Implementation and application of rapid diagnosis method for teenager tuberculosis based on serology

Abstract

The invention discloses a serology-based rapid diagnosis method for juvenile tuberculosis. The invention provides an economical and efficient method for diagnosing tuberculosis of teenagers. Based on serum proteomics of clinically active teenager tuberculosis patients, a rapid tuberculosis diagnosis method based on serology is found. According to the present invention, through a variety of machine learning algorithms, the combination of the three proteins such as the apolipoprotein A1 (Apolipoprotein A-I, APOA1), the hemoglobin subunit alpha (Hemoglobin subunit alpha-1, HBA1) and the hemoglobin subunit beta (Hemoglobin subunit beta, HBB) has the highest accuracy and the highest sensitivity in the teenager tuberculosis diagnosis process, such that the combination can be adopted as the serological diagnosis marker of the teenager tuberculosis; the invention provides a new method for rapid diagnosis of juvenile tuberculosis.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of molecular diagnostics, in particular to the development and application of a method for diagnosing tuberculosis in adolescents. BACKGROUND

[0002] Tuberculosis (TB) is a contagious disease caused by Mycobacterium tuberculosis that continues to be a global epidemic, infecting more than 10 million people each year. Of those infected with Mtb, about 5-15% will eventually develop active pulmonary TB. TB surveillance usually classifies the population simply as "children" (0-14 years) and "adults" (> 15 years), ignoring the special group of adolescents (defined as 10-24 years). A recent study showed that about 1.8 million new adolescent TB patients are added each year, accounting for 17% of the total TB patients. Since 1990, the incidence of adolescent TB has decreased, but the incidence of drug-resistant TB has increased. Although it is recognized that adolescents are at an increased risk of TB due to the decline in the efficacy of the Bacillus Calmette-Guerin vaccine, adolescents have not been treated as a unique group in TB control efforts to date. In addition, due to the large and dense social contact of adolescents, efficient diagnosis of TB in this group is crucial for TB prevention and control. Mycobacterium tuberculosis culture is the gold standard for TB diagnosis, but it takes 4-8 weeks. However, this diagnostic method is complex and time-consuming, hindering the rapid diagnosis of TB. Therefore, it is particularly urgent to find a rapid diagnostic marker for TB and establish a new TB diagnostic model. SUMMARY

[0003] In view of the above-mentioned disadvantages of the prior art, the purpose of the present application is to provide a novel serological-based rapid diagnostic method for bovine tuberculosis. To improve the detection efficiency of bovine tuberculosis, promote the prevention and control of bovine tuberculosis, increase the safety of animal husbandry, and improve the quality of meat and milk.

[0004] The technical solution adopted by the present application is as follows: APOA1, HBA1 and HBB proteins are used as a combination for diagnosing tuberculosis in adolescents.

[0005] Further, the tuberculosis is a human infection with Mycobacterium tuberculosis caused by Mycobacterium tuberculosis.

[0006] Further, the content changes of APOA1, HBA1 and HBB proteins in serum are used as the basis for diagnosing tuberculosis in adolescents.

[0007] Further, the expression levels of APOA1, HBA1 and HBB proteins in the serum of adolescent TB patients are significantly lower than those of latent TB patients or healthy people.

[0008] Furthermore, the APOA1, HBA1 and HBB three proteins show an AUC coverage area of up to 95.42% in diagnosing tuberculosis in adolescents.

[0009] The beneficial effects of the present application are:

[0010] 1. The present application collects serum samples of active tuberculosis, latent tuberculosis infection patients and healthy controls of Chinese adolescents, and draws a serum protein atlas of active tuberculosis in Chinese adolescents through a label-free quantitative proteomics method.

[0011] 2. The present application finds a serum protein combination for efficient diagnosis of tuberculosis in adolescents. The accuracy and sensitivity of different serum protein combinations in diagnosing tuberculosis in adolescents are tested. The results of the receiver operating characteristic curve show that the APOA1, HBA1 and HBB three proteins have an AUC coverage area of up to 95.42% for combination diagnosis of tuberculosis, and have the highest accuracy and sensitivity.

[0012] 3. The present application verifies the effectiveness of the APOA1, HBA1 and HBB three proteins in diagnosing tuberculosis in adolescents through external queues. Since the determination of serum protein content is rapid and does not require bacterial culture, it is more economical and fast than traditional methods. Therefore, the diagnosis of tuberculosis in adolescents based on the three proteins has great application value. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 is the serum protein group characteristics of active tuberculosis patients in adolescents.

[0014] Figure 2 is the serum protein interaction network of the difference between active tuberculosis patients in adolescents and non-active tuberculosis patients.

