Application of Protein Biomarkers in Identifying Acute Pulmonary Embolism Complicated with Pulmonary Arterial Hypertension Model

Abstract

The present invention belongs to the technical field of biology, and provides the application of protein markers in identifying a model of acute pulmonary embolism complicated with pulmonary hypertension. Based on the plasma proteomics data of patients with acute pulmonary embolism, the present invention obtains protein markers related to acute pulmonary embolism complicated with pulmonary hypertension, and the protein marker combination is composed of LRG1, LDHA and PEPD. The model includes the following content: LogitP = 2.031 * LRG1 - 1.524 * PEPD - 0.719 * LDHA - 0.730, where P is the probability of complicated with pulmonary hypertension. This protein marker combination can be used to identify whether a patient with acute pulmonary embolism is complicated with pulmonary hypertension, and can help guide the risk stratification and formulation of treatment strategies for patients with acute pulmonary embolism, thereby improving the prognosis of patients.

Description

Technical Field

[0001] The present invention belongs to the technical field of biology, and particularly relates to the application of protein markers in establishing a model for identifying acute pulmonary embolism complicated with pulmonary hypertension. Background Art

[0002] In acute pulmonary embolism, the elevation of pulmonary artery pressure and the resulting dysfunction of the right ventricular function are closely related to the clinical deterioration and prognosis of patients. The right heart failure caused by pulmonary embolism leading to pulmonary hypertension is the main cause of patient death. It is reported that about 35%-61% of patients have concurrent pulmonary hypertension at the time of diagnosis of acute pulmonary embolism, 45%-64% of patients may further develop right ventricular dilation, and the 30-day mortality rate of patients with right ventricular dilation is about 15%, which is twice that of patients with normal pulmonary artery pressure and right ventricular diameter. Based on this, in the 2019 ESC Guidelines for the Diagnosis and Treatment of Pulmonary Embolism (Konstantinides SV, Meyer G, Becattini C, et al. 2019 ESC Guidelines for the diagnosis and management of acute pulmonary embolism developed in collaboration with the European Respiratory Society (ERS). Eur Heart J 2020; 41: 543-603. 2019 / 09 / 11. DOI: 10.1093 / eurheartj / ehz405.), pulmonary hypertension and the resulting right ventricular dysfunction are recommended as an important reference index in the risk stratification and treatment strategy of acute pulmonary embolism. Therefore, based on the importance of pulmonary hypertension and the resulting right ventricular insufficiency in the risk stratification, treatment strategy formulation and prognosis evaluation of acute pulmonary embolism patients, how to accurately, simply and non-invasively identify whether acute pulmonary embolism patients have concurrent pulmonary hypertension and the resulting right ventricular insufficiency is a key link in the diagnosis and treatment of acute pulmonary embolism patients.

[0003] Currently, there are various clinical methods available to evaluate pulmonary hypertension and the resulting right ventricular dysfunction, including imaging methods such as ultrasound, magnetic resonance, and right heart catheterization, as well as biomarker detection represented by NT-proBNP. However, echocardiography is easily affected by variant factors such as cardiac structure, morphology, preload and afterload, and the subjective factors of the operator. The accuracy of judging pulmonary hypertension and the resulting right ventricular dysfunction remains a challenge; although right heart catheterization and magnetic resonance imaging are the gold standards for evaluating pulmonary hypertension and the resulting right ventricular dysfunction, their clinical applications are not widespread due to invasive operation characteristics or the complexity and high cost of equipment conditions, and their applications are more restricted in patients with unstable conditions during the acute phase of pulmonary embolism. At this time, as a simple and non-invasive evaluation method, biomarkers are more crucial in evaluating whether acute pulmonary embolism patients are complicated with pulmonary hypertension and the resulting right ventricular dysfunction. However, there is currently a lack of specific biomarkers related to acute pulmonary embolism complicated with pulmonary hypertension and the resulting increase in right ventricular afterload. NT-proBNP is a biomarker widely used at present, but NT-proBNP has no specificity in identifying pulmonary hypertension and the resulting right ventricular dysfunction. Therefore, there is an urgent need to discover specific biomarkers related to acute pulmonary embolism complicated with pulmonary hypertension and the resulting right ventricular dysfunction, which can help identify the pulmonary circulation status more quickly and accurately.

