Biomarker combinations for the diagnosis of asthma in pre-school children and screening methods thereof

Abstract

This invention discloses a combination of biomarkers for diagnosing asthma in preschool children and a screening method thereof, belonging to the field of biomedicine. The biomarker combination includes the insulin-like growth factor acid-instable subunit IGFALS and latent transforming growth factor binding protein LTBP1. The amino acid sequence of the IGFALS molecular marker is shown in SEQ ID NO.1, and the amino acid sequence of the LTBP1 molecular marker is shown in SEQ ID NO.2. This invention obtains and purifies the biomarker combination IGFALS+LTBP1 by screening in the peripheral blood of patients, providing a more convenient and reliable basis for the early diagnosis of asthma in preschool children, effectively improving the diagnostic accuracy of asthma in preschool children and simplifying the diagnostic process.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, specifically to a combination of biomarkers for diagnosing asthma in preschool children and a screening method thereof. Background Technology

[0002] Asthma is the most common chronic disease in children, characterized by airway hyperresponsiveness, reversible airway obstruction, and chronic airway inflammation. The incidence and hospitalization rates of asthma are higher in preschool children than in older adults. Lung function trajectories are established during childhood, and asthma-related airway remodeling occurs before age 3 in children aged 4-7. Therefore, preschool children are a critical period for asthma intervention, and accurate identification and diagnosis of asthma in preschool children may help in understanding asthma symptoms and improving treatment adherence. Because asthma symptoms are recurrent and fluctuating, diagnosis in children remains challenging, and effective independent diagnostic tests are scarce. Recently, the National Institute for Health and Care Excellence and the Asthma 10-12 Global Initiative proposed a diagnostic algorithm that combines available tests, such as vital capacity measurement, bronchodilator reversibility testing, bronchial provocation testing to measure bronchial hyperresponsiveness, exhaled nitric oxide fraction (FeNO), and allergy testing.

[0003] However, the accuracy of these algorithms in diagnosing asthma in preschool children remains uncertain. Therefore, there is an urgent need for better asthma diagnostic methods. To achieve this goal, new research is needed to identify biomarkers that distinguish asthmatic children from healthy preschool children, which can then be incorporated into diagnostic algorithms. In asthma, certain proteins associated with airway obstruction and inflammation are produced in tissue cells and secreted into the circulatory system. Therefore, proteomics is a promising approach for identifying potential diagnostic biomarkers for asthma in preschool children. Although proteomics has been used in previous studies to analyze blood samples from asthma patients, most have used data-dependent acquisition (DDA)-mass spectrometry (MS) and focused on older children or adults. Data-independent acquisition (DIA)-MS is a time-parallel acquisition method with better consistency and reproducibility than DDA, and is particularly suitable for large-scale proteomics studies. Previous studies have identified several asthma protein biomarkers. For example, Nieto-Fontarigo et al. found serum IGFALS to be a biomarker for allergic asthma in adults. Zamora et al. identified salivary interleukin (IL)-8 and IL-10 as biomarkers for childhood asthma. Another study showed that sputum LXA4 can differentiate between children with severe asthma and those with intermittent asthma. Furthermore, proteomic analysis revealed varying degrees of accumulation of C7, C3, C4, α-1-antitrypsin, PDE7, arginase, UK16-binding protein, phospholipase D, and cyclooxygenase in the serum of both patients with bronchial asthma and healthy individuals. However, few studies have focused on biomarkers of asthma in preschool children, making asthma diagnosis more challenging in this population.

[0004] To address the above issues, there is an urgent need to design a combination of biomarkers and a screening method for diagnosing asthma in preschool children, in order to solve the problems existing in the current technology. Summary of the Invention

[0005] To address the aforementioned problems, this invention aims to provide a combination of biomarkers for diagnosing asthma in preschool children and a screening method thereof. The biomarker combination IGFALS+LTBP1 was obtained and purified by screening in the peripheral blood of patients, providing a more convenient and reliable basis for the early diagnosis of asthma in preschool children. This can effectively improve the diagnostic accuracy of asthma in preschool children and simplify the diagnostic process.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A combination of biomarkers for diagnosing asthma in preschool children includes the insulin-like growth factor acid-instable subunit IGFALS and latent transforming growth factor binding protein LTBP1, wherein the amino acid sequence of the IGFALS molecular marker is shown in SEQ ID NO.1 and the amino acid sequence of the LTBP1 molecular marker is shown in SEQ ID NO.2.

