A set of markers associated with the frequent acute exacerbation phenotype of chronic obstructive pulmonary disease and uses thereof

Abstract

The application discloses a group of markers related to the phenotype of frequent acute exacerbation of chronic obstructive pulmonary disease (COPD) and application thereof. The markers include any one or a combination of at least two of inter-alpha-trypsin inhibitor heavy chain H3, lymphatic endothelial hyaluronan receptor 1, paraoxonase 1, alanine-glyoxylate transaminase, immunoglobulin kappa variable region 3D-11, fodrin 2, apolipoprotein F, dopamine beta-hydroxylase, muscle creatine kinase, FAM20C golgi-associated secretory pathway kinase or fat storage-inducing transmembrane protein 1. The application mines a group of nucleic acid / protein biomarkers which can be used for detecting and identifying the patient population of frequent acute exacerbation and non-frequent acute exacerbation phenotypes in the stable stage of COPD, can diagnose the two different patient populations of COPD, and can perform precise treatment and early warning.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology and relates to a group of biomarkers associated with the phenotype of frequent acute exacerbations of COPD and their applications. Background Technology

[0002] COPD is a common, progressive, and severe chronic disease characterized by airway obstruction. Based on the frequency of acute exacerbations each year, COPD patients can be divided into two clinical phenotypes: those with frequent exacerbations and those with infrequent exacerbations. Frequent exacerbations are a unique phenotype of COPD with a worse prognosis. Compared to patients with infrequent exacerbations, they experience more severe respiratory lesions, faster deterioration of lung function, a higher risk of hospitalization, and other serious complications due to hypoxia, resulting in a poorer quality of life and a greater financial burden on families. This subtype implies the presence of many complex underlying factors that regulate the pathophysiological processes of different COPD subtypes. These factors determine a patient's susceptibility to recurrent acute exacerbations of COPD and influence the severity and prognosis of the disease.

[0003] Currently, the prediction of frequent acute exacerbations of COPD relies on clinical assessment based on patients' recollections of previous treatment events. This method is not only time-consuming but also lacks standardized criteria. There is a lack of rapid, convenient, unified, and practical diagnostic standards and detection methods. There is a need to discover specific, functional, simple, and clinically applicable biomarkers to guide the early diagnosis, precise intervention, and personalized treatment of patients with frequent acute exacerbations of COPD. For example, CN114410772A discloses the application of substances that detect whether susceptibility genes of test subjects are mutated in the preparation of products that predict or assist in predicting whether test subjects are susceptible to acute exacerbation phenotypes of COPD. The susceptibility genes are ITK, ROCK1, ADCY9, ITGA2B, PDGFRB, FGFR3, SERPINA3, ITPR1, CFTR, USP24, SAA1, TEK, SPTBN2, PLXNA4, SPTA1, PLG, MAPKAPK2, LAMA3, P4HB, and / or MRC2 genes.

[0004] In conclusion, developing novel biomarkers associated with the phenotype of frequent acute exacerbations of COPD and enriching detection indicators and methods are of great significance to the field of COPD treatment. Summary of the Invention

[0005] To address the shortcomings of existing technologies and practical needs, this invention provides a set of biomarkers associated with the frequent acute exacerbation phenotype of COPD and their applications. It explores novel, highly specific, and highly sensitive nucleic acid / protein biomarkers that can be used to detect and diagnose patients with frequent and infrequent acute exacerbations of COPD.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a set of biomarkers associated with the phenotype of frequent acute exacerbations of COPD, characterized in that the biomarkers include any one or a combination of at least two of the following: interstitial α-trypsin inhibitor heavy chain H3 (ITIH3), lymphatic endothelial hyaluronic acid receptor 1 (LYVE1), paraoxygenase 1 (PON1), alanine glyoxylate transaminase (AGXT), immunoglobulin κ variable region 3D-11, cytoschizoprotein 2 (SEPTIN2), apolipoprotein F (APOF), dopamine β-hydroxylase (DBH), muscle creatine kinase (CKM), FAM20C Golgi-associated secretory pathway kinase (FAM20C), or fat storage-induced transmembrane protein 1 (FITM1).