[0015] Figure 3 is the accuracy and sensitivity of APOA1, HBA1 and HBB in diagnosing tuberculosis in adolescents, and the diagnosis effect in external verification queue. DETAILED DESCRIPTION

[0016] The present application first collects serum samples of active tuberculosis, latent tuberculosis infection patients and healthy controls of Chinese adolescents, and determines the relative expression amount of different serum proteins through a label-free quantitative proteomics method. Based on the expression data of all serum proteins, a variety of machine learning methods are used to identify the serum protein combination with the highest diagnosis efficiency for active tuberculosis in adolescents.

[0017] (I) Serum sample collection and protein sample preparation

[0018] The method is as follows:

[0019] 1. Process samples using the recommended standard operating procedures of the Human Proteome Organization (HUPO). Collect 40 mL blood samples from each participant, add ethylenediaminetetraacetic acid.

[0020] 2. Distribute serum samples into 1 mL low-protein adsorption tubes and store in a -80 °C ultra-low temperature freezer.

[0021] 3. Precipitate total proteins in serum samples by adding a pre-chilled six-fold volume of acetone and incubate overnight at -20 °C.

[0022] 4. After centrifugation, resuspend the dried protein pellet in 0.1 M tetraethylammonium bromide buffer solution. Measure protein concentration by bicinchoninic acid assay. Confirm protein integrity by SDS-PAGE and silver staining.

[0023] 5. Perform disulfide bond reduction using 5 mM dithiothreitol for 30 minutes at 32 °C, followed by alkylation with 10 mM iodoacetate for 45 minutes at room temperature in the dark.

[0024] 6. Digest serum proteins with 1.5 pg trypsin overnight at 37 °C. Digest peptides are subsequently acidified with 10% trifluoroacetic acid and desalted using C18 spin columns. Dry desalted peptides and dissolve with buffer (1% formic acid and 1% acetonitrile).

[0025] (ii) Mass spectrometry for proteome quantification

[0026] 1. After liquid chromatography separation, analyze peptide mixtures in data-independent acquisition mode on an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific). Load samples onto a capillary column and elute for 150 minutes with a non-linear gradient (600 nL / min). Peptides are ionized at high pressure (2.2 kV). The resolution of survey scans is 120000, the target value is set to 400000 ions, and the mass range of scans is 350 to 1500 m / z.

[0027] 2. Search human protein sequence files in Uniprot database using Spectronaut software (v15.7) with default parameters, set False discovery rate (FDR) < 0.01. Results are Figure 1

[0028] (iii) Protein pathway enrichment analysis

[0029] Significantly differentially expressed proteins were screened using the limma package. Pathway enrichment analysis was performed using the ClusterProfiler package, with FDR < 0.05 to screen for significantly enriched pathways. The STRINGdb package was used to construct a protein interaction network for the differentially expressed proteins. The results are Figure 2

[0030] (iv) Machine learning identifies protein diagnostic markers

[0031] 1. The proteome dataset was normalized using the quantile method, and proteins with a missing rate of more than 20% were removed. Missing values were imputed using the mean imputation method.

[0032] 2. The mlr3verse package (https: / / github.com / mlr-org / mlr3verse) was used to screen important serum proteins that distinguish between groups using XGBoost and RF machine learning algorithms. For XGBoost, the important variables were extracted using the default parameters; for RF, variables with Mean Decrease Gini > 0.5 were retained. The union of the variables screened by the two machine learning algorithms was taken as the candidate proteins.

[0033] 3. A support vector machine algorithm based on feature recursive elimination was used, and five-fold cross-validation was performed to obtain the optimal protein combination for diagnosis.

[0034] 4. The expression changes of the three proteins were verified using tuberculosis serum proteome data from an external cohort. The results are Figure 3 .

Claims

1. A novel rapid and efficient method for detecting tuberculosis in adolescents, characterized in that... This is a serum-based molecular diagnostic procedure that is very simple to perform and allows for rapid sample collection. The proteins involved include apolipoprotein A1 (APOA1), hemoglobin subunit alpha-1 (HBA1), and hemoglobin subunit beta (HBB). The expression levels of these three proteins in serum are used to detect whether adolescents have tuberculosis.

2. As described in claim 1, characterized in that: The serum samples from the adolescents were obtained from 81 adolescents at a hospital in Shenyang.

3. The diagnostic method according to claim 1, characterized in that: Includes the following steps: (1) Serum sample collection: Peripheral blood samples were processed according to the standard operating procedures recommended by the Human Proteome Organization (HUPO). After adding ethylenediaminetetraacetic acid (EDTA), the serum samples were dispensed into 1 mL low-protein adsorption tubes; (2) Protein abundance detection: The abundance of the three proteins was determined by immunoturbidimetric assay.

4. The application of the serum-based molecular diagnostic method according to claims 1-3 in the rapid diagnosis of tuberculosis in adolescents.

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