[0004] The increase in pulmonary artery pressure during acute pulmonary embolism can be formed by the mechanical obstruction caused by thrombus and the constriction of the pulmonary vascular bed. The pulmonary vasoconstriction caused by multiple mechanisms largely explains why acute pulmonary embolism patients with similar thrombus burdens may present with or without concurrent pulmonary hypertension, or with different degrees of concurrent pulmonary hypertension and the resulting right ventricular dysfunction. Previous studies have suggested that multiple mechanisms and pathways may be involved in pulmonary vasoconstriction during acute pulmonary embolism, such as inflammatory response, immune response, hypoxia, platelet activation, etc. And the above possible mechanisms involve a variety of biological markers and potential intervention targets, which can help clinicians better identify patients who may develop pulmonary hypertension and the resulting right heart failure in the acute pulmonary embolism population. At the same time, treatment targeting relevant targets has important guiding significance for formulating prevention strategies for high-risk groups in the era of individualized precision medicine.

[0005] Therefore, it is necessary to develop specific biomarkers to help identify the population of acute pulmonary embolism patients complicated with pulmonary hypertension, so as to guide the formulation of risk stratification and treatment strategies, and then improve the prognosis of patients. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide the application of protein markers in identifying the model of acute pulmonary embolism complicated with pulmonary hypertension, for identifying whether acute pulmonary embolism is complicated with pulmonary hypertension.

[0007] To achieve the above object, the present invention provides the application of protein markers in identifying a model of acute pulmonary embolism complicated with pulmonary hypertension, and the protein marker combination is composed of one or more of LRG1, LDHA, and PEPD.

[0008] Furthermore, the model includes the following content: LogitP = 2.031 * LRG1 - 1.524 * PEPD - 0.719 * LDHA - 0.730, where P is the probability of complicated with pulmonary hypertension.

[0009] The present invention screens out differentially expressed proteins between groups among all quantifiable proteins through DIA untargeted proteomics, and verifies them through PRM targeted proteomics. The ROC analysis obtains protein markers that can identify acute pulmonary embolism complicated with pulmonary hypertension. Applying the above protein markers to establish a Logistics diagnostic model, the regression equation is LogitP = 2.031 * LRG1 - 1.524 * PEPD - 0.719 * LDHA - 0.730, where P is the probability of complicated with pulmonary hypertension. This equation can help identify whether acute pulmonary embolism is complicated with pulmonary hypertension.

[0010] On the one hand, the present invention screens and verifies three protein markers that can identify whether acute pulmonary embolism is complicated with pulmonary hypertension, and establishes a prediction model for acute pulmonary embolism patients complicated with pulmonary hypertension, which can help better identify patients who may be complicated with pulmonary hypertension and even right heart failure in the population of acute pulmonary embolism, and has important guiding significance for formulating individualized treatment strategies.

[0011] The beneficial effects of the present invention are as follows:

[0012] The application of the protein markers provided by the present invention in establishing a model for identifying acute pulmonary embolism complicated with pulmonary hypertension is based on the importance of pulmonary hypertension and the resulting right ventricular dysfunction in the risk stratification, treatment strategy formulation, and prognosis evaluation of acute pulmonary embolism patients. The protein markers can accurately, simply, and non-invasively identify whether acute pulmonary embolism patients are complicated with pulmonary hypertension, which is a key link in the diagnosis and treatment of acute pulmonary embolism. The present invention can help clinicians perform risk stratification, formulate treatment strategies, and evaluate the prognosis of acute pulmonary embolism. Description of the Drawings

[0013] Figure 1 It is a diagram of the results of differentially expressed proteins between two groups of acute pulmonary embolism complicated and not complicated with pulmonary hypertension screened by DIA untargeted proteomics in Example 1.