[0008] In this invention, the α-trypsin inhibitor heavy chain H3 covalently binds to hyaluronic acid, playing a crucial role in stabilizing the extracellular matrix; lymphatic endothelial hyaluronic acid receptor 1 participates in the transport of hyaluronic acid in the lymph; paraoxygenase 1, an antioxidant enzyme, inhibits lipopolysaccharide-induced secretion of inflammatory cytokines from macrophages and the proliferation of lung fibroblasts; alanine glyoxylate transaminase, mainly located in peroxisomes, participates in glyoxylate detoxification; immunoglobulin κ variable region 3D-11 participates in antigen recognition; and cytoschizoprotein 2 modulates cortical muscle... The expression of actin regulates the airway epithelial barrier function; apolipoprotein F participates in cholesterol transport and / or esterification; dopamine β-hydroxylase, an oxidoreductase, catalyzes the conversion of dopamine to norepinephrine; muscle creatine kinase, a cytoplasmic enzyme involved in energy homeostasis, plays an important role in energy transduction in tissues with large fluctuations in energy demand, such as skeletal muscle; FAM20C, a Golgi-associated secretory pathway kinase, plays a role in lipid homeostasis, wound healing, and cell migration and adhesion; and fat storage-induced transmembrane protein 1 participates in muscle development.

[0009] In this invention, a highly sensitive and high-throughput proteomics detection method was used to capture 47 plasma-expressed proteins related to the respective disease phenotypic characteristics of COPD by conducting cohort detection, statistical comparison and bioinformatics analysis on plasma samples from two groups of patients with frequent acute exacerbations and infrequent acute exacerbations. After GO enrichment analysis, KEGG signaling pathway enrichment analysis, and ROC curve analysis, 11 proteins with AUC>0.7 were selected (including interstitial α-trypsin inhibitor heavy chain H3, lymphatic endothelial hyaluronic acid receptor 1, paraoxygenase 1, alanine glyoxylate transaminase, immunoglobulin κ variable region 3D-11, cytosolic protein 2, apolipoprotein F, dopamine β-hydroxylase, muscle creatine kinase, FAM20C Golgi-associated secretion pathway kinase, or fat storage-induced transmembrane protein 1). ROC analysis of these 11 differentially expressed proteins showed an AUC of 0.985 (95% CI: 0.966–1.000), a sensitivity of 90.9%, and a specificity of 100%. It can be used as a biomarker for early clinical diagnosis / differential diagnosis of patients with frequent and infrequent acute exacerbations during the stable phase of COPD, to provide early warning and intervention for the occurrence of frequent acute exacerbations of COPD, and to promote the prevention and effective treatment of frequent acute exacerbations of COPD.

[0010] In a second aspect, the present invention provides the use of biomarkers and / or substances for detecting the frequent acute exacerbation phenotype of COPD as described in the first aspect in the preparation of products that predict or assist in the prediction of the frequent acute exacerbation phenotype of COPD.

[0011] Thirdly, the present invention provides a product for predicting or assisting in predicting the frequent acute exacerbation phenotype of COPD, the product comprising reagents and / or devices for detecting the expression levels of biomarkers associated with the frequent acute exacerbation phenotype of COPD as described in the first aspect.

[0012] Fourthly, the present invention provides the use of biomarkers associated with the frequent acute exacerbation phenotype of COPD as described in the first aspect in constructing a predictive model of the frequent acute exacerbation phenotype of COPD and / or preparing a predictive device for the frequent acute exacerbation phenotype of COPD.

[0013] Fifthly, the present invention provides a predictive model for the phenotype of frequent acute exacerbations of COPD, the predictive model being used to perform the following:

[0014] Input the expression levels of the biomarkers associated with the frequent acute exacerbations of COPD as described in the first aspect, and fit a binary logistic regression model;

[0015] Using a fitted binary logistic regression model, the Nomogram results were calculated. Based on the contribution of each protein to the outcome variable in the model, the expression level of each protein was scored. These scores were then summed to obtain a total score. Finally, by using the functional relationship between the total score and the probability of the outcome event, the predictive value for the patient's frequent acute exacerbation phenotype of COPD was calculated. Figure 1 As shown.

[0016] In this invention, the model fitted with 11 screened proteins—ITIH3+LYVE1+PON1+AGXT+IGKV3D+Septin-2+APOF+DBH+CKM+FAM20C+FITM1—gave an ROC curve with an AUC of 0.985, demonstrating high diagnostic predictive efficacy.

[0017] In a sixth aspect, the present invention provides a device for predicting the phenotype of frequent acute exacerbations of COPD, the device comprising a detection unit and an evaluation unit.

[0018] The detection unit is used to perform the following:

[0019] The expression levels of the biomarkers associated with the frequent acute exacerbations of COPD described in the first aspect were detected in the test fluid samples of the subjects.

