it is not intended that the present invention necessarily depends on the above embodiment for implementation. It will be apparent to those skilled in the art that any modification of the present invention, equivalent substitutions of selected materials and additions of auxiliary components, selection of specific modes and the like, which are within the scope and disclosure of the present invention, are contemplated by the present invention.
Claims (8)
1. A method for constructing a tuberculosis lesion activity detection model based on a tuberculosis lesion activity marker is characterized in that a detection algorithm is used for constructing a tuberculosis lesion activity rapid diagnosis model of C1QB protein, CCL19 protein or MIP3B protein; the detection algorithm comprises the following steps:
(1) collecting and processing a plasma sample, separating the plasma sample from whole blood, and acquiring sample data by using a data acquisition module;
(2) determining a plasma sample, the data processing module determining from the sample an indicator of a plasma protein biomarker, the plasma protein biomarker specifically comprising C1QB protein, CCL19 protein, or MIP3B protein;
(3) the data model construction module uses a neural network method to fit a training set to construct a model, 70% of sample size is used as the training set, 30% of sample size is used as a test set, expression of the plasma protein marker is subjected to integrated analysis, and optimal model parameters are recorded; meanwhile, a threshold value calculation module calculates the threshold value of the classification of the model by using a verification set according to an ROC curve to construct and obtain a tuberculosis lesion activity detection model,
(4) wherein an increase in the expression level of C1QB protein in the plasma sample of the subject relative to the level in a normal human subject, a decrease in the expression level of CCL19 or MIP3B protein relative to the level in a normal human subject is indicative of the presence of tuberculosis lesion activity in the subject;
(5) or an increase in the expression level of the C1QB protein and CCL19 or MIP3B protein relative to the level of improvement in tuberculosis or a cured subject, indicating the presence of active tuberculosis in the subject.
2. A tuberculosis lesion activity marker which is a plasma protein biomarker in a blood sample, wherein the plasma protein biomarker is a combined marker comprising one or more of C1QB protein, CCL19 protein or MIP3B protein.
3. The tuberculosis lesion activity marker as claimed in claim 2, wherein the amino acid sequence of CCL19 protein or MIP3B protein in the combined marker is shown as SEQ ID NO. 2, and the nucleotide sequence is shown as SEQ ID NO. 1.
4. The tuberculosis lesion activity marker as claimed in claim 2, wherein the combined marker has the amino acid sequence of C1QB protein shown as SEQ ID NO. 4 and the nucleotide sequence shown as SEQ ID NO. 3.
5. A pulmonary tuberculosis lesion activity detection kit based on a pulmonary tuberculosis lesion activity marker is characterized by comprising a reagent related to plasma extraction and separation in a whole blood sample, a reagent related to proteomic quantitative analysis of the plasma sample, and a reagent related to protein expression level determination of C1QB protein, CCL19 protein or MIP3B protein in the plasma sample; the kit also comprises a standard substance, wherein the standard substance is one or more of C1QB protein, CCL19 protein or MIP3B protein.
6. A method for detecting an activity of a tuberculosis lesion detection kit based on a tuberculosis lesion activity marker, wherein a detection reagent in the kit is used for determining the expression level of the marker protein in a plasma sample obtained from a subject, comprising the steps of:
a. determining the expression level of C1QB protein, CCL19 protein, or MIP3B protein in plasma from the subject;
b. comparing the level of expression of the marker protein in the plasma of the subject to the level of expression of the marker protein in the plasma of a normal subject;
c. based on the comparison made in step b, wherein an increase in the expression level of C1QB protein in the plasma sample of the subject relative to the level in a normal human subject, a decrease in the expression level of CCL19 or MIP3B protein relative to the level in a normal human subject is indicative of the presence of active tuberculosis in the subject; an increase in the expression level of the C1QB protein and CCL19 or MIP3B protein relative to the level of improvement in tuberculosis or a cured subject, indicating the presence of active tuberculosis in the subject.
7. The method of detecting a tuberculosis lesion activity detection kit based on a tuberculosis lesion activity marker as claimed in claim 6, wherein the method of determining the level of plasma protein biomarker in the biological sample comprises: a protein quantitative method, a protein concentration determination method and a model construction algorithm.
8. The method for detecting the activity of the tuberculosis lesion detection kit based on the tuberculosis lesion activity marker as claimed in claim 7, which includes but is not limited to tandem mass spectrometry-liquid chromatography/mass spectrometry (TMT-LC/MS), liquid chromatography-parallel reaction monitoring/mass spectrometry (LC-PRM/MS), enzyme linked immunosorbent assay (ELISA), immunoblotting (WB), protein chip, etc. and logistic regression algorithm, decision tree, neural network algorithm, etc., Polymerase Chain Reaction (PCR), real-time polymerase chain reaction (RT-PCR).
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| CN114778656A (en) * | 2022-03-29 | 2022-07-22 | 浙江苏可安药业有限公司 | Serum metabolic marker for detecting drug-resistant tuberculosis and kit thereof |
| CN114791459A (en) * | 2022-03-29 | 2022-07-26 | 浙江苏可安药业有限公司 | Serum metabolic marker for detecting pulmonary tuberculosis and kit thereof |
| CN115876991A (en) * | 2023-03-08 | 2023-03-31 | 中国医学科学院北京协和医院 | Sugar chain marker for pulmonary embolism diagnosis and application thereof |
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