[0014] Figure 2A It is an ROC curve of LRG1 in identifying whether acute pulmonary embolism patients are complicated with pulmonary hypertension in Example 1.

[0015] Figure 2BROC curve for LDHA in Example 1 to identify whether acute pulmonary embolism patients are complicated with pulmonary hypertension.

[0016] Figure 2C ROC curve for PEPD in Example 1 to identify whether acute pulmonary embolism patients are complicated with pulmonary hypertension.

[0017] Figure 3A ROC curve graph of the test set of the multivariate logistics prediction model.

[0018] Figure 3B ROC curve graph of the validation set of the multivariate logistics prediction model. Detailed implementation manners

[0019] The embodiments of the present invention will be described in detail and comprehensively below, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0020] Example 1

[0021] Using proteomics to screen protein markers for acute pulmonary embolism complicated with pulmonary hypertension

[0022] 1.1 Sample collection

[0023] The present invention collected fasting peripheral blood venous specimens of acute pulmonary embolism patients from Fuwai Hospital, Chinese Academy of Medical Sciences and Beijing Chaoyang Hospital from July 2018 to September 2020. All enrolled patients signed informed consent forms. Among them, 5 cases of acute pulmonary embolism patients with and without pulmonary hypertension completed DIA untargeted proteomics, and 21 cases and 47 cases of acute pulmonary embolism patients with and without pulmonary hypertension completed PRM targeted proteomics respectively.

[0024] 1.2 Sample pretreatment and storage

[0025] First, collect blood samples into 5 ml EDTA anticoagulant tubes, centrifuge at 1500 g for 15 minutes at 4°C. The supernatant after centrifugation is transferred to Eppendorf centrifuge tubes, and then centrifuged at 3200 g for 15 minutes at 4°C again. The supernatant is transferred to Eppendorf tubes again, aliquoted at 0.5 ml / tube, added with cocktail protease inhibitor at a ratio of 1:100, and stored in a -80°C refrigerator.

[0026] 1.3 Screening of differential proteins by DIA untargeted proteomics

[0027] 1.3.1 Activation of commercial columns

[0028] The commercial column Pierce Top2 Abundant Protein Depletion Spin Columns (Thermo 85162) was taken out from 4°C and placed on the experimental bench to restore to room temperature. Then, the column was flicked gently or shaken mildly in a vortex to suspend the gel particles inside the column.

[0029] 1.3.2 Sample loading and incubation

[0030] Take 5 μl of serum sample, add it to the column, flick gently or shake mildly in a vortex until thoroughly mixed, and then place it on a vertical mixer and rotate and incubate at room temperature for 1 hour. During this process, the two highly abundant proteins (serum albumin, IgG) in the serum sample are bound by the corresponding antibodies inside the column, while the target sample components are not bound.

[0031] 1.3.3 Elution of target sample

[0032] Remove the plug at the bottom of the column, place the column in a new 1.5 ml EP tube, centrifuge at 1000 g at room temperature for 2 min. At this time, the eluate is the sample with the two highly abundant proteins removed.

[0033] 1.3.4 Sample before FASP

[0034] The sample eluted from the column is about 400 - 450 μl, and the solution environment is PBS.

[0035] 1.3.5 FASP treatment of sample

[0036] After the sample is reduced and alkylated, directly add it to a 10 KD (Sartorius, VNO1H02) ultrafiltration tube, centrifuge at 14000 g at room temperature for 15 min, discard the flow-through, then add 300 μl of 50 mM ammonium bicarbonate solution, centrifuge, and discard the flow-through as above. Repeat this washing process 3 times. After the last wash, replace the ultrafiltration tube sleeve.

[0037] 1.3.6 Protease digestion of sample

[0038] Add 300 μl of 50 mM ammonium bicarbonate solution to the ultrafiltration tube, then add 5 μg of trypsin, mix well, wrap the mouth of the ultrafiltration tube with a sealing film, rotate and incubate at 37°C for 4 - 6 hours, then add another 5 μg of trypsin, mix well, seal, and rotate and incubate overnight.