[0008] A method for diagnosing asthma in preschool children using a combination of biomarkers, comprising the steps of

[0009] S1. Collection of subjects and serum samples;

[0010] S2. Protein extraction from serum and trypsin digestion;

[0011] S3. Perform high-pH reverse-phase fractionation on the peptides treated in step S2;

[0012] S4. Perform (DDA)LC–MS / MS analysis on the peptides processed in step S3 to infer protein composition;

[0013] S5. Based on step S4, perform (DIA)LC–MS / MS analysis to screen out the molecular markers IGFALS and LTBP1.

[0014] Preferably, the method for collecting serum samples in step S1 includes:

[0015] S11. On the morning of the second day after the patient has not received any drug treatment, collect a 4 mL blood sample and place it at room temperature (22–25°C) in the dark for 1 hour.

[0016] S12. Then centrifuge at 3000 rpm for 15 minutes at 4°C to separate the serum;

[0017] S13. Finally, divide the serum into equal portions and store them in a refrigerator at 80°C.

[0018] Preferably, the protein extraction and trypsin digestion process in step S2 includes the following steps:

[0019] S21. Centrifuge the serum sample at 12000g for 10 minutes at 4℃ to remove cell debris;

[0020] S22. Then, retain the supernatant and use the BCA kit to determine the protein concentration in the serum;

[0021] S23. Then, reduce the serum protein solution with 5 mM dithiothreitol at 56 °C for 30 minutes and alkylate it with 11 mM iodoacetamide for 15 minutes in the dark at room temperature;

[0022] S24. For the first overnight digestion, add trypsin at a ratio of 1:50; for the second 4-hour digestion, add trypsin at a ratio of 1:100.

[0023] S25. The digested peptides were desalted using C18 Ziptips, eluted with 0.1% TFA dissolved in 50–70% acetonitrile, then lyophilized and redissolved in 1% formic acid and 5% acetonitrile;

[0024] S26. Add the iRT peptide to the sample prior to LC–MS / MS analysis.

[0025] Preferably, the high pH-reverse phase fractionation process of the peptide described in step S3 includes:

[0026] S31. The peptide solutions treated in step S2 were combined in equal volumes and further separated by high pH-reversed phase separation using a Dionex UHPLC and ethylene-bridged hybrid C18 column at 40°C, with a flow rate of 0.2 mL / min and an ACN gradient of 5-30% in 5 mM ammonium formate at pH 10 for 60 minutes.

[0027] S32. Collect scores at 1-minute intervals and aggregate them into 12 scores;

[0028] S33. Then, each component is lyophilized and redissolved in 1% formic acid and 5% acetonitrile.

[0029] Preferably, the process of analyzing peptides by (DDA)LC-MS / MS in step S4 includes the following steps:

[0030] S41. First, each peptide was loaded onto an Easy-nLC1200UPLC system and separated at 50 °C in a linear gradient of 250 nL / min from 95% solvent to 28% solvent B (0.1% formic acid / 80% acetonitrile) over 120 minutes.

[0031] Solvent A contains 0.1% formic acid, 2% acetonitrile and 98% water, and solvent B contains 0.1% formic acid and 80% acetonitrile.

[0032] S42. The mass spectrometer was operated in data-dependent mode, acquiring full MS scans from 350 to 1500 m / z at high resolution R=120000;

[0033] Among them, the MS / MS scan resolution is 30000, the isolation window is 4Da, and the high-energy collision dissociation (HCD) fragmentation has a collision energy of 30±5%.

[0034] S43. Dynamic exclusion is set to 30 seconds, raw data is processed using the Pulsar search engine in SpectronautX, and the UniProt human proteome database is searched within the default parameters to generate a spectral library.

[0035] S44. Use the IDPicker algorithm in the Spectronaut software for protein inference.

[0036] Preferably, the (DIA)LC-MS / MS analysis process described in step S5 includes the following steps:

[0037] S51. For MS / MS acquisition, set the DIA mode according to the 50 variable isolation windows of the full width at half maximum (FWTH), and construct a specific window list based on the corresponding DDA data of the merged samples;

[0038] S52. In the range of m / z from 350 to 1500, the full scan is set to 1200,000, followed by a diameter scan with a resolution of 30,000.