[0020] The evaluation unit is used to perform the following:

[0021] The expression levels of biomarkers associated with the frequent acute exacerbation phenotype of COPD detected by the analysis unit are input into the COPD frequent acute exacerbation phenotype prediction model described in the fifth aspect for calculation, and it is determined whether the patient is a COPD patient with frequent acute exacerbations during the stable phase.

[0022] Preferably, the body fluid sample to be tested includes any one of peripheral circulating blood, urine, saliva, sputum, lavage fluid, sweat, or extracellular vesicles of body fluids.

[0023] Preferably, the detection method includes proteometry, enzyme-linked immunosorbent assay (ELISA), or protein chip assay.

[0024] In a seventh aspect, the present invention provides the use of the biomarkers associated with the frequent acute exacerbation phenotype of COPD described in the first aspect as targets in screening drugs for the prevention or treatment of the frequent acute exacerbation phenotype of COPD.

[0025] Preferably, the screening includes determining whether the candidate drug can be used to prevent or treat the frequent acute exacerbation phenotype of COPD based on the effects of candidate drug use on biomarkers associated with the frequent acute exacerbation phenotype of COPD before and after use.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] This invention identifies novel biomarkers for detecting and identifying patients with frequent and infrequent exacerbations during the stable phase of COPD. It improves the specificity and accuracy of detection. ROC analysis showed an AUC of 0.985 (95% CI: 0.966–1.000), a sensitivity of 90.9%, and a specificity of 100%. These biomarkers can be used for the clinical diagnosis and differential diagnosis of patients with frequent and infrequent exacerbation phenotypes, providing early warning and intervention for the occurrence of frequent COPD exacerbations, and facilitating prevention and effective treatment of frequent COPD exacerbations. Attached Figure Description

[0028] Figure 1 The Norman diagram (nomogram) for frequent and infrequent acute exacerbations of COPD is used to calculate a total score for each patient by assigning a score to the expression level of each protein gene. The probability of frequent acute exacerbations for each patient is then calculated using a conversion function between the score and the probability of the outcome.

[0029] Figure 2 Volcano plot of differentially expressed proteins between frequent and infrequent acute exacerbations of COPD, FC>1.2 or <0.83 and p-value<0.05;

[0030] Figure 3 Figure 1 shows the results of differential protein GO analysis between the frequent and infrequent acute exacerbations of COPD.

[0031] Figure 4 Figure 1: KEEG analysis results of differentially expressed proteins between the frequent and infrequent acute exacerbations of COPD.

[0032] Figure 5 Differential protein ROC curves for predicting frequent acute exacerbations of COPD;

[0033] Figure 6 ROC curves of 11 differentially expressed proteins for predicting frequent acute exacerbations of COPD. Detailed Implementation

[0034] To further illustrate the technical means and effects of this invention, the following description, in conjunction with embodiments and accompanying drawings, provides a further explanation of the invention. It is understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it.

[0035] Where specific techniques or conditions are not specified in the examples, they shall be performed in accordance with the techniques or conditions described in the literature in this field, or in accordance with the product instructions. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased through legitimate channels.

[0036] Example 1

[0037] Plasma was collected from 34 patients with frequent acute exacerbations of COPD and 42 patients with infrequent acute exacerbations. The plasma from patients with frequent acute exacerbations and patients with infrequent acute exacerbations of COPD were then compared and analyzed using high-throughput proteomics.

[0038] The specific process is as follows:

[0039] This study included patients with stable COPD who visited the outpatient department of Zhongshan Hospital affiliated with Fudan University between March 2017 and September 2018 (with no history of acute exacerbations within 4 weeks prior to enrollment). Patients were divided into frequent and infrequent exacerbation groups based on their history of acute exacerbations. An acute exacerbation was defined as an acute worsening of respiratory symptoms requiring emergency or hospitalization for antibiotic or systemic steroid treatment. Frequent exacerbations were defined as at least two acute exacerbations per year or hospitalization due to one exacerbation. Researchers recorded patients' demographic data, smoking history, and history of exposure to biofuels or occupational exposure, laboratory tests, pulmonary function tests, and collected peripheral venous blood samples. Included patients were ≥40 years old and had a smoking history (years of smoking × packs smoked per day) ≥10, or a history of exposure to biofuels or occupational exposure. Exclusion criteria included: 1) history of acute lung disease within 3 months; 2) history of other chronic lung diseases (e.g., bronchiectasis, pulmonary interstitial fibrosis); 3) history of malignant tumors; 4) pregnant or lactating women. After patient enrollment, approximately 5 mL of blood was collected into an anticoagulant blood collection tube and centrifuged as soon as possible (4°C, 3000 rpm, 10 min). The supernatant plasma was stored at -80°C. To detect lower concentrations of plasma proteins, 14 high-abundance human proteins and structural proteins were removed according to the manufacturer's instructions. After trypsin digestion of proteins, peptides were separated using high-pH reversed-phase high-performance liquid chromatography (HPLC). Data-dependent and data-independent acquisition analyses were performed using a Q-Exactive mass spectrometer (Thermo) and an Easy-nanoLC 1200 system. The spectral library of plasma samples was constructed from raw MS files in the Human UniProt protein database and analyzed using Proteome Discoverer (V2.1.0.81). The raw data from the spectral library and DIA were loaded into Spectranaut Pulsar X software by relative protein quantification analysis. After using a t-test, p-values ​​< 0.05 and fold changes in expression levels > 1.2 or < 0.83 were used as criteria for processing DIA data to screen for differentially expressed proteins between frequent acute adventitious groups and infrequent acute adventitious groups.