[0039] 1.3.7 Centrifugation to collect peptide fragments

[0040] The next morning, tear off the sealing film of the sample ultrafiltration tube, centrifuge at 14000 g at room temperature for 16 min, retain the flow-through, then add 300 μl of mass spectrometry water to the ultrafiltration tube, centrifuge as above, retain the flow-through, and combine the flow-through eluted twice (i.e., the target peptide fragments), transfer them to a new 1.5 ml EP tube.

[0041] 1.3.8 Peptide Concentration Determination

[0042] Use Nanodrop to detect the concentration of the peptide sample, and calculate the mass (μg). The blank control is mass spectrometry water.

[0043] 1.3.9 Drying and Submission for Detection

[0044] Dry in vacuo at 60 °C and submit for detection in the mass spectrometry room.

[0045] 1.3.10 Chromatographic Conditions

[0046] Reverse-phase C18 pre-column: packing with 3 μm particle size, 2 cm × 100 μm inner diameter; reverse-phase C18 analytical column: packing with 1.9 μm particle size, 20 cm × 150 μm inner diameter; the flow rate during analysis is set to 600 nL / min, and the gradient is that solvent B (0.08% formic acid, 80% acetonitrile) rises from 7% to 95% within 90 min.

[0047] 1.3.11 Mass Spectrometry Conditions

[0048] Set the electrospray voltage to 2.0 kV, and use the data-dependent tandem mass spectrometry method to analyze the peptide sample. The first-level resolution is 120,000, and the second-level resolution is 15,000. The first-level full scan is completed in the electrostatic field Orbitrap, the scanning range is 300 - 1400, and the 20 ions with the highest intensity in each scan are automatically selected to be fragmented in the HCD fragmentation cell, the fragmentation energy is 27%, and detected by Orbitrap; the first-level scan automatic gain control (AGC targets) is 3×e6 ions, the maximum ion injection time is 80 ms; the second-level scan automatic gain control (AGC targets) is 5×e4 ions, the maximum ion injection time is 40 ms; the dynamic exclusion time is set to 18 s.

[0049] 1.3.12 DIA Result Analysis

[0050] Use the R language package limma to perform a comparative analysis on the proteins determined by DIA technology. Screen for differentially expressed proteins with a threshold of P Value < 0.05. The 22 differentially expressed proteins obtained by screening are: H2BC12, LDHA, CFB, SERPINC1, SERPINA3, C5, IGKV1D-33, C1QA, LRG1, CFI, CLEC3B, SFTPB, FCGR3A, DBH, SPP1, PEPD, DSP, LBP, SDC1, IGFBP5, CFP, TPM4. The results are as Figure 1 shown.

[0051] From Figure 1 It can be seen that through DIA untargeted proteomics, compared with acute pulmonary embolism patients without concurrent pulmonary hypertension, in acute pulmonary embolism patients with concurrent pulmonary hypertension, the protein levels of H2BC12, IGFBP5, DBH, etc. are up-regulated, and the protein levels of DSP, SDC1, TPM4, etc. are down-regulated.