[0039] During scanning, CE was set to 30.5%; AGC target was 1e6; maximum injection time was 54ms; DIA raw files were processed using Spectronaut and default parameters; retention time prediction type was dynamic iRT; correction factor was window 1; and interference correction at the MS2 level was enabled. System variance was normalized using a local normalization strategy; and FDR for peptide precursors and proteins was evaluated using the mProphet method with a 1% critical value.

[0040] S53. Calculate the total peak area of ​​peptide MS2 fragment ions as protein intensity, filter all results using Q value and 1% FDR critical value, and complete the screening of molecular markers IGFALS and LTBP1.

[0041] The beneficial effects of this invention are: This invention discloses a combination of biomarkers for diagnosing asthma in preschool children and a screening method thereof. Compared with the prior art, the improvement of this invention lies in:

[0042] 1. This invention is the first to obtain and purify the biomarker combination IGFALS+LTBP1 by screening in the peripheral blood of patients, and at the same time confirms the objective existence of the biomarker combination IGFALS+LTBP1 in the peripheral blood of patients;

[0043] 2. The serum protein molecular marker combination IGFALS+LTBP1 extracted in this invention can provide a more convenient and reliable basis for the early diagnosis of asthma in preschool children. By combining the expression level of the combined molecular marker with other asthma diagnostic indicators for comprehensive evaluation, the diagnostic accuracy of asthma in preschool children can be improved, the diagnostic process can be simplified, and it plays an important role in the diagnosis and treatment of childhood asthma. Attached Figure Description

[0044] Figure 1 The results of biomarker screening and validation in this invention

[0045] Among them: Figure 1 In the figure, Figure (a) is a heatmap of the abundance of six candidate biomarkers in the preschool asthma and healthy cohorts from proteomics data, Figure (b) is the ELISA validation data of three candidate biomarkers in the preschool asthma and healthy cohorts, Figure (c) is the ROC analysis of the proteomics data of biomarkers in the preschool asthma and healthy cohorts, and Figure (d) is the ROC analysis of the ELISA validation data of biomarkers in the preschool asthma and healthy cohorts. Detailed Implementation

[0046] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0047] Example 1: Refer to Appendix Figure 1 The biomarker combination screening method shown for diagnosing asthma in preschool children includes the following steps:

[0048] S1. Subject and Serum Sample Collection

[0049] Between 2020 and 2021, a cohort of 46 children was recruited from the Second Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine. These children were divided into three study groups: acute asthma exacerbation (n=17), recovery asthma (n=19), and healthy controls (n=10). Children with immune disorders, chronic kidney disease, or other diseases affecting serum proteins were excluded. All clinical diagnoses were in accordance with the 2019 Global Asthma Initiative guidelines

[10] . On the morning of the second day after admission without medication, blood samples (4 mL) were collected, kept in the dark at room temperature (22–25°C) for 1 hour, and then centrifuged at 3000 rpm for 15 minutes at 4°C to separate the serum. Finally, the serum was aliquoted and stored in a refrigerator at 80°C. The study protocol was approved by the Ethics Committee of the Second Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine (ChiCTR2000033383). Written informed consent was provided by all participants.

[0050] S2. Protein extraction and trypsin digestion

[0051] First, serum samples were centrifuged at 12,000g for 10 minutes at 4°C to remove cell debris. The supernatant was then retained, and serum protein concentration was determined using a BCA kit (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer's instructions. The serum protein solution was then reduced with 5 mM dithiothreitol at 56°C for 30 minutes and alkylated with 11 mM iodoacetamide for 15 minutes in the dark at room temperature. A first overnight digestion was performed with trypsin added at a ratio of 1:50 (trypsin / protein mass ratio), followed by a second 4-hour digestion with trypsin added at a ratio of 1:100. The digested peptides were desalted using C18 Ziptips (Millipore), eluted with 0.1% TFA dissolved in 50–70% acetonitrile, lyophilized, and redissolved in 1% formic acid and 5% acetonitrile. iRT peptides (Biognosys, Schlieren, Switzerland) were added to the sample prior to LC-MS / MS analysis according to the manufacturer's instructions.