[0040] Results showed that mass spectrometry analysis of plasma proteins from both groups identified 47 differentially expressed proteins. Of these, 20 proteins were upregulated and 27 were downregulated. Figure 2 ).

[0041] Example 2

[0042] Forty-seven differentially expressed proteins screened in Example 1 were subjected to GO enrichment analysis, KEGG signaling pathway enrichment analysis, and ROC curve analysis.

[0043] The specific process is as follows: GO enrichment analysis and KEGG signaling pathway analysis were performed using Metascape (http: / / metascape.org). ROC curve analysis was performed using SPSS software.

[0044] GO enrichment analysis results are as follows Figure 3 As shown, the biological processes are mainly enriched in the following aspects: neutrophil degranulation, cellular or subcellular component motility, and immune responses. Furthermore, changes in cellular components are related to extracellular vesicles, extracellular space, and extracellular regions. In addition, changes in molecular function are related to protein homodimerization activity, ribonuclease activity, and endonuclease activity.

[0045] KEGG signal pathway enrichment analysis results are as follows: Figure 4 As shown, the differentially expressed proteins are mainly involved in complement and coagulation cascade reactions, bacterial invasion of epithelial cells, and arginine and proline metabolism.

[0046] The ROC curve analysis results are as follows: Figure 5 As shown, the AUC of 11 differentially expressed proteins was >0.7, including: interstitial α-trypsin inhibitor heavy chain H3, lymphatic endothelial hyaluronic acid receptor 1, paraoxygenase 1, alanine glyoxylate transaminase, immunoglobulin κ variable region 3D-11, cytosolic protein 2, apolipoprotein F, dopamine β-hydroxylase, muscle creatine kinase, FAM20C Golgi-associated secretory pathway kinase, and fat storage-induced transmembrane protein 1.

[0047] ROC analysis of these 11 differentially expressed proteins showed an AUC of 0.985 (95% CI: 0.966–1.000), a sensitivity of 90.9%, and a specificity of 100%. Figure 6 This indicates that using specific combinations of biomarkers can further improve detection sensitivity and specificity.

[0048] Example 3

[0049] Enzyme-linked immunosorbent assay (ELISA) was used to detect individual differentially expressed proteins in plasma to determine the concentration changes of the detected differentially expressed proteins.

[0050] The specific process includes:

[0051] 1) Prepare the standard solution, detection antibody, horseradish peroxidase-labeled streptavidin, and washing solution according to the instructions;

[0052] 2) Prepare the required number of strips based on the quantity of standards and the quantity of samples to be tested. First, soak the microplate with 300 μL / well washing buffer.

[0053] 3) Add 100 μL of plasma sample and the pre-prepared standards of various concentrations in sequence, then add 50 μL of detection antibody, seal the plate with sealing film, shake to mix, and incubate at 25°C for 90 min.

[0054] 5) Discard the liquid in the well plate, add 300 μL of washing solution to each well, wait for 1 minute and then discard the washing solution. Wipe the plate dry on absorbent paper. Repeat 4 times.

[0055] 6) Add 100 μL of horseradish peroxidase-labeled streptavidin to each well, seal the plate with a new sealing membrane, and incubate at 25°C with shaking for 30 min.

[0056] 7) Discard the liquid in the well plate, add 300 μL of washing solution to each well, wait for 1 min and then discard the washing solution. Wipe the plate dry on absorbent paper. Repeat 4 times.

[0057] 8) Add 100 μL of colorimetric reagent to each well and incubate at 25°C in the dark for 20 min;

[0058] 9) Add 100 μL of stop solution to each well and mix thoroughly;

[0059] 10) Measure OD on an ELISA reader. 450nm value;

[0060] 11) Use Excel to plot a standard curve and calculate the concentration of differentially expressed proteins in plasma.