[0052] 1.4 PRM targeted proteomics

[0053] 1.4.1 Sample preparation

[0054] Protein extraction: Take serum samples and use High-Select TM High-abundance protein removal centrifugal column (Thermo Scientific (Rockford, USA), A36370) to remove high-abundance proteins according to the instructions. Reduction and alkylation: Add DTT to 5 mM and incubate with shaking at 55 °C for 10 min to reduce disulfide bonds. Cool the sample to room temperature, add IAA to 10 mM and react in the dark for 15 min to alkylate the reduced disulfide bonds. Transfer the reduced and alkylated sample to an ultrafiltration tube, centrifuge at 12000 g at 4 °C for 30 min, and discard the filtrate. Add 200 μL of 0.1 mmol / L TEAB solution, centrifuge at 12000 g at 4 °C for 30 min, and discard the filtrate. Repeat three times. Wash the bottom of the ultrafiltration tube twice with 400 μL of deionized water. Protease digestion: Add 100 μL of 0.1 mol / L TEAB solution to the above extract, dissolve Trypsin in Resuspension buffer to 0.5 μL / μL, incubate at room temperature for 5 min, and mix Trypsin and the sample thoroughly at a ratio of Trypsin:protein = 1:50. After simple centrifugation, incubate with shaking at 37 °C at 1000 rpm overnight. BCA quantification: Pipette BCA working solution into a 96-well plate, 180 μL per well, 7 standard points, 1 blank. Add 20 μL of sample to each well. Shake at 37 °C for 15 min and measure the absorbance at a wavelength of 480 nm. Fit the standard curve according to the standard product and calculate the polypeptide concentration of the corresponding sample. Polypeptide desalting: Add 1 mL of Buffer C to activate the C18 column, and let all the solution flow slowly into the centrifuge tube. Add 1 mL of Buffer A to balance, and let all the solution flow slowly into the centrifuge tube. Add the sample supernatant, and let all the solution flow slowly into the centrifuge tube. Collect the effluent (FT). Add 1 mL of Buffer A to wash twice, and let all the solution flow slowly into the centrifuge tube. Add 400 μL of Buffer B to elute, and pipette the eluate into a new EP tube (E1). Repeat desalting of the effluent FT once (E2), and combine the two eluates (E1 + E2). Dry under vacuum at 4 °C overnight for standby.

[0055] 1.4.2 nanoLC-MS / MS Detection

[0056] For each sample, ~1 μL of total peptides was separated by the nanoUPLC liquid phase system EASYnLC 1200 and then coupled with a mass spectrometer (QExactive HFX) equipped with a nanoelectrospray ion source for data acquisition. Chromatographic separation was performed using a 100 μL ID × 15 cm reversed-phase chromatographic column (Reprosil Pur 120 C18 AQ, 1.9 μL, Dr. Maisch). The mobile phase was an acetonitrile-water-formic acid system, where mobile phase A was 0.1% formic acid - 98% aqueous solution (2% acetonitrile), and phase B was 0.1% formic acid - 80% acetonitrile solution (20% water). After the chromatographic column was equilibrated with 100% of phase A, the sample was directly loaded onto the chromatographic column by an autosampler and then gradient separated by the chromatographic column at a flow rate of 300 nL / min for a gradient duration of 90 min. Proportion of mobile phase B: 2 - 5% for 2 min, 5 - 22% for 68 min, 22 - 45% for 16 min, 45 - 95% for 2 min, 95% for 2 min.

[0057] Mass spectrometry analysis used the parallel reaction monitoring (PRM) method, with a positive ion detection mode, and the inclusion list is shown in Table 3. The quadrupole isolation window was 0.7 m / z, the normalized collision energy (NCE) was 27%, and the secondary scan resolution was 15 k.

[0058] 1.4.3 Data Analysis

[0059] Adoption of the Spectra library generation method: The classical DDA data acquisition mode is combined with database search software for identification. The original data file is first converted into the mzML general file format using ProteoWizard (version 3.0.18299) software. The mass spectrometry spectrum data is searched and matched with the target protein fasta database sequence (uniprot-Human-9606-2020-10.fasta) using the MSFragger1 software. The main database search parameters adopt the official recommended values (see philosopher.yaml for details). The digestion specificity is set to: trypsin; the allowable polypeptide length range is: 7 - 50; the variable modifications include: 15.994915[M], 42.010565[n-term]; the fixed modification includes: 57.021464[C]; the precursor ion mass accuracy is: + / -20ppm; the fragment ion accuracy is: + / -20ppm. The MSFragger database search results are then analyzed using the Philosopher (v3.3.11)2 toolset, mainly including PeptideProphet and ProteinProphet (v5.2.1) for calculating the correct probabilities of polypeptides and proteins (validation), filter for controlling the PSM, polypeptide, and protein FDR (1%), and freequant for quantitative analysis of polypeptides (proteins).