[0052] S3. High pH value - Reverse phase fractionation

[0053] Equal volumes of the treated peptide solutions from the subjects were combined and further separated by high pH reversed-phase separation using a Dionex UHPLC (Thermo Fisher Scientific) with an ethylene-bridged hybridized C18 column (Waters) at 40 °C, at a flow rate of 0.2 mL / min and a 60-minute ACN gradient (5–30%) in 5 mM ammonium formate (pH 10). Fractions were collected at 1-minute intervals and pooled into 12 fractions. Each fraction was then lyophilized and redissolved in 1% formic acid and 5% acetonitrile.

[0054] S4. Data-dependent acquisition (DDA) LC-MS / MS analysis and spectral library generation

[0055] To generate the spectral library, DDA-MS analysis was performed in tandem with an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific) on an Easy-nLC1200 UPLC system. First, each peptide was loaded onto the Easy-nLC1200 UPLC system and separated at 250 nL / min within a linear gradient of 120 min from 95% solvent A (0.1% formic acid / 2% acetonitrile / 98% water) to 28% solvent B (0.1% formic acid / 80% acetonitrile). The mass spectrometer was operated in data-dependent mode. Full MS scans from 350 to 1500 m / z were acquired at high resolution R = 120,000 (defined as m / z = 400); MS / MS scans were performed at a resolution of 30,000, with an isolation window of 4 Da and high-energy collisional dissociation (HCD) fragmentation at a collision energy of 30 ± 5%. Dynamic exclusion was set to 30 seconds. Raw data was processed using the Pulsar search engine in SpectronautX (Biognosys, Schlieren, Switzerland), and the UniProt proteome database was searched within default parameters to generate a spectral library. The digestive enzyme was a specific trypsin with two deletions for specific cleavage; the fixed modification was the aminomethyl group of cysteine, and the variable modification was the oxidation of methionine. The iRT was calculated from the median iRT of all DDA runs. Fragment ions used for target data analysis were selected from 300 to 1800 m / z, with a minimum relative intensity set to >5% and a fragment ion count >3. The false discovery rate (FDR) for protein and peptide spectrum matching was set to 1%. Protein inference was performed using the IDPicker algorithm in Spectronaut software.

[0056] S5. Independent Data Acquisition (DIA) LC–MS / MS Analysis

[0057] DIA-MS was performed using the same LC–MS system and LC linear gradient method as DDA-MS. For MS / MS acquisition, the DIA mode was set to 50 variable isolation windows based on FWTH (full width at half maximum), and a specific window list was constructed based on the corresponding DDA data of the pooled samples. Full scans were set to 1,200,000 m / z, followed by diameter scans at 30,000 m / z resolution, within the m / z range of 350 to 1500; CE: 30.5%; AGC target: 1e6; maximum injection time: 54 ms. DIA raw files were processed using SpectronautX (Biognosys, Schlieren, Switzerland) with default parameters. Retention time prediction type was set to dynamic iRT, correction factor to window 1, and interference correction at the MS2 level was enabled. System variance was normalized using a local normalization strategy. FDR for peptide precursors and proteins was evaluated using the mProphet method with a 1% critical value. The total peak area of ​​peptide MS2 fragment ions was calculated as the protein intensity. All results were filtered using the Q value and a 1% FDR threshold to obtain the differentially expressed proteins in the serum proteome as shown in Table 1.

[0058] Table 1: Differentially Differential Proteins in Serum Proteome

[0059]

[0060] a Relative abundance is the LC-MS / MS intensity value.

[0061] b The p-value is the p-value of the Kruskal-Wallis test.

[0062] Example 2: The biomarker combination obtained by the preparation method described in Example 1 includes IGFALS and LTBP1. IGFALS is the protein name or gene name of the acid unstable subunit of insulin-like growth factor in a relevant database, and the amino acid sequence of the IGFALS molecular marker is shown in SEQ ID NO.1. LTBP1 is the protein name or gene name of latent transforming growth factor binding protein in a relevant database, and the amino acid sequence of the LTBP1 molecular marker is shown in SEQ ID NO.2.

[0063] Example 3: Unlike the examples above, this example was designed to demonstrate that the biomarker combination (IGFALS+LTBP1) described in Examples 1 and 2 can be applied to the detection of peripheral blood in preschool children with asthma.