[0061] Table 1 lists the differentially expressed plasma proteins in patients with frequent and infrequent COPD exacerbations.

[0062] Table 1. Differences in plasma protein levels between patients with frequent and infrequent acute exacerbations of COPD.

[0063]

[0064]

[0065] In summary, this invention discovers novel nucleic acid / protein biomarkers that can be used to detect and identify patients with frequent and infrequent acute exacerbations during the stable phase of COPD. These biomarkers can improve the specificity, sensitivity, and accuracy of detection. Compared with existing COPD-related diagnostic and differential diagnostic tests, the detection based on the biomarkers of this invention has higher diagnostic and therapeutic specificity and monitoring and early warning capabilities.

[0066] The applicant declares that the detailed method of the present invention is illustrated by the above embodiments, but the present invention is not limited to the above detailed method, that is, it does not mean that the present invention must rely on the above detailed method to be implemented. Those skilled in the art should understand that any improvements to the present invention, equivalent substitutions of the raw materials of the product of the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

Claims

1. A set of biomarkers associated with the phenotype of frequent acute exacerbations of COPD, characterized in that, The biomarkers consist of interstitial α-trypsin inhibitor heavy chain H3, lymphatic endothelial hyaluronic acid receptor 1, paraoxygenase 1, alanine glyoxylate transaminase, immunoglobulin κ variable region 3D-11, cytosolic protein 2, apolipoprotein F, dopamine β-hydroxylase, muscle creatine kinase, FAM20C Golgi-associated secretory pathway kinase, and adipose storage-induced transmembrane protein 1.

2. The use of the biomarkers and / or substances for detecting the frequent exacerbations of COPD as described in claim 1 in the preparation of products that predict or assist in the prediction of the frequent exacerbations of COPD.

3. A group of products that predict or assist in predicting the frequent acute exacerbation phenotype of COPD, characterized in that, The product includes reagents and / or devices for detecting the expression levels of biomarkers associated with the frequent acute exacerbation phenotype of COPD as described in claim 1.

4. The application of the biomarkers associated with the frequent acute exacerbation phenotype of COPD as described in claim 1 in constructing a predictive model for the frequent acute exacerbation phenotype of COPD and / or in preparing a predictive device for the frequent acute exacerbation phenotype of COPD.

5. A predictive model for frequent acute exacerbations of COPD, characterized in that, The prediction model is used to perform the following: Input the expression levels of the biomarkers associated with frequent acute exacerbations of COPD as described in claim 1, and fit a binary logistic regression model; Using a fitted binary logistic regression model, the Nomogram results were calculated. Based on the contribution of each protein to the outcome variable in the model, the expression level of each protein was scored. Then, the scores were summed to obtain the total score. Finally, the predictive value of the subject having the frequent acute exacerbation phenotype of COPD was calculated by using the functional transformation relationship between the total score and the probability of the outcome event.

6. A device for predicting the phenotype of frequent acute exacerbations of COPD, characterized in that, The device includes a detection unit and an evaluation unit; The detection unit is used to perform the following: The expression levels of the biomarkers associated with the frequent acute exacerbations of COPD as described in claim 1 were detected in the body fluid samples of the subjects. The evaluation unit is used to perform the following: The expression levels of biomarkers associated with the frequent acute exacerbation phenotype of COPD detected by the analysis unit are input into the COPD frequent acute exacerbation phenotype prediction model of claim 5 for calculation, and it is determined whether the patient is a COPD frequent acute exacerbation patient.

7. The COPD frequent acute exacerbation phenotype prediction device according to claim 6, characterized in that, The body fluid sample to be tested includes any one of peripheral circulating blood, urine, saliva, sputum, irrigation fluid, sweat, or extracellular vesicles of body fluids.

8. The COPD frequent acute exacerbation phenotype prediction device according to claim 6 or 7, characterized in that, The detection methods include proteometry, enzyme-linked immunosorbent assay (ELISA), or protein chip assay.

9. The biomarker associated with the frequent acute exacerbation phenotype of COPD as described in claim 1 can be used as a target in screening drugs for the prevention or treatment of the frequent acute exacerbation phenotype of COPD.

10. The application according to claim 9, characterized in that, The screening includes determining whether a candidate drug can be used to prevent or treat the frequent exacerbation phenotype of COPD based on the effects of candidate drug use on biomarkers associated with the COPD frequent exacerbation phenotype before and after use.

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