[0060] The construction of the PRM method is completed using the Skyline software. The general process is as follows: 1) The target polypeptide sequence is imported into the Skyline software. After setting information such as polypeptide charge and heavy isotope labeling, the inclusion list is exported to the Xcalibar software to construct the PRM method for collecting actual samples. 2) The PRM raw data is imported into the Skyline software. The chromatographic peak boundaries of the target polypeptide are determined based on the spectra and RT characteristics in the Spectralibrary, and the DDA database search results are given priority when selecting the secondary spectrum information. 3) Multiple fragment ions are selected for each target polypeptide for quantification at most.

[0061] 1.4.4 Experimental results

[0062] Through the PRM method, it is verified that among the differential protein lists obtained by DIA, there are significant differences in three protein markers between the groups with and without acute pulmonary embolism complicated by pulmonary hypertension (with a threshold of P Value < 0.05). The protein markers include: LRG1, LDHA, and PEPD. Using ROC analysis, the results are as Figures 2A to 2C shown.

[0063] From Figures 2A to 2CIt can be seen that in the ROC curve for identifying acute pulmonary embolism complicated with pulmonary hypertension, the AUC of LRG1 is 0.688, the AUC of LDHA is 0.656, and the AUC of PEPD is 0.671, which can relatively accurately identify patients with acute pulmonary embolism complicated with pulmonary hypertension.

[0064] From the above results, it can be seen that the AUCs of LRG1, LDHA, and PEPD are all in the range of 0.6 < AUC < 1, which have predictive value and can be used as single factors to identify patients with acute pulmonary embolism complicated with pulmonary hypertension.

[0065] Example 2

[0066] Subsequently, 70% was randomly selected as the training set in the PRM cohort to establish a multi-factor logistics prediction model using the above three protein markers. The established regression equation is LogitP = 2.031 * LRG1 - 1.524 * PEPD - 0.719 * LDHA - 0.730. Then, the remaining 30% was used as the test set to verify the probability of the model predicting acute pulmonary embolism patients complicated with pulmonary hypertension. The results of the training set are as Figure 3A , and the results of the test set are as Figure 3B shown.

[0067] From Figure 3A and Figure 3B it can be seen that the AUC of the logistics model constructed by combining the three protein markers of LRG1, LDHA, and PEPD for identifying acute pulmonary embolism patients complicated with pulmonary hypertension is 0.811 in the training set and 0.810 in the test set, indicating that the accuracy of this identification of acute pulmonary embolism complicated with pulmonary hypertension is closer to the extreme value of 1 for perfect AUC prediction, and the prediction accuracy is improved compared with that of a single protein marker. The three protein markers can be used to identify the population with acute pulmonary embolism complicated with pulmonary hypertension, and the occurrence probability of acute pulmonary embolism complicated with pulmonary hypertension can be obtained according to the results of protein determination.

[0068] From the above examples, it can be seen that the protein markers provided by the present invention, as substances in establishing a model for identifying acute pulmonary embolism complicated with pulmonary hypertension, based on the plasma proteomic data of acute pulmonary embolism patients, through the methods of DIA non-targeted proteomics and PRM targeted proteomics, the protein markers related to acute pulmonary embolism complicated with pulmonary hypertension are obtained, which can help clinicians conduct risk stratification, formulate treatment strategies, and evaluate the prognosis of acute pulmonary embolism.

[0069] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

Claims

1. Use of a protein marker in the preparation of a product for identifying an acute pulmonary embolism complicated with pulmonary hypertension model, characterized in that, The protein biomarker consists of LRG1, LDHA, and PEPD; Among them, the model includes the following: LogitP = 2.031 * LRG1 - 1.524 * PEPD - 0.719 * LDHA - 0.730, where P is the probability of concurrent pulmonary arterial hypertension.

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