[0064] In this embodiment, IGFALS and LTBP1 screening were performed using liquid chromatography-mass spectrometry (LC-MS / MS). The main conditions of this method include trypsin, buffer, water, chromatographic conditions, and mass spectrometry conditions. The characteristics of the above reagents and conditions are known to the public, and their preparation and setting methods are performed using methods well known to those skilled in the art.

[0065] Experiments have shown that IGFALS and LTBP1 are significantly upregulated in the serum of preschool children with asthma compared to the serum of healthy children. Therefore, this embodiment proposes a scientific hypothesis based on literature and research: IGFALS and LTBP1 can serve as a combination of early biomarkers for predicting asthma in preschool children, and this hypothesis has been confirmed by the following experimental design.

[0066] The following experimental methods are specific examples:

[0067] 1. Subject and serum sample collection

[0068] Between 2020 and 2021, a cohort of 46 children was recruited from the Second Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine. These children were divided into three study groups: acute asthma exacerbation (n=17), recovery asthma (n=19), and healthy controls (n=10). Children with immune disorders, chronic kidney disease, or other diseases affecting serum proteins were excluded. All clinical diagnoses were made in accordance with the 2019 Global Asthma Initiative guidelines. On the morning of the second day after admission without medication, blood samples (4 mL) were collected, kept in the dark at room temperature (22–25°C) for 1 hour, and then centrifuged at 3000 rpm for 15 minutes at 4°C to separate the serum. Finally, the serum was aliquoted and stored in a refrigerator at 80°C.

[0069] 2. ELISA Validation

[0070] All reagents and components should be brought to room temperature first. Reproduced wells are recommended for standards, controls, and samples. Prepare working solutions for each component of the kit according to the instructions. Remove the required strips from the foil pouch; seal any remaining strips in a resealable bag and return them to the refrigerator. Set up wells for standards, zero values, blanks, and samples. Add 50 μL of different concentrations of standard to each well, 50 μL of sample diluent to each zero value well, nothing to the blank wells, and 50 μL of the sample to be tested to each sample well. Except for the blank wells, add 100 μL of horseradish peroxidase (HRP)-labeled detection antibody to each well (HRP, HRP, and sample). Cover the reaction plate with sealing film and incubate at 37°C in a water bath or incubator in the dark for 60 min. Remove the sealing film, discard the liquid, pat dry on absorbent paper, fill each well with washing buffer, let stand for 20 seconds, shake off the washing buffer, pat dry on absorbent paper, and repeat this process 5 times. If using an automated plate washer, please follow the washer's operating procedure. Adding a 30-second soaking time can improve detection accuracy. After washing, before adding the substrate, thoroughly pat the reaction plate dry on clean, lint-free paper. Mix substrates A and B thoroughly in a 1:1 volume ratio, and add 100 μL of the substrate mixture to all wells. Cover the reaction plate with sealing film and incubate at 37°C in a water bath or incubator in the dark for 15 minutes. Add 50 μL of stop solution to all wells, and read the absorbance (OD value) of each well on a microplate reader. Plot a standard curve and calculate the content of the analyte as shown in Table 1.

[0071] Table 2: Test Results Table

[0072]

[0073] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A combination of biomarkers for diagnosing asthma in preschool children, characterized in that: It includes the insulin-like growth factor acid unstable subunit IGFALS and latent transforming growth factor binding protein LTBP1. The amino acid sequence of the IGFALS molecular marker is shown in SEQ ID NO.1, and the amino acid sequence of the LTBP1 molecular marker is shown in SEQ ID NO.

2.

2. A method for preparing a combination of biomarkers for diagnosing asthma in preschool children as described in claim 1, characterized in that: Including steps S1. Collection of subjects and serum samples; S2. Protein extraction from serum and trypsin digestion; S3. Perform high-pH reverse-phase fractionation on the peptides treated in step S2; S4. Perform (DDA)LC–MS / MS analysis on the peptides processed in step S3 to infer protein composition; S5. Based on step S4, perform (DIA)LC–MS / MS analysis to screen out the molecular markers IGFALS and LTBP1.

3. The method for screening a combination of biomarkers for diagnosing asthma in preschool children according to claim 2, characterized in that: The method for collecting serum samples in step S1 includes: S11. On the morning of the second day after the patient has not received any drug treatment, collect a 4 mL blood sample and place it at room temperature (22–25°C) in the dark for 1 hour. S12. Then centrifuge at 3000 rpm for 15 minutes at 4°C to separate the serum; S13. Finally, divide the serum into equal portions and store them in a refrigerator at 80°C.

4. The method for screening a combination of biomarkers for diagnosing asthma in preschool children according to claim 2, characterized in that: The protein extraction and trypsin digestion process described in step S2 includes the following steps: S21. Centrifuge the serum sample at 12000g for 10 minutes at 4℃ to remove cell debris; S22. Then, retain the supernatant and use the BCA kit to determine the protein concentration in the serum; S23. Then, reduce the serum protein solution with 5 mM dithiothreitol at 56 °C for 30 minutes and alkylate it with 11 mM iodoacetamide for 15 minutes in the dark at room temperature; S24. For the first overnight digestion, add trypsin at a ratio of 1:50; for the second 4-hour digestion, add trypsin at a ratio of 1:

100. S25. The digested peptides were desalted using C18 Ziptips, eluted with 0.1% TFA dissolved in 50–70% acetonitrile, then lyophilized and redissolved in 1% formic acid and 5% acetonitrile; S26. Add the iRT peptide to the sample prior to LC–MS / MS analysis.

5. The method for screening a combination of biomarkers for diagnosing asthma in preschool children according to claim 2, characterized in that: Step S3 describes the high pH-reverse phase fractionation process of the peptide, which includes... S31. The peptide solutions treated in step S2 were combined in equal volumes and further separated by high pH-reversed phase separation using a Dionex UHPLC and ethylene-bridged hybrid C18 column at 40°C, with a flow rate of 0.2 mL / min and an ACN gradient of 5-30% in 5 mM ammonium formate at pH 10 for 60 minutes. S32. Collect scores at 1-minute intervals and aggregate them into 12 scores; S33. Then, each component is lyophilized and redissolved in 1% formic acid and 5% acetonitrile.

6. The method for screening a combination of biomarkers for diagnosing asthma in preschool children according to claim 2, characterized in that: Step S4 describes the process of analyzing peptides using (DDA) LC-MS / MS, which includes the following steps: S41. First, each peptide was loaded onto an Easy-nLC 1200UPLC system and separated at 50 °C in a linear gradient of 250 nL / min from 95% solvent to 28% solvent B (0.1% formic acid / 80% acetonitrile) over 120 minutes. Solvent A contains 0.1% formic acid, 2% acetonitrile and 98% water, and solvent B contains 0.1% formic acid and 80% acetonitrile. S42. The mass spectrometer was operated in data-dependent mode, acquiring full MS scans from 350 to 1500 m / z at high resolution R=120000; Among them, the MS / MS scan resolution is 30000, the isolation window is 4Da, and the high-energy collision dissociation (HCD) fragmentation has a collision energy of 30±5%. S43. Dynamic exclusion is set to 30 seconds, raw data is processed using the Pulsar search engine in Spectronaut X, and the UniProt human proteome database is searched within the default parameters to generate a spectral library. S44. Use the ID Picker algorithm in the Spectronaut software to infer proteins.

7. The method for screening a combination of biomarkers for diagnosing asthma in preschool children according to claim 2, characterized in that: The (DIA) LC-MS / MS analysis procedure described in step S5 includes the following steps: S51. For MS / MS acquisition, set the DIA mode according to the 50 variable isolation windows of the full width at half maximum (FWTH), and construct a specific window list based on the corresponding DDA data of the merged samples; S52. In the range of m / z from 350 to 1500, the full scan is set to 1200,000, followed by a diameter scan with a resolution of 30,000. During scanning, CE was set to 30.5%; AGC target was 1e6; maximum injection time was 54ms; DIA raw files were processed using Spectronaut and default parameters; retention time prediction type was dynamic iRT; correction factor was window 1; and interference correction at the MS2 level was enabled. System variance was normalized using a local normalization strategy; and FDR for peptide precursors and proteins was evaluated using the mProphet method with a 1% critical value. S53. Calculate the total peak area of ​​peptide MS2 fragment ions as protein intensity, filter all results using Q value and 1% FDR critical value, and complete the screening of molecular markers IGFALS and LTBP